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Internet Access: Wireless Internet is available for delegates carrying a laptop and can be accessed in the meetingroom. Laptops must be wi-fi enabled. Username: transplant Password: meeting

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C2: Inside Front Cover

Ad Genentech/Roche

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TABLE OF CONTENTS

Committees 2

Message from the President of TTS 3

Message from the Conference Chairs 4

Conference Information 5

Floor Plans 6

Local Information 7

Evening Event 8

Conference Learning Objectives 9

Instructions to Oral and Poster Presenters 10

Invited Speakers & Chairs 11

Wednesday • Feb. 24 • Pre-Conference Workshop 13

Thursday/Friday • Program Quick-View 14

Thursday • Feb. 25 • Detailed Program 16

Friday • Feb. 26 • Detailed Program 36

Posters 51

Presenter Index 71

Sponsor Acknowledgements 72

The Transplantation SocietyInternational Headquarters

1255 University Street, Suite 325Montreal, QC, Canada  H3B 3B4

Phone: 514-874-1717 Fax:  514-874-1716 Email: [email protected]: www.tts.org

Printed in Canada, February 2010

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The Transplantation Society • www.tts.org

Transplantomics and Biomarkers in Organ Transplantation

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LOCAL ORGANIZING COMMITTEE

Minnie Sarwal, Conference ChairStanford, CA, USA

Mark M. Davis, Conference Co-ChairStanford, CA, USA

Atul Butte, Conference Co-ChairStanford, CA, USA

THE TRANSPLANTATION SOCIETYREPRESENTATIVES

Jeremy Chapman, TTS PresidentWestmead, Australia

Kathryn Wood, TTS Past President 2006-2008Oxford, United Kingdom

SCIENTIFIC PROGRAM COMMITTEE

Minnie Sarwal, Conference ChairStanford, CA, USA

Tom Blydt-HansenWinnipeg, MB, Canada

Atul Butte, Conference Co-Chair Stanford, CA, USA

Anthony JevnikarLondon, ON, Canada

Allan D. KirkAtlanta, GA, USA

Roslyn B. MannonBirmingham, AL, USA

Elaine ReedLos Angeles, CA, USA

David RushWinnipeg, MB, Canada

Daniel SalomonSan Diego, CA, USA

Manikkam SuthanthiranNew York, NY, USA

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February 24-26, 2010 • 1st International Conference

COMMITTEES

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MESSAGE FROM THE PRESIDENT OF TTS

Transplantation has evolved over the last 60 years through the combined efforts ofclinicians and scientists. The problems that our early predecessors faced included onlyvery limited understanding of the immunological barriers, however this was combatedwith clinical experimentation and by slowly accrued experience. Science providedsome answers as we came into the 1960’s during which the cross match test andimmunosuppressive drugs yielded some initial triumphs over the biology oftransplantation. Slowly we have used our scientific knowledge to bring forward bothan understanding of the clinical problems that face us and some solutions. The toolsof our trade have been crude in comparison to the sophistication of the immune

system and the responses to injury - we have histology, some biochemical measures, some techniques fordetection of antibody specificity, imaging techniques mostly based on the scientific developments of the1940’s and slow application of information technology. If we were to be honest in our appraisal of the currentstate of affairs - clinical transplantation remains mired in the mud of our application of old technology.

This conference is about bringing together those with expertise in the new technologies of genomics,proteomics and metabalomics and those who carry expertise in clinical application of technologies intransplantation. Forgive us the title ‘Transplantomics‘ as it is an attempt to bring these concepts into a singleword.

The Transplantation Society stands for development in the science and clinical practice of transplantation. It isour expectation that smaller concentrated workshops and meetings such as this will help to stimulate thetranslation of these new technologies into clinical practice over the years ahead. We thank our generoussponsors Roche/Genentech, Bristol-Myers Squibb, Novartis, Pfizer, Astellas and Genzyme who have acceptedthe challenge of assisting TTS with funding this first Transplantomics conference and hope that you will enjoythis opportunity to meet with your colleagues here in San Francisco.

The 2nd International Conference on Transplantomics will be held next year and we would welcome proposalsfor the venue.

Jeremy ChapmanPresident, The Transplantation Society

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MESSAGE FROM THE CONFERENCE CHAIRS

Dear colleagues,

Welcome to the 1st International Conference on Transplantomics andBiomarkers in Organ Transplantation and welcome to the beautiful cityof San Francisco, California.

As host of the meeting, The Transplantation Society (TTS) has calledfor this first-ever “Transplantomics” meeting in order to establish ameeting platform that brings together disciplines in transplantationresearch in genomics, proteomics, informatics and clinicaltransplantation with the goal to create more dialogue andcollaboration across disciplines and researchers.

The agenda has been drafted with the objectives to maximizeoutstanding presentations as a basis for discussion, time for questionsand answers, discussions and networking. The poster reception will bethe perfect opportunity to explore specific subjects with yourcolleagues.

Enjoy this conference!

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Minnie SarwalConference Chair

Mark M. DavisConference Co-Chair

Atul ButteConference Co-Chair

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Certificate of AttendanceAn attendance certificate can be requested via e-mail to [email protected]. Thisconference is not CME-accredited.

Conference EvaluationA conference evaluation form will be distributedduring the morning coffee break on Friday. Pleasecomplete and return to the registration desk.

Emergency / First AidFor any emergency or first aid services inside thehotel, please dial “0” from any house phone.

Exhibit DisplayOur Platinum sponsor Genentech / Roche will havea table-top display in the Cyril Magnin Foyer onFebruary 25 and 26 from 10:00-18:00.

InformationThe Conference Service Desk is located in theregistration area and is in service for the entireduration of the Conference. Should you require anyassistance outside of service desk hours, please call1-514-991-3851.

Internet Access

Wireless Internet is available for delegates carryinga laptop and can be accessed in the meeting room.Laptops must be wi-fi enabled.

Username: transplant Password: meeting

Lost and FoundAny lost and found items will be held at theConference Service Desk for the duration of theevent. For any unclaimed items after theconference, please contact The TransplantationSociety.

Luggage We recommend that you leave your luggage withthe Bellman at your hotel. The TransplantationSociety does not take any responsibility forsuitcases that are left in the meeting area, includingthe registration desk.

Poster DisplaysPosters are on display in the Cyril Magnin Foyer onFebruary 25 and February 26. Delegates can visitposters at their convenience. Poster presenters areencouraged to be at their posters during breaktimes. An official poster reception will take place onFebruary 25 from 17:00-18:00.

Public NoticeThe Parc 55 Hotel is a smoke-free environment.Smoking is permitted only outside the building.

Registration Hours

Wednesday, February 24 13:00-18:00(outside Divisadero)

Thursday, February 25 07:00-18:00Friday, February 26 07:00-17:00(outside Cyril Magnin)

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CONFERENCE INFORMATION

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FLOOR PLANS

Level Two - Divisadero

Level Four – Cyril Magnin I & II

6 February 24-26, 2010 • 1st International Conference

D ASHBURY BOARDROOM AND

H SUTRO CREATES A PRIVATE

E

Haight

Sutro

Divisadero

Ashbury

cityhouse

Guest Reception

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About San FranciscoThe City and County of San Francisco is the fourthmost populous city in California and the 12th mostpopulous city in the United States, with a 2008estimated population of 808,976. It is the secondmost densely populated major city in the U.S. andis the financial, cultural, and transportation centerof the larger San Francisco Bay Area, a region ofmore than seven million people. The city is locatedat the northern end of the San Francisco Peninsula,with the Pacific Ocean to the west and SanFrancisco Bay to the north and east.

San Francisco inspires images recognized the worldover: the Golden Gate Bridge, Fisherman’s Wharf,Chinatown, cable cars, that beautiful city by theBay. San Francisco heightens an appreciation for‘the good life’.

Known for its fine restaurants and shops, SanFrancisco has something for every appetite andbudget. Home to the highest concentration of artsorganizations in the country, audiences arecaptivated by everything from street minstrels andsidewalk art shows to the highly acclaimed SanFrancisco Opera and Symphony and a multitude offascinating museums.

Stroll through Golden Gate Park past theArboretum and Botanical Gardens, the Children’sPlayground (complete with carousel) and theNational AIDS Memorial Grove. Take the ferry toAlcatraz or Sausalito, head north to Muir Woodsand see the magnificent redwoods, or explorewine country in Napa and Sonoma just an hour’sdrive from the city. Two days or two decades herereveal only that there is more to learn, more to see,more to do.

Getting Around San Francisco

Public Transportation:

Muni rail lines serve only San Francisco. Bus,historic streetcar, and Metro trips for adults cost$2.00, including a free transfer. Fares can be paidwith any US coins. Exact change is required.

Cable car trips cost $5.00 per single ride.

There are single-ride ticket booklets for multiplerides (booklets of 10 single tickets) and passportswhich offer unlimited travel on the transit system.Ride streetcars, buses and cable cars as many timesa day as you wish with your Passport. Available for1 day, 3 consecutive days or 7 consecutive days. 1-day Cable Car passes, available from Cable Carconductors, are good only on Cable Cars.

Taxis:

Taxis are easy to spot in downtown San Francisco,particularly during rush hour. Taxis can be easilyhailed - just look for the lighted sign on the top thatindicates if the taxi is available for hire. Major hotelsaround Union Square and Fisherman’s Wharf usuallyhave taxis in line for hire. PIER 39 in Fisherman’sWharf is also a good place to hail a cab. Extra travelcharges may be added for luggage or late-nighttraveling, so ask the driver before leaving. TaxiFares: First 1/5th mile or flag $3.10; each additional1/5th mile or fraction thereafter,45¢; each minute of waiting, or traffic time delay, 45¢; airportsurcharge $2.00.

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LOCAL INFORMATION

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Forbes Island Fantasy Fine Dining aboardthe World’s Only Floating IslandThursday, February 2519:00 to 22:00 (bus departure from hotel at 18:45, return at 22:30)

Dress Code: Casual • Tickets available for $85 per person (limited capacity)Forbes Island provides a fantasy dining experience, beneath the sea and on the white sand patios withincredible views of San Francisco Bay, Downtown, Alcatraz, Sea Lions, Coit Tower & the Golden Gate Bridge.You surely will want to be at this dinner!

We recommend reading about the 7 Wonders of Forbes Island / www.forbesisland.com.

1) The English Tudor paneling on the interior walls of the island is decorated with tight fitted molding which is secured with

no nails or glue. The molding, if pieced together, would span more than 10,000 feet or nearly 2 miles.

2) The antique ship's wheel in the wheelhouse was

from the Brigatine, Regina Maris, built in 1906

and she rounded Cape Horn 17 times.

3) The 40 foot Lighthouse is the only privately built

Lighthouse in the United States and is equipped

with an authentic Fresnel Lens on loan from the

US Lighthouse Society. The Fresnel Lens was built

in France in 1820 and was first lit using whale oil.

4) The island is powered by an actual Sea Mule

motor, which is the world's largest outboard

motor and was used extensively in World War II

by the US Navy to propel ocean going barges. It

can rotate 360 degrees and is a 250 horse power

motor.

5) Forbes Island displaces 700 tons of water, the

structure was made with 280 tons of concrete, 120 tons of rocks surround the perimeter, 90 tons of sand top the shores,

and 40 tons of topsoil are the earth for the plants and palms.

6) During the spring the Washatona Palm Trees are the nesting grounds for hundreds of Starling blackbirds and the rocks

around the perimeter of the island are the nesting grounds of several seagulls.

7) Forbes Island launched on December 23, 1980. On launch day the island had 3 staterooms all with private baths, 56

portholes throughout, and the waterfall cascaded into a hot tub. Shortly thereafter it was featured on "Lifestyles of the

Rich and Famous" and "That's Incredible".

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EVENING EVENT

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The overall objective of the meeting is to present the latest progress on using high throughput andinformatics approaches to improve translational biomedical research in organ transplantation.

After attending this conference, delegates will be able:

n To review and gain an understanding of key lessons learnt by translational bioinformatics researchers inorgan transplantation and to better set up cross-talk between groups;

n To identify the current challenges of translational research omics (transplantomics) in organ transplantationand to define the future directions;

n To articulate challenges and opportunities in transplantomics;

n To learn a framework for developing, deploying and assessing the success and applications of translationalbioinformatics initiatives in organ transplantation;

n To understand the techniques for implementing specific clinical decision support interventions;

n To appreciate how translational bioinformatics may be deployed to enhance clinical and translationalresearch;

n To identify areas of interaction among computational biology, genomics research, electronic healthrecords, health information exchanges, HLA disparity testing and public health.

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CONFERENCE LEARNING OBJECTIVES

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THERE IS NO SPEAKER READY ROOM. Speakers must arrive with their final PowerPoint presentation onsite.All presentation files will be uploaded directly onto the meeting room computer (PC) and will be erased at theend of the day. Only authorized presentations will be recorded and posted online.

If you speak in the morning block, please bring your presentation to the AV technician in the meeting roomat least 30 minutes before the session starts or during the coffee break.

If you speak in the afternoon block, please bring your presentation to the AV technician during the lunchbreak and at least 30 minutes before session starts.

As the schedule is very compact, we want to make sure that the presentations for each block are pre-loadedand tested. While we recommend using the session computer, we also allow the use of a speaker’s owncomputer.

SPEAKERS MUST ADVISE THE TECHNICIAN BEFORE THE SESSION IF USING THEIR OWN COMPUTER.

INSTRUCTIONS TO POSTER PRESENTERS

Participants will view posters during lunches and breaks, therefore authors are encouraged to be present attheir posters during those times.

Authors are responsible for the setting up and the removal of their posters according to the followingschedule:

Mounting time: Thursday, February 25, 2010 07:00 to 08:00

Removal: Friday, February 26, 2010 by 17:00

Room: Foyer Cyril Magnin

Posters not removed by the specified time on the last day of their presentation will be removed anddiscarded by Meeting staff. TTS cannot accept liability for lost or damaged posters. TTS will not mail postersto authors after the meeting.

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INSTRUCTIONS TO ORAL PRESENTERS

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Dany AnglicheauAssociate Professor, Kidney Transplant Unit, NeckerHospital, Paris, France

Atul ButteAssistant Professor, Medicine, Stanford MedicalInformatics, Stanford University, Stanford, CA, USA

Jeremy ChapmanDirector, Acute Interventional Medicine and RenalServices, Westmead Hospital, SWAHS, Westmead,Australia

Christopher ContagCo-Director, Molecular Imaging Program at Stanford,Department of Pediatrics and of Microbiology andImmunology, Stanford University, Stanford, CA, USA

Mark M. Davis Professor, Microbiology & Immunology, StanfordUniversity, Stanford, CA, USA

Ronald W. DavisProfessor of Biochemistry and Professor of Genetics,Member of the Stanford Comprehensive Cancer Center,Stanford University, Stanford, CA, USA

Stuart FlechnerDirector, Clinical Research, Section of RenalTransplantation, Cleveland Clinic; Professor of Surgery,Cleveland Clinic Lerner College of Medicine of CaseWestern Reserve University, Cleveland, OH, USA

Federico GoodsaidAssociate Director for Operations in Genomics; Office ofClinical Pharmacology; Office of Translational Science;Center for Drug Evaluation and Research; U.S. Food andDrug Administration; Silver Spring, MD, USA

Philip F. HalloranDirector, Alberta Transplant Applied Genomics Centre;Distinguished University Professor, University of Alberta;Editor-in-Chief, American Journal of Transplantation,Edmonton, AB, Canada

Peter S. HeegerDirector, Clinical Research Program, TransplantationInstitute, Mount Sinai School of Medicine, New York, NY, USA

Ajay IsraniAssistant Professor of Medicine, Adjunct Professor ofEpidemiology & Community Health, Hennepin CountyMedical Center, University of Minnesota, Minneapolis,MN, USA

Kathleen Kelly Associate Professor and Technical Director, Department ofPathology & Laboratory Medicine, David Geffen School ofMedicine, UCLA, Los Angeles, CA, USA

Allan D. Kirk Professor of Surgery and Pediatrics, Emory University andScientific Director of the Emory Transplant Center, Atlanta, GA, USA

Graham LordProfessor of Medicine, Nephrology, Transplantation andInternal Medicine; Director of Translational ResearchDevelopment and Deputy Director of NIHRComprehensive Biomedical Research Centre, Guy’s andSt. Thomas’ Hospital and King’s College London, London, UK

Roslyn B. MannonDirector of Research, Alabama Transplant Center;Professor, Department of Medicine, Division ofNephrology; Department of Surgery, Division ofTransplantation, University of Alabama at Birmingham,Birmingham, AL, USA

Francesco M. MarincolaChief Infectious Disease and Immunogenetics Section(IDIS), Department of Transfusion Medicine, ClinicalCenter; Associate Director, Trans-NIH Center for HumanImmunology, National Institutes of Health; Director,CC/CHI FOCIS Center of Excellence, Bethesda, MD, USA

Steven G.E. MarshDeputy Director of Research, Anthony Nolan ResearchInstitute and Professor of Immunogenetics, UCL CancerInstitute, Royal Free Campus, London, UK

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INVITED SPEAKERS & CHAIRS

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Valeria MasAssociate Professor, Departments of Surgery andPathology; Director, Molecular Transplant ResearchLaboratory, Division of Transplant, VirginiaCommonwealth University, Richmond, VA, USA

Bruce McManusProfessor, Department of Pathology and LaboratoryMedicine, University of British Columbia, Vancouver, BC, Canada

Herwig-Ulf Meier-KriescheUniversity of Florida, Gainesville, FL, USA

Thalachallour MohanakumarJacqueline G. & Wm. E. Maritz Professor, Surgery,Pathology and Immunology; Director, Histocompatibility& Immunogenetics; Director, Islet Isolation Core,Washington University, St. Louis, MO, USA

Thomas Mueller, Division of Nephrology andImmunology, University of Alberta, Edmonton, AB, Canada

Maarten NaesensDepartment of Nephrology and Renal Transplantation,University Hospitals Leuven, Leuven, Belgium;Department of Pediatrics, Stanford University School ofMedicine, Stanford, CA, USA

Philip O’ConnellDirector, Transplantation and CTRR, WestmeadMillennium Institute for Medical Research, Westmead,Australia

Richard N. Pierson IIIProfessor of Surgery, University of Maryland School ofMedicine, Baltimore, MD, USA

Caius G. RaduAssistant Professor, Department of Molecular and MedicalPharmacology, UCLA Crump Institute, Los Angeles, CA, USA

Elaine ReedProfessor and Director of Immunogenetics,Transplant/Immunogenetics Testing, David Geffen Schoolof Medicine at UCLA, Los Angeles, CA, USA

Michael ReichBroad Institute of MIT and Harvard, Boston, MA, USA

David RushProfessor and Head, Section of Nephrology; Director,Transplant Manitoba Adult Kidney Program, HealthSciences Centre, Winnipeg, MB, Canada

Alberto Sanchez-FueyoHospital Clinic Barcelona, University of Barcelona,Barcelona, Spain

Minnie SarwalProfessor of Pediatrics and Immunology, StanfordUniversity, Stanford, CA, USA

Richard SmithBiological Sciences Division, Pacific Northwest NationalLaboratory, Richland, VA, USA

Manikkam SuthanthiranStanton Griffis Distinguished Professor of Medicine, Chief,Nephrology and Transplantation Medicine, New YorkPresbyterian Hospital-Cornell, New York, NY, USA

Robert Tibshirani Associate Chairman and Professor of Health Research andPolicy, and Statistics, Stanford University, Stanford, CA,USA

David WishartProfessor, Departments of Biological Sciences andComputing Science, University of Alberta; SeniorResearch Officer and Co-director, Nanobiology Program,NRC’s National Institute for Nanotechnology (NINT),Edmonton, AB, Canada

Kathryn WoodAssociate of the Oxford Stem Cell Institute, Professor ofImmunology, University of Oxford, Oxford, UK

12 February 24-26, 2010 • 1st International Conference

INVITED SPEAKERS & CHAIRS

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CURRENT AND NEW TECHNOLOGIES IN GENOMICS ANDPROTEOMICSSponsored by InvitrogenChair: Holden Maecker, Director, Human Immune Monitoring Center, Stanford University, Stanford, CA, USA

1. CURRENT TECHNOLOGIES

15:00 FLOW CYTOMETRYSmita Ghanekar, BD Biosciences

15:30 LUMINExHolden Maecker, Stanford University

16:00 GENE ARRAYSSharoni Jacobs, Agilent

2. NEW TECHNOLOGIES

17:00 NANOIMMUNOASSAYSAlice Fan, Stanford University

17:20 MICROFLUIDIC SINGLE CELL ASSAYSCaroline Dando, Fluidigm Corporation

17:40 CyToFSean Bendall, Stanford University

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PRE-CONFERENCE WORKSHOP – WEDNESDAY • FEB 24DIVISADERO ROOM

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NOVEL APPLICATIONS FOR GENOMIC TECHNOLOGIES IN ORGAN TRANSPLANT INJURYSession is sponsored through an unrestricted educational grant by Pfizer.Co-chairs: Jeremy Chapman and Kathryn Wood

08:00 Opening Message • Jeremy Chapman, Australia

08:10 Advances in Genome Analysis Technologies • Ronald W. Davis, USA

08:40 Reclassifying Graft Injury by Genomics • Philip F. Halloran, Canada

09:00 Deconvoluting the Peripheral Blood Transcriptome in Graft Rejection • Minnie Sarwal, USA

09:20 Noninvasive Diagnosis of Renal Allograft Status • Manikkam Suthanthiran, USA

09:40 Exploring Genomic Medicine Using Translational Bioinformatics • Atul Butte, USA

10:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

NOVEL APPLICATIONS FOR GENOMIC TECHNOLOGIES IN ORGAN TRANSPLANT INJURY (cont.)

Co-chairs: Philip F. Halloran and Manikkam Suthanthiran

10:30 Immune-Monitoring in Health and Infection • Mark M. Davis, USA

11:00 The Evolution of Non-Immune Histological Injury • Maarten Naesens, USA

11:20 The Genomics of Fibrosis Progression • Valeria Mas, USA

11:40 RNA Silencing in Gene Regulation • Christopher Contag, USA

12:00 LUNCH, POSTERS & EXHIBITS (FOYER)

PREDICTING GRAFT RISK BY TRANSPLANTOMICSSession is sponsored through an unrestricted educational grant by Bristol-Myers SquibbCo-chairs: Philip O'Connell and Thomas Mueller

13:30 The Impact of Genome-wide Variation in Renal Transplant Donors and Recipients on Graft Survival • Graham Lord, UK

14:00 Challenges in Association Studies of Single Nucleotide Polymorphism Associated and Renal Transplant Outcomes • Ajay Israni, USA

14:20 MicroRNA and RNA Profiles with Graft Rejection • Dany Anglicheau, France

14:40 Predictors of Transplant Vasculopathy and Glomerulopathy • Roslyn B. Mannon, USA

15:00 A Signature for Operational Liver Transplant Tolerance • Alberto Sanchez-Fueyo, Spain

15:20 Can Immune Accommodation Be Predicted Using "-omics" Tools? • Bruce McManus, Canada

15:40 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

16:00 MINI-ORAL PRESENTATIONS (See detailed program on page 34)Co-chairs: Allan D. Kirk and Roslyn B. Mannon

17:00 POSTER RECEPTION

19:00 DINNER AT FORBES ISLAND (BUS DEPARTS FROM HOTEL AT 18:45)

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THURSDAY • FEB 25 PROGRAM QUICK-VIEWCYRIL MAGNIN I & II

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PERSONALIZING MEDICINE THROUGH OMICSCo-chairs: Herwig-Ulf Meier-Kriesche and Richard N. Pierson III

08:30 Conducting Transplant Trials for Biomarker Discovery • Allan D. Kirk, USA

09:00 Tools for Integrative Genomics • Michael Reich, USA

09:30 Path from Exploratory Biomarkers for Qualified Biomarkers in the Clinic • Federico Goodsaid, USA

10:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

THE ANTIBIOME AND TRANSPLANTATIONCo-chairs: Atul Butte and Stuart Flechner

10:30 Common Signatures of Rejection • Francesco M. Marincola, USA

11:00 Cross Talk between AlloImmunity and AutoImmunity in Organ Transplantation • Thalachallour Mohanakumar, USA

11:20 Phosphoproteomics and the Endothelium • Elaine Reed, USA

11:40 Antibody Repertoires to Non-HLA Antigens in Kidney Transplant Recipients • Peter Heeger, USA

12:00 LUNCH, POSTERS & EXHIBITS (FOYER)

PROTEINS AND METABOLITES IN TRANSPLANTATIONChair: Elaine Reed

13:30 Population Proteomics and Protein Biomarker Discovery • Richard Smith, USA

14:00 Metabolomics in Monitoring Organ Transplant • David Wishart, USA

14:20 Metabolomics in Renal Transplantation • David Rush, Canada

14:40 HLA Diversity in Transplantation • Steven G.E. Marsh, UK

15:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

NOVEL APPLICATIONS OF OMICSSession is sponsored through an unrestricted educational grant by Novartis.Chair: Minnie Sarwal

15:30 A Method to Systematically Identify Cell-Type-Specific Differential Gene Expression from ComplexTissues • Robert Tibshirani, USA

16:00 Molecular Imaging in Transplantation • Caius Radu, USA

16:30 Use of Nanoparticles for Augmenting Mucosal Immunity • Kathleen Kelly, USA

17:00 CONFERENCE WRAP-UPChair: Jeremy Chapman

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PROGRAM QUICK-VIEW FRIDAY • FEB 26CYRIL MAGNIN I&II

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08:00-12:00 NOVEL APPLICATIONS FOR GENOMIC TECHNOLOGIES INORGAN TRANSPLANT INJURY Session is sponsored through an unrestricted educational grant by Pfizer.

Co-chairs: Jeremy Chapman, Westmead, AustraliaKathryn Wood, Oxford, UK

08:00 OPENING MESSAGEJeremy Chapman, President, The Transplantation Society

08:10 ADVANCES IN GENOME ANALYSIS TECHNOLOGIESRonald W. Davis, Professor of Biochemistry and Professor of Genetics, Member of the StanfordComprehensive Cancer Center, Stanford University, Stanford, CA, USA

New biological and engineering technology are advancing very fast. They will have a major impacton diagnostic medicine.

Learning Objectives:

1. Biochemical/Genetic assays can be multiplexed where the cost of millions of assays is the same asone current assay.

2. Direct DNA sequencing of predetermined Targeted Regions (exons and control regions) usingnew DNA sequencing Instruments currently under development will soon become cheaper andmuch faster.

3. New engineering/biology interfaces will allow many new point of use real time assays to bedeveloped at low cost.

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THURSDAY • FEB 25 DETAILED PROGRAM

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08:40 RECLASSIFYING GRAFT INJURY BY GENOMICSPhilip F. Halloran, Director, Alberta Transplant Applied Genomics Centre; Distinguished UniversityProfessor, University of Alberta; Editor-in-Chief, American Journal of Transplantation; Edmonton, AB,Canada

Learning Objectives:

1. To understand how the molecular features of a biopsy add to the other features such as anti HLA,clinical state, biopsy histopathology, in predicting diagnosis and outcomes.

2. To examine the general implications of these findings for understanding disease mechanisms.3. To discuss the platforms by which this new knowledge can be made available to clinicians.

A new global view of the molecular changes in kidney transplant biopsies is emerging from datadriven approaches. This approach uses iterative loops to define the relationship of molecularfeatures to the other phenotypes: clinical (function, proteinuria), HLA antibody, biopsy histology, andoutcomes in approximately 650 kidneys with microarray results. Analysis incorporates annotation inmouse models, class comparison and classifier approaches, principal component analysis. Thetroubled kidneys display striking stereotyping of changes reflecting key events: T cell andmacrophage infiltration, IFNG effects, active injury response and dedifferentiation, and timedependent cumulative burden of injury changes. The Other diseases can then be defined by relativeshifts in the molecular features of this stereotyped disturbance. Specificity for T cell mediatedrejection is captured by selective changes in T cell and macrophage genes and alternativemacrophage activation, whereas specific for antibody-mediated rejection is derived from endothelialand NK cell transcripts. The injury response is the best correlate of both functional disturbance andprobability of graft loss. Time dependent changes in injured kidneys include B cell, plasma cell, andmast cell transcripts, but these have little impact in multivariate analysis when time is factored in,since late biopsies have an intrinsic high risk due to the diseases operating. Transcripts of potentialdiagnostic utility for ABMR include those associated with DSA in biopsies for cause.

The results indicate that:

1. TCMR is an intense inflammatory process with an excellent prognosis when ABMR is absent.2. ABMR is a disease of endothelium and NK cells that is often C4d negative and not diagnosed.3. The strong reflection of progression is the ongoing injury response, driven by disease processes

that are unresponsive to therapy. To progress, one must have a potentially progressive disease,but the true predictor of progression is the injury response.

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DETAILED PROGRAM THURSDAY • FEB 25

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09:00 DECONVOLUTING THE PERIPHERAL BLOOD TRANSCRIPTOME IN GRAFT REJECTIONMinnie Sarwal, Professor of Pediatrics and Immunology, Stanford University, Stanford, CA, USA

Learning Objectives:

1. To discuss why the transplant field needs non-invasive means to predict for alloimmune injury tocustomize immunosuppression.

2. Microarrays as a means to discover new biomarkers for acute rejection.3. The process of biomarker validation and cross-validation to develop a sensitive and specific

predictor for graft rejection.

Early detection of acute renal allograft rejection (AR) remains a major clinical concern and unmetneed in organ transplantation. Current blood and biofluid non-invasive screening and monitoringmethods cannot detect early and subclinical graft injury. The clinical current practice only allows forthe screening of established tissue rejection by the detection of inflammatory infiltrates on kidneybiopsy samples, despite the fact that this methodology is limited by sampling variability, proceduralmorbidity and cost. The optimal monitoring approach in organ transplantation would be to non-invasively evaluate the risk for graft rejection before the onset of renal dysfunction such thatimmunosuppression could be proactively titrated to limit graft injury, and immunosuppressiondelivery could be customized to the patients’ immunosuppression threshold and thus limit patientmorbidity from infectious and malignant complications.

Transcriptional profiling studies on biopsy specimens have confirmed that significant, coordinatedexpression changes occur in many genes with established AR. However, when these studies areapplied to peripheral blood, the expression of the rejection response is substantially weaker than thecorresponding response in the organ. The gene signature for AR is also influenced by biological andexperimental variance, resulting in low signal to noise ratio. This talk discusses the issues inbiomarker discovery in blood relating to AR and the results of a recent study that has identified ahighly specific and sensitive gene-based biomarker panel in blood that can predict the onset of AR,well before any injury can be detected by organ dysfunction or graft biopsy. This approach providesa skeleton for further studies for biomarker discovery of disease phenotypes in organ transplantation.

09:20 NONINVASIVE DIAGNOSIS OF RENAL ALLOGRAFT STATUSManikkam Suthanthiran, Stanton Griffis Distinguished Professor of Medicine; Chief, Nephrology andTransplantation Medicine; New York Presbyterian Hospital-Cornell, New York, NY, USA

Development of predictive, diagnostic and prognostic biomarkers of allograft status and outcome isimportant and challenging, and may be rewarded with individualized therapy of the organ graftrecipient.

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Learning Objectives:1. To improve understanding of allograft rejection.2. To improve understanding of molecular markers of allograft rejection.3. To improve understanding of biomarkers of allograft status.

In order to noninvasively characterize renal allograft status and outcome we performed urinary cellmRNA profiling studies and report that: (a) Urinary cell levels of mRNA for perforin and granzyme Bare significantly higher in renal allograft recipients with a biopsy confirmed episode of acute rejectionthan in the patients without an episode of acute rejection (Li et al. NEJM 2001); (b) CD103 mRNAlevels are higher in urinary cells from renal allograft recipients with a biopsy confirmed episode ofacute rejection than in the patients without acute rejection (Ding et al. Transplantation 2003); (c) BothIP-10 and CxCR3 mRNA levels are highly associated with acute rejection (Tatapudi et al. KidneyInternational 2004); (d) Whereas mRNA for FOxP3, CD25, CD3ε-chain and perforin are all higherduring an episode of acute rejection than in the group with CAN or normal biopsy group, levels ofmRNA for FOxP3 alone: (1) inversely correlate with serum creatinine levels measured at the time ofbiopsy in the acute rejection group; (2) predict the reversal of acute rejection, and (3) identifysubjects at risk for graft failure within six months after the incident episode of acute rejection(Muthukumar et al. NEJM 2005).

We subscribe to the definition proposed by the NIH Biomarker Definition Working Group: “Acharacteristic that is objectively measured and evaluated as an indicator of normal biologicalprocesses, pathogenic responses, or pharmacological responses to a therapeutic intervention”. Inthis light, mRNA profiles, measured at the time of allograft biopsy and predicting acute rejectionwith a high specificity and sensitivity serve as a diagnostic biomarker; mRNA levels, measured duringan episode of acute rejection and predicting responsiveness to anti-rejection therapy serve as aprognostic biomarker. The ongoing NIH sponsored Cooperative Clinical Trials in Transplantationshould validate or refute the hypothesis that urinary cell mRNA profiles function as predictivebiomarkers (mRNA levels in sequential samples will predict the subsequent development of acuterejection or maintenance of stable graft function) and noninvasive diagnostic biomarkers (mRNAlevels measured at the time of diagnostic allograft biopsies will predict allograft histopathology) ofacute rejection of renal allografts. These trials are also designed to test the hypothesis thatsequential urinary cell mRNA profiles predict renal allograft status (stable graft function vs. acuterejection) and function. Should future studies demonstrate that the measured biomarker iscausatively involved in the biologic process studied (e.g., acute rejection), the biomarker can bedesignated as a mechanistic biomarker, and help accomplish the objective of developing mechanismbased therapy.

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09:40 ExPLORING GENOMIC MEDICINE USING TRANSLATIONAL BIOINFORMATICSAtul Butte, Assistant Professor, Medicine, Stanford Medical Informatics, Stanford University,Stanford, CA, USA

Learning Objectives:

1. How publicly-available molecular measurements can be used to probe disease mechanisms.2. How RNA is the new proteomics.3. How bioinformatics has moved from a service-provider role to a science role.

With the end of the United States NIH budget doubling and completion of the Human GenomeProject, there is a need to translate genome-era discoveries into clinical utility.  The difficulties inmaking bench-to-bedside translations have been described: comprehensive molecular studies onpatients are expensive, and hospitals are not phenotypers.  The nascent field of translationalbioinformatics may help.   I will show how we build and apply tools that convert the billions of pointsof molecular, clinical, and epidemiological data measured by biomedical investigators and cliniciansover the past decade into insights into diagnostic and therapeutic potential.  I will highlight howusing publicly-available molecular data enables the discovery of new gene variants and biomarkersfor diseases like transplantation rejection and diabetes, suggests novel roles for drugs in thetreatment of disease, and for the first time allows us to probe the inner commonality across disease. 

10:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

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10:30-12:00 NOVEL APPLICATIONS FOR GENOMIC TECHNOLOGIES INORGAN TRANSPLANT INJURY (continued)Co-chairs: Philip F. Halloran, Edmonton, AB, Canada

Manikkam Suthanthiran, New York, NY, USA

10:30 IMMUNE-MONITORING IN HEALTH AND INFECTIONMark Davis, Professor, Microbiology & Immunology, Stanford University, Stanford, CA, USA

Learning Objectives:

1. Why has the translation of basic immunology into the clinic been so slow?2. What are some possible solutions to this problem?3. What might this mean with respect to transplantation?

There has been an explosive growth in our understanding of basic immunological mechanisms, celltypes and functions over the past fifty years, but the application of this knowledge to human healthhas ranged from "minute" to "undetectable". There are many reasons for this, including thediversity of human beings, likely differences between mice and humans, and problems with theexperimental design of animal models of disease. The key question though, is how to moveforward, and at Stanford we have launched a series of initiatives designed to fill in critical gaps in ourunderstanding of human immunology and establish metrics of immunological health. With suchmetrics we can begin to systematically diagnose correctly functioning immune systems from aberrantones and develop corrective therapies for the later. We might also be able to predict who will rejectan organ with standard therapy versus who will not. We also see this as a way to develop a systemsbiology approach to analyzing the immune system, which could reveal a wealth of new insights intohow this complex network of cells and molecules organizes itself and responds to both pathologicaland non-pathological microorganisms.

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11:00 THE EVOLUTION OF NON-IMMUNE HISTOLOGICAL INJURYMaarten Naesens, Department of Nephrology and Renal Transplantation, University HospitalsLeuven, Leuven, Belgium; Department of Pediatrics, Stanford University School of Medicine,Stanford, CA, USA

Learning Objectives:

1. Progression of histological injury of a kidney allograft is associated with important gene expressionalterations over time, and future histological phenotypic changes are preceded by changes on themolecular level.

2. The variability of the clinical background and the complexity of the histological picture need to betaken into account when patient samples are used for transcriptomic analysis.

3. Even in the absence of acute rejection, it becomes clear that the innate and adaptive immunesystems play an important role in the evolution of histological injury over time after renaltransplantation.

In renal transplantation, slowly progressive chronic tubulo-interstitial damage jeopardizes long-termrenal allograft survival. Both immune and non-immune mechanisms contribute to this progressiverenal allograft scarring, as is demonstrated in protocol biopsy studies. Until now the specific tools toprevent this progression of chronic histological damage have not yet been identified. Micro-arraytechnology can be applied on biopsy samples in order to get a better insight in these molecularchanges and pathways, and could yield promising targets for timely intervention.

In this presentation, protocol biopsy results are used to demonstrate the pathways involved in theevolution of histological injury over time. Previous and recent micro-array data are reviewed thatshed light on the risk factors and mechanisms of chronic histological damage. As is demonstrated inthese studies, it has to be emphasized that great care should be given to careful patient selection,unbiased and detailed histological scoring and strict sample classification. The complexity of thehistological picture and the important clinical variability has to be taken into account whentranscriptomic data are analyzed in clinical samples. The complexity of the clinical parameters, thecomplex physiology and immunology, the complex histological outcome, the multitude of data persample and the complex data analysis can only lead to biologically and clinically meaningful resultswith a multidisciplinary, holistic approach.

Finally, it is becoming clear that immune and non-immune factors are impossible to separate fromeach other after transplantation, and many non-immune phenomena also lead to immune activation.Immune activation is already evident in biopsies of deceased donor kidneys prior to implantationcompared to living donor kidneys. When rejection-free renal allograft biopsies obtained post-transplantation are compared to pre-implantation samples, there is also a major shift in global gene

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expression, with highly significant overrepresentation of immune genes involved in mostly adaptiveimmune responses. In post-transplantation samples of patients who did not experience delayed graftfunction, clinical or subclinical rejection episodes, there is a highly significant association ofestablished, ongoing and most importantly, future chronic histological damage with regulation ofadaptive immunity but also innate immune response genes.

These findings underscore the complexity of the immunological processes in human kidneytransplantation, and corroborate the idea that inflammation that is quantitatively below thediagnostic threshold of acute T-cell mediated rejection is involved in early subclinical stages ofprogressive renal allograft damage. Timely intervention aimed at influencing these early immuneresponses could well be the clue to slow or abort the progression of chronic renal graft scarring andimprove long-term graft survival.

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11:20 THE GENOMICS OF FIBROSIS PROGRESSIONValeria Mas, Associate Professor, Departments of Surgery and Pathology; Director, MolecularTransplant Research Laboratory, Division of Transplant, Virginia Commonwealth University,Richmond, VA, USA

Learning Objectives:1. Understand the molecular events involved in fibrogenesis in allograft response to chronic injury.2. Evaluate the utility of early systematic molecular signatures study of protocol biopsy tissues to

identify those patients at high risk of allograft fibrosis progression.3. Analyze the critical importance of prospective studies with appropriate sample size for power of

calculation in biomarker discover of fibrogenesis post-transplantation.

Fibrosis is the replacement of normal tissue by scar tissue as consequence of a reactive or reparativeprocess called fibrogenesis. Stimuli to injury may include cell necrosis, apoptosis, inflammatory cellinfiltration, and extra cellular matrix (ECM) alterations. The response to injury triggers the productionof cytokines and other extracellular signals, including reactive oxygen species. These stimuli induce afibrogenic response, resulting in an accumulation of ECM proteins within the organ as consequenceof an imbalance between the deposition and degradation of ECM components.

Although self-reliant scar tissue has no effect on long-term outcomes, fibrogenesis will result in organfailure if injury persists or if response to injury is excessive. Protocol biopsies have played animportant role demonstrating that fibrosis occurs before graft dysfunction is present.

Transcriptional changes may be detectable prior to histological apparent fibrosis, and discriminationof inflammatory infiltrates according to the group of expressed genes, promises to both improvediagnoses and optimize treatment strategies. Systematic analysis of gene-expression patterns willprovide a window into the biology and pathogenesis of allograft fibrosis development. Innovativedata of early detection of molecular patterns associated with fibrosis graft development in earlyprotocol biopsies will be presented.

Gene expression analysis results will be presented for two different conditions (Loss of graft functionwith interstitial fibrosis (IF) and tubular atrophy (TA) in kidney transplant recipients (KTR) and HCVrecurrence post-liver transplantation (LT)). For loss of graft function with IF/TA, gene expression(microarrays) in protocol biopsies was performed. Whether the pre-existing histological changes inthe time zero biopsies were involved in post-transplant IF/TA progression was considered in theanalysis.

For HCV recurrence post-LT, formalin fixed embedded tissues (FFPE) protocol biopsies wereevaluated using Whole Genome DASL Assay (Illumina). Prediction modeling systems wereestablished combining molecular and clinical data for predicting risk of allograft fibrosisdevelopment.

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11:40 RNA SILENCING IN GENE REGULATIONChristopher Contag, Co-Director, Molecular Imaging Program at Stanford, Associate Professor,Department of Pediatrics and of Microbiology and Immunology, Stanford University, Stanford, CA, USA

Learning Objectives:

1. Participants should learn the strengths and limitations of the various imaging modalities used tostudy transplantation biology.

2. Participants should learn about optical imaging and the opportunities for advancingtransplantation biology.

3. The molecular basis of how several mediators of successful tissue and cell engraftment enablelong term survival will be identified and the participants should understand the basic mechanisms.

Tissue and cell transplantation hold tremendous potential for the development of new therapeuticstrategies, however the nature of these tissues and cells that make them so valuable, also makesthem very difficult to study. The development of imaging tools that enable visualization of the fatesand function or transplants will accelerate and refine studies in transplantation biology. In stem celltherapies the aim is to transfer relatively small numbers of undifferentiated cells that then sense thetissue environment and respond with a directed proliferation into a large number of cells dedicatedto a specific function. Therefore to study these processes effectively, tools need to be used that havea broad dynamic range to initially detect small numbers of cells in vivo and then monitor thetremendous cellular expansion and differentiation associated with tissue restoration. This requires theuse of molecular markers that are linked to cellular metabolism, are replicated during the cellularproliferation such that the signals are not diluted or lost, and that are stable during the differentiationprocess with tolerance to significant changes in cell physiology. These signals need to be detectedexternally and monitored temporally. The emerging technologies in the field of molecular imaginghave been used for these purposes and are providing new insights into stem cell and transplantationbiology.

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12:00 LUNCH, POSTERS & EXHIBITS (FOYER)

13:30-16:00 PREDICTING GRAFT RISK BY TRANSPLANTOMICSCo-chairs: Philip O’Connell, Westmead, Australia

Thomas Mueller, Edmonton, AB, Canada

Session is sponsored through an unrestricted education grant from Bristol-Myers Squibb.

13:30 THE IMPACT OF GENOME-WIDE VARIATION IN RENAL TRANSPLANT DONORS AND RECIPIENTSON GRAFT SURVIVALGraham Lord, Professor of Medicine, Nephrology, Transplantation and Internal Medicine; Director ofTranslational Research Development and Deputy Director of NIHR Comprehensive BiomedicalResearch Centre; Guy’s and St. Thomas’ Hospital and King’s College London, London, UK

Learning Objectives:

1. Understand the theory of genome-wide association scans.

2. Understand ways of analyzing the interaction of two genomes in a single patient.

3. Learn what is known about the genetics of allograft dysfunction.

Genetic interactions between donor and recipient genomes in the context of renal transplantationdetermine early and late renal allograft dysfunction and subsequent transplant failure. Renaltransplant failure is largely genetically determined and the majority of the donor and recipient genesthat cause allografts to fail are unknown. Genome wide association scans in this patient populationwill help us to define the genetic variation in donor and recipient genomes that determine long termrenal allograft outcome and the variation in donor and recipient genomes that determine short termrenal allograft dysfunction. Furthermore, we are able to discover variation in the recipient genomethat correlates with end-stage renal failure.

Resolving these scientific questions will rapidly enable early translational studies of organ allocationand graft monitoring with a realistic prospect of improving patient outcomes within a relatively shorttimeframe.

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14:00 CHALLENGES IN ASSOCIATION STUDIES OF SINGLE NUCLEOTIDE POLYMORPHISMASSOCIATED AND RENAL TRANSPLANT OUTCOMESAjay Israni, Assistant Professor of Medicine, Adjunct Professor of Epidemiology & CommunityHealth, Hennepin County Medical Center, University of Minnesota, Minneapolis, MN, USA

Learning Objectives:

1. To understand issues of study design related to single nucleotide polymorphisms (SNPs) intransplantation.

2. To understand challenges of analyzing outcomes data in genetic epidemiology studies.

3. Consider the future direction for studies of genomic variation in transplantation.

The Genomics of Transplantation is a NIH funded genetic ancillary to an ongoing prospective cohortof renal transplant recipients. This ongoing, international, multi-center cohort is Deterioration ofKidney Allograft Function (DeKAF) study (PI, Arthur Matas). We will discuss the issues relevant to thedesign of our Genomics of Transplantation study. Our study includes 2 projects, geneticepidemiology project (Project Leader, Ajay Israni) and pharmacogenomics (Project Leader, PamalaJacobson). All study subjects are prospectively enrolled, kidney transplant recipients and their livingdonors, at the 6 study sites of DeKAF. Target enrollment is 4,000 recipients in the test and validationcohorts. Sites are: University of Minnesota and Hennepin County Medical Center, Minneapolis, MN;University of Alberta, Edmonton, Canada; University of Iowa, Iowa City, IA; University of Alabama,Birmingham, AL; and the Mayo Clinic, Rochester, MN. Genotyping will employ a custom Affymetrixchip with 3,500 functional single nucleotide polymorphisms (SNPs) in the Genotyping Core (CoreLeader, William Oetting).

The genetic epidemiology project will study the relationship SNPs of recipient and donor genes withchronic allograft dysfunction (CGD) and estimated glomerular filtration rate (eGFR). The project willalso compare the frequency of SNPs that are associated with CGD and eGFR among AfricanAmericans (AA) and non-AA, given the increased risk of allograft loss among AA.

The pharmacogenomics project will test the hypothesis that SNPs of drug metabolizing enzymes,transporters, drug targets and biological pathways are associated with immunosuppressantexposure, adverse effects and clinical outcomes.

The results from the test cohort of both projects will be discussed.

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14:20 MICRORNA AND RNA PROFILES WITH GRAFT REJECTIONDany Anglicheau, Associate Professor, Kidney Transplant Unit, Necker Hospital, Paris, France

Learning Objectives:

1. Learn a framework for developing microRNA as new biomarkers of kidney allograft outcome.

2. Discuss the implication of miRNAs as new biomarkers of allograft rejection.

3. Gain an understanding of the application of urinary cell mRNA levels as markers of IFTA and graftoutcome.

The overall objective of this talk is to present new biomarkers of acute T-cell mediated rejection ofthe kidney allograft and of interstitial fibrosis/tubular atrophy, the hallmark of chronic allograftnephropathy, by the analysis of microRNA (miRNA) or messenger RNA (mRNA) profiles in biopsysamples or urinary cells.

We have identified a molecular signature of acute rejection based on a high throughput miRNAquantification of kidney allografts. Our investigation identified a subset of 17 miRNAs that aredifferentially expressed in acute rejection biopsies compared to normal allograft biopsies at a P-value < 0.01, and the presence or absence of acute rejection could be accurately predicted usingmiRNA expression patterns. The identification of differentially expressed miRNAs during an episodeof acute rejection could lead to the development of new non-invasive biomarkers.

Through the analysis of mRNA expression levels in urinary cells, we have recently developed newhypothesis-driven mRNA biomarkers that can noninvasively diagnose interstitial fibrosis/tubularatrophy. In addition, a combination of mRNAs involved in epithelial-to-mesenchymaltransition/fibrogenesis and alloimmune response appeared predictive of the subsequent function ofkidney allograft with normal histology.

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14:40 PREDICTORS OF TRANSPLANT VASCULOPATHY AND GLOMERULOPATHY

Roslyn B. Mannon, Director of Research, Alabama Transplant Center; Professor, Department ofMedicine, Division of Nephrology; Department of Surgery, Division of Transplantation, University ofAlabama at Birmingham, Birmingham, AL, USA

Learning Objectives:

1. To understand the methodology utilizing low density real time PCR arrays.

2. To recognize the potential factors mediating transplant glomerulopathy.

3. To identify novel strategies to diagnose and monitor for late kidney allograft injury.

Long-term kidney allograft survival continues to improve modestly, despite dramatic improvementsin acute rejection rates and short term patient and graft survivals (1). Identification of biomarkers ofallograft failure and the development of tools for their interpretation is of critical interest, both inproviding disease detection in a more sensitive and specific fashion, and in allowing sufficient leadtime for intervention. Additionally, such markers may allow for risk assessment and medical-regimentailoring that is personalized to provide optimum outcomes.

Transplant glomerulopathy (TG) is a disease of the kidney allograft initiated by endothelial injury.Morphologically, there is widening of the subendothelial space with accumulation of debris,mesangial interpositioning and matrix deposition in the glomerular capillary wall, and capillary walldouble-contouring in the absence of immune complex deposition (2). The etiology of TG is underconsiderable scrutiny. Prior studies implicated an antibody mediated response (3-5), but this has notbeen consistently demonstrated (6-7). Accompanying this lesion may be evidence of chronic injury,including interstitial fibrosis and tubular atrophy (IF/TA), the hallmarks of chronic allograftnephropathy (8). Clinical presentation often occurs a year or more after transplantation, although inthe context of protocol kidney biopsies, light microscopic changes may be seen earlier, withassociated proteinuria, hypertension, and a progressive decline in function culminating in graft loss(9). Importantly, there is no specific effective therapeutic strategy beyond augmentation ofimmunosuppression. Thus, identifying pathogenic mediators not only for therapeutic purposes butalso for early identification may lead to improved outcomes.

We have assessed the potential of a novel diagnostic method utilizing custom low density geneexpression arrays and machine learning algorithms in an effort to determine the transcriptionalfeatures associated with TG and to begin to identify biomarkers that may be indicative of TG. Initialdata analysis using conventional statistical methods confirms the pro-inflammatory state of thislesion. Incorporation of these data utilizing machine-learning software, however, has derivedstatistically significant yet substantially novel associations between individual transcripts. Moreover,

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the resulting model provides insight into the probable pathogenesis of TG and a set of potentialbiomarkers to test and characterize recipients at risk for disease. These results highlight thehypothesis-generating potential of this method by elucidating potential pathways for investigationand the decision-supportive utility of defined, quantitative classification models of disease versushealth states.

References:1. Meier-Kriesche HU, Schold JD, Srinivas TR, Kaplan B: Lack of improvement in renal allograft survival despite a marked decrease

in acute rejection rates over the most recent era, Am J Transplant 2004, 4:378-383

2. Racusen L: Chronic transplant glomerulopathy: need for further assessment, Clin J Am Soc Nephrol 2007, 2:1108-1109

3. Mauiyyedi S, Pelle PD, Saidman S, Collins AB, Pascual M, Tolkoff-Rubin NE, Williams WW, Cosimi AA, Schneeberger EE, ColvinRB: Chronic humoral rejection: identification of antibody-mediated chronic renal allograft rejection by C4d deposits inperitubular capillaries, J Am Soc Nephrol 2001, 12:574-582

4. Regele H, Bohmig GA, Habicht A, Gollowitzer D, Schillinger M, Rockenschaub S, Watschinger B, Kerjaschki D, Exner M:Capillary deposition of complement split product C4d in renal allografts is associated with basement membrane injury inperitubular and glomerular capillaries: a contribution of humoral immunity to chronic allograft rejection, J Am Soc Nephrol2002, 13:2371-2380

5. Sis B, Campbell PM, Mueller T, Hunter C, Cockfield SM, Cruz J, Meng C, Wishart D, Solez K, Halloran PF: Transplantglomerulopathy, late antibody-mediated rejection and the ABCD tetrad in kidney allograft biopsies for cause, Am J Transplant2007, 7:1743-1752

6. Akalin E, Dinavahi R, Dikman S, de Boccardo G, Friedlander R, Schroppel B, Sehgal V, Bromberg JS, Heeger P, Murphy B:Transplant glomerulopathy may occur in the absence of donor-specific antibody and C4d staining, Clin J Am Soc Nephrol2007, 2:1261-1267

7. Al Aly Z, Yalamanchili P, Cortese C, Salinas-Madrigal L, Bastani B: C4d peritubular capillary staining in chronic allograftnephropathy and transplant glomerulopathy: an uncommon finding, Transpl Int 2005, 18:800-805

8. Gloor JM, Sethi S, Stegall MD, Park WD, Moore SB, DeGoey S, Griffin MD, Larson TS, Cosio FG: Transplant glomerulopathy:subclinical incidence and association with alloantibody, Am J Transplant 2007, 7:2124-2132

9. Cosio FG, Gloor JM, Sethi S, Stegall MD: Transplant glomerulopathy, Am J Transplant 2008, 8:492-496

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15:00 A SIGNATURE FOR OPERATIONAL LIVER TRANSPLANT TOLERANCEAlberto Sanchez-Fueyo, Hospital Clinic Barcelona, University of Barcelona, Barcelona, Spain

Learning Objectives:

1. Operationally tolerant liver recipients exhibit characteristic expression patterns in peripheralblood.

2. Innate type immune cells appear to be involved in the maintenance of the tolerant state in humanliver recipients.

3. Transcriptional profiles from tolerant liver and kidney recipients show minimal overlap.

A fraction of liver transplant recipients can discontinue all immunosuppressive therapies withoutundergoing rejection (operational tolerance). However, accurate identification of these recipientsremains a challenge. We have employed both Affymetrix microarrays and real-time PCR technologiesto explore in peripheral blood samples the differential gene expression between tolerant recipientsand those requiring indefinite immunosuppressive therapy, and ultimately to design a clinicallyapplicable molecular test of tolerance in liver transplantation. To do so we have studied peripheralblood transcriptional patterns from 80 liver transplant recipients in whom a previous attempt atimmunosuppression withdrawal had been attempted, and from 96 recipients enrolled in aprospective trial of immunosuppression withdrawal. This has resulted in the discovery and validationof several gene signatures comprising a modest number of genes capable of identifying tolerant andnon-tolerant recipients with high accuracy. Multiple peripheral blood lymphocyte subsets andfunctional pathways contribute to the tolerance-associated transcriptional patterns, but NK-relatedgenes appear to exert a predominant influence. These patterns substantially differ from theexpression profile identified in tolerant kidney recipients. We conclude that transcriptional profilingof peripheral blood can be employed to identify liver transplant recipients who can discontinueimmunosuppressive therapy and that innate immune cells are likely to play a major role in themaintenance of operationally tolerance in liver transplantation.

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15:20 CAN IMMUNE ACCOMMODATION BE PREDICTED USING “-OMICS” TOOLS? Bruce McManus, Professor, Department of Pathology and Laboratory Medicine, University of BritishColumbia, Vancouver, BC, Canada

Learning Objectives:

1. To convey the overall discovery rationale and strategies in the Biomarkers in Transplantationinitiative within the PROOF Centre of Excellence.

2. To share current data and early insights regarding the ability to predict rejection or its absence inkidney and heart allograft recipients.

3. To foster discussion and collaboration in regards to prediction and the use of “-Omic” tools.

Introduction: Organ transplantation remains the main treatment for end-stage heart and kidneyfailure. The Biomarkers in Transplantation (BiT) team and the PROOF Centre of Excellence haveundertaken an unbiased discovery strategy to identify and ultimately validate biomarker panelsdiagnostic and predictive of immune rejection in prospectively enrolled heart and kidney failurepatients receiving transplanted allografts. Utilizing high-performance genomics, proteomics andmetabolomics platforms, the BiT team has internally validated peripheral blood-derived diagnosticbiomarker panels of acute and chronic rejection. These panels are currently undergoing externalvalidation and qualification in a Canada-wide trial.

Predictive Biomarkers: The challenges of precision, accuracy, timeliness and invasiveness of currentpatient monitoring approaches post-transplant provide significant impetus to a search for “-Omics”markers for prediction of those at risk of immune rejection. Indeed, a significant goal in transplantimmunology remains the prediction and prevention of organ rejection as opposed to the diagnosisand treatment. The realization that humans are immunologically distinct, dating back to discoveriesof ABO blood groups and MHC antigens, has led to extensive research directed towards predictingand preventing organ rejection. The application of “-Omics” technologies to the task of predictingimmune accommodation, tolerance or rejection is a natural extension of these efforts.

Kidney Transplantation: Biomarkers of early graft accommodation would offer an important optionfor post-transplant monitoring and permit timely and effective therapeutic intervention. The BiTteam investigated longitudinal PAXgene-based gene expression patterns in peripheral blood ofquiescent kidney transplant recipients to better understand early phases of accommodation. Wehave generated a comprehensive signature of immediate gene expression changes in whole bloodafter renal transplantation reflecting a variety of immune and inflammatory processes, as well asregenerative processes occurring after the transplantation procedure. Monitoring longitudinalchanges in biological processes as reflected in peripheral gene expression may provide insights intothe mechanisms of immunological accommodation, and thus facilitate personalization ofimmunosuppressive regimens.

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Heart Transplantation: End-stage heart failure is characterized by a peripheral blood molecularsignature reflective of the homogeneity of the final common pathways of failure. Reversion of thelevels of these markers post-transplant to baseline may be reflective of “normalized” graftperformance and could impact patient outcomes. The BiT team analyzed gene expression profiles ofa subset of patients, demonstrating that approximately one third of end-stage genomic markersrevert to normal levels post-transplant. These molecular signatures may give insight into both thepathogenesis of heart failure and the processes of tolerance and accommodation occurring followingtransplantation.

Conclusion: Limitations of current diagnostic and predictive approaches has led many intransplantation science to assess “-Omics” platforms for more sensitive and specific, clinically helpfulbiomarkers. While the notion that graft integrity post-transplant may be predicted pre-surgery hasexisted for many years, current approaches may bring the field closer to this yet elusive goal.

15:40 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

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16:00 MINI-ORAL PRESENTATIONS Co-chairs: Allan D. Kirk, Atlanta, GA, USA

Roslyn B. Mannon, Birmingham, AL, USA

This session has one combined Q&A period at the end of the session. Delegates are encouraged tovisit the presenters at their posters during the Poster Reception (immediately after this session).Abstracts are located on pages 51 to 68.

16:00 P-01 – EARLY EVENTS IN THE ALLOGRAFT IDENTIFY MARKERS THAT PREDISPOSE AND INITIATETHE DAMAGE INVOLVED IN THE PROGRESSION TO INTERSTITIAL FIBROSIS (IF) ANDTUBULAR ATROPHY (TA)Daniel Maluf, Kellie Archer, Mariano Scian, Anne King, Davis Massey, Benjamin Whitehill,Marc Posner, Valeria Mas. Hume-Lee Transplant Center, Virginia Commonwealth University,Richmond, VA, USA.

16:05 P-09 – INNATE AND ADAPTIVE IMMUNE GENE ExPRESSION DYNAMICS AND PROGRESSION OFCHRONIC HISTOLOGICAL DAMAGE OF RENAL ALLOGRAFTSMaarten Naesens, Li Li, Tara Sigdel, Purvesh Khatri, Neeraja Kambham, Oscar Salvatierra,Minnie Sarwal. Department of Pediatrics, Stanford University School of Medicine, Stanford,CA, USA.

16:10 P-08 – ExPRESSION SIGNATURES OF ExTRACELLULAR MATRIx RELATED TRANSCRIPT SETSLINKED RENAL ALLOGRAFT INTERSTITIAL FIBROSIS/TUBULAR ATROPHY WITH ACUTE T-CELL MEDIATED REJECTIONSilke Rödder1, Andreas Scherer2, Hans-Peter Marti1. 1University of Bern, Inselspital Bern,Department of Nephrology and Hypertension, Switzerland; 2Spheromics, Kontiolahti, Finland.

16:15 P-18 – ASSESSMENT OF KIDNEY ORGAN QUALITY AND OUTCOME USING THETRANSCRIPTOME OF THE IMPLANT BIOPSYThomas Mueller1, Motaz Obeidat1, Gordon Broderick1, Wenjie Wang2, Phillip Halloran1,Valerie Luyckx1. 1Division of Nephrology and Immunology, Department of Medicine,University of Alberta, Edmonton, AB, Canada; 2Division of Nephrology, Department ofMedicine, University of Calgary, Calgary, AB, Canada.

16:20 P-05 – A PERIPHERAL BLOOD 12 GENE-SET FOR DIAGNOSIS OF PEDIATRIC LIVER ALLOGRAFTTOLERANCELi Li, Anita Talisetti, Sue Hsieh, Ken Cox, Carlos Esquivel, Waldo Concepcion, Minnie Sarwal.Pediatic Department, Stanford University, Stanford, CA, USA.

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16:25 P-14 – THE EUROPEAN TOLERANCE INVESTIGATION PLATFORM: A UNIFIED RESOURCE FORTOLERANCE DATA MININGPatrick Miqueu1, Coline Thomas2, Hilke Schmidts3, Olivier Rivain2, Michel Goldman4, LucienneChatenoud1, Kathryn Wood5, Hans-Dieter Volk3. 1INSERM U580, Hôpital Necker-EnfantsMalades, Université Paris Descartes, Paris, France; 2EA 4275, Faculty of PharmaceuticalSciences, University of Nantes, Nantes, France; 3Institute for Medical Immunology and Berlin-Brandenburg Center for Regenerative Therapies, Charité University Medicine, Berlin,Germany; 4Institute for Medical Immunology, Université Libre de Bruxelles, Brussels, Belgium;5Transplantation Research Immunology Group, Nuffield Department of Surgery, University ofOxford, Oxford, UK.

16:30 P-16 – META-ANALYSIS OF SOLID ORGAN TRANSPLANT DATA SETS IDENTIFIES DIFFERENTIALLYExPRESSED MIRNAS COMMON IN HEART, KIDNEY AND LUNG ALLOGRAFTSPurvesh Khatri, Richard Hayden Jones, Atul Butte, Minnie Sarwal. Department of Pediatrics,School of Medicine, Stanford University, Stanford, CA, USA.

16:35 P-19 – ExPERIMENTAL DESIGN AND QUALITY ASSURANCE OF HIGH-THROUGHPUT CLINICALTRANSPLANTOMICS STUDIES: A CRUCIAL STEP TOWARD ROBUST BIOMARKERDISCOVERYZhong Gao1, Adam Asare1, Vicki Seyfert-Margolis1, Deborah Phippard1, Vincent Carey2.1Immune Tolerance Network / UCSF, Tolerance Assays and Data Analysis, Bethesda; 2HarvardMedical School, Channing Laboratory, Boston, MA, USA

16:40 P-21 – PROTEIN MICROARRAYS IDENTIFY NOVEL NHLA ANTIBODIES SPECIFIC TO CHRONICRENAL ALLOGRAFT INJURYTara Sigdel, Li Li, Hong Dai, Poonam Sansanwal, Szu-Chuan Hsieh, Minnie Sarwal.1Department of Pediatrics, Stanford University, Stanford, CA, USA.

16:45 P-24 – AUTOANTIGEN BIOMARKER DISCOVERY THROUGH IMMUNOLOGICAL PROFILING WITHFUNCTIONAL PROTEIN MICROARRAYSDawn Mattoon1, Mary Brodey1, Gengxin Chen1, Barry Schweitzer1, Thien Dinh1, Dhavel Patel2.1Life Technologies, Cupertino, CA; 2Novartis; USA.

17:00-18:00 POSTER RECEPTION (FOYER CYRIL MAGNIN)

19:00 DINNER AT FORBES ISLAND(bus departure at 18:45 from hotel, return at 22:30; Please present your ticketupon boarding the bus.)

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08:30-10:00 PERSONALIZING MEDICINE THROUGH OMICSCo-chairs: Herwig-Ulf Meier-Kriesche, Gainesville, FL, USA

Richard N. Pierson III, Baltimore, MD, USA

08:30 CONDUCTING TRANSPLANT TRIALS FOR BIOMARKER DISCOVERYAllan D. Kirk, Professor of Surgery and Pediatrics, Emory University and Scientific Director of theEmory Transplant Center, Atlanta, GA, USA

Learning Objectives:

1. Describe the nature of clinical sample collection for -omics analysis of clinical trials.

2. Describe the informatics logistics for -omics sample collection.

3. Describe strategies for intigrating -omics into observational and interventional clinical tr

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09:00 TOOLS FOR INTEGRATIVE GENOMICSMichael Reich, Broad Institute of MIT and Harvard, Boston, MA, USA

Learning Objectives:

1. Learn how integrative genomics is contributing to our understanding of biology and themechanisms of disease.

2. Learn about tools developed at the Broad Institute for the analysis of integrative genomics data.

Integrative genomics provides unprecedented power to increase our understanding of basicbiological processes and determine the mechanisms of disease. This approach – the combining ofevidence from multiple data modalities such as gene expression, copy number, epigenetic, andmutation data to find the genomic causes of a disease state – has resulted in the identification ofnovel mutations, the discovery of causal relationships between genomic aberrations and clinicalpathologies, and other important insights in the short time it has been in practice. To take advantageof this wealth of data, new tools are needed that can span data modalities and support the verylarge datasets characteristic of integrative efforts. The Broad Institute has produced a number ofsoftware tools to facilitate integrative genomics investigations, including GenePattern, a suite of over120 tools for the analysis of gene expression, copy number, proteomics, flow cytometry, and otherdata, along with extensive capabilities for combining these tools to create complex, reproduciblemethodologies; and the Integrative Genomics Viewer (IGV), a flexible, scalable, high-performancetool for the concurrent visualization of multiple large scale datasets. These freely available tools areused by tens of thousands of researchers worldwide to improve our understanding of cancer,immunology, microbial genomics, stem cell biology, and other fields.

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09:30 THE PATH FROM ExPLORATORY BIOMARKERS TO QUALIFIED BIOMARKERS IN THE CLINICFederico Goodsaid, Associate Director for Operations in Genomics, Center for Drug Evaluation andResearch, U.S. Food and Drug Administration, Silver Spring, MD, USA

Learning Objectives:

1. Understand the need for biomarker qualification in the acceptance of new biomarkers.2. Recognize how and why regulatory agencies have developed Biomarker Qualification Processes.3. Describe the general features of the path for Biomarker Qualification at the FDA.

Exploratory biomarkers are used throughout drug development and are tested exhaustively inmultiple clinical studies. Their acceptance by clinicians depends on the data available to supporttheir use as well as on guidelines integrating these biomarkers within the standard of care. Theirtherapeutic application is also identified in drug labels. How can we determine whether exploratorybiomarkers are ready for clinical applications? How can we determine whether they are acceptablefor regulatory decision-making?

Several paths have been followed in the past to qualify biomarkers. The FDA has developed aBiomarker Qualification Process to provide a regulatory path for the qualification of biomarkerswhich may impact the use of more than one drug. This qualification path captures the consensus ondata available to support a specific context of use for a biomarker. A consensus on a context of useallows the uniform application of a biomarker across different submissions, reviewers and clinicalareas in regulatory review, as well as a predictable integration into regulatory submissions. ThisBiomarker Qualification Process is supported by draft guidelines at the US and ICH levels. Itsapplication at the EMEA is supported by legislation in the European Union and is being tested bythe PMDA in Japan. Case studies in biomarker qualification highlight the usefulness of this Processand its impact on drug development and regulatory review.

10:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

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10:30-12:00 THE ANTIBIOME AND TRANSPLANTATIONCo-chairs: Atul Butte, Stanford, CA, USA

Stuart Flechner, Cleveland, OH, USA

10:30 COMMON SIGNATURES OF REJECTION Francesco M. Marincola, Chief Infectious Disease and Immunogenetics Section (IDIS), Departmentof Transfusion Medicine, Clinical Center; Associate Director, Trans-NIH Center for HumanImmunology, National Institutes of Health & Director, CC/CHI FOCIS Center of Excellence,Bethesda, MD, USA

Learning Objectives:1. Learn about biomarkers that are relevant to cancer rejection during immune therapy.2. Lean about a common mechanism that seems to be responsible for the rejection of tissues

through immune activation.3. Discuss how this information could be used to improve treatment.

COMMON SIGNATURES OF REJECTION Ena Wang and Francesco M. MarincolaInfectious Disease and Immunogenetics Section (IDSI), Department of Transfusion Medicine, ClinicalCenter and Trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda,MD, USA.

Fundamental strides in the understanding of the molecular basis of tumor rejection were made in thelast decade thanks to observational studies performed at relevant time points in human canceroustissues. The following concepts emerged: immune surveillance against tumors is a likely occurrence.When cancer cells evolve to escape the ongoing immune defense, the neoplastic process reaches aclinically observable phase. By necessity, at this clinical stage, escape mechanisms override anti-cancer mechanisms for tumors to be observable. When cancers become established, two molecularphenotypes can usually be observed: one is characterized by a tumor microenvironment infiltratedby immune cells bearing transcriptional signatures consistent with a status of partial activation.Although incapable of dramatically affecting tumor growth, immune infiltration bears a favorableprognostic and/or predictive connotation on the natural history of the disease or its responsivenessto therapy. In this presentation, we will discuss the significance of transcriptional signatures observedin pre-treatment biopsies as predictive of responsiveness to biological therapy. Moreover, we willdiscuss the transcriptional signatures observable during and after therapy documenting the switchfrom chronic to acute inflammation that leads to tumor rejection. Finally, we will discuss howmechanisms leading to tumor rejection, largely overlap those associated with other aspects ofimmune-mediated tissue-specific destruction such as allograft rejection, graft versus host disease,acute clearance of pathogen and autoimmunity. These include overlapping yet distinct themes that

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are consistently present when TSD occurs:

• the STAT-1/IRF-1/T-bet/IFN-γ, IL-15 path

• the Granzyme A/B, TIA-1 pathway

• the CxCR3 ligand chemokine pathway

• the CCR5 ligand chemokine pathway

Understanding the basic mechanisms that can switch a chronic inflammatory process incapable oferadicating its cause into an acute reaction with the power of destroying completely the triggeringcause, may shed insights that may guide the development of novel therapeutic strategies.

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11:00 CROSS TALK BETWEEN ALLOIMMUNITY AND AUTOIMMUNITY IN ORGAN TRANSPLANTATIONThalachallour Mohanakumar, Jacqueline G. & Wm. E. Maritz Professor, Surgery, Pathology andImmunology; Director, Histocompatibility & Immunogenetics; Director, Islet Isolation Core,Washington University, St. Louis, MO, USA

Learning Objectives:

1. What are the self antigens which are known at the present time to which immune responses havebeen identified in patients with chronic rejection following human lung, heart and kidneytransplantation?

2. What are the approaches to detect immune responses to alloantigens and self antigens followingorgan transplantation?

3. What are the mechanisms by which alloimmunity may induce autoimmunity?

Chronic rejection is a major cause for morbidity and mortality resulting in poor longterm survival ofthe allografts. Our studies began with chronic rejection following human lung transplantation (LTx) ie,bronchiolitis obliterans syndrome (BOS) which develops in approximately 50% at 5 and over 90% at10 years. We demonstrated that development of anti-HLA Abs (DSA) and Abs to non-HLA antigens(self-antigens, K-alpha 1 tubulin (K-α1T) and Collagen V (ColV)) precede the development of BOS.To define mechanisms by which alloimmune responses may induce the development of autoimmuneresponses which leads to chronic rejection, we serially analyzed LTx sera from 103 LTx for thedevelopment of Ab to HLA and self-antigens (K-α1T, ColV). 42.7% developed DSA and 30.1%developed Abs to K-α1T and ColV. Detection of DSA preceded development of Abs to self-antigensand the auto-Abs persisted even when DSA was undetectable. Further, lymphocytes from BOS+ LTxproliferated upon stimulation with K-α1T and ColV. BOS+ LTx demonstrated higher frequency of Tcells secreting IL-17 and IFNγ with decreased IL-10. To confirm and define mechanisms, wedeveloped an animal model of obliterative airway disease (OAD) by administration of anti-MHC Abto native lung. Results from this model of OAD confirmed our findings in LTx which allowed us toconclude that alloimmune responses to mismatched donor HLA can induce autoimmune responsesto self-antigens which are characterized by activation of Th17 cells leading to increased IL-17 andautoimmune responses. Therefore, autoimmune responses induced by alloimmunity plays a pivotalrole in BOS pathogenesis and strategies to prevent the development of autoimmunity may beimportant in preventing chronic rejection. Cross talk between allo- and auto-immunity and theirpotential role in chronic rejection of human heart (self-antigens, myosin and vimentin) and renaltransplants (self-antigens, Col IV, Vimenin) will also be presented.

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11:20 PHOSPHOPROTEOMICS AND THE ENDOTHELIUMElaine Reed, Professor and Director of Immunogenetics, Transplant/Immunogenetics Testing, DavidGeffen School of Medicine at UCLA, Los Angeles, CA, USA

Learning Objectives:

1. Attendees of the symposium will learn different approaches to investigate biomarkers that arebeing used to detect ongoing rejection as well as attempts to identify markers that predict thedevelopment of graft injury and eventual loss.

2. Foster interactions within clinical disciplines to develop new approaches to detect and treatrejection.

3. Showcase new approaches to monitor the efficacy of immunosuppression protocols to improvepatient care.

The morphologic classification of antibody-mediated rejection (AMR) has limited sensitivity andreproducibility. Therefore, a new direction in the diagnosis of transplant rejection is the switch frommorphological classification to an approach based on molecular biomarkers. In light of thedevelopment of new immunosuppressive agents inhibiting signaling pathways, this goal is evenmore important for both diagnosis and selection of appropriate treatment strategies. Numerousstudies have demonstrated that the production of antibodies to donor HLA antigens aftertransplantation is a major risk factor for the development of AMR. The pathological effect of donorspecific antibody binding to the transplanted organ is likely to involve signaling pathways elicited byligation of class I and class II molecules on the surface of endothelial cells (EC). Ligation of HLAmolecules by antibodies induces phosphorylation of FAK and Src and prompts the assembly ofmTORC1 and mTORC2, resulting in concomitant activation of cell survival and proliferation signalingpathways. mTORC1 stimulates cell proliferation by activating Erk, p70 S6 ribosomal protein and S6kinase (S6K). mTORC2 stimulates cell survival by activating Akt and upregulating the anti-apoptoticproteins Bcl-2 and Bcl-xL. With the availability of phosphorylation-specific antibodies that can detectactivated signaling molecules, we investigated the significance of phosphorylated S6K, S6RP, and Erkin AMR by immunohistochemical staining of paraffin embedded cardiac biopsy tissue. We found astrong association between the diagnosis of AMR in cardiac transplants and the presence ofphosphorylated forms of S6 ribosomal protein and S6 kinase in the capillary endothelium of the graft(p<0.0001).Protein phosphorylation also correlated with the presence of circulating donor specificHLA antibodies (p<0.001). These data indicate that phosphorylation of S6 kinase and S6 ribosomalprotein are useful biomarkers for the diagnosis of AMR and support a role for antibody-mediatedHLA signaling in the process.

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11:40 ANTIBODY REPERTOIRES TO NON-HLA ANTIGENS IN KIDNEY TRANSPLANT RECIPIENTSPeter Heeger, Director, Clinical Research Program in Transplanation Institute, Mount Sinai School ofMedicine, New York, NY, USA

Learning Objectives:1. To list the strengths and weaknesses of antibody repertoire analysis using protein microchips.2. To explain the hypothesis that antibodies reactive to non HLA antigens can contribute to the

development of chronic allograft injury.3. To distinguish pathogenic mechanisms from biomarker analysis in the context of transplant

studies.

Emerging evidence indicates that autoreactive antibodies contribute to chronic allograft injury butthe prevalence and specificity of antibodies reactive to non-HLA antigens are poorly defined. Wetested the hypothesis that following solid organ transplantation, exposure of neo/self antigens in aproinflammatory environment breaks self-tolerance, and the induced autoantibodies contribute tochronic allograft injury. We used a protein microarray (>8000 proteins) to compare serum antibodyrepertoires, first in cross-sectional cohorts of transplant recipients with and without chronic allograftinjury. We found stronger reactivity >300 antigensin kidney transplant recipients compared to thoseon dialysis, and stronger reactivity to >100 antigens in recipients with transplant glomerulopathy(TGP) compared to those with stable kidney function. Selected antibodies, including those reactiveto EGFR and CDK9 were confirmed by dot blot assays to be more prevalent in patients with TGP. Ina second design, we analyzed antibody repertoires before and after transplant in kidney transplantrecipients with stable function and with TGP. While antibody repertoires of normal volunteers didnot change over 12 months, transplantation induced a statistically significant change in antibodyrepertoires (p=0.03 vs controls). 44% of the reactivities detected posttransplant in the stablerecipients were new compared with those found prior to transplantation, and the numbers of newreactivities increased between 6-12 months. In the TGP cohort, we found shared reactivities in theposttransplant samples to more than 100 new targets compared to the pretransplant samples.Potentially important antigens include ion transporters and histone F2A2, a described target of lupusnephritis. Together, our findings support the hypothesis that kidney transplantation inducesformation of serum antibodies reactive to self/non-HLA antigens, which may contribute to chronicinjury. In addition to providing insight into mechanisms of human allograft injury, screening antibodyrepertoires with protein arrays has the potential to identify novel biomarkers associated with allograftfailure.

12:00 LUNCH, POSTERS & EXHIBITS (FOYER)

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13:30-15:00 PROTEINS AND METABOLITES IN TRANSPLANTATIONChair: Elaine Reed, Los Angeles, CA, USA

13:30 POPULATION PROTEOMICS AND PROTEIN BIOMARKER DISCOVERYRichard Smith, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, VA,USA

Emerging proteomics technologies are promising biomarker discovery tools because of their abilityto measure thousands of proteins from complex biological samples, e.g., human blood and urine.Platforms for proteomics measurements are now largely based on mass spectrometry, and continueto advance rapidly. Yet, these technologies have met with limited success to date in establishingnew clinical biomarkers. A major challenge is to provide sufficient sensitivity for sufficiently broadcoverage of the proteome in combination with the throughput needed to account for the range ofhuman biological variation. Population studies present a tremendous challenge for the throughput ofcurrent discovery proteomics platforms that are typically capable of analyzing, at most, a fewsamples per day. Compounding this challenge is the range of protein abundances in blood, and thesensitivity needed to detect clinically relevant analytes expected to be present in low ng/mL topg/mL concentrations. In this presentation, the challenges relevant to candidate protein/proteomebiomarker discovery and verification will be discussed, and illustrated in the context of a range ofstudies using currently available platforms. New developments and platform advances will bedescribed for both broad discovery proteomics studies, and also for targeted proteomics studieswhere a subset of proteins are selected in advances for analysis with greater sensitivity andthroughput than achievable in broad discovery measurements. Present capabilities and newdevelopments will be illustrated in the context of several biomarker related applications.

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14:00 METABOLOMICS IN MONITORING ORGAN TRANSPLANTSDavid Wishart, Professor, Departments of Biological Sciences and Computing Science, University ofAlberta; Senior Research Officer and Co-director, Nanobiology Program, NRC’s National Institute forNanotechnology (NINT), Edmonton, AB, Canada

Learning Objectives:

1. To understand what metabolomics is and the kinds of technologies that are used in metabolomicsstudies.

2. To understand how metabolomics complements other “omics” methodologies.3. To learn about new, small molecule biomarkers that can be used to monitor organ function, early

stage rejection and immunosuppressive drug toxicity.

Metabolomics is an emerging field of “omics” science that allows one to rapidly identify andquantify hundreds of metabolites in organs, tissues and biofluids. It offers a complementary pictureto what can be revealed via genomics, transcriptomics, proteomics or histology. Because metabolicchanges typically happen within seconds or minutes after an “event” whereas transcript, proteinabundance or tissue changes may take place over days or weeks, metabolomic measurements mayoffer a particularly useful and inexpensive diagnostic tool to monitor donor organ viability or detectorgan rejection. While the concept of metabolomics is relatively new to organ transplantation, theidea of measuring metabolites as a quick, non-invasive probe of organ function is not. Indeed, serumcreatinine has long been used to assess pre- and post-operative organ function. However, with thedevelopment of improved metabolomic techniques, the ability to identify much more specificbiomarkers for organ function, organ viability and immunosuppressive toxicity has greatly improved.In this presentation I will give a brief introduction to metabolomics and discuss some of its strengthsand limitations. I will also provide a short overview of the results from a number of metabolomicstudies on organ transplants with a special focus on using metabolomics to monitor kidney and hearttransplants. Many of these studies have identified a number of lesser-known, organ-specificmetabolites that appear to be good diagnostic indicators of organ function, early stage rejection anddrug toxicity.

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14:20 METABOLOMICS AND RENAL TRANSPLANTATIONDavid Rush, Professor and Head, Section of Nephrology; Director, Transplant Manitoba Adult KidneyProgram, Health Sciences Centre, Winnipeg, MB, Canada

Learning Objectives:

1. To review the technique of urine 1H-NMR spectroscopy. 2. To discuss its use in serial cases post-renal transplantation.3. To review preliminary findings of the DeKAF study.

Of all the “omics” or systems biology approaches to biomarker discovery, metabolomics hastheoretically the greatest potential, as it examines biological processes that actually take place, asopposed to the examination of genes that may or may not be transcribed or of proteins that may benon-functional. The metabolomics of various biotissues and biofluids have been studied in a varietyof conditions. Our group has been studying the urine metabolome of renal transplant patients using1H-NMR spectroscopy for the last 10 years. Our initial studies focused on the differentiation betweenthe urine metabolome of patients with grafts with normal histology from that of patients withsubclinical acute rejection. More recently, and as part of the NIAID-sponsored DeKAF study, we haveexamined the urine metabolome of patients with late-onset new graft dysfunction where a clinicallyindicated biopsy showed interstitial fibrosis and tubular atrophy (IF/TA), IF/TA plus inflammation, ortransplant glomerulopathy. For each of these conditions, the urine spectra of many (n=50-100)samples with contemporary biopsies has allowed for the development of “classifiers” that wereaccurate with ~90% sensitivity and specificity for the histological diagnosis. Validation studies areunderway, and preliminary data are encouraging. With subclinical rejection, resolution ofinflammation on repeat protocol biopsy shows ‘normalization’ of the urine 1H-NMR spectrum, andpersistence of the spectrum of rejection if inflammation is not eliminated. Our data suggest that the1H-NMR spectroscopy determination of the urine metabolome in renal transplant patients has greatpotential as a non-invasive test of kidney histology, and may become a useful method to assess thesafety of immunosuppressive minimization strategies.

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14:40 HLA DIVERSITY IN TRANSPLANTATION Steven G.E. Marsh, Deputy Director of Research, Anthony Nolan Research Institute, Royal FreeHospital, London, UK

Learning Objectives:

1. Understanding the current level of HLA diversity.2. Understanding the methodology for HLA typing.3. Understanding the new HLA nomenclature.

Successful outcomes of transplantation are still highly dependant on the accurate matching of HLAmolecules between donor and recipient. Unfortunately, HLA genes are the most polymorphic geneswithin the human genome. To date over 4300 alleles have been recognised and surprisingly the rateat which new alleles are discovered is continuing to accelerate. Over 1000 alleles were described in2009 alone. This rapid expansion is primarily due to the use of sequence-based HLA typing methodsfor tissue typing. The immunogenetic and transplantation communities face major challenges in bothin defining HLA diversity and in the informatic approaches to dealing with the complex and oftenambiguous HLA data. These and related issues will be discussed.

15:00 NETWORKING COFFEE BREAK, POSTERS & EXHIBITS (FOYER)

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15:30-17:00 NOVEL APPLICATIONS OF OMICSSession sponsored through an unrestricted educational grant by Novartis.

Chair: Minnie Sarwal, Stanford, CA, USA

15:30 A METHOD TO SYSTEMATICALLY IDENTIFY CELL-TYPE-SPECIFIC DIFFERENTIAL GENEExPRESSION FROM COMPLEx TISSUESRobert Tibshirani, Associate Chairman and Professor of Health Research and Policy, and Statistics,Stanford University, Stanford, CA, USA

Accurate analysis of gene expression patterns from many tissues is hampered by the variation inrelative cell subset frequency from one sample to another and the different expression patterns ofeach cell type. Blood is a mixed tissue containing many different cell subsets, which vary in relativefrequency between individuals, both in humans and in animal models. Despite this, and at a loss ofsensitivity for differential expression, analysis of gene expression from peripheral blood is frequentlyused in both basic and clinical research as it is easily accessible and is thought to be reflective ofimmune state.

Here, we will describe a statistical methodology aimed at harnessing quantitative information onmixed tissue composition to control for tissue heterogeneity and yield increased sensitivity andspecificity from gene expression studies. We apply the method to a study of rejection in kidneytransplants.

This work is in collaboration with Shai Shen-Orr, Dale Bodian, Atul Butte, Mark Davis, Trevor Hastie,Purvesh Khatri, Balasubramanian Narasimhan, Nicholas Perry, Minnie Sarwal, Lihua Ying.

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16:00 MOLECULAR IMAGING IN TRANSPLANTATIONCaius Radu, Assistant Professor, Department of Molecular and Medical Pharmacology, UCLA CrumpInstitute, Los Angeles, CA, USA

Learning Objectives:

1. Overview of molecular imaging modalities.2. Direct and indirect PET imaging techniques to monitor immune responses.3. Potential applications of PET in transplantation.

In recent years, Positron Emission Tomography (PET) has emerged as a powerful non-invasivemolecular imaging tool. PET provides quantitative measurements of the 3D distribution of positronemitting radio-nuclides. PET scanners routinely measure radioactivity concentrations in the 10-12 Mrange, making PET the most sensitive imaging technology applicable to both preclinical and clinicalstudies. Briefly, positrons released from nuclear decay of isotope-labeled probes collide withelectrons in surrounding tissues resulting in 511keV annihilation photons emitted approximately 180°apart. These annihilation photons are detected by specialized PET detectors and variousmathematical algorithms are used to reconstruct tomographic images of probe biodistributionthroughout the body. MicroPET scanners approach a spatial resolution of ~1 mm3 while clinicalscanners have an intrinsic resolution of ~4-5 mm3. While PET was initially developed as a clinicaldiagnostic tool, the invention of the microPET has made it possible to more easily test new PETimaging strategies in small animals, before translation to the clinic. This talk will describe theadvances and challenges in using PET to visualize immune responses in vivo. I will highlight theutilization of novel probes and transgenic reporters to monitor and quantify adaptive immuneresponses and proceed to address efforts that will improve reporter imaging for basic science andclinical applications. While mainly focused on PET imaging, this talk will also highlight other imagingmodalities, including optical imaging and computed tomography, with a special emphasis on theconcept of multimodality imaging.

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16:30 USE OF NANOPARTICLES FOR AUGMENTING MUCOSAL IMMUNITYKathleen Kelly, Associate Professor and Technical Director, Department of Pathology & LaboratoryMedicine, David Geffen School of Medicine at UCLA, UCLA, Los Angeles, CA, USA

Learning Objectives:

1. Discuss the application of Nanotechnology in clinical practice and research.2. Recognize the contribution of dendritic cells for inducing immunity.3. Understand the role of an inflammasome in immunity.

Mucosal immune responses provide superior protection against disease but the ability of theimmune system to protect mucosal surfaces against invasion by pathogens is a poorly understoodprocess. Currently there are no FDA-approved adjuvants capable of stimulating robust mucosalimmunity. Protective immunity requires activation of the innate immune system and adjuvantsprovide this critical stimulation. However, the mechanism whereby adjuvants activate innateimmunity was not known until recently. Adjuvants initiate adaptive immune responses by activating aclass of innate pathogen receptors called pattern recognition receptors (PRRs), specifically Toll-likereceptors and Inflammasomes. Nanoparticles have the unique ability to deliver immunogenicpeptides and activate PRRs. This has accelerated vaccine design by engineering nanoparticle toselectively activate protective immunity. To test the utility of vaults as mucosal vaccine deliveryplatforms, we chose an infection that relies on cell-mediated mucosal immune responses forelimination and is a significant burden on health care; Chlamydia trachomatis infection. C.trachomatis is a prominent cause of STI, with approximately 92 million cases occurring annually andis an instigator of female reproductive dysfunction. T helper immune cells (Th1) must be presentwithin vaginal tissues in order to eradicate infection. We encapsulated an immunogenic protein, themajor outer membrane protein (MOMP) of Chlamydia muridarum, within hollow, vault nanocapsules(MOMP-vaults) that were engineered to bind IgG for enhanced immunity. Our data indicate thatvaults engineered to deliver antigens may in fact act as “smart adjuvants” directing Th1 mediatedimmunity in mucosal tissues without inducing excessive inflammation. Thus, natural nanoparticlescalled vaults can be engineered to act as “smart” adjuvants and serve as platforms to inducemucosal immunity against mucosal infections.

17:00 CONFERENCE WRAP UPJeremy Chapman, TTS President, Westmead, AustraliaMinnie Sarwal, Conference Chair, Stanford, CA, USAAtul Butte, Conference Co-Chair, Stanford, CA, USA

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P-01 – EARLY EVENTS IN THE ALLOGRAFT IDENTIFY MARKERS THAT PREDISPOSE AND INITIATE THE DAMAGEINVOLVED IN THE PROGRESSION TO INTERSTITIAL FIBROSIS (IF) AND TUBULAR ATROPHY (TA)

Daniel Maluf, Kellie Archer, Mariano Scian, Anne King, Davis Massey, Benjamin Whitehill, Marc Posner, Valeria Mas. Hume-Lee Transplant Center, Virginia Commonwealth University, Richmond, VA, USA.

Early gene expression (GE) changes might signal allograft injury post-transplantation (Tx) and identify kidney recipients(KRs) at risk of IF/TA progression. Prospective GE profiling of allograft biopsies (Bx)(N=120) from 30 KRs at pre-implantation(PI), post-reperfusion (PR), 3 and 9 mo post-Tx was evaluated. Time-dependent associations among GE profiling,histological allograft damage and graft stressors were evaluated. GE on PI biopsies with and without glomerusclerosis(GSC) was evaluated. KRs were classified as with (N=12) or without (N=18) IF/TA (Banff score system) at 9 mo post-KTx. TheRMA method was used to obtain probe set (Pset) expression summaries. For comparing PI to 3 mo Bx GE profiles, Psetlevel paired t-tests were performed. For 3 mo GE analysis between the biopsies with and without IF/TA at 9 mo post-KTx atwo sample t-test was used. P-values were used in estimating the false discovery rate (FDR) using the q-value method.Allograft Bx from 20 KRs were used as a validation group. Six significant Psets (P<0.001) were identified when analyzing thesamples with and without GSC at PI time. 668 probe sets were significant when comparing T0 vs. 3mo post-KTx (FDR<5%).The top molecular and cellular functions associated with these genes were cell death and protein synthesis. Apoptosissignaling was up regulated in the PI biopsies. Growth factors signaling were also up regulated. Cytotoxic T lymphocytemediated apoptosis of target cells, CD28 signaling in T helper cells and T helper cells differentiation signaling were upregulated in 3mo Bx. GE at 3mo post-KTx (IF/TA vs. no-IF/TA at 9mo post-KTx,) showed 143 significant Psets (p<0.001).HGF and FGF signaling and THBS1 expression were up-regulated in IF/TA Bxs. IL10 signaling were up-regulated in patientswithout IF/TA at 9 mo post-KTx. GE profiling changes in early protocol graft biopsies was associated with progression toIF/TA.

P-02 – DISTINGUISHING ABMR FROM TCMR USING ROC CURVE DIAGNOSTICS

J Sellarés1, J Reeve1, B Sis1, B Kaplan2, A Matas3, P Halloran1. 1Department of Medicine, University of Alberta, Edmonton,Canada; 2Department of Medicine, Nephrology Section, Arizona Health Science Centre, Tucson, AZ, USA; 3Department ofSurgery, University of Minnesota, Minneapolis, Minnesota, MN, USA.

Antibody mediated rejection (ABMR) and T cell mediated rejection (TCMR) share an intense inflammatory disturbance butthe molecular phenotype of ABMR remains poorly understood. To address this problem, we studied 403 biopsies for causefrom kidney transplant patients, analyzed with microarray chips.The area under the curve (AUC) in a receiver operatingcharacteristic (ROC) curve can be used to assess the diagnostic value of a biomarker over the full range of that marker’svalues. In addition, modifications including partial areas under the curve and user-defined sensitivity/specificity cutoffs makeROC curve statistics an attractive alternative to the more commonly used t-test. To assess the reliability of ROC curve baseddiagnostics, we used Monte Carlo cross-validation, where the full dataset was split into 1000 training:test set splits. In eachtraining set, the probeset with the highest AUC was chosen, and evaluated in the corresponding test set. The test set AUCwas then recorded. Also recorded were the proportion of times a probeset had the best AUC in the training sets, and theaverage ranking of each probeset in the training sets. Each of these methods has been advocated as a good method forfinding diagnostically relevant genes. We assessed the genes for two separate tasks: 1) Distinguishing C4d+ ABMR fromTCMR, and 2) C4d(+ or –) from TCMR. C4d-(negative) ABMR is a new category whose importance is now gainingrecognition in the transplant community. For task 1, the top genes included CD5 and GZMK (TCMR expression > ABMRexpression) and SOx7, and CDH13 (ABMR >TCMR). For task 2, the top genes included COL3A1 and CCL18 (TCMR >

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ABMR)and SLC5A11 and SOx7 (ABMR > TCMR). AUCs in the test sets for these genesranged from 72-82%. Sox7 emergesas one of the best genes for distinguishing TCMR from ABMR using either definition of ABMR.

P-03 – ASSIGNING A MOLECULAR PROBABILITY OF T CELL MEDIATED REJECTION IN KIDNEY TRANSPLANT BIOPSIES

Jeff Reeve1, Joana Sellarés1, Banu Sis1, Michael Mengel1, Bert Kasiske3, Bruce Kaplan4, Arthur Matas2, Phil Halloran1.1Alberta Transplant Applied Genomics Centre, Department of Medicine, University of Alberta, Edmonton, AB, Canada;2Department of Surgery, University of Minnesota, Minneapolis, Minnesota, MN, USA;3Department of Medicine, University of Minnesota and Hennepin County Medical Center, Minneapolis, Minnesota, MN,USA; 4Department of Medicine, Nephrology Section, Arizona Health Science Centre, University of Arizona, Tucson, AZ,USA.

T cell mediated rejection (TCMR) in kidney transplants is currently defined by an international consensus, the Banff system,based on histopathological lesion thresholds. Attempts have recently been made to define “true” or “canonical” TCMRusing gene sets from model rejection systems using mice. While both histology- and gene set-based methods will generatediagnoses highly concordant with the true disease state, each makes decisions using arbitrary definitions, and the absolutetruth can never be known with certainty. Since each allows only two categories (TCMR/no TCMR), samples close to theinterface will somtimes be misclassified. We developed a machine-learning classifier whose goal was to assign acontinuous molecular “probability of TCMR” to each biopsy sample. Individual gene expression values from 403 kidneybiopsy microarrays were used by Predictive Analysis of Microarrays (PAM) to build the classifier. We addressed the problemof the imperfect gold standard by using an iterative approach as follows: to be included in the next iteration’s gold standarddefinition of TCMR, a sample must be TCMR by the previous gold standard and have a PAM probability of TCMR of >0.5.This process resulted in the removal of samples that were called TCMR by the gold standard, but that were unlikely to betrue TCMR according to the classifier, resulting in a more robust gold standard. In both the histopathology and gene setclassifiers, the process converged within 3 iterations to produce a stable set of index cases. Furthermore, the probabilitiesof TCMR assigned by the histology and gene set classifiers were highly correlated with each other (r = 0.97), despitedifferent samples being used as index cases. The resulting continuous probability of TCMR helps the clinician assess thecertainty with which calls can be made in diagnostically difficult cases.

P-04 – A HIGHLY SPECIFIC NOVEL 3 GENE-SET CAN NON-INVASIVELY PREDICT OPERATIONAL RENAL ALLOGRAFTTOLERANCE

Li Li, Sue Heish, John Scandling, Tara Sigdel, Minnie Sarwal. Stanford University, Stanford, CA, USA.

Objectives: To improve on the sensitivity and specificity of a peripheral blood transcriptional biomarker gene-panel fordiagnosis and prediction of operational tolerance in a heterogeneous cohort of 63 adult kidney transplant recipients.

Methods: 31 peripheral blood samples were analyzed by oligonucleotide Agilent arrays from 3 different phenotypes fromdifferent transplant centers: 16 operational tolerant (TOL) kidney transplant patients without medications for more than 1year, 10 with chronic graft injury and on triple maintenance immunosuppression (CAN), and 5 healthy donors (HD). Sampleswere used as a training set to define a minimum gene-set for diagnosis of operational tolerance which were cross validatedon an 20 independant samples, including 9 TOL, previously run on cDNA microarrays (PNAS, 2007). Q-PCR was run on 21genes to build a model for prediction of tolerance by logistic regression and tested on an independent sample setcontaining 7 TOL patients. Bioinformatics analysis including GeneSpring, AILUN, SAM, PAM, logistic regression and IPAwere used.

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Results: Twenty-one unique genes were identified (FDR<5%) by prediction analysis of microarrays (PAM) and statisticalanalysis of microarray (SAM) as a minimum gene for TOL. Genes overlapping across cDNA and Agilent platforms, amongthe 21 set, could back predict 9 TOL samples run on cDNA arrays with 100% sensitivity and specificity. These genes areenriched in immune cell trafficking and 13/21 genes are regulated by TNF, IL6 and IL4. Multinomial logistic regressionmodeling by Q-PCR for all samples identified 3 genes as a minimal gene set for TOL in the array data-set with 93%sensitivity and PPV, and 90% specificity and NPV. The 3-gene model predicted TOL with 100% sensitivity and NPV, 80%specificity, and 88% PPV, in a blinded independent data-set containing 7 TOL patients. 2 out of the final 3 genes are highlyexpressed in B cells.

Conclusion: A highly regulated minimal gene-set in peripheral blood has been validated across multiple patients groupsand transplant centers. This gene-set can be used as a non-invasive monitoring tool for screening patients with stableoperational tolerance after kidney transplantation. Serial measurement of expression for this gene-set in peripheral bloodopens the door for deliberate immunosuppression minimization after transplantation, and should be further tested for itsutility in also monitoring patients on tolerance induction protocols in kidney transplantation.

P-05 – A PERIPHERAL BLOOD 12 GENE-SET FOR DIAGNOSIS OF PEDIATRIC LIVER ALLOGRAFT TOLERANCE

Li Li, Anita Talisetti, Sue Hsieh, Ken Cox, Carlos Esquivel, Waldo Concepcion, Minnie Sarwal. Pediatic Department, StanfordUniversity, Stanford, CA, USA.

Objectives: To investigate shared and unique pathways that drive pediatric and adult liver transplant tolerance. To identifythe monitoring biomarkers of liver TOL specific to pediatric and adult liver transplant tolerance.

Methods: 46 unique whole blood samples from 4 demographically matched patient phenotypes were run on AgilentWhole Human Genome 44K microarrays: 7 operational tolerant pediatric liver transplant patients were on no medicationsfrom 9.3-17.1 years (P-TOL). Additional liver transplant recipient groups were: 13 with biopsy proven acute rejection (AR), 7on low-dose prograf monotherapy/ minimal immunosuppression (MIS), and 13 stable patients on dual immunosuppression.Additionally we also processed samples from 6 healthy donors (HD). Standardized bioinformatic analyses were applied andsignificant TOL genes were mapped by AILUN to published data on Affymetrix arrays from an operational tolerance studyin adult liver transplant recipients (A-TOL; Llordella et al).

Results: Twelve unique genes were identified (FDR<5%) by prediction analysis of microarrays (PAM) as a minimum gene setto cross-validate and predict P-TOL with 100% sensitivity and 85% specificity. These genes are enriched in liverregeneration and 11/12 genes are regulated by NFkB1 and SMAD3. The tolerant specific genes are highly expressed in Tcells, CD34+ endothelial and NK cells. 65% MIS and STA patients were predicted as TOL based on prediction probabilityscores >50%. These genes also correctly predicted 76% of the 17 A-TOL samples and 95% of the 21 non-TOL samples inthe adult study. The most significant 100 genes from the A-TOL published study could not back predict any of the P-TOLsamples in the tolerance class. There is no association between gene expression and age either at the sample time or ageat the transplant for these 12 gene set.

Conclusion: Specific peripheral transcriptional programs can be identified in operational tolerance in pediatric recipients ofliver allografts, distinct from those previously identified in adult operationally tolerant liver recipients, and may provide ameans to non-invasively monitor patients in a serial manner for immunosuppression minimization. These genes are highlyexpressed in specific peripheral blood lymphocyte subsets, and their coordinated regulation by specific cytokines maysupport the maintenance of operational tolerance in children, following liver transplantation.

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P-06 – GENDER SPECIFIC DIFFERENCES IN ALLOGRAFT BIOLOGICAL AGE IMPACT ON POST TRANSPLANT ORGANFUNCTIONLiane McGlynn, Marc Gingell Littlejohn, David Kingsmore, Marc Clancy, Paul Shiels. Department of Surgery, Facultyof Medicine, University of Glasgow, Glasgow, UK.

Donor age is a key predictor of post transplant organ function but lacks the predictive value required for targetedintervention. CDKN2A transcription levels, however, act as a biomarker for allograft function at 6months and 1year posttransplant. Consequently, we have employed renal CDKN2A transcription levels pre-transplant as a prognostic biomarker ofpost transplant organ function.

Pre-implantation deceased donor renal allograft biopsies (n=61) were assayed for CDKN2A expression and any associationwith recipient urinary protein/creatinine ratio (UPCR- a sensitive marker of tubulo-glomerular damage and proven predictorof later graft failure) and white cell count (WCC) post transplant.

Patients whose donor organ expressed high CDKN2A levels had significantly elevated UPCR at 6months (p=0.025), 1year(p=0.035) and 2years post transplant (p=0.028). Conversely, these same patients had reduced WCC at 6months (p=0.028),1year (p=0.009) and 2years post transplant (p=0.020). When patients were categorised by donor sex, the associationbetween UPCR, WCC and CDKN2A was lost in patients receiving male organs. However, in patients receiving femaleorgans, high CDKN2A expression remained significantly associated with increased UPCR (p=0.012, p=0.033, p=0.009) anddecreased WCC (p=0.095, p=0.004, p=0.008) at 6months, 1year, 2years post transplant.

This study confirms that allograft biological age, as assayed by CDKN2A transcript levels, is a novel prognostic determinantfor renal function post transplant and that this is influenced by donor gender. In female organs elevated CDKN2Atranscription is associated with increased biological age and correspondingly poorer organ function post transplant. Thiswas not observed for male organs and suggests there are gender specific drivers of biological ageing. CDKN2A expressionmay provide valuable pre-transplant prognostic information on organ quality, allowing improved patient counselling andproviding the possibility for targeted intervention strategies.

P-07 – ILLUMINA-MICROARRAY ANALYSIS OF MYCOPHENOLIC ACID (MPA -INDUCED) CELL DEATH IN INSULIN-PRODUCING CELL LINE AND PRIMARY ISOLATED ISLET CELLS FROM RAT: NEW MECHANISMS INTO THEAPOPTOSIS PATHWAYS INVOLVED

Yun-Jong Park1, Joon Ye Kim1, Yuri Cho1, Hyung Joon Ahn1,2, Dong Jin Joo1,3, Yu Seun Kim1,3. 1The Research Institute forTransplantation, Yonsei University College of Medicine; 2Department of Surgery, Kyunghee University School of Medicine;3Department of Surgery, Yonsei University College of Medicine; Seoul, South Korea.

MPA, an IMPDH inhibitor, is one of the effective immunosuppressive drugs. However, MPA may induce cellular toxicity andimpair cellular function in β-cells. The mechanisms underlying cell death following MPA treatment have not been fullyexplored yet. RhoGTPases has been reported for playing a critical role such as differentiation and gene expression, andthey worked as a molecular switch on many cellular events. Among RhoGTPase subfamily, activated Rac and Cdc42 werereported to induce JNK (c-jun N-terminal kinase) activation through MEK pathway following MPA treatment. This could leadapoptosis by JNK activation through PKC (protein kinase C) activation-dependent pathway. In that pathway, activation ofp38 MAPK, Akt and ERK1/2 by TNF-α signaling are closely involved. In this study, using a microarray approach, weexamined gene expression patterns in MPA-treated INS-1E and primary isolated rat islets. Through western-blot analysis,we found that RhoGDI-α expression was altered time dependently after MPA treatment, and then these mechanismsaffected RhoGTPases, especially Rac1 activation in downstream pathway. We examined the relationship between RhoGDI-αexpression and JNK activation during MPA-induced apoptosis. MPA decreased the cellular expression of RhoGDI-α andenhanced the activation of JNK. Also, decrease of RhoGDI-α was inhibited when we treated cells with GTP and MPA

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simultaneously. Furthermore, we found that, using MTT assay, altered expression of RhoGDI-α (by using siRNA and geneover-expression methods) directly affected the cell death rate, and then regulated the apoptosis pathway through Rac1activation and downstream of MAPKs pathway. In conclusion, MPA induced cell death in insulin secreting cell line andprimary isolated pancreatic β-cells via down-regulation of RhoGDI-α linked with increased Rac1 activation, and they causedJNK activation. This RhoGDI-α/Rac1/JNK pathway could be the main therapeutic target for the prevention of MPA-inducedislet apoptosis.

P-08 – ExPRESSION SIGNATURES OF ExTRACELLULAR MATRIx RELATED TRANSCRIPT SETS LINKED RENALALLOGRAFT INTERSTITIAL FIBROSIS/TUBULAR ATROPHY WITH ACUTE T-CELL MEDIATED REJECTION

Silke Rödder1, Andreas Scherer2, Hans-Peter Marti1. 1University of Bern, Inselspital Bern, Department of Nephrology andHypertension, Switzerland; 2Spheromics, Kontiolahti, Finland.

Renal allograft T cell-mediated acute rejection (AR) and interstitial fibrosis / tubular atrophy (IF/TA) commonly shareexcessive extracellular matrix remodelling, which is regulated by the Zn-protease family of metzincins, including matrixmetalloproteases, tissue inhibitors of metalloproteases and their related genes.

Metzincins (METS, n=81) and metzincins and related genes (MARGS, n=160) were deregulated in renal allograft biopsieswith AR (n=10) and IF/TA (n=22), and microarray profiling identified METS and MARGS based AR and IF/TA genesignatures 1, 2.

Here, we illustrate the differences and conformities between AR and IF/TA METS and MARGS signatures applyingdifferential gene expression analyses, together with pathway and biological process analyses. Expression changes of METSand MARGS were also linked to patient histology.

A five-way VENN diagram of all deregulated (log2 fold change vs. Banff Normal 3(N), p<0.05) METS and MARGS in AR,AR+IF/TA, IF/TA (I, II, III) identified 2 METS and 7 MARGS to be commonly deregulated in all patient groups. Interestingly,no gene was solely deregulated in AR. In contrast, 4 MARGS, 1 METS showed unique IF/TAI deregulation and could beassociated to renal injury and hypertrophy by Ingenuity Pathway Analyses (IPA). IF/TAII and -III patients showed the greatestnumber of commonly deregulated genes. 5 MARGS, 1 METS were solely deregulated in IF/TAII, and 34 MARGS, 16 METSin IF/TAIII.

METS and MARGS, deregulated in AR were associated to the canonical pathway “hepatic fibrosis”, and higher expressionof METS in our severe and moderate IF/TA patients was significantly associated to the occurrence of AR prior to IF/TAdiagnosis.

THBS2, previously identified as IF/TA marker 2 belonged to the top scoring candidates associated to connective tissuedisorders, apoptosis and cancer identified by IPA in IFTA. QRT-PCR of microdissected functional kidney compartmentsshowed significant upregulation of THBS2 in proximal tubuli of AR and in glomeruli, proximal tubuli and tubular interstitiumof IF/TA patients. Serum ELISA revealed increasing expression of THBS2 comparing AR and IF/TA, both significantlydifferent from N patients.

In conclusion, METS and MARGS expression in IF/TA was linked to AR, and AR THBS2 upregulation may be indicative ofIF/TA development.

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P-09 – INNATE AND ADAPTIVE IMMUNE GENE ExPRESSION DYNAMICS AND PROGRESSION OF CHRONICHISTOLOGICAL DAMAGE OF RENAL ALLOGRAFTS

Maarten Naesens, Li Li, Tara Sigdel, Purvesh Khatri, Neeraja Kambham, Oscar Salvatierra, Minnie Sarwal. Department ofPediatrics, Stanford University School of Medicine, Stanford, CA, USA.

Background: In renal transplantation, slowly progressive chronic tubulo-interstitial damage jeopardizes long-term renalallograft survival. Both immune and non-immune mechanisms are thought to contribute to this progressive renal allograftscarring, but the most promising targets for timely intervention have not yet been identified.

Methods: In the current study we seek to determine the driving force behind progressive histological damage of renalallografts, without donor pathology, delayed graft function and clinical or subclinical acute graft rejection. We usedmicroarrays to examine whole genome expression profiles using tissue from 161 unique human renal allograft protocolbiopsies obtained within the first two years from two independent patient cohorts: a cross-sectional cohort [N= 89] and alongitudinal cohort [N=72].

Results: In this highly cross-validated study, we demonstrate a major shift in global gene expression when rejection-freerenal allograft biopsies obtained post-transplantation were compared with pre-implantation samples, with highly significantoverrepresentation of immune genes involved in mostly adaptive immune responses, i.e. T- and B-cell associated transcriptsets. In post-transplantation samples, we demonstrate the highly significant association of established, ongoing and mostimportantly also future chronic histological damage with regulation of adaptive immunity (T-cell and B-cell transcript sets)but also innate immune response genes (dendritic cell, NK-cell, mast cell and granulocyte transcripts), even in the absenceof classic types of acute T-cell mediated or antibody-mediated rejection as defined in the current Banff classification.

Conclusion: Progressive chronic histological damage after kidney transplantation is associated with significant regulation ofboth innate and adaptive immune responses, months before the histological lesions appear. This study thereforeunderscores the complexity of the immunological processes in human kidney transplantation, and corroborates thehypothesis that quantitative inflammation below the diagnostic threshold of classic T-cell or antibody-mediated rejection isinvolved in early subclinical stages of progressive renal allograft damage.

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P-10 – ExPRESSION OF THE PRO-APOPTOTIC MOLECULES BNIP3, BNIP3L AND BAx INDICATES THAT HUMAN ISLETSARE ExPOSED TO NUTRIENT AND OxYGEN DEPRIVATION DURING ISOLATION

Peter Campbell1, Jonathon Chee1, Lina Mariana1, Tom Loudovaris1, Shane Grey2, Helen Thomas1, Thomas Kay1.1St. Vincent’s Institute, Fitzroy, Victoria; 2Garvan Institute, Darlinghurst, NSW; Australia.

Allogeneic human islet transplantation replaces the insulin producing beta cells and corrects blood glucose levels in type 1diabetic recipients. Islets isolated from cadaveric donors are exposed to a number of insults during the isolation procedureincluding mechanical stress, hypoxia, temperature variations and enzyme impurities. These insults may lead to functionalimpairment and activation of cell death pathways resulting in loss of viable beta cell mass in the first days aftertransplantation. We investigated the expression of the Bcl-2 family of pro- and anti-apoptotic molecules in human isletspost isolation. These molecules are activated in a death stimulus-specific manner, therefore knowledge of their expressionmay help to understand the mechanism of the cellular responses involved in loss of islet homeostasis after transplantation.Microarray analysis and real time PCR were performed using RNA isolated from human islets post isolation. There was highexpression of the pro-apoptotic molecule Bax, indicating islets may be undergoing apoptosis. The hypoxia-inducible BH3-only proteins BNIP3 and BNIP3L were highly expressed, even in islets meeting the quality control criteria fortransplantation, suggesting oxygen deprivation occurs during isolation. The autophagy-inducing molecule Beclin 1 was alsohighly expressed indicating degradation of islet cell components under conditions of nutrient starvation. There was nocorrelation of cell death molecule expression with quality control assays, donor characteristics or isolation variables.Therefore expression of pro-apoptotic members of the Bcl-2 family indicates that islets are exposed to a lack of nutrientsand oxygen during isolation and this may contribute to their death after transplantation. Inhibition of these moleculesduring islet isolation may prevent the initial graft loss after transplantation.

P-11 – THE RESEARCH OF FOxP3 GENE-TRANSFERRED CD4+CD25- T-CELLS ON IMMUNE TOLERANCE IN RATCARDIAC ALLOGRAFTS

Zhenya Shen, Ning Zhong, Michun He, xiaomei Ten, Wenxue Ye, Yanqiu Hu. Department of Cardiovascular Surgery andClinical Immunology Laboratory, First Affiliated Hospital of Soochow University, Jiangsu, China.

Objective: To investigate the immune suppression effect of Foxp3 gene-transferred CD4+CD25- T-cells on acute rejection ofrat cardiac allografts and the involved mechanisms.

Methods: Rat model of abdomen heterotopic heart transplantation were established. Recipients (Wistar rat) were dividedinto four groups. Group 1: 1 ml PBS was injected before transplantation, Group 2: 1×106 fresh CD4+CD25+ regulatory Tcells were injected into recipients before transplantation. Group 3: CSA was used for intragastric administration one weekbefore transplantation. Group 4: 1×106 CD4+CD25- T cells transfected with Foxp3 gene were injected into recipientsbefore transplantation. Abdominal touch was carried out 3 times one day, 8 Wistar rats from every group were operated toobserve the abdominal graft condition. The level of IL-6 and TGF-β1 of peripheral blood in the recipients were detected.

Results: The Foxp3 gene-transferred CD4+CD25- T cell and isolated CD4+CD25+ T cell have the similar ability insuppressing the lymphocyte proliferation in vitro. Mean survival time of the grafted heart of group 1 and group 2 wasshorter obviously than that of group 2 and group 4. There was no manifest difference between group 2 and group 4. Thelevel of IL-6 of group 1 was higher than that of other groups, but there is no difference in group 2, group 3 and group 4.The level of TGF-β1 of group 2 and group 4 was much higher than group 1 and group 3, but there were no differencebetween group 2 and group 4.

Conclusion: Foxp3 gene-transferred CD4+CD25- T cells can suppress the proliferation of responsive cell, and wassuccessfully used to induce immune tolerance in rat cardiac allografts. There was no apparent difference comparing withCD4+CD25+ T cell.

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P-12 – MONITORING OF PHARMACOLOGICAL TREATMENT AND CLINICAL EVOLUTION OF RENAL TRANSPLANT, BYMETABONOMICS, NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY PROFILING AND MULTIVARIATESTATISTIC

Antonio Vivi2, Maria Tassini2, Marco Calderisi2, Mario Carmellini1, Johan Trygg3, Rasmus Madsen3, Hans Stenlund3, TorbjörnLundstedt4. 1Department of Surgery and Bioengineering, University of Siena, Siena, Italy; 2Nuclear Magnetic ResonanceCentre of Siena University, Siena, Italy; 3Department of Chemistry, Computational Life Science Cluster (CLiC), UmeåUniversity, Umeå, Sweden; 4AcureOmics AB, Umeå, Sweden.

1H Nuclear Magnetic Resonance spectroscopy (NMR) of body fluids has been successfully applied to investigate numerousdiseases and toxic processes.

Metabonomic refers to analytical techniques, like NMR spectroscopy and to the intensive use of multivariate statistic(Chemometrics).

Projection based methods such as Principal Component Analysis (PCA) and Orthogonal Projection to Latent Structures(OPLS) are applied.

An important challenge posed by NMR spectroscopy of bio-fluids is how to efficiently recover metabolic information thatallows diagnosis or classification of the post-trasplant events or pharmacological toxicity.

Proper elaboration of this data can bring to identification of a “recovery trajectory” model, i.e. evolution of metabolicprofile during recovery time, that could be the starting point for the interpretation of postoperative courses of patients. Themain strength of the proposed approach is that each patient is used as his own reference, thus the focus is on variationaround an individual starting point.

We already demonstrated the feasibility of identifying a profile reflecting biochemical changes that occur in the first twoweeks after a kidney transplant (Chemometrics and Intelligent Laboratory Systems (vol.98, 45 – 50, 2009)), the recoveryduring the first two weeks could be seen as a discrete two-stage progress.

Since each patient is used as his own reference, it is possible to build models that are more sensitive then standardmultivariate pattern recognition models, that treat data from a large group of patients altogether. In particular, the use ofrecently developed OPLS-DA analysis of NMR spectroscopy data, allow us to estimate a joint intra-person effect that isrepresentative for the majority of the individuals.

A larger dataset with more than 30 patients that have been followed also after hospital discharge (follow-up). There is theevidence that the metabolic profile trajectory go on all along the patient life and could effectively be used to monitor itsstatus.

P-13 – TLR4 SIGNALING IS INVOLVED IN IGA-STIMULATED MESANGIAL CELL ACTIVATION

Da Hye Lee1, Beom Jin Lim2, Yu Seun Kim1,3, Hyeon Joo Jeong2. 1The Research Institute for Transplantation; 2Department ofPathology; 3Department of Surgery; Yonsei University College of Medicine, Seoul, Korea.

Background: Deposition of polymeric IgA in renal mesangium is the hallmark of IgA nephropathy. However, the molecularmechanisms of IgA-mediated mesangial responses and the initiation of inflammatory injury remain still poorly understood.Renal TLR4 expression is involved in patients with IgA nephropathy. However, it is not known whether TLR4 pathway isinvolved in this mesangial activation.

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Method: Murine mesangial cell line was stimulated with LPS (1ug/ml) or IgA (20ug/ml). TLR4 expression was measured byreal time RT-PCR and western blotting. Intracellular responses to LPS or IgA were assessed by Western blotting for ERK1/2,JNK, p38 MAP kinase, and Iκ-Bα. Secretion of MCP-1 were assessed by ELISA. The effects were tested using smallinterfering RNA (siRNA) of TLR4 (25nM).

Result: LPS and IgA up-regulated the level of TLR4 mRNA and protein levels in cultured mesangial cell line at 24hr. LPSinduced rapid phosphorylation of MAP kinases (ERK1/2, JNK, p38) and degradation of Iκ-Bα. IgA also induced rapidphosphorylation of MAP kinases, but Iκ-Bα degradation was not observed. LPS and IgA induced secretion of MCP-1 at 6hr.LPS- or IgA-induced mesangial cellular TLR4, MAPKs activation and MCP-1 secretion were inhibited by transfection of TLR4siRNA.

Conclusion: Activation of MAPKs and secretion of MCP-1 by IgA are mediated, in part, by TLR4 in mesangial cells. TLR4seems to be involved in mesangial cell injury by induction of pro-inflammatory cytokines in IgA nephropathy.

P-14 – THE EUROPEAN TOLERANCE INVESTIGATION PLATFORM: A UNIFIED RESOURCE FOR TOLERANCE DATAMINING

Patrick Miqueu1, Coline Thomas2, Hilke Schmidts3, Olivier Rivain2, Michel Goldman4, Lucienne Chatenoud1, Kathryn Wood5,Hans-Dieter Volk3. 1INSERM U580, Hôpital Necker-Enfants Malades, Université Paris Descartes, Paris, France; 2EA 4275,Faculty of Pharmaceutical Sciences, University of Nantes, Nantes, France; 3Institute for Medical Immunology and Berlin-Brandenburg Center for Regenerative Therapies, Charité University Medicine, Berlin, Germany; 4Institute for MedicalImmunology, Université Libre de Bruxelles, Brussels, Belgium; 5Transplantation Research Immunology Group, NuffieldDepartment of Surgery, University of Oxford, Oxford, UK.

The European Tolerance Investigation Platform is a unique resource organizing the data pertaining to innovative clinicaltrials in the field of transplantation tolerance, launched in the framework of the European Consortium: RISET(Reprogramming the Immune System for the Establishment of Tolerance). Allowing transversal statistical analyses, thisplatform aims at the qualification and discovery of fit-for-purpose biomarkers. Twelve pilot clinical investigations, includingweaning, minimization and tolerance induction trials in kidney, liver and bone marrow transplantation, have been integratedinto a relational database. With more than 530 exhaustively monitored patients, around 4000 samples have been collectedand tested by dedicated biological assays including ‘omics’ technologies (Agilent microarrays, T cell repertoires analysis),functional investigations (screening of HLA alloantibodies, IFN-gamma ELISPOT, CTLp frequencies), virology assays andexploratory biomarkers (HMOx-1 polymorphism, expression of tolerance related genes). Cross-comparisons of clinical andimmunological data allow both confirmation of findings and new discoveries. Integrating multiple gene expressiondatasets, where genes behave similarly across several independent experiments, improves for example the statisticalconfidence of a novel biomarker. The collaborative culture established between clinicians and scientists within the RISETconsortium allows sharing and reanalysis of rare and expensive datasets. Promoting the development of a data federatinginfrastructure and knowledge management tools, such as clinical decision support algorithms, will make possible anindividually-tailored approach to post-transplant management.

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P-15 – NOVEL CELL-TYPE SPECIFIC DECONVOLUTION OF WHOLE-BLOOD GENE ExPRESSION PROFILES IN RENALACUTE REJECTION

Purvesh Khatri, Shai Shen-Orr, Robert Tibshirani, Atul Butte, Minnie Sarwal. Department of Pediatrics, School of Medicine,Stanford University, Stanford, CA, USA.

Background: Although, a set of blood-based biomarkers have been identified for acute rejection, the expression profile ofdifferent blood cell-types in rejection is unknown.

Methods: We developed a novel statistical deconvolution method for identifying cell-type specific gene expression profilesusing whole blood microarray expression data and relative frequencies of individual cell types in each sample. Whole bloodgene expression data from 24 renal transplant patients were analyzed on Affymetrix HGU133 plus 2 whole genomeexpression arrays. Of the 24 patients, 15 samples were from biopsy-proven acute rejection patients and 9 were from stablepatients. Simultaneous Complete Blood Counts (CBCs), containing relative frequencies of monocytes, lymphocytes,eosinophils, basophils, and neutrophils, were available for each sample.

Results: Whole blood gene expression analysis using SAM did not identify any significantly differentially expressed genesbetween AR and STA patients at FDR of 10%. We estimated expression profiles for each cell type in each sample usingstatistical deconvolution. Significance analysis of the estimated expression profiles identified 213 genes significantlyupregultaed in AR in one of the cell types at an FDR of 5%. Furthermore, while hierarchical clustering using whole bloodexpression data does not classify the samples correctly, the deconvoluted gene expression profile in specific cell subsetscould distinctly cluster the samples in two groups (Fig. 1). In addition, we downloaded 132 microarrays of a specific bloodcell type from NCBI GEO. As shown in Fig. 1, the estimated cell-specific expression profile in STA group is highly correlatedwith measured expression profiles in that cell type, whereas the estimated cell-specific expression profile in AR group doesnot correlate with the measured cell-specific expression profile, which clearly show that during rejection gene expressionprofiles of a specific cell-type are clearly disrupted.

Conclusion: Our novel statistical deconvolution method is able to identify the specific subset of blood cells that correlateswith acute rejection in renal allografts.

(figure1)

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P-16 – META-ANALYSIS OF SOLID ORGAN TRANSPLANT DATA SETS IDENTIFIES DIFFERENTIALLY ExPRESSED MIRNASCOMMON IN HEART, KIDNEY AND LUNG ALLOGRAFTS

Purvesh Khatri, Richard Hayden Jones, Atul Butte, Minnie Sarwal. Department of Pediatrics, School of Medicine, StanfordUniversity, Stanford, CA, USA.

Background: Recently, differentially expressed miRNAs in kidney and liver allograft rejection have been identified. The aimof our study was to investigate if there is a set of miRNAs that exhibit regulatory effects in acute rejection (AR), irrespectiveof the transplanted organ.

Method: We downloaded 5 allograft biopsy datasets from GEO (3 heart, 1 kidney and 1 lung datasets). Using miRBase, thegenes in each sample in each dataset were divided into target and non-target genes. The genes in both groups wereranked by their expression values and difference in the average ranks for both groups was computed such that highdifference in average ranks (called RE-score of a miRNA) indicate lower expression of target genes. We then calculated a t-score for each miRNA measuring the difference in RE-scores in AR versus stable (STA) samples, where higher t-scoreindicate higher regulatory effect of the corresponding miRNA in AR. The significance of t-scores was computed usingsample label permutations for both two-tail and one-tail tests.

Results: All 5 datasets showed overall trend of higher t-scores (Fig. 1A), suggesting that many miRNAs have strongregulatory effects in AR. Using a two-tail test, we identified 40 miRNAs in the lung dataset, 278 miRNAs in the kidney and40 miRNAs in all 3 heart datasets with statistically significant t-scores. Furthermore, there were 40 miRNAs that werestatistically significant (FDR [lt] 0.2) in all 5 datasets. Interestingly, hierarchical clustering of the kidney dataset using the RE-scores of these 40 miRNAs classifies the samples into two distinct clusters with one sample misclassified (Fig. 1B). Similarly,using one-tail test, we identified 128 miRNAs with statistically significant positive t-scores in all 5 datasets. Interestingly,these 128 miRNAs include 9 miRNAs that were recently found to be differentially expressed in acute rejection of renalallografts, suggesting that they may also be differentially expressed during acute rejection in other solid organs.

Conclusion: Our analysis of solid organ transplant datasets suggests there may be a common set of miRNAs that playsignificant role in rejection of allografts.

(figure1)

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P-17 – URINE METABOLITE PROFILES ASSOCIATED WITH ACUTE REJECTION IN PEDIATRIC RENAL TRANSPLANTS

Tom Blydt-Hansen1, Rajmund Somorjai2, Kirk Marat3. 1Department of Pediatrics and Child Health (Nephrology), University ofManitoba; 2Institute for Biodiagnostics, National Research Council of Canada; 3Department of Chemistry, University ofManitoba; Winnipeg, MB, Canada.

Renal biopsy is used for surveillance and diagnosis of rejection. Non-invasive testing could reduce morbidity and possiblyidentify rejection risk at an earlier stage. Nuclear magnetic resonance (NMR) spectroscopy may be used to identifymetabolite profiles associated with acute rejection in children after renal transplantation.

195 urine samples from 39 pediatric patients were obtained at the time of renal biopsy for surveillance and clinicalindication to identify rejection. Biopsies were graded according to Banff criteria and classified as no-, borderline- or acute-rejection (NR=108, BR=65, AR=22). NMR spectra (500 MHz) were obtained after correction to pH=7.0. Association ofsamples with AR was tested using Hierarchical cluster analysis. Classifiers for AR were developed using Genetic-algorithm-based optimal region selection methodology on whole spectra.

Hierarchical analysis yielded 5 principal clusters. Samples with AR were associated with clusters 2 and 4 (p=0.019). Of these,AR in surveillance biopsies (subclinical) was associated with cluster 2, whereas clinically suspected AR was associated withcluster 4 (p=0.012). Comparing AR vs. NR (excluding BR), the classification methodology achieved a balanced optimizedsensitivity/specificity of 90.7% and 90.9%. Optimizing the classifier for 100% sensitivity resulted in modest reduction inspecificity to 82.4%. Applying the classifier to the 65 BR samples, 36% and 43% were classified as AR, using the balancedand sensitivity- optimized classifiers, respectively. In a subset (NR=68, BR=40, AR=14), BR & NR were combined vs. AR,yielding sensitivity/specificity of 92.9% and 93.5%. It was not possible, however, to optimize sensitivity when the BR groupwas included with NR.

This approach is noninvasive and inexpensive and may be useful in prospective surveillance for rejection. Unsupervisedanalysis shows distinct clustering of samples with subclinical and overt AR. Urine metabolite profiles associated with acuterejection are identified in this cohort. Before being applied clinically, validation with a larger independent sample isneeded.

P-18 – ASSESSMENT OF KIDNEY ORGAN QUALITY AND OUTCOME USING THE TRANSCRIPTOME OF THE IMPLANTBIOPSY

Thomas Mueller1, Motaz Obeidat1, Gordon Broderick1, Wenjie Wang2, Phillip Halloran1, Valerie Luyckx1. 1Division ofNephrology and Immunology, Department of Medicine, University of Alberta, Edmonton, AB, Canada; 2Division ofNephrology, Department of Medicine, University of Calgary, Calgary, AB, Canada.

Robust prediction of early and late kidney transplant function using clinical and/or pathology based markers available attime of transplantation has not been achieved. Transcriptome studies are promising but the identification of predictivegenes needs reliable reference markers.

Our goal is to utilize objective measures of transplant function to refine transcriptome analysis and identify gene sets thatcharacterize organ quality and predict early and long-term kidney function.

Unsupervised microarray analysis was performed on implantation biopsies taken post-reperfusion in deceased (DD) andliving donor (LD) kidneys (test set: 42 DD, 45 LD; validation set: 25 DD, 39 LD). A ‘livingness’ vs. ‘deceasedness’ gene set,reflecting an individual kidney’s similarity to best functioning LD kidneys or worst functioning DD kidneys, was derived fromgenes overlapping between those differentially expressed among LD vs. DD and low vs. high risk for delayed graft function,

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as scores of organ quality. Early function was measured byisotope scans on post-operative days 1 or 2.

In the test set, 3718 genes differentiated LD vs DD, 1051differentiated low vs. high risk kidneys (adj p<0.01, 676 genesoverlapped between these two sets. Kidneys were plottedaccording to individual expression of the 15 highest, ‘livingness’,and 15 lowest, ‘deceasedness’, expressed genes within this set.Kidneys were strongly separated into those with best and worstearly function. When applied to our validation set the same genesagain demonstrated a continuum from best functioning to worstfunctioning kidneys (Figure 1).

This data demonstrates that the closer a DD is to an LD kidney thebetter its function, and conversely the closer an LD is to a DDkidney, the worse its function. Prospectively the coordinates of anindividual kidney plotted on this graph may reflect organ quality and permit prediction of utility of an organ fortransplantation.

P-19 – ExPERIMENTAL DESIGN AND QUALITY ASSURANCE OF HIGH-THROUGHPUT CLINICAL TRANSPLANTOMICSSTUDIES: A CRUCIAL STEP TOWARD ROBUST BIOMARKER DISCOVERY

Zhong Gao1, Adam Asare1, Vicki Seyfert-Margolis1, Deborah Phippard1, Vincent Carey2. 1Immune Tolerance Network /UCSF, Tolerance Assays and Data Analysis, Bethesda; 2Harvard Medical School, Channing Laboratory, Boston; MA, USA.

Background: Validation of biomarkers derived from smaller pilot studies requires careful consideration of technicalvariability associated with multi-site, high-throughput clinical trial settings. Microarray processing on peripheral wholeblood samples is characterized by heterogeneous cell types that are subject to drastic technical fluctuations, lowersignal/noise ratio, and higher risk of systemic batch bias. These issues hamper accuracy and robustness of biomarkerdiscovery and validation. To tackle these challenges requires sound experimental design and standardized qualityassurance methods. We address both of these aspects through: 1) Statistical design and planning for controlling batcheffect; and 2) an automated microarray QA program based on statistical modeling.

Methods: We surveyed the impact of batch effect under different circumstances including study design (cross-sectional andlongitudinal studies), and processing (retrospective and incremental processing). A parametric multivariate outlierdetection algorithm (PMVO) was developed within the Bioconductor/R statistical framework. We conducted a negativecontrol test of the system using the MAQC Affymetrix data and applied the procedure to 507 Affymetrix HG-U133 2.0 PlusGeneChips© processed with human peripheral blood RNA from five Immune Tolerance Network (ITN) trials.

Results: For retrospective studies, statistical modeling that includes batch effect as a parameter controlled systemic bias.For longitudinal studies with incremental sample processing, two RNA references with known differential expression wereused as a normalization factor to adjust expression estimates on the array. For detection of technical artifacts using PMVO,we found 18/507 trial samples to be problematic based on poor microarray quality. Statistical power analysis indicated thatexclusion of these outlier arrays substantially enhanced inferential power for detecting differential gene expression. Nooutliers were found using MAQC samples as the negative control.

Conclusion: Integration of modeling for batch effects and PMVO in a statistical pipeline constitutes a novel approach toimproving robustness of biomarker discovery.

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P-20 – PROTEOMICS IN ExPERIMENTAL AND CLINICAL LIVER ALLOGRAFT TOLERANCE

Shigeru Goto, Li-Wen Hsu, Toshiaki Nakano, Chia-Yun Lai, Yu-Fan Cheng, Chao-Long Chen. Center for TranslationalResearch in Biomedical Sciences, Liver Transplantation Program, Chang Gung Memorial Hospital-Kaohsiung MedicalCenter, Kaohsiung, Taiwan.

We have performed proteomic studies to investigate the mechanisms of immunological status of drug-free tolerance inexperimental and clinical liver transplantation.

In experimental setting of liver allograft tolerance, tolerogenic OLT (DA liver into PVG) rats were applied to proteomestudies. On the other hand, as a clinical drug-free tolerance case, one OLT patient, who has not requiredimmunosuppressive drugs for the last 9 years following post-transplant lymphoproliferative disease (PTLD) was applied toproteomic analysis using liquid chromatography-mass spectrometry.

In rat OLT, the results differentiated the varying protein expressions in sera extracted from tolerogeneic OLT rats ascompared with naïve rats. Proteomic assay also demonstrated 12 differentiated spots exclusive to a drug-free OLT patient.Among these proteins, haptoglobin (Hp), which is related to inhibition of T-cell proliferation, was found to be up-regulatedfollowing clinical and experimental OLT, may play an important role in the maintenance of experimental and clinical drug-free OLT tolerance as a natural immunological suppressor. Further identification of common proteins specific toexperimental and clinical drug-free OLT is currently been carried out.

Proteomic analysis will allow us to develop biomarkers to establish a novel weaning protocol for patients on long-termimmunosuppression to avoid major immunosuppressant-related complications.

P-21 – PROTEIN MICROARRAYS IDENTIFY NOVEL NHLA ANTIBODIES SPECIFIC TO CHRONIC RENAL ALLOGRAFTINJURY

Tara Sigdel, Li Li, Hong Dai, Poonam Sansanwal, Szu-Chuan Hsieh, Minnie Sarwal. Department of Pediatrics, StanfordUniversity, Stanford, CA, USA.

Chronic allograft injury (CAI) is mostly a humoral response driven by Ab against HLA and non-HLA antigens.

Method: To study novel nHLA targets of CAI injury, we analyzed 60 serum samples at 0, 6, and 24 mo from 20 renal txppatients, at the time of paired protocol biopsies. Protein arrays (8300 antigens) targets were used to measure reactivities ofnon-HLA Abs. Histological CAI lesions were characterized by a semi-quantitative score for CAI applied to each biopsybased on the Banff, CADI and CNIT scores. Seven kidney compartment specific gene expression analysis was performed onmicroarray data (GEO-GSE:3931) by ian ntegrated informatics approach (Li et al PNAS 2009) and CAI specific non-HLAtargets were mapped to 7 kidney regions (inner and outer cortex, inner and outer medulla, papillary tips, renal pelvis andglomeruli). Data handling, normalization and hypergeometric enrichment analysis was performed using customizedalgorithms.

Results: We observed an increase of reactivity of a total of 577 abs against non-HLA antigens in response of graft injury.When mapped to kidney specific compartments, specific nHLA abs specificites were found maximally against the renalpelvis, followed by the renal cortex. Fewer nHLA Ab were also found against the glomerulus and medulla specific renalantigens. Specific nHLA Ab are mounted at the time of established CAI to different renal compartments (P= 6.00E-5), and adefined subset of these are also idenitified as critical for CAI progression, as their signal intensity is detected at significantlevels in sera, prior to established injury on subsequent graft biopsies. Among the significant antigens, some are previously

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identified in matrix remodelling injury pathways and cell cycle progression but a number of them suggest novel pathways oftissue injury. Integrated statistical analysis of delta creatnine clearance, proteinuria and semiquantitive biopsy compartmentscores for tubular atrophy, interstitial fibrosis, mesangial matrix expansion, glomerulosclerosis and intimal thickening arecurrently underway.

Conclusion: We have identified and extensivelt mapped kidney compartment specific non-HLA abs specific to CAI that cannot only detect graft injury but also can track evolution of graft injury in real time. Further correlation of the impact of thesenHLA Ab with specific triggers of graft injury are underway. This immune atlas of the kidney is an exciting opportunity todiscover and refine our understanding and monitoring of CAI.

P-22 – NOVEL SHOTGUN PROTEOMICS APPROACH IDENTIFIES PROTEINS SPECIFIC FOR ACUTE RENAL TRANSPLANTREJECTION

Tara Sigdel1, Amit Kaushal1, Angela Norbeck2, Wei-Jun Qian2, Wenzhong xiao1, David Camp2, Richard Smith2, MinnieSarwal1. 1Department of Pediatrics, Stanford University, Stanford, CA; 2Pacific Northwest National Laboratory, Richland, WA;USA.

Background: Proteomic analysis using high-throughput proteomic analysis of urine is a unique approach to identify diseasespecific urine protein biomarkers to diagnose, predict and improve renal transplantation.

Methods: We used high throughput shotgun proteomics using cutting edge LC-MS/MS and ELISA to analyze a set of 92urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls (HC). Urine proteins >10 kDawere were subjected for strong cation exchange (SCx) fractionation. The data was acquired by using ThermoScientific LTQlinear ion trap mass spectrometer and the proteins were identified with SEQUESTTM. ELISA validation assays wasperformed on UMOD, SERPINF1, and CD44 so as to test the validity of the method and utility of identified proteins.

Results: A total of 1446 urinary proteins were identified along with a number of NS specific, renal transplantation specificand AR specific proteins. We identified alterations in a number of specific urinary proteins in AR, primarily relating to MHCantigens, the complement cascade and extra-cellular matrix proteins. Nine proteins were identified only in AR urine thatincluded HLA class II histocompatibility antigen, DP(W4) beta chain (HLA-DBP), HLA class II histocompatibility antigen,DRB1-8 beta chain (IgHM), C4b-binding protein alpha chain (C4BPA), MHC class II antigen (HLA-DR), Myosin light chain 1(MYL6B), HLA class II histocompatibility antigen DQ(3) beta chain (HLA-DQB1). A subset of proteins (UMOD, SERPINF1 andCD44), have been further cross-validated by ELISA for significant differences in the abundance of these urinary proteins inAR. The area under the curve for AR classification by the ROC analysis was calculated as 97.3% for CD44, 93.2% forSERPINF, and 84.6% for UMOD.

(Figure 1).

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P-23 – INTEGRATIVE URINARY PEPTIDOMICS IN RENAL TRANSPLANTATION IDENTIFIES NOVEL BIOMARKERS FORACUTE REJECTION

Tara Sigdel, Bruce Ling, Ken Lau, Lihua Ying, Irwin Lau, James Schilling, Minnie Sarwal. 1Stanford University Medical School,Stanford University, Stanford, CA, USA.

Background: Non-invasive, peptidomic analysis combined with microarray and Q-PCR analysis is a unique approach toidentify disease specific urine peptide biomarkers to predict and improve present status of renal transplantation.

Methods: A total of 70 archived urine samples from 50 renal transplant patients including biopsy proven AR, stable graft(STA), BK virus nephropathy (BKV), and 20 control including non-specific proteinurea (NS) or healthy controls (HC). We usedMALDI-TOF mass spectrometry in the discovery step. A quantitative multiple reaction monitoring (MRM) assay was used toverify two potential candidate peptides of uromodulin (UMOD). Available Affymetirx GeneChips data on matched kidneytransplant biopsies (20 AR and 20 STA) (NCBI GEO: GSE14328) was used for transcriptomic analysis. We extracted totalRNA from kidney biopsy samples using TRIzol reagent. cDNA was synthesized from total RNA and Q-PCR were performedon 5 ng of cDNA.

Results: Urine peptidomic analysis of 70 unique samples, from renal transplant patients (n=50) and controls (n=20),identified a specific panel of 53 peptides for acute rejection (AR). Peptide sequencing revealed underlying mechanisms ofgraft injury with a pivotal role for proteolytic degradation of uromodulin (UMOD) and a number of collagens includingCOL1A2 and COL3A1. The 40 peptide panel discriminated AR in both training (n=46) and test (n=24) sets (ROC,AUC>0.96). Integrative analysis of transcriptional data from paired renal biopsies revealed coordinated transcriptionalchanges for the corresponding genes, in addition to dysregulation of extracellular matrix proteins in AR (MMP7, SERPING1and TIMP1). Q-PCR on an independent set of 34 transplant biopsies, validated microarry data and verified a 6 genebiomarker panel (COL1A2, COL3A1, UMOD, MMP7, SERPING1, TIMP1) that can classify AR with high specificity andsensitivity (ROC, AUC 0.98).

Conclusion: Integrated urine peptidomic and biopsy transcriptional analyses identified potential AR specific markerpeptides and revealed that key collagen remodeling pathways are modulated in AR tissue.

P-24 – AUTOANTIGEN BIOMARKER DISCOVERY THROUGH IMMUNOLOGICAL PROFILING WITH FUNCTIONALPROTEIN MICROARRAYS

Dawn Mattoon1, Mary Brodey1, Gengxin Chen1, Barry Schweitzer1, Thien Dinh1, Dhavel Patel2. 1Life Technologies,Cupertino, CA; 2Novartis; USA.

The diagnostic value of serum autoantibodies for many diseases, including cancer, diabetes, and autoimmune disorders iswell established. Identifying the antigens that elicit an autoimmune response can yield panels of biomarkers that can beused as classifiers for particular diseases, disease stages, or as predictors of patient outcomes. The present study utilizedhigh content protein microarrays comprised of more than 5,000 purified full-length human proteins, including a panel of 25known autoantigens, to evaluate immunological profiles across panels of serum samples derived from healthy donors andSystemic Lupus Erythemasosus (SLE) patients. Three statistical algorithms were applied to analyze data from individualmicroarrays, to compare data between populations and identify candidate biomarkers. This line of investigation identified apanel of 18 novel biomarkers which could differentiate SLE patients from healthy individuals more accurately than a panelof 10 established SLE biomarkers. Studies utilizing the Luminex platform and a custom-printed protein microarray wereused to validate the results obtained from the ProtoArray . Taken together, our results suggest that functional proteinmicroarray technology is a powerful new tool for the rapid discovery of autoantigen biomarkers.

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P-25 – THE ROLE OF JUN IN APOPTOTIC DEATH OF INSULIN-PRODUCING CELLS FOLLOWING MYCOPHENOLIC ACIDTREATMENT

Yuri Cho1, Yun-Jong Park1, Dong Jin Joo1,2, Hyung Joon Ahn1,3, Yu Seun Kim1,2. 1The Research Institute for Transplantation,Yonsei University College of Medicine; 2Department of Surgery, Yonsei University College of Medicine; 3Department ofSurgery, Kyunghee University School of Medicine, Seoul, South Korea.

Mycophenolic acid (MPA) is widely used as an immunosuppressive drug after organ transplantations including pancreaticislet cell transplantation. However, MPA has cellular toxicity, and causes apoptotic cell death in several insulinoma cell linesand primary isolated pancreatic β-cells. However, the signal transduction mechanisms underlying this process have notbeen fully explored yet. In this study, we have used diverse technologies including illumina-microarray to examine genesthat are regulated time-dependently following MPA treatment. We found that thousands of genes were altered duringMPA-induced apoptosis. Among them, jun gene expression pattern was significantly altered, and cyclin D1 and fas-L alsowere directly affected by MPA treatment.

Pancreatic β-cell line INS-1E cells were treated with MPA for 12hr, 24hr and 36hr. Functional screening was determined byusing small interference RNA (siRNA)-mediated knockdown and over-expression of jun gene in INS-1E cell line. Expressionlevels of mRNA and protein in target genes in cell line and primary cells were determined by quantitative real-time PCR(qRT-PCR) and western blot analysis.

We found that MPA significantly increased cell death by Caspase-3, Caspase-8 and p-JNK activation. Fas-L expressionlevels were increased following MPA treatment. Over-expressed Jun decreased cell viability, and increased activation of p38MAPK, phosphorylation of JNK, Caspase-3, -8 and Fas-L expression after MPA treatment. However, knockdown of jun bysiRNA decreased MPA-induced cell death and p-JNK and Fas-L activation. In conclusion, MPA induced apoptosis in insulin-secreting cell via up-regulation of jun gene that were closely linked with MAPK pathway. In this process, activated JNKleads Fas-L long-term expression and accumulation of activated caspase-8. This accumulation of caspase-8 initiatesapoptosis through activation of caspase-3. JNK/c-Jun/FasL/caspase-dependent apoptotic pathway will play a critical role inmediating MPA-induced apoptosis of pancreatic β-cell line.

P-26 – ANTI-NUCLEAR AUTOANTIBODIES AS BIOMARKERS IN LIVER TRANSPLANTATION TOLERANCE

Toshiaki Nakano1,2, Chia-Yun Lai1, Shigeru Goto1,6, Li-Wen Hsu1, Kuei-Chen Chiang3, Kazuhisa Ono4, Hideo Kawarasaki5,Chao-Long Chen1. 1Center for Translational Research in Biomedical Sciences, Liver Transplantation Program, Chang GungMemorial Hospital-Kaohsiung Medical Center, Kaohsiung, Taiwan; 2Graduate Institute of Clinical Medical Sciences, ChangGung University College of Medicine, Kaohsiung, Taiwan; 3Kazusa Institute for Drug Discovery, Josai InternationalUniversity, Chiba, Japan; 4Department of Molecular Biotechnology, Graduate School of Advanced Sciences of Matter,Hiroshima University, Higashi-Hiroshima, Japan; 5Department of Transplant Surgery, Jichi Medical University, Tochigi, Japan;6Iwao Hospital, Oita, Japan.

Unlike other organ transplantation, orthotopic liver transplantation (OLT) is unique in terms of tolerance where recipientscan survive without immunosuppressive drugs after experimental and clinical OLT. Recent proteomic approach allows us toinvestigate the diagnostic and therapeutic potentials of various biomarkers specific to liver allograft tolerance. Especially, anew insight has been given into our study since we found that post-transplant autoimmune responses with high titer of anti-nuclear antibodies against histone H1 and high mobility group box 1 (HMGB1) play an important role in induction of liverallograft tolerance in OLT rats and clinical drug-free OLT patients. Our previous studies showed that either treatment ofrecipient rats with commercially available anti-histone H1 polyclonal Ab or immunization with calf thymus histone H1 could

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prolong allograft survival in heterotopic heart transplantation. We have also reported that the blockade of histone H1modulated dendritic cells toward tolerogenic status, decreased the cytotoxicity of lymphokine activated killer and naturalkiller cells, and induced CD4+CD25+ T cells. For further analysis of this mechanism, we generated an immunosuppressiveanti-histone H1 monoclonal Ab (16G9 mAb). From phage display peptide library, we have selected one peptide(designated SSV) that binds directly to 16G9 mAb. The binding of SSV to 16G9 mAb was inhibited by histone H1.Immunization of mice with SSV induced immunosuppression in serum, suggesting that SSV was an epitope responsible forthe immunosuppressive activity of 16G9 mAb. Furthermore, SSV binds to serum of both tolerogeneic OLT rats and clinicaldrug-free OLT patients, and the binding to SSV was also inhibited by histone H1. Further studies of biomarkers related toanti-nuclear antibodies including peptide SSV will allow us to establish a novel diagnostic and therapeutic therapy in livertransplantation.

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Anglicheau, Dany page 28

Bendall, Sean page 13

Blydt-Hansen, Tom Poster-17

Butte, Atul page 20

Chapman, Jeremy page 16

Cho, Yuri Poster-25

Contag, Christopher page 25

Dando, Caroline page 13

Davis, Mark page 21

Davis, Ronald W. page 16

Dinh, Thien Poster-24

Fan, Alice page 13

Gao, Zhong Poster-19

Ghanekar, Smita page 13

Goodsaid, Federico page 38

Goto, Shigeru Poster-20

Halloran, Philip F. page 17

Heeger, Peter page 43

Israni, Ajay page 27

Jacobs, Sharoni page 13

Kay, Thomas Poster-10

Kelly, Kathleen page 50

Khatri, Purvesh Poster-15, 16

Kirk, Allan D. page 36

Lee, Da Hye Poster-13

Li, Li Posters-04, 05

Lord, Graham page 26

Maecker, Holden page 13

Maluf, Daniel Poster-01

Mannon, Roslyn B. page 29

Marincola, Francesco M. page 39

Marsh, Steven G.E. page 47

Mas, Valeria page 24

McGlynn, Liane Poster-06

McManus, Bruce page 32

Miqueu, Patrick Poster-14

Mohanakumar, Thalachallour page 41

Mueller, Thomas Poster-18

Naesens, Maarten page 22, Poster-09

Nakano, Toshiaki Poster-26

Park, Yun-Jong Poster-07

Radu, Caius page 49

Reed, Elaine page 42

Reeve, Jeff Poster-03

Reich, Michael page 37

Rödder, Silke Poster-08

Rush, David page 46

Sanchez-Fueyo, Alberto page 31

Sarwal, Minnie page 18

Sellarés, Joana Poster-02

Shen, Zhenya Poster-11

Sigdel, Tara Posters-21, 22, 23

Smith, Richard page 44

Suthanthiran, Manikkam page 18

Tibshirani, Robert page 48

Vivi, Antonio Poster-12

Wishart, David page 45

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