CHARACTERIZATION OF LYMPHATIC VESSELS AND LYMPHATIC ENDOTHELIAL CELLS IN TYPE 2 DIABETES MELLITUS Structural, morphological and molecular analysis DOCTORAL THESIS for obtaining the academic degree of Doctor of Philosophy (Ph.D.) submitted by Monika Hämmerle, MD within the thematic program: Cell communication in health and disease (CCHD) supervised by Prof. Dr. Dontscho Kerjaschki & Dr. Brigitte Hantusch Clinical Institute of Pathology Vienna, August 2012
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CHARACTERIZATION OF LYMPHATIC
VESSELS AND LYMPHATIC ENDOTHELIAL CELLS IN TYPE 2 DIABETES MELLITUS
Structural, morphological and molecular analysis
DOCTORAL THESIS for obtaining the academic degree of
Doctor of Philosophy (Ph.D.)
submitted by Monika Hämmerle, MD within the thematic program: Cell communication in health and disease (CCHD)
supervised by Prof. Dr. Dontscho Kerjaschki & Dr. Brigitte Hantusch
Clinical Institute of Pathology Vienna, August 2012
Acknowledgements
First of all, I would like to thank my supervisors Prof. Dontscho Kerjaschki und Dr. Brigitte
Hantusch for giving me the opportunity to do my PhD in the research laboratory of the Clinical
Institute of Pathology and who supported me throughout the years.
I would like to thank my cooperation partners at the Department of Rheumatology, Carl‐Walter
Steiner, for excellent technical assistence in FACS sorting and at the Department of General
Surgery, Dr. Christoph Neumayer, for guaranteeing me that I could use my material as fresh as
possible. Moreover, I would like to thank Dr. Stefan Thurner and especially Dejan Stokic for
helping me with the bioinformatical data analysis.
I thank all my friends and colleagues from the CCHD PhD program, especially my lab mate Tom
without whom the day would not have been so much fun.
I would like to announce a big thank to Bernhard Höfle, who triggered my enthusiasm for
science.
Last but not least, I would like to thank my family and friends for their incessant support, love
and motivation.
Die Wissenschaft, richtig verstanden, heilt den Menschen von seinem Stolz;
denn sie zeigt ihm seine Grenzen.
Albert Schweitzer
I
Summary
Background ‐ Small vessel disease of kidney, nerves, retina and skin, referred to as
microangiopathy, is a major cause of morbidity in type 2 diabetes mellitus (T2DM). While
characteristic changes in blood capillary walls and endothelial dysfunction of blood vessels are
well studied in type 2 diabetes, examination of lymphatic endothelial cells (LECs) and lymphatic
vessels (LVs) is scarcely done. However, complications seen in type 2 diabetes, e.g. increased
risk for infections, wound healing defects and obesity, may be related to lymphatic dysfunction.
Therefore, we aimed at comprehensively analyzing potential morphological and structural
differences of lymphatic endothelial cells and lymphatic vessels in the skin of type 2 diabetes
mellitus patients. Further, we wanted to identify gene expression signatures that are
deregulated in human dermal lymphatic vessels to define mechanisms that are linked with
microvascular complications observed in type 2 diabetes.
Methods – By immunohistochemistry, basement membranes of lymph vessels were analyzed
and blood and lymph vessel densities of diabetic versus normoglycemic skin was evaluated.
Further, we identified signs of inflammation, e.g. macrophage infiltration and TNFα expression.
We compared the gene expression profiles of ex vivo isolated dermal LECs retrieved from
normoglycemic versus type 2 diabetic patients using microarrays and subsequent intensive
bioinformatical analysis. The up‐ or downregulated expression of selected candidate genes was
confirmed by quantitative real‐time PCR and immunofluorescence stainings. Further, we focused
on two differentially regulated genes and performed macrophage adhesion, transmigration and
chemotatic assays as well as siRNA‐mediated knockdown experiments to identify their specific
function in lymphatic endothelial cells.
Results ‐ Neither prominent alterations in extracellular matrix (ECM) protein deposition, nor
morphological BM changes of lymphatic capillaries and collecting LVs were found in the skin of
T2DM patients. This excluded the occurrence of diabetic lymphangiopathy comparable to that of
blood vessels. However, the evaluation of lymph vessel counts revealed a prominent enhanced
lymph vessel density in type 2 diabetic patient's skin. Further, we traced a strong macrophage
infiltration in the dermis of type 2 diabetic patients. These macrophages produced vascular
endothelial growth factors VEGF‐A and VEGF‐C, as well as the pro‐inflammatory cytokine TNFα.
II
Transcriptomal analysis of ex vivo isolated diabetic versus non‐diabetic LECs resulted in a list of
180 differently expressed genes. Consistent with earlier studies, we identified several genes that
have already been linked to genetic susceptibility for type 2 diabetes, including HP, APOD, HHEX,
CD55, ANXA1, LMNA and FABP4. Essentially, we observed multiple changes related to altered
LEC proliferation, adhesion and migration. Further, in line with increased TNFα abundance, we
observed expression changes of CXCL10, VCAM1, CYR61, CXADR, SDC1 and AQP3. TNFα treatment
of cultured LECs led to deregulated expression of selected genes, recapitulating the array results,
indicating that TNFα is one major contributor to diabetes‐specific gene expression signatures in
lymphatic endothelial cells. CXCL10 was confirmed as one important candidate gene only
expressed in chronically inflamed lymphatic vessels, contributing to adhesion and
transmigration of macrophages and possibly intending to resolute the dermal inflammation.
Further, the fatty acid transporter FABP4 was specifically upregulated in LECs and lymphatic
vessels in type 2 diabetes in comparison to blood endothelial cells (BECs) and blood vessels.
FABP4 was shown to regulate LEC proliferation and permeability in vitro, and pointed out the
crucial role of lymphatic vessels in fatty acid transport and metabolism.
Conclusion ‐ These data reveal gene sets highlighting the dramatically altered milieu skin
lymphatic vessels have to cope with during type 2 diabetes mellitus. Further, we discovered that
skin lymphatics show a chronic subacute inflammatory phenotype characterized by macrophage
recruitment and de novo lymphangiogenesis. We provide evidence for a paracrine crosstalk,
mainly via TNFα and CXCL10, fostering macrophage recruitment to LECs as one
pathophysiological process that might contribute to persistent inflammation and consecutively,
aberrant lymphangiogenesis in the skin.
III
Zusammenfassung
Hintergrund ‐ Mikroangiopathie, eine Erkrankung der kleinen Gefäße der Nieren, der Nerven,
der Retina und der Haut, ist eine häufige Komplikation im Verlauf des Typ 2 Diabetes mellitus.
Während diabetische Veränderungen der Blutgefäße in der Haut sehr gut charakterisiert sind,
ist über mögliche morphologische, strukturelle und molekulare Veränderungen von
Lymphgefäßen wenig bekannt. Trotzdem besteht die Vermutung, dass Komplikationen des
Diabetes wie erhöhtes Infektionsrisiko, Wundheilungsstörungen und Veränderungen des
Fettstoffwechsels auch die Folge einer Lymphgefäßdysfunktion sind. Das Ziel dieser Arbeit war
es, potentielle Veränderungen des Lymphgefäßsystems in der Haut auf morphologischer,
zellulärer und molekularer Ebene zu beschreiben. Darüber hinaus war es das Ziel, deregulierte
Genexpressionsmuster zu erkennen, um sie mit den oben genannten Komplikationen in
Verbindung zu bringen.
Methoden – In dieser Arbeit wird eine umfassende immunhistochemische Analyse der
diabetischen Haut, inklusive einer Analyse der Basalmembranen der Gefäße, der Gefäßdichte
und von Zeichen einer Entzündung, präsentiert. Zusätzlich wurde mit Hilfe der Genechip
Microarray‐Technologie und nachfolgender intensiver bioinformatischen Analyse das mRNA‐
Expressionsprofil der diabetischen im Vergleich zu nicht‐diabetischen Lymphendothelzellen, die
ex vivo aus Patientenhaut isoliert wurden, analysiert. Die Expression wichtiger Kandidatengene
wurde mit Hilfe von quantitativen PCR‐Analysen sowie Immunfluoreszenzfärbungen bestätigt.
Im weiteren Verlauf haben wir funktionell auf zwei Gene fokussiert. Es wurden
Makrophagenadhäsions‐, ‐transmigrations und –chemotaxis‐Experimente durchgeführt, um ihre
Rolle in der Interaktion mit Makrophagen zu analysieren. In siRNA‐mediierten knockdown
Studien wurde versucht, die spezifische Funktion dieser Gene in lymphatischen Endothelzellen
herauszufinden.
Ergebnisse ‐ Signifikante Veränderungen der Basalmembranen von, sowie erhöhte Expression
von Extrazellulärmatrixproteinen rund um diabetische Lymphgefäße konnten nicht gefunden
werden, was die Existenz einer sogenannten diabetischen Lymphangiopathie ausschloss.
Dennoch zeigte ein Vergleich der Lymphgefäßdichte von diabetischer und nicht‐diabetischer
Haut eine signifikant erhöhte Dichte der Lymphgefäße beim diabetischen Patienten. Zusätzlich
konnte in der diabetischen Haut eine starke Infiltration mit Makrophagen nachgewiesen
IV
werden. Diese Makrophagen produzierten vaskuläre Wachstumsfaktoren wie VEGF‐A und
VEGF‐C, sowie das pro‐inflammatorische Zytokin TNFα. Der transkriptionelle Vergleich des
mRNA‐Profils von diabetischen und nicht‐diabetischen Lymphendothelzellen führte zur
Identifikation von 180 differentiell regulierten Genen. Neben Genen, die als mögliche
Suszeptibilitätsgene für die Entwicklung des Typ 2 Diabetes gelten, wie z.B. HP, APOD, HHEX,
CD55, ANXA1, LMNA und FABP4, wurden Transkripte gefunden, die mit der Proliferation von
Lymphendothelzellen, sowie mit der Adhäsion und Migration von inflammatorischen Zellen in
Gefäßen assoziiert sind, was mit dem immunhistochemischen Befund korrelierte. Es wurden
besonders prominente Expressionsunterschiede von CXCL10, VCAM1, CYR61, CXADR, SDC1 und
AQP3 detektiert. Diese konnten durch eine Stimulation von Lymphendothelzellen mit TNFα in
vitro spezifisch rekapituliert werden. CXCL10 wurde als ein wichtiges Chemokin identifiziert, das
wahrscheinlich nur im Rahmen einer Entzündung auf dermalen Lymphgefäßen exprimiert wird
und das eine wichtige Rolle bei der Adhäsion und Transmigration von Makrophagen und damit
möglicherweise bei der Auflösung einer lokalen Entzündung spielt. Es war auch eine
Gensignatur von Lipidtransportern in dLECs dereguliert. Darunter war speziell die Expression
von FABP4 nicht nur in diabetischen Lymphendothelzellen und Lymphgefäßen signifikant
erhöht, sondern grundsätzlich spezifisch für Lymph‐ im Vergleich zu Blutendothelzellen. Ein
Einfuss von FABP4 auf das Verhalten von Lymphendothelzellen, wie endotheliale Proliferation
und Permeabilität wurde gezeigt. Die verstärkte Expression von FABP4 in Lymphendothelzellen
hebt damit die essentielle Rolle der Lymphgefäße im Rahmen des Lipidtransports und
Fettsäurestoffwechsels hervor.
Schlussfolgerung ‐ Diese Arbeit beleuchtet die Genexpressionsveränderungen von
Lymphendothelzellen der Haut im Rahmen des Typ 2 Diabetes mellitus und zeigt mit welchen
metabolischen Veränderungen diese zu kämpfen haben. Die erhöhte Lymphgefäßdichte ist mit
einer starken Makrophagendichte assoziiert, und es scheint hier eine enge Kommunikation
zwischen diesen Zellen, vor allem mittels der Chemokine CXCL10 und TNFα stattzufinden.
Umgestellt: Zusammenfassend lässt sich sagen, dass es über einen parakrinen Mechanismus zu
einer vermehrten Rekrutierung von Makrophagen in der diabetischen Haut kommt, was zu
chronischer Entzündung und in der Konsequenz zu vermehrter Lymphangiogenese führt.
Dadurch konnten wir zeigen, dass dermale Lymphkapillaren aktiv an den bekannten
Phänomenen der verzögerten Wundheilung und persistierenden Entzündungen im Typ 2
Diabetes beteiligt sind.
V
Contents
ACKNOWLEDGEMENTS 1
SUMMARY 1
ZUSAMMENFASSUNG 3
CONTENTS 5
LIST OF FIGURES 9
LIST OF TABLES 11
ABBREVIATIONS 12
1. AIMS AND RESEARCH OBJECTIVES 1
2. THE LYMPHATIC VASCULAR SYSTEM 3
2.1 Embryonic lymphatic vascular development 4
2.2 Lymphatic vessel anatomy and structure 8
2.3 Molecular markers for lymphatic endothelial cells 9
2.4 Lymphatic vascular function 14
2.5 Perspective 16
3. TYPE 2 DIABETES MELLITUS 17
3.1 Hereditary factors in T2DM 17
3.2 Insulin action and resistance 18
VI
3.3 Role of adipose tissue in insulin resistance and type 2 diabetes mellitus 18
3.4 Vascular complications in diabetes mellitus 20
3.5 Skin symptoms and clinical signs of T2DM 21
3.6 Diagnosis of T2DM 22
3.7 Therapy of T2DM 23
4. LYMPHATIC VESSELS, TYPE 2 DIABETES MELLITUS AND LIPID METABOLISM 25
4.1 Lymph vessel morphology in T2DM 25
4.2 Lymph vessels and inflammation 26
4.3 Lymph vessels with special emphasis on lipid metabolism 27
5. DNA MICROARRAYS 28
5.1 Advantages and problems of using DNA microarrays 28
5.2 Application of the microarray technique in T2DM research 29
6. MATERIAL AND METHODS 31
6.1 Patients and skin samples 31
6.2 Antibodies 32
6.3 Buffers and solutions 33
6.4 Micropreparation of lymphatic endothelial cells from human skin 35
6.9 Sample preparation for microarray experiment 37
6.10 Bioinformatical and statistical analysis 38
6.11 Quantitative Realtime PCR 38
6.12 SDSPAGE and Western Blot 39
6.13 Immunohistochemistry and Immunofluorescence 40
6.14 Evaluation of lymph and blood vessel density and counting of macrophages 40
VII
6.15 Tissue fixation and processing for electron microscopy 41
6.16 Primary Human Dermal Endothelial Cell Culturing 41
6.17 siRNA mediated gene knockdown 42
6.18 LEC Proliferation assay 43
6.19 Protein CoImmunoprecipitation (CoIP) 43
6.20 Chromatin immunoprecipitation (ChIP) 43
6.21 TNFα stimulation of LECs 46
6.22 Scratch wounding assay 46
6.23 Enyzmelinked Immunosorbent Assay (ELISA) 46
6.24 Macrophage adhesion assay 47
6.25 Macrophage transmigration experiment 47
6.26 Agarose spot assay 47
6.27 LEC monolayer permeability assay and TEER measurements 48
6.28 Statistical methods and analysis 48
7. RESULTS AND DISCUSSION 49
7.1 Morphological features of diabetic skin 49 7.1.1 Basement membrane morphology of small blood and lymphatic capillaries in diabetic skin 49 7.1.2 Basement membrane morphology of lymphatic collectors in diabetic skin 53 7.1.3 Increased lymphatic vessel density in the skin of T2DM patients 53 7.1.4 Increased macrophage infiltration in diabetic skin 56 7.1.5 Macrophages produce vascular endothelial growth factors 57 7.1.6 Increased TNFα levels in human diabetic skin 59 7.1.7 TNFα production by CD68+ macrophages 60
7.2 Ex vivo isolation of LECs from human skin 62 7.2.1 Quality control of isolated LECs 62
7.3 Bioinformatical analysis of diabetic versus nondiabetic LEC transcriptomes 67 7.3.1 Identification of deregulated pathways and gene functions using Ingenuity Pathway Analysis 70 7.3.2 Verification of LEC specific genes and comparison with other arrays 84 7.3.3 Diabetic LECs exhibited a distinct gene expression profile compared to diabetic BECs 85 7.3.4 Genes linked to altered lipid transport and metabolism, increased oxidative stress and to the pathogenesis of type 2 diabetes mellitus 87 7.3.5 Identification of a gene signature related to wound healing and tissue repair in dLECs 89 7.3.6 Identification of a gene signature related to increased adhesion of inflammatory cells 91 7.3.7 Deregulated genes associated with cellular host defense 93
7.4 TNFαinduced effects on LEC behavior 96 7.4.1 TNFα responsiveness of LEC genes in vitro 96
VIII
7.4.1 Increased migration of LECs upon TNFα stimulation 99 7.4.2 Macrophage adhesion to LECs is increased by TNFα stimulation 99
7.5 CXC motif chemokine 10 (CXCL10) expression and function in LECs 102 7.5.1 CXCL10 is upregulated and secreted by LECs upon TNFα stimulation 102 7.5.2 CXCL10 mediates macrophage adhesion to LECs 103 7.5.3 CXCL10 induces chemotaxis of macrophages 106 7.5.4 CXCL10 enhances LEC‐transmigration of macrophages 108
7.6 Characterization of Fatty acid binding protein 4 (FABP4) expression and function in LECs 110 7.6.1 FABP4 is specifically expressed in lymphatic endothelial cells 111 7.6.2 FABP4 expression could be specifically knocked down in LECs 112 7.6.3 FABP4 regulates LECs proliferation 113 7.6.4 FABP4 expression increases LEC permeability 114 7.6.5 FABP4 expression regulates PPARγ expression in LECs 114 7.6.6 Possible interactions of FABP4 with PPARγ 115
8. CONCLUSIONS AND FUTURE PERSPECTIVES 118
REFERENCES 124
CURRICULUM VITAE 144
IX
List of Figures Figure 1: Growth of lymphatic vessels in the mammalian embryo: Injection model of
Sabin. 4
Figure 2: Development of the vascular systems. 5
Figure 3: Pathways of how glucotoxicity contributes to diabetic complications in blood vessels.
20
Figure 4: Confirmation of LEC purity used for cell culture experiments. 42
Figure 5: Graphical depiction of the human FABP4 promotor. 45
Figure 6: BM morphology of blood and lymphatic capillaries in human diabetic skin. 50
Figure 7: Laminin expression of diabetic and non‐diabetic LVs and BVs. 51
Figure 8: Collagen IV expression of diabetic and non‐diabetic LVs and BVs. 52
Figure 9: Ultrastructural analysis of LVs. 52
Figure 10: Lymphatic collectors in diabetic skin do not show any morphological changes. 53
Figure 11: LV and BV density in diabetic versus normoglycemic skin. 55
Figure 12: Macrophage infiltration in normoglycemic versus diabetic human skin. 56
Figure 13: VEGF‐C and VEGF‐A expression of infiltratin skin macrophages. 57
Figure 14: Quantitative analysis of VEGF‐C and VEGF‐A production by infiltrating skin
macrophages.
58
Figure 15: TNFα expression in skin. 59
Figure 16: Production of TNFα by macrophages. 60
Figure 17: Fluorescent activated cell sorting of ex vivo isolated LECs and BECs. 63
Figure 18: Exclusion of leukocyte contaminations. 63
Figure 19: Quality control of isolated LECs. 64
Figure 20: Amplification check of RNA isolated from dLECs. 65
Figure 21: Amplification check of RNA isolated from ndLECs. 66
Figure 22: Normalization of microarray chip data. 67
Figure 23: Bioinformatical analysis using Student's t‐test and RVM. 67
Figure 24: Hierarchical cluster analysis. 69
Figure 25: Pathway analysis using IPA. 71
Figure 26: Deregulated cellular functions in dLECs. 71
Figure 27: Confirmation of FABP4, APOD and NOX4 by realtime PCR and 88
X
immunofluorescence.
Figure 28: Confirmation of AQP3, MMP2 and CYR61 expression by realtime PCR and immunofluorescence.
90
Figure 29: Confirmation of VCAM‐1, CXCL10, CXADR and SDC1 expression by realtime PCR and immunofluorescence.
92
Figure 30: Upregulation of CXCL10, VCAM‐1 and CYR61 gene expression of cultured LECs by TNFα stimulation.
97
Figure 31: Downregulation of CXADR, SDC1 and AQP3 gene expression of cultured LECs by TNFα stimulation.
97
Figure 32: Downregulation of FABP4, GALNTL2 and APOD gene expression of cultured LECs by TNFα stimulation.
98
Figure 33: No change of MMP2 and NOX4 gene expression of cultured LECs by TNFα stimulation.
98
Figure 34: Increased migration of LECs after TNFα stimulation. 100
Figure 35: Adhesion of macrophages to primary LECs in vitro. 101
Figure 36: Expression and secretion of CXCL10 in LECs upon TNFα stimulation. 103
Figure 37: CXCL10 is responsible for macrophage adhesion to lymphatic endothelial monolayer.
104
Figure 38: VCAM‐1 is dispensable for macrophage adhesion to lymphatic endothelial monolayer.
105
Figure 39: Secreted CXCL10 is responsible for chemotaxis of macrophages. 107
Figure 41: FABP4 is specifically expressed in LECs compared to BECs. 111
Figure 42: siRNA‐mediated knockdown of FABP4 in LECs. 112
Figure 43: FABP4 regulates LEC proliferation. 113
Figure 44: FABP4 expression is not upregulated by lymphangiogenic factors. 113
Figure 45: FABP4 regulates permeability of LEC monolayers. 114
Figure 46: FABP4 regulates PPARγ expression. 115
Figure 47: Co‐Immunoprecipitations of FABP4 and PPARγ. 116
Figure 48: Chromatin immunoprecipitations of PPARγ. 116
Figure 49: Importance of lymphatic vessels in type 2 diabetic skin and the attempt of establish a model showing their contribution, involvement and alterations in the skin of type 2 diabetic patients.
122
XI
List of Tables
Table 1: Structural differences of blood capillaries, lymphatic capillaris and collecting LVs
9
Table 2: Lymphatic specific genes and their knockouts. 13
Table 3: Clinical data of selected diabetic patients and normoglycemic controls. 32
Table 4: Primary antibodies 33
Table 5: Secondary antibodies 33
Table 6: Primers used for RT‐PCR. 37
Table 7: Taqman gene expression assays used for quantitative real‐time PCR. 39
Table 8: Primers used for qPCR to check binding of PPARγ to FABP4 promotor region. 45
Table 9: Genes associated with most deregulated pathways as evaluated by IPA analysis. 72
Table 10: Genes assciated with most deregulated functions as evaluated by IPA analysis. 73
Table 11: Transcript levels of deregulated candidate genes functionally clustered in (A) Inflammatory Response, (B) LEC Adhesion and Migration, (C) LEC growth and Lymphangiogenesis, and (D) Small Molecule Biochemistry.
78
Table 12: Transcript levels of LEC specific genes. No significant differences could be seen for LEC‐specific genes between diabetic LECs (dLECs) and non‐diabetic LECs (ndLECs).
85
Table 13: Gene overlap of diabetic LECs (dLECs) and diabetic BECs (dBECs) 86
Table 14: Transcript levels of deregulated genes already associated with type 2 diabetes. 88
Table 15: Transcript levels of genes associated with wound healing and tissue repair. 90
Table 16: Transcript levels of genes linked to increased adhesion of inflammatory cells. 91
Table 17: Transcript levels of genes associated with cellular host defense. 95
XII
Abbreviations ANGPT2 Angiopoietin 2 AQP3 Aquaporin 3 APC(s) Antigen presenting cell(s) APOD Apolipoprotein d BEC(s) Blood endothelial cell(s) BM Basement membrane BMI Body mass index BV(s) Blood vessel(s) ChIP Chromatin immunoprecipitation CLEC‐2 C‐type lectin‐like receptor 2 CLEVER‐1 Common lymphatic endothelial and vascular endothelial receptor‐1 Co‐IP Co‐immunoprecipitation CRP C‐reactive protein COUP‐TF II COUP transcription factor 2 CXADR Coxsackie and adenovirus receptor CXCL10 Chemokine (C‐X‐C motif) ligand 10 CYR61 Cysteine rich, angiogenic inducer, 61 DARC Duffy antigen/chemokine receptor DAVID Database for Annotation, Visualization and Integrated Discovery DC(s) Dendritic cell(s) ddH2O Double destilled water dLEC(s) Diabetic lymphatic endothelial cell(s) DM Diabetes mellitus EC(s) Endothelial cell(s) ECM Extracellular matrix ER Endoplasmatic reticulum FABP(s) Fatty acid binding protein(s) FACS Fluorescence activated cell sorting FFAs Free fatty acids FITC Fluorescein isothiocyanate FOXC2 Forkhead box protein C2 FPG Fasting plasma glucose GLUT‐4 Glucose transporter type 4 HA Hyaluronic acid HDMEC(s) Human dermal microvascular endothelial cell(s) HUVEC(s) Human umbilical venous endothelial cell(s) ICAM‐1 Interendothelial cell adhesion molecule 1 IFG Impaired fasting glucose IGT Impaired glucose tolerance IL Interleukin IR Insulin resistance IRS Insulin receptor substrate LEC(s) Lymphatic endothelial cell(s) LN(s) Lymph node(s)
The number of patients suffering from type 2 diabetes mellitus (T2DM) is increasing constantly.
Impairment of wound healing and higher frequence of skin infections are common
complications seen in T2DM patients. These symptoms widely rely on pathological changes of
big and small blood vessels which is called macro‐ and microangiopathy, respectively
(Stehouwer and Schaper, 1996). While endothelial dysfunction of blood vessels (BVs) is a well‐
studied situation in T2DM, research on pathological changes of lymphatic vessels (LVs) has
rarely been done. Complications seen in T2DM seem to be not only caused by BV dysfunction. It
was hypothesized that LVs additionally account for these complications, because LV dysfunction
leads to wound healing defects (Saaristo et al., 2006), local inflammation (Rockson, 2001) and
obesity (Harvey et al., 2005). These are conditions often associated with the diagnosis of T2DM.
However, almost nothing is known about potential morphological, structural and functional
changes of lymphatic endothelial cells (LECs) and LVs in T2DM.
The aim of this thesis project was to perform a comprehensive illustration of the morphological,
structural and molecular changes of LVs and LECs in the skin of T2DM patients. To gain insight
into how T2DM alters the lymphatic vasculature and to elucidate functional implications of LVs
in the pathogenesis of the disease, three major research objectives were addressed:
1) Trace potential structural and morphological changes of LVs in the skin of T2DM patients,
including basement membrane changes, vessel density and signs of inflammation.
2) Perform an ex vivo transcriptomal comparison of diabetic versus nondiabetic LECs
isolated from the skin of four type 2 diabetic and four normoglycemic patients.
3) Identification of deregulated functional gene expression patterns of diabetic LECs and
confirmation of association with the pathogenesis of T2DM by in vitro cell culture assays.
The first issue was addressed by extensive histochemical and electron microscopy analyses to
trace morphological alterations of LVs in T2DM, such as altered composition and thickness of
basement membranes, LV shape or dilation, and changes of vacuolisations or organelles in LECs.
Further, we determined the number of BVs and LVs in the skin of T2DM compared to
2
normoglycemic patients and analyzed whether these morphological differences were associated
with signs of inflammation, e.g. immune cell infiltration.
Secondly, in order to discover cellular processes affected in LVs by T2DM, we performed
microarray analyses of ex vivo isolated LECs from diabetic versus non‐diabetic human skin and
compared their transcriptomal profiles. Extensive bioinformatical pathway analysis and
literature search identified gene expression signatures linking LEC biology with T2DM. These
gene clusters contained well known factors as well as gene candidates that were novel in this
context, and they highlighted the role of LECs in processes related to 'inflammation', 'lipid
metabolism' and 'wound healing' as well as 'lymphangiogenesis'.
Thirdly, strong deregulated candidate genes were selected and confirmed by quantitative real‐
time PCR and immunofluorescent stainings on human diabetic and normoglycemic skin. Among
these, C‐X‐C motif chemokine 10 (CXCL10) and fatty acid binding protein 4 (FABP4), were
selected for further functional characterization. CXCL10 was shown to be a chemotactic factor
for macrophages, contributing to the quite uncharted knowledge about the interaction between
lymphatic endothelium and macrophages. Further, the involvement of FABP4 expression in LEC
proliferation and endothelial monolayer permeability was analyzed.
Conclusively, a comprehensive morphological and molecular characterization of LECs and LVs in
the skin of diabetic versus normoglycemic patients is presented and is, to the thesis author’s
knowledge, the first of this kind. The data implicate that lymphatic vessels play a significant
active role in the skin alterations of type 2 diabetes. It is hoped that by identifying patterns of
dLEC gene expressions, new therapeutic targets for this upcoming worldwide epidemic will
become available.
3
2. The lymphatic vascular system
The lymphatic vascular system represents a network of blind‐ended lymph capillaries and
lymphatic collectors which drain the interstitial fluid and transport it back to the blood
vasculature, thereby maintaining tissue fluid homeostasis. Besides, lymphatic vessels are
important regulators of immune cell trafficking and absorption of dietary fats. The existence of
the lymphatic vascular system is indispensable for life and lymphatic dysfunction in individuals
leads to chronic edema and impaired immune response (Tammela and Alitalo, 2010; Alitalo
2011). The lymphatic vasculature was first described by Gaspare Aselli (Aselli, 1627). In 1902,
Florence Sabin proposed a model of lymphatic vasculature development (Sabin, 1902). She
injected ink into pig embryos and showed that lymphatic endothelial cells (LECs) bud from veins
and form primary lymphatic sacs near the junction of the subclavian and anterior cardinal vein.
From these primary lymphatic sacs, LECs form a primitive lymphatic vessel (LV) system by
endothelial sprouting (see Figure 1) surrounding tissues and organs. The thoracic duct, the main
deliverer of lymph fluid, develops from the cisterna chyli, a dilated sac at the lower end of the
thoracic duct, and remains as a final connection to the blood circulation (van der Putte, 1975).
The Sabin model suggests that the LV system arises from the blood vasculature. In 1910, an
alternative model was proposed by Huntington and McClure (1910) who claimed that the
primary lymph sacs are built in the mesenchyme, and only later venous connections are formed.
At least, this theory is true in birds (Schneider et al., 1999).
Until a few years ago the differentiation between blood vessels (BVs) and LVs within tissues was
merely possible according to morphological and histological criteria, e.g. thinner walls of
lymphatics, no basement membranes (BM) and lack of pericytes. However, uncertainty
remained about distinguishing blood endothelial cells (BECs) from LECs. Especially in the last 10
to 20 years progress in this field accelerated dramatically because of the identification of
lymphatic specific markers like vascular endothelial growth factor receptor 3 (VEGFR3,
Kaipainen et al., 1995), Prospero homeobox protein 1 (PROX1, Wigle and Oliver, 1999),
lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1, Banerji et al., 1999) and
podoplanin (Breiteneder‐Geleff et al., 1999). Along with the discovery of these lymphatic specific
4
markers, it became possible to sort and cultivate primary LECs and BECs in vitro. Still, only few
specific markers for LECs are available and most endothelial cell (EC) markers are expressed on
both, BVs and LVs. This affirms the close structural and developmental relationship between the
two vessel systems.
2.1 Embryonic lymphatic vascular development
Due to the importance of the lymphatic vasculature in physiologic and pathological condition,
the development of LVs has been extensively studied. Embryonic blood vessels originate from
mesodermal cells which give rise to hemangioblasts and angioblasts, the precursor cells of all
endothelial cells (ECs; Figure 2 A). Afterwards, angiogenesis occurs that includes formation and
remodeling of new vessels by endothelial sprouting and splitting. LVs originate from the venous
vascular system. They start to develop in the sixth to seventh embryonic week in humans and at
embryonic day (E) 9.0‐9.5 in mice (Tammela and Alitalo, 2010; Oliver, 2004). Oliver (2004) and
colleagues (Oliver and Srinivasan, 2010) suggested a four stage model of the lymphatic
vasculature development: LEC competence, LEC commitment, LEC specification and LV
differentiation and maturation (Figure 2 B). During these steps certain genes are specifically up‐
and downregulated in LECs, each of them important for these distinct stages of development.
Lymphatic endothelial cell competence and commitment
In order to gain a certain competence, cells become able to respond to an initial inducing signal
(Grainger, 1992). The key step for development of LECs is that venous ECs become responsive to
a lymphatic‐inducing signal. Concerning the developmental competence for embryonic veins, it
is believed that the expression of COUP transcription factor 2 (COUPTF II) is important for
development of the venous vascular system by inhibiting Notch‐signaling, which is required for
Figure 1: Growth of lymphatic vessels in the mammalian embryo: Injection model of Sabin(Sabin, 1902). Lymphatic ducts growing in the three directions (a) and building of lymphatic sacs(b) from which EC are sprouting to form a primary lymphatic capillary system (c).
5
arterial cell differentiation (You et al., 2005). Further, COUPTF II might be involved in the
repression of lymphatic key transcription factor PROX1 to prevent too early LEC differentiation
(Oliver and Srinivasan, 2010). Earlier, it was suggested that the expression of LYVE1 by some
endothelial cells lining the anterior cardinal vein at E 9.0‐9.5 is important for gaining lymphatic
competence (Jurisic and Detmar, 2009; Cueni and Detmar, 2008; Maby‐El Hajjami and Petrova,
2008). However, the lack of a specific lymphatic phenotype in Lyve1 knockout mice voiced the
concern whether it is really crucial for LEC phenotype development (Luong et al., 2009; Gale et
al., 2007).
Figure 2: Development of the vascular systems. Scheme of the main steps of blood andlymphatic vascular development starting from the mesodermal angioblasts, which differentiateinto endothelial cells (A). Stepwise development of the lymphatic vascular system (B); modifiedfrom Oliver and Srinivasan (2010).
6
There are speculations that not LYVE1 alone, but another factor is responsible for the initiation
of this important step in venous endothelial cells. This factor was claimed to be SOX18, a
transcription factor which is an upstream regulator of the lymphatic master regulator PROX1.
SOX18 is expressed in a subpopulation of ECs in the anterior cardinal vein and its loss results in
lack of PROX1 expression and termination of lymphatic development. SOX18 might be
transiently required for lymphatic differentiation as it is detected only up to E 14.5 (Francois et
al., 2008). The signal leading to the expression of SOX18 in endothelial cells is still unknown.
However, after gaining lymphatic competence, the cells are able to form a specific cell type
which is dependent on the inducing tissue (Grainger, 1992). This is called lymphatic
commitment and occurs between E 9.0‐10.5 and is characterized by the expression of PROX1.
PROX1 is only expressed in a subpopulation of ECs in the region anterior of the developing
forelimb of mice (Wigle and Oliver, 1999) and it is the most important regulator to confer and
maintain the LEC phenotype (Tammela and Alitalo, 2010).
Lymphatic specification
Lymphatic specification takes place between E 10.5‐11.5. in mice. After formation of LEC
precursor cells, ECs start to bud from the anterior cardinal vein on E 11.0 to build the primary
lymph sacs. This is stimulated by vascular endothelial growth factor C (VEGFC) which is the
most important lymphangiogenic factor (Kukk et al., 1996) and enhancer of lymphatic sprouting
(Saaristo et al., 2002). During lymphatic specification, additionally to LYVE1 and PROX1, other
lymphatic specific markers, e.g. secondary lymphoid chemokine (SLC), podoplanin, VEGFR3 and
Neuropilin 2 (NRP2), are expressed, whereas typical blood vascular markers like CD34 become
downregulated (Kume, 2010; Tammela and Alitalo, 2010; Wigle and Oliver, 1999).
Lymphatic differentiation and maturation
The final step of LEC development is characterized by differentiation and maturation of LECs.
This last stage lasts several days and is a stepwise process (Oliver and Harvey, 2002; Alitalo
2011). LECs are budding and sprouting from the lymph sacs to form a primitive lymphatic
vasculature. Additional lymphatic markers are expressed, e.g. desmoplakin, β‐chemokine
receptor D6 and angiopoietin 2 (ANGPT2) and NFATC1. Shortly before birth, the whole gamut of
lymphatic specific markers that is found in adult LVs is present (Tammela and Alitalo, 2010). A
recent publication claims that besides the well known factors semaphorin3a‐neuropilin‐1
signaling is additionally required for lymph vessel maturation and valve formation (Jurisic et al.
2012).
7
Separation of blood and lymphatic vessels
Important for the formation of an independent and functional LV system is its complete
separation from the blood vasculature. Several genes have been shown to control the separation
process of LVs from BVs: SRC homology 2‐domain‐containing leukocyte protein of 76 kDa (SLP
76) and tyrosine kinase SYK (Abtahian et al., 2003), phospholipase C2 (PLC2) (Ichise et al.,
2009), O‐glycans (Fu et al., 2008) and podoplanin (Uhrin et al., 2010). Slp76/ and Syk/ mice
exhibit vascular malformations, e.g. arteriovenous shunts, abnormal blood‐lymphatic
connections, haemorrhage and blood filled lymphatics (Abtahian et al., 2003). Similar
phenotypes were observed in mice lacking PLC2 (Ichise et al., 2009) or O‐glycans (Fu et al.,
2008). However, the mechanism leading to these misconnections is not absolutely clear. It is
hypothesized that failed platelet aggregation and thrombi formation in the blood‐lymphatic
connector regions are the reason, due to a failure in signaling between C‐type lectin‐like
receptor 2 (CLEC2), SLP76, SYK and podoplanin. CLEC2‐mediated platelet activation is
dependent on the activity of SYK and SLP76 (Suzuki‐Inoue et al., 2006). Moreover it was shown
that podoplanin is a direct interaction partner of CLEC2 expressed on platelets (Suzuki‐Inoue et
al., 2007). Loss of CLEC2‐podoplanin interaction leads to failed platelet activation and
aggregation. Confirmation of this hypothesis was recently provided by Uhrin et al. (2010) and
Bertozzi et al. (2010) who showed that podoplanin is responsible for activation of platelets via
CLEC2, which results in activation of SLP67, and for subsequent closure of blood‐lymphatic
connections. Another important molecule responsible for separation of the two vascular systems
is T‐synthase, a glycosyltransferase, possibly also by regulating podoplanin expression (Fu et al.,
2008).
Development of lymph nodes
Another important feature of lymphatic development is the formation of lymph nodes (LNs)
which begins at around E 12.5 in mice when connective tissue protrudes into lymph sacs.
Incipient clusters of cells were shown to express interleukin‐7‐receptor‐α (IL7Rα) and to be
positive for CD4 and CD45, but negative for CD3 (Mebius, 2003). Via IL7Rα signaling, expression
of lymphotoxin‐α1β2 is induced which is necessary for lymphoid neoangiogenesis. Crucial for
formation of LNs is not only the clustering of CD45+CD4+CD3‐‐cells but also the expression of
adhesion molecules like vascular endothelial growth factor‐1 (VCAM1) which keeps incoming
cells in place for their interaction with hematopoietic and stromal cells. Chemokines expressed
and necessary for the development of LNs are CCL19, CCL21, CXCL12 and CXCL13 (Tammela and
Alitalo, 2010; Mebius, 2003).
8
2.2 Lymphatic vessel anatomy and structure
There are mainly five different compartments of the lymphatic vasculature system: lymphatic
capillaries, lymphatic collectors, lymph nodes, lymphatic trunks and lymphatic ducts, having
diameters ranging between 10µm and 2 mm (Rovenská and Rovenský, 2011; Swartz, 2001). The
LV system starts in the periphery with blind‐ended and thin‐walled lymph capillaries. They have
a diameter of 10‐50µm. The lymph capillaries build a network, the so‐called lymphatic areolas
which finally assemble to bigger collecting LVs. These collecting vessels then assemble to mainly
five main lymphatic trunks: the lumbal, the intestinal, the bronchomediastinal, the subclavian
and the jugular trunk. These trunks in turn pass the lymph into the right and the left thoracic
ducts.
The main LV is the left thoracic duct which drains the lymph fluid from the whole body, except
the upper right body region, and transports it back to the blood vasculature via the left
subclavian vein. The right thoracic duct drains lymph from the upper right body region into the
right subclavian vein (Jeltsch et al., 2003; Fritsch and Kühnel, 2001). Except these two sites
where lymph enters the blood, no connections between the blood and the lymph vascular
system exist. The two vascular systems rather run in parallel and in close proximity to each
other. Along its way, lymph is filtered by passing through LNs where foreign antigens are taken
up and presented by antigen‐presenting cells (APCs) to initiate a specific immune reaction.
Besides, LNs are sites of immigration and reservoir for white blood cells and tumor cells which
gain access to the blood vasculature via high endothelial venules (Swartz and Skobe, 2001).
Lymphatic capillaries, blood capillaries and bigger collecting LVs dispose of eminent structural
differences (summarized in Table 1). In contrast to blood capillaries with narrow and regular
lumina, LVs normally have wide and irregular lumina. The wall of lymphatic capillaries is formed
by a single layer of non‐fenestrated ECs with an incomplete or absent BM (Leak, 1970; Leak and
Burke, 1968, 1966). Small LVs are not covered by pericytes and do not have valves (Alitalo et al.,
2005). Because a BM is mostly absent from lymphatic capillaries, LECs are directly attached to
the extracellular matrix (ECM) with elastic anchoring filaments to prevent collapse of vessels
due to high interstitial pressure. These anchoring filaments, 6‐10nm in diameter, are composed
of emilin‐1 and fibrillin (Danussi et al., 2008; Gerli et al., 2000) and tether the LECs to collagen
fibers (Leak and Burke, 1968, 1966). Lymphatic capillaries show overlapping ECs which build
valve‐like opening structures and hence regulate permeability for interstitial fluid (Trzewik et
al., 2001). The lack of interendothelial tight junctions also contributes to their increased
permeability compared to blood capillaries. Pre‐collecting and collecting lymph vessels are
characterized by a smooth muscle cell (SMC) layer, interendothelial tight junctions and bileaflet
valves (Alitalo et al., 2005). The contractility of the SMCs is important to propulse lymph,
whereas the valves prevent its backflow (Tammela and Alitalo, 2010). The distance between two
9
valves is called the lymphangion (Jeltsch et al., 2003), each of which is a contractile compartment
pumping lymph into the next one. Important proteins for valve formation are integrin α9
(Bazigou et al., 2009) and FOXC2 (Norrmén et al., 2009; Petrova et al., 2004). In functional LVs,
which have separated regularly from BVs, no blood can be found intraluminally.
Blood Present Usually absent Usually absentPericytes Present Absent Present
Table 1: Structural differences of blood capillaries, lymphatic capillaris and collecting LVs: based on data from Tammela et al. (2005b), Nathanson (2003), Schmid‐Schönbein (1990) and Gnepp and Green (1979).
2.3 Molecular markers for lymphatic endothelial cells
LECs exhibit a panel of specific markers which are not expressed in BECs. Some EC markers are
expressed on both cell types, e.g. CD31 (PECAM1; platelet and endothelial cell adhesion molecule
1) and vascular endothelial (VE)‐cadherin. Others, like pathologische anatomie Leiden‐
endothelium (PALE) and endoglyx‐1 are only expressed on BECs (Wilting et al., 2002; Christian
et al., 2001). Many studies aimed at characterizing differential gene expression in BECs versus
LECs using transcriptomal and proteomic approaches (Podgrabinska et al., 2002; Hirakawa et
al., 2003; Wick et al., 2007; Roesli et al., 2008), as well as phage display technique (Keller T.M.,
unpublished). Due to the identification of specific lymphatic markers, research in this field
accelerated dramatically in the last 20 years. Table 2 shows a summary of all important
lymphatic specific genes including lymphatic phenotypes in murine gene knockout models. The
four main lymphatic specific markers LYVE1, PROX1, Podoplanin and VEGFR3 are described in
Microangiopathy No No No No Hypertension No No No Yes
Antihypertensive therapy
No No No Yes
Indication for operation
Cutis laxa abdominis
Cutis laxa abdominis Trauma Ulcus cruris
Table 3: Clinical data of selected diabetic patients and normoglycemic controls. HbA1c: glycated hemoglobin, BMI: body mass index, PAOD: peripheral artery occlusive disease.
6.2 Antibodies The following antibodies were used in immunohistochemistry, FACS and Western blotting:
0.05 ml 10% SDS (Sodium dodecyl sulfate; no. 161‐0302, Biorad)
0.05 ml 10% APS (Ammonium persulfate; no. 161‐0700, Biorad)
0.005 ml TEMED (N,N,N,N'‐Tetra‐methyl‐ethylenediamine; no. 161‐0800, Biorad)
Electrophoresis buffer: 10 l
144 g Glycine (no. 161‐0718, Biorad)
30g Tris (Tris‐hydroxymethyl‐aminomethan; no. 1.08382.1000, Merck)
50 ml 20% SDS (Sodium dodecyl sulfate; no. 161‐0302, Biorad)
up to 10 l with Aqua bidestillata
Transfer buffer: 10 l
24.58 g Tris (Tris‐hydroxymethyl‐aminomethan; no. 1.08382.1000, Merck)
112.08 g Glycine (no. 161‐0718, Biorad)
2 l Methanol (no. M/4000/17, Fisher Scientific)
TrisBuffered Saline Tween20 (TBST):
6.1 g (50mM) Tris
9 g (150mM) NaCl
up to 1000 ml with Aqua bidestillata
500µl Tween‐20
35
6.4 Micropreparation of lymphatic endothelial cells from human skin Ex vivo isolation of ECs from human skin of diabetic patients and normoglycemic controls was
performed according to a combined enzymatic‐mechanical protocol as previously described
(Wick et al., 2008, 2007; Kriehuber et al., 2001). The whole procedure was conducted on ice.
Around 6‐8 hours after surgical amputation, approximately a ten to ten centimeter piece of skin
was removed and immediately put on ice onto a NIROSTA plate, disinfected with 70% alcohol.
Excessive subcutaneous fat was removed and skin was cut into 2 cm wide stripes for easier
handling. Thereafter, skin was dermatomized with a clamp and a dermatome with a sterile blade
mounted (E.Weck%CO; 10 mm). The dermatomized skin was collected in ice‐cold Iscove's
Modified Dulbecco's Medium (IMDM, InvitrogenTM, no. 21056‐023) and washed several times
with fresh IMDM on a shaker to remove excessive blood and fat. In the meantime, Dispase I
(Roche Applied Science, 10 x 2 mg sterile, no. 04942086001) was reconstituted in 1 ml of aqua
bidestillata (Abd) and further diluted with pre‐warmed PBS (cell culture grade, free of Ca2+ and
Mg2+) to obtain a final concentration of the enzyme of 0.6‐2.4 U/ml. The skin was put into 10 cm
dishes with its epidermal side up and covered with a sterile NIROSTA grid and the Dispase I
solution. The dishes were incubated for at least 60 minutes in an incubator at 37°C/5% C02. The
enzymatic reaction was stopped with pre‐warmed IMDM/10% FCS/1% 500mM EDTA solution.
After 60 minutes, the dermis could be easily removed from the epidermis using two tweezers.
The dermal sheets were put into 10cm dishes containing ice‐cold EBM‐2 medium supplemented
with 5% fetal serum and EGM‐2‐MV SingleQuots R (CC‐4147; Lonza). Thereafter, ECs were
released from the dermal sheets by scraping with an inverted scalpel until the skin fragments
were disaggregated. Released cells were sieved with a cell strainer (70µm pore size, BD
FalconTM, Bedford, USA, no. 352350) positioned on 50 ml tubes. The expected cell loss within
the sieving process was 10‐15%. Released and sieved cells were pelleted at 4°C at 1600 rpm (in
443g) for 8 minutes and resuspended in 20 ml ice‐cold PBS/2%BSA/1mM EDTA and sieved
again.
6.5 Cell staining procedure for subsequent fluorescent activated cell sorting The isolated single cells were stained with antibodies directed to CD45, CD31 and podoplanin.
Cell staining was performed to sort EC populations into LECs (CD31+PDPN+) and BECs
(CD31+PDPN‐) and to exclude contaminations with CD45+ cells, e.g. leukocytes and fibroblasts.
The antibodies were diluted in PBS/2%BSA/1mM EDTA, and incubated for 20 minutes in the
dark. After sieving through a cell strainer, cells were spun down again at 1600 rpm (443g) for 8
minutes, resuspended in 1100µl PBS/2%BSA/1mM EDTA and transferred into micronic tubes
36
for subsequent cell staining. 100µl of cells were used for antibody isotype control staining (tube
B) and transferred into a separate micronic tube. The rest of the cells represented the vast
majority of the cells and the definite sample (tube A).
A three‐step staining procedure was performed with intermediate washing steps and
centrifugation of cells at 1600 rpm for 8 minutes in between:
Fermentas Life Sciences), a 3‐color ladder with a mixture of 10 proteins covering a molecular
weight range from 10 to 170 kDa (5µl/well) was used as marker. The gels were run at 120V for
the first 30 minutes and then with 160V until the sample buffer front left the gel. Protein blotting
was done overnight at 24V using nitrocellulose transfer membranes (BA83, Whatman Protran).
Afterwards, the nitrocellulose membrane was dried between 30 minutes and overnight and
blocked with 5% milk powder in TBS‐T. The membrane was washed three times for 10 minutes
in TBS‐T buffer at room temperature (RT) and incubated with indicated antibodies in TBS‐
T/5%BSA for 1 hour at RT or overnight at 4°C (depending on the antibody used). After first
antibody hybridization, the membrane was washed three times for 10 minutes in TBS‐T buffer
and incubated with HRP‐conjugated secondary antibodies for 1 additional hour. Afterwards, the
membrane was washed for 1 hour to reduce background as much as possible. For detecting the
chemoluminescent signal, ECL plus (GE) was used. Exposure times varied between 30 seconds
and 10 minutes depending on the intensity of the signal. Densitometric evaluation was
performed with the LumiImager software.
40
6.13 Immunohistochemistry and Immunofluorescence Human skin was fixed in 4% paraformaldehyde at room temperature or in 20% sucrose at 4°C
overnight for embedding in paraffin or geltol, respectively. For deparaffinization, 2‐5µm sections
were incubated at 60°C for 30 minutes or overnight, subsequently dewaxed in xylene and
rehydrated in a series of descending concentrations of ethanol (100%, 96%, 70%, 50% and
water) to completely remove the paraffin. Antigen retrieval was performed in an autoclave for
60 minutes or in a microwave (600 W, 3 x 5 minutes) in 10mM citrate buffer, pH 6. In the case of
frozen sections, 5µm were cut using a cryotome and used immediately or stored at ‐20 to ‐80°C.
For immunostaining, sections were thawed, dried at room temperature for 10 minutes and fixed
in ice‐cold acetone or 1% paraformaldehyde (PFA) for 20 minutes. Thereafter, the individual
staining procedure was started. Blocking of sections was performed for 20 minutes at room
temperature with 10% goat or donkey serum. Afterwards sections were washed shortly in PBS
and first antibody solution was added. Depending on the first antibody, incubation was done for
1 hour at RT or overnight at 4°C. Next, the sections were washed 3 times 5 minutes in PBS and
secondary antibody dilution was applied. For fluorescence microscopy, fluorescently labeled
secondary antibodies were used. Immunohistochemical stainings were performed by using
either Avidin Biotin Complex (ABC), Alkaline Phosphatase (AP) or Horseradish Peroxidase
(HRP) staining according to standard protocols. Pictures were taken with a VANOX AHBT3
microscope (Olympus) or a laser scanning microscope (LSM 5 Exciter, Zeiss).
6.14 Evaluation of lymph and blood vessel density and counting of macrophages In order to quantify the number of BVs and LVs in skin samples of T2D and normoglycemic
patients, 5µm sections were immunostained with anti‐Duffy antigen/receptor for chemokines
(DARC) and anti‐podoplanin antibodies for visualization of BVs and LVs, respectively. The
number of CD68‐positive macrophages was determined in the dermis of four diabetic and four
non‐diabetic patients by staining with mouse anti‐human CD68 antibody (DAKO Cytomation; no.
M0876). Non‐overlapping fields were captured with an Olympus VANOX AHBT3 microscope at
200x magnification and the number of vessels was counted per medium power field, the number
of CD68‐positive cells was counted per 100µm2. Mean numbers of vessels/macrophages were
calculated per group of patients and the significance of difference was evaluated using paired
Student's t‐test.
41
6.15 Tissue fixation and processing for electron microscopy Dermatomized skin was cut into 1mm2 small pieces and fixed in 4% paraformaldehyde + 0.1%
glutaraldehyde in 0.1 M cacodylate buffer for 24 to 72 hours. Thereafter, skin was washed in
cacodylate buffer 2 times for 10 minutes and contrasted using osmium tetroxide for 2 hours.
After washing in aqua bidestillata and dehydrating in a series of ascending concentrations of
ethanol (70%, 80%, 96%, 100%) the skin was put into 100% propylenoxide for 10‐15 minutes
(twice) and into a 1:1 solution of propylenoxide and embedding medium EPON 812 for
additional 60 minutes. Afterwards, skin was put into pure EPON812 overnight. On the next day,
tissue was poured into fresh resin and this was polymerized at 60°C for two to three days.
Ultrathin sections (80nm) were cut using a Reichert‐Jung Ultracut E Mikrotom and collected on a
copper grid. The grids were stained with uranyl acetate/methanol and lead citrate. Pictures
were taken at different magnifications using a transmission electron microscope (JEOL 1010).
6.16 Primary Human Dermal Endothelial Cell Culturing Human dermal microvascular endothelial cells (HDMECs) were purchased from Promocell (no.
C‐12260). Pure LEC populations were obtained by magnetic bead sorting using the rabbit anti‐
podoplanin antibody. LEC purity was checked by Western blotting for the presence of
podoplanin and CD31 and for the negativity of CD146 as BEC specific marker (Amatschek et al.,
2007). Further, nuclear PROX‐1 as well as podoplanin expression was confirmed by
immunofluorescence stainings on LECs (see Figure 4). Cells were grown in endothelial basal
medium (EBM‐2) supplemented with 5% fetal serum and EGM‐2‐MV SingleQuots (CC‐4147;
Lonza) in an incubator at 37°C and 5% CO2. For all cell culture experiments, LECs were used
between passages 5‐8 and starved overnight in EBM‐2/0.5% FCS, unless otherwise indicated.
42
6.17 siRNA mediated gene knockdown siRNA transfection of LECs was done by using RNAiFect (Qiagen, no. 301605) in 24 well plates.
5*104 LECs were seeded the day before transfection in EGM‐2MV medium containing serum and
antibiotics and incubated at 37°C and 5% CO2. 20 µmol of siRNA (FABP4: nos. s4964 and s4965;
PPARg: nos. s10887 and s10888 from Ambion) was diluted in the appropriate volume of Buffer
EC‐R (supplied within the kit) to give a final volume of 100µl. 6 µl of RNAiFect were added and
samples were incubated for 15 minutes at room temperature to induce complex formation.
300µl of fresh EGM‐2MV medium and 100µl of the complexes were added to the adherent cells.
Medium was replaced after 6 hours to avoid cell toxicity by the transfection reagent. Gene
silencing was monitored after 48 hours using western blot analysis.
Figure 4: Confirmation of LEC purity used for cell culture experiments. Purity of LECs wasconfirmed by western blotting by checking the presence of podoplanin and CD31 and the absenceof CD146. Immunofluorescence double staining with the lymphatic specific markers podoplaninand PROX‐1 and CD31 further confirmed the purity of LECs in vitro.
43
6.18 LEC Proliferation assay 2*104 cells of scrambled or FABP4‐specific siRNA‐transfected LECs were seeded into 24‐well
plates with EGM‐2MV medium. The number of cells was counted every 48 hours and plotted as a
line diagram against time on the y‐axis using Microsoft®Excel 2003.
6.19 Protein CoImmunoprecipitation (CoIP) To show a direct interaction of FABP4 with PPARγ in LECs, co‐immunoprecipitations were
performed using the ProFoundTM Mammalian Co‐Immunoprecipitation Kit (no. 26149, Pierce)
according to the manufacturer's instructions. Both antibodies against FABP4 and PPARγ were
examined for the ability to pull down the antigen together with the other protein. LECs were
stimulated with 20µM rosiglitazone (no. 350‐125‐M025; Enzo Life Sciences) for 24 hours prior
to cell lysis in order to enhance PPARg levels. For immobilization of antibody, 50µg of either
FABP4 or PPAR was coupled to the AminoLink® Plus Coupling Resin. LECs were lyzed with IP
Lysis Buffer (0.5% Triton‐X100 in PBS, 10% protease inhibitor). Lysates were pulled through a
syringe with a 22‐gauge needle, put on the resin and gently mixed overnight at 4°C. The day
after, co‐immunoprecipitates were eluted using 50µl of Elution Buffer (supplemented with 5µl
1M Tris‐HCl pH 9.5) provided within the kit. Eluates were concentrated using centrifugal filter
units (Amicon Ultra ‐ 0.5ml 10k Ultracel®, no. UFC501024, Millipore). 30µl of eluates were
mixed with 6µl of 6x Laemmli sample buffer and applied to the gel for SDS‐PAGE analysis. For
long time storage of resin, 200 µl of 1X Coupling Buffer plus 0.02% sodium azide was added to
the spin columns, which then can be reused up to 10 times.
6.20 Chromatin immunoprecipitation (ChIP) To study activation of the FABP4 promotor by PPARγ ChIP was performed as previously
described (Gal‐Yam et al., 2008).
Cell culturing and antibody coupling:
LECs were seeded into 14 cm dishes, grown to confluence and stimulated with or without 20µM
rosiglitazone for 24 hours. The day before cell harvesting, sheep anti‐mouse IgG magnetic beads
(Dynabeads R M‐280, no. 112.01D, Invitrogen) were washed three times and resuspended with
1 ml of PBS‐BSA (bovine albumin serum, no. A7030, Sigma, 5mg/ml). Beads were incubated with
8µg/ml of anti‐PPARγ antibody (no. ab41928, Abcam) or mouse IgG (ChromPure mouse IgG,
whole molecule; no. 015‐000‐003, JacksonImmunoResearch) overnight at 4°C at 10 rpm.
44
DNA‐protein crosslinking and chromatin isolation:
Confluent cells were collected in EGM‐2MV, pelleted at 1600 rpm for 5 minutes, resuspended in
5 ml EGM‐2MV/1% formaldehyde (no. 47608, Sigma) for DNA‐protein crosslinking and
incubated for 10‐15 minutes. Cells were quenched with 1.37 M glycine for 5 minutes, washed
with 10ml of ice‐cold PBS plus 1% protease inhibitors (complete EDTA‐free, no. 11873580001,
Roche) and centrifuged for 5 minutes at 1600 rpm. Pellet was lyzed in 1ml SDS lysis buffer (1%
SDS, 10mM EDTA, 50mM Tris‐HCl (pH 8.1)) plus 1% protease inhibitors and put on ice for 10
minutes. Chromatin was sonicated 10 seconds for 25 times (100%, continuous, low) and
checked by gel electrophoresis. Therefore, 20µl of chromatin was filled up with H2O, 10µl 5M
NaCl was added and boiled for 15 minutes at 95°C. RNA was digested by adding 1µl RNAse
(DNAse free) and incubation for 30 minutes at 37°C, proteins were digested by adding 1µl
proteinase K (10mg/ml) and incubation for 20 minutes at 45°C. Chromatin was centrifuged at
full speed for 1 minute, supernatant was collected and DNA was purified using a QIAquick
column (Qiagen PCR Purification Kit, no. 28106). DNA concentration was measured by
Nanodrop 2000 (Thermo Scientific) and 2µg of DNA was loaded onto a 2% agarose gel to check
for the size of DNA‐fragments, which should be between 500 and 1000 base pairs for IP
experiments.
Chromatin immunoprecipitation and PCR analysis:
30µg of chromatin was used for IP and diluted 10‐fold with IP dilution buffer (0.01% SDS, 1.1%
Triton X 100, 1.2 mM EDTA, 16.7 mM Tris‐HCl (pH 8.1), 167 mM NaCl) up to 2ml. 80µl of
prepared beads coupled with anti‐PPARγ antibody were added and incubated overnight at 4°C
(10 rpm). On the following day, beads were washed 5 times with 1 ml RIPA buffer (50mM
Table 8: Primers used for qPCR to check binding of PPARγ to FABP4 promotor region.
The following temperature protocol was used. Step 2, 3 and 4 were repeated 40 times with
intermediate plate reading. The annealing temperature for the primer pairs FABP4‐1, FABP4‐5
and FABP4‐6 was 59.8°C, for FABP4‐2, FABP4‐3 and FABP4‐4 61.8°C:
1) 95°C ‐ 00:03:00
2) 95°C ‐ 00:00:03
3) 59.8°C or 61.8°C ‐ 00:00:30
4) 72°C ‐ 00:00:01
Figure 5: Graphical depiction of the human FABP4 promotor. Forward and reverse primers are labeled red. Restriction sites of different restriction enzymes are labeled black. PPARresponsive elements (PPREs) and CCAAT‐enhancer‐binding proteins (C/EBP) binding sites are labeled green.
46
6.21 TNFα stimulation of LECs In order to analyze the gene expression responsiveness of LECs to TNFα, cells were starved
overnight in EBM‐2/0.5% FCS and stimulated with or without 1, 10 and 20 ng/ml of TNFα (R&D;
no. 210‐TA‐010) for 6, 12 and 24 hours. In neutralization experiments, LECs were cultured in
EBM‐2/0.5% FCS containing 10 ng/ml TNFα with or without 25µg/ml TNFα antibody (Abcam;
no. ab6671). Altered gene expressions induced by TNFα were checked using subsequent
quantitative real‐time PCR and Western blotting.
6.22 Scratch wounding assay In order to check whether TNFα has an influence on wound closure of LEC monolayers and
therefore also migration of LECs, we starved and stimulated LECs with or without 10ng/ml of
TNFα for 24 hours. Thereafter, an artificial wound was created using a 200µl pipette tip. Non‐
adherent cells were washed away and wound closure was monitored with an inverted live cell
microscope (AxioVert 200M, Zeiss) by taking pictures of the same section every hour for 24
hours. Wound area was measured using AxioVision 4.7 and calculated as amount of wound
closure (in %) from timepoint t=0.
6.23 Enyzmelinked Immunosorbent Assay (ELISA) Supernatants of stimulated LECs were collected and concentrated 20‐fold from 2 ml to
approximately 100µl using centrifugal filter units (Amicon Ultra ‐ 0.5ml 10k Ultracel R, no.
UFC501024, Millipore). 80µl of supernatants were used for coating of 96‐well ELISA plates
overnight and checked for the secretion of CXCL10. Primary anti‐CXCL10 antibody (no. AF‐266‐
NA, R&D Systems) was diluted 1:200 in PBS/1%BSA and 100µl was added to each well. After
incubation for 2 hours at room temperature, the plate was washed three times with 300µl
PBS/0.1% tween‐20 and 100µl of secondary antibody (diluted 1:3500 in PBS) was pipetted to
each well. Secondary antibody solution was incubated for an additional hour at room
temperature. Thereafter, plate was washed and 50µl of substrate solution (3,3',5,5'‐
Tetramethylbenzidine Liquid Substrate, no. T4444, Sigma) was added and incubated for 20
minutes under light protection. The reaction was stopped using Stop Reagent for TMB Substrate
(no. S5814, Sigma). The color development was read at 450nm in a microtiter plate reader
(Synergy HT; Bio‐Tek) within 10 minutes.
47
6.24 Macrophage adhesion assay 5*104 LECs were seeded into 24 well plates, starved overnight in EBM‐2/0.5% FCS and
stimulated with or without 10 ng/ml TNFα for 24 hours. Additionally, LECs were pre‐incubated
with inhibitory antibodies to CXCL10 (no. AF‐266‐NA, R&D Systems) and VCAM‐1 (no. 1244,
Immunotech). THP‐1 macrophages were grown in RPMI‐1640 medium containing 10% FCS (no.
10108, Gibco) and 1% Pen/Strep (no. 15140, Gibco). Before addition to LEC monolayer, THP‐1
macrophages were labeled using Cell trackerTM green CMFDA (1:5000, no. C2925, Invitrogen,
10ng/ml PMA) were diluted in 500µl EBM‐2/0.5% FCS and added to the upper chamber.
Fluorescence of transmigrated macrophages was measured in the lower chamber at 1, 3 and 6
hours using a fluorescence plate reader (485‐530nm; Synergy HT, Bio‐Tek).
6.26 Agarose spot assay Wiggins and Rappoport (2010) presented a novel chemotaxis assay based on the invasion of
cells into agarose spots containing chemoattractants. Due to the fact that CXCL10 is secreted by
LECs upon TNFα stimulation, we wanted to know if supernatants containing CXCL10 are
chemotactic for THP‐1 macrophages. Therefore, we applied this assay to our needs. 4% Agarose
solution (no. 18300‐012, Gibco) was shortly boiled and diluted in PBS to obtain a 1% agarose
solution. Thereafter, 20µl of agarose solution was mixed with 20µl of cell culture supernatants,
which was previously concentrated (see above). Two 10 µl‐spots of agarose‐supernatant
solution were pipetted in each well of a 24‐well plate and allowed to cool for 10 minutes at 4°C.
THP‐1 macrophages were labeled using Cell trackerTM green CMFDA (1:5000, no. C2925,
48
Invitrogen, Molecular probes), diluted in RPMI1640/0.5%FCS/1% Pen/Strep, stimulated with
10ng/ml PMA and 500.000 cells were added to each well of the 24‐well plate. After 24 and 48
hours, pictures were taken with an inverted live cell microscope (AxioVert 200M, Zeiss).
6.27 LEC monolayer permeability assay and TEER measurements 2*104 LECs were seeded onto fibronectin coated transwell filters (no. 3421, Costar) and grown
to confluence. Then, cells were starved overnight in EBM‐2/0.5% FCS and 150µl FITC‐dextran
solution (10µg/ml; no. FD70S‐100MG, Sigma) was applied to the upper and 500µl of medium to
the lower chamber. Diffused FITC‐dextran was measured spectroscopically in the lower
chamber at λ=485‐530nm using a fluorescence plate reader (Synergy HT, Bio‐Tek).
Transendothelial electric resistance (TEER) measurements were done using Millicell®‐ERS
electrode (Millipore). Resistance was measured in triplicates and calculated as per cm2 of
transwell filters. Transwell filters without LECs were used as background control and fresh
medium was added to the wells prior to each measurement.
6.28 Statistical methods and analysis Evaluation and compilation of data was carried out by using Microsoft Office Excel® 2003.
Significance was assessed using Student’s T‐Tests after determination of the variance equality
using an F‐Test. Graphics were made using Adobe Illustrator CS3. A p‐value of < 0.05 was
considered as statistically significant. * indicates a p‐value < 0.05, ** indicates a p‐value < 0.01,
*** indicates a p‐value < 0.001.
49
7. Results and Discussion
7.1 Morphological features of diabetic skin
Changes of vessel morphology and structure in T2DM have been reported earlier, especially for
BVs. These include BM thickening due to increased expression and deposition of ECM proteins.
Moreover, important features of tissue morphology in diabetic skin include changes in BV and
LV density as well as associated signs of inflammation.
In the first part of my thesis, I performed an extensive histological examination of dermal
lymphatic capillaries in T2DM skin specimens to trace potential morphological alterations.
7.1.1 Basement membrane morphology of small blood and lymphatic capillaries in diabetic skin
BM thickening is a common well described feature of diabetic BVs. Expression and deposition of
ECM proteins like type IV collagen and laminin is generally increased in DM (Asselot‐Chapel et
al., 1996; Roy et al., 1994, 1996). Around physiological normal LVs, ECM protein expression and
deposition is generally low and, if present, LVs show no regular continuous BM, but a rather
fragmented BM‐like structure (see also section 2.1.4, Vainionpää et al., 2007; Petrova et al.,
2002; Podgrabinska et al., 2002). Especially, the expression of some laminins was shown to be
completely absent from LECs (Vainionpää et al., 2007; Wigle et al., 2002). In order to take a
closer look at potential BM alterations of skin lymphatic capillaries in T2DM, we co‐stained
paraffin sections of human skin of T2DM and normoglycemic patients with the routinely used
Periodic acid‐Schiff (PAS) stain that labels the glycoproteins forming the BM, together with an
anti‐podoplanin antibody. Figure 6 A shows the onionskinned‐like thickening of BM in BVs of
human diabetic skin (black arrow) compared to normoglycemic skin, while LVs were PAS‐
negative both in diabetic and normoglycemic condition (black arrowheads). By staining
consecutive sections of diabetic skin with antibodies directed against podoplanin and smooth
muscle actin (SMA), lymphatic capillaries were identified due to their negativity for smooth
muscle actin (Figure 6 B; Tammela et al., 2005b). Next, we stained frozen sections of human skin
with anti‐laminin antibody to visualize eventual deposition alterations of this ECM protein
(Figure 7). This staining showed a more prominent deposition of laminin in diabetic (Figure 7 A)
50
compared to non‐diabetic BVs (Figure 7 D), whereas laminin was neither expressed in diabetic
(Figure 7 B) nor in non‐diabetic human skin LVs (Figure 7 E).
Moreover, double labeling with antibodies to podoplanin and collagen IV showed similar
amounts of collagen IV expression by both, LVs and BVs, indicating no significant expression
difference between diabetic (Figure 8 A‐C) and normoglycemic skin (Figure 8 D‐F).
Additionally, we performed ultrastructural analysis of LVs using electron microscopy, which
Figure 6: BM morphology of blood and lymphatic capillaries in human diabetic skin. A:Double labeling with PAS and anti‐podoplanin antibody shows thickening of BM of diabetic BVs(black arrow) but PAS negativity for LVs in diabetic and normoglycemic skin (blackarrowheads). B: Staining of consecutive sections of diabetic skin identified SMA‐negative, butpodoplanin‐positive vessels as a lymphatic capillary; Size bar: 20µm.
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visualizes cellular alterations like membrane and organelle changes at high resolution.
Longitudinal pictures from the LVs confirmed that there are no obvious morphological changes
of lymphatic capillaries in diabetic versus normoglycemic skin and that LVs of diabetic skin do
not dispose of a BM lining (Figure 9). Vielleicht auch noch erwähnen: we did not trace luminal
expansions of LVs or LEC vacuolisations with this detailed technique, indicating no grave lymph‐
edematous condition in the skin specimens.
To conclude, in contrast to early observations tracing modifications of lymphatic vessel basal
lamina in T2DM (Ohkuma, 1979) and aberrant lymphatic vessels newly grown in carcinomas
(Vainionpää et al., 2007), we could not detect laminin and type IV collagen expression in T2DM.
Figure 7: Laminin expression of diabetic and nondiabetic LVs and BVs. A‐F: Double labeling with antibodies against laminin (A, D) and podoplanin (B, E); Merged images: C, F; Upper panel: diabetic skin, lower panel: normoglycemic skin; Size bar: 20µm.
52
Figure 9: Ultrastructural analysis of LVs. Electron microscopy of LVs of diabetic and normoglycemic skin revealed no changes in LEC morphology, e.g. appearance of BM; Lu: vessel lumen; Stars mark endothelial cell layer; Magnification: 10.000x.
Figure 8: Collagen IV expression of diabetic and nondiabetic LVs and BVs. AF:Double labeling with antibodies against collagen IV (A, D) and podoplanin (B, E) to showcollagen IV positive LVs in diabetic (upper panel) and normoglycemic skin (lower panel).Size bar: 20µm.
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7.1.2 Basement membrane morphology of lymphatic collectors in diabetic skin
In contrast to lymphatic capillaries, the larger collecting LVs are characterized by the presence of
a BM and smooth muscle cell layers (Tammela et al., 2005b). We identified smooth muscle actin
(SMA)‐positive LVs with PAS in order to show whether they are altered in the diabetic condition.
However, similar to lymphatic capillaries, lymphatic collecting vessels did not show any
dramatic BM changes, as it is observed for diabetic BVs (Figure 10).
Overall, from these histological data we conclude that there are neither prominent alterations in
ECM protein deposition, nor morphological BM changes of lymphatic capillaries and collecting
LVs in the skin of T2DM patients. This finding is in contrast to reports by Ohkuma (1979) and
Kaufmann et al. (1980), where histochemical and ultrastructural changes of LVs were described
in the skin of patients with T2DM, namely thickening of BM, dilatations of intracellular spaces
and dislocation of the lymphatic endothelium. All of these changes were accepted as proof for a
diabetic lymphangiopathy. However, it is questionable if the described changes can be attributed
to LVs, as BVs and LVs could not be distinguished at that time due to the lack of specific markers
for lymphatic vessels.
7.1.3 Increased lymphatic vessel density in the skin of T2DM patients
However, the density of dermal capillaries itself might be an indicator of pathologic vessel
alterations, as it was described in lymphedema or acute inflammation (Seyama et al., 2010;
Kerjaschki et al., 2004). Hence, we quantified the density of LVs and BVs in the skin of diabetic
versus normoglycemic patients by immunostaining of paraffin sections using antibodies against
DARC to visualize BVs (Wick et al., 2008) and podoplanin for the detection of LVs (Breiteneder‐
Figure 10: Lymphatic collectors in diabetic skin do not show any morphological changes. A: Labeling of diabetic skin with PAS and anti‐podoplanin antibody; B: Double labeling of consecutive sections of diabetic skin with anti‐SMA and anti‐podoplanin antibodies to identify the indicated vessel as a lymphatic collecting vessel; Size bar: 20µm.
54
Geleff et al., 1999). Figure 11 shows representative images of human diabetic and
normoglycemic skin containing podoplanin‐positive LVs (left panel, black arrows) and DARC‐
positive BVs (right panel). Counting and quantification of LVs revealed a significant higher
number of LVs in diabetic compared to normoglycemic skin (p‐value = 0.04). Similarly, BV
density was slightly increased in diabetic compared to normoglycemic skin, but this was not
significant (p‐value = 0.7).
Under physiological conditions LECs scarcely proliferate. De novo lymphangiogenesis seems to
occur rather upon inflammatory or cancerous signals (Cueni and Detmar, 2008). Hence, we
supposed that the higher LV density in the skin of T2DM patients could be the result of a chronic
inflammatory stimulus present in the dermis. Moreover, higher LV density in diabetic patients
might represent a reaction of the skin and the skin vasculature to a perturbed metabolic
situation. In agreement with studies in human patients with metabolic diseases, enhanced LV
densities were previously detected in pathological situations such as cholesterol‐rich
atherosclerotic lesions (Kholova et al., 2011), and in chronic venous insufficiency ulcers
(Fernandez et al., 2011). In contrast to our findings, a decreased LV density associated with
reduced macrophage number and impaired wound healing was found in skin wounds (Saaristo
et al., 2006) and in a corneal suture model assay (Maruyama et al., 2007) of db/db mice.
However, although established murine models were used, artificial and acute wounds were
created which might not reflect the chronic inflammatory condition of the skin of patients
included in our study. Furthermore, our morphological characterization did not include skin
wounds or skin ulcera but rather (apparently) healthy skin.
Other studies showed that accelerated lymph vessel formation was crucial for resolution of
airway obstruction (Baluk et al., 2005), and to restore gut homeostasis in Crohn’s disease (von
der Weid et al., 2011). However, in chronic inflammation, LVs are suggested to be more
detrimental. Several reports indicate that inflammatory‐driven lymphangiogenesis leads to
dysfunctional vessel formation, representing an overproliferative phenomenon with reduced
lymph drainage capacity and enhanced leakyness (Baluk et al., 2009, Alexander et al., 2010).
Consistent with these findings, in pancreatic island inflammation, blocking of
lymphneoangiogenesis was beneficial for island transplants (Yin et al., 2011). Although some
reports indicate beneficial effects of increased lymphangiogenesis in inflammatory conditions
(Saaristo et al. 2006, Maruyama et al. 2005), other publications report dysfunctional lymphatic
vessels especially in chronic inflammatory diseases leading to prolongation of inflammation
(Alexander et al. 2010; von der Weid et al., 2011). Conclusively, the question whether
exaggerated lymphatic vessel formation might be dysfunctional but still be useful to resolve
inflammation and function as a bystander in tissue remodelling and wound repair in T2D has to
be explored.
55
Our findings also raise the question why BV density was not enhanced in T2DM skin. Consistent
with our observations, recent studies in murine models showed that acute inflammation
strongly enhances lymph vessel density but not that of blood vessels (Kim et al., 2009;
Huggenberger et al., 2011). Further, reduced blood vasculature was observed in diabetic skin
due to hypoxia and ischemia, which regulate VEGF production (Galiano et al. 2004; Enholm et al.,
1997; Thangarajah et al., 2009). Further, CXCL10, which was upregulated in dLECs, is known to
have an inhibitory effect on angiogenesis (Belperio et al., 2000; Bodnar et al., 2009).
Figure 11: LV and BV density in diabetic versus normoglycemic skin. Staining for LVs (black arrows) with anti‐podoplanin antibody and quantification of LV density shows higher LV density in diabetic skin; Right panel: Staining for BVs with anti‐DARC antibody and quantification of BV density reveals slightly elevated but not significantly different number of BVs in diabetic compared to normoglycemic skin; Size bar: 20µm.
56
Overall, our results suggest that lymphatic vessels follow a different proliferative stimulus than
blood vessels in T2D skin, which might be due to significant differences in tissue‐residing factors
and mechanisms that drive lymphangiogenesis versus angiogenesis.
7.1.4 Increased macrophage infiltration in diabetic skin
Considering the above mentioned murine wound healing study in db/db mice (Maruyama et al.,
2005), we evaluated the number of CD68‐ positive macrophages in normoglycemic and diabetic
human skin. Macrophage infiltration, measured as the number of macrophages per 100µm2 was
highly pronounced in diabetic compared to normoglycemic human skin, representing a 3.5‐fold
increase (Figure 12, p‐value < 0.001).
Macrophages produce growth factors which in turn support re‐epithelialization and promote
angiogenesis during wound healing. When they are missing, retarded of wound healing is
observed (Martin & Leibovich, 2005). The process of wound healing is strongly disturbed in
non‐healing diabetic wounds (Mahdavian Delavary et al., 2011). There is retarded wound
healing when macrophages show increased cytokine production and are dysfunctional (Khanna
et al., 2010). Pierce et al. (2001) report macrophage dysfunction which is characterized by the
enhanced production of inflammatory cytokines. Moreover, Zampell et al. (2012) show a more
than 3‐fold increase in macrophage number in lymph stasis, a condition of lymphatic vessel
dysfunction. Anti‐TNFα treatment of skin wounds depleted macrophages and increased wound
healing in diabetic mice (Goren et al., 2007). Hence, increased macrophage infiltration could be a
sign of enhanced production of inflammatory cytokines, but also of their reduced clearance by
newly grown, but dysfunctional lymphatic vessels.
Figure 12: Macrophage infiltration in normoglycemic versus diabetic human skin.Immunohistochemical labeling of human skin sections with anti‐CD68 antibody andquantification of macrophage number per 100µm2; Size bar: 20µm.
57
7.1.5 Macrophages produce vascular endothelial growth factors
As increased macrophage tissue infiltration is a critical sign of skin inflammation, we next aimed
to analyze their potential of production angiogenic and proinflammatory substances, supporting
a pro‐lymphangiogenic and pro‐inflammatory milieu in the skin of T2DM patients.
It is well accepted that macrophages can produce vascular endothelial growth factors (VEGFs),
e.g. VEGF‐A and VEGF‐C, and thereby are able to drive lymphangiogenesis (Machnik et al., 2009;
Kerjaschki, 2006; Maruyama et al., 2005).
Figure 13: VEGFC and VEGFA expression of infiltratin skin macrophages. A: Doublelabeling of human diabetic (upper panel) and normoglycemic (lower panel) skin with antibodiesto CD68 and VEGF‐C showing that macrophages in diabetic and normoglycemic skin are able toexpress VEGF‐C; Size bar: 20µm. B: Double labeling of human diabetic (upper panel) andnormoglycemic (lower panel) skin with antibodies to CD68 and VEGF‐A showing thatmacrophages in diabetic and normoglycemic skin are able to express VEGF‐A; Size bar: 20µm.
58
Therefore, we evaluated VEGF‐C and VEGF‐A expression by infiltrating tissue macrophages in
human diabetic and normoglycemic skin. As shown in Figure 13 A, both, 'diabetic' and
'normoglycemic' macrophages were expressing VEGF‐C, which is a strong lymphangiogenic
factor (Jussila and Alitalo, 2002). Similarly, VEGF‐A production was visible in infiltrating
macrophages of diabetic and normoglycemic skin (Figure 13 B).
Quantitative analysis (Figure 14) revealed that 76% and 90% of macrophages expressed VEGF‐C
in nondiabetic and diabetic skin, respectively (p‐value = 0.11). Further, 85% and 82% of
macrophages expressed VEGF‐A in non‐diabetic and diabetic skin, respectively (p‐value = 0.31).
Due to the fact that there was a highly increased number of infiltrating macrophages in diabetic
skin, which produced these (lymph‐)angiogenic factors, we assumed the generation of a steep
VEGFA and VEGF‐C interstitial tissue gradient, which could be a potent driver of
lymphangiogenesis in the skin of T2DM patients. Due to this result, it is tempting to hypothesize
that increased macrophage infiltration could be directly involved in the generation of the
strongly increased LV density and of the slightly elevated BV number in T2DM skin.
Figure 14: Quantitative analysis of VEGFC and VEGFA production by infiltrating skinmacrophages.
59
7.1.6 Increased TNFα levels in human diabetic skin
In skin diseases, e.g. psoarisis, TNFα expression has been identified as a key agent driving
persistent inflammation, and its expression was mainly assigned to T‐cell and macrophages
(Bonifati and Ameglio, 1999). Further, low grade vascular inflammation and elevated levels of
pro‐inflammatory cytokines are predictive for the development of cardiovascular diseases and
T2DM (Haddy et al., 2003). Especially, TNFα levels are increased in subjects with endothelial
dysfunction, as this pro‐inflammatory cytokine downregulates endothelial NO expression
(Yoshizumi et al., 1993) and causes acute local vascular inflammation (Chia et al., 2003).
Moreover, it is well established that TNFα levels are significantly increased in wounds of
diabetic mice (Goova et al., 2001). In order to trace if TNFα expression is increased in diabetic
skin, we performed respective immunofluorescence stainings. As shown in Figure 15, highly
increased levels of TNFα were detected in the skin of T2DM patients. In particular, diabetic
vasculature (white arrows) and epidermis (white arrowheads) as well as cellular structures in
between exhibited the strongest TNFα expression. These data further strongly suggested a
possible functional role of TNFα in the skin of type 2 diabetic patients.
Figure 15: TNFα expression in skin. Human diabetic (upper panel) and non‐diabetic (lowerpanel) skin was stained with anti‐TNFα antibody. Increased staining could be found invasculature and epidermis of diabetic skin.
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7.1.7 TNFα production by CD68+ macrophages
Activated macrophages are not only crucial regulators of wound healing processes in diabetic
skin but also an important source of TNFα (Goren et al., 2007). Immunofluorescent double
staining with anti‐CD68 and anti‐TNFα antibody reconfirmed the increased macrophage
infiltration in diabetic (Figure 16 A) compared to normoglycemic skin (Figure 16 B) and showed
that these macrophages expressed TNFα (magnified inlets). It has been shown that macrophages
contribute to diabetes‐associated impaired wound healing mainly by producing TNFα (Goren et
al., 2007). Dysfunction of cutaneous macrophages combined with their reduced efferocytosis
(i.e. their phagocytosis capacity) contributes to impaired resolution of local inflammation and
complicated wound healing (Khanna et al., 2010). Our data suggested that a pro‐inflammatory
milieu in human diabetic skin is generated in part by macrophages via production of TNFα,
which in turn could have a detrimental impact on wound healing processes (Eming et al., 2007;
Goren et al., 2007) as well as migration of immune cells to the afferent LVs (Johnson et al., 2006).
All in all, enhanced levels of dysfunctional macrophages seem to contribute to disturbed skin
wound healing and susceptibility to skin infections, which was underlined by our data.
Figure 16: Production of TNFα by macrophages. Human diabetic (A) and non‐diabetic (B) skin was stained with anti‐CD68 and anti‐TNFα antibody. Increased macrophage infiltration could bedetected in diabetic skin as well as TNFα production by these macrophages (A, lower panel), whereas no expression was found in macrophages of normoglycemic skin (B, lower panel).
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To summarize the first part of my thesis, the morphological findings we retrieved from the
immunohistochemical analysis of diabetic and normoglycemic skin showed increased lymph
vessel density, accompanied by a strong macrophage infiltration, which produced on one hand,
vascular endothelial growth factors, and, on the other hand the pro‐inflammatory cytokine
TNFα.
However, no dramatic differences where found regarding deposition of extracellular matrix
proteins, including laminin and collagen IV. Additionally, on an ultrastructural level, no BM or
cellular alterations could be traced for LVs in T2DM skin. Similarly to small LVs, also the bigger
collecting LVs showed no significant changes when compared to BVs of T2DM skin, which are
characterized by an increased staining for smooth muscle actin.
Altogether, these findings suggest that, although LV did not exhibit a form of diabetic
lymphangiopathy, as it was reported earlier, the dermis of T2D patients manifests dramatic
tissue remodelling processes characterized by enhanced LV density and increased macrophage
infiltration, supporting the pro‐inflammatory milieu and predisposing for recurrent infections.
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7.2 Ex vivo isolation of LECs from human skin
Besides the fact that we observed significantly increased lymphangiogenesis associated with
enhanced macrophage infiltration in diabetic skin, there were no strong morphological
differences evident. However, we hypothesized that dermal LECs might reflect the altered load
of metabolites and retarded wound healing of T2DM skin on a molecular level. We expected that
we could answer the question whether complications seen in T2DM skin may be related to LV
malfunction, because this leads to wound healing defects (Saaristo et al., 2006), contributes to
local infection (Rockson, 2001) and has an important impact on lipid transport and metabolism
(Harvey et al., 2005). This potential LV dysfunction, together with signs for enhanced
lymphangiogenesis, should become evident by deregulation of respective gene expression
patterns.
Therefore, the second aim of my thesis was the analysis of the differential transcriptome of LECs
derived from T2DM patients and normoglycemic controls. I isolated LECs from human skin of
four diabetic and four non‐diabetic patients using a combined enzymatic‐mechanical protocol as
previously established and described (Wick et al., 2007, 2008; Kriehuber et al., 2001, see also
Material and Methods). The clinical characteristics of included patients are described in Table 3.
As shown in Figure 17 A, cells were sorted into LECs (CD31+Podoplanin+, green dots) and BECs
(CD31+Podoplanin‐, red dots). Reanalysis after sorting demonstrated the enrichment of CD31‐
and podoplanin‐positive LECs (in %) in the upper right quadrant, suggesting isolation of highly
pure populations of CD31/podoplanin double‐positive cells (Figure 17 B).
7.2.1 Quality control of isolated LECs
In order to exclude leukocyte contaminations, isolated cells were additionally stained with PC5‐
labeled CD45. As shown in Figure 18, the percentage of CD45+ cells after sorting was less than
one percent in all cell preparations, indicating nearly complete absence of leukocytes.
To stay as close as possible to the in vivo situation, immediately after sorting, cells were lyzed,
RNA was isolated and transcribed into cDNA. Using RT‐PCR, non‐diabetic (ndLECs) and diabetic
(dLECs) LECs were shown to be positive for lymphatic markers von Willebrand factor (vWF),
podoplanin and PROX1, but negative for keratin, suggesting exclusion of keratinocytes (Figure
19 A). Quantitative realtime PCR analysis confirmed similar expression levels of podoplanin in
dLECs and ndLECs (Figure 19 B). Altogether, these data confirmed high purity of isolated LEC
populations and exclusion of keratinocyte and leukocyte contaminations.
63
Figure 17: Fluorescent activated cell sorting of ex vivo isolated LECs and BECs. LECs andBECs were sorted by fluorescence using antibodies to podoplanin and CD31. BECs were CD31+and podoplanin‐ (A, red dots), while LECs were double positive for CD31 and podoplanin (A,green dots). B: Post‐sort analysis shows accumulation of double positive LECs in the upper rightquadrant. X‐axis: CD31 (FITC‐labeled) intensities, y‐axis: podoplanin (PE‐labeled) intensities;ndLECs: non‐diabetic LECs, dLECs: diabetic LECs.
Figure 18: Exclusion of leukocyte contaminations. Staining of cell populations with anti‐CD45staining was done in order to exclude leukocyte contaminations. Post‐sort analysis showsexclusion of CD45 positivity in isolated cells.
64
In order to obtain reliable microarray data and due to the low amount of RNA starting material,
two RNA amplification steps were amended (Wick et al., 2004) and checked by Agilent
Bioanalyzer 2100 measurements. Figures 20 and 21 show the Agilent graphs of RNA amounts
before and after two amplification rounds. This analysis further visualized the high quality of the
amplified RNA, excluded the possibility of degradation artefacts and guaranteed sufficient
amounts of RNA for subsequent array hybridization.
Figure 19: Quality control of isolated LECs. A: Using RT‐PCR and gel electrophoresis,transcripts for actin, vWF, keratin, podoplanin and prox1 were detected; ndLEC: non‐diabeticLEC, dLEC: diabetic LEC, +: positive control, ‐: negative control. B: Quantitative realtime PCRconfirmed expression of podoplanin in isolated cells, which showed no significant difference;dLEC: diabetic LEC, ndLEC: non‐diabetic LEC.
65
Figure 20: Amplification check of RNA isolated from dLECs. Left panel: RNA amount of isolated dLECs before amplification; right panel: RNA amount of isolated dLECs after two amplification rounds. The x‐axis of depicted graphs represents the runtime (s), the y‐axis represents the fluorescence units [FU].
66
Figure 21: Amplification check of RNA isolated from ndLECs. Left panel: RNA amount of isolated ndLECs before amplification; right panel: RNA amount of isolated ndLECs after two amplification rounds. The x‐axis of depicted graphs represents the runtime (s), the y‐axis represents the fluorescence units [FU].
67
7.3 Bioinformatical analysis of diabetic versus nondiabetic LEC transcriptomes
Files obtained from GCOS (.cel) were used to analyze significant changes between gene
expression profiles of different patients and groups (Wick et al., 2004, 2007, 2008). Only genes
with postnormalization values above the BioB control were included in the calculations. After
background correction and normalization (Figure 22) using the robust multichip average (RMA)
method, datasets were analyzed using two‐sample t‐test and relative variance method (RVM,
Stokić et al., 2006) (Figure 23). The RVM method was developed to trace gene expression
alterations in small sample entities, and is was successfully tested to identify important
endothelial markers like podoplanin (Stokić et al., 2006). Further, a p‐value < 0.05 was
considered to identify genes significantly different between dLECs and LECs.
Figure 23: Bioinformatical analysis using Student's ttest and RVM. Bioinformatical analysis of diabetic versus non‐diabetic LECs using RVM and t‐test. Both methods in one graph are shown on the right.
Figure 22: Normalization of microarray chip data. Normalization was done by RobustMultichip Average (RMA) using Bioconductor software in R.
68
Further, y‐comparison of LEC‐specific marker genes and of the genes differentially regulated
between dLECs and dBECs from the same patients was performed. Redundant annotation terms
were identified and omitted. All data has been deposited in NCBIs Gene Expression Omnibus and
are accessible through GEO accession number GSE38396
(http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38396). Gehört schon hierher:
Hierarchical clustering was used to analyze expression profiles of the different samples and was
carried out using Euclidean distance metric and centroid linkage rule analysis with the
GeneSpringGX (Ambion) software. Data were represented as a dendrogram with the closest
branches of the tree representing arrays with similar gene expression patterns. The expression
profiles of the eight different array samples was analyzed, which illustrated a broad similarity
among the four dLEC arrays or the four LEC arrays from normoglycemic controls (ndLECs;
Figure 24).
The t‐test and RVM analysis retrieved a list of 180 genes that were differentially expressed
between dLECs and ndLECs. While 49 genes were upregulated, 131 genes were downregulated
in dLECs compared to ndLECs. This 180 significantly deregulated dLEC candidate genes were
the basis of a gene network that was assumed to be of functional relevance. The Gene Ontology
Browser available on the affymetrix website (www.affymetrix.com) was used as sources to
classify genes according to functionality context. Ingenuity Pathway Analysis (IPA) software
(Ingenuity Systems, Redwood City, CA, USA) was used to identify cellular networks that
statistically fit to a given input gene list and according expression values. The association of
genes with particular functions, pathways and diseases was analyzed according to their scores. A
Canonical pathway analysis identified pathways which were most significant to the input data
set. The significance value associated with functions and pathways is a measure of how likely it
is that genes from the data set file participate in that function. The significance is then expressed
as a p‐value, which is calculated by the right‐tailed Fisher’s exact test. An extensive NCBI GEO
and PubMed ‘in silico’ research was amended to retrieve information on gene expression and
relevance for LEC biology.
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Figure 24: Hierarchical cluster analysis: LECs derived from four T2DM patients exhibit aunique gene expression pattern. Hierarchical clustering of the four LEC versus four dLEC geneexpression data (A) and of the 180 differentially expressed genes (FC>1.5) (B). Combined entityand condition trees are shown. On the y‐axis, an entity tree was generated by grouping the probesets based on the similarity of their expression profiles. On the x‐axis, a condition tree wasgenerated showing the relationship between the samples.
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7.3.1 Identification of deregulated pathways and gene functions using Ingenuity Pathway Analysis
In order to identify functional gene patterns offering insight into the role of LECs in T2DM, the
differentially expressed genes were grouped according to their biological functions using the
NetAffx tool as well as Ingenuity Pathway Analysis (IPA). IPA revealed, which canonical
pathways and which gene functions are mainly altered in dLECs versus ndLECs. The top 10 of
the canonical pathways (Figure 25) and gene functions (Figure 26) were visualized using a bar
chart. Genes associated with these pathways and functions are highlighted in the Tables 9 and
10. Combining all in silico analyses, this led to the establishment of four overrepresented themes
in dLECs, comprising (A) defense response and inflammation, (B) tissue remodeling and cell
motility, (C) lymphangiogenesis and cell fate regulation and (D) lipid handling and small
molecule biochemistry (Table 11). Furthermore, the dLEC transcripts were highly enriched for
“plasma membrane” (44 transcripts) and “cell periphery and extracellular space” (71
transcripts) compartments (both P < 0.001), highlighting an extensive modulation of dLEC
molecules at the environmental interface.
Conclusively, these unbiased, computer‐based methods identified a dLEC transcriptome strongly
distinct from that of LECs under physiologic condition. This transcriptome mirrored the
phenotypic changes of T2DM skin on a molecular level and highlighted an involvement of LVs in
T2DM skin alterations. In the following sections, I will present the main candidates of the
deregulated gene themes and will discuss implications of their deregulation in LECs.
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Figure 25: Pathway analysis using IPA. For the canonical pathway categorization of alteredexpressed genes, IPA software was used to calculate a p‐value (set ≤ 0.05, shown as blue bars) byFishers exact test, determining the probability with which a set of genes is associated with aknown biological function or pathway. The ratio (yellow squares) represents the number ofdifferentially expressed genes from the dataset divided by the total number of genes thatconstitute that canonical pathway.
Figure 26: Deregulated cellular functions in dLECs. Rankings of the top twenty Molecular andCellular Functions.
F2RL1 Coagulation factor II (thrombin) receptor‐like 1 0.17 0.010 Receptor for trypsin and trypsin‐like enzymes coupled to G proteins, innate immune response
Cluster D: Small Molecule BiochemistryLipid transport / metabolic process 1554833_at NM_018349 MCTP2 Multiple C2 domains, transmembrane 2 5.14 < 0.05 binds Ca in absence of phospholipids, obesity marker!
220331_at NM_006668 CYP46A1 Cytochrome P450, family 46, subfamily A, polypeptide 1 4.14 < 0.05 Monooxygenase, cholesterol turnover , steroid degradation
235978_at AI766029 FABP4 Fatty acid binding protein 4, adipocyte 3.85 0.006 FFA chaperone, intracell. fa transport 49452_at NM_001093.3 ACACB Acetyl‐CoA carboxylase 3.70 0.014 rate‐limiting enzyme in fatty acid oxidation
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201525_at NM_001647 APOD Apolipoprotein D 2.64 0.012 lipid transporter glycoprotein
222217_s_at NM_024330 SLC27A3 Solute carrier family 27 (fatty acid transporter), member 3
2.17 0.003 Fa transport and acyl‐CoA activation
205769_at NM_003645 SLC27A2 Solute carrier family 27 (fatty acid transporter), member 2 0.28 < 0.05 acyl‐CoA ligase activity
Table 11: Transcript levels of deregulated candidate genes functionally clustered in (A) Inflammatory Response, (B) LEC Adhesion and Migration, (C) LEC growth and Lymphangiogenesis, and (D) Small Molecule Biochemistry. *Shown are ratios of diabetic (dLECs) versus non‐diabetic (ndLECs) LECs probeset expression. †Statistical significance of that ratio is indicated either as P‐value, or as significant result of RVM analysis, which integrates a P‐value ≤ 0.05. ‡Differentially expressed genes were grouped according to their biological functions (GO annotation) and the top differentially expressed genes were ranked in order, based on their mean fold change differences.
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7.3.2 Verification of LEC specific genes and comparison with other arrays
In order to additionally control and confirm the purity of LEC preparations, we examined for
expression changes of several LEC‐specific marker genes which were shown to be not
significantly altered between dLECs and ndLECs (Table 12). For example, the transcript level of
podoplanin, which was used for FACS sorting had a fold change (FC) of 1.08 (dLEC/ndLEC) and
was considered to be unchanged between the two groups of cells (see also Figure 18 B).
Expression alterations of established LEC transcripts (e.g. CD44, CCL27, CXADR, CXCL14, LYVE1,
PKP1, APP, EDNRB, FABP4, KRT14, MMRN1) (Podgrabinska et al., 2002; Hirakawa et al., 2003;
Wick et al., 2007; Wick et al., 2008) underlined their specific role in lymphatic vessels and
validated the quality of our approach. dLECs further revealed some overlapping gene expression
changes with hypoxic LECs (Irigoyen et al., 2007), and with LECs derived from skin of
lymphedema patients (Ogunbiyi et al., 2011) and lymph node derived LECs (Malhotra et al.,
2012), pointing towards a similar role of these gene candidates in pathological lymphatic
dysfunction. In contrast to our results, recent studies detected downregulation of key lymphatic
markers PROX1 and VEGFR3 in adipose tissue lymphatics in familial human hyperlipidemia
(Horra et al., 2009) as well as murine skin inflammation (Vigl et al., 2011).
Moreover, we compared our data with data sets derived from LECs in pathological situations
associated with diabetes, inflammation, wound healing and lymphatic dysfunction, though only
few studies have investigated the gene expression changes of human endothelial cells in
pathophysiologic situations (St. Croix et al., 2000; Seaman et al., 2007; Clasper et al., 2008;
Ogunbiyi et al., 2011). Here, we traced some overlaps with gene expression changes in hypoxic
LECs (GALNTL2) (Irigoyen et al., 2007). However, compared to another study using an
experimental model of acute post‐surgical lymphedema, nearly no overlap could be detected
(Tabibiazar et al., 2006). Moreover, only a weak overlap could be detected with VEGFC
responsive genes in LECs (Yong et al., 2005). This points towards a specific role of deregulated
genes in LECs in different pathological conditions.
Overall, our findings indicated that LEC‐specific markers are stable in diabetic skin and that their
expression alterations in LVs of other tissue types might depend on the specific
pathophysiological situation and microenvironment.
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Gene symbol Gene name FC (dLEC/ndLEC) pvalue
ABCA4 Retinal‐specific ATP‐binding cassette
transporter 0.66 0.58
ANGPT2 Angiopoietin‐2 precursor 1.27 0.31KLHL4 Kelch‐like protein 4 0.95 0.89
Table 12: Transcript levels of LEC specific genes. No significant differences could be seen for LEC‐specific genes between diabetic (dLECs) and non‐diabetic (ndLECs); FC = fold change.
7.3.3 Diabetic LECs exhibited a distinct gene expression profile compared to diabetic BECs
The mRNA expression analysis of BECs derived from the same four diabetic and normoglycemic
patients revealed a completely diverse set of genes differentially regulated in diabetic BECs
(dBECs). Out of the 180 differentially regulated genes in dLECs, only 19 were also altered in
dBECs (Table 13), which represents an overlap of only 10.5%. This result suggested that a highly
specific gene signature was present in dLECs compared to dBECs and indicated that LVs
undertake completely different tasks than BVs in the skin of T2DM patients.
Table 13: Gene expression overlap of diabetic LECs (dLECs) and diabetic BECs (dBECs) with documented fold change (FC) between diabetic and nondiabetic cell populations.
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7.3.4 Genes linked to altered lipid transport and metabolism, increased oxidative stress and to the pathogenesis of type 2 diabetes mellitus
First, we identified expression changes of several genes that have already been genetically
linked to T2DM in humans (see Table 14), including haptoglobin (HP, Quaye et al., 2006), JUN
oncogene (Malhotra et al., 2009), tetraspanin 8 (TSPAN8, Zeggini et al., 2008) apolipoprotein d
(APOD, Vijayaraghavan et al., 1994), hematopoietically‐expressed homeobox protein (HHEX,
Sladek et al., 2007; Saxena et al., 2007), lamin A/C (LMNA, Wegner et al., 2007) and fatty acid
binding protein 4 (FABP4, Chan et al., 2010). Genes additionally crucial for lipid metabolic
processes included FABP4 and APOD. APOD is reported to be a genetic marker for T2DM and
obesity (Vijayaraghavan et al., 1994), to be increased in T2DM myotubes and gestational
diabetes (Navarro et al., 2010; Hansen et al., 2004) and to be involved in defense mechanisms
against oxidative stress (Navarro et al., 2010).
The results indicate that established T2D markers prove valid in the lymphatic vessel
compartment and confirmed their importance as potential biomarkers. However, other markers
very characteristic for T2DM, like PPARγ, did not come up in dLECs, highlighting the multi‐
faceted genetic contribution in this disease. Taken together, these alterations presumably confer
altered adhesive, metabolic and inflammatory properties to type 2 diabetes LECs.
FABP4 is highly and specifically expressed in LECs (Ferrell et al., 2008; Wick et al., 2007 and
unpublished result) and is an important mediator of IR in mice (Uysal et al., 2000). Moreover, its
expression in human umbilical venous endothelial cells (HUVECs) is regulated by VEGF (Elmasri
et al., 2009). NOX4 is a major contributor of reactive oxygen species (ROS) production in
endothelial cells (Goettsch et al., 2009) and a mediator of angiogenesis (Ushio‐Fukai, 2007). We
confirmed FABP4, NOX4 and APOD upregulation by quantitative realtime PCR (Figure 27 A) and
reconfirmed FABP4 protein expression by immunofluorescence (Figure 27 B). Elevated
expression levels of FABP4, NOX4 and APOD in dLECs pointed towards a highly disturbed
metabolic status in the skin of T2DM patients. These lipid handling abnormalities, together with
the downregulation of small molecule transporters (examples) show that LVs are compromised
in their function in T2DM.
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AffyID Accession
no. Gene symbol
Gene name FC
(dLEC/ndLEC) pvalue
208470_s_at P00738 HP Haptoglobin 8.43 0.0209
235978_at AI766029 FABP4 Fatty acid binding
protein 4, adipocyte
3.85 0.006
201525_at P05090 APOD Apolipoprotein D 2.64 0.0115
204689_at Q03014 HHEX Hematopoietically
expressed homeobox
2.14 0.0027
201464_x_at P05412 JUN Jun oncogene 1.65 0.0182212086_x_at P02545 LMNA Lamin A/C 0.53 0.0042203824_at P19075 TSPAN8 Tetraspanin 8 0.17 0.0285
Table 14: Transcript levels of deregulated genes already associated with type 2 diabetes. Transcript levels of dereguated genes which were published to be genetically associated with type 2 diabetes. FC (dLEC/ndLEC) = fold change between diabetic (dLEC) and non‐diabetic (ndLEC) LECs.
Figure 27: Confirmation of altered expression of FABP4, APOD and NOX4 in dLECs by realtime PCR and immunofluorescence. A: Differential expression of FABP4, APOD and NOX4 was confirmed by quantitative realtime PCR using Taqman ® gene expression assays. B: FABP4 expression was additionally confirmed by double‐labeling of human diabetic and non‐diabetic skin with antibodies to FABP4 and podoplanin; Size bar: 20µm.
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7.3.5 Identification of a gene signature related to wound healing and tissue repair in dLECs
A huge number of transcripts involved in ECM remodeling and adhesion processes indicated a
major effect of T2DM on LEC growth and migration, pointing at ongoing LV morphogenesis
and/or tissue remodeling (Table 15). There were prominent deregulations of a gene set of
proteases (MMP1, MMP2) and protease inhibitors (SERPINs), and of a gene set of transcripts
involved in formation and binding of ECM components and LEC motility (CYR61, GALNTL2) and
wound repair (AQP3).
Two important genes implicated in angiogenesis, tissue remodeling and wound healing are
cysteine rich protein 61 (CYR61) and matrix metalloproteinase 2 (MMP2), which were found to
be upregulated in dLECs. CYR61 is an ECM protein that mediates wound healing (Chen et al.,
2001) and angiogenesis via integrins (Leu et al., 2002). Further, it is implicated in the
pathogenesis of diabetic retinopathy (You et al., 2009) as a downstream target of advanced
glycation endproducts (Hughes et al., 2007). Additionally, MMP2 expression was shown to
stimulate angiogenesis and wound healing (Slyke et al., 2009; Agah et al., 2004). Furthermore,
we detected downregulation of aquaporin 3 (AQP3), a water and glycerol transporter, which is
also important for cutaneous wound healing by reducing epidermal proliferation and migration
(Hara‐Chikuma and Verkman, 2008). Additionally, chemokine ligand 14 (CXCL14, Maerki et al.,
2009) and defensin beta 1 (DEFB1, Schittek et al., 2008) were downregulated in dLECs. Both
have antimicrobial effects, suggesting a function for LECs of diabetic skin in the regulation of
infections (see Table 15).
We confirmed altered expression of AQP3, MMP2 and CYR61 by quantitative realtime PCR
(Figure 28 A). Further, downregulation of AQP3 protein in diabetic LVs was reconfirmed by
immunofluorescent double staining (Figure 28 B), as well as upregulation of CYR61 (Figure 28
C). MMP2 and CYR61 overexpression in dLECs indicated involvement of LVs in increased tissue
remodeling as observed during wound healing processes and increased lymphangiogenesis.
AQP3 expression was not reported in LECs before but its expression in diabetic LECs
additionally points towards an involvement of LVs in dermal healing processes. Moreover, this
gene could represent a new water and glycerol transporter in LECs (Ishibashi et al., 2009).
Table 15: Transcript levels of genes associated with wound healing and tissue repair. FC (dLEC/ndLEC) = fold change between diabetic (dLEC) and non‐diabetic (ndLEC) LECs.
Figure 28: Confirmation of altered AQP3, MMP2 and CYR61 expression in dLECs by realtime PCR and immunofluorescence. A: Analysis of differential expression by quantitative realtime PCR using Taqman ® gene expression assays. B, C: AQP3 and CYR61 expression was additionally confirmed by double‐labeling of human diabetic and non‐diabetic skin with antibodies to respective antigen and podoplanin; Size bar: 20µm.
Conclusively, The gene alterations might indicate a stage of increased active reparative
mechanism in T2D skin. and show that lvs play an active role in T2D skin disorder.
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7.3.6 Identification of a gene signature related to increased adhesion of inflammatory cells
A plethora of genes implicated in cell adhesion and inflammatory processes was altered
significantly in dLECs (Table 16). The most upregulated genes included vascular cell adhesion
molecule (VCAM1) and chemokine (CXC‐motif) ligand 10 (CXCL10), while coxsackie and
adenovirus receptor (CXADR) and syndecan 1 (SDC1) were downregulated. These genes are
mainly responsible for the regulation of immune cell traffcking. VCAM1 was previously reported
to be expressed in LECs upon TNFα stimulation and to be an important regulator of DC adhesion
and migration in vitro and in vivo (Johnson et al., 2006). CXCL10 seems to be a crucial chemokine
in T‐cell and macrophage infiltration (Heller et al., 2006; Dufour et al., 2002) and implicated in
resolution of inflammation (Rahman et al., 2010). CXADR interacts with junctional adhesion
molecule 1 to regulate monocyte, neutrophil and T‐cell migration across junctional connections
(Luissint et al., 2008; Zen et al., 2005) and was previously reported to be specifically expressed
on LECs (Vigl et al., 2009). SDC1 has major tasks in inhibiting leukocyte adhesion to the
endothelium (Götte et al., 2002) and is reported to be downregulated by TNFα (Kainulainen et
226374_at P78310 CXADR Coxsackie virus and adenovirus
receptor 0.21 0.0080
201287_s_at P18827 SDC1 Syndecan 1 0.12 0.0165
Table 16: Transcript levels of genes linked to increased adhesion of inflammatory cells. FC (dLEC/ndLEC) = fold change between diabetic (dLEC) and non‐diabetic (ndLEC) LECs.
Differential gene expression of VCAM1, CXCL10, CXADR and SDC1 was confirmed by realtime
PCR and showed that expression ratios matched those retrieved from microarray analysis
(Figure 29 A). Differential gene expression of CXCL10 and CXADR was further approved on
protein level by double‐immunofluorescence stainings of human skin (Figure 29 B and C).
Conclusively, differential expression of VCAM1, CXCL10, CXADR and SDC1 suggested increased
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adhesion of inflammatory cells to the lymphatic endothelium in the skin of T2DM patients,
possibly as a result of an increased pro‐inflammatory milieu.
Figure 29: Confirmation of altered VCAM1, CXCL10, CXADR and SDC1 expression in dLECs by realtime PCR and immunofluorescence. A: Differential expression of VCAM‐1, CXCL10, CXADR and SDC1 was confirmed by quantitative realtime PCR using Taqman ® gene expression assays. B, C: Differential expression of CXCL10 and CXADR was reconfirmed by double‐labeling of human diabetic and non‐diabetic skin with antibodies to CXCL10, CXADR and podoplanin; Size bar: 20µm.
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7.3.7 Deregulated genes associated with cellular host defense
The prominent inflammation‐related gene cluster revealed alterations of processes related to
cellular defense, response to infection, chemotaxis/leukocyte adhesion and tissue repair/wound
healing (Table 17).
A group of acute phase and antimicrobial defense response factors contained transcripts of well
described extracellular factors, which previously have been detected as important inflammatory
markers in plasma, lymph fluid or wound tissue. Of note, we detected upregulation of transcripts
for HP (haptoglobin), PTX3 (pentraxin), C1S (complement 1), SERPING1 (serpin peptidase
inhibitor, clade G (C1 inhibitor), member 1) and APP (amyloid precursor protein), and
Table 17: Transcript levels of genes associated with cellular host defense. Transcript levels of dereguated genes which are implicated in the process of cellular and host defense. FC (dLEC/ndLEC) = fold change between diabetic (dLEC) and non‐diabetic (ndLEC) LECs.
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7.4 TNFαinduced effects on LEC behavior
In the final part of my thesis, I aimed to develop a mechanistic link between the observed
morphological changes of T2DM skin, i.e. the enhanced LV and macrophage number, and the
specific gene expression profile of dLECs. In order to establish this link between skin lymphatic
morphology and the dLEC transcriptome, we were looking for a factor possibly bridging the gap
between these two findings.
7.4.1 TNFα responsiveness of LEC genes in vitro
Due to the finding that the highly increased macrophage number in diabetic skin was capable of
producing a local pro‐inflammatory milieu via TNFα, we aimed at investigating whether in vitro
TNFα stimulation of LECs could recapitulate the differential gene expression observed by our
transcriptomal analysis of dLECs versus ndLECs ex vivo. TNFα treatment induced upregulation
of CXCL10, VCAM1 and CYR61 (Figure 30) and downregulation of SDC1, CXADR and AQP3
(Figure 31) as it was identified by the transcriptomal analysis of ex vivo isolated LECs from
T2DM patients. Additionally, treatment with an inhibitory TNFα antibody reversed TNFα
induced expression changes of genes and suggested that differential gene expressions are highly
specific for TNFα. However, expression of FABP4, GALNTL2 and APOD was downregulated,
which is in contrast to the array data (Figure 32). Moreover, no effect could be found on
expression of MMP2 and NOX4 (Figure 33).
We conclude from these data that increased TNFα levels, mainly produced by infiltrating
macrophages, might directly influence the expression of some genes in microvascular LECs.
Hence, we identified TNFα‐driven gene expression as one signaling pathway leading to
differential gene expression in dLECs versus ndLECs. However, TNFα‐driven differential
expression of other genes did not match array data. Therefore, we hypothesize that not only one
predominant but rather the interplay of several phenomena, including epigenetic,
transcriptional, or microRNA‐mediated mechanisms, is crucial for the diabetic metabolic status
and responsible for observed gene expression changes of dLECs versus ndLECs.
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Figure 30: Upregulation of CXCL10, VCAM1 and CYR61 gene expression of cultured LECs byTNFα stimulation. Primary dermal LECs were cultured in EBM‐2/0.5% FCS and stimulated with10ng/ml TNFα for 24 hours (with or without TNFα inhibitor). TNFα treatment of primary culturedLECs perfectly recapitulated upregulation of CXCL10, VCAM1 and CYR61 as found by microarrayanalysis.
Figure 31: Downregulation of CXADR, SDC1 and AQP3 gene expression of cultured LECs by TNFα stimulation. Primary dermal LECs were cultured in EBM‐2/0.5% FCS and stimulated with 10ng/ml TNFα for 24 hours (with or without TNFα inhibitor). TNFα treatment of primary cultured LECs perfectly recapitulated downregulation of SDC1, CXADR and AQP3 as found by microarray analysis.
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Figure 32: Downregulation of FABP4, GALNTL2 and APOD gene expression of cultured LECsby TNFα stimulation. Primary dermal LECs were cultured in EBM‐2/0.5% FCSand stimulatedwith 10ng/ml TNFα for 24 hours (with or without TNFα inhibitor). Downregulation of FABP4,GALNTL2 and APOD expression by TNFα treatment is contrary to array results.
Figure 33: No change of MMP2 and NOX4 gene expression of cultured LECs by TNFα stimulation. Primary dermal LECs were cultured in EBM‐2/0.5% FCS and stimulated with 10ng/ml TNFα for 24 hours (with or without TNFα inhibitor). No effect of TNFα could be found on MMP2 and NOX4 expression.
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7.4.1 Increased migration of LECs upon TNFα stimulation
Interestingly, expression of several genes integrated in the clusters of ‘cell adhesion’ and
‘inflammatory response’ were regulated by TNF‐α and the in vitro stimulation experiments
matched the array data. Therefore, the effect of TNFα on LEC behavior was studied more
detailed.
LVs are able to react to an inflammatory milieu by increasing lymphangiogenesis (Cueni and
Detmar, 2008). TNFα is a pro‐inflammatory cytokine which can stimulate EC migration and
proliferation (Gao et al., 2002). In order to analyze the effect of TNFα on the behaviour of human
primary LECs, we performed an in vitro scratch wound healing assay with and without TNFα
stimulation. Stimulation of LECs seeded into 24‐well plates with 10ng/ml TNFα for 24 hours
significantly increased LEC migration and induced faster wound closure in a scratch wound
assay (Figure 34, p‐value = 0.007).
This data indicated that TNFα might lead to lymph vessel remodeling or enhanced lymph vessel
growth (Baluk et al., 2009) and further corroborated a potential link between increased TNFα
levels and increased LV density in the skin of T2DM patients.
7.4.2 Macrophage adhesion to LECs is increased by TNFα stimulation
Molecular mechanisms which regulate the entry of inflammatory cells from the blood into the
lymphoid tissues during their circulation in the body are well characterized (Miyasaka and
Tanaka, 2004; von Andrian and Mempel, 2003). In contrast, much less is known about the exit
mechanisms of these cells, especially of macrophages, from the surrounding tissues into afferent
lymphatics. However, migration of professional antigen‐presenting cells like lymphocytes, DCs
and macrophages is essential for controlling immune responses (Angeli and Randolph, 2006).
Increased TNFα levels were found in T2DM patients as well as T2DM mouse models.
Additionally, it was shown that endothelial interactions with immune cells are increased during
hyperglycemia (Algenstaedt et al., 2003).
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Therefore, we tested whether TNFα exerted effects on the interaction between LECs and
macrophages. In vitro stimulation of primary LECs with TNFα led to a massively increased
adhesion of macrophages (p‐value < 0.001). This was highly specific for TNFα as this effect could
be reduced to the amount of adherent macrophages of unstimulated LECs by additional
treatment with an inhibitory anti‐TNFα antibody (Figure 35).
Conclusively, we could show increased macrophage adhesion to LEC monolayers after TNFα
stimulation, indicating massive upregulation of adhesion molecules on LECs responsible for
macrophage adhesion. Similar results were shown for DCs, adhering to and transmigrating
through TNFα‐stimulated LECs, which was dependent on VCAM1 expression (which was also
upregulated in dLECs compared to ndLECs) in vitro and in vivo (Johnson et al., 2006). This fact
indicats that macrophages might undergo enhanced lymphatic traffcking in T2DM.
Figure 34: Increased migration of LECs after TNFα stimulation. Primary dermal LECs werecultured in EBM‐2/0.5% FCS and stimulated with or without 10ng/ml TNFα for 24 hours. Anartificial wound was made in each well. Representative images at timepoints t=0h, t=12h andt=24h and quantification of measured closure of wound area are shown.
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Figure 35: Adhesion of macrophages to primary LECs in vitro. Primary dermal LECs werestarved overnight in EBM‐2/0.5% FCS and stimulated with or without 10ng/ml TNFα for 24hours (with or without TNFα inhibitor). Increased macrophage adhesion to LECs was detectedupon TNFα treatment, which was reversible with an anti‐TNFα antibody; Size bar: 100µm.
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7.5 CXC motif chemokine 10 (CXCL10) expression and function in LECs
The array results indicated a prominent upregulation of CXCL10 in dLECs (Table 16), and we
could recapitulate strong upregulation of CXCL10 expression in LECs by TNFa stimulation
(Figure 29). CXCL10 is a small cytokine and is also called interferon gamma‐induced protein 10
(IP‐10). It has fundamental roles in effector T‐cell generation and function (Dufour et al., 2002).
Moreover, it is suggested to be involved in the invasion of immune cells into the brain, thereby
contributing to the pathogenesis of multiple sclerosis (Salmaggi et al., 2002). Additionally,
CXCL10 contributes to airway inflammation in asthma (Medoff et al., 2002) and its upregulation
is accompanied by a delayed resolution of local inflammation (Rahman et al., 2010). CXCL10 is
angiostatic and was shown to lead to apoptosis and dissociation of newly formed BVs (Bodnar et
al., 2009, 2006). In diabetes, CXCL10 leads to beta cell destruction via interaction with TLR4
(Schulthess et al., 2009). Here, we aimed to analyze the functional implications of CXCL10
expression in LECs.
7.5.1 CXCL10 is upregulated and secreted by LECs upon TNFα stimulation
As shown by realtime PCR, CXCL10 was not expressed in unstimulated but dramatically
upregulated in TNFα‐stimulated LECs (see Figure 30). This upregulation could be further
confirmed by Western blotting analysis on a protein level (Figure 36 A). Moreover, we could
show that LECs secrete this chemokine upon stimulation with TNFα using ELISA and Western
blotting of supernatants (Figure 36 B).
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Figure 36: Expression and secretion of CXCL10 in LECs upon TNFα stimulation. Primary dermal LECs were starved overnight in EBM‐2/0.5% FCS and stimulated with or without 10ng/ml TNFα for 24 hours (with or without TNFα inhibitor). Cells were lysed in Laemmli sample buffer and respective supernatants were collected. A: CXCL10 expression in LECs was checked using western blotting. GAPDH was used as loading control. CXCL10 is not visible in unstimulated but massively upregulated in TNFα‐stimulated LECs. B: Supernatants of stimulated and unstimulated LECs were checked for CXCL10 secretion by ELISA and Western blotting showing secretion of this chemokine by TNFα‐stimulated LECs.
7.5.2 CXCL10 mediates macrophage adhesion to LECs
Due to the fact that CXCL10 was upregulated and secreted upon TNFα treatment, and that TNFα
significantly increased adhesion of macrophages to the LEC monolayers, we hypothesized that
CXCL10 could be one factor responsible for the massively increased macrophage adhesion to
LECs. Therefore, we stimulated primary LECs with 10ng/ml TNFα, with or without an inhibitory
antibody to CXCL10. A massively increased adhesion of THP‐1 macrophages to LECs was found
upon TNFα treatment, which was almost completely abrogated by addition of an inhibitory
CXCL10 antibody (Figure 37, p‐value = 0.04). Conversely, treatment of LECs with TNFα plus an
inhibitory antibody to VCAM1 – which was also upregulated by TNFα treatment and shown to
be responsible for DC adhesion in LECs (Johnson et al., 2006) ‐ did not affect macrophage
adhesion to the lymphatic endothelium (Figure 38, p‐value = 0.65). This suggests that CXCL10 is
an important mediator of macrophage adhesion to lymphatics, possibly only in an inflammatory
condition when TNFα levels are increased and, hence, lead to its secretion by LECs.
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Figure 37: CXCL10 is responsible for macrophage adhesion to lymphatic endothelialmonolayer. Primary dermal LECs were starved overnight in EBM‐2/0.5% FCS and stimulated withor without 10ng/ml TNFα for 24 hours with or without an inhibitory antibody to CXCL10. Increasedmacrophage adhesion to LECs could be found upon TNFα treatment which was reversed by CXCL10inhibitory antibody; Size bar: 100µm.
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Figure 38: VCAM1 is dispensable for macrophage adhesion to lymphatic endothelial monolayer. Primary dermal LECs were starved overnight in EBM‐2/0.5% FCS and stimulatedwith or without 10ng/ml TNFα for 24 hours with or without an inhibitory antibody to VCAM1.VCAM1 inhibitory antibody did not change macrophage adhesion to LECs; Size bar: 100µm.
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7.5.3 CXCL10 induces chemotaxis of macrophages
Having shown that CXCL10 is secreted by LECs upon TNFα stimulation and that CXCL10 is in part
responsible for macrophage adhesion, we asked whether CXCL10 secreted from stimulated LECs
had a chemotactic effect on macrophages. Therefore, we used the supernatants of LECs
stimulated with or without TNFα ‐ with addition of inhibitory antibodies to TNFα and CXCL10 ‐
and performed an agarose spot assay (Wiggins and Rappoport, 2010). As shown in Figure 39,
there was increased migration of macrophages into the agarose spots which contained TNFα (C)
compared to spots lacking TNFα (B). Increased migration induced by TNFα could be significantly
inhibited by an anti‐TNFα antibody (D). Similarly, when using a specific inhibitory antibody to
CXCL10, macrophage migration into the agarose spots could be reduced to the same extent as
with the anti‐TNFα antibody at both timepoints (p‐value = 0.008, E).
Conclusively, CXCL10 was identified as a factor regulated by TNFα in LECs. Our findings suggest
that this chemokine could be responsible for the chemotaxis of macrophages towards LVs.
Additionally, it could be possible that the interaction between lymphatic endothelium and other
inflammatory cells are affected by CXCL10, e.g. T‐cells and DCs, as well as the interaction of LVs
with tumor cells. However, additional experiments by using a recombinant form of CXCL10 are
needed to confirm observed effects on adhesion and chemotaxis of macrophages to LECs.
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Figure 39: Secreted CXCL10 induces chemotaxis of macrophages. Primary dermal LECs werestarved overnight in EBM‐2/0.5% FCS and stimulated with or without 10ng/ml TNFα for 24hours plus an inhibitory antibody to TNFα and CXCL10. Supernatants were collected andconcentrated for use in an agarose spot assay to measure chemotaxis of macrophages. Migrationarea was evaluated after 24 and 48 hours, respectively. Representative pictures andquantification of migration area (in µm2) shows an increased chemotaxis of macrophages intospots containing TNFα (C) which was specifically inhibited by an inhibitory antibody againstTNFα (D) and CXCL10 (E). PBS (A) and supernatant of LECs not stimulated with TNFα (B) wereused as controls.
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7.5.4 CXCL10 enhances LECtransmigration of macrophages
Similar to CCL27 in LECs, which was shown to be responsible for the transmigration of
CCR10+T‐lymphocytes (Wick et al., 2008), we hypothesized that CXCL10 could also confer
transmigration of THP‐1 macrophages. Therefore, we performed a transwell migration assay by
culturing LECs on the underside of fibronectin‐coated transwell filters. After having grown to
Figure 40: CXCL10 confers macrophage transmigration. Dermal LECs were grown toconfluence on the underside of fibronectin‐coated transwell filters and stimulated with 10ng/mlTNFα for 24 hours with or without an inhibitory antibody to CXCL10 to show involvement ofCXCL10 in macrophage transmigration. After putting the macrophages into the upper chamber,fluorescence of transmigrated macrophages was measured in the lower chamber after one (A),three (B) and six hours (C). As a control for LEC monolayer permeability, measurement of FITC‐dextran permeability of conuent monolayers showed no difference when stimulated withdifferent substances (D). Conclusively, TNFα stimulation led to enhanced macrophagetransmigration, which could be specifically diminished by an inhibitory CXCL10 antibody.
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confluence, LEC monolayers were stimulated with TNFα with or without a specific inhibitory
CXCL10 antibody. TNFα significantly enhanced transmigration of macrophages after one, three
and six hours, which was blocked by addition of a specific inhibitory anti‐TNFα antibody. When
adding a blocking anti‐CXCL10 antibody, transmigration of macrophages was significantly
reduced at the 3 hours stimulation timepoint, but only slightly after one and six hours (see
Figure 40 A‐C). The increase of transmigrated macrophage number was not due to increased
permeability of the confluent LEC monolayers, as permeability for FITC‐dextran was unchanged
(Figure 40 D). This indicated that CXCL10 is substantially involved in mediating transmigration
of macrophages through lymphatic endothelium. CXCL10 might regulate transmigration via
binding to CXCR3 expressed on THP‐1 macrophages, which is the counterreceptor for CXCL10
(Singh et al., 2007). Similar to TNFα, CXCL10 could be an important, yet unrecognized regulator
of immune cell trafficking in the context of persistent T2DM skin inflammation.
In summary, we could show that CXCL10 was highly upregulated in T2DM skin, possibly due to
higher levels of TNFα, as it could not be detected in non‐diabetic LECs or LECs not treated with
TNFα. Further, CXCL10 was shown to be secreted by LECs after TNFα‐stimulation. CXCL10
derived from LECs might be crucial not only for macrophage adhesion but also for chemotaxis
and transmigration in a pro‐inflammatory milieu.
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7.6 Characterization of Fatty acid binding protein 4 (FABP4) expression and function in LECs
Among the metabolically altered genes in dLECs, we detected strong upregulation of FABP4
(Table 14). Fatty acid binding proteins represent a family of lipid chaperones, which facilitate
the transport of fatty acids to different compartments of the cell, including lipid droplets,
endoplasmatic reticulum, nucleus, cytoplasm, peroxisomes or mitochondria (Furuhashi and
Hotamisligil, 2008). Additionally, they are implicated in integrating lipid signaling and
inflammatory pathways. Their expression is highly conserved as they are expressed in different
species from Drosophila melanogaster and Caenorhabditis elegans up to mice and humans
(Makowski and Hotamisligil, 2004). Fatty acid binding protein 4 (FABP4), also called adipocyte
protein 2 (aP2) is mainly expressed in adipocytes, macrophages and DCs. Its expression is highly
regulated by fatty acids, PPARγ‐agonists and insulin (Furuhashi and Hotamisligil, 2008). Its
importance in the pathogenesis of T2DM and IR was demonstrated in Fabp4 knockout mice
(Hotamisligil et al., 1996). FABP4 expression has not been reported in LECs before, although
hints exist that this gene could be important for LEC behavior, as it was reported as a potential
candidate gene involved in lymphedema (Ferrell et al., 2008).
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7.6.1 FABP4 is specifically expressed in lymphatic endothelial cells
FABP4 was upregulated in dLECs versus ndLECs. Additionally, we found it exclusively expressed
in LECs compared to BECs. This differential expression could be confirmed Western blotting
analysis (Figure 41 A). Additionally, FABP4 could be detected by immunofluorescence in
podoplanin‐positive LECs (Figure 41 B). Moreover, FABP4 co‐localized with podoplanin‐positive
LVs in human skin (Figure 41 C), whereas on a consecutive section, blood vessels stained with
endoglyx‐1 do not show FABP4 expression (Figure 41 D).
Figure 41: FABP4 is specifically expressed in LECs compared to BECs. A: Protein expression analysis of FABP4 in LECs and BECs is shown. GAPDH was used as a loading control. B: Immunofluorescent stainings of LECs with antibodies to podoplanin and FABP4 showed the strong FABP4 expression of LECs. C: Double staining of human skin with antibodies to podoplanin and FABP4 showed FABP4 expression by LVs. D: Double staining of a consecutive section using antibodies to podoplanin and endoglyx‐1, which is highly specific for BVs. This confirms that FABP4 is not expressed on BVs of human skin. Size bar: 20µm.
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7.6.2 FABP4 expression could be specifically knocked down in LECs
To analyze whether FABP4 knockdown has an impact on cell behavior, LECs were transfected
with FABP4‐specific siRNA and scrambled siRNA as control using RNAiFect. Efficient knockdown
of FABP4 expression was shown by Western blot analysis (Figure 42 A) as well as
immunofluorescent stainings (Figure 42 B).
Figure 42: siRNAmediated knockdown of FABP4 in LECs. LECs were transfected with FABP4‐specific or scrambled siRNA using RNAiFect. Knockdown of FABP4 expression was analyzed byWestern blotting (A) and immunofluorescence stainings (B).
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7.6.3 FABP4 regulates LECs proliferation
Elmasri et al. (2009) showed that FABP4 expression is induced by VEGF stimulation in HUVECs
and that it is involved in the regulation of HUVEC proliferation. In order to analyze the specific
role of FABP4 in LECs, we comparatively determined the proliferation rate of scrambled versus
FABP4 siRNA‐transfected LECs. As shown in Figure 43, proliferation of LECs was significantly
reduced in FABP4 siRNA‐transfected LECs after 96 and 144 hours (p‐value = 0.04) compared to
LECs transfected with scrambled control siRNA. However, in contrast to the findings of Elmasri
et al. (2009), we did not find induction of FABP4 expression by VEGFs (Figure 44). This suggests
that besides VEGFs other, yet unidentified factors are responsible for highly specific FABP4
expression in LECs and LVs compared to BECs and BVs.
Figure 44: FABP4 expression is not upregulated by lymphangiogenic factors. Cell lysates ofLECs stimulated with VEGF‐A, VEGF‐C and VEGF‐D were analyzed for protein expression ofFABP4. No differences of FABP4 expression were observed. GAPDH was used as a loadingcontrol.
Figure 43: FABP4 regulates LEC proliferation. LECs were transfected with FABP4‐specific or scrambled siRNA using RNAiFect and cells were counted at respective timepoints.
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7.6.4 FABP4 expression increases LEC permeability
Using these siRNA‐mediated transfection tools, we investigated whether manipulation of FABP4
expression has an impact on LEC‐LEC adhesion and on the stability of inter‐lymphatic
endothelial cell junctions by measuring FITC‐dextran permeability and transendothelial electric
resistance (TEER) of a LEC monolayer. Reduced permeability for FITC‐dextran was measured
when FABP4 expression was knocked down in LECs (Figure 45 A). In concordance with the
reduced permeability, we found increased TEER in FABP4 knockdown LECs compared to
scrambled siRNA transfected cells (Figure 45 B). These data indicate that FABP4, besides its well
established function as a fatty acid transporter in adipocytes, seems to exert important basic
cellular features in LECs.
7.6.5 FABP4 expression regulates PPARγ expression in LECs
It has been shown that peroxisome proliferator activated receptor gamma (PPARγ) regulate
FABP4 expression in adipocytes and fibroblasts (Furuhashi and Hotamisligil, 2008). Hence, we
wanted to know if this concept also applies to LECs. We transfected LECs with FABP4‐ and
PPARγ‐specific siRNAs. As shown in Figure 46, knockdown of FABP4 led to a strong decrease of
Figure 45: FABP4 regulates permeability of LEC monolayers. LECs were seeded onfibronectin (FN) coated transwell filters and grown to confluence. A: FITC‐dextran diffusion wasmeasured using an ELISA reader at λ=485‐530nm in transwells with LEC monolayers transfectedwith FABP4‐specific and scrambled siRNA and in FN coated wells only. B: Transendothelialelectric resistance (TEER) was measured using a manual electrode.
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FABP4 expression and similarly also PPARγ expression in LECs (A). Conversely, PPARγ
knockdown did not influence FABP4 expression in LECs (B).
This could indicate that FABP4 expression in LECs is driven by a rather solid differentiation‐
dependent transcriptional regulation, while PPARγ is sensitive to the presence of FABP4.
7.6.6 Possible interactions of FABP4 with PPARγ
FABPs serve as shuttle proteins for fatty acids in order to activate PPARs (Wolfrum, 2007),
which then, in concert with retinoic acid receptors, activate so‐called peroxisome‐proliferator‐
responsive element (PPREs) in genes. FABP4 was shown to directly interact with PPARγ in COS‐
7 cells (Tan et al., 2002). By functional analysis of PPRE motifs in genes of fatty acid‐binding
proteins, a direct binding of PPARγ/RXR heterodimers to PPREs in the FABP4 promoter was
demonstrated (Schachtrup et al., 2004). By this way, FABPs activate their own transcription,
regulating a positive feedback‐loop. Moreover, it was shown that treatment with the PPARγ
agonist rosiglitazone upregulated the expression of FABP4 and PPARγ (Cabré et al., 2007; Allen
et al., 2006) and a nuclear translocation of FABP4 occured (Ayers et al., 2007; Gillilan et al.,
2007), thereby possibly stimulating the interaction of FABP4 and PPARγ.
Due to the fact that FABP4 regulated PPARγ expression in LECs (Figure 46), we were interested
to know whether these two genes were interacting directly with each other in LECs. Therefore,
we performed co‐immunoprecipitations with anti‐FABP4 and anti‐PPARγ antibodies,
Figure 46: FABP4 regulates PPARγ expression in LECs but not vice versa. 5x104 LECs wereseeded into 24 well plates and transfected with FABP4‐/PPARγ‐specific siRNA as well asscrambled siRNA using RNAiFect transfection reagent. PPARγ (A) and FABP4 (B) proteinexpression was checked usingWestern blot analysis. GAPDH protein expression served as aloading control.
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respectively from whole LEC lysates. As shown in Figure 47, we could not detect any direct
interaction between FABP4 and PPARγ in either of the two immunoprecipitates. This finding
does not completely exclude an interaction of these two molecules in LECs. Rather, low amounts
of starting material, too low expression of PPARγ in LECs or too weak or too short interaction
between these proteins could be the limitations of our practical approach.
In order to see whether PPARγ protein binds to PPREs in the promotor region of FABP4 gene,
we performed ChIP assays as previously described (Gal‐Yam et al., 2008).
Figure 47: CoImmunoprecipitations of FABP4 and PPARγ. Co‐immunoprecipitation, usinganti‐FABP4 or anti‐PPARγ antibodies, from the lysates of LECs stimulated with 20µM ofrosiglitazone. The precipitates were analyzed by immunoblotting. Western blots indicate thatproteins are not interacting with each other.
Figure 48: Chromatin immunoprecipitations of PPARγ to show potential interactions withPPREs in the FABP4 promotor region. Chromatin immunoprecipitations of LEC lysatesstimulated with or without 20µM rosiglitatzone for 24 hours. Binding of PPARγ to PPREs waschecked using SybrGreen quantitative real‐time PCR and specific primer pairs. MYT1 primerwas used as negative control.
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In all of the six potential PPRE sites, except for site 6, no significant enrichment in site
amplification by quantitative PCR could be detected between unstimulated and rosiglitazone‐
stimulated LECs (Figure 48). Site 6 represents a PPRE in the core promotor region of FABP4
very near to the 5'‐UTR and the start codon of the FABP4 gene, suggesting that PPARγ
preferentially binds to this PPRE of endothelial FABP4. The primer for myelin transcription
factor 1 (MYT1) served as a negative control.
In summary, we could show that FABP4 is significantly increased in diabetic LECs. It could serve
as a new specific marker for LECs, as it is not expressed in BECs and BVs of human skin.
Moreover, it significantly influences proliferation and permeability of LECs and influences
PPARγ expression after knockdown. FABP4 could represent one important connector gene
between lipid metabolism and lymphatic vessel functioning, as it was shown that LV dysfunction
lead to lymphedema, which is associated with increased formation of adipose tissue (Rockson,
2001) and increased obesity in mice (Harvey et al., 2005).
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8. Conclusions and Future Perspectives
A final model for involvement of dermal lymphatic vessels in type 2 diabetes
1. Morphological analysis
During this thesis work, a comprehensive analysis of LVs and LECs in the skin of type 2 diabetic
patients was performed. A morphological as well as molecular characterization is presented. A
great merit is that this work boldly analyzed human tissue specimens, and it addressed a less
studied vascular system in diabetes. While endothelial dysfunction of BVs is a well‐studied
complication in T2DM, research data on how lymphatics may be altered and involved in disease
pathogenesis is barely known so far. However, skin complications associated with diabetes are
not only related to BV but additionally to LV dysfunction. LV malfunctioning may lead to wound
healing defects (Saaristo et al., 2006), increased risk for local infections (Rockson, 2001) and
formation of adipose tissue (Harvey et al., 2005).
Increased lymphatic vessel density was observed in cholesterol‐rich atherosclerotic lesions
(Kholova et al., 2010) and chronic venous insufficiency ulcers (Fernandez et al., 2011) of human
patients, suggesting causal relationships between these diseases. In contrast to newly grown
carcinoma‐associated lymphatic vessels (Vainionpää et al., 2007), we could not detect laminin
and type IV collagen expression alterations, which was consistent with unaltered lymphatic
vessel diameter and absence of hyperplasia. Although a 'so‐called' diabetic lymphangiopathy
was reported earlier (Kaufmann et al., 1980; Ohkuma, 1979), no phenotypical changes of LVs
could be found in the skin of T2DM patients, regardless of their size. We conclude that mostly
due to a completely different assembly of the vessel wall (no regular BM, no SMC coverage),
observed changes are not similar to BV changes in T2DM. Additionally, intraluminal LV pressure
is significantly lower and lymph flow rate is approximately 100‐500 times less than blood flow
rate (Swartz, 2001). However, if intraluminal pressure and lymph flow rate is changed in a
similar way than in BVs in type 2 diabetics (Calles‐Escandon and Cipolla, 2001), this would be an
interesting features to measure, although this is very difficult to conduct in humans.
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Significantly increased LV and macrophage density was found in the skin of T2DM patients.
Although controversial to previously published studies (Maruyama et al., 2007; Saaristo et al.,
2006), we suggest that this could be an intercorrelating feature, where macrophages regulate LV
density via the expression of VEGFs (Machnik et al., 2009; Maruyama et al., 2005) and possibly
also via TNFα, which has pro‐migratory and proliferative activity. It needs further investigations
to answer the question why there is increased macrophage infiltration in the skin of type 2
diabetic patients. Is it related to ischemia, to hyperglycemia or is it a result of reduced
efferocytosis due to a dysfunction of macrophages which in turn could sustain local
inflammation?
2. The dLEC transcriptome
Extensive bioinformatical and literature analysis of microarray data retrieved a long list of genes
which were dissected into different functional pathways using Ingenuity Pathway Analysis
(IPA). This led to the establishment of four overrepresented themes, comprising (Cluster A)
defense response and inflammation, (Cluster B) tissue remodeling and cell motility, (Cluster C)
lymphangiogenesis and cell fate regulation and (Cluster D) lipid handling and small molecule
transport.
We did not trace downregulation of key lymphatic differentiation markers, as was observed in
obesity and inflammation (Horra et al., 2009; Vigl et al., 2011), and we did not trace deregulation
of transcripts for lymphatic valve and junction proteins (Hämmerling et al., 2006), though
lymphatic vessels were postulated to contribute to obesity due to disrupted integrity (Harvey et
al., 2005). Rather, the overlaps with hypoxic LECs and LECs derived from skin of lymphedema
patients (Irigoyen et al., 2007; Ogunbiyi et al., 2011) emphasized a role of these candidates in
pathological lymphatic dysfunction. Further, overlaps with transcriptomes of whole tissue
lysates from nonhealing venous ulcers (Charles et al., 2008), wound inflammation (Roy et al.,
2008) and diabetic wound microbiome (Grice et al., 2010) might indicate that these specifically
derive from LECs. Therefore, we concluded that lymphatic vessels show stable LEC identity in
type 2 diabetic skin, while they manifest alterations that highlight the specific
pathophysiological microenvironment.
The functional gene sets underlined the emergence of enhanced lymphatic vessel density.
During capillary morphogenesis, LECs have to be released from their quiescent phenotype,
which is triggered by dissolution of the basement membrane and complex changes of their
migratory behaviour. Mature LECs scarcely proliferate and must re‐enter the cell cycle during
growth of new vessels from pre‐existing ones. The huge number of positive and negative
regulators of cell growth, migration, proliferation and survival suggested an activation of cellular
differentiation and survival processes in LECs in T2DM skin. The transcriptional downregulation
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of GTPase‐activating molecules might indicate relief of a quiescent LEC proliferation state, as it
was described recently for Ras GTPase‐activating RASA1 (Lapinski et al., 2012). dLECs revealed
decrease of p53‐mediated downstream effectors, hence extending their proliferation potential.
Accordingly, p53‐deficient mice show enhanced lymphangiogenesis (Ruddell et al., 2008), and
silencing of p53 signaling improved diabetic wound healing (Nguyen et al., 2010). However, the
master‐regulators dictating the concerted gene suppressions of several gene clusters remain
unknown, suggesting involvement of epigenetic, transcriptional, or microRNA‐mediated
mechanisms. Recent findings point towards such regulatory traits in diabetic endothelial cells
(Pirola et al., 2011; Cayrol et al., 2007; Zampetaki et al., 2010).
3. Mechanistic analysis that brings all findings together
In T2DM, the interstitial space of the dermis contains an overload of fatty acids, glucose, proteins
and adipogenic factors derived from the blood circulation (Tammela et al., 2010). Despite absent
regulation of adipokines or their cognate receptors in dLECs, enhanced lipid levels per se might
contribute to pathological alterations of lymphatic vessels. Dyslipidemia was associated with
dysfunctional lymphatic vessels that lead to chronic inflammatory disorders of the skin (Lim et
al., 2009). Hence, incomplete clearance of interstitial fluid and its contents might lead to
phenotypic changes similar to lymphedema like increased collagen deposition, fibrotic
alterations, and dermal swelling (Alitalo, 2011). Type 2 diabetic skin specimens showed obvious
thickening (own observation), pointing at such alterations. This might be added to the obviously
damaged skin barrier‐immune axis and underlines the paramount importance of initial
lymphatics for maintenance of skin homeostasis.
Though macrophages are essential for physiological wound healing (Mahdavian Delavary et al.,
2011), in type 2 diabetes, their increased influx has been correlated with impaired wound
healing (Wetzler et al., 2000), characterized by expression of pro‐inflammatory cytokines,
especially TNF‐α (Khanna et al., 2010). Here, we show that macrophage infiltration and TNF‐α
production is associated with human dermal pathology as well. Activated macrophages have
been recognized to directly contribute to de novo lymphangiogenesis (Kerjaschki, 2005) by (1)
production of lymphangiogenic factors and (2) conversion into LECs. However, we detected
relatively low enhancement of VEGF‐C levels, which was not significantly different between
diabetic and non‐diabetic skin, corresponding to a poor overlap with VEGF‐C responsive genes
in LECs (Yong et al., 2005), which suggested a minor contribution to the increased lymph vessel
count. Pathologic lymphangiogenesis might be driven by additional mediators such as PDGF‐BB,
HIF or FGF‐2 (Alitalo, 2011), though we did not trace altered expression of these factors or their
cognate receptors in dLECs. Rather, we provide the first confirmation of TNF‐α‐induced gene
deregulation in human LECs in vivo that is strongly correlated with a pro‐migratory LEC
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phenotype. Accordingly, enhanced TNF‐α levels were shown to drive lymph vessel remodeling
(Baluk et al., 2009).
Besides indications from murine studies (Tammela & Alitalo, 2010), in humans, enhanced lymph
vessel density was correlated with accelerated chronic wound healing (Labanaris et al., 2009)
and restoration of gut homeostasis in Crohn’s disease (von der Weid et al., 2011). However,
several reports indicate that inflammatory‐driven lymphangiogenesis leads to dysfunctional
active recruitment of macrophages to dLECs via CXCL10 chemotaxis might be indicative of such
impeded clearance, but could also be the prerequisite to lymph vessel integration. In a LPS‐
driven peritonitis model, enhanced numbers of macrophages were closely attached to newly
formed inflammatory lymphatic vessels, then directly incorporating into these (Kim et al., 2009).
It is tempting to speculate that macrophages in human patients´ skin are involved in an
analogous mechanism of lymphatic vessel expansion. This exaggerated macrophage entrapment
and de novo lymph vessel formation could lead to decreased tissue fluid, lipid and immune cell
drainage and, finally, persistent inflammation that altogether hinder skin regeneration. The
question whether exaggerated lymph vessel formation is beneficial for the skin pathology in
type 2 diabetes, has to be explored.
To summarize, we revealed that dLECs contribute to chronic inflammation, decreased defense of
infections, leukocyte recruitment, tissue remodeling and severely altered homeostasis of T2DM
skin. Figure 49 summarizes the effects evoking the altered dLEC properties, including increased
load of metabolites and macrophage influx over time, which lead to molecular alterations in
dermal LECs. LECs in T2DM skin show an unprotected, activated phenotype characterized by
increased inflammatory, migratory, lipid handling and lymphangiogenic capacity and apoptosis
resistance. A paracrine cross‐talk between macrophages and dLECs leads to increased
macrophage recruitment which might be the source of enhanced lymph vessel expansion.
Specifically, TNF‐α is a key mediator of cross talk between proinflammatory macrophages and
LECs. TNF‐α
Conclusively, the analysis of lymphatic endothelial cells from different anatomic sites and
pathological situations allows a better understanding of the mechanisms involved in lymphatic
vascular growth, function and repair, depending on the specific pathophysiological
microenvironment. Transcriptomal comparison led to the identification of a distinct gene
expression profile that characterized lymphatic vascular changes in T2DM on a molecular level,
suggesting that LECs are undergoing major changes during T2DM, including changes in vessel
permeability, lipid transport, proliferation and vessel remodelling. Importantly, the array data
underlined our morphological findings. We could show a correlation between the gene cluster
‘inflammation’ with the increased macrophage infiltration and TNFα expression. Additionally,
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mediated gene expression alterations in LECs lead to further macrophage recruitment, hence
reinforcing lymph vessel propagation and chronic inflammation.
Figure 49: Importance of lymphatic vessels in type 2 diabetic skin and the attempt of establishing a model showing their contribution, involvement and alterations in the skin of type 2 diabetic patients.
dLECs are characterized by increased tissue regeneration efforts, reflected by differentially
regulated genes asscociated with wound healing and tissue remodelling as well as the fact that
we found increased lymphangiogenesis in T2DM skin. This finding also underlined the fact that
we detected an increased number of genes implicated in lymphangiogenesis as well as increased
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survival. Moreover, it is suggested that LECs are directly and actively involved in lipid and small
molecule transport, highlighted by the differentially regulated genes in the cluster ‘lipid handling
and small molecule biochemistry’.
The data suggest that skin lymphatic vessels react actively on the multiple, metabolic as well as
inflammatory interstitial burden. Inflammatory reaction is a prominent event, as well as
cytoskeletal regulatory pathways that lead to extensive lymphatic vessel expansion and
remodelling in T2DM. Overall, dLECs seem to be actively involved in the skin alterations in the
advanced stage of T2DM skin disease. Moreover, the dLEC transcriptome could include
important marker genes for T2DM, which will lead to alternative therapies as well as future
candidate genes for regulating leukocyte adhesion and migration and potentially be crucial for
clearance of tissue inflammation in type 2 diabetic patients.
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Curriculum vitae Contact details
Private address: Blumenthalstraße 49 69120 Heidelberg, Deutschland
Working address: University of Heidelberg German Cancer Research Center (DKFZ) Institute of Pathology Helmholtz‐University‐Group "Molecular
RNA Biology & Cancer" Im Neuenheimer Feld 224 Im Neuenheimer Feld 280 69120 Heidelberg 69120 Heidelberg Email: [email protected]; [email protected]‐heidelberg.de Mobil: +49‐1577‐8408901 Personal Information
Date and Place of Birth: 22 June 1983, Lustenau/Vorarlberg, Austria Nationality: Austrian Academic Degree: Medical Doctor (MD) Education
2010present: Resident pathologist at the Institute of Pathology, University Hospital & University of Heidelberg
2010present: Postdoctoral research fellow at the Research Group "Molecular RNA Biology & Cancer" – Dr. Sven Diederichs (www.diederichslab.org) Main focus on: Identification and functional analysis of long noncoding RNAs in hepatocellular carcinoma
2007present: PhD student at the Clinical Institute of Pathology, General
Hospital and Medical University Vienna, Austria: “Molecular and functional characterization of lymphatic vessels and
lymphatic endothelial cells in type 2 diabetes mellitus”
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July – Dec 2011: Gerok stipend within the SFB TRR77 ‘Liver cancer’: Subproject B3 (Non‐coding RNAs in Hepatocellular Carcinoma), Dr. Sven Diederichs
September 2007: Research internship at the Institute of Physiology, Katowice University,
Poland “Matrix Metalloproteinases in child tumors”
20062007: MD thesis at the Neurological Research Laboratory Innsbruck: ”Matrix Metalloproteinases and their Inhibitors in Multiple Sclerosis: Correlation with Inflammation and Clinical Parameters”
20012007: Studies of Human Medicine at the Medical University of Innsbruck, Austria (Graduation: 08/2007)
Scholarships
2005: Scholarship of the Federal State of Vorarlberg for a study visit at the UniversityHospital Monterrey, Mexico
2006: Merit scholarship of the Medical University of Innsbruck
Language skills German: Mother tongue English: fluent in speaking and writing French: basic Swedish: basic Software skills Statistical software: SPSS, R Office: MS Office (Word, Excel, PowerPoint), Open Office, Adobe Creative Suite
(Acrobat, Illustrator, Photoshop), Latex, Jabref, Endnote Operating systems: Windows, Linux Other activities
Project manager: Molecular mechanisms of diabetic microangiopathy Responsible Organizer:
‐ BRIDGING THE GAP ‐ International workshop on cell communication in health and disease (February 2009 and 2010) at the Medical University of Vienna (www.phd‐cchd.at/cchd‐workshop)
Member of the Young Scientist Association (YSA) of the Medical University (www.ysa‐muv.org) and organisation of the PhD‐Symposium 2010 at the Medical University of Vienna
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Publications M. Hämmerle, T.M. Keller, B. Hantusch, D. Kerjaschki. Transcriptome analysis reveals inflammatory, growth and lipid metabolic changes of lymphatic vessels in human type 2 diabetes. In revision. T. Gutschner, M. Hämmerle, M. Eißmann, J. Hsu, Y. Kim, G. Hung, A. Revenko, G. Arun, M. Stentrup, M. Groß, M. Zörnig, A. Robert MacLeod, D. L. Spector, S. Diederichs The noncoding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. In revision. M. Polycarpou‐Schwarz, T. Gutschner, M. Hämmerle, S. Grund, A. Roth, C. Hildenbrand, A. Warth, T. Longerich, S. Aulmann, J. Rom, M. Meister, T. Muley, H. Zabeck, S. Schmidt, T. Ivacevic, V. Benes, K. Breuhahn, P. Schnabel, P. Sinn, H. Hoffmann, P. Schirmacher, S. Diederichs Defining the noncoding RNA landscape of lung, liver and breast cancer reveals concerted regulation, novel tumorassociated long ncRNAs and high tissue specificity. Submitted. M. Eißmann*, T. Gutschner*, M. Hämmerle, S. Günther, M. Caudron‐Herger, M. Groß, P. Schirmacher, K. Rippe, T. Braun, M. Zörnig* and S. Diederichs*. Loss of the abundant nuclear noncoding RNA MALAT1 is compatible with life and development. RNA Biology 2012, Aug 1;9(8). M. Zeyda, B. Wernly, S. Demyanets, C. Kaun, M. Hämmerle, B. Hantusch, M. Schranz, A. Neuhofer, B.K. Itariu, M. Keck, G. Prager, J. Wojta, T.M. Stulnig. Severe obesity increases adipose tissue expression of interleukin‐33 and its receptor ST2, both predominantly detectable in endothelial cells of human adipose tissue. Int J Obes (Lond). 2012 Jul 17. [Epub ahead of print] C. Vonach, K. Viola, B. Giessrigl, N. Huttary, I. Raab, R. Kalt, S. Krieger, TP. Vo, S. Madlener, S. Bauer, B. Marian, M. Hämmerle, N. Kretschy, M. Teichmann, B. Hantusch, S. Stary, C. Unger, M. Seelinger, A. Eger, R. Mader, W. Jäger, W. Schmidt, M. Grusch, N. Dolznig, W. Mikulits, G. Krupitza. NFκB mediates the 12(S)HETEinduced endothelial to mesenchymal transition of lymphendothelial cells during the intravasation of breast carcinoma cells. British Journal of Cancer 2011; 105(2):263‐71. D. Kerjaschki, M. Rudas, G. Bartel, Z. Bago‐Horvath, V. Sexl, S. Wolbank, C. Schneckenleithner, H. Dolznig, S. Krieger, B. Hantusch, K. Nagy‐Bojarszky, N. Huttary, I. Raab, R. Kalt, K. Lackner, M. Hämmerle, T. Keller, K. Viola, M. Schreiber, A. Nader, W. Mikulits, M. Gnant, K. Krautgasser, H. Schachner, K. Kaserer, S. Rezar, S. Madlener, C. Vonach, A. Davidovits, H. Nosaka, S. Hirakawa, M. Detmar, K. Alitalo, S. Nijman, F. Offner, T. J. Maier, D. Steinhilber and G. Krupitza. Lipoxygenase driven tumor cell invasion of intrametastatic lymphatic vessels propagates lymph node metastasis of human carcinomas. Journal of Clinical Investigation 2011; 121(5):2000‐12. M. Hämmerle, T.M. Keller, B. Hantusch, D. Stokic, C.W. Steiner, D. Kerjaschki. Transcriptomal comparison of human dermal diabetic versus nondiabetic lymphatic endothelial cells ex vivo. Wiener Klinische Wochenschrift 2008; Vol. 120 (Suppl. 1): 117. B. Kuenz, A. Lutterotti, R. Ehling, C. Gneiss, M. Hämmerle, C. Rainer, F. Deisenhammer, M. Schocke, T. Berger, M. Reindl. Cerebrospinal fluid B cells correlate with early brain inflammation in multiple sclerosis. PLoS ONE. 2008 Jul 2;3(7):e2559.
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M. Hämmerle, T.M. Keller, B. Hantusch, D. Stokic, N. Wick, E. Gurnhofer, S. Thurner, D. Kerjaschki. Transcriptomal comparison of human dermal diabetic versus nondiabetic lymphatic endothelial cells ex vivo. Der Pathologe 2008, Suppl. 1: 26 (Do‐091). B. Kuenz, A. Lutterotti, R. Ehling, C. Gneiss, M. Hämmerle, M. Schocke, T. Berger, M. Reindl. Cerebrospinal fluid B cells correlate with early brain inflammation in multiple sclerosis. Multiple Sclerosis 2008, 14 (Suppl. 1): S133‐134 (P 356). M. Hämmerle. Matrix metalloproteinases and their inhibitors in multiple sclerosis – Correlation with inflammation and clinical parameters. Medizinische Dissertation, Medizinische Universität Innsbruck. Scientific presentations
Talks: M. Hämmerle Molecular and functional analysis of long noncoding RNAs in hepatocellular carcinoma. German Society of Pathology (DGP), Berlin, Germany, May 2012 M Hämmerle. Noncoding RNA in malignant tumors: A new world of tumor biomarkers and target structures in cancer cells. German Society for Endocrinology (DGE), Mannheim, Germany, March 2012. M. Hämmerle. Molecular and Functional Analysis of long noncoding RNAs in Liver Cancer. SFB TRR77 Annual Meeting, Fulda, Germany, November 2011. M Hämmerle Noncoding RNA profiling in hepatocellular carcinoma. German Society of Pathology (DGP), Leipzig, Germany, June 2011. M. Hämmerle. Morphological and molecular characterization of lymphatic vessels and lymphatic endothelial cells in type 2 diabetes mellitus. Invited talk, German Cancer Research Center, Heidelberg, May 2010. M. Hämmerle. Morphological and molecular characterization of lymphatic vessels and lymphatic endothelial cells in type 2 diabetes mellitus. Invited talk, Institute of Pathology, Heidelberg, April 2010. M. Hämmerle. Characterization of lymphatic endothelial cells in type 2 diabetes mellitus. Hearing of the Austrian Science Fund (FWF), Vienna, May 2009. M. Hämmerle. Characterization of diabetic versus nondiabetic lymphatic endothelial cells ex vivo. '92. Jahrestagung der Deutschen Gesellschaft für Pathologie', Berlin, May 2008.
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Posters: M. Hämmerle, T. Gutschner, S. Diederichs. Molecular and Functional Analysis of long noncoding RNAs in Liver Cancer. SFB TRR77 Annual Meeting, Fulda, Germany, November 2011. M. Hämmerle, T. Gutschner, H. Uckelmann, M. Baas, K. Breuhahn, P. Schirmacher, S. Diederichs. Molecular and Functional Analysis of long noncoding RNAs in Liver Cancer. 12th Young Scientist Meeting of the German Society of Cell Biology (DGZ): "RNA & Disease", Jena, Germany, September 2011. M. Hämmerle, T.M. Keller, C.W. Steiner, D. Stokic, B. Hantusch D. Kerjaschki. Lymphatic endothelial cells and lymphatic vessels are altered by the diabetic condition. 6th PhD Symposium, Medical University Vienna, June 2010. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Characterization of lymphatic endothelial cells in type 2 diabetes. 5th PhD Symposium, Medical University Vienna, June 2009. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Characterization of lymphatic endothelial cells in type 2 diabetes. ESH: Interdisciplinary Conference on Angiogenesis, Helsinki, June 2009. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Characterization of lymphatic endothelial cells in type 2 diabetes. EMBO Workshop: Lymphatic & blood vasculature ‐ from models to human disease, Biomedicum Helsinki, June 2009. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Transcriptomal comparison of diabetic versus nondiabetic lymphatic endothelial cells ex vivo. Joint Annual Meeting of Immunology, Vienna General Hospital, September 2008. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Transcriptomal comparison of diabetic versus nondiabetic lymphatic endothelial cells ex vivo. 4th PhD Symposium, Medical University Vienna, May 2008. M. Hämmerle, T.M. Keller, B. Hantusch, C.W. Steiner, D. Haluza, D. Kerjaschki. Transcriptomal comparison of diabetic versus nondiabetic lymphatic endothelial cells ex vivo. Gordon Research Conference, Ventura, March 2008. B. Künz, M. Hämmerle, R. Ehling, A. Lutterotti, C. Gnei, K. Egger, M. Schocke, T. Berger, M. Reindl. Characterization of Cell Populations in Cerebrospinal Fluid of Patients with Multiple Sclerosis. 6. Jahrestagung der Österreichischen Gesellschaft für Neurologie, Innsbruck, February 2008. B. Künz, M. Hämmerle, R. Ehling, C. Gneiss, A. Millonig, F. Deisenhammer, T. Berger, M. Reindl. Characterization of Cell Populations in Cerebrospinal Fluid of Patients with Multiple Sclerosis. 3rd Meeting of Doctoral students from Innsbruck's Medical University, November 2007.