Personalizzazione della terapia medica · Personalizzazione della terapia medica Francesco Massari U.O.C. di Oncologia Medica d.U. ... Netrofilia Calo ponderale Sintomi Istotipo Età

Personalizzazione della terapia medica

Francesco MassariU.O.C. di Oncologia Medica d.U.

Azienda Ospedaliera Universitaria Integrata – Verona

2nd YOUNG SPECIALIST RENAL CARE – Verona, 06 Marzo 2015

The quest for precision cancer medicine

The Right Dose ofThe Right Dose of

The Right Drug forThe Right Drug for

The Right Indication forThe Right Indication for

The Right Patient atThe Right Patient at

The Right TimeThe Right Time

Treatment for mRCC ‐ Decision‐making Algorithm

Prognostic FactorsPrognostic Factors Predictive FactorsPredictive Factors

Risk assessmentRisk assessment Proportional benefit

Proportional benefit

Absolute benefitAbsolute benefit

Toxicities (short and long term)


Patient Characteristics and preference


Treatment for mRCC

Precision Medicine: Prognostic and Predictive Factors

Definition Aim

Prognostic Factors

Provide information on outcome regardless of therapy

To spare unnecessary treatments

Predictive Factors

Provide information on probability of benefit or toxicity from a specific therapy

To spare ineffective treatments

Prognostic Factors in mRCC

Patient Factors

Performance StatusSymptoms

ProinflammatoryMarkers

IL‐6ESR

NeutrophiliaThrombocytosis

C‐reactive proteinTumor Burden

Prior nephrectomySites of metastasesBone MetastasesLDHAnemiaCalciumSodium

Treatment‐relatedFactors

Prior therapyPrior radiotherapy

Disease‐free intervalDiagnosis to treatment interval

Patient X

Patient Y

Patient Z

SURVIVAL

Necrosi tumorale

Tempo dalla diagnosi al trattamento

LDHN° siti

metastaticiTerapie di

combinazione

Sedi di metastasi

Emoglobina Nefrectomia

Presenza di neutrofili intratumorali

Calo ponderaleNetrofilia

IstotipoSintomi

Età

Invasione del grasso perirenale

Grading

Presenza di segni di Infiammazione

Differenziazione sarcomatoide

Ipercalcemia

MultifocalitàPregressa chemioterapia

Albumina basale SessoTNM

Tempo alla metastatizzazione

Livelli TSH

Basso n° CD57+ intratumorali

Piastrinosi

Fosfatasi alcalina

Precedente RT

Dimensioni tumore

Metastasectomia

Trombosi cavaleKPS/ECOG

Courtesy of M. Santoni

Necrosi tumorale

Tempo dalla diagnosi al trattamento

LDHN° siti

metastatici

Terapie di combinazione

Sedi di metastasi

Emoglobina

Nefrectomia

Presenza di neutrofili intratumorali

Calo ponderale

Netrofilia

Istotipo

Sintomi

Età

Invasione del grasso perirenale

Grading

Presenza di segni di Infiammazione

Differenziazione sarcomatoide

Ipercalcemia Multifocalità

Pregressa chemioterapia

Albumina basale Sesso

TNM

Tempo alla metastatizzazione

Livelli TSH Basso n° CD57+ intratumorali

Piastrinosi

Fosfatasi alcalina

Precedente RT

Dimensioni tumore

Metastasectomia

Livello/presenza Trombosi cavale

Alterazioniematochimiche

Caratteristiche del tumore

Stadiazione Trattamento Paziente

KPS/ECOG


Risk Criteria Can Provide Prognostic Information

Risk Criteria for VGFR‐targeted therapy(Prognostic factors for poor OS)

KPS <80Diagnosis to therapy <1 year

Hemoglobin < lower limit of normalCorrected calcium > upper limit of normal

Neutrophils > upper limit of normalPlatelets > upper limit of normal

0 factors: Favourable risk1‐2 factors: Intermediate risk

≥3 factors: Poor risk

Heng DYC et al. J Clin Oncol. 2009;27:5794‐9.

Heng Prognostic Model [Targeted Agents Age]

Favorable 43 mons

Intermediate 23 mons

Poor 8 mons

IMDC in non‐clear cell RCC

Kroeger et al., Cancer 2013

IMDC in 2nd line targeted therapy

Ko et al., GU Cancer Symposium 2014

Risk Stratification does not predict response to therapy

Predictive biomarkers are needed to better guide treatment selection

Favourable Intermediate Poor

Retrospective analysis of patients with mRCC treated with initial anti‐VEGF therapy

Stratification of patients who had PD as best response by Heng risk group

Heng DY et al. J Clin Oncol. 2011;29(suppl 7):305.

Category Markers

Adhesion molecules cadherin‐6, E‐cadherin, MUC1‐EMA, ICAM‐1, VCAM‐1, ELAM‐1, KSA)

Inducers of immune‐suppression

HLA class 1, IL‐6, IL‐8, IP‐10, MIG, MIP1, B7‐H1, B7‐H4, CD44

Growth factors receptors VEGFR‐3, TGFR‐II

Hypoxia‐induced molecules CAIX, CAXII, CXCR‐4, HIF‐1, VEGF, IGF‐I

Markers of proliferation Ki‐67, PCNA, Ag‐NORs

Cell cycle regulatory proteins p53, bcl‐2, PTEN, cyclin A, Akt, p27

Others VHL, mTOR, ribosomal protein S6, survivin, IMP3, caveolin‐1, PCR, vimentin, fascin, seric amiloide A, NGAL, IGF‐1

Table courtesy of G. Tortora

Renal cell carcinoma

Primary refractory10‐20%

Late relapsing10‐13%

Poor risk15‐25%

Intermediaterisk

50‐70%

Good risk10‐20%

Clear cell RCC 70%

Non‐Clear cell RCC 30%

Papillary type I 9%

Papillary type II 6%

Chromophobe 4‐5%

Oncocytoma 3‐5%

Xp11 traslocation

Associated to neuroblastoma

Tubulocystic

Neuroendocr. tumors

Mesenchymal

Ducts of Bellini <1%

Tubulo‐papillary

t(6,11) traslocation

Mucinous tubular

Her. leiomyomathosis

Unclassified

Tubulocystic

«Poor»poor risk45%

Interm. poor risk40%

«Good»poor risk 15%

PrognosisResponse to TKIs

Slow progressor


APPROPRIATENESSfrom Histology to molecularly characterized diseases

Modified by M. Brunelli

RCC ‐ HISTOTYPES

• New renal histotypes:

• CLEAR CELL PAPILLARY RCC

• TUBULOCYSTIC CARCINOMA

• ACQUIRED CYSTIC DISEASE (ACD)‐ASSOCIATED RCC

• TANSLOCATION RENAL CELL CARCINOMAs

• THYROID‐LIKE FOLLICULAR CARCINOMA

• Hybrid oncocytic chromophobic tumor

Clear cell papillary RCC

Promise: Progress in Genome Sequencing

Pasche B, Absher D. JAMA. 2011;305:1596.

MR Stratton et al. Nature 458, 719‐724 (2009) doi:10.1038/nature07943

Circos Plots

Promise: Progress in Genome Sequencingc ‐ RCC

The Cancer Genome Atlas Research Network; Nature 2013, doi:10.1038/nature12222

Linehan WM, et al. In: Cancer: Principles and Practice of Oncology. 2006:1139‐1140.

BHD = Birt‐Hogg‐Dubé

FH = Fumarate hydratase

VHL = von Hippel‐Lindau

Clear cell (75%)

Gene: VHL

Papillary Type 2 (10%)

Gene: FH

Papillary Type 1 (5%)

Gene: C‐Met

Chromophobe (5%)

Gene: BHD

Other

Gene expression

A lot of new genes: SEDT2, PBRM1, BAP1, KMD61, NF2…

Promise: Progress in Genome Sequencing ‐ RCC

AA Hakimi et al. Nature Genetics 2013, 45(8), 849‐850

BAP1 and PBRM1 are mutually exclusive

Peña‐Llopis S et al. Nat Genetics 2012

BAP1 activity in RCC

Santoni M, Massari F ‐ submitted

Lancet Oncol 2013; 14: 159–67

BAP1 and PBRM1 as prognostic factor for OS

Genomic signatures are coming for RCC

Escudier at 2014 ASCO Annual Meeting

From Precision Oncology to Personalized Cancer Medicine

“If it were not for the great variability among individuals, medicine might have well been a science and not an art”

Sir William Osler, 1892










Treatment for mRCC

Patient Characteristics

Patient Characteristics

Treatment for cancer: the elements of the risk/benefit equation

Modified by PF Conte

Cancer and Comorbidities: A Complex Relationship

Modified by PF Conte

mRCC: therapeutic targets ‐ 2009

Kaelin WG. Nat Rev Cancer 2002;2:673–82

VHL HIF=

VEGFR EGFRPDGFR

Raf

mTOR

SorafenibSunitinibPazopanib SorafenibSorafenib

Temsirolimus

Everolimus

Bevacizumab

mTOR = mammalian target of rapamycinEGFR = endothelial growth factor receptorVEGFR = VEGF receptor; PDGFR = PDGF receptor

Raf

PDGFVEGF TGF‐α

mRCC: therapeutic targets ‐ 2015

Santoni M. et al, Int J Cancer 2013

IMMUNOTHERAPY

The host’s immune function:

1. can control tumor growth

2. can be stimulated

•Melanoma

•Renal cell carcinoma

mRCC: Targeted Immunotherapy

Massari F, Santoni M, Ciccarese C and Santini D, EOBT 2015 ‐ submitted

PD‐1 Blockade as a Strategy for Cancer Immunotherapy

Okazaki T. et al, Nat Immunol 2013, 14:1212–1218

Blocking PD‐1/PD‐1L in RCC tumor microenvironment

Massari F, Santoni M, Ciccarese C. et al, Cancer Treat Rev 2015

CLINICAL ACTIVITY AND SAFETY OF ANTI‐PROGRAMMED DEATH‐1 (PD‐1) (BMS‐

936558/MDX‐1106/ONO‐4538) IN PATIENTS (PTS) WITH PREVIOUSLY TREATED, METASTATIC

RENAL CELL CARCINOMA (MRCC)

• BMS‐936558 is a fully human monoclonal antibody that blocks the PD‐1 co‐inhibitory receptor expressed by activated T cells.

• In the initial portion of a phase 1 study, BMS‐936558 showed promising activity in pts with various solid tumors, including mRCC.

McDermott DF et al, ESMO 2012, abs 784O

Topalian SL, NEJM 2012

CTLA‐4 pathway PD‐1 pathway

Expressed only on T‐lymphocytesExpressed on T, B‐lymphocytes, NK

cells

Ligands: B7.1 (CD80), B7.2 (CD86)Ligands: PD‐L1 (B7‐H1), PD‐L2 (B7‐

DC)

Ligands expressed only on APC cellsLigands expressed on APC and

tumour cells

CTLA‐4 blockade increases CD4+ and CD8+ T cells proliferation

PD‐1/PD‐L1 blockade especially increases CD8+ T cells proliferation

(> CD4+ T cells)


Does PD‐L1 expression alone reliably predict responders?

PROBABLY NOT!!


Issues With PD‐L1 as a Biomarker

• PD‐L1 negativity an unreliable biomarker

Assays are technically difficult, imperfect; results may

differ depending on the antibody/assay (tumor vs

immune cells)

5% expression, tumor heterogeneity, and inducible gene

= sampling error (false negative)

Archived tissue different than recent biopsy

• PD‐L1 expression may be less relevant for combination

therapies

• PD‐L1 expression might be constitutive (no immune

infiltrate)

BMS Phase III Study

Eligibility criteria

• Advanced clear cell or a component of clear cell mRCC

• Progression on or after most recent therapy and within 6 months of study enrollment

• 1 or 2 prior anti‐VEGF• NO prior mTOR inhibitor

Nivolumab 3 mg/Kg IV Q 2wks

Everolimus 10 mg/day PO

RANDOMISATION

N= 822

Primary end point: Overall Survival

Hypoxia triggers increase in cMET expression and activity:

Cell invasion and migration

Cell proliferation

Cell survival

Inhibition of cMET may help overcome acquired resistance to the VEGF pathway

Dual inhibitors of cMET and VEGFr2 such as Cabozantinib are active

MET and Acquired Resistance to VEGFMET and Acquired Resistance to VEGF‐‐targeted Therapies targeted Therapies

Aftab DT et al. Clin Transl Oncol, 2011; 13: 703‐9

Lancet Oncol 2013; 14: 81–87

Patients with localised renal‐cell carcinoma and the MET polymorphism rs11762213 might have an increased risk of recurrence after nephrectomy

cMET expression in clear cell RCC

Courtesy of Bin Teh

CABOZANTINIB (XL 184) CABOZANTINIB (XL 184) in Patients with Metastatic, Refractory RCC

Choueiri T et al. J Clin Oncol 30, 2012 (suppl; abst 4504)

Relapsed or refractory mRCC (N= 25)

• No limit on prior therapies• ECOG PS 0‐1• Measurable disease

CABOZANTINIB140 mg daily(+ single dose rosiglitazone)

Rationale:‐ Drug‐drug interaction study at Phase 1 defined MTD (140 mg)‐ Dose reductions could be employed to optimize tolerability

Study endpoints:‐ Safety and tolerability of cabozantinib‐ Antitumor activity of cabozantinib

Choueiri T et al. J Clin Oncol 30, 2012 (suppl; abst 4504)

CABOZANTINIB (XL 184) CABOZANTINIB (XL 184) in Patients with Metastatic, Refractory RCC

METEOR Study

Primary end point: PFS


• Advanced clear cell or a component of clear cell mRCC

• Progression on or after most recent therapy and within 6 months of study enrollment

• 1 or 2 prior anti‐VEGF• NO prior mTOR inhibitor

Cabozantinib 60 mg/day PO

Everolimus 10 mg/day PO

RANDOMISATION

N= 650

ALLIACE/CALGB Phase II study

Primary end point: PFS


• Locally advanced or metastatic RCC

• No prior systemic treatment

Cabozantinib 60 mg/day PO

Sunitinib 50 mg/day (4/6w)

RANDOMISATION










Treatment for mRCC

Patient’s preferencePatient’s preference

Who are our patients?

Conclusions

Personalized cancer medicine requires diagnostic and therapeutic options developed according to the individual tumor and patient characteristics, acknowledging that:

•not all the patients require the BEST treatment;

•the BEST treatment is not necessarely so for all the patients;

•the tradeoff between efficacy and toxicity is quite individual

Personalizzazione della terapia medica · Personalizzazione della terapia medica Francesco Massari U.O.C. di Oncologia Medica d.U. ... Netrofilia Calo ponderale Sintomi Istotipo Età

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