1. Pitié-Salpêtriètre Hospital Assistance-Publique Hôpitaux de Paris
Molecular Genetics for the Practicing Physician: Can the Cancer Genome Atlas Impact How We Treat Patients?
Gabriel G. Malouf, MD, PhD
Assistant Professor
Pitié-Salpêtriètre Hospital
Assistance-Publique Hôpitaux de Paris
Paris, France
Many thanks to the organizing committee for the opportunity to present this talk, entitled “Molecular Genetics for the Practicing Physician: Can the Cancer Genome Atlas Impact How We Treat Patients?

2. Outline Cell of Origin of Kidney Tumors
Diagnostic Markers and Therapeutic Targets
Predictive Biomarkers

3. Renal Cell Carcinoma is NOT a Single Disease
Mucinous tubular &
spindle cell RCC
Clear cell RCC
Papillary RCC
Chromophobe RCC
Translocation RCC
Type 1
Type 2
Collecting Duct RCC

4. The Cancer Genome Atlas (TCGA) Project (2006-2016)
Clear-cell RCC (n=417)
Papillary RCC (n=161)
Chromophobe (n=66)
TCGA, Nature Genetics, 2013

5. Practicing Physicians
Pathologist
Urologist
Radiologist
Medical Oncologist
Radiation Oncologist
Comorbidities
Optimal therapy to improve survival and quality of life
Clear-cell RCC1
Chromophobe RCC2
Papillary RCC3
Tumor biology
Molecular Genetics
TCGA
Practicing Physicians
Patients
1TCGA, Nature, 2013
2Davis C et al, Cancer Cell, 2014
3Linehan WM et al. NEJM, 2015

6. I. Cell of Origin of Kidney Tumors

7. Hierarchical Clustering of Gene Expression in Kidney Structure
Proximal tubules
Glomeruli
Distal Convoluted tubules
Thick ascending limbs of
the loop of Henle
Distal nephrons
cTAL = cortical TAL, mTAL =medullary TAL, DCT= distal convoluted tubules, CNT= connecting tubules, OMCD = outer medullary collecting ducts
Cheval L et al. Physiol. Genomics, 2010

8. DNA Methylation and Gene Expression Differences Between ChrRCC and ccRCC
CCD = cortical collecting ducts; ccRCC = clear cell renal cell carcinoma; chRCC = chromophobe renal cell carcinoma; cTAL = cortical thick ascending limbs of the loop of Henle; DCT = distal convoluted tubules; Glom = glomeruli; mTAL =medullary thick ascending limbs of the loop of Henle; OMCD = outer medullary collecting ducts; TCGA = The Cancer Genome Atlas.
Davis C et al, Cancer Cell, 2014

9. Survival Prediction of Clear-cell Renal Cell Carcinomas Based on Gene Expression Similarity to the Proximal Tubule of the Nephron
Clustering of renal Cancer-specific survival (CSS) of clear cell renal cell carcinoma (ccRCC) tumours predicted by the S3-score
Clustering of renal cell carcinoma (RCC) tumours by means of gene expression correlation between profiles of tumours and profiles of human nephron cell types
Büttner et al, Eur Urol, 2015

10. DNA Methylation Establishes the Foundation of RCC Ontogeny
Malouf GG et al, ASCO GU 2016

11. II. Diagnostic Markers and Therapeutic Targets

12. Incidence of Fusion Transcripts Detected in TCGA Clear-cell RCC
TCGA KIRC dataset
(n=460)
No Translocation* (n=379)
Translocation (n=81) (17.6%)
MITF family RCC
(n=7) (1.9%)
Previously known gene fusions
(n=12)
Novel fusions
(n=62)
PRCC/TFE3 (n=5)
KHSRP/TFE3 (n=1)
KHDRBS2/TFEB (n=1)
FHIT (n=2), SLC9A9 (n=2), AFF1 (n=1), MKL1 (n=1), LHFP (n=1), JAK2 (n=1), ELL (n=1), DCX (n=1), EP300 (n=1) & LNP1 (n=1)
Figure 2
Malouf GG et al. Clin Cancer Res, 2014

13. Incidence of Fusion Transcripts Detected in TCGA Papillary RCC
TCGA KIRP dataset
(n=161)
No Translocation* (n=144)
Translocation (n=17) (10.6%)
Non MITF family RCC
(n=9)
MITF family RCC (n=8)
7 out of 60 Papillary Type II (11.6%)
1 out of 101 Papillary type I (1%)
Figure 2
Linehan WM et al. NEJM, 2015

14. A Subgroup of Papillary RCC Manifests a CpG Island Methylator Phenotype (CIMP) and FH Mutations
Linehan WM et al. NEJM, 2015

15. ChRCC with Eosinophilic Variants Resemble Oncocytoma Type II
Davis C et al, Cancer Cell, 2014
Joshi et al, Cell Reports, 2015

16. Putative Therapeutic Targets in Clear-cell RCC
TCGA, Nature, 2013

17. Putative Therapeutic Targets in Papillary RCC
Linehan WM et al. NEJM, 2015

18. III. Predictive Biomarkers

19. TCGA Transcriptomic Classification of ccRCC
Four subgroups
Response to sunitinib
TCGA, Nature, 2013
Beuselinck, Clin Cancer Res, 2015

20. Overall Survival in Two Independent Datasets of ccRCC
HR= hasard ratio.
UT South Western cohort
TCGA cohort
Kapur P et al, Lancet Oncol, 2013

21. While Many Biomarkers Are Associated in Univariate Analysis with Outcome in TCGA Clear-Cell RCC, only ccB Remains in Multivariate Analysis
Clinical and pathological charecteristics
Somatic mutations
Somatic copy number expression
Gene expression analysis
Gulati S et al, Eur Urol, 2014

22. Tumor-based Biomarkers Confounded by Intratumor Heterogeneity
63-69% of all mutations not detectable across regions in same tumor
Gerlinger et al. NEJM, 2012

23. Multi-Region Sequencing of Clear-cell Renal Cell Carcinoma
How to move from studying universality to assess variability and take it in account to personalize patients therapy

24. Multi-Region Sequencing of RCC with IVC Thrombus

25. Long-non coding RNA Classification of ccRCC Reveals Four Subtypes Associated with Clinical Outcome
Malouf GG et al, Molecular Oncology , 2015

26. CIMP Defines a Subtype of Clear-cell Renal Cell Carcinomas with Poor Outcome
Cluster 1: CpG Island Methylator Phenotype (CIMP) low; Cluster 2: CIMP negative; Cluster 3: CIMP positive
Malouf GG et al, Unpublished

27. Conclusions
Understanding ontogeny of different RCC subtypes will provide insights on tumorigenesis
To date, there are no approved biomarkers to predict recurrence after nephrectomy or response to therapy
Frequent mutations in chromatin modifying genes in both ccRCC and pRCC imply a role for epigenetic therapy

28. Conclusions (continued)
Inter- and intra-tumoral genetic heterogeneity might hamper the development of predictive and prognostic genetic biomarkers in RCC
Mutational Convergence in chromatin modifying genes highlights the importance of epigenetic drift in the evolution of aggressive RCC clones
Epigenetic biomarkers might be more stable and therefore should be pursued for precision medicine

29. Acknowledgements Pitié-Salpêtrière Hospital, Paris, France
Pr David Khayat (Oncology)
Pr Jean-Philippe Spano (Oncology)
Dr Haide Boostandoost (Oncology)
Pr Eva Compérat (Pathology)
Pr Morgan Rouprêt (Urology)
Dr Jérôme Parra (Urology)
Dr Christophe Vaessen (Urology)
Fondation AVEC laboratory, Paris, France
Dr Roger Mouawad, PhD
Frédérick Allanick, Ms
Dr Souheyla Bensalma, PhD
Dr Linda Denaise, MD, PhDc
Dr Marion Classe, MD, PhDc
Dr Ronan Flippot, MD, MS
Temple University, Philadelphia, USA
Jaroslav Jelinek
Jean-Pierre Issa
MD Anderson Cancer Center, Houston, USA
Pr Nizar M. Tannir (Medical Oncology)
Dr Xiaoping Su (Bionformatics)
Dr Hui Yao (Bionformatics)
Dr Jose A. Karam (Urology)
Pr Christopher G. Wood (Urology)
The patients and their families