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Roma, 22 febbraio 2013 Highlights in the management of renal cell carcinoma

Roma, 22 febbraio 2013 Highlights in the management of renal cell carcinoma. Clinical and Molecular Predictive factors to molecularly targeted agents: what we know so far.

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Roma, 22 febbraio 2013 Highlights in the management of renal cell carcinoma

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  1. Roma, 22 febbraio 2013 Highlights in the management of renal cell carcinoma Clinical and Molecular Predictive factors to molecularly targeted agents: what we know so far.. Enrico Ricevuto, Eleonora Palluzzi Oncologia Medica Ospedale San Salvatore Università dell’Aquila

  2. Renal cell carcinoma Evolution of medical treatment Markers None “One fit (unfit) all”

  3. Renal cell carcinoma Evolution of medical treatment Parameters • None “One fit (unfit) all” • Bio-Clinical “One fit some” (>10%) • Patient fitness (age, comorbidities) • Tumor prognostic risk • Drugs prediction (safety/toxicity, efficacy)

  4. ccRCCPredictive markers of target therapy • Bio-Clinical • Hypertension (>90 mm/hg DBP) • LDH • Hypothiroidism (increased TSH)

  5. Hypertension Biomarker of Efficacy with Sunitinib B Rini, J Natl Cancer Inst 2011; 103:763-773.

  6. Diastolic blood pressure Biomarker of efficacy with axitinib in solid tumors OS with landmark at 8 weeks. B Rini, Clin Cancer Res; 17(11); 3841–9.2011

  7. Serum LDH Biomarker with Temsirolimus Andrew J Armstrong et al, J Clin Oncol 30:3402-3407. 2012

  8. Hypothyroidism (increased TSH)Biomarker of activity with TKI in solid tumors Objective Remission According to Response Evaluation Criteria in Solid Tumors Based on Increased Thyroid-Stimulating Hormone Levels Schmidinger M, Cancer 2011

  9. Hypothyroidism (increased TSH)Biomarker of efficacy with TKI in solid tumors Schmidinger M, Cancer 2011.

  10. Renal cell carcinoma Evolution of medical treatment Markers • None “One fit (unfit) all” • Clinical “One fit some” (>10%) • Monogene “One fit few” (1-10%) • VHL • Other genetic alterations • Heterogeneity (tumor/metastasis) • VHL/HIF epigenetics alterations

  11. Renal Cell carcinomaDifferent diseases Different histology Different genes Different clinical courses Different response to therapy

  12. Renal Cell CarcinomaPathology Clear cell (75-85%) Proximal tubule origin Abnormalities in chromosome 3p Chromophilic (15%) 85% of these are diagnosed as stage I tumors Also proximal tubule in origin, but 3p is normal Trisomy 12, 16, 20 can be seen Chromophobic (5%) Oncocytic (uncommon) usually not aggressive Collecting duct origin 11q13 rearrangements in some cases Collecting duct (Bellini’s duct) tumors – very rare Unclassifiable (<3%) – worse prognosis

  13. Renal Cell CarcinomaMorphology and Genetics

  14. Renal Cell carcinoma Disease of cell metabolism: Biomolecular Complexity Pathways that respond to metabolic stress or nutrient stimulation VHL oxygen and iron sensing MET LKB1-AMPK energy sensing FLCN binds AMPK and might interact with the cellular energy and nutrient sensing TSC1 downstream of AMPK and negatively regulates mTOR in response to TSC2 cellular energy deficit FH central role in the mitochondrial tricarboxylic acid cycle SDH coupled to energy production through oxidative phosphorylation

  15. pVHL targets hypoxia-inducible factor (HIF)-α for ubiquitin-mediated degradation

  16. Sporadic ccRCCGenetic alterations of the VHL gene LOH 3p 24-25 78-96% Intragenic mutations 51-71% Hypermethylation 5-20% Biallelic loss 50-75% Sukosd et al, Canc Res’03, 63, 455 Kondo et al, Gene Chrom Cancer’02, 34, 58-68 Banks et al, Canc Res’06, 66, 2000-11

  17. Spectrum of VHL mutationscumulative data of 1244 mutations reported in the literature Young A et al, Clin Canc Res’09, 15; 7582

  18. RCCSpectrum of VHL gene alterations Young A et al, Clin Canc Res’09, 15; 7582

  19. VHL genetic alterationsPrognostic relevance Young A et al, Clin Canc Res’09, 15; 7582

  20. Choueiri et al, J Urol. 2008; Rini BI, et al. BJU Int. 2006

  21. Choueiri et al, J Urol. 2008; Rini BI, et al. BJU Int. 2006

  22. Klatte et al, Clin Canc Res’07

  23. Metastatic ccRCCHeterogeneity Gerlinger M et al, N Engl J Med 2012;366:883-92

  24. Metastatic ccRCCHeterogeneity Gerlinger M et al, N Engl J Med 2012;366:883-92

  25. Expanded HIF signal output activates mediators of metastasis CXCR4 expression correlates with poor prognosis and metastasis in ccRCC and is inducted by VHL loss. Vanharanta S et al, Nature Medicine 2013

  26. DNA demethylation allows CYTIP expression in metastatic ccRCC Vanharanta S et al, Nature Medicine 2013

  27. Current renal cell carcinoma biomarker initiatives EuroTARGET SCOTRRCC Predict Consortium TCGA CAGEKID Vasudev et al. BMC Medicine 2012, 10:112

  28. Renal cell carcinoma Evolution of medical treatment Markers • None “One fit (unfit) all” • Clinical “One fit some” (>10%) • Monogene “One fit few” (1-10%) • Multigenes “One fit one” (<1%) • Multiple biopsies • Genetic and epigenetic alterations

  29. Multiple drugs • anti-angiogenesis • mTOR-inh • Need of drugable and actionable targets

  30. mRCCAngiogenesis inhibitors Sonpavde G Exp Opin Invest Drugs 2008

  31. mTOR inh image

  32. Why should we need clinical and biological markers? • Individual tumor heterogeneity • differential clinical outcome • aggressiveness • efficacy • OS • differential biology

  33. Biological heterogeneity • Genetic alterations 1 2 3 4 • VHL M M M M

  34. Metastatic ccRCCHeterogeneity Gerlinger M et al, N Engl J Med 2012;366:883-92

  35. Open question • Multiple biopsies

  36. Hand-foot syndrome (HFS) as a potential biomarker of efficacy in patients (pts) with metastatic renal cell carcinoma (mRCC) treated with sunitinib. Methods: Analyses included pooled data from 770 pts who received single-agent SU as 50 mg/d on a 4-week-on/2-week-off schedule (n=544; 71%) or 37.5 mg continuous once-daily dosing (n=226; 29%). Median PFS and OS were estimated by Kaplan-Meier methods and compared between pts with vs without HFS using a log-rank test. ORR was compared by Pearson's chi-square test. Tumor response was assessed by investigators and adverse events were recorded regularly. Multivariate and time-dependent covariate analyses were performed. Results: Of 770 pts, 179 (23%) developed any-grade HFS, compared with 591 (77%) who did not. Most instances of HFS (63%) initially occurred during the first 3 treatment cycles. Pts who developed HFS had significantly better ORR (55.6% vs. 32.7%), PFS (14.3 vs. 8.3 mo), and OS (38.3 vs. 18.9 mo) than pts who did not develop HFS (p<0.0001). In a multivariate analysis, SU-associated HFS remained a significant independent predictor of both PFS and OS (and of OS by time-dependent covariate analysis). Conclusions: In mRCC pts, SU-associated HFS was significantly and independently associated with improved clinical outcomes. Overall, pts who did not develop HFS still had substantial benefit from SU. However, the presence of HFS identified a subset of pts that manifested highly favorable efficacy results with SU. These findings suggest that development of HFS may serve as a predictive biomarker of SU efficacy, although prospective validation is warranted. Michealson MD, J Clin Oncol 2011; 29 abstract 320..

  37. Renal Cell carcinoma Disease of cell metabolism Pathways that respond to metabolic stress or nutrient stimulation VHL oxygen and iron sensing MET LKB1-AMPK energy sensing FLCN binds AMPK and might interact with the cellular energy and nutrient sensing TSC1 downstream of AMPK and negatively regulates mTOR in response to TSC2 cellular energy deficit FH central role in the mitochondrial tricarboxylic acid cycle SDH coupled to energy production through oxidative phosphorylation

  38. ccRCCPrognostic and Predictive Biomarkers • DNA RNA Protein • FISH MutationsIHC Elisa Western • VHL X • HIF1 alfa X • CAIX X • VEGF X • sVEGFR-2 X • TIMP-1 X • Ras p21 X

  39. Bui, Clin Canc res’03 Atkins et al, Clin Canc Res’05

  40. VHL genotype in ccRCC • Structural alteration Point mutations • Methylation • Prevalence of mutations 60% • Functional relevance Gain of function • Diagnostic strategy Direct Sequencing • Scanning for unknown mutations • Clinical implications Predictive anti-VEGF

  41. VHL geneStructural Features • Chromosomal locus 3p24-25 • Exons 3 • mRNA 4.7 kb. • Proteins pVHL30 213 aa. (28-30 KD) • pVHL19 160 aa. (18-19 KD)

  42. Hypoxia-inducible factor (HIF)-α Transcriptional activity: Pathways and Genes • Energy metabolism: increase in glycolytic pathway • Glut-1 • Angiogenesis • VEGF VEGFR PDGF • Ang-2 FGF Tie-2 • PH regulation • CA IX • Proliferation • TGF-alfa/beta CXCR • IGF • Apoptosis • p53 NIX BNIP-3 • Erythrocitosis • EPO

  43. Hypoxia-inducible factor (HIF)-α Transcriptional activity: Pathways and Genes Energy metabolism: increase in glycolytic pathway Glut-1 Angiogenesis VEGF VEGFR PDGF Ang-2 FGF Tie-2 PH regulation CA IX Proliferation TGF-alfa/beta CXCR IGF Apoptosis p53 NIX BNIP-3 Erythrocitosis EPO

  44. Renal Cell CarcinomaEvidence for VHL initiation • Both sporadic and VHL disease-associated ccRCC display loss of VHL • HIF activation is found in early renal lesions including cysts and dysplasias • Features of ccRCC are consistent with overexpression of HIF target genes and pathways

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