EPIDEMIOLOGIA Y FACTORES DE RIESGO

2. EPIDEMIOLOGIA Y FACTORES DE RIESGO CANCER DE RIÑON Prof. Dr. L. M. Antón Aparicio C.H.U. A Coruña

3. EPIDEMIOLOGY

4. DEMOGRAPHIC ASPECTS • Accounts for 2% all new cares worldwide • Twice as common men vs women • Mean age at diagnosis early 60s • Incidence rates rising each year EU & USA ↑ incidental finding improved imaging technology ↑ incidence of late-stage has been observed ↓ autopsies • Incidence rates age/race adjunted white (m/w) black (m/w). 13.8/6.6 16.8/8.0 • International rate↑ variability ↑ role for exogemous risk • Internacional incidence (Figure)

5. 2002 RCC World Incidence and Mortality Rates, Stratified by Region Northern America Australia/New Zealand Western Europe Central and Eastern Europe Northern Europe Southern Europe Central America South America Western Asia Caribbean World Regions Southern Africa Eastern Asia Polynesia Southeastern Asia Northern Africa Renal cancer incidence Micronesia East Africa Renal cancer mortality Melanesia South Central Asia Middle Africa Western Africa 0 1 2 3 4 5 6 7 8 9 10 Rates per 100,000 Ries LAG, et al. SEER Cancer Statistics Review, 1975-2002.

6. RISK FACTORS (I) • GENERAL - Sporadic vs familial forms (two to fourfold) - Different types of genetic predispositions - Case – Control / Cohort studies (Table I & II) • CIGARETTE SMOKING - Meta-analysis (m vs w) smokers 1.5 1.2 relative risk 2.0 1.6 increased risk • OBESITY - ↑ 1.07 per unit /body massrelative risk - Mechanism unknown - Hormonal change steroid hormonal IGF-I - Lipid peroxidation DNA adducts • HYPERTENSION - Hypertension ranging 1.3 to 2 relative risk - Mechanism unknown - renal injury

7. RISK FACTORS (II) • ANALGESIC / DIURETICS / ANTI-HYPERTENSIVES - Phenacetin containing drug ?? - ASS derivates ?? - Hydrochlorothiazide / Furosemide ?? • DIETARY FACTORS - Protein / alcohol consumption ¿? - Fruit / vegetable consumption protective effects • HORMONAL / REPRODUCTIVE FACTORS - Oral contraception ¿reduced risk? - Hysterectomy / ophorectomy in consistent - Menarche / menopause not affect risk • OCCUPATION - Jobs / industries asbestos ¡! petroleum works ¿? solvent trichloro ethylene ?? • TRANSPLANTION / DIALISIS - Duration of dialysis increased risk - Mechanism of action acquired renal cystic disease

8. PROGNOSTIC FACTORS (I)

9. PROGNOSTIC FACTORS (II) • ANATOMIC FACTORS

10. PROGNOSTIC FACTORS (III) HISTOLOGIC FACTORS • Histologic morphology5-year cancer-specific survival Main subtypes Clear cell 70%-80% 68% Papillary 10% 15% (type 2 more aggressive) 87.4% Chromophobe 5% 86.9% Collecting duct 1% (Medullary Ca. Poor prognosis) • Tumor necrosis Incidence Clear cell 28% Papillary 47% Chromophobe 20% Independent predictor of survival (twice the risk of death) Indipendent predictor of poor out come (clear cell risk ratio 1.95) • Microvascular invasion Indicence 25% to 28% Independent predictor of disease recurrence Independent predictor of cancer-specific survival • Sarcomatoid fratures Found in less than 5% High – grade forms of RCC Associated with a poor outcome

11. PROGNOSTIC FACTORS (IV) CLINICAL FACTOR • Performance status5-year cancer-specific survival ECOG-PS 0 81% ECOG-PS ≥1 51% Independend prognostic factor of survival in mRCC Independent predictor of poor outcome • Paraneoplastic syndrome Cachexia – related findings: anorexia, malaise, weight loss Overall incidence 14-8% Independent predictor of both poor prognosis and / or outcome Significantly affect recurrence free survival, cancer-specific survival • Laboratory abnomalities - Thrombocytosis / Anemia - Serum Calcium - Serum lactate dehydrogenase - Hypoalbuminemia

12. MOLECULAR PROGNOSTIC FACTORS MOLECULAR MARKERS (I) Hypoxia inducible CAIX CAXII CXCR4 VEGF ILGF-1 Proliferation ki-67 Cell cycle regulation P53 Bcl-2 PTEN Cyclin A P27 • Cell adhesion • EpCAM • EMA • E-cadherin • a-Catenin • Cadherin-6 • Miscellaneous • Gelsolin • Vimentin • CA125 • CD44 • Androgen receptors • Caveolin-1 • VEGFR

13. MOLECULAR MARKERS (II) HIPOXIA INDUCIBLE FACTORS

14. MOLECULAR MARKERS (III) REGULATOR APOPTOSIS

15. MOLECULAR MARKERS (III)REGULATOR CELL CYCLE

16. P53 is an independent predictor of tumor recurrence and progression after nephrectomy in patients with localized renal cell carcinoma RR: 14.4% • 193 localized RCC • TMA: CA9, CA12, gelsolin, p53 EpCAM and pTEN • 15% tumor recurrence • Univariate analysis: T stage, grade, ECOG, Ki67, EpCAM and p53 were significantly associated with recurrence (p<0.05) • Multivariate analysis: T stage, ECOG, and p53 were the 3 most significant predictors of tumor recurrence RR: 37.7% Shvarts, O, Seligson D, Lam J et al. J Urol; 2005: 725-728

17. Using protein expression to predict survival in RCC • 318 RCC patients • TMA: Ki67, p53, gelsolin, CA9, CA12, PTEN, EpCAM and vimentin CA9 PTEN CA12 EpCAM WORSE SURVIVAL Ki-67 P53 Vimentin gelsolin Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471

18. A prognostic model based on a combination of clinical and molecular predictors • Multivariate analysis: p53, CA9, vimentin were statistically significant predictors of survival independent of the clinical variables metastasis status, T stage, ECOG and grade. • Prognostic systems based on protein expression profiles for clear cell RCC performed better than standard clinical predictors Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471

19. INTEGRATED PREDICTION MODELS Concept: Integration of independent prognostic indicators into comprehensive out come models Objetive: To facilitate patient counseling To identify patients who might benefit from therapy Historical perspective 1986 Maldazys JD J Urol 136:376-379 1988 Elson PJ Cancer Res 48: 7310-7313 2001 Kattan MW J Urol 166: 63-67 UISS 2001 Zisman A J Clin Oncol 10: 1649-1657(UCLA) 2002 Zisman A J Clin Oncol 20: 4559-4560 SSIGN 2002 Frank I J Urol 168: 2395-2400(Mayo Clinic) MSKCC 2004 Motzer RJ J Clin Oncol 22: 454-463(Memorial) 2005 Mekhail TM J Clin Oncol 23: 832-841(Cleveland Clinic) Types Preoperative models: Yayciogly and Cindolo Postoperative models: Kattan momogram

20. Risk Groups for Advanced RCC • Pretreatment features associated with shorter survival • Low Karnofsky performance status (< 80%) • High lactate dehydrogenase level (> 1.5 x normal) • Low hemoglobin level • High serum calcium • Absence of nephrectomy Motzer RJ, et al. J Clin Oncol. 1999;17:2530-2540.

21. Survival stratified according to risk group MS: 20m MS: 4m MS: 10m Motzer, R. J. et al. J Clin Oncol; 17:2530 1999

22. Fig 3. Kaplan-Meier survival analysis of the study population according to the UISS categories Zisman, A. et al. J Clin Oncol; 19:1649-1657 2001

23. Comprehensive staging systems for localized and metastatic RCC

24. Comparison of Predictive Accuracy of Four Prognostic Models for Nonmetastatic Renal Cell Carcinoma after Nephrectomy • 2404 patients • Kattan and UISS postoperative models • Cindolo and Yaycioglu preoperative models KATTAN MODEL WAS THE MOST ACCURATE IN PREDICTING PROGNOSIS Cindolo L, Patard JJ, Chiodini et al. Cancer 2005; 1362-1371

25. Factores pronóstico desfavorables dependientes del paciente de uso común • Presentación con síntomas de enfermedad • Pérdida de peso (>10% de masa corporal) • ECOG2-3 • Reactantes de fase aguda • VSG > 30 • Proteína C Reactiva elevada • Anemia • Hb< 10g/dl en mujer • Hb< 12 g/dl en varón • Hipercalcemia • Fosfatasa alcalina elevada • Hipoalbuminemia • Trombocitosis

26. Factores pronóstico desfavorables dependientes del paciente no consolidados • Edad • Sexo • Raza • Localización geográfica • Nivel socioeconómico

27. Factores pronóstico desfavorables dependientes del tumor de uso común • Macroscópicos • Afectación de márgenes quirúrgicos • Metástasis • Presencia de múltiples metástasis • Afectación hepática o pulmonar • Presencia de trombo en sistema venoso • Microscópicos • TNM (factor pronóstico más importante descrito) • Grado nuclear • necrosis • Tipo histológico • Células claras convencional • Carcinoma de conductos colectores • Sarcomatoide • Morfología nuclear: área aumentada y formas variables • Contenido en DNA: aneuploidía • Marcadores de proliferación • Ki-67 elevada • Ag-NOR (proteínas nucleolares argirófilas) elevado

28. Factores pronóstico desfavorables dependientes del tumor no consolidados • Fase S elevada • PCNA elevado • P-53, bcl2, p21 • Factores de crecimiento • Moléculas de adhesión celular • Angiogénesis

29. CONCLUSION • The last decade has lead to the gradual transition from the use of solitary clinical factors as prognostic markers to the introduction of systems that integrate molecular and genetic markers. • These markers will eventually enhance our ability to predict individual tumor behavior and stratify patients into more sophisticated risk categories. • They also can select patients for targeted biological therapies and transform the management of this malignancy in the near future.