EPIDEMIOLOGIA Y FACTORES DE EPIDEMIOLOGIA Y FACTORES DE RIESGORIESGO

CANCER DE RICANCER DE RIÑONÑON

Prof. Dr. L. M. Antón AparicioProf. Dr. L. M. Antón AparicioC.H.U. A CoruñaC.H.U. A Coruña

EPIDEMIOLOGYEPIDEMIOLOGYDEMOGRAPHIC ASPECTS• Incidence• Age / race• International incidence

PROGNOSTIC FACTORS• Anatomic factors• Histologic factors• Clinical factors• Molecular markers

RISK FACTORS• General• Gigarette smoking• Obesity / Dietary factors• Hypertension / Drug• Hormonal• Occupation• Transplantation / Dialysis

PREDICTOR MODELS• Concept• Objective• Historical - perspective

DEMOGRAPHIC ASPECTSDEMOGRAPHIC 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)

2002 RCC World Incidence and Mortality Rates, Stratified by Region

Renal cancer incidence

0 1 2 3 4 5 6 7 8 9 10

Western AfricaMiddle Africa

South Central AsiaMelanesia

East AfricaMicronesia

Northern AfricaSoutheastern Asia

PolynesiaEastern Asia

Southern AfricaCaribbean

Western AsiaSouth America

Central AmericaSouthern EuropeNorthern Europe

Central and Eastern EuropeWestern Europe

Australia/New ZealandNorthern America

Wo

rld

Reg

ion

s

Rates per 100,000

Renal cancer mortality

Ries LAG, et al. SEER Cancer Statistics Review, 1975-2002.

RISK FACTORSRISK FACTORS (I)(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 mass relative 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

RISK FACTORSRISK FACTORS (II)(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

PROGNOSTIC FACTORS (I)PROGNOSTIC FACTORS (I)• ANATOMIC FACTORS • Tumor size

• Tumor extesion/ adrenal involvement

• Venous involvement

• Lymph node involvement

• Metastasis

• HISTOLOGIC FACTORS • Tumor grade (TNM)

• Histologic morphology

• Tumor necrosis

• Microvascular invasion

• Sarcomatoid features

• CLINICAL FACTORS • Performance status

• Laboratory abnormalitis

• Paraneoplastic syndrome

• Thrombocytosis

• MOLECULAR MARKERS • Angiogenesis

• Proliferation

• Apoptosis

• Others

PROGNOSTIC FACTORS PROGNOSTIC FACTORS (II)(II)

• ANATOMIC FACTORS

• Tumor size 5-year cancer-specific survival (rate)

T1

T2

T3

Range

Range

Range

91% to 60%

74% to 71%

67% to 37%

(T1a T1b)

(T2a T2b)

(T3a T3b)

• Tumor extensión

• Adrenal involvement 5-year cancer-specific survival (rate)

Similar to T4

• Venous involvement

RV

IVC

IVC

3-year cancer-specific survival (rate)

70%

63% (below diaphragma)

23% (above diaphragma)

• Lymph node

N+ Range

2-year cancer-specific survival (rate)

10% to 20%

PROGNOSTIC FACTORS (III)PROGNOSTIC FACTORS (III)HISTOLOGIC FACTORS

• Histologic morphology 5-year cancer-specific survivalMain 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 necrosisIncidence 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 invasionIndicence 25% to 28%Independent predictor of disease recurrenceIndependent predictor of cancer-specific survival

• Sarcomatoid fraturesFound in less than 5%High – grade forms of RCCAssociated with a poor outcome

PROGNOSTIC FACTORS (IV)PROGNOSTIC FACTORS (IV)CLINICAL FACTOR

• Performance status 5-year cancer-specific survivalECOG-PS 0 81%ECOG-PS ≥1 51%

Independend prognostic factor of survival in mRCC Independent predictor of poor outcome

• Paraneoplastic syndromeCachexia – related findings: anorexia, malaise, weight lossOverall incidence 14-8%Independent predictor of both poor prognosis and / or outcomeSignificantly affect recurrence free survival, cancer-specific survival

• Laboratory abnomalities- Thrombocytosis / Anemia- Serum Calcium- Serum lactate dehydrogenase- Hypoalbuminemia

MOLECULAR PROGNOSTIC FACTORSMOLECULAR PROGNOSTIC FACTORS

Hypoxia inducibleCAIXCAXIICXCR4VEGFILGF-1

Proliferationki-67

Cell cycle regulationP53Bcl-2PTENCyclin AP27

Cell adhesionEpCAMEMAE-cadherina-CateninCadherin-6

MiscellaneousGelsolin

VimentinCA125CD44Androgen receptorsCaveolin-1VEGFR

MOLECULAR MARKERS MOLECULAR MARKERS (I)(I)

MOLECULAR MARKERSMOLECULAR MARKERS (II)(II)

HIPOXIA INDUCIBLE FACTORS↑ HIF-1α expression: an independent predictor of survival (Clear cell)

↓ CA Ix expression: an independent prognostic indicator poor survival (m RCC)

an predictor with response to IL-2

VHL alterations: an independent predictor of cancer-free survival

an independent predictor of disease-free survival

VEGF

VEGF-A / VEGF-2: higher expression (papillary) / lower expression (clear)

VEGF-A, VEGFR-1, VEGFR-2:

(↑ epithelium)

independent predictor lymp node involvemt

independent predictor disease-free survival

VEGFR-3

(↓ low endothelial)

independent predictor lymph node involvement

independent predictor disease-free survival

MOLECULAR MARKERS (III)MOLECULAR MARKERS (III)REGULATOR APOPTOSIS

p53 • Tumor-suppressor gene

incidence range 16% to 57%

↑ papillary, metastatic

overexpression: independent predictor poor survival

independent prognostic disease progression (clear)

indipendent predictor disease recurrence

BCl-2 • Survival protein

incidence range 10% to 80%

Expression: significant correlation higher tumor grade

correlated with improved overall survival

associated with lower stage & grade

not predict disease-free or disease-specific survival

not correlated with recurrence & metastasis

Smac/DIABLO • caspase family proteins

incidence: lower

+ expression: inversely correlated with tumor grade

- expression: worse cancer-specific survival

MOLECULAR MARKERS (III)MOLECULAR MARKERS (III)REGULATOR CELL CYCLE

p27

↓ expression

• regulated proliferation G1/s transition

Cyclin-dependent kinases

Higher-grade & large tumor size

Independent predictor poor disease & specific survival

PTEN • Tumor – suppressor protein

PI3K – AKT – mTOR signaling pathway

+ Expression:

↓ Expression:

Loss expression:

Found to correlate with pAKT & HIF-1α expression

Independent predictor poor survival (m clear RCC)

Increased in all RCC

↓ loss: Clear cell RCC & sarcomatoid features

pAKT:

SGK:

Collecting duct (89%)

Sarcomatoid (61%)

High-grade 73%

High-stage 50%

Clear cell (58%)

Clear cell (41%)

31%

30%

ADHESION MOLECULES

EpCAM

Eph A2

Frequently absent (clear cell RCC)

Independent predictor improved disease- specific survival

Associated larger tumor size

Predictor decrease-free recurrence & overall survival

P53 is an independent predictor of tumor recurrence and P53 is an independent predictor of tumor recurrence and progression after nephrectomy in patients with localized renal progression after nephrectomy in patients with localized renal

cell carcinomacell carcinoma

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%

RR: 14.4%

Shvarts, O, Seligson D, Lam J et al. J Urol; 2005: 725-728

Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471

Using protein expression to predict Using protein expression to predict survival in RCCsurvival in RCC

318 RCC patients

TMA: Ki67, p53, gelsolin, CA9, CA12, PTEN, EpCAM and vimentin

CA9

PTEN

CA12

EpCAM

Ki-67

P53

Vimentin

gelsolin

WORSE

SURVIVAL

Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471

A prognostic model based on a combination of clinical and A prognostic model based on a combination of clinical and molecular predictorsmolecular 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

INTEGRATED PREDICTION MODELSINTEGRATED PREDICTION MODELSConcept: Integration of independent prognostic indicators into

comprehensive out come models

Objetive: To facilitate patient counselingTo identify patients who might benefit from therapy

Historical perspective1986 Maldazys JD J Urol 136:376-3791988 Elson PJ Cancer Res 48: 7310-73132001 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 CindoloPostoperative models: Kattan momogram

Risk Groups for Advanced RCCRisk Groups for Advanced RCC

Risk GroupsNo. of Risk

Factors

2-Year Survival Rate,

%Favorable Risk 0 45

Intermediate Risk 1-2 17

High Risk ≥ 3 3

Motzer RJ, et al. J Clin Oncol. 1999;17:2530-2540.

Pretreatment features associated with shorter survivalLow Karnofsky performance status (< 80%)

High lactate dehydrogenase level (> 1.5 x normal)

Low hemoglobin level

High serum calcium

Absence of nephrectomy

Motzer, R. J. et al. J Clin Oncol; 17:2530 1999

Survival stratified according to risk groupSurvival stratified according to risk group

MS: 20m

MS: 10mMS: 4m

Copyright © American Society of Clinical Oncology

Zisman, A. et al. J Clin Oncol; 19:1649-1657 2001

Fig 3. Kaplan-Meier survival analysis of the study population according to the UISS categories

Comprehensive staging systems for Comprehensive staging systems for localized and metastatic RCClocalized and metastatic RCC

KattanKattan(localized)(localized)

FrankFrank(localized)(localized)

(SSIGN)(SSIGN)

ZismanZisman(localized (localized

and metastatic)and metastatic)

(UISS)(UISS)Tumor subtypes All Clear cell All

Prognostic indicators

TNM, size, histology, symptons

TNM, size, grade, necrosis

TNM, grade, ECOG

Prognostic information

recurrence survival survival

Comparison of Predictive Accuracy of Four PrognosticComparison of Predictive Accuracy of Four PrognosticModels for Nonmetastatic Renal Cell Carcinoma afterModels for Nonmetastatic Renal Cell Carcinoma after

NephrectomyNephrectomy

Cindolo L, Patard JJ, Chiodini et al. Cancer 2005; 1362-1371

2404 patients

Kattan and UISS postoperative models

Cindolo and Yaycioglu preoperative models

KATTAN MODEL WAS THE MOST KATTAN MODEL WAS THE MOST ACCURATE IN PREDICTING ACCURATE IN PREDICTING

PROGNOSISPROGNOSIS

Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del paciente de uso comúndependientes del paciente de uso común

Presentación con síntomas de enfermedadPérdida de peso (>10% de masa corporal)ECOG2-3Reactantes de fase agudao VSG > 30o Proteína C Reactiva elevada

Anemiao Hb< 10g/dl en mujero Hb< 12 g/dl en varón

HipercalcemiaFosfatasa alcalina elevadaHipoalbuminemiaTrombocitosis

Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del paciente no consolidadosdependientes del paciente no consolidados

• Edad

• Sexo

• Raza

• Localización geográfica

• Nivel socioeconómico

Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del tumor de uso comúndependientes 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

Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del tumor no consolidadosdependientes del tumor no consolidados

• Fase S elevada

• PCNA elevado

• P-53, bcl2, p21

• Factores de crecimiento

• Moléculas de adhesión celular

• Angiogénesis

CONCLUSIONCONCLUSIONThe 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.