Individualizing Therapy For Patients With Advanced Rcc

Individualizing Therapy for Patients With Advanced RCC Robert A. Figlin, MD Arthur and Rosalie Kaplan Chair in Oncology Professor and Chair, Medical Oncology and Therapeutics Research City of Hope National Medical Center and Beckman Research Institute Associate Director for Clinical Research City of Hope Comprehensive Cancer Center Duarte, California

Overview

RCC Statistics
US estimates for 2008 1
54,390 individuals will be diagnosed with cancer of the kidney and renal pelvis
Median age at diagnosis: 65 years
13.010 individuals will die from cancer of the kidney and renal pelvis
Median age at death: 71 years
Accounts for 3.5% of all cancers in the US 2
3 rd most common genitourinary cancer after prostate cancer and bladder cancer
7 th most common cancer in men
9 th most common cancer in women
1. National Cancer Institute. SEER cancer statistics fact sheet: cancer of the kidney and renal pelvis. Accessed 2008. 2. Jemal A et al. CA Cancer J Clin . 2008;58:71.

Stage Distribution National Cancer Institute. SEER cancer statistics fact sheet: cancer of the kidney and renal pelvis. Accessed 2008. 35.5% 5% Unknown 9.9% 20% Distant 61.3% 19% Regional 89.9% 56% Localized 5-Year Relative Survival Rate At Diagnosis Disease Distribution

Advanced RCC
1. National Cancer Institute. SEER cancer statistics fact sheet: cancer of the kidney and renal pelvis. Accessed 2008.
2. Janzen N et al. Urol Clin North Am . 2003;30:843.
20-30% of patients present with metastatic disease 1
Another 25-50% of individuals treated for localized disease experience recurrence 2
Prognosis for patients with metastatic RCC is dismal, with a 5-year survival rate of 9.9% 1
Surgery not an option for cure
RCC resistant to radiotherapy and chemotherapy
Immunotherapy results in limited benefit with marked toxicity
Prompted need for rational therapeutic approaches based on disease biology

Biologic Basis of Renal Oncogenesis

Subtypes 1-3 1. Thoenes W et al. Path Res Pract . 1986;181:125. 2. Störkel S, van den Berg E. World J Urol . 1995;13:153. 3. Linehan WM et al. J Urol. 2003;170:2163. Very rare Collecting duct tumors (a.k.a. Bellini’s duct) BHD Uncommon (≤2%) Oncocytomas BHD 5 – 10% Chromophobic carcinomas c-Met , fumarate hydratase 10 – 15% Chromophilic (papillary) carcinomas VHL 75 – 85% Clear cell carcinoma Microscopic Features Genetic Defect Prevalence Subtype

VHL and RCC
VHL is a tumor suppressor gene located on chromosome 3p25
Loss of heterozygosity of VHL gene locus detected in ~85-95% of clear-cell RCCs 1,2
VHL genetic abnormalities present in 60-90% of patients with sporadic RCC 1,2
VHL mutated in 52-71% of patients with sporadic RCC
VHL silenced by hypermethylation in an additional 5-20%
Inactivation of VHL thought to be a very early event in clear-cell RCC tumorigenesis
1. Shuin T et al. Cancer Res . 1994;54:2852. 2. Brauch H et al. Cancer Res . 2000;60:1942. 3. Yao M et al. J Natl Cancer Inst . 2002;94:1569. 4. Banks RE. Cancer Res . 2006;66:2000. VHL = von Hippel-Lindau

Normal VHL Function Stadler WM. Cancer . 2005;104:2323. O 2 VEC NEDD8 Degradation by proteasome
Hypoxia Response:
Angiogenesis
Glycolysis
Erythropoiesis
pH
Cell adhesion
ECM assembly
Cul2 VHL Rbx1 Elongin B Elongin C OH HIF-1  OH x Ub

Mutant VHL Stadler WM. Cancer . 2005;104:2323. O 2 VEC NEDD8 Degradation by proteasome X X X Mutant VHL mimics conditions of hypoxia HIF-1  mRNA transcription Cul2 Mutant VHL Rbx1 Elongin B Elongin C HIF-1  HIF-1  VEGF PDGF TGF-  EGFR Ub

Pathways Activated by HIF-1  1,2 1. Stadler WM. Cancer . 2005;104:2323. 2. Vignot S et al. Ann Oncol . 2005;16:525. Endothelial/ Tumor cells Angiogenesis/Cell proliferation Angiogenesis Cell survival Upregulation in response to HIF-1 transcription PDGF VEGF EGF Ras RAF MEK Erk PLC RAC P38MAPK Cell migration PKC Cell proliferation Cell survival PI3K AKT/PKB SRC JAK STAT Cell survival

mTOR Pathway Seeliger H et al. Cancer Metastasis Rev . 2007;26:611. PI3K Growth factors = insulin, IGF, VEGF, IL-2 Protein synthesis Upregulation in response to HIF-1 transcription Growth Factor AKT mTOR S6K1 PTEN HIF-1  eIF-4E

Targeting the Molecular Pathways of RCC Oncogenesis Proposed CME slide Stadler WM. Cancer . 2005;104:2323. Angiogenesis/Cell proliferation/Cell survival bevacizumab gefitinib, cetuximab, erlotinib, panitimumab Gene expression rapamycin, temsirolimus, everolimus, AP23573 CI-1040 sorafenib, ISIS-5132 Endothelial/ Tumor cells Upregulation in response to HIF-1 transcription sorafenib, sunitinib, PTK/ZK PDGF VEGF EGF Ras RAF PI3K AKT MEK ERK mTOR

RCC Prognostic Factors and Risk Stratification

Rationale for RCC Staging
Predict tumor behavior
Patient prognosis
Stratify patients into risk categories
Predict disease recurrence and cancer-related death
Select treatment approach
Choose therapy based on molecular markers expressed by tumor
Predict response to therapy
Minimize treatment exposure to avoid unnecessary toxicity
Standardize inclusion criteria for clinical trials
Leppert JT et al. BJU Int . 2007;99:1208.

Determinants of RCC Prognosis Shuch BM et al. Semin Oncol. 2006;33:563.
Tumor necrosis
Venous involvement
Thrombocytosis
Microvascular invasion
Metastasis
Cachexia-related symptoms
Morphology
Lymph node involvement
Performance status
Fuhrman grade
Tumor size
Clinical Factors Histopathology Anatomic Extent of Disease

Integrated Prognostic Models
Various prognostic models developed that integrate information on anatomic staging, histopathology, and clinical parameters
Most widely used model is the validated UCLA integrated staging system (UISS) 1,2
Uses TNM classification scheme, Fuhrman grade, and ECOG performance status to classify patients into 5 prognostic categories that correlate with post-nephrectomy outcome
1. Zisman A et al. J Clin Oncol . 2001;19:1649. 2. Patard JJ et al. J Clin Oncol . 2004;22:3316. TNM = tumor node metastasis ECOG = Eastern Cooperative Oncology Group

UISS and Survival Zisman A et al. J Clin Oncol . 2001;19:1649. RCC Prognosis Stratified by UISS Stage PS = performance status 0 ± 4.0% ≥ 1 4 IV V ≥ 1 1-3 IV 23 ± 3.1% 0 3, 4 IV IV 0 1, 2 IV 39 ± 2.8% ≥ 1 2-4 III III ≥ 1 1 III 0 Any III Any Any II Any 3, 4 I 67 ± 6.4% ≥ 1 1, 2 I II 94 ± 2.5% 0 1, 2 I I 5-Year Survival ECOG PS Fuhrman Grade TNM Stage UISS Stage

Biomolecular Prognostic Factors in RCC 1. Bui MH et al. Clin Cancer Res . 2003;9:802. 2. Patard JJ et al. Int J Cancer . 2008;123:395. 3. Bui MH et al. J Urol . 2004;171:2461. 4. Weiss RH et al. J Urol . 2007;177:63. 5. Shvarts O et al. J Urol . 2005;173:725. 6. Kim HL et al. J Urol . 2005;173:1496. 7. Bukowski RM et al. ASCO 2007; Abstract 5023. 8. Klatte T et al. Clin Cancer Res . 2007;13:7388. 9. Thompson RH et al. ASCO 2008; Abstract 5052. 10. Kim H et al. ASCO 2008; Abstract 16015. 11. Tanimoto S et al. J Med Invest . 2008;55:106. 12. Pantuck AJ et al. Cancer . 2007;109:2257. Poor survival Low PTEN 6,12 Poor survival High cytoplasmic levels Akt 12 Poor survival High Hepatocyte growth factor 11 Non-response, poor survival Low COX (cyclooxygenase)-2 10 Advanced tumor stage High B7x 9 Poor survival High HIF (hypoxia-inducible factor)-1  8 Shorter progression free survival (PFS) High serum levels VEGF 7 (vascular endothelial growth factor) Higher recurrence rate High P53 5,6 Poor survival High p21 (metastatic disease) 4 Poor survival High Ki67 3 Poor survival Low CAIX 1,2 Predicted Response to Treatment Expression Level Marker

CAIX Expression Bui MH et al. Clin Cancer Res . 2003;9:802. .033 1.32 (1.02-1.71) Nodal status .005 1.44 (1.12-1.87) Tumor stage .004 1.52 (1.15-2.01) Grade .003 1.62 (1.18-2.24) ECOG PS <.001 3.17 (2.07-4.86) Low CAIX staining P Value HR (95% CI) Factor

Predicting Response to Treatment Based on Molecular/Genetic Markers nsSNPs: nonsynonymous single nucleotide polymorphisms 1. Kim HL et al. J Urol . 2005;173:1496. 2. Patel PH et al. ASCO 2008. Abstract 5008. 3. Faber PW et al. ASCO 2008. Abstract 5009. 4. Jaeger E et al. ASCO 2008. Abstract 5043. 5. Choueiri TK et al. J Urol . 2008; [Epub ahead of print]. Good response to VEGF therapy VHL loss-of-function mutation 5 Non-response to interleukin-2 (IL-2) Loss of chromosomes 4, 9, or 17p 4 Significant sunitinib toxicity Various nsSNPs 3 Predicted Response to Treatment Genetic Marker Good response to sunitinib High HIF-1  /HIF-2  2 Good response to immunotherapy High COX-2 1 Good response to immunotherapy High CAIX 1 Predicted Response to Treatment Expression Level Molecular Marker

Poor-Risk Clinical Features of Advanced RCC * In liver, lungs, or retriperitoneal lymph nodes MSKCC = Memorial Sloan Kettering Cancer Center CCF = Cleveland Clinic Foundation 1. Motzer RJ et al. J Clin Oncol . 2004;22:454. 2. Mekhail TM et al. J Clin Oncol . 2005;23:832. Yes Presence of metastasis* Yes Prior radiotherapy <12 months Time from diagnosis to interferon (IFN)-  >1.5 x upper limit of normal Lactose dehydrogenase <80% Karnofsky performance status >10.0 mg/dL Corrected serum calcium ≥ 10.0 mg/dL Corrected serum calcium <lower limit of normal Hemoglobin ≤ 13.0 g/dL men, ≤ 11.5 g/dL women Hemoglobin CCF Criteria 2005 2 MSKCC Criteria 2004 1

Comparison of MSKCC 1 and CCF 2 Criteria 1. Motzer RJ et al. J Clin Oncol . 2004;22:454. 2. Mekhail TM et al. J Clin Oncol . 2005;23:832.
MSKCC risk groups
Favorable: 0 risk factors
Intermediate: 1 risk factor
Poor: 2-3 risk factors
CCF risk groups
Favorable: 0-1 risk factor
Intermediate: 2 risk factors
Poor: ≥3 risk factors
OS = overall survival CCF Criteria MSKCC Criteria Median OS, mo Proportion, % Median OS, mo Proportion, % Risk Group 73 28 5.4 23 Poor 14.4 35 11.9 35 Intermediate 26 37 22 42 Favorable

Individualizing Therapy for Metastatic RCC

Rationale for Individualizing Therapy
RCC has a highly variable natural history with no available systemic cure
No one therapy predicted to be uniformly active in all patient populations
Individualizing therapy offers patients the best chance of disease control balanced with the best possible quality of life

Issues to Consider
Overall goals of treatment for metastatic RCC
Delay life-threatening burden of disease
Optimize chance of long-term disease control
Maximize quality of life and patient convenience
Weigh benefits vs risks to identify optimal therapeutic for a given patient
Most patients will likely receive a sequence of several agents to help control disease
Development of targeted agents has outpaced an understanding of their optimal use
Broad approval ≠ broad activity

Clinically Available Targeted Agents for Advanced RCC 1. Escudier B et al. Lancet . 2007;370:2103. 2. Rini BI et al. 2008 ASCO Genitourinary Cancers Symposium. Abstract 350. 3. Motzer RJ et al. N Engl J Med . 2007;356:115. 4. Escudier B et al. N Engl J Med. 2007;356:125. 5. Hudes G et al. N Engl J Med . 2007;356:2271. ORR = overall response rate TTP = time to progression 8.5 vs 5.2; P < .0001 26% vs 13% 732 Bevacizumab + IFN-  vs IFN-  2 3.7 vs 1.9 (IFN-  ); P = .001 9% vs 7% vs 11% 626 Temsirolimus vs IFN-  vs both agents 5 mTOR Temsirolimus 5.5 vs 2.8; P = .000001 10% vs 2% 903 Sorafenib vs PBO 4 VEGF receptor Sorafenib 11.1 vs 5; P = .00001 37% vs 9% 750 Sunitinib vs IFN-  3 VEGF receptor Sunitinib 10.2 vs 5.4; P = .0001 31% vs 13% 649 Bevacizumab + IFN-  vs placebo (PBO) + IFN-  1 VEGF Bevacizumab TTP (mos) ORR No. Treated Comparison Efficacy in Randomized Phase III Trials Target Agent

When Should Systemic Therapy Be Started?
Immediately start treatment or delay therapy to offset treatment burden?
Evidence suggests that treatment benefit may be preserved even if treatment initiation is delayed in asymptomatic patients
Randomized phase II discontinuation trial of sorafenib vs placebo
28 patients initially randomized to placebo arm subsequently received sorafenib upon disease progression at a median of 7 weeks
Median PFS = 24 weeks
PFS identical to that of patients in original sorafenib arm
Ratain MJ et al. J Clin Oncol . 2006;24:2505.

Which Agent Is Best? Rini BI, Bukowski RM. Oncology (Williston Park) . 2008;22:388.
Only active in a subset of patients
Considerable toxicity
Requires infusion
Higher ORR in patients with high CAIX expression – requires clinical trial confirmation
High-dose IL-2
Less efficacy in front-line setting
Active in cytokine-refractory disease
Oral dosing
Favorable toxicity profile
Sorafenib
Requires infusion
Often requires combination therapy with IFN- 
Favorable toxicity profile
Bevacizumab
Activity appears to be restricted to patients with poor-risk disease
Requires infusion
Survival advantage
Active in patients with poor-risk disease
Temsirolimus
Long-term disease control may not be robust
Highest ORR
Oral dosing
Survival advantage
Sunitinib Cons Pros Agent

Which Agent Is Best? Hutson TE, Figlin RA. Cancer J . 2007;13:282.
Everolimus
Prior VEGF therapy
Sorafenib, Sunitinib
Prior cytokine therapy
Second-line therapy
Temsirolimus
Poor risk
Sunitinib
Bevacizumab ± IFN- 
High-dose IL-2
Low + intermediate risk
First-line therapy Therapy Setting

NCCN Practice Guidelines in Oncology: Kidney Cancer Relapse or Stage IV and medically or surgically unresectable Predominant clear cell histology Clinical trial or Sunitinib (category 1) or Temsirolimus for poor-prognosis patients * (category 1) or Bevacizumab + IFN or High-dose IL-2 for selected patients or Sorafenib for selected patients and Best supportive care  FIRST-LINE THERAPY * Temsirolimus indicated for poor-prognosis patients, defined as those with ≥3 predictors of short survival  Best supportive care can include palliative radiation therapy (RT), metastasectomy or biphosphonates for bony metastasis NCCN Clinical Practice Guidelines in Oncology. 2007;v.1.2008.

NCCN Practice Guidelines in Oncology: Kidney Cancer Relapse or Stage IV and medically or surgically unresectable Clinical trial (preferred) or Temsirolimus * (category 1 for poor-prognosis, category 2A for other risk groups) or Sorafenib or Sunitinib or Chemotherapy (category 3): gemcitabine or capecitabine or floxuridine or 5-FU or doxorubicin (in sarcomatoid only) and Best supportive care  FIRST-LINE THERAPY (cont.) Non clear cell histology * Temsirolimus indicated for poor-prognosis patients, defined as those with ≥3 predictors of short survival  Best supportive care can include palliative RT, metastasectomy or biphosphonates for bony metastasis NCCN Clinical Practice Guidelines in Oncology. 2007;v.1.2008.

NCCN Practice Guidelines in Oncology: Kidney Cancer Clinical trial (preferred) or Sorafenib (category 1 following cytokine therapy and category 2A following TKI) or Sunitinib (category 1 following cytokine therapy and category 2A following TKI) or Temsirolimus (category 2A following cytokine therapy and category 2B following TKI) or IFN (category 2B) or High dose IL-2 (category 2B) or Low dose IL-2 + IFN (category 2B) or Bevacizumab and Best supportive care* SUBSEQUENT THERAPY (use crossover regimen) Progression * Best supportive care can include palliative RT, metastasectomy or biphosphonates for bony metastasis NCCN Clinical Practice Guidelines in Oncology. 2007;v.1.2008.

Does the Sequence of Agents Matter?
Use of sequential targeted agents has become the de facto treatment approach in metastatic disease
Ideal sequence of agents unknown
Many unresolved issues
Is immunotherapy active after targeted therapy?
Does the biology of a tumor change after exposure to an agent?
Does this affect the effectiveness of subsequent therapy?
What are the mechanisms of drug resistance?
Does the toxicity profile of 1 agent affect the tolerability of subsequent agents?

Factors to Consider When Individualizing Therapy
Risk status
Extent of disease
Histopathology
Clinical factors
Tumor molecular characteristics
First-line, second-line, subsequent lines of therapy
Patient preference
Regarding start of treatment
Desired clinical outcomes
Acceptable/unacceptable toxicities

Summary
Accurately predicting patient outcomes is important for individualizing therapy
Enables patients to be informed about their prognosis
Enables educated decision-making regarding treatment
RCC staging will evolve as factors defining patient prognosis are better understood
Patient prognosis will become more accurate as molecular marker information is incorporated into staging systems
Additional molecular marker research needed to better facilitate individualized therapy selection
Current goal of individualized therapy is to maximize treatment effectiveness and minimize toxicity

Individualizing Therapy For Patients With Advanced Rcc

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