Modern Management of Advanced

Kidney Cancer

Primo N. Lara, Jr., MD

Professor of Medicine

University of California Davis

Comprehensive Cancer Center

Sacramento, CA USA

RCC is not a single disease

Clear cell

75%

Type

Incidence (%)

Hereditary mutations VHL

Papillary type 1

5%

MET

Papillary type 2

10%

FH

Chromophobe

5%

FLCN

Oncocytoma

5%

FLCN

Proximal Nephron Distal Nephron

FLCN= folliculin; BHD= Birt-Hogg-Dubé; FH = fumarate hydratase; MET = mesenchymal epithelial transition factor; VHL = von Hippel-Lindau.

Pfaffenroth . Expert Opin Biol Ther. 2008; Linehan, Semin Cancer Biol 2012

Sporadic mutations

VHL

(89%) MET

(13%)

TBD TBD TBD

Biology 1: Consequences of VHL Gene Disruption

Ubiquitin Ligase Complex Disrupted

X Chr 3

Hypoxia

Inducible

Factor (HIF)

Accumulation

HIF

VEGF, etc.

Angiogenesis

Also…

- Erythropoiesis

- Cell proliferation &

survival

- Glucose metabolism

- pH regulation

- Proteolysis

Tools are available to interrogate

biomarkers involved in the

complex VHL-HIF pathways

RTK IGFR-1

PI3K

HIF1a

S6K

AKT

HIF2a

4EBP1

VHL

PTEN

LKB1

p53

PIP2 PIP3

Glucose Amino

Acids

TSC1

TSC2

RHEB

PRAS40

GSK3a/b

RAF

MEK

RSK ERK1/2

RAS

MDM2

AMPK

PDK1 IRS-1

ATP

ATP

mTOR

Raptor

mTOR

Rictor

Vps34

eIF4E

eIF4B

Biology 2: Complexity of mTOR Signaling Pathways

Biology 3: RCC is a metabolic disease

Vander Heiden, Science 2009

Nature 2013

Key altered pathways

and metabolites

Worse survival correlates with

upregulation of :

• Pentose phosphate

pathway genes (G6PH,

PGLS, TALDO and TKT)

• Fatty acid synthesis genes

(ACC and FASN)

• PI(3)K pathway enhancing

genes (MIR21).

Better survival correlates with

upregulation of:

• AMPK complex genes

• Multiple Krebs cycle genes

• PI(3)K pathway inhibitors

(PTEN, TSC2).

Increased gene expression:

• Red shading = worse survival

• Blue shading = better survival

Gordan JD, et al. Cancer Cell. 2008;14:435-446 .

Biology 4: RCC has molecularly

distinct phenotypes

H2

(HIF2+ only)

H1H2

(HIF1+ and

HIF2+)

VHL wild type

Gerlinger, NEJM 2012

Biology 5: RCC is heterogeneous

“Intratumor heterogeneity can

lead to underestimation of the

tumor genomics landscape

portrayed from single tumor-

biopsy samples and may

present major challenges to

personalized-medicine and

biomarker development.”

Prognostic Factors in RCC:

Targeted Therapies Era

Heng DY, et al. J Clin Oncol 2009

●N = 645 patients with mRCC treated with VEGF-targeted therapy

– Sunitinib (61%); Sorafenib (31%); Bevacizumab (8%)

●Predictors for OS:

– Time from diagnosis

to treatment*

– Hemoglobin*

– Calcium*

– Performance status*

– Neutrophil count

– Platelet count

* Components of MSKCC

prognostic criteria

Risk Group Number of

Risk Factors

Median

Survival Time

Favorable Risk (n=133) 0 37 months

Intermediate Risk (n=292) 1-2 28.5 months

Poor Risk (n=139) >2 9.4 months

Favorable: 0 factors

(OS 37 months)

Intermediate: 1–2 factors

(OS 28 months)

Poor: 3–6 factors

(OS 9.4 months)

Timeline of RCC Drug Approvals (USA)

1987~

2004 2005 2006 2007 2008 2009 2010 2011 2012

High-dose IL-2: 1992

Sorafenib: Dec 2005

Sunitinib: Jan 2006

Temsirolimus: May 2007

Everolimus: May 2009

Bevacizumab: Aug 2009

Pazopanib: Oct 2009

Axitinib: Jan 2012

Metastatic RCC: Treatment Principles

● The best treatment is one that results in cure

– Not currently achievable in most patients

● In absence of cure, goals are palliative

– Disease control and prolongation of life are achievable with

current systemic agents

● Current standard of care:

– Risk stratification

– Sequential use of “targeted” agents, starting with VEGF-

directed therapy in good/intermediate risk

– New (presumably non-cross resistant) treatment initiated at

time of progression or unacceptable toxicity

Metastatic Clear Cell RCC: Current Algorithm

RISK CATEGORY

Initial Assessment Candidate for nephrectomy?

Which prognostic group?

Favorable Intermediate Poor

INITIAL CHOICE

OF THERAPY HD IL2

(select pts) VEGF-targeted mTORi

SECOND LINE

THERAPY VEGF-targeted mTORi

?

Pazopanib vs. Sunitinib for First-line Treatment of

Clear Cell mRCC (COMPARZ)

Pazopanib 800 mg/day

Sunitinib 50 mg/day (Schedule

4/2*)

• Primary Endpoint: PFS (non-inferiority – upper bound of 95% CI for HR < 1.25)

N = 1100

Eligibility Criteria:

•Locally advanced

or mRCC with

clear cell histology

•No prior systemic

therapy for advanced

or mRCC

•Measurable disease

by RECIST

•KPS ≥70%

RANDOM I Z A T I ON

Phase 3 study

*Schedule 4/2 = 4 weeks on treatment/ 2 weeks off.

Available at: http://www.clinicaltrials.gov. NCT00720941.

COMPARZ: Intent to Treat Population

Efficacy Pazopanib (n=557) Sunitinib (n=553) HR

(95% CI); P Value

Median PFS, mos

(95% CI) Independent Review

8.4 (8.3, 10.9)

9.5 (8.3, 11.1)

1.047 (0.898, 1.220)

Interim OS, mos (95% CI)

28.4 (26.2, 35.6)

29.3 (25.3, 32.5)

0.908

(0.762, 1.082) P=0.275

Objective Response Rate (CR+ PR), %

31 (26.9, 34.5)

25 (21.2, 28.4)

P=0.032

Dose modifications Pazopanib

(n=554) Sunitinib (n=548)

Dose interruptions, %* 60 63

Dose reductions, % 44 51

Discontinuations due to AE, % 24 19

Motzer RJ, et al. Presented at ESMO. 2012 (abstr LBA8_PR). * Eisen ESMO 2012 (Discussant for abstr 2325).

COMPARZ: PFS and OS (Intent to Treat)

Pazopanib non-inferior to sunitinib

(PFS HR < 1.25)

Motzer, ESMO 2012

COMPARZ: Most Common Adverse Events

(Treatment-emergent)

17

Adverse Event a

Pazopanib (n = 554) % Sunitinib (n = 548) %

All Grs Gr 3/4 All Grs Gr 3/4

Any event b >99 59/15 >99 57/17

Diarrhea 63 9/0 57 7/<1

Fatigue 55 10/<1 63 17/<1

Hypertension 46 15/<1 41 15/<1

Nausea 45 2/0 46 2/0

Decreased appetite 37 1/0 37 3/0

ALT increased 31 10/2 18 2/<1

Hair color changes 30 0/0 10 <1/0

Hand-foot syndrome 29 6/0 50 11/<1

Taste Alteration 26 <1/0 36 0/0

Thrombocytopenia 10 2/<1 34 12/4

a AE ≥30% in either arm b 2% of patients in pazopanib arm and 3% of patients in sunitinib arm had grade 5 adverse events.

Motzer R, et al. ESMO 2012 (LBA8_PR) Taken directly from Motzer. ESMO 2012 oral abstract presentation

Instrument Domain Description Treatment difference :

mean change from baseline 2

P -value

FACIT-F Fatigue/Total score 2.32 <0.001

FKSI-19

Kidney Symptom Index/Total score 1.41 0.018

Physical 0.78 0.027

Emotional 0.05 0.409

Treatment Side Effects 0.31 0.033

Functional Well Being 0.31 0.098

Cancer Treatment Satisfaction Questionnaire (CTSQ)

Expectations of Therapy 1.41 0.284

Feelings about Side Effects 8.50 <0.001

Satisfaction with Therapy 3.21 <0.001

Supplementary Quality of Life Questionnaire (SQLQ)

Worst mouth/throat soreness 0.505 <0.0001

Worst foot soreness 0.204 0.0016

Worst hand soreness 0.267 0.0008

Limitations due to mouth/throat soreness 0.94 <0.001

Limitations due to foot soreness 0.65 0.014

1Pre-specified analysis. HRQoL changes in mean scores over time were analyzed with a repeated measures analysis of covariance (ANCOVA). 2Yellow Font: favors pazopanib. Blue Font: favors sunitinib. P-value <0.05 is statistically significant

Motzer R, et al. ESMO 2012 (LBA8_PR) Taken directly from Motzer. ESMO 2012 oral abstract presentation

COMPARZ: Quality of Life Results (First 6 months1)

18

COMPARZ: Per-protocol analysis of PFS

Pazopanib Sunitinib HR (95% CI)

Median PFS (IRC

PP)

Months (95%CI)

8.4 (8.3-10.9) (n=501)

10.2 (8.3-11.1) (n=494)

1.069 (0.910-1.255)

VEG108844: http://www.gsk-clinicalstudyregister.com/result_detail.jsp;jsessionid=0E2869B9C6A1942B31984ACDE6CE84D7?

protocolId=108844&studyId=A1C548E6-186D-405F-B1D6-853A51D9376B&compound=pazopanib

Does not meet protocol defined non-inferiority criteria

(HR upper bound of 95% CI <1.25)

COMPARZ Trial: Insights

Median PFS lower than original registration trials

– Likely due to lower % of good risk patients

Median OS higher than original registration trials

– Likely due to subsequent lines of active therapy

Sunitinib and pazopanib: comparable efficacy (PFS, OS)

– Per-protocol analysis did not meet non-inferiority criterion

Several HRQoL domains favored pazopanib

– Confounded by timing of QOL assessment (day 28, time of worst toxicity for sunitinib)

Sunitinib Pazopanib

NEJM 2007 COMPARZ JCO 2010 COMPARZ

PFS (months) 11 9.5 11.1 8.4

OS (months) 26.4* 29.3 22.9** 28.4

Good risk 38% 27% 39% 27%

Intermediate

risk

56% 59% 55% 58%

* Crossover patients censored; **from GSK website

Efficacy Scorecard: First-line RCC

1. Motzer RJ, et al. J Clin Oncol. 2009;27:3584–3590. 2. Escudier B, et al. J Clin Oncol. 2009;27(Suppl. 15S):5020 (Abstract); 3. Rini B, et al. J Clin Oncol. 2009;27(Suppl. 15S):LBA5019

(Abstract); 4. Escudier B, et al. J Clin Oncol. 2009;27:1280–1289. 5. Sternberg CN, et al. J Clin Oncol. 2010;28:1061–1068. 6. Hudes G, et al. N Eng J Med. 2007;356:2271–2281.

n ORR (%)

Median PFS (months)

Median OS (months)

Sunitinib vs. IFN-α1 750 47 vs. 12* 11 vs. 5* 26.4 vs. 21.8

Bevacizumab + IFN-α vs. IFN-α2, 3

649 31 vs. 12 10.4 vs. 5.5 23.3 vs. 21.3

732 25.5 vs. 13.1 8.4 vs. 4.9 18.3 vs. 17.4

Sorafenib vs. IFN-α4 189 5.2 vs. 8.7 5.7 vs. 5.6* NA

Pazopanib vs. placebo5 233 30 vs. 3 11.1 vs. 2.8 22.9 vs. 20.5

Pazopanib vs. Sunitinib 1,110 31 vs. 25 8.4 vs. 9.5 28.4 vs. 29.3

Tivozanib vs. Sorafenib 362 33 vs. 23 12.7 vs. 9.1 28.8 vs. 29.3

Temsirolimus vs. IFN-α6 (poor risk) 626 8.6 vs. 4.8 5.5 vs. 3.1* 10.9 vs. 7.3

*Independent assessment. ORR = overall response rate; PFS = progression-free survival; OS = overall survival; NA= not available

How does one choose?

In frontline RCC, efficacy is similar

across all VEGF inhibitors

– Poor risk: mTORi preferred

Therapy must be individualized

– Patient and tumor characteristics

– Preferences

– Reimbursement status

– Office workflow, nursing support

– Physician experience

Principle: “Choose one and use it

well!”

… and what about combinations?

Patients with previously untreated

advanced RCC (N=791)

Stratification factors:

• MSKCC risk group • Nephrectomy status

R

A

N

D

O

M

I

Z

E

TEM + BEV TEM: 25 mg IV weekly†

BEV: 10 mg/kg IV every 2 wk

(n=400)

1:1

IFN + BEV IFN: 9 MU SC 3 x wk†

BEV: 10 mg/kg IV every 2 wk

(n=391)

INTORACT* Study Design

BEV, bevacizumab; IFN, interferon alfa; IRC, independent review committee; IV, intravenous; MSKCC, Memorial Sloan-Kettering Cancer Center; PFS, progression-free survival; RCC, renal cell carcinoma; SC, subcutaneously; TEM, temsirolimus.

*ClinicalTrials.gov Identifier: NCT00631371 †Dose reductions were allowed for TEM and IFN, but not for BEV

April 2008–October 2012

Treat until PD, unacceptable

toxicity, or discontinuation for any other

reason

Characteristic

TEM + BEV (n=400)

IFN + BEV (n=391)

MSKCC risk factors,1 %

0 (good)

1–2 (intermediate)

3 (poor)

28

65

8

27

65

8

MSKCC Prognostic Risk Groups

1. Motzer RJ, et al. J Clin Oncol 2004;22:454-463.

BEV, bevacizumab; IFN, interferon alfa; MSKCC, Memorial Sloan-Kettering Cancer Center; TEM, temsirolimus.

0

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42

TEM + BEV

IFN + BEV

1-sided P=0.759 (log-rank)

Stratified HR: 1.07

(95% CI: 0.89, 1.28)

Median PFS,

months 95% CI

9.1

9.3

8.1, 10.2

9.0, 11.2

Progression-Free Survival (IRC Assessment)

BEV, bevacizumab; CI, confidence interval; HR, hazard ratio; IFN, interferon alfa; IRC, Independent Review

Committee; PFS, progression-free survival; TEM, temsirolimus.

400 316 256 208 161 120 95 76 59 48 36 31 26 21 14 9 4 3 2 1 1

391 280 230 196 167 138 114 92 78 68 60 42 32 26 22 16 12 9 6 2 2

TEM + BEV

IFN + BEV

Patients at risk, n Time (months)

Pro

ba

bil

ity o

f P

FS

PFS by Stratification Factors

Median PFS, mo (95% CI)

TEM + BEV (n=400)

IFN + BEV (n=391)

Nephrectomy

No

Yes

9.2 (7.2, 11.1)

9.1 (8.1, 10.4)

6.8 (2.4, 7.5)

10.9 (9.0, 12.7)

MSKCC status

Good

Intermediate

Poor

11.0 (9.0, 14.5)

9.2 (8.1, 10.9)

4.0 (3.4, 7.2)

11.2 (10.7, 14.9)

9.1 (7.3, 12.7)

2.1 (1.8, 5.4)

BEV, bevacizumab; CI, confidence interval; IFN, interferon alfa; MSKCC, Memorial Sloan-Kettering Cancer Center; PFS, progression-free survival; TEM, temsirolimus.

Is There an Optimal Sequence of Drugs?

• Current therapeutic options are not considered

curative in late-stage disease

• Sequencing of agents is presently a community

standard of care

• There are no phase III data showing one specific

sequence is superior to another

– Data from phase II RECORD-3 suggest that mTOR ->

TKI is inferior to TKI -> mTOR

Sunitinib

50 mg/day**

RECORD-3: Study design

S

C

R

E

E

N

R

A

N

D

O

M

I

Z

E

*

Everolimus

10 mg/day

Sunitinib

50 mg/day**

Everolimus

10 mg/day

Study endpoints

Primary

•PFS 1st line

Secondary

•Combined PFS

•ORR 1st line

•OS

•Safety

1:1 Cross-over upon

progression

N=471 First line Second line

*stratified by MSKCC prognostic factors. **4 weeks on, 2 weeks off.

Motzer RJ et al. ASCO 2013 Abstract 4504

Primary endpoint: First-line PFS

0 3 6 9 12 15 18 21 24 27 30 33

0

10

20

30

40

50

60

70

80

90

100

Cu

mu

lati

ve e

ven

t-fr

ee p

rob

ab

ilit

y (

%)

Time (months)

Everolimus

Sunitinib

164 238 118 88 68 44 31 23 12 5 0 0

181 233 145 108 84 55 42 28 15 9 3 0

Number of patients still at risk

Everolimus (events/N=182/238)

Sunitinib (events/N=158/233)

K-M Median PFS (mo)

Everolimus Suntinib

7.85 10.71

Hazard ratio=1.43

Two-sided 95% CI [1.15, 1.77]

Motzer RJ et al. ASCO 2013 Abstract 4504

RECORD-3: Secondary endpoints

Motzer RJ et al. ASCO 2013 Abstract 4504

SUN EVE HR (2-sided 95% CI)

ORR (%) 26.6 8.0

CR (%) 1.3 0.4

PR (%) 25.3 7.6

SD (%) 51.9 57.6

First PFS favorable risk (months) 13.40 11.07 1.20 (0.83,1.75)

First PFS poor risk (months) 2.99 2.63 1.73 (0.96, 3.12)

First PFS clear cell (months) 10.84 8.08 1.39 (1.10, 1.75)

First PFS non clear cell (months) 7.23 5.09 1.54 (0.86, 2.75)

SUNEVE EVESUN HR (2-sided 95% CI)

Crossed to 2nd line 42.9% 45.4%

Combined PFS (months) 25.79 21.13 1.28 (0.94, 1.73)

OS (months) 32.03 22.41 1.24 (0.94, 1.64)

Dovitinib: FGF Inhibitor

Fibroblast Growth Factor

(FGF) pathway is a potential

resistance mechanism to

VEGF-targeted therapies

Dovitinib (TKI258) is an oral

tyrosine kinase inhibitor that

targets FGFR, VEGFR,

PDGFR, and other kinases

Semrad, CLC 2012

DOVE Trial: Study Design

Key Eligibility Criteria

• Metastatic RCC with clear cell

component

• 1 prior VEGF-targeted therapy

and 1 prior mTOR inhibitor

• Other anticancer therapies

permitted (cytokines)

• Progressive disease within 6

months of last targeted

therapy

• Measurable disease

Sorafenib

400 mg

twice daily

Dovitinib

500 mg/day

5 days on/2 days off

R

A

N

D

O

M

I

Z

A

T

I

O

N

1:1

Stratification

MSKCC risk group: favorable, intermediate, poor

Geographic region: Japan, Asia Pacific,

Europe/Middle East, Americas

Motzer, ESMO 2013

• Primary Endpoint: PFS (central review)

• 33% risk reduction (hazard ratio = 0.67)

• 550 patients randomized to observe the 411 events

needed for 96% powera

Progression-Free Survival (Central)

100

80

60

40

20

0

0 3 6 9 12 15 18 21

Months

Pro

ba

bil

ity (

%)

eve

nt-

free

284 148 41 20 3 1 1 0 Dovitinib

286 152 42 12 2 1 0 0 Sorafenib

n/N Median, months

(95% CI)

Hazard Ratio

(95% CI)

Dovitinib 209/284 3.7 (3.5-3.9) 0.86 (0.72-1.04)

P = .063a Sorafenib 231/286 3.6 (3.5-3.7)

Patients at risk

a1-sided based on

stratified log-rank test

Interim Overall Survival

100

80

60

40

20

0

0 3 6 9 12 15 18 21

Months

Pro

ba

bil

ity (

%)

eve

nt-

free

284 246 165 102 51 23 9 0 Dovitinib

286 242 160 95 52 22 7 0 Sorafenib

n/N Median, months

(95% CI)

Hazard Ratio

(95% CI)

Dovitinib 130/284 11.1 (9.5-13.4) 0.96 (0.75-1.22)

Sorafenib 135/286 11.0 (8.6-13.5)

Patients at risk

Maximum % Change in Target Lesions and Objective Response Rate (Central)

100

75

50

25

–25

Be

st

% c

ha

ng

e f

rom

ba

se

lin

e

(me

as

ura

ble

le

sio

ns

)

0

– 75

– 50

– 100

Best response

Dovitinib n = 284

PR, % 4

SD, % 52

PD, % 29

UNK/other, % 15

Best response

Sorafenib n = 286

PR, % 4

SD, % 52

PD, % 31

UNK/other, % 13

Future Directions

1. Biology-based drug development

2. Predictive biomarkers to select therapy

3. Revisiting immunotherapy

“Drugging” driver mutations in clear cell RCC

Gerlinger, NEJM 2012; Varela, Nature 2011

Biology-based drug development

• Restoring tumor

suppressor

function is a drug

development

challenge

• Oncogenes easily

“druggable” but not

common in RCC

Vander Heiden, Science 2009

Biology-based drug development

Serum lactate dehydrogenase (LDH) as a predictive

biomarker for mTOR inhibition in patients with mRCC

Predictive biomarkers to select therapy

0 6 12 18 24 30

Time (months)

0.0

0.2

0.4

0.6

0.8

1.0

Su

rviv

al

Pro

bab

ilit

y

LDH <1 ULN: 11.15 mo LDH >1 ULN: 5.63 mo

Time (months)

0.0

0.2

0.4

0.6

0.8

1.0

Su

rviv

al

Pro

bab

ilit

y

6 12 18 24 30 0

Log rank p-value = 0.5138

Median Survival Time:

Temsirolimus: 11.74 mo

IFN-α: 10.36 mo

HR 0.90 (95％ Cl 0.61-1.22)

NORMAL LDH (<1x ULX)

Time (months)

0.0

0.2

0.4

0.6

0.8

1.0

Su

rviv

al

Pro

bab

ilit

y

6 12 18 24 30 0

Log rank p-value = 0.0017

ELEVATED LDH (≥1x ULX) Median Survival Time:

Temsirolimus: 6.88 mo

IFN-α: 4.18 mo

HR 0.56 (95％ Cl 0.38-0.81)

Median Survival Time:

HR 1.97(95% CI 1.54-2.47)

Log rank p-value < 0.0001

OS in patients with normal pretreatment serum LDH (n=140)

OS in patients with elevated pretreatment serum LDH (n=264)

Armstrong AJ, et al. JCO 2012

IL-6 is both prognostic and predictive: VEGFR-TKI therapy

Tran & Heymach; Lancet Oncol 2012

Predictive biomarkers to select therapy

Randomize

Temsirolimus

Pazopanib

PROGRESS ION

Newly diagnosed metastatic

ccRCC

Poor Risk

(Heng criteria)

Stratification

LDH (local)

Mandatory

Plasma (for biomarkers)

PBMCs

FFPE tumor tissue

(patient must agree to

release)

Phase III study 562 patients

•Co-Primary Endpoints: Validate LDH and IL-6 as predictive plasma markers for PFS

PFS (TKI vs mTOR)

•IL-6, LDH are candidate biomarkers, but others to be tested as well.

•Biomarkers are integral to the study, but not measured pre-randomization

•Other biomarkers: Other Plasma CAFs

SNPs (PBMCS)

Tissue based Markers

Proposed Intergroup Trial in Poor Risk RCC

Interim analyses •Evaluate for PFS in TKI vs mTOR

N=562

NEJM 2012

Revisiting Immunotherapy

PDL1 expressed in ~20% of RCC

Revisiting Immunotherapy

BMS-936558

Topalian, NEJM 2012

Targeting PD1

Revisiting Immunotherapy

Cho, ASCO 2013

• MPDL3280A: Engineered Anti-PDL1 Antibody

• Phase 1A trial in solid tumors (RCC = 55 pts)

• No MTD, DLT, deaths

• Most AEs: Grade 1 or 2

RCC

(n=47 evaluable)

RECIST SD > 24

weeks

24 week PFS

All 13% 32% 53%

Clear cell 13% 35% 57%

Non-clear cell 17% 0 20%

PDL1 + PDL1 - All

20% (2/10) 10% (2/21) 13% (6/47)

RECIST RR by PD-L1 expression

Targeting PD-L1

Metastatic Clear Cell RCC: Future Algorithm

BIOLOGIC

PROFILE

Initial Assessment:

MOLECULAR PROFILING OF

TUMOR AND HOST

(+ CLINICAL FEATURES)

Sensitive to

VEGF-

targeted

therapy

Sensitive to

mTORi Sensitive to

immunotherapy

INITIAL CHOICE

OF THERAPY Immunotherapy VEGF-targeted mTORi

SUBSEQUENT

THERAPY Based on predicted resistance patterns

from molecular profile

Primary resistance

to known agents

Clinical trial

Tumor: VHL, HIF,

mTOR, AKT, s6k,

MET, FGF, PD-L1,

etc.

Serum markers:

IL6, LDH

Conclusions

● Frontline mRCC treatment is guided by

prognostic (rather than predictive) groups

● VEGFR-targeted therapy is standard for

good/intermediate risk patients in frontline

setting

● Targeting molecular drivers will likely result in

better outcomes

● Need to address biomarker development,

intratumoral heterogeneity, and drug resistance