Personalized Therapy in Colorectal Cancers
J. Randolph Hecht, MDProfessor of Clinical Medicine
Director, UCLA GI Oncology ProgramDavid Geffen School of Medicine at UCLA
What Does Personalized Therapy Mean?
• Right Treatment
• Right Patients
Biomarker• NIH Definition: a characteristic that is objectively
measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.
• Predictive: (Ex: HER-2, BRAF, cytogentic abnormalities)
• Prognostic: (Ex: HER-2, KRAS)
Biomarkers
Evaluating Predictive Biomarkers: Trial Design
Patient Population R
Biomarkerpositive
Biomarkernegative
Receive treatment
Do not receive treatment
Receive treatment
Do not receive treatment
Biology of Colorectal Cancers
• Subgroup Analysis– Breast cancer does it, is it time for CRC?
• CIN vs MSI vs CIMP+– CIN: Majority of tumors MSS, APC mutation– MSI: Abnormal DNA mismatch repair
• ~15%• Most Sporadic (BRAF mut); others HNPCC
• Molecular Subgroup Analysis
Tabernero, ASCO GI 2013
Uronis, ASCO GI 2013
Cancer Genome Atlas Network, Nature 2012
Biomarkers• Histology: TNM
Dukes, J Path Bacteriol, 1932
Survival Rates of by Stage of Adenocarcinoma of the Colon
Edge SB, et al. AJCC cancer staging manual. 2010. Data from the SEER 1973-2005 Public Use File diagnosed in years 1998-2000.
Surv
ival
Rat
e
0
20
0
40
60
80
100
1 2 3 4 5
30
50
70
90
10
100100100100100100100100
IIIAIIBIICIIIAIIIBIIIC
IV
91.489.985.466.098.383.471.939.9
87.083.477.852.588.070.850.319.7
82.677.869.145.383.659.339.011.3
78.272.062.941.579.151.732.97.6
74.066.558.637.373.146.328.05.7
Yrs From Diagnosis
Other Putative Biomarkers:
• Molecular pathology• CTCs• Molecular abnormalities
– Mutations– microRNAs
• Gene expression profiles
Where Would Biomarkers Be Most Useful?
• Adjuvant– Treat those who would benefit– Don’t treat those that won’t
• Metastatic Disease– We have multiple agents. How can we
choose for safety and efficacy?
Stage II Colon Cancer
• Which stage II colon cancer patients should be treated with adjuvant chemotherapy?– 75% to 80% cured with surgery alone– Benefit of chemotherapy is small and no
consensus on whom to treat or on how to identify whom to treat
• Decision to give chemotherapy based on– Clinical/pathologic markers of risk– Molecular biomarkers – Not informative for majority of patients
1.0
0.8
0.6
0.4
0.2
0
Stage II Stage III
Follow-up (Yrs)
Surgery alone: 66.8%Surgery + FU-based chemotherapy: 72.2%
Surgery alone: 42.7%Surgery + FU-based chemotherapy: 53.0%
0 1 2 3 4 5 6 7 8
1.0
0.8
0.6
0.4
0.2
0
Sargent D, et al. J Clin Oncol. 2009;27:872-877.
∆ = 5.4%P = .026
0 1 2 3 4 5 6 7 8
∆ = 10.3%P < .0001
Adjuvant Therapy Increases OS:ACCENT Database of 20,898 Patients
Prob
abili
ty o
f Sur
viva
l
Prob
abili
ty o
f Sur
viva
l
Determining Who Benefits From Adjuvant Therapy in CRC
• Risk assessment in stage II (III) CRC: prognostic factor(s) of recurrence of disease and predictive factor(s) to the treatment.– High-risk prognostic factors[1]
• Stage II: T4, tumor perforation, bowel obstruction, poorly differentiated tumor, venous invasion, or < 10 examined nodes
• Stage III: age, lymph node involvement, T stage, tumor obstruction, differentiation
– Defective mismatch repair and microsatellite instability[2-5]
1. André T, et al. J Clin Oncol. 2009;27:3109-3116. 2. Hutchins G, et al. J Clin Oncol. 2011;29:1261-1270. 3. Sargent DJ, et al. J Clin Oncol. 2010;28:3219-3226. 4. Sinicrope FA, et al. J Natl Cancer Inst. 2011;103:863-875. 5. Ribic CM, et al. N Engl J Med. 2003;349:247-257.
MOSAIC: Exploratory Analysis of DFS and OS in “High-Risk” Stage II CRC
André T, et al. J Clin Oncol. 2009;27:3109-3116.
0.4 0.6 0.8 1.0 1.2 1.4 1.6
Stage II
High-risk stage II
Stage III
Stage II
High-risk stage II
Stage III
OS at 6 Yrs
DFS at 5 Yrs
HR
Favors FOLFOX4 Favors LV5FU2
Missed Micrometastases
IHC+
H&E
LN “N0”
RT-PCR+
MMR-D (MSI) Is a Favorable Prognostic Marker in Stage II (and III) Colon Cancer
Study StageTreatment
EndpointMMR-D vs MMR-P
HR (95% CI; P Value)
Ribic et al[1] II/IIISurgery alone OS 0.31 (0.14-0.72; .004)
Roth et al(PETACC-3)[2]
II5-FU/LV ± irinotecan
Relapse-free survival
OS
0.27 (0.10-0.72; .0094)0.14 (0.03-0.64; .011)
Sargent et al[3] II/IIISurgery alone
DFSOS
0.46 (0.22-0.95; .03*)0.51 (0.24-1.10; .06*)
Gray et al(QUASAR)[4]
IISurgery alone
Recurrence-free interval 0.31 (0.15-0.63; < .001)
1. Ribic CM, et al. N Engl J Med. 2003;349:247-257. 2. Roth AD, et al. J Clin Oncol. 2010;28:466-474. 3. Sargent DJ, et al. J Clin Oncol. 2010;28:3219-3226. 4. Gray R, et al. J Clin Oncol. 2011;29:4611-4619.
5-FU Not Beneficial and Survival Longer in Stage II Patients With MMR Deficiency
Sargent DJ, et al. J Clin Oncol. 2010;28:3219-3226.
No Adjuvant 5-FU Chemotherapy
Adjuvant 5-FU Chemotherapy
HR for OS: 0.47 (95% CI: 0.26-0.83;
P = .004)
HR for OS: 0.78 (95% CI: 0.49-1.24;
P = .28)
Perc
ent A
live
and
Prog
ress
ion
Free
Yrs0 21 3 4 5
0
20
40
60
80
100
MMR-d (n = 86)MMR-p (n = 426)
HR: 0.79 (95% CI:0.49-1.25; P = .30)
Perc
ent A
live
and
Prog
ress
ion
Free
Yrs0 21 3 4 5
0
20
40
60
80
100
MMR-d (n = 79)MMR-p (n = 436)
HR: 0.51 (95% CI:0.29-0.89; P = .009)
• Gene signatures provide prognostic, not predictive, information• 12-gene recurrence score assay validated for recurrence risk in
stage II patients
– QUASAR: 12% (low risk) vs 22% (high risk) 3-yr recurrence risk[1]
– CALGB 9581: 13% (low risk) vs 21% (high risk) 5-yr recurrence in T3, MMR proficient disease[2]
1. Gray RG, et al. J Clin Oncol. 2011;29:4611-4619. 2. Venook AP, et al. ASCO 2011. Abstract 3518.
Genomic Tests for CRC Risk Stratification
Ris
k of
Rec
urre
nce
at 5
Yrs
(%)
Colon Cancer Recurrence Score0 2010 30 40 50 60
0
5
10
15
20
25
30
35
70
Risk95% CI
Ris
k of
Rec
urre
nce
at 3
Yrs
(%)
Recurrence Score0 2010 30 40 50 60
0
5
10
15
20
25
30
35
70
P = .004
Personalized Therapy For Metastatic Disease
• Cytotoxics
• Anti-EGFR Antibodies
• Anti-VEGF Pathway Agents
Cytotoxic Agents
• Fluoropyrimidines– TS: A target. No clear evidence for choosing therapy– DPD: Dihydropyrimidine dehydrogenase deficiency
associated with severe FP toxicity• Testing only in patients with toxicity
• Irinotecan– UGT1A1*28 (10% of North Americans)
• Originally associated with diarrhea but later studies with neutropenia instead
• In package insert, but not used– Topo 1: Conflicting data
• Oxaliplatin– ERCC1: Unproven for efficacy
Anti-EGFR Agents
EGFR Signaling Pathway
Extracellular
Intracellular
Ligand
EGFR
PI3K
Akt
Ras
Raf
MEK
MAPK
Cell motility
MetastasisAngiogenesis
Proliferation
Cell survivalDNA
PTEN
KRAS as a Biomarker for Panitumumab Response in Metastatic CRC
• PFS log HR significantly different depending on KRAS status (p < .0001)• Percentage decrease in target lesion greater in patients with wild-type KRAS receiving
panitumumab• Approved in EU in KRAS WT
Patients With Mutant KRAS
Meanin Wks
Stratified log rank test: P < .0001
115/124 (93)
Patients With Wild-Type KRAS
1.00.9
Prop
ortio
n W
ith P
FS
0.80.70.60.50.40.30.20.1
00 2 4 6 8 10
Events/N (%)Medianin Wks
Pmab + BSCBSC alone
114/119 (96)12.37.3
19.09.3
HR: 0.45 (95% CI: 0.34–0.59)
12 14 16 18 20 22 24 26 28 30 32 3436 38 4042 44 46 48 50 52
Weeks
Prop
ortio
n W
ith P
FS
1.00.90.80.70.60.50.40.30.20.1
00 2 4 6 8 10 12 14 16 18 20 22 24 26 2830 32 3436 38 4042 44 46 48 50
Weeks
Pmab + BSCBSC alone Mean
in Wks
76/84 (90)
Events/N (%)Medianin Wks
95/100 (95)7.47.3
9.910.2
HR: 0.99 (95% CI: 0.73–1.36)
52
Amado et al., JCO 2008.
Tejpar et al., ASCO 2011
What About G13D (~20% mutations)
No Effect Of G13D in Larger Sample
Peeters ASCO GI 2012
EGFR Signaling Pathway
Extracellular
Intracellular
Ligand
EGFR
PI3K
Akt
Ras
Raf
MEK
MAPK
Cell motility
MetastasisAngiogenesis
Proliferation
Cell survivalDNA
PTEN
BRAF– V600E mutation relatively common in CRC (5-15%)
– Poor prognostic factor (Van Cutsem ASCO GI, 2010)• FOLFIRI+cetuximab PFS: 25.1 vs 14.1 months
– Inhibitors: sorafenib, PLX4032 (vemurafenib)
– PLX4032: 70% RR in V600E melanoma, but 5% in CRC
CI, confidence interval; CT, chemotherapy; HR, hazard ratio; mt, mutant; OS, overall survival; wt, wild-type
32 25 16 12 8 5 2 2 2 038 24 14 6 6 3 3 1 0 0
00CT
CT + cetuximab
Pro
babi
lity
of o
vera
ll su
rviv
al
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
180 6 12 24 6030 36 42 48 54Time (months)Number of patients
349 317 268 225 163 120 80 63 19 4381 350 283 212 149 107 63 46 17 2
00CT
CT + cetuximab
KRAS wt/BRAF wtHR [95% CI]: 0.840 [0.710–0.993]p=0.041 FOLFIRI / FOLFOX4 + cetuximab: (n=349) median 24.8 months FOLFIRI / FOLFOX4: (n=381) median 21.1 monthsKRAS wt/BRAF mtHR [95% CI]: 0.633 [0.378–1.060]p=0.079 FOLFIRI / FOLFOX4 + cetuximab: (n=32) median 14.1 months FOLFIRI / FOLFOX4: (n=38) median 9.9 months
Bokemeyer
Pooled analysis of OS in patients with KRAS wt/BRAF mt tumors
Other Markers (Unknown Benefit)
• Rare KRAS mutations• NRAS• Ligands (amphiregulin, epiregulin)• Copy Number
Anti-VEGF Pathway Drugs
None!
Molecular Profiling
• Multiple Targets (Caris, Foundation Medicine)• Sequencing• Explants
• No Evidence of Clinical Benefit• Hours of Physician Time
We are on the verge of truly personalized therapy for colorectal cancer
• We need to be able to identify subgroups by genetic alterations and activated pathways
• We need to validate molecular tests before selling them to the public
• We need to identify new targets for new drugs• We may have to find ways to do trials in small
subsets
BONUS
New indications for anti-VEGF pathway agents!!
Agents Targeting the Vascular Endothelial Growth Factor (VEGF) Pathway
VEGFR-2VEGFR-1PPP
PPPP
P
Endothelial cell Small-moleculeVEGFR inhibitors
(PTK787, sunitinib, sorafenib, regorafenib, axitinib)
Anti-VEGFR antibodies(IMC-1121b)
Soluble VEGF
receptors(VEGF-TRAP/ aflibercept)
VEGFAnti-VEGF antibodies
(bevacizumab)
Golden Age of CRC Therapeutics: Bevacizumab
Hurwitz H et al. N Engl J Med. 2004;350:2335-2342.
HR = 0.66, P <.001
Perc
ent S
urvi
ving
Duration of Survival (months)
1.0
0.8
0.6
0.4
0.2
0.00 10 20 30 40
IFL/bevacizumab IFL/placebo
20.315.6
10.6
100
80
60
40
20
00 10 20 30
Prog
ress
ion-
free
Sur
viva
l (%
)
Progression-Free Survival (months)
6.2
(n = 402)
(n = 411)
HR = 0.54, P <.001
What About Angiogenesis Inhibition After First Line Therapy?
• Bevacizumab• Aflibercept• Regorafenib
E3200: Overall SurvivalP
r o
b a
b i
l i
t y
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
OS (months)0 3 6 9 12 15 18 21 24 27 30 33 36
ALIVEDEAD MEDIANTOTALA:FOLFOX4 + bevacizumab 289 246 43 12.9B:FOLFOX4 290 257 33 10.8C:bevacizumab 243 216 27 10.2
HR = 0.76A vs B: p = 0.0018B vs C: p = 0.95
Giantonio BJ, et al. ASCO 2005
No first line bev!
BEV + standard first-line CT (either
oxaliplatin oririnotecan-based)
(n=820)
Randomise 1:1
Standard second-line CT (oxaliplatin or irinotecan-
based) until PD
BEV (2.5 mg/kg/wk) + standard second-line CT (oxaliplatin or irinotecan-
based) until PD
PD
ML18147 (TML) study design
CT switch:Oxaliplatin → IrinotecanIrinotecan → Oxaliplatin
Study conducted in 220 centres in Europe and Saudi Arabia
Primary endpoint • Overall survival (OS) from randomisation
Secondary endpoints included
•Progression-free survival (PFS)•Best overall response rate•Safety
Stratification factors • First-line CT (oxaliplatin-based, irinotecan-based)• First-line PFS (≤9 months, >9 months)• Time from last BEV dose (≤42 days, >42 days)• ECOG PS at baseline (0/1, 2)
Arnold 2012
OS: ITT populationO
S es
timat
e
Time (months)
1.0
0.8
0.6
0.4
0.2
00 6 12 18 24 30 36 42 48
No. at riskCT 410 293 162 51 24 7 3 2
0BEV + CT 409 328 188 64 29 13 4 1
0
CT (n=410)BEV + CT (n=409)
9.8 mo 11.2 mo
Unstratifieda HR: 0.81 (95% CI: 0.69–0.94)p=0.0062 (log-rank test)
Stratifiedb HR: 0.83 (95% CI: 0.71–0.97)p=0.0211 (log-rank test)
aPrimary analysis method; bStratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (≤9 months, >9 months), time from last dose of BEV (≤42 days, >42 days), ECOG performance status at baseline (0, ≥1)
PFS: ITT populationPF
S es
timat
e
Time (months)
1.0
0.8
0.6
0.4
0.2
00 6 12 18 24 30 36 42
No. at riskCT 410 119 20 6 4 0 0 0BEV + CT 409 189 45 12 5 2 2 0
CT (n=410)BEV + CT (n=409)
4.1 mo 5.7 mo
Unstratifieda HR: 0.68 (95% CI: (0.59–0.78) p<0.0001 (log-rank test)
Stratifiedb HR: 0.67 (95% CI: 0.58–0.78)p<0.0001 (log-rank test)
aPrimary analysis method; bStratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (≤9 months, >9 months), time from last dose of BEV (≤42 days, >42 days), ECOG performance status at baseline (0, ≥1)
What else does TML teach us?
• Affirms the limited utility of Registry studies regarding interventions and outcomes:– BRITE: 9.5 v. 19.2 OS beyond PD– TML: 9.8 v. 11.2
BRiTE findings not replicated; the publication* could be cited as an example of the pitfalls of Registry data
* Grothey et al, JCO, 2008 Venook 2012
Aflibercept (VEGF-TRAP)• Fully human fusion protein and
soluble recombinant decoy VEGF receptor composed of Domain 2 of VEGFR1 and Domain 3 of VEGFR2 fused to the Fc of IgG1
• Higher affinity for VEGF-A than bevacizumab and also blocks PlGF; T1/2 17 days
• EFC10262 (VELOUR )– Phase III Trial 2nd Line
FOLFIRI +/- VEGF-TRAP (Aflibercept)
• Where has it been?
VELOUR Study Design
Primary endpoint: overall survival
Sample size: HR=0.8, 90% power, 2-sided type I error 0.05
Final analysis of OS: analyzed at 863rd death event using a 2-sided nominal significance level of 0.0466 (α spending function)
Metastatic Colorectal Cancer
RANDOMIZE
Aflibercept 4 mg/kg IV, day 1 + FOLFIRI q2 weeks
Placebo IV, day 1+ FOLFIRIq2 weeks
1:1 Disease Progression Death
600
600Stratification factors:• ECOG PS (0 vs 1 vs 2)• Prior bevacizumab (Y/N)
VELOUR: Results
Van Cutsem, et al. WCGC 2011
VELOUR Study• Overall results
– Adding aflibercept to FOLFIRI in mCRC patients previously treated with an oxaliplatin-based regimen resulted in significant OS and PFS benefits
Van Cutsem E et al. ESMO/WCGC 2011, Barcelona, Abstract O-0024.
OS PFS
Overall Survival: Stratified by Prior Bevacizumab – ITT Population
Allegra 2012
Progression-Free Survival: Stratified by Prior Bevacizumab – ITT Population
Allegra 2012
TML/VELOUR
• Is aflibercept better than bevacizumab second-line?
• ? Differences in toxicity than bevacizumab
• What about anti-EGFR Ab? SPIRITT trial (KRAS WT) pending
Small Molecule TKIs
• Both Abs and TKIs may inhibit the “classic” VEGF-A/VEGFR-2 pathway
• Inhibition of multiple VEGF receptors may be important
• Inhibition of other receptors (Clean vs. Dirty)• c-kit, PDGF-R, RET, FGF-R
MAb
TKI
Godzilla vs. Mothra 1964
CRC: Graveyard of VEGFR TKIs
Negative Randomized Trials: 6365+ pts
SU5416 719CONFIRM 1 1168CONFIRM 2 855HORIZON II/III 1050/1614SUN1122 768SUN1104 191
TKI
TKI
TKI
TKITKI
VEGFR TKIs: Take 2
• Negative in combination with chemotherapy
• New studies with chemo free regimens
• Front-line vs salvage
Regorafenib: What A Difference a F Makes!
Regorafenib:• Small molecule inhibitor of VEGFR and
FGFR-1• CORRECT Trial Grothey et al. 760 pts 2:1• Chemorefractory mCRC vs BSC, interim
analysis• PFS: 1.9 v 1.7m (HR=0.493) p<0.000001• OS: 6.4 v 5.0m (HR=0.773) p=0.0051• Positive but is it clinically significant?
Overall survival (primary endpoint)
Primary endpoint met prespecified stopping criteria at interim analysis (1-sided p<0.009279 at approximately 74% of events required for final analysis)
1.00
0.50
0.25
0
0.75
200100500 150 300250 400350 450
Days from randomization
Sur
viva
l dis
tribu
tion
func
tion
Placebo N=255Regorafenib N=505
Median 6.4 mos 5.0 mos95% CI 5.9–7.3 4.4–5.8
Hazard ratio: 0.77 (95% CI: 0.64–0.94) 1-sided p-value: 0.0052
Regorafenib Placebo
Grothey 2012
1.00
0.50
0.25
0
0.75
200100500 150 300250 350
Days from randomization
Sur
viva
l dis
tribu
tion
func
tion
Placebo N=255Regorafenib N=505
Regorafenib Placebo
Median 1.9 mos 1.7 mos95% CI 1.9–2.1 1.7–1.7
Hazard ratio: 0.49 (95% CI: 0.42–0.58) 1-sided p-value: <0.000001
Progression-free survival (secondary endpoint)
Grothey 2012
Overall response and disease control rates(secondary endpoints)
*DCR = PR + SD; p<0.000001
Grothey 2012
Why these results?
• Possibly benefit from long term anti-VEGF inhibition (BRITE)
• Can anti-VEGF therapy worsen post-therapy outcome? (Bevacizumab Addiction)– Bevacizumab only leads to modest improvement in OS– VEGF inhibition may up-regulate other parts of pathway and other pathways– Preclinical models of increased metastasis with VEGFR-2 inhibition (Rip-
TAG Paez-Ribes, 2009 and sunitinib conditioning Ebos, 2009)– Differences between PFS and OS with PTK/ZK (Hecht JCO 2010)
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