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The quest to improve the molecular classification of CRC: myth or reality. Abstracts # 3515, 3516, 3517, 3518, 3519, 3520, 3521. Josep Tabernero , MD Vall d’Hebron University Hospital and Vall d’Hebron Institute of Oncology (VHIO) Barcelona. Disclosure.
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The quest to improve the molecular classification of CRC: myth or reality Abstracts # 3515, 3516, 3517, 3518, 3519, 3520, 3521 Josep Tabernero, MD Valld’Hebron University Hospital and Valld’Hebron Institute of Oncology (VHIO) Barcelona
Disclosure • Advisory role for Amgen, BMS, Genentech, Imclone, Merck-Serono, Novartis, Roche, Sanofi-Aventis and Symphogen
Amphiregulin, Epiregulin and EGFR gene copy number A3516 – Poster Board #8: Richard Adams et al. Epiregulin (EREG) and amphiregulin (AREG) gene expression to predict response to cetuximab therapy in combination with oxaliplatin (Ox) and 5FU in first-line treatment of advanced colorectal cancer (aCRC) – analysis of the phase III COIN trial A3519 – Poster Board 11#: Sebastian Stintzinget al.Ligand expression of the EGFR ligands amphiregulin, epiregulin, and amplification of the EGFR gene to predict for treatment efficacy in KRAS wild-type mCRC patients treated with cetuximab plus CAPIRI and CAPOX: Analysis of the randomized phase II AIO CRC-0104 trial
Amphiregulin/Epiregulin • EGFR ligands: • 1 in C. Elegans • 4 in Drosophila • 7 in mammals: EGF, TGF-α, HB-EGF, amphiregulin (AREG), betacellulin, epiregulin (EREG) and epigen1 • EREG and AREG bind more weakly to EGFR than EGF but much more potently and prolonged • EREG preferentially activates heterodimers2 • High gene expression levels of EREG and AREG predict response to cetuximab3-5 1Singh, AB et al. Cell Signal2005; 2Shelly, M et al. J BiolChem 1998 3Khambata-Ford, S. et al. J ClinOncol 2007; 4Tejpar S, et al. J ClinOncol2009; 5Tabernero, J. et al. J ClinOncol 2010
Adams: Results (2). EREG & KRAS in control arm EREG, OS EREG, PFS 1.00 KRAS-mut low expression Global log-rank test: P=0.004 Global log-rank test: P=0.014 KRAS-mut high expression 0.75 KRAS-wt low expression Survival 0.50 KRAS-wt high expression 0.25 0.00 0 6 12 18 24 30 36 42 0 6 12 18 24 30 36 42 Time from randomisation (months) Time from randomisation (months) • The combination of KRAS=wt and high EREG expression selects a good prognostic group. • This is in the absence of cetuximab use, suggesting previously reported similar findings in a non randomised series of patients treated with cetuximab (Jacob) may be a prognostic effect not a predictive effect.
Adams: Results (3). EREG predictive Modelled survival plots by chemo regimen within the KRAS-wt subgroup 1.0 0.8 0.6 Survivor function 0.4 0.2 0 0 6 12 18 24 30 36 42 0 6 12 18 24 30 36 42 Time from randomisation (months) Time from randomisation (months) KRAS-wt, mFOLFOX KRAS-wt, Xelox Interaction P=0.0042 Interaction P=0.14 In the mFOLFOX subgroup, high EREG expression is predictive of increased cetuximab efficacy. Arm A Arm B Upper quartile of EREG expression Median of EREG expression Lower quartile of EREG expression
Stitzing: Patients and methods 1Moosmann et al. J ClinOncol 2011
Adams & Stintzing: Conclusions • More robust population for the COIN than the AIO study • COIN (525 pts, control arm): • EREGand AREG highly prognostic, even after adjustment for other known factors (including KRAS and BRAF) • High EREG expression predictive for cetuximab +mFOLFOX in KRAS-wt(p=0.0042), not XELOX • AIO (59-62 pts, no control arm): • AREG, EREG, and EGFR-amplification predictive for cetuximab + CAPIRI/CAPOX • In KRAS-wt EGFR-FISH and AREG expression more predictive
Adams & Stintzing: Implications • The quest to identify other predictive factors for cetuximab: • We are not yet there • Are they prognostic? • EREG & AREG: • Pros: Define addicted tumors to EGFR and predicts effect to EGFR inhibition, consistent data1-3, prognostic (?) • Cons: threshold, method, validation • Not ready for the clinic • EGFR amplification: • Pros: Define addicted tumors to EGFR and may predict effect to EGFR inhibition, conflicting data • Cons: threshold • Not ready for the clinic 1Khambata-Ford, S. et al. J ClinOncol 2007; 2Tejpar S, et al. J ClinOncol2009; 3Tabernero, J. et al. J ClinOncol 2010
BRAF, PIK3CA and other KRAS mutationsPTEN loss A3515 – Poster Board #7: Derek Jonker et al.BRAF, PIK3CA, and PTEN status and benefit from cetuximab in the treatment of advanced colorectal cancer. Results from NCIC CTG / AGITG CO.17: A phase III trial of cetuximabvs best supportive careA3520 – Poster Board #12: David Tougeronet al.Effect of low-frequency KRAS mutations on the response to anti-EGFR therapy in metastatic colorectal cancer
Jonker: Results (1) PFS N=572 N=230 N=198 N=10 N=57 N=148
Jonker: Results (2) OS N=572 N=230 N=198 N=10 N=57 N=148
Jonker: Conclusions Jonker: Implications • Neither PIK3CA-mt nor PTEN expression were predictive • BRAF-mt limited number of samples, single agent • BRAF-mt: • Pros: Define tumors with less (no) benefit to EGFR inhibitors. Consistent data with irinotecan-based chemotherapy in refractory1, 2nd-line2 and 1st-line3 settings. Validated method • Cons: BRAF-mt uncommon • Ready for the clinic: not from regulatory but… • PIK3CA-mt: • Inconsistent data, largest dataset predictive (ex 20 vs 9)1 • PTEN loss: • Inconsistent data (60 vs 40%), different methodology (-/+ vs H-score), low concordance4-6 1De Roock, W et al. Lancet Oncol 2011; 2Seymour S. et al. Proc ASCO 2011; 3Van Cutsem, E. et al. J ClinOncol 2011; 4Loupakis, F et al. J ClinOncol 2009; 5Frattini, M et al. Br J Cancer 2007; 6Perrone F et al. Ann Oncol 2009; 7Laurent-Puig P et al. J ClinOncol 2009
Tougeron: Results PFS 6.0 months 2.7 months PFS 6.0 ± 0.3 months P<0.01 2.7 ± 0.5 months
Tougeron: Conclusions Tougeron: Implications • Tumors with KRAS-lowmt have lower benefit from anti-EGFR MoAbs than those KRAS-wt • Very provocative data • This data may suggest clonal heterogeneity and selection under treatment pressure • More data is coming soon • The challenges: • More sensitive methods to detect KRAS mutations, for enhanced predictions of resistance to anti-EGFR MoAbs in mCRC are required: • Direct sequencing ≈ 10-20% alleles • Mass-Array techs ≈ 5-10% alleles • RT-PCR ≈ 1-2% alleles • Change of paradigm in treatment: plasticity, heterogenous disease, treatment for multiple and/or predominant clones?
Micro RNA signatures A3521 – Poster Board #13: Federico. Cappuzzo et al.MicroRNA signature predicts sensitivity to anti-EGFR monoclonal antibodies in metastatic colorectal cancer (mCRC).
Cappuzzo: Results (1) • MicroRNA (miRNA) are a class of small non-coding RNA that bind to mRNA, silencing their mRNA target • Several recent studies have uncovered a relationship between EGFR pathway and miRNA • Available data indicate that miRNA levels could modulate sensitivity to target agents including anti-EGFR compounds1-2 • Let-7 complementary site LCS6 (T>G) polymorphism: T/T worse prognosis Let-7c/miR-99a/miR-125b 1Graziano, F. et al. Pharmacogenomics 2010,; 2Zhang, W, et al. Ann Oncol 2011
Cappuzzo: Results (2). Let-7c/miR-99a/miR-125b cluster levels in both cohorts High Low + censored High Low + censored PFS OS Time (months) Time (months)
Cappuzzo: Results (3). Let-7c/miR-99a/miR-125b cluster levels in KRAS/BRAF wt High Low + censored High Low + censored PFS OS Time (months) Time (months)
Capuzzo: Conclusions • MiR-99a/Let-7c/miR-125b signature seems useful for improving selection of KRAS/BRAF wild-type mCRC patients candidate for anti-EGFR strategies • Provocative data • How these miRNAs were selected? • Validation set needed • Predictive vs prognostic • No evaluation of the previously published LCS6 (T>G) • The dark side of the moon: • Only effects in PFS and OS, not in RR • We need to better understand the biological effect of these miRNAs to dissect their future role in CRC Capuzzo: Implications
VEGF/VEGFR polymorphisms A3518 – Poster Board #10: Chiara Cremolini et al.Prospective evaluation of candidate SNPs of VEGF/VEGFR pathway in metastatic colorectal cancer (mCRC) patients (pts) treated with first-line FOLFIRI plus bevacizumab (BV)
Cremolini: Patients and methods 1Loupakis, F. et al. BMC Cancer 2011
Cremolini: Results (1). VEGF rs833061 C/T variants and PFS No association of VEGF rs833061 C/T variants with PFS was found TT (N= 147) median PFS: 10.2 mos C- (N= 276) median PFS: 10 mos HR: 1.17 (0.91-1.50) Log-rank test p=0.218
Cremolini: Results (2). Other SNPs & PFS • At the univariate analysis, no association of other candidate SNPs with PFS was found, except for VEGFR2 12505758 C/T variants C- (N= 118) mPFS: 9.5 m TT (N= 306) m PFS: 10.9 m HR: 1.40 (1.07-1.84) Log-rank test p=0.015 CC (N= 11) mPFS: 10.7 m CT (N= 107) mPFS: 9.5 m TT (N= 306) mPFS: 10.9 m Log-rank test p=0.047 • At the multivariate analysis, including Köhne score, mucinous histology, ECOG PS, LDH levels and primary tumor site as covariates, the association of VEGFR2 125057581 C- variants with shorter PFS was still significant (HR: 1.402 [1.079-1.822], p=0.012) • Significance was lost when applying multiple testing correction 1Lambrechts, D. et al. Ann Oncol 2011
Cremolini: Conclusions • No confirmation of the predictive value of VEGF rs833061 C/T and other SNPs • The prospective validation is an essential step on biomarkers’ way toward clinical practice • Initial publication: 111 pts FOLFIRI + bev; 107 pts FOLFIRI T/T shorter PFS (HR 2.13, p=0.0027) • Current presentation: 424 pts FOLFIRI + bev • No other VEGF & VEGFR SNPs have been confirmed • No clear advances in the field of personalized medicine with angiogenesis inhibitors (bevacizumab) Cremolini: Implications 1Loupakis, F. et al. BMC Cancer 2011
TP53 status and gender in adjuvant CC A3517 – Poster Board #9: Robert Warren et al.A novel interaction of genotype, gender and adjuvant treatment in survival after resection of stage III colon cancer: results of CALGB 89803
TP53 in colon cancer • TP53 mutations occur in ≈ 50% of CRCs • 95% occur in the DNA binding domain (exons 5-8) • This is composed by Zn-binding and non-Zn binding regions • They may have different functional implications
Warren: Results (1) Kaplan-Meier OS estimates • 274/607 had TP53 mutations • 190 cause single aa changes resulting in non-functional p53
Warren: Conclusions • No confirmation of the predictive value of VEGF rs833061 C/T and other SNPs • The interface of patient characteristics and tumor characteristics • Very provocative results suggesting that clustering of CRC may be closer to us than we expect: • Combination of TP53 status and gender • Clear opportunity for validation: PETACC-3 study • Please contact A. Roth or S. Tejpar!!!! Warren: Implications
Conclusions • Each of these studies constitute and Academic effort to personalize the treatment in patients with CRC by tuning the target population beyond the standard of care • In order to completely define the ultimate role of the different prognostic/ predictive factors more international collaboration is needed
Acknowledgements ASCO Program Committee Poster presenters for providing their presentations in a timely fashion Eduardo Vilar, MD PhD Audience