Combination of variations in inflammation- and endoplasmic reticulum-associated genes as putative biomarker for bevacizumab response in KRAS wild-type colorectal cancer

Ana Barat,Diether Lambrechts,Chiara Cremolini,Darran P O’connor ,Deborah A Mcnamara,Timo Gaiser,H Verheul ,Heinz Josef Lenz ,Annette T Byrne,William M Gallagher,Bauke Ylstra,Zhi‐Ying Wu ,Bozena Fender,Johannes Betge,Nicole C.t Van Grieken ,Aparna R Parikh ,Bruce Moran,Fotios Loupakis,Sudipto Das,Verena Murphy,Elaine W Kay,Matthias Ebert ,Rut Klinger,Bryan T Hennessy,Dominiek Smeets,Shu Cao,Nadine Schulte,Christoph Mancao,Orna Bacon,Jochen H M Prehn

doi:10.1038/s41598-020-65869-2

Abstract

Chemotherapy combined with the angiogenesis inhibitor bevacizumab (BVZ) is approved as a first-line treatment in metastatic colorectal cancer (mCRC). Limited clinical benefit underpins the need for improved understanding of resistance mechanisms and the elucidation of novel predictive biomarkers. We assessed germline single-nucleotide polymorphisms (SNPs) in 180 mCRC patients (Angiopredict [APD] cohort) treated with combined BVZ + chemotherapy and investigated previously reported predictive SNPs. We further employed a machine learning approach to identify novel associations. In the APD cohort IL8 rs4073 any A carriers, compared to TT carriers, were associated with worse progression-free survival (PFS) (HR = 1.51, 95% CI:1.03–2.22, p-value = 0.037) and TBK1 rs7486100 TT carriers, compared to any A carriers, were associated with worse PFS in KRAS wild-type (wt) patients (HR = 1.94, 95% CI:1.04–3.61, p-value = 0.037), replicating previous findings. Machine learning identified novel associations in genes encoding the inflammasome protein NLRP1 and the ER protein Sarcalumenin (SRL). A negative association between PFS and carriers of any A at NLRP1 rs12150220 and AA for SRL rs13334970 in APD KRAS wild-type patients (HR = 4.44, 95% CI:1.23–16.13, p-value = 0.005), which validated in two independent clinical cohorts involving BVZ, MAVERICC and TRIBE. Our findings highlight a key role for inflammation and ER signalling underpinning BVZ + chemotherapy responsiveness.

Highlights

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in both men and women and is associated with high mortality and morbidity[1]
For VEGFR2/KDR rs11133360 C/T, TT carriers had improved OS (HR = 0.63, 95% CI: 0.40–0.99, p-val = 0.045) in APD, partially in line with our earlier study that any T at this locus was associated with improved progression-free survival (PFS) in metastatic colorectal cancer (mCRC), renal cell carcinoma and breast cancer patients treated with BVZ (6,7,22 and references therein)
In this study we have investigated previously discovered single-nucleotide polymorphisms (SNPs) associated with BVZ-responsiveness, and used a machine-learning approach to select new candidate germline SNPs

Summary

Introduction

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in both men and women and is associated with high mortality and morbidity[1]. It has been reported that AA carriers for rs8602 on MKNK1, a gene that upregulates angiogenic factors, had worse PFS in KRAS wt patients[13], and AA carriers for rs4588 on GC, a vitamin D-binding protein, had shorter OS14 in two independent cohorts of patients treated with BVZ + chemotherapy Notwithstanding these studies, identifying and validating predictive biomarkers for BVZ remains an urgent clinical need. To this end we have performed exome sequencing to assess germline SNPs in a retrospective cohort of 180 mCRC patients treated with BVZ + chemotherapy regimens as part of the ANGIOPREDICT (APD) study[17,18,19]. We have employed repeated cross-validated Cox penalized regression as a ML approach to select SNPs as candidate biomarkers to predict therapy outcome, and validated novel identified SNPs in two independent clinical cohorts

Methods

Results

Conclusion