AbstractChemotherapy 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.