93P - Biomarker selection of liver metastatic colorectal patients for anti-EGFR monoclonal antibodies: A machine learning analysis

Background

New predictive biomarkers for cetuximab-resistance for patients with RAS wild-type colorectal liver metastases (CRLM).

Methods

216 patients with initially unresectable liver-limited RAS wild-type CRLM were identified from previous clinical studies. Among these patients, 103 patients received chemotherapy (mFOLFOX6 or FOLFIRI) plus cetuximab, and 113 received chemotherapy alone as first-line treatment. Next-generation sequencing of primary tumors was done for single nucleotide polymorphism according to custom panel. The patients receiving cetuximab-based chemotherapy were divided into two groups: one group was cetuximab-resistant group and the other group was cetuximab-sensitive group. Potential predictive biomarkers were determined by “random forest" machine learning.

Results

Ten potential predictive genes, namely RET, PTPN11, FLT3, AKT1, ACTN4, ERBB4, FGFR3, MDC1, CUL9, and ZNF462, were identified. In the cohort of cetuximab-based chemotherapy, patients with all-wild-type genes had markedly improved median progression-free survival (12.0 vs. 4.0 months, P < 0.0001) and overall survival (37.0 VS. 24.0 months, P < 0.0001) compared with those with gene mutation; In the cohort of at-least-one gene mutation, patients receiving chemotherapy alone had comparable median PFS (4.0 VS. 4.0 months, P = 0.9498). Moreover, mutated are more common in patients with right-sided colon cancer.

Conclusions

Ten new predictive mutations help to refine the selection of RAS and BRAF wild-type metastatic colorectal cancer patients candidates for anti-EGFRs.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Zhongshan Hospital.

Funding

The National Natural Science Foundation of China.

Disclosure

All authors have declared no conflicts of interest.