Objective: To examine genomic correlates of conversion to resection (CTR and overall survival (OS) in patients with initially unresectable colorectal liver metastasis (IU-CRLM) treated with combination systemic and hepatic artery infusion (HAI) chemotherapy.
Background: In patients presenting with IU-CRLM, combination systemic and HAI chemotherapy enables CTR with associated long-term OS in a subset of patients. Genomic correlates of CTR and OS in IU-CRLM have not been previously explored.
Methods: Specimens from IU-CRLM patients receiving systemic/HAI chemotherapy (2003-2017) were submitted for next-generation sequencing. Fisher Exact test assessed associations with CTR, and Kaplan-Meier/Cox methods assessed associations with OS from HAI initiation.
Results: Of 128 IU-CRLM patients, 51 (40%) underwent CTR at median 6 months (range: 3-35) from HAI initiation. CTR and persistently unresectable cohorts differed significantly in preoperative systemic chemotherapy exposure, node-positive primary status, and size of largest liver metastasis. Median and 5-year OS was 66 months and 51%. CTR was associated with prolonged survival (time-dependent HR 0.23,95% CI: 0.12-0.46, P < 0.001). The most frequently altered genes were APC (81%), TP53 (77%), and KRAS (37%). Oncogenic mutations in SOX9 and BRAF were associated with CTR. BRAF mutations, any RAS pathway alterations, and co-altered RAS/RAF-TP53 mutations wereassociated with worse survival. Classification and regression tree analysis defined prognostically relevant clusters of genomic risk to reveal co-altered RAS/RAF-TP53 as the highest risk subgroup. Co-altered RAS/RAF-TP53 remained independently associated with worse survival (HR 2.52, 95% CI: 1.37-4.64, P = 0.003) after controlling for CTR, number of liver metastases, and preoperative extrahepatic disease.
Conclusions: Distinct genomic profiles are associated with CTR and survival in patients with IU-CRLM treated with HAI/systemic chemotherapy. Presence of SOX9, BRAF , and co-altered RAS/RAF- TP53 mutations are promising biomarkers that, when validated in larger datasets, may impact treatment of IU-CRLM patients.
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