Effect of Liver Metastases on Survival in Microsatellite-Stable Metastatic Colorectal Cancer Treated with Immune...

Immune checkpoint inhibitors (ICI) have limited efficacy in microsatellite-stable (MSS) metastatic colorectal cancer (mCRC), potentially because of immunosuppressive mechanisms associated with liver metastases. The impact of liver metastases on survival outcomes was evaluated in a retrospective cohort of patients with MSS mCRC treated with ICI-based therapies at Mass General Brigham between January 2015 and December 2022. Patients were stratified by liver metastasis status at ICI initiation. The primary endpoint was progression-free survival (PFS); the secondary endpoint was overall survival (OS). A total of 132 patients were included, of whom 93 (70.5%) had liver metastases at ICI initiation. Most patients in both groups had received ≥2 prior lines of therapy. No significant differences were observed between groups for RAS/BRAF mutation status or tumor mutational burden. Patients without liver metastases demonstrated higher clinical benefit rates (46.2% vs. 16.1%; P = 0.001), longer median PFS (2.5 vs. 2.1 months; HR, 1.68; P = 0.009), and higher 12-month PFS rates (12.8% vs. 1.1%; P = 0.034). The median OS was also prolonged in patients without liver metastases (11.5 vs. 6.2 months; HR, 2.03; P < 0.001). No history of liver metastases was an independent favorable risk factor for PFS and OS in univariable and multivariable analyses. These findings indicate that liver metastases are associated with inferior survival outcomes in patients with MSS mCRC treated with ICI-based therapies, supporting the immunosuppressive role of liver metastases and underscoring the importance of stratifying patients by liver metastasis status to guide patient selection and optimize therapeutic strategies.

The limited efficacy of ICIs in MSS mCRC remains a major challenge. The association between liver metastases and inferior outcomes supports the liver's immunosuppressive role and suggests that liver metastasis status may guide patient selection and treatment optimization.