A specific microRNA profile as predictive biomarker for systemic treatment in patients with metastatic colorectal cancer

Abstract

Background: Palliative systemic therapy is currently standard of care for patients with extensive metastatic colorectal cancer (mCRC). A biomarker predicting chemotherapy benefit which prevents toxicity from ineffective treatment is urgently needed. Therefore, a previously developed tissue-derived microRNA profile to predict clinical benefit from chemotherapy was evaluated in tissue biopsies and serum from patients with mCRC. Methods: Samples were prospectively collected from patients (N = 132) who were treated with capecitabine or 5-FU/LV with oxaliplatin ± bevacizumab. Response evaluation was performed according to RECIST 1.1 after three or four cycles, respectively. Baseline tissue and serum miRNAs expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p, and miR-98-5p were quantified with RT-qPCR and droplet digital PCR, respectively. Combined predictive performance of selected variables was tested using logistic regression analysis. Results: From 132 patients, 81 fresh frozen tissue biopsies from metastases and 93 serum samples were available. Based on expression levels of miRNAs in tissue, progressive disease could be predicted with an AUC of 0.85 (95% CI:0.72-0.91) and response could be predicted with an AUC of 0.70 (95% CI:0.56-0.80). This did not outperform clinical parameters alone (respectively P =.14 and P =.27). Expression levels of miR-92a-3p and miR-98-5p in serum significantly improved the predictive value of clinical parameters for response to chemotherapy (AUC 0.74, 95% CI:0.64-0.84, P =.003) in this cohort. Conclusions: The additive predictive value to clinical parameters of the tissue-derived six miRNA profile for clinical benefit could not be validated in patients with mCRC treated with first-line systemic therapy. Although miR-92a-3p and miR-98-5p serum levels improved the predictive value of clinical parameters, it remained insufficient for clinical decision-making.