Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer

Background: First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC. Methods: MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC. Results: Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts. Conclusion: A six miR expression signature was identified that predicted treatment response to fluoropyrimidine containing first line systemic treatment in patients with mCRC when combined with four clinicopathological factors. Independent validation demonstrated added predictive value of this miR-signature for predicting treatment response versus SD. However, added predicted value for separating patients with PD could not be validated. The clinical relevance of the identified miRs for predicting treatment response has to be further explored.