MicroRNA Signature Predicts Risk of Recurrence After Surgery for Stage II Colon Cancer
In a study reported in The Lancet Oncology, Jia-Xing Zhang, MD, of Sun Yat-sen University, and colleagues identified a six-microRNA (miRNA) signature that predicted risk of recurrence after surgery for stage II colon cancer and that may help to identify patients most likely to benefit from adjuvant chemotherapy.
Study Details
In the study, 35 miRNAs were initially found to exhibit differential expression in 40 paired stage II colon cancer tumors and adjacent normal tissue samples. Differential expression of these miRNAs was confirmed in paraffin-embedded specimens from an additional 138 patients using real-time reverse transcription polymerase chain reaction.
A six-miRNA–based classifier was constructed using a LASSO Cox regression model based on the association between the expression of each miRNA and the duration of individual patient disease-free survival after surgery. The six miRNAs in the classifier were (for low vs high risk) miR-21-5p (low vs high expression), miR-20a-5p (low vs high expression), miR-103a-3p (low vs high expression), miR-106b-5p (low vs high expression), miR-143-5p (high vs low expression), and miR-215 (high vs low expression).
The classifier was analyzed in the initial training set of 138 patients and validated in an internal testing set of 137 patients and an independent validation set of 460 patients.
Disease-Free Survival According to Classifier-Based Risk
Five-year disease-free survival for low-risk vs high-risk patients using the six-miRNA classifier was 89% vs 60% (hazard ratio [HR] = 4.24, P < .0001) in the initial training set of patients, 85% vs 57% (HR = 3.63, P < .0001) in the internal testing set, and 85% vs 54% (HR = 3.70, P < .0001) in the independent validation set, in the latter of which 45% of patients were classified as high risk and 55% as low risk.
In multivariate analysis adjusting for clinicopathologic variables and mismatch repair status, the six-miRNA classifier remained a significant independent predictor in the total cohort of 735 cases (HR = 3.79, P < .0001). The classifier showed significantly higher prognostic accuracy than any clinicopathologic risk factor (P < .0001 vs individual factors, P = .042 for combined risk factors), mismatch repair status (P < .0001), or single miRNAs alone (P < .0001 vs each).
Benefit of Adjuvant Chemotherapy
Adjuvant chemotherapy was not associated with improved disease-free survival in the entire cohort of 735 patients (HR = 1.26, P = .13) or in patients with any poor prognostic features (HR = 1.30, P = .12). In an ad hoc exploratory analysis, significant disease-free survival benefit with adjuvant chemotherapy was observed among patients at high risk based on the six miRNA classifier (HR = 1.69, P = .0054) and among patients with both classifier-defined high risk and any poor clinical prognostic feature (HR = 1.94, P = .0015).
On the basis of these findings, the investigators have developed two nomograms for clinical use (untreated and treated with adjuvant chemotherapy) that integrate the six miRNA classifier and four clinicopathologic risk factors to predict which patients might benefit from adjuvant chemotherapy.
The investigators concluded, “Our six-miRNA–based classifier is a reliable prognostic and predictive tool for disease recurrence in patients with stage II colon cancer, and might be able to predict which patients benefit from adjuvant chemotherapy. It might facilitate patient counselling and individualise management of patients with this disease.”
The study was funded by the Natural Science Foundation of China.
Jun-Hang Luo, MD, of Sun Yat-sen University, is the corresponding author for The Lancet Oncology article.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
