MicroRNAs Expression Patterns Predict Tumor Mutational Burden in Colorectal Cancer

Area of Science:

• Oncology
• Genomics
• Immunology

Background:

• Tumor mutational burden (TMB) is a potential biomarker for predicting response to immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC).
• MicroRNAs (miRNAs) play a role in regulating anti-tumor immune responses.
• Identifying predictive biomarkers for TMB is crucial for optimizing CRC treatment strategies.

Purpose of the Study:

• To determine miRNA expression patterns in CRC patients.
• To develop and validate a miRNA-based signature for predicting TMB in CRC.
• To assess the performance of the miRNA signature compared to microsatellite instability (MSI).

Main Methods:

• Tumor mutational burden (TMB) was measured using next-generation sequencing (NGS) on formalin-fixed paraffin-embedded samples.
• MicroRNA expression data from The Cancer Genome Atlas (TCGA) was analyzed to identify differentially expressed miRNAs between high and low TMB groups.
• A miRNA signature was constructed using the least absolute shrinkage and selection operator (LASSO) method and validated in independent cohorts using RT-PCR.

Main Results:

• A four-miRNA signature was identified as a robust predictor of TMB in CRC patients.
• The signature demonstrated high accuracy in predicting TMB: 0.963 (training set), 0.902 (test set), and 0.946 (total set).
• The miRNA signature outperformed microsatellite instability (MSI) in predicting TMB within the TCGA dataset, although MSI showed a stronger correlation in the validation cohort.

Conclusions:

• This study presents the first miRNA-based signature classifier validated with high-quality clinical data for accurate TMB prediction in CRC.
• The developed miRNA signature offers a promising tool for predicting TMB and potentially guiding ICI therapy selection in colorectal cancer.
• Further validation in larger, diverse patient cohorts is warranted to confirm the clinical utility of this miRNA signature.