Development of a CMS Classifier for Clinical CRC Samples

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, emphasizing the need for improved predictive biomarkers to guide treatment decisions. A classification system based on gene expression profiles, known as CMS, has shown promise in stratifying CRC into distinct subtypes with varying clinical outcomes. However, the lack of a reliable assay to classify formalin-fixed paraffin-embedded (FFPE) samples poses a challenge for translating this system into routine clinical practice. In this paper, we introduce the NanoClassifier, an NanoString-based CMS classifier to classify both FFPE and Fresh frozen (FF) tumors. We demonstrate the strong accuracy of the NanoClassifier in predicting CMS for CRC samples. By validating its performance on FF and FFPE samples, we highlight the prognostic significance of CMS in CRC. ### Competing Interest Statement The authors have declared no competing interest.