Project description:Colorectal cancer (CRC) is a significant contributor to global cancer-related mortality, emphasizing the critical need for advanced predictive biomarkers to guide treatment decisions. In our pursuit of identifying novel biomarkers, as part of an international consortium, we have previously categorized CRCs into four transcriptome-based consensus molecular subtypes (CMS1-4). These subtypes show promise for predicting outcomes and facilitating biological investigations. To streamline the integration of CMS classification into clinical practice, where routinely formalin-fixed paraffin-embedded (FFPE) samples are used, we developed NanoCMSer. This NanoString-based CMS classifier reliably stratifies both fresh-frozen (FF) and FFPE samples using a concise panel of just 55 genes. Employing domain adaptation methods during training enhanced the generalizability of the classifier, resulting in high accuracy for both FF and FFPE samples. For FF NanoString-based datasets, an accuracy of 95% and for FFPE NanoString-based datasets an accuracy of 92% was achieved, which is the highest reported for FFPE tissues. Furthermore, using the NanoCMSer, a 96% accuracy across a comprehensive collection of 1,976 RNAseq-based samples from 23 datasets aggregated in this study was determined. Additionally, our findings highlight that even with a limited number of genes, the biological relevance of predictions at the individual sample level can be still identified, with distinct CMS biology readily recognizable upon conducting enrichment analysis. Furthermore, our observations revealed a substantial difference in 5-year recurrence free survival (RFS) for CMS2 and CMS3 patients in stage III compared to II (CMS2 21% more recurrences, CMS3 31% more recurrences), while this difference is less pronounced for CMS1 and CMS4 with 11% and 9%, respectively. We posit NanoCMSer as a robust tool with potential applications to assess the CMS status of CRCs in both tumor biology and clinical practice, accessible through the NanoCMSer R package.

Project description:The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, in the clinical practice only patients with MSI tumors have experienced a change in the management of their disease. Proteomics has experimented significant technical advances with the implementation of data-independent acquisition (DIA) as the gold-standard for the analysis of large cohort of patients, providing a dynamic framework of the disease and direct information about the effectors of the biological processes. The aim of this study is the characterization of the proteome of colon cancer CMS by DIA–based proteomics and expand the utility of CMS in the clinical practice. CMS were assigned and differences in the protein profiles between CMS were defined and evaluated using a Systems Biology approach. One hundred fifty-eight paraffin samples from colon cancer patients with stage II-III disease treated with adjuvant chemotherapy were analyzed. After applying quality criteria, 1,940 identified and quantified proteins were used for the analyses. CMS1 had an overexpression of proteins related to immune system, specifically neutrophils, phagocytosis and antimicrobial response, and a glycolytic profile. CMS3 had an overexpression of proteins related to metabolic pathways, while CMS2 showed an intermediate protein profile between CMS1-3, but with a characteristic profile regarding translation, adhesion, and mitochondria and metabolism biological processes. Two proteomics subtypes within CMS2 with different protein characteristics and prognosis were identified. CMS4 was the most different group with an overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. In conclusion, DIA LC-MS/MS proteomics characterization of CRC CMS established new features for each CMS, such as a higher mitochondrial activity in CMS2 or an overexpression of proteins related to phagocytosis in CMS1, but also confirmed previous findings established using transcriptomics such as an overexpression of proteins related to angiogenesis in CMS4. In this CMS4 subtype, several adhesion-related proteins suggested a high metastatic profile and a possible chemoresistance that may explain the worse prognosis of this subtype. CMS1 was characterized as immune and glycolitic-active subtype, being the combination of immunotherapy and glycolytic inhibitors a possible therapeutic strategy. Additionally, two different CMS2 proteomics-based subtypes with different prognosis and possible therapeutic targets were identified. These proccesses could be used as therapeutic targets in the future.

Dataset Information

NanoCMSer: A Clinically Applicable Tool for Stratification of Colorectal Cancer Samples [March2024.CODE]

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