Comprehensive characterisation of adipogenesis-related genes in colorectal cancer for clinical significance and immunogenomic landscape analyses

Abstract

Abstract Objective: Colorectal cancer (CRC) is a significant global health concern, necessitating the identification of biomarkers and molecular subtypes to enhance clinical management. This study aims to evaluate the clinical significance of adipogenesis-related genes (ARGs) and molecular subtypes in CRC. Methods: A comprehensive analysis of ARGs in CRC was conducted using publicly available datasets from accessible databases and bioinformatics tools. Unsupervised clustering analysis determined CRC molecular subtypes, while LASSO regression produced a prognostic model for risk assessment. The immunogenomic patterns and immunotherapy analysis were used for predicting patient response to immunotherapy. Additionally, qPCR analysis validated the identified pivotal gene expressions. Results: Analysis of RNAseq data obtained from normal and tumour tissues revealed 50 differentially expressed biomarker genes. Unsupervised clustering identified two subtypes (Clusters A and B) with distinct survival outcomes. Clusters A and B displayed differing immune cell compositions and enriched biological pathways, suggesting potential therapeutic targets. A risk score model, employing five ARGs, effectively stratified patients into high and low-risk categories, demonstrating significant differences in survival outcomes. The model was validated and demonstrated robust predictive performance. High-risk patients exhibited altered immune cell proportions and gene expressions compared to low-risk patients. Furthermore, qPCR experiments confirmed the bioinformatics analysis findings. Conclusion: This study provides valuable insights into the clinical relevance of ARGs and molecular subtypes in CRC, facilitating improved precision medicine and personalised treatment modalities.