Exosome secretion related gene signature predicts chemoresistance in patients with colorectal cancer

Colorectal cancer (CRC) is a highly heterogeneous malignancy, and patients often have different responses to treatment. In this study, the genetic characteristics related to exosome formation and secretion procedure were used to predict chemoresistance and guide the individualized treatment of patients. Firstly, seven microarray datasets in Gene Expression Omnibus (GEO) and RNA-Seq dataset from the Cancer Genome Atlas (TCGA) were used to analysis the transcriptome profiles and associated characteristics of CRC patients. Then, a predictive model based on gene features linked to exosome formation and secretion was created and validated using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine learning. Finally, we evaluated the model using chemoresistant/chemosensitive cells and tissues by immunofluorescence (IF), western blot (WB), quantitative real-time PCR (qRT-PCR) and immunocytochemistry (IHC) experiments, and the predictive value of integrated model in the clinical validation cohort were performed by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves analyses. We established a risk score signature based on three genes related to exosome secretion in CRC. Better Overall Survival (OS) and greater chemosensitivity were seen in the low-risk group, whereas the high-risk group exhibited chemoresistance and a subpar response to immune checkpoint blockade (ICB) therapy. Higher expression of the model genes EXOC2, EXOC3 and STX4 were observed in chemoresistant cells and specimens. The AUC of 5-year disease-free survival (DFS) was 0.804. Compared with that in the low-risk group, patients' DFS was found to be significantly worse in the high-risk group. In summary, the gene signature related to exosome formation and secretion could reliably predict patients' chemosensitivity and ICB treatment response, which providing new independent biomarkers for the treatment of CRC.