Development of an exosome-related and immune microenvironment prognostic signature in colon adenocarcinoma - Cui, Guoliang; Wang, Can; Liu, Jinhui; Shon, Kinyu; Gu, Renjun; Chang, Cheng; Ren, Lang; Wei, Fei; Sun, Zhiguang (Frontiers in Genetics, 2022)
Background: The correlation between exosomes and the tumor immune microenvironment has been proved to affect tumorigenesis and progression of colon adenocarcinoma (COAD). However, it remained unclear whether exosomes had an impact on the prognostic indications of COAD patients. Methods: Expression of exosome-related genes (ERGs) and clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The ERGs associated with prognosis were identified and exosome-related prognostic signature was constructed. Patients in two risk groups were classified according to the risk score calculation formula: Risk score = 1.0132 * CCKBR + 0.2416 * HOXC6 + 0.7618 * POU4F1. The expression of three ERGs was investigated by qRT-PCR. After that, we developed a nomogram predicting the likelihood of survival and verified its predictive efficiency. The differences of tumor immune microenvironment, immune cell infiltration, immune checkpoint and sensitivity to drugs in two risk groups were analyzed. Results: A prognostic signature was established based on the three ERGs (CCKBR, HOXC6, and POU4F1) and patients with different risk group were distinguished. Survival analysis revealed the negative associated of risk score and prognosis, ROC curve analyses showed the accuracy of this signature. Three ERGs expression was investigated by qRT-PCR in three colorectal cancer cell lines. Moreover, risk score was positively correlated with tumor mutational burden (TMB), immune activities, microsatellite instability level, the expression of immune checkpoint genes. Meanwhile, the expression level of three ERGs and the risk score were markedly related with the sensitive response to chemotherapy. Conclusion: The novel signature composed of three ERGs with precise predictive capabilities can be used to predict prognosis and provide a promising therapeutic target for improving the efficacy of immunotherapy.