A comprehensive study based on exosome-related immunosuppression genes and tumor microenvironment in hepatocellular carcinoma

• Published in: BMC cancer 2022-12, Vol.22 (1), p.1344-1344, Article 1344
• Main Authors: Yang, Zhan, Li, Xinmiao, Pan, Chaoran, Li, Yifei, Lin, Lifan, Jin, Yan, Zheng, Jianjian, Yu, Zhengping
• Format: Article
• Language: English
• Subjects: Carcinoma, Hepatocellular - genetics; Care and treatment; Diagnosis; Exosome; Exosomes - genetics; Genetic aspects; Hepatocellular carcinoma; Hepatoma; Hospitals, University; Humans; Immunosuppression; Immunosuppression Therapy; Immunosuppressive gene; Immunotherapy; Liver Neoplasms - genetics; Metastasis; Patient outcomes; Prevention; Prognosis; Risk factors; Tumor microenvironment; Tumor Microenvironment - genetics
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-022-10463-0

Exosomes play an important role in the tumor microenvironment (TME) and the mechanisms of tumor immune escape in hepatocellular carcinoma (HCC). It is known that immunosuppressive genes, involved in the processes of tumor immunosuppression, are associated with cancer progression. This study aimed to explore the prognostic values of exosome-related immunosuppression genes (ERIGs) in HCC. The RNA-seq transcriptome data of 374 HCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The TCGA cohort was randomly divided into the training cohort and validation cohort in a 1:1 ratio. WGCNA analysis and Pearson correlation analysis were used to identify ERIGs. The Lasso regression method was used to construct a 5-ERIG signature. The prognostic value of our signature was examined in the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort. Univariate Cox regression analysis was used to screen prognostic ERIGs. Subsequently, these prognostic ERIGs were included in Lasso regression analyses to identify 5 key ERIGs (ASAP1, IARS1, GTF3C2, TPD5L2 and SLC52A2) and construct a 5-ERIG signature. The patients in the low-risk group had better prognosis than those in the high-risk group. Univariate and multivariate cox regression revealed that risk score was an independent prognostic risk factor of HCC. Gene set enrichment analysis (GSEA) showed that this signature was highly associated with TME-related pathways. Subsequent analyses revealed the potential role of the signature in regulating the TME in HCC. In addition, a lower immunotherapy score was found in patients with high risk-score. Of note, this signature was confirmed to have a good performance in predicting HCC prognosis in the FAHWMU cohort. Moreover, knockdown of 5 ERIGs of this signature contributed to the suppression the Hep3B cell proliferation. We generated a novel prognostic 5-ERIG signature to accurately predict the prognosis of patients with HCC, and this signature may serve as an indicator of immunotherapy for HCC.