Overexpression of TCERG1 as a prognostic marker in hepatocellular carcinoma: A TCGA data-based analysis

Abstract

Objective: Transcription elongation factor 1 (TCERG1) is a nuclear protein consisted of multiple protein structural domains that plays an important role in regulating the transcription, extension, and splicing regulation of RNA polymerase II. However, the prognostic and immunological role of TCERG1 in human cancer remains unknown. In this study, we analyzed the expression of TCERG1 gene in hepatocellular carcinoma (HCC) patients, its clinical significance, and its possible prognostic value by bioinformatics.Methods: RNA sequencing data and clinicopathological characteristics of patients with HCC were collected from TCGA and CCLE databases. The Wilcoxon rank-sum test was used to analyze the expression of TCERG1 in HCC tissues and normal tissues. The protein levels of TCERG1 between normal and liver cancer tissues were analyzed by the Human Protein Atlas Database (HPA) (www.proteinatlas.org). Validation was performed using the Gene Expression Omnibus (GEO) dataset of 167 samples. The expression of TCERG1 in HCC cells were verified by qRT-PCR, and CCK-8, scratch assay and Transwell assay were performed to detect cell proliferation, migration and invasion ability. According to the median value of TCERG1 expression, patients were divided into high and low subgroups. Logistic regression, GSEA enrichment, TME, and single-sample set gene enrichment analysis (ssGSEA) were performed to explore the effects of TCERG1 on liver cancer biological function and immune infiltrates. TCERG1 co-expression networks were studied through the CCLE database and the LinkedOmics database to analyze genes that interact with TCERG1.Results: The expression levels of TCERG1 in HCC patient tissues were significantly higher than in normal tissues. Survival analysis showed that high levels of TCERG1 expression were significantly associated with low survival rates in HCC patients. Multifactorial analysis showed that high TCERG1 expression was an independent risk factor affecting tumor prognosis. This result was also verified in the GEO database. Cellular experiments demonstrated that cell proliferation, migration and invasion were inhibited after silencing of TCERG1 gene expression. Co-expression analysis revealed that CPSF6 and MAML1 expression were positively correlated with TCERG1. GSEA showed that in samples with high TCERG1 expression, relevant signaling pathways associated with cell cycle, apoptosis, pathways in cancer and enriched in known tumors included Wnt signaling pathway, Vegf signaling pathway, Notch signaling pathway, MAPK signaling pathway and MTOR pathways. The expression of TCERG1 was positively correlated with tumor immune infiltrating cells (T helper two cells, T helper cells).Conclusion:TCERG1 gene is highly expressed in hepatocellular carcinoma tissues, which is associated with the poor prognosis of liver cancer, and may be one of the markers for the diagnosis and screening of liver cancer and the prediction of prognosis effect. At the same time, TCERG1 may also become a new target for tumor immunotherapy.

Identification of oncogenes and tumor-suppressor genes with hepatocellular carcinoma: A comprehensive analysis based on TCGA and GEO datasets

“…There is an urgent need to find new targets for the diagnosis and treatment of liver cancer in the direction of a breakthrough in the current treatment limitations. Some previous studies used TCGA and GEO databases to screen oncogenes and identify prognostic or immune-related genes ( Chen et al, 2020 ; Gao et al, 2021 ; Yan et al, 2021 ; Shen et al, 2022a ; Shen et al, 2022b ; Ding et al, 2022 ; Gao et al, 2022 ; Long et al, 2022 ; Yang et al, 2022 ). However, in this study, four GSE datasets, GSE36376, GSE102079, GSE54236, and GSE45267, were summarized for analysis, hoping to find the mechanism of cancer-promoting and tumor-suppressor factors in liver cancer from the perspective of improving the accuracy of the research results.…”

“…Currently, public data and bioinformatic analysis methods have provided us with invaluable resources to find HCC-related oncogenes and tumor-suppressor genes. Some studies searched cancer-related target genes through public databases, whether prognostic oncogene identification ( Gao et al, 2021 ; Yan et al, 2021 ; Shen et al, 2022a ; Gao et al, 2022 ), single-gene research studies ( Ding et al, 2022 ; Yang et al, 2022 ), or immune-related oncogenes ( Chen et al, 2020 ; Shen et al, 2022b ; Long et al, 2022 ), all of which provided a strong basis for targeted therapy and precise treatment of liver cancer. However, many studies only consider the differential expression of oncogenes in tumors, ignoring the important role and potential association of tumor-suppressor genes.…”

AP4M1 as a prognostic biomarker associated with cell proliferation, migration and immune regulation in hepatocellular carcinoma

“…According to statistics, there are more than 900,000 new diagnoses and more than 800,000 deaths each year [ 4 ]. In the past decade, even though great progress has been made in the treatment and diagnosis of hepatocellular carcinoma, the overall survival rate of patients is still low [ 5 ]. Since the majority of patients with HCC were diagnosed in the advanced stages, or with invasion and metastasis within and outside the liver, the optimal time for surgical treatment was lost [ 6 , 7 ].…”