{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9"],"submitter":["Liu J"],"pubmed_abstract":["<b>Background:</b> The spliceosome plays an important role in mRNA alternative splicing and is aberrantly expressed in several tumors. However, the potential roles of spliceosome-related genes in the progression of hepatocellular carcinoma (HCC) remain poorly understood. <b>Materials and Methods:</b> Patient data were acquired from public databases. Expression differences and survival analyses were used to assess the importance of spliceosome-related genes in HCC prognosis. To explore the potential regulatory mechanisms of these genes, a protein-protein interaction network was constructed and screened using univariate and multivariate Cox regression and random forest analyses. This was used to create a five-gene prognostic model. The prognostic value and predictive power of the five-gene signature were assessed using the Kaplan-Meier and time-dependent receiver operating characteristic analyses in the training set. These results were further validated in an independent external set. To facilitate clinical application, a nomogram was prepared to predict the overall survival of HCC patients. The relative expression of five genes was detected using real-time quantitative polymerase chain reaction. <b>Results:</b> The analysis revealed that <i>LSM1-7, SNRPB, SNRPD1-3, SNRPE, SNRPF, SNRPG,</i> and <i>SNRPN</i> could be used as prognostic biomarkers in HCC patients. Moreover, the five-gene risk model could clearly distinguish between the high-and low-risk groups. Furthermore, the risk model was associated with the tumor mutation burden, immune cell infiltration of CD8<sup>+</sup> T cells, natural killer T cells, M2 macrophages, and immune checkpoint inhibitors, which also demonstrated the predictive efficacy of this risk model in HCC immunotherapy. <b>Conclusion:</b> Spliceosome-related genes and the five-gene signature could serve as novel prognostic biomarkers for HCC patients, aiding clinical patient monitoring and follow-up."],"journal":["Frontiers in molecular biosciences"],"pagination":["759792"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8907852"],"repository":["biostudies-literature"],"pubmed_title":["Determining the Prognostic Value of Spliceosome-Related Genes in Hepatocellular Carcinoma Patients."],"pmcid":["PMC8907852"],"pubmed_authors":["Li W","Liu J","Zhang D","Gu L"],"additional_accession":[]},"is_claimable":false,"name":"Determining the Prognostic Value of Spliceosome-Related Genes in Hepatocellular Carcinoma Patients.","description":"<b>Background:</b> The spliceosome plays an important role in mRNA alternative splicing and is aberrantly expressed in several tumors. However, the potential roles of spliceosome-related genes in the progression of hepatocellular carcinoma (HCC) remain poorly understood. <b>Materials and Methods:</b> Patient data were acquired from public databases. Expression differences and survival analyses were used to assess the importance of spliceosome-related genes in HCC prognosis. To explore the potential regulatory mechanisms of these genes, a protein-protein interaction network was constructed and screened using univariate and multivariate Cox regression and random forest analyses. This was used to create a five-gene prognostic model. The prognostic value and predictive power of the five-gene signature were assessed using the Kaplan-Meier and time-dependent receiver operating characteristic analyses in the training set. These results were further validated in an independent external set. To facilitate clinical application, a nomogram was prepared to predict the overall survival of HCC patients. The relative expression of five genes was detected using real-time quantitative polymerase chain reaction. <b>Results:</b> The analysis revealed that <i>LSM1-7, SNRPB, SNRPD1-3, SNRPE, SNRPF, SNRPG,</i> and <i>SNRPN</i> could be used as prognostic biomarkers in HCC patients. Moreover, the five-gene risk model could clearly distinguish between the high-and low-risk groups. Furthermore, the risk model was associated with the tumor mutation burden, immune cell infiltration of CD8<sup>+</sup> T cells, natural killer T cells, M2 macrophages, and immune checkpoint inhibitors, which also demonstrated the predictive efficacy of this risk model in HCC immunotherapy. <b>Conclusion:</b> Spliceosome-related genes and the five-gene signature could serve as novel prognostic biomarkers for HCC patients, aiding clinical patient monitoring and follow-up.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-05-19T03:11:19.739Z","creation":"2025-04-04T07:56:04.865Z"},"accession":"S-EPMC8907852","cross_references":{"pubmed":["35281269"],"doi":["10.3389/fmolb.2022.759792"]}}