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Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma

BACKGROUND: An important stage in controlling gene expression is RNA alternative splicing (AS), and aberrant AS can trigger the development and spread of malignancies, including hepatocellular carcinoma (HCC). A crucial component of AS is cleavage and polyadenylation-specific factor 4 (CPSF4), a com...

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Autores principales: Yuemaierabola, Anwaier, Guo, Jun, Sun, Lili, Yeerkenbieke, Buerlan, Liu, Fuzhong, Ye, Dilinaer, Zhai, Xiaoyi, Guo, Wenjia, Cao, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590311/
https://www.ncbi.nlm.nih.gov/pubmed/37542549
http://dx.doi.org/10.1007/s00432-023-05178-z
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author Yuemaierabola, Anwaier
Guo, Jun
Sun, Lili
Yeerkenbieke, Buerlan
Liu, Fuzhong
Ye, Dilinaer
Zhai, Xiaoyi
Guo, Wenjia
Cao, Yan
author_facet Yuemaierabola, Anwaier
Guo, Jun
Sun, Lili
Yeerkenbieke, Buerlan
Liu, Fuzhong
Ye, Dilinaer
Zhai, Xiaoyi
Guo, Wenjia
Cao, Yan
author_sort Yuemaierabola, Anwaier
collection PubMed
description BACKGROUND: An important stage in controlling gene expression is RNA alternative splicing (AS), and aberrant AS can trigger the development and spread of malignancies, including hepatocellular carcinoma (HCC). A crucial component of AS is cleavage and polyadenylation-specific factor 4 (CPSF4), a component of the CPSF complex, but it is unclear how CPSF4-related AS molecules describe immune cell infiltration in the total tumor microenvironment (TME). METHODS: Using RNA-sequencing data and clinical data from TCGA-LIHC from the Cancer Genome Atlas (TCGA) database, the AS genes with differential expression were found. The univariate Cox analysis, KM analysis, and Spearman analysis were used to identify the AS genes related to prognosis. Screening of key AS genes that are highly correlated with CPSF4. Key genes were screened using Cox regression analysis and stepwise regression analysis, and prognosis prediction models and the topography of TME cell infiltration were thoroughly analyzed. RESULTS: A model consisting of seven AS genes (STMN1, CLSPN, MDK, RNFT2, PRR11, RNF157, GHR) was constructed that was aimed to predict prognostic condition. The outcomes of the HCC samples in the high-risk group were considerably worse than those in the lower risk group (p < 0.0001), and different risk patient groups were formed. According to the calibration curves and the area under the ROC curve (AUC) values for survival at 1, 2, and 3 years, the clinical nomogram performs well in predicting survival in HCC patients. These values were 0.76, 0.70, and 0.69, respectively. Moreover, prognostic signature was markedly related to immune infiltration and immune checkpoint genes expression. CONCLUSION: By shedding light on the function of CPSF4 and the seven AS genes in the formation and progression of HCC, this research analysis contributes to the development of more useful prognostic, diagnostic, and possibly therapeutic biomarkers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05178-z.
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spelling pubmed-105903112023-10-23 Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma Yuemaierabola, Anwaier Guo, Jun Sun, Lili Yeerkenbieke, Buerlan Liu, Fuzhong Ye, Dilinaer Zhai, Xiaoyi Guo, Wenjia Cao, Yan J Cancer Res Clin Oncol Research BACKGROUND: An important stage in controlling gene expression is RNA alternative splicing (AS), and aberrant AS can trigger the development and spread of malignancies, including hepatocellular carcinoma (HCC). A crucial component of AS is cleavage and polyadenylation-specific factor 4 (CPSF4), a component of the CPSF complex, but it is unclear how CPSF4-related AS molecules describe immune cell infiltration in the total tumor microenvironment (TME). METHODS: Using RNA-sequencing data and clinical data from TCGA-LIHC from the Cancer Genome Atlas (TCGA) database, the AS genes with differential expression were found. The univariate Cox analysis, KM analysis, and Spearman analysis were used to identify the AS genes related to prognosis. Screening of key AS genes that are highly correlated with CPSF4. Key genes were screened using Cox regression analysis and stepwise regression analysis, and prognosis prediction models and the topography of TME cell infiltration were thoroughly analyzed. RESULTS: A model consisting of seven AS genes (STMN1, CLSPN, MDK, RNFT2, PRR11, RNF157, GHR) was constructed that was aimed to predict prognostic condition. The outcomes of the HCC samples in the high-risk group were considerably worse than those in the lower risk group (p < 0.0001), and different risk patient groups were formed. According to the calibration curves and the area under the ROC curve (AUC) values for survival at 1, 2, and 3 years, the clinical nomogram performs well in predicting survival in HCC patients. These values were 0.76, 0.70, and 0.69, respectively. Moreover, prognostic signature was markedly related to immune infiltration and immune checkpoint genes expression. CONCLUSION: By shedding light on the function of CPSF4 and the seven AS genes in the formation and progression of HCC, this research analysis contributes to the development of more useful prognostic, diagnostic, and possibly therapeutic biomarkers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05178-z. Springer Berlin Heidelberg 2023-08-05 2023 /pmc/articles/PMC10590311/ /pubmed/37542549 http://dx.doi.org/10.1007/s00432-023-05178-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Yuemaierabola, Anwaier
Guo, Jun
Sun, Lili
Yeerkenbieke, Buerlan
Liu, Fuzhong
Ye, Dilinaer
Zhai, Xiaoyi
Guo, Wenjia
Cao, Yan
Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title_full Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title_fullStr Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title_full_unstemmed Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title_short Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma
title_sort comprehensive analysis of cpsf4-related alternative splice genes in hepatocellular carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590311/
https://www.ncbi.nlm.nih.gov/pubmed/37542549
http://dx.doi.org/10.1007/s00432-023-05178-z
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