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A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients

The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle‐related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prog...

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Detalles Bibliográficos
Autores principales: Shen, Xiaoyong, Su, Zheng, Dou, Yan, Song, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439494/
https://www.ncbi.nlm.nih.gov/pubmed/37431829
http://dx.doi.org/10.1049/syb2.12069
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author Shen, Xiaoyong
Su, Zheng
Dou, Yan
Song, Xin
author_facet Shen, Xiaoyong
Su, Zheng
Dou, Yan
Song, Xin
author_sort Shen, Xiaoyong
collection PubMed
description The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle‐related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F‐associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA‐COAD (n = 521), GSE17536 (n = 177) and GSE39582 (n = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F‐related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F‐based classification and ‘protein secretion’ issues of multiorgans and tumour infiltration of ‘T‐cell regulatory (Tregs)’ and ‘CD56dim natural killer cell’ were detected. The authors’ findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.
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spelling pubmed-104394942023-08-20 A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients Shen, Xiaoyong Su, Zheng Dou, Yan Song, Xin IET Syst Biol Original Research The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle‐related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F‐associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA‐COAD (n = 521), GSE17536 (n = 177) and GSE39582 (n = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F‐related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F‐based classification and ‘protein secretion’ issues of multiorgans and tumour infiltration of ‘T‐cell regulatory (Tregs)’ and ‘CD56dim natural killer cell’ were detected. The authors’ findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer. John Wiley and Sons Inc. 2023-07-11 /pmc/articles/PMC10439494/ /pubmed/37431829 http://dx.doi.org/10.1049/syb2.12069 Text en © 2023 The Authors. IET Systems Biology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Research
Shen, Xiaoyong
Su, Zheng
Dou, Yan
Song, Xin
A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title_full A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title_fullStr A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title_full_unstemmed A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title_short A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients
title_sort novel investigation into an e2f transcription factor‐related prognostic model with seven signatures for colon cancer patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439494/
https://www.ncbi.nlm.nih.gov/pubmed/37431829
http://dx.doi.org/10.1049/syb2.12069
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