Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma
The prognosis of colon adenocarcinoma (COAD) remains poor. However, the specific and sensitive biomarkers for diagnosis and prognosis of COAD are absent. Transcription factors (TFs) are involved in many biological processes in cells. As the molecule of the signal pathway of the terminal effectors, T...
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| Format: | Article |
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Frontiers Media S.A.
2021-09-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.709133/full |
| _version_ | 1818643567237660672 |
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| author | Jianwei Lin Zichao Cao Dingye Yu Wei Cai |
| author_facet | Jianwei Lin Zichao Cao Dingye Yu Wei Cai |
| author_sort | Jianwei Lin |
| collection | DOAJ |
| description | The prognosis of colon adenocarcinoma (COAD) remains poor. However, the specific and sensitive biomarkers for diagnosis and prognosis of COAD are absent. Transcription factors (TFs) are involved in many biological processes in cells. As the molecule of the signal pathway of the terminal effectors, TFs play important roles in tumorigenesis and development. A growing body of research suggests that aberrant TFs contribute to the development of COAD, as well as to its clinicopathological features and prognosis. In consequence, a few studies have investigated the relationship between the TF-related risk model and the prognosis of COAD. Therefore, in this article, we hope to develop a prognostic risk model based on TFs to predict the prognosis of patients with COAD. The mRNA transcription data and corresponding clinical data were downloaded from TCGA and GEO. Then, 141 differentially expressed genes, validated by the GEPIA2 database, were identified by differential expression analysis between normal and tumor samples. Univariate, multivariate and Lasso Cox regression analysis were performed to identify seven prognostic genes (E2F3, ETS2, HLF, HSF4, KLF4, MEIS2, and TCF7L1). The Kaplan–Meier curve and the receiver operating characteristic curve (ROC, 1-year AUC: 0.723, 3-year AUC: 0.775, 5-year AUC: 0.786) showed that our model could be used to predict the prognosis of patients with COAD. Multivariate Cox analysis also reported that the risk model is an independent prognostic factor of COAD. The external cohort (GSE17536 and GSE39582) was used to validate our risk model, which indicated that our risk model may be a reliable predictive model for COAD patients. Finally, based on the model and the clinicopathological factors, we constructed a nomogram with a C-index of 0.802. In conclusion, we emphasize the clinical significance of TFs in COAD and construct a prognostic model of TFs, which could provide a novel and reliable model for the prognosis of COAD. |
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| language | English |
| last_indexed | 2024-12-17T00:01:00Z |
| publishDate | 2021-09-01 |
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| spelling | doaj.art-b919e747647b48fe832e50277a34f3442022-12-21T22:11:05ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-09-011210.3389/fgene.2021.709133709133Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon AdenocarcinomaJianwei LinZichao CaoDingye YuWei CaiThe prognosis of colon adenocarcinoma (COAD) remains poor. However, the specific and sensitive biomarkers for diagnosis and prognosis of COAD are absent. Transcription factors (TFs) are involved in many biological processes in cells. As the molecule of the signal pathway of the terminal effectors, TFs play important roles in tumorigenesis and development. A growing body of research suggests that aberrant TFs contribute to the development of COAD, as well as to its clinicopathological features and prognosis. In consequence, a few studies have investigated the relationship between the TF-related risk model and the prognosis of COAD. Therefore, in this article, we hope to develop a prognostic risk model based on TFs to predict the prognosis of patients with COAD. The mRNA transcription data and corresponding clinical data were downloaded from TCGA and GEO. Then, 141 differentially expressed genes, validated by the GEPIA2 database, were identified by differential expression analysis between normal and tumor samples. Univariate, multivariate and Lasso Cox regression analysis were performed to identify seven prognostic genes (E2F3, ETS2, HLF, HSF4, KLF4, MEIS2, and TCF7L1). The Kaplan–Meier curve and the receiver operating characteristic curve (ROC, 1-year AUC: 0.723, 3-year AUC: 0.775, 5-year AUC: 0.786) showed that our model could be used to predict the prognosis of patients with COAD. Multivariate Cox analysis also reported that the risk model is an independent prognostic factor of COAD. The external cohort (GSE17536 and GSE39582) was used to validate our risk model, which indicated that our risk model may be a reliable predictive model for COAD patients. Finally, based on the model and the clinicopathological factors, we constructed a nomogram with a C-index of 0.802. In conclusion, we emphasize the clinical significance of TFs in COAD and construct a prognostic model of TFs, which could provide a novel and reliable model for the prognosis of COAD.https://www.frontiersin.org/articles/10.3389/fgene.2021.709133/fulltranscription factorscolon adenocarcinomarisk scorebioinformaticsnomogram |
| spellingShingle | Jianwei Lin Zichao Cao Dingye Yu Wei Cai Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma Frontiers in Genetics transcription factors colon adenocarcinoma risk score bioinformatics nomogram |
| title | Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma |
| title_full | Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma |
| title_fullStr | Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma |
| title_full_unstemmed | Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma |
| title_short | Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma |
| title_sort | identification of transcription factor related gene signature and risk score model for colon adenocarcinoma |
| topic | transcription factors colon adenocarcinoma risk score bioinformatics nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.709133/full |
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