A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma
Background: Hepatocellular carcinoma (HCC) is one of the most common aggressive malignancies with increasing incidence worldwide. The oncogenic roles of transcription factors (TFs) were increasingly recognized in various cancers. This study aimed to develop a predicting signature based on TFs for th...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1068837/full |
| _version_ | 1797943566932115456 |
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| author | Yanbing Yang Xuenian Ye Haibin Zhang Zhaowang Lin Min Fang Jian Wang Yuyan Yu Xuwen Hua Hongxuan Huang Weifeng Xu Ling Liu Zhan Lin |
| author_facet | Yanbing Yang Xuenian Ye Haibin Zhang Zhaowang Lin Min Fang Jian Wang Yuyan Yu Xuwen Hua Hongxuan Huang Weifeng Xu Ling Liu Zhan Lin |
| author_sort | Yanbing Yang |
| collection | DOAJ |
| description | Background: Hepatocellular carcinoma (HCC) is one of the most common aggressive malignancies with increasing incidence worldwide. The oncogenic roles of transcription factors (TFs) were increasingly recognized in various cancers. This study aimed to develop a predicting signature based on TFs for the prognosis and treatment of HCC.Methods: Differentially expressed TFs were screened from data in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Univariate and multivariate Cox regression analyses were applied to establish a TF-based prognostic signature. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the signature. Subsequently, correlations of the risk model with clinical features and treatment response in HCC were also analyzed. The TF target genes underwent Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, followed by protein-protein-interaction (PPI) analysis.Results: A total of 25 differentially expressed TFs were screened, 16 of which were related to the prognosis of HCC in the TCGA-LIHC cohort. A 2-TF risk signature, comprising high mobility group AT-hook protein 1 (HMGA1) and MAF BZIP transcription factor G (MAFG), was constructed and validated to negatively related to the overall survival (OS) of HCC. The ROC curve showed good predictive efficiencies of the risk score regarding 1-year, 2-year and 3-year OS (mostly AUC >0.60). Additionally, the risk score independently predicted OS for HCC patients both in the training cohort of TCGA-LIHC dataset (HR = 2.498, p = 0.007) and in the testing cohort of ICGC-LIRI-JP dataset (HR = 5.411, p < 0.001). The risk score was also positively correlated to progressive characteristics regarding tumor grade, TNM stage and tumor invasion. Patients with a high-risk score were more resistant to transarterial chemoembolization (TACE) treatment and agents of lapatinib and erlotinib, but sensitive to chemotherapeutics. Further enrichment and PPI analyses demonstrated that the 2-TF signature distinguished tumors into 2 clusters with proliferative and metabolic features, with the hub genes belonging to the former cluster.Conclusion: Our study identified a 2-TF prognostic signature that indicated tumor heterogeneity with different clinical features and treatment preference, which help optimal therapeutic strategy and improved survival for HCC patients. |
| first_indexed | 2024-04-10T20:25:07Z |
| format | Article |
| id | doaj.art-422fbb28889d49398032b7e661424a13 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-10T20:25:07Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Genetics |
| spelling | doaj.art-422fbb28889d49398032b7e661424a132023-01-25T11:29:54ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-01-011310.3389/fgene.2022.10688371068837A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinomaYanbing Yang0Xuenian Ye1Haibin Zhang2Zhaowang Lin3Min Fang4Jian Wang5Yuyan Yu6Xuwen Hua7Hongxuan Huang8Weifeng Xu9Ling Liu10Zhan Lin11Department of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Orthopedics, Dongguan People’s Hospital, Dongguan, ChinaDepartment of Orthopedics, Dongguan People’s Hospital, Dongguan, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Orthopedics, Dongguan People’s Hospital, Dongguan, ChinaDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Radiology, The First Affiliated Hospital of Dali University, Dali, ChinaDepartment of Radiology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, ChinaBackground: Hepatocellular carcinoma (HCC) is one of the most common aggressive malignancies with increasing incidence worldwide. The oncogenic roles of transcription factors (TFs) were increasingly recognized in various cancers. This study aimed to develop a predicting signature based on TFs for the prognosis and treatment of HCC.Methods: Differentially expressed TFs were screened from data in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Univariate and multivariate Cox regression analyses were applied to establish a TF-based prognostic signature. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the signature. Subsequently, correlations of the risk model with clinical features and treatment response in HCC were also analyzed. The TF target genes underwent Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, followed by protein-protein-interaction (PPI) analysis.Results: A total of 25 differentially expressed TFs were screened, 16 of which were related to the prognosis of HCC in the TCGA-LIHC cohort. A 2-TF risk signature, comprising high mobility group AT-hook protein 1 (HMGA1) and MAF BZIP transcription factor G (MAFG), was constructed and validated to negatively related to the overall survival (OS) of HCC. The ROC curve showed good predictive efficiencies of the risk score regarding 1-year, 2-year and 3-year OS (mostly AUC >0.60). Additionally, the risk score independently predicted OS for HCC patients both in the training cohort of TCGA-LIHC dataset (HR = 2.498, p = 0.007) and in the testing cohort of ICGC-LIRI-JP dataset (HR = 5.411, p < 0.001). The risk score was also positively correlated to progressive characteristics regarding tumor grade, TNM stage and tumor invasion. Patients with a high-risk score were more resistant to transarterial chemoembolization (TACE) treatment and agents of lapatinib and erlotinib, but sensitive to chemotherapeutics. Further enrichment and PPI analyses demonstrated that the 2-TF signature distinguished tumors into 2 clusters with proliferative and metabolic features, with the hub genes belonging to the former cluster.Conclusion: Our study identified a 2-TF prognostic signature that indicated tumor heterogeneity with different clinical features and treatment preference, which help optimal therapeutic strategy and improved survival for HCC patients.https://www.frontiersin.org/articles/10.3389/fgene.2022.1068837/fulltranscription factorhigh mobility group AT-hook protein 1MAF BZIP transcription factor Gprognosistherapeutic responsehepatocellular carcinoma |
| spellingShingle | Yanbing Yang Xuenian Ye Haibin Zhang Zhaowang Lin Min Fang Jian Wang Yuyan Yu Xuwen Hua Hongxuan Huang Weifeng Xu Ling Liu Zhan Lin A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma Frontiers in Genetics transcription factor high mobility group AT-hook protein 1 MAF BZIP transcription factor G prognosis therapeutic response hepatocellular carcinoma |
| title | A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| title_full | A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| title_fullStr | A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| title_full_unstemmed | A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| title_short | A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| title_sort | novel transcription factor based signature to predict prognosis and therapeutic response of hepatocellular carcinoma |
| topic | transcription factor high mobility group AT-hook protein 1 MAF BZIP transcription factor G prognosis therapeutic response hepatocellular carcinoma |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1068837/full |
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