Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence
Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed...
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| Format: | Article |
| Language: | English |
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BMC
2021-04-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-021-08173-0 |
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| author | Ping Yan Zuotian Huang Tong Mou Yunhai Luo Yanyao Liu Baoyong Zhou Zhenrui Cao Zhongjun Wu |
| author_facet | Ping Yan Zuotian Huang Tong Mou Yunhai Luo Yanyao Liu Baoyong Zhou Zhenrui Cao Zhongjun Wu |
| author_sort | Ping Yan |
| collection | DOAJ |
| description | Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies. |
| first_indexed | 2024-12-19T02:14:07Z |
| format | Article |
| id | doaj.art-915def800e90490ab41535dc12b59b57 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-12-19T02:14:07Z |
| publishDate | 2021-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-915def800e90490ab41535dc12b59b572022-12-21T20:40:30ZengBMCBMC Cancer1471-24072021-04-0121112110.1186/s12885-021-08173-0Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrencePing Yan0Zuotian Huang1Tong Mou2Yunhai Luo3Yanyao Liu4Baoyong Zhou5Zhenrui Cao6Zhongjun Wu7Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical UniversityAbstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.https://doi.org/10.1186/s12885-021-08173-0Hepatocellular carcinomaRecurrenceCompeting endogenous RNAPrognosisBiomarker |
| spellingShingle | Ping Yan Zuotian Huang Tong Mou Yunhai Luo Yanyao Liu Baoyong Zhou Zhenrui Cao Zhongjun Wu Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence BMC Cancer Hepatocellular carcinoma Recurrence Competing endogenous RNA Prognosis Biomarker |
| title | Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| title_full | Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| title_fullStr | Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| title_full_unstemmed | Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| title_short | Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| title_sort | comprehensive analyses of competing endogenous rna networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence |
| topic | Hepatocellular carcinoma Recurrence Competing endogenous RNA Prognosis Biomarker |
| url | https://doi.org/10.1186/s12885-021-08173-0 |
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