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Wang Y, Zhang L, Chen H, Yang J, Cui Y, Wang H. Coronary artery disease-associated immune gene RBP1 and its pan-cancer analysis. Front Cardiovasc Med 2023; 10:1091950. [PMID: 36970364 PMCID: PMC10034062 DOI: 10.3389/fcvm.2023.1091950] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 02/22/2023] [Indexed: 03/11/2023] Open
Abstract
PurposeTo identify immune-related biomarkers in coronary artery disease (CAD), investigate their possible function in the immunological milieu of tumors, and initially investigate the mechanisms and therapeutic targets shared by CAD and cancer.MethodsDownload the CAD-related dataset GSE60681 from the GEO database. GSVA and WGCNA analyses were performed based on the GSE60681 dataset to identify the modules most pertinent to CAD, identify candidate hub genes and finally intersect the genes associated with immunity downloaded from the import database to find the hub genes. The GTEx, CCLE, and TCGA database were used to examine the expression of the hub gene in normal tissues, tumor cell lines, tumor tissues, and different tumor STAGES. One-factor cox and Kaplan-Meier analyses were performed to explore the prognosis of hub genes. Hub gene methylation levels in CAD and cancer were analyzed in the diseaseMeth 3.0 and ualcan databases, respectively. R package CiberSort processed the GSE60681 dataset to assess immune infiltration in CAD. TIMER2.0 evaluated hub genes with pan-cancer immune infiltration. The hub genes were analyzed for drug sensitivity and correlation with TMB, MSI, MMR, cancer-related functional status, and immune checkpoints in different tumors. Finally, GSEA was carried out on the crucial genes.ResultsWGCNA were used to pinpoint the green modules that were most closely related to CAD and intersections with immune-related genes were taken to remember the pivotal gene RBP1. RBP1 is hypermethylated in CAD and multiple cancers. Its expression levels in different cancers were associated with poor prognosis of cancer, with significant expression levels at higher stages of cancer staging. The immune infiltration results showed that RBP1 was closely associated with CAD and tumor-associated immune infiltration. The results indicated that RBP1 was strongly correlated with TMB, MSI, MMR, cancer-associated functional status, and immune checkpoints in various cancers. RBP1 was related to the sensitivity of six anticancer drugs. GSEA showed RBP1 was associated with immune cell activation, immune response, and cancer development.ConclusionRBP1 is a pivotal gene associated with immunity in CAD and pan-cancer and may mediate the development of CAD and cancer through immunity, making it a common therapeutic target for both.
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Feng S, Yang C, Wang J, Fan X, Ying X. Aggrephagy-related LncRNAs index: A predictor for HCC prognosis, immunotherapy efficacy, and chemosensitivity. Technol Health Care 2023:THC220738. [PMID: 36872811 DOI: 10.3233/thc-220738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
BACKGROUND Due to the complexity and heterogeneity of hepatocellular carcinoma, the existing clinical staging criterias are insufficient to accurately reflect the tumor microenvironment and predict the prognosis of HCC patients. Aggrephagy, as a type of selective autophagy, is associated with various phenotypes of malignant tumors. OBJECTIVE This study aimed to identify and validate a prognostic model based on aggrephagy-related LncRNAs to assess the prognosis and immunotherapeutic response of HCC patients. METHODS Based on the TCGA-LIHC cohort, aggrephagy-related LncRNAs were identified. Univariate Cox regression analysis and lasso and multivariate Cox regression were used to construct a risk-scoring system based on eight ARLs. CIBERSORT, ssGSEA, and other algorithms were used to evaluate and present the immune landscape of tumor microenvironment. RESULTS The high-risk group had a worse overall survival (OS) than the low-risk group. Patients in the high-risk group are more likely to benefit from immunotherapy because of their high infiltration level and high immune checkpoint expression. CONCLUSION The ARLs signature is a powerful predictor of prognosis for HCC patients, and the nomogram based on this model can help clinicians accurately determine the prognosis of HCC patients and screen for specific subgroups of patients who are more sensitive to immunotherapy and chemotherapy.
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Affiliation(s)
- Shengchun Feng
- Department of Clinical Laboratory, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China.,Department of Clinical Laboratory, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China
| | - Chunyan Yang
- Department of Ultrasound Medicine, Chongqing University Cancer Hospital, Chongqing, China.,Department of Clinical Laboratory, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China
| | - Jun Wang
- Department of Hepatopancreatobiliary Surgery, The People's Hospital of Lishui, Lishui, Zhejiang, China
| | - Xiaopeng Fan
- Department of Hepatopancreatobiliary Surgery, The People's Hospital of Lishui, Lishui, Zhejiang, China
| | - Xiaowei Ying
- Department of Hepatopancreatobiliary Surgery, The People's Hospital of Lishui, Lishui, Zhejiang, China
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3
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Huang P, Zhang B, Zhao J, Li MD. Integrating the Epigenome and Transcriptome of Hepatocellular Carcinoma to Identify Systematic Enhancer Aberrations and Establish an Aberrant Enhancer-Related Prognostic Signature. Front Cell Dev Biol 2022; 10:827657. [PMID: 35300417 PMCID: PMC8921559 DOI: 10.3389/fcell.2022.827657] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/31/2022] [Indexed: 12/22/2022] Open
Abstract
Recently, emerging evidence has indicated that aberrant enhancers, especially super-enhancers, play pivotal roles in the transcriptional reprogramming of multiple cancers, including hepatocellular carcinoma (HCC). In this study, we performed integrative analyses of ChIP-seq, RNA-seq, and whole-genome bisulfite sequencing (WGBS) data to identify intergenic differentially expressed enhancers (DEEs) and genic differentially methylated enhancers (DMEs), along with their associated differentially expressed genes (DEE/DME-DEGs), both of which were also identified in independent cohorts and further confirmed by HiC data. Functional enrichment and prognostic model construction were conducted to explore the functions and clinical significance of the identified enhancer aberrations. We identified a total of 2,051 aberrant enhancer-associated DEGs (AE-DEGs), which were highly concurrent in multiple HCC datasets. The enrichment results indicated the significant overrepresentations of crucial biological processes and pathways implicated in cancer among these AE-DEGs. A six AE-DEG-based prognostic signature, whose ability to predict the overall survival of HCC was superior to that of both clinical phenotypes and previously published similar prognostic signatures, was established and validated in TCGA-LIHC and ICGC-LIRI cohorts, respectively. In summary, our integrative analysis depicted a landscape of aberrant enhancers and associated transcriptional dysregulation in HCC and established an aberrant enhancer-derived prognostic signature with excellent predictive accuracy, which might be beneficial for the future development of epigenetic therapy for HCC.
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Affiliation(s)
- Peng Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bin Zhang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Junsheng Zhao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ming D. Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
- *Correspondence: Ming D. Li,
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4
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Fu Y, Wei X, Han Q, Le J, Ma Y, Lin X, Xu Y, Liu N, Wang X, Kong X, Gu J, Tong Y, Wu H. Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma. BMC Cancer 2021; 21:1165. [PMID: 34717566 PMCID: PMC8556945 DOI: 10.1186/s12885-021-08827-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 09/30/2021] [Indexed: 02/06/2023] Open
Abstract
Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08827-z.
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Affiliation(s)
- Yi Fu
- Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.,Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.,School of Medical Instruments, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Xindong Wei
- Nanjing University of Traditional Chinese Medicine, Nanjing, 210000, China
| | - Qiuqin Han
- Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.,Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Jiamei Le
- Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.,Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Yujie Ma
- Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Xinjie Lin
- Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Yuhui Xu
- Graduate School of Art and Sciences, Columbia University, New York, NY, 10027, USA
| | - Ning Liu
- Department of Clinical Oncology, Taian City Central Hospital, Taian, 271000, Shandong, China
| | - Xuan Wang
- Department of General Surgery, Nanjing General Hospital of Nanjing Military Command, Nanjing, 210000, China
| | - Xiaoni Kong
- Institute of Clinical Immunology, Department of Liver Diseases, Central Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200021, China
| | - Jinyang Gu
- Department of Transplantation, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
| | - Ying Tong
- Department of Liver Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
| | - Hailong Wu
- Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China. .,Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.
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Cai S, Guo X, Huang C, Deng Y, Du L, Liu W, Yang C, Zhao H, Ma K, Wang L, He J, Yu Z. Integrative analysis and experiments to explore angiogenesis regulators correlated with poor prognosis, immune infiltration and cancer progression in lung adenocarcinoma. J Transl Med 2021; 19:361. [PMID: 34419075 PMCID: PMC8380343 DOI: 10.1186/s12967-021-03031-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/07/2021] [Indexed: 02/07/2023] Open
Abstract
Angiogenesis is the process of capillary sprouting from pre-existing vessels and it plays a critical role in the carcinogenic process of lung adenocarcinoma (LUAD). However, the association of angiogenesis regulators with the prognosis and progression of LUAD needs to be further elucidated. In this study, we adopted differential expression analysis, Cox proportional hazards (PH) regression analysis and experimental validation to identify angiogenesis regulators correlated with a poor prognosis, immune infiltration and cancer progression in LUAD. These results showed that the diagnostic and prognostic models based on COL5A2 and EPHB2 served as independent biomarkers with superior predictive ability. The patients in the high-risk group exhibited a worse prognosis in the TCGA cohort (P < 0.001, HR = 1.72, 95% CI 1.28-2.30), GSE310210 cohort (P = 0.005, HR = 2.87, 95% CI 1.46-5.61), and GSE31019 cohort (P = 0.01, HR = 2.14, 95% CI 1.19-3.86) than patients in the low-risk group. The high prognostic risk patients had a higher TMB (P < 0.001); higher fractions of M0 macrophages, neutrophils, NK cells resting, and T cells CD4 memory activated (P < 0.05); and higher expression of immune checkpoints PD-1, PDL-1, PDL-2, and B7H3 (P < 0.001). Patients in the high-risk group were more sensitive to chemotherapeutic drugs and molecular targeted drugs such as cisplatin, doxorubicin, gefitinib, and bosutinib (P < 0.0001). In addition, inhibition of COL5A2 and EPHB2 effectively suppressed the proliferation and migration of LUAD cells. The current study identified angiogenesis regulators as potential biomarkers and therapeutic targets for LUAD and may help to further optimize cancer therapy.
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Affiliation(s)
- Songhua Cai
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Xiaotong Guo
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Chujian Huang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Youjun Deng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Longde Du
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Wenyi Liu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Chenglin Yang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Hongbo Zhao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Kai Ma
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Lixu Wang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China. .,Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Zhentao Yu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China.
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6
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Huang G, Wang C, Fu X. Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma. Future Oncol 2021; 17:4481-4495. [PMID: 34374301 DOI: 10.2217/fon-2021-0659] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Aims: Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate multi-omics data and predict survival in HCC. Methods: DNA methylation and mRNA expression data for HCC samples from the TCGA database were integrated using BiDNNs. With optimal clusters as labels, a support vector machine model was developed to predict survival. Results: Using the BiDNN-based model, samples were clustered into two survival subgroups. The survival subgroup classification was an independent prognostic factor. BiDNNs were superior to multimodal autoencoders. Conclusion: This study constructed and validated a BiDNN-based model for predicting prognosis in HCC, with implications for individualized therapies in HCC.
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Affiliation(s)
- Guojun Huang
- Department of Oncology, Pidu District People's Hospital, Chengdu, Sichuan, China
| | - Cheng Wang
- Department of General Surgery, Pidu District People's Hospital, Chengdu, Sichuan, China
| | - Xi Fu
- Department of Oncology, Pidu District People's Hospital, Chengdu, Sichuan, China
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7
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Aishanjiang K, Wei XD, Fu Y, Lin X, Ma Y, Le J, Han Q, Wang X, Kong X, Gu J, Wu H. Circular RNAs and Hepatocellular Carcinoma: New Epigenetic Players With Diagnostic and Prognostic Roles. Front Oncol 2021; 11:653717. [PMID: 33959506 PMCID: PMC8093866 DOI: 10.3389/fonc.2021.653717] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/22/2021] [Indexed: 12/24/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Due to the lack of potent diagnosis and prognosis biomarkers and effective therapeutic targets, the overall prognosis of survival is poor in HCC patients. Circular RNAs (circRNAs) are a class of novel endogenous non-coding RNAs with covalently closed loop structures and implicated in diverse physiological processes and pathological diseases. Recent studies have demonstrated the involvement of circRNAs in HCC diagnosis, prognosis, development, and drug resistance, suggesting that circRNAs may be a class of novel targets for improving HCC diagnosis, prognosis, and treatments. In fact, some artificial circRNAs have been engineered and showed their therapeutic potential in treating HCV infection and gastric cancer. In this review, we introduce the potential of circRNAs as biomarkers for HCC diagnosis and prognosis, as therapeutic targets for HCC treatments and discuss the challenges in circRNA research and chances of circRNA application.
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Affiliation(s)
- Kedeerya Aishanjiang
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China.,Department of Transplantation, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin-Dong Wei
- Department of General Surgery, The 81st Hospital Affiliated to Nanjing University of Traditional Chinese Medicine, Nanjing, China
| | - Yi Fu
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China
| | - Xinjie Lin
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China
| | - Yujie Ma
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China
| | - Jiamei Le
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China
| | - Qiuqin Han
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China
| | - Xuan Wang
- Department of General Surgery, The 81st Hospital Affiliated to Nanjing University of Traditional Chinese Medicine, Nanjing, China
| | - Xiaoni Kong
- Institute of Clinical Immunology, Department of Liver Diseases, Central Laboratory, ShuGuang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jinyang Gu
- Department of Transplantation, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hailong Wu
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Collaborative Innovation Center for Biomedicine, Shanghai, China.,Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China.,Collaborative Innovation Center for Biomedicine, Shanghai University of Medicine & Health Sciences, Shanghai, China
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8
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Zhu J, Tang B, Lv X, Meng M, Weng Q, Zhang N, Li J, Fan K, Zheng L, Fang S, Xu M, Ji J. Identifying Apoptosis-Related Transcriptomic Aberrations and Revealing Clinical Relevance as Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma. Front Oncol 2021; 10:519180. [PMID: 33680905 PMCID: PMC7931692 DOI: 10.3389/fonc.2020.519180] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 12/17/2020] [Indexed: 12/24/2022] Open
Abstract
In view of the unsatisfactory treatment outcome of liver cancer under current treatment, where the mortality rate is high and the survival rate is poor, in this study we aimed to use RNA sequencing data to explore potential molecular markers that can be more effective in predicting diagnosis and prognosis of hepatocellular carcinoma. RNA sequencing data and corresponding clinical information were obtained from multiple databases. After matching with the apoptotic genes from the Deathbase database, 14 differentially expressed human apoptosis genes were obtained. Using univariate and multivariate Cox regression analyses, two apoptosis genes (BAK1 and CSE1L) were determined to be closely associated with overall survival (OS) in HCC patients. And subsequently experiments also validated that knockdown of BAK1 and CSE1L significantly inhibited cell proliferation and promoted apoptosis in the HCC. Then the two genes were used to construct a prognostic signature and diagnostic models. The high-risk group showed lower OS time compared to low-risk group in the TCGA cohort (P < 0.001, HR = 2.11), GSE14520 cohort (P = 0.003, HR = 1.85), and ICGC cohort (P < 0.001, HR = 4). And the advanced HCC patients showed higher risk score and worse prognosis compared to early-stage HCC patients. Moreover, the prognostic signature was validated to be an independent prognostic factor. The diagnostic models accurately predicted HCC from normal tissues and dysplastic nodules in the training and validation cohort. These results indicated that the two apoptosis-related signature effectively predicted diagnosis and prognosis of HCC and may serve as a potential biomarker and therapeutic target for HCC.
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Affiliation(s)
- Jinyu Zhu
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Bufu Tang
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiuling Lv
- Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Miaomiao Meng
- Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Qiaoyou Weng
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Nannan Zhang
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jie Li
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Kai Fan
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Liyun Zheng
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Shiji Fang
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Min Xu
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Jiansong Ji
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, China.,Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
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