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Xia F, Zhang Q, Xia G, Ndhlovu E, Chen X, Huang Z, Zhang B, Zhu P. A pathologic scoring system for predicting postoperative prognosis in patients with ruptured hepatocellular carcinoma. Asian J Surg 2024; 47:3015-3025. [PMID: 38326117 DOI: 10.1016/j.asjsur.2024.01.139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/14/2024] [Accepted: 01/26/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND The accuracy of pathological factors to predict the prognosis of patients with ruptured hepatocellular carcinoma (rHCC) is unclear. We aimed to develop and validate a novel scoring system based on pathological factors to predict the postoperative survival of patients with rHCC. METHOD Patients with rHCC who underwent hepatectomy were recruited from three hospitals and allocated to the training (n = 221) and validation (n = 194) cohorts. A new scoring system, namely the MSE (microvascular invasion-satellite foci-Edmondson Steiner) score, was established based on three pathological factors using univariate and multivariate Cox proportional hazards regression analyses, including microvascular invasion, satellite foci, and differentiation grade. Finally, patients were stratified into three groups based on their risk of prognosis (low, intermediate, or high) according to their MSE score. We also constructed MSE score-based nomograms. The performance of the nomograms was assessed by receiver operating characteristic and calibration curve analyses and validated using the validation cohort. RESULTS Three pathological factors were significantly correlated with overall survival (OS) and recurrence-free survival (RFS), three of which were included in the MSE score. The score can clearly stratify rHCC patients after hepatectomy (P < 0.05). And we established nomograms based on the MSE score (MSE score, Barcelona Clinic Liver Cancer stage, and alpha-fetoprotein concentration) to predict postoperative OS and RFS in patients with rHCC. The nomograms showed good discrimination, with C-indices over 0.760 for OS and RFS at 1, 3, and 5 years, respectively. The calibration curve showed excellent nomogram calibration, which was also verified in the validation cohort. CONCLUSION The clinical MSE score were accurate in predicting OS and RFS in patients with rHCC with resectable lesions after hepatectomy.
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Affiliation(s)
- Feng Xia
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiao Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Zhongshan People's Hospital Affiliated to Guangdong Medical University, Guangdong, China
| | - Guobing Xia
- Department of Hepatobiliary and Pancreatic Surgery, Huangshi Central Hospital of Edong Healthcare Group, Hubei Polytechnic University.Huangshi, Hubei, China
| | - Elijah Ndhlovu
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoping Chen
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhiyuan Huang
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Bixiang Zhang
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Peng Zhu
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Chen H, Li J, Cao D, Tang H. Construction of a Prognostic Model for Hepatocellular Carcinoma Based on Macrophage Polarization-Related Genes. J Hepatocell Carcinoma 2024; 11:857-878. [PMID: 38751862 PMCID: PMC11095518 DOI: 10.2147/jhc.s453080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/07/2024] [Indexed: 05/18/2024] Open
Abstract
Background The progression of hepatocellular carcinoma (HCC) is related to macrophage polarization (MP). Our aim was to identify genes associated with MP in HCC patients and develop a prognostic model based on these genes. Results We successfully developed a prognostic model consisting of six MP-related genes (SCN4A, EBF3, ADGRB2, HOXD9, CLEC1B, and MSC) to calculate the risk score for each patient. Patients were then classified into high- and low-risk groups based on their median risk score. The performance of the MP-related prognostic model was evaluated using Kaplan-Meier and ROC curves, which yielded favorable results. Additionally, the nomogram demonstrated good clinical effectiveness and displayed consistent survival predictions with actual observations. Gene Set Enrichment Analysis (GSEA) revealed enrichment of pathways related to KRAS signaling downregulation, the G2M checkpoint, and E2F targets in the high-risk group. Conversely, pathways associated with fatty acid metabolism, xenobiotic metabolism, bile acid metabolism, and adipogenesis were enriched in the low-risk group. The risk score positively correlated with the number of invasion-related genes. Immune checkpoint expression differed significantly between the two groups. Patients in the high-risk group exhibited increased sensitivity to mitomycin C, cisplatin, gemcitabine, rapamycin, and paclitaxel, while those in the low-risk group showed heightened sensitivity to doxorubicin. These findings suggest that the high-risk group may have more invasive HCC with greater susceptibility to specific drugs. IHC staining revealed higher expression levels of SCN4A in HCC tissues. Furthermore, experiments conducted on HepG2 cells demonstrated that supernatants from cells with reduced SCN4A expression promoted M2 macrophage polarization marker, CD163 in THP-1 cells. Reduced SCN4A expression induced HCC-related genes, while increased SCN4A expression reduced their expression in HepG2 cells. Conclusion The MP-related prognostic model comprising six MPRGs can effectively predict HCC prognosis, infer invasiveness, and guide drug therapy. SCN4A is identified as a suppressor gene in HCC.
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Affiliation(s)
- Han Chen
- Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
- Division of Infectious Diseases, State Key Laboratory of Biotherapy and Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Jianhao Li
- Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
- Division of Infectious Diseases, State Key Laboratory of Biotherapy and Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Dan Cao
- Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
- Division of Infectious Diseases, State Key Laboratory of Biotherapy and Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Hong Tang
- Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
- Division of Infectious Diseases, State Key Laboratory of Biotherapy and Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
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Wang J, Cai L, Huang G, Wang C, Zhang Z, Xu J. CENPA and BRCA1 are potential biomarkers associated with immune infiltration in heart failure and pan-cancer. Heliyon 2024; 10:e28786. [PMID: 38576566 PMCID: PMC10990859 DOI: 10.1016/j.heliyon.2024.e28786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/06/2024] Open
Abstract
Heart failure (HF) and cancer are the two leading causes of death worldwide and affect one another in a bidirectional way. We aimed to identify hub therapeutic genes as potential biomarkers for the identification and treatment of HF and cancer. Gene expression data of heart samples from patients with ischemic HF (IHF) and healthy controls were retrieved from the GSE42955 and GSE57338 databases. Difference analysis and weighted gene co-expression network analysis (WGCNA) were used to identify key modules associated with IHF. The overlapping genes were subjected to gene and protein enrichment analyses to construct a protein-protein interaction (PPI) network, which was screened for hub genes among the overlapping genes. A total of eight hub genes were subjected to correlation, immune cell infiltration, and ROC analyses. Then we analyzed the roles of two significant genes in 33 tumor types to explore their potential as common targets in HF and cancer. A total of 85 genes were identified by WGCNA and differentially expressed gene (DEG) analyses. BRCA1, MED17, CENPA, RXRA, RXRB, SMARCA2, CDCA2, and PMS2 were identified as the hub genes with IHF. Finally, CENPA and BRCA1 were identified as potential common targets for IHF and cancer. These findings provide new perspectives for expanding our understanding of the etiology and underlying mechanisms of HF and cancer.
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Affiliation(s)
- Jian Wang
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
| | - Lin Cai
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
| | - Gang Huang
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
| | - Chunbin Wang
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
| | - Zhen Zhang
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
- Chengdu Institute of Cardiovascular Disease, 82 Qinglong Street, Chengdu, 610014, China
| | - Junbo Xu
- Department of Cardiology, The Affiliated Hospital of Southwest Jiaotong University, 82 Qinglong Street, Chengdu, 610014, China
- Department of Cardiology, The Third People's Hospital of Chengdu, 82 Qinglong Street, Chengdu, 610014, China
- Chengdu Institute of Cardiovascular Disease, 82 Qinglong Street, Chengdu, 610014, China
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Yu X, Zhang H, Li J, Gu L, Cao L, Gong J, Xie P, Xu J. Construction of a prognostic prediction model in liver cancer based on genes involved in integrin cell surface interactions pathway by multi-omics screening. Front Cell Dev Biol 2024; 12:1237445. [PMID: 38374893 PMCID: PMC10875080 DOI: 10.3389/fcell.2024.1237445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 01/23/2024] [Indexed: 02/21/2024] Open
Abstract
Background: Liver cancer is a common malignant tumor with an increasing incidence in recent years. We aimed to develop a model by integrating clinical information and multi-omics profiles of genes to predict survival of patients with liver cancer. Methods: The multi-omics data were integrated to identify liver cancer survival-associated signal pathways. Then, a prognostic risk score model was established based on key genes in a specific pathway, followed by the analysis of the relationship between the risk score and clinical features as well as molecular and immunologic characterization of the key genes included in the prediction model. The function experiments were performed to further elucidate the undergoing molecular mechanism. Results: Totally, 4 pathways associated with liver cancer patients' survival were identified. In the pathway of integrin cell surface interactions, low expression of COMP and SPP1, and low CNVs level of COL4A2 and ITGAV were significantly related to prognosis. Based on above 4 genes, the risk score model for prognosis was established. Risk score, ITGAV and SPP1 were the most significantly positively related to activated dendritic cell. COL4A2 and COMP were the most significantly positively associated with Type 1 T helper cell and regulatory T cell, respectively. The nomogram (involved T stage and risk score) may better predict short-term survival. The cell assay showed that overexpression of ITGAV promoted tumorigenesis. Conclusion: The risk score model constructed with four genes (COMP, SPP1, COL4A2, and ITGAV) may be used to predict survival in liver cancer patients.
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Affiliation(s)
- Xiang Yu
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Radiology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Hao Zhang
- Department of Hepatobiliary Surgery, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Hepatobiliary Surgery, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Jinze Li
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Radiology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Lu Gu
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Radiology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Lei Cao
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Radiology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Jun Gong
- Department of Hepatobiliary Surgery, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Hepatobiliary Surgery, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Ping Xie
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Radiology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Jian Xu
- Department of Hepatobiliary Surgery, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Hepatobiliary Surgery, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
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Wang X, Cui X, Wang W, Sun J, Wang Y, Han W, Xie X, Zhu Z, Zhang X, Yu L, Liu D. Deciphering essential druggable genes reveals potential immune-inflammatory axis in hepatocellular carcinoma. Comput Biol Med 2023; 167:107625. [PMID: 37918266 DOI: 10.1016/j.compbiomed.2023.107625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/30/2023] [Accepted: 10/23/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis in patients. Its pathogenesis is a complex process of multi-factors and multi-steps. However, the etiology and exact molecular mechanism are not completely clear. METHODS Here, we constructed a specific-expressed network based on RNA sequencing data. Gene and miRNA expression profiles and clinical evidence were integrated to detect hepatocellular carcinoma survival modules. Finally, we attempted to identify potential key biomarkers and drug targets by integrating drug sensitivity analysis and immune infiltration analysis. RESULTS A total of 42 prognostic modules for hepatocellular carcinoma were detected. The prognostic modules were significantly enriched with known cancer-related molecules and 12.93 % molecules of prognostic modules had been found were the targets of small molecule drug. In addition, we found that 38 of 42 (90.48 %) essential genes were associated with the proportions of at least one of the 7 immune cell types. CONCLUSION We integrated clinical prognosis information, RNA sequencing data, and drug activity data to explore risk modules of hepatocellular carcinoma. Through drug sensitivity analysis and immune infiltration analysis, we assessed the value of hub genes in the modules as potential biomarkers and drug targets for hepatocellular carcinoma. The protocol provides new insight into parsing the molecular mechanism and theoretical basis of hepatocellular carcinoma.
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Affiliation(s)
- Xiaoren Wang
- Department of Infectious Disease, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xudong Cui
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Wencan Wang
- Guangzhou National Laboratory, Guangzhou, China
| | - Jia Sun
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Yan Wang
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Wanru Han
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Xiaotong Xie
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Zhu Zhu
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Xijun Zhang
- E.N.T. Department, The Fourth Hospital of Harbin Medical University, Harbin, China
| | - Lei Yu
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China.
| | - Dabin Liu
- Department of Infectious Disease, The Fourth Hospital of Harbin Medical University, Harbin, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China.
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Lin Q, Jiang Z, Mo D, Liu F, Qin Y, Liang Y, Cheng Y, Huang H, Fang M. Beta2-Microglobulin as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram. J Hepatocell Carcinoma 2023; 10:1813-1825. [PMID: 37850078 PMCID: PMC10577246 DOI: 10.2147/jhc.s425344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/04/2023] [Indexed: 10/19/2023] Open
Abstract
Background Accurate prognosis is crucial for improving hepatocellular carcinoma (HCC) patients, clinical management, and outcomes post-liver resection. However, the lack of reliable prognostic indicators poses a significant challenge. This study aimed to develop a user-friendly nomogram to predict HCC patients' post-resection prognosis. Methods We retrospectively analyzed the data from 1091 HCC patients, randomly split into training (n=767) and validation (n=324) cohorts. Receiver operating characteristic (ROC) curves determined the optimal cut-off value for alpha1-microglobulin (α1MG) and Beta2-microglobulin (β2MG). Kaplan-Meier analysis assessed microglobulin's impact on survival, followed by Cox regression to identify prognostic factors and construct a nomogram. The predictive accuracy and discriminative ability of the nomogram were measured by the concordance index (C-index), calibration curves, area under the ROC curve (AUC), and decision curve analysis (DCA), and were compared with the BCLC staging system, Edmondson grade, or BCLC stage plus Edmondson grade. Results Patients with high β2MG (≥2.395mg/L) had worse overall survival (OS). The nomogram integrated β2MG, BCLC stage, Edmondson grade, microvascular invasion (MVI), and serum carbohydrate antigen 199 (CA199) levels. C-index for training and validation cohorts (0.712 and 0.709) outperformed the BCLC stage (0.660 and 0.657), Edmondson grade (0.579 and 0.564), and the combination of BCLC stage with Edmondson grade (0.681 and 0.668), improving prognosis prediction. Calibration curves demonstrated good agreement between predicted and observed survival. AUC values exceeded 0.700 over time, highlighting the nomogram's discriminative ability. DCA revealed superior overall net income compared to other systems, emphasizing its clinical utility. Conclusion Our β2MG-based nomogram accurately predicts HCC patients' post-resection prognosis, aiding intervention and follow-up planning. Significantly, our nomogram surpasses existing prognostic indicators, including BCLC stage, Edmondson grade, and the combination of BCLC stage with Edmondson grade, by demonstrating superior predictive performance.
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Affiliation(s)
- Qiumei Lin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Zongwei Jiang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Dan Mo
- Department of Breast, Guangxi Zhuang Autonomous Region Maternal and Child Health Care Hospital, Nanning, 530025, People’s Republic of China
| | - Fengfei Liu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yuling Qin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yihua Liang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yuchen Cheng
- Department of Clinical Laboratory, Wuzhou Maternal and Child Health-Care Hospital, Wuzhou, People’s Republic of China
| | - Hao Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Min Fang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
- Engineering Research Center for Tissue & Organ Injury and Repair Medicine, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
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Huang C, Li Y, Ling Q, Wei C, Fang B, Mao X, Yang R, Zhang L, Huang S, Cheng J, Liao N, Wang F, Mo L, Mo Z, Li L. Establishment of a risk score model for bladder urothelial carcinoma based on energy metabolism-related genes and their relationships with immune infiltration. FEBS Open Bio 2023; 13:736-750. [PMID: 36814419 PMCID: PMC10068335 DOI: 10.1002/2211-5463.13580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/28/2023] [Accepted: 02/21/2023] [Indexed: 02/24/2023] Open
Abstract
Bladder urothelial carcinoma (BLCA) is a common malignant tumor of the human urinary system, and a large proportion of BLCA patients have a poor prognosis. Therefore, there is an urgent need to find more efficient and sensitive biomarkers for the prognosis of BLCA patients in clinical practice. RNA sequencing (RNA-seq) data and clinical information were obtained from The Cancer Genome Atlas, and 584 energy metabolism-related genes (EMRGs) were obtained from the Reactome pathway database. Cox regression analysis and least absolute shrinkage and selection operator analysis were applied to assess prognostic genes and build a risk score model. The estimate and cibersort algorithms were used to explore the immune microenvironment, immune infiltration, and checkpoints in BLCA patients. Furthermore, we used the Human Protein Atlas database and our single-cell RNA-seq datasets of BLCA patients to verify the expression of 13 EMRGs at the protein and single-cell levels. We constructed a risk score model; the area under the curve of the model at 5 years was 0.792. The risk score was significantly correlated with the immune markers M0 macrophages, M2 macrophages, CD8 T cells, follicular helper T cells, regulatory T cells, and dendritic activating cells. Furthermore, eight immune checkpoint genes were significantly upregulated in the high-risk group. The risk score model can accurately predict the prognosis of BLCA patients and has clinical application value. In addition, according to the differences in immune infiltration and checkpoints, BLCA patients with the most significant benefit can be selected for immune checkpoint inhibitor therapy.
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Affiliation(s)
- Caihong Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yexin Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Qiang Ling
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Chunmeng Wei
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Bo Fang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Xingning Mao
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Rirong Yang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - LuLu Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Shengzhu Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jiwen Cheng
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Naikai Liao
- School of Public Health, Guangxi Medical University, Nanning, China
| | - Fubo Wang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Linjian Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Longman Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
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Wei X, Zhou Z, Long M, Lin Q, Qiu M, Chen P, Huang Q, Qiu J, Jiang Y, Wen Q, Liu Y, Li R, Nong C, Guo Q, Yu H, Zhou X. A novel signature constructed by super-enhancer-related genes for the prediction of prognosis in hepatocellular carcinoma and associated with immune infiltration. Front Oncol 2023; 13:1043203. [PMID: 36845708 PMCID: PMC9948016 DOI: 10.3389/fonc.2023.1043203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Background Super-enhancer (SE) refers to a regulatory element with super transcriptional activity, which can enrich transcription factors and drive gene expression. SE-related genes play an important role in the pathogenesis of malignant tumors, including hepatocellular carcinoma (HCC). Methods The SE-related genes were obtained from the human super-enhancer database (SEdb). Data from the transcriptome analysis and related clinical information with HCC were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The upregulated SE-related genes from TCGA-LIHC were identified by the DESeq2R package. Multivariate Cox regression analysis was used to construct a four-gene prognostic signature. According to the median risk score, HCC patients were divided into high-risk and low-risk group patients. Results The Kaplan-Meier (KM) curve showed that a significantly worse prognosis was found for the high-risk group (P<0.001). In the TCGA-LIHC dataset, the area under the curve (AUC) values were 0.737, 0.662, and 0.667 for the model predicting overall survival (OS) over 1-, 3-, and 5- years, respectively, indicating the good prediction ability of our prediction model. This model's prognostic value was further validated in the LIRI-JP dataset and HCC samples (n=65). Furthermore, we found that higher infiltration level of M0 macrophages and upregulated of CTLA4 and PD1 in the high-risk group, implying that immunotherapy could be effective for those patients. Conclusion These results provide further evidence that the unique SE-related gene model could accurately predict the prognosis of HCC.
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Affiliation(s)
- Xueyan Wei
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zihan Zhou
- Department of Cancer Prevention and Control, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Meiying Long
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Qiuling Lin
- Department of Clinical Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Moqin Qiu
- Department of Respiratory Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Peiqin Chen
- Editorial Department of Chinese Journal of Oncology Prevention and Treatment, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiongguang Huang
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Jialin Qiu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yanji Jiang
- Scientific Research Department, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiuping Wen
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yingchun Liu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Runwei Li
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, United States
| | - Cunli Nong
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Qian Guo
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Hongping Yu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Key Laboratory of Early Prevention and Treatment for Regional High-Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, China,Key Cultivated Laboratory of Cancer Molecular Medicine, Health Commission of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
| | - Xianguo Zhou
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
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Li D, Lei L, Wang J, Tang B, Wang J, Dong R, Shi W, Liu G, Zhao T, Wu Y, Zhang Y. Prognosis and personalized medicine prediction by integrated whole exome and transcriptome sequencing of hepatocellular carcinoma. Front Genet 2023; 14:1075347. [PMID: 36816040 PMCID: PMC9932713 DOI: 10.3389/fgene.2023.1075347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/23/2023] [Indexed: 02/05/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a clinically and genetically heterogeneous disease. To better describe the clinical value of the main driver gene mutations of HCC, we analyzed the whole exome sequencing data of 125 patients, and combined with the mutation data in the public database, 14 main mutant genes were identified. And we explored the correlation between the main mutation genes and clinical features. Consistent with the results of previous data, we found that TP53 and LRP1B mutations were related to the prognosis of our patients by WES data analysis. And we further explored the associated characteristics of TP53 and LRP1B mutations. However, it is of great clinical significance to tailor a unique prediction method and treatment plan for HCC patients according to the mutation of TP53. For TP53 wild-type HCC patients, we proposed a prognostic risk model based on 11 genes for better predictive value. According to the median risk score of the model, HCC patients with wild-type TP53 were divided into high-risk and low-risk groups. We found significant transcriptome changes in the enrichment of metabolic-related pathways and immunological characteristics between the two groups, suggesting the predictability of HCC immunotherapy by using this model. Through the CMap database, we found that AM580 had potential therapeutic significance for high-risk TP53 wild-type HCC patients.
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Affiliation(s)
- Debao Li
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong, China,Chongqing International Institute for Immunology, Chongqing, China,Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Lei Lei
- Department of Ophthalmology, Airforce Hospital, Chengdu, Sichuan, China
| | - Jinsong Wang
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Bo Tang
- Chongqing International Institute for Immunology, Chongqing, China
| | - Jiuling Wang
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Rui Dong
- Chongqing International Institute for Immunology, Chongqing, China
| | - Wenjiong Shi
- Chongqing International Institute for Immunology, Chongqing, China
| | - Guo Liu
- Qionglai Hospital of Traditional Chinese Medicine, Qionglai, Sichuan, China
| | - Tingting Zhao
- Chongqing International Institute for Immunology, Chongqing, China,School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, China
| | - Yuzhang Wu
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong, China,Chongqing International Institute for Immunology, Chongqing, China,Institute of Immunology, PLA, Army Medical University, Chongqing, China,*Correspondence: Yi Zhang, ; Yuzhang Wu,
| | - Yi Zhang
- Chongqing International Institute for Immunology, Chongqing, China,School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, China,*Correspondence: Yi Zhang, ; Yuzhang Wu,
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Fan W, Chen X, Li R, Zheng R, Wang Y, Guo Y. A prognostic risk model for ovarian cancer based on gene expression profiles from gene expression omnibus database. Biochem Genet 2023; 61:138-150. [PMID: 35761155 DOI: 10.1007/s10528-022-10232-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 04/18/2022] [Indexed: 01/24/2023]
Abstract
This study explored prognostic genes of ovarian cancer and built a prognostic model based on these genes to predict patient's survival, which is of great significance for improving treatment of ovarian cancer. GSE26712 dataset was downloaded from Gene Expression Omnibus database as training set, while OV-AU dataset was downloaded from ICGC website as validation set. All genes in GSE26712 were analyzed by univariate Cox regression, Lasso regression, and multivariate Cox regression analyses. Then prognosis-related feature genes were screened to construct a multivariate risk model. Meanwhile, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed on samples in the high/low-risk groups using Gene Set Enrichment Analysis (GSEA) software. Finally, survival curve and receiver operating characteristic curve were drawn to verify the validity of the model. Ten feature genes related to prognosis of ovarian cancer were obtained: CMTM6, COLGALT1, F2R, GPR39, IGFBP3, RNF121, MTMR9, ORAI2, SNAI2, ZBTB16. GSEA enrichment analysis showed that there were notable differences in biological pathways such as gap junctions and homologous recombination between the high/low-risk groups. Through further verification of training set and validation set, the 10-gene prognostic model was found to be effective for the prognosis of ovarian cancer patients. In this study, we constructed a 10-gene prognostic model which predicted the prognosis of ovarian cancer patients well by integrating clinical prognostic parameters. It may have certain reference value for subsequent clinical treatment research of ovarian cancer patients and help in clinical treatment decision-making.
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Affiliation(s)
- Wei Fan
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Xiaoyun Chen
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Ruiping Li
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Rongfang Zheng
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Yunyun Wang
- Lanzhou University Second Hospital, Lanzhou City, 730030, Gansu Province, China
| | - Yuzhen Guo
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China.
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Xun Z, Wang Y, Long J, Li Y, Yang X, Sun H, Zhao H. Development and validation of a genomic instability-related lncRNA prognostic model for hepatocellular carcinoma. Front Genet 2023; 13:1034979. [PMID: 36712850 PMCID: PMC9877230 DOI: 10.3389/fgene.2022.1034979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/22/2022] [Indexed: 01/15/2023] Open
Abstract
Genomic instability is a characteristic of tumors, and recent studies have shown that it is related to a poor prognosis of multiple cancers. Long non-coding RNAs (lncRNAs) have become a research hotspot in recent years, and many unknown biological functions are being explored. For example, some lncRNAs play a critical role in the initiation and progression of multiple cancer types by modulating genomic instability. However, the role of genomic instability-related lncRNAs in liver cancer remains unclear. Therefore, we screened genomic instability-related lncRNAs by combining somatic mutation data and RNA-Seq data in The Cancer Genome Atlas (TCGA) database. We established a genomic instability-related lncRNA model (GLncM) involving ZFPM2-AS1 and MIR210HG to predict the hepatocellular carcinoma (HCC) prognosis and further explore the clinical significance of these lncRNAs, and the robustness of the model was validated in the verification set. Thereafter, we calculated the immune score for each patient and explored the relationship between genome instability and the immune microenvironment. The analysis indicated that this model was better than the immune microenvironment in predicting the prognosis of HCC patients, suggesting that the GLncM may be an effective indicator of HCC prognosis and providing a new direction and strategy for estimating the prognosis of HCC patients.
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12
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Wang D, Hu H, Ding H, Zhao H, Tian F, Chi Q. Elevated expression of TNFRSF4 impacts immune cell infiltration and gene mutation in hepatocellular carcinoma. Cancer Biomark 2023; 36:147-159. [PMID: 36591653 DOI: 10.3233/cbm-210538] [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: 12/28/2022]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, which makes prognostic prediction challenging.We aimed to investigate association of TNFRSF4 expression with the immune infiltration and gene mutation in HCC. METHODS In this study, the expression profiles and corresponding clinical data of HCC patients were downloaded from the Cancer Genome Atlas (TCGA) database.Kaplan-Meier and Cox regression were used to evaluate the clinical value of TNFRSF4. ESTIMATE and CIBERSORT algorithms were applied to investigate the infiltration ratio of 22 immune cells. The WGCNA and LASSO COX algorithms were performed, establishing a prognostic risk model that was then validated by HCC samples from GEO. Finally, the effects on gene mutation occurring in HCC patients of TNFRSF4 expression and risk score were appraised. RESULTS In HCC tissues, it was found the TNFRSF4 expression profile was significantly different with age, gender, tumor grade, disease stage, prominently affecting the survival outcome and prognosis of patients. Univariate and multivariate COX regression analysis suggested that TNFRSF4 was an independent prognostic marker. Samples of high/low expression of TNFRSF4 were screened for differential genes, and then the WGCNA and LASSO COX constructed a 13-gene signature, excellently dividing samples into hign/low risk groups. Compared with the low-risk group, the overall survival (OS) of high-risk group was markedly lower, with P< 0.0001. By ROC curve analysis, the predictive ability of the 13-gene signature was further confirmed. Both the high/low TNFRSF4 expression and the high/low risk score were demonstrated to exert effects on the frequency of gene mutation in HCC. CONCLUSIONS As an independent prognostic marker of HCC, TNFRSF4 was found simultaneously to affect the immune infiltration of cells and the frequency of gene mutations.
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Affiliation(s)
- Di Wang
- School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Huan Hu
- School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Huan Ding
- School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Han Zhao
- School of Integrated Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Feifei Tian
- School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Qingjia Chi
- Department of Engineering Structure and Mechanics, School of Science, Wuhan University of Technology, Wuhan, Hubei, China
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Hao J, He AY, Zhao X, Chen XQ, Liu QL, Sun N, Zhang RQ, Li PP. Pan-Cancer Study of the Prognosistic Value of Selenium Phosphate Synthase 1. Cancer Control 2023; 30:10732748231170485. [PMID: 37072373 PMCID: PMC10126790 DOI: 10.1177/10732748231170485] [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: 04/20/2023] Open
Abstract
Objective: This study sought to determine the mean prognostic usefulness of seleniumphosphate synthase (SEPHS1) by investigating its expression in 33 human malignancies and its relationship to tumor immunity.Methods: The expression of selenophosphate synthase 1 (SEPHS1) in 33 human malignant tumors was examined using the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), and TIMER databases. Furthermore, the TCGA cohort was used to investigate relationships between SEPHS1 and immunological checkpoint genes (ICGs), tumor mutation burden (TMB), microsatellite instability (MSI), and DNA mismatch repair genes (MMRs). To establish independent risk factors and calculate survival probabilities for liver hepatocellular carcinoma (LIHC) and brain lower-grade glioma (LGG), Cox regression models and Kaplan-Meier curves were utilized. Eventually, the Genomics of Cancer Drug Sensitivity (GDSC) database was used to evaluate the drug sensitivity in LGG and LIHC patients with high SEPHS1 expression.Results: Overall, in numerous tumor tissues, SEPHS1 was highly expressed, and it significantly linked with the prognosis of LGG, ACC, and LIHC (P < .05). Furthermore, in numerous cancers, SEPHS1 expression was linked to tumor-infiltrating immune cells (TIICs), TMB, MSI, and MMRs. According to univariate and multivariate Cox analyses, SEPHS1 expression was significant for patients with LGG and LIHC.Conclusion: High SEPHS1 expression has a better prognosis for LGG, while low SEPHS1 expression has a better prognosis for LIHC. Chemotherapy was advised for LGG patients, particularly for those with high SEPHS1 expression because it can predict how responsive patients will be to 5-Fluorouracil and Temozolomide. This interaction between SEPHS1 and chemoradiotherapy has a positive clinical impact and may be used as evidence for chemotherapy for LGG and LIHC patients.
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Affiliation(s)
- Jie Hao
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Ao-Yue He
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Xu Zhao
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Xue-Qin Chen
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Qi-Ling Liu
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Na Sun
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Rong-Qiang Zhang
- Shannxi University of Chinese Medicine, Xianyang, Shaanxi, P. R. China
| | - Ping-Ping Li
- Department of Vip Center, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China
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Feng Y, Li P, Yang F, Xu K. Establishment of a prognostic prediction system based on tumor microenvironment of pancreatic cancer. Medicine (Baltimore) 2022; 101:e32364. [PMID: 36595826 PMCID: PMC9794356 DOI: 10.1097/md.0000000000032364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Pancreatic cancer (PC) is an inflammatory tumor. Tumor microenvironment (TME) plays an important role in the development of PC. This study aims to explore hub genes of TME and establish a prognostic prediction system for PC. METHODS High throughput RNA-sequencing and clinical data of PC were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium database, respectively. PC patients were divided into high- and low-score group by using stromal, immune scores system based on ESTIMATE. Differentially expressed genes between high- and low-score patients were screened and survival-related differentially expressed genes were identified as candidate genes by univariate Cox regression analysis. Final variables for establishment of the prognostic prediction system were determined by LASSO analysis and multivariate Cox regression analysis. The predictive power of the prognostic system was evaluated by internal and external validation. RESULTS A total of 210 candidate genes were identified by stromal, immune scores system, and survival analyses. Finally, the prognostic risk score system was constructed by the following genes: FAM57B, HTRA3, CXCL10, GABRP, SPRR1B, FAM83A, and LY6D. In process of internal validation, Harrell concordance index (C-index) of this prognostic risk score system was 0.73, and the area under the receiver operating characteristic curve value of 1-year, 2-year, and 3-year overall survival period was 0.67, 0.76 and 0.86, respectively. In the external validation set, the survival prediction C-index was 0.71, and the area under the curve was 0.81, 0.72, and 0.78 at 1-year, 2-year, and 3-year, respectively. CONCLUSION This prognostic risk score system based on TME demonstrated a good predictive capacity to the prognosis of PC. It may provide information for the treatment strategy and follow-up for patients with PC.
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Affiliation(s)
- Yan Feng
- Department of Hepatology, the Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Pengcheng Li
- Clinical Medical College, Chengdu Medical College, Sichuan, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Sichuan, China
- Key Clinical Specialty of Sichuan Province, Sichuan, China
| | - Fang Yang
- Clinical Medical College, Chengdu Medical College, Sichuan, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Sichuan, China
- Key Clinical Specialty of Sichuan Province, Sichuan, China
| | - Ke Xu
- Clinical Medical College, Chengdu Medical College, Sichuan, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Sichuan, China
- Key Clinical Specialty of Sichuan Province, Sichuan, China
- * Correspondence: Ke Xu, Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan 610500, China (e-mail: )
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15
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Zhang G, Hou Y. Screening for aberrantly methylated and differentially expressed genes in nonalcoholic fatty liver disease of hepatocellular carcinoma patients with cirrhosis. World J Surg Oncol 2022; 20:364. [PMCID: PMC9673405 DOI: 10.1186/s12957-022-02828-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/03/2022] [Indexed: 11/19/2022] Open
Abstract
Abstract
Background
Nonalcoholic fatty liver disease (NAFLD) as the leading chronic liver disease worldwide causes hepatic fibrosis, cirrhosis and hepatocellular carcinoma (HCC). The aim of this study was to find potential aberrantly methylated and differentially expressed genes in NAFLD of HCC patients with cirrhosis.
Methods
DNA methylation data, mRNA expression data, and the corresponding clinical information of HCC were downloaded from the Cancer Genome Atlas (TCGA, tissue sample) database. HCC patients with cirrhosis were divided into two groups according to the presence of NAFLD. The differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were obtained.
Results
By overlapping 79 up-regulated genes and 1020 hypomethylated genes, we obtained 5 hypomethylated-highly expressed genes (HypoHGs). By overlapping 365 down-regulated genes and 481 hypermethylated genes, we identified 13 hypermethylated-lowly expressed genes (Hyper-LGs). Survival analysis of these 18 MDEGs indicated that the expression of DGKK and HOXD9 was significantly correlated with the overall survival time of NAFLD patients.
Conclusions
We identified several candidate genes whose expressions were regulated by DNA methylation of NAFLD of HCC with cirrhosis, which may provide a new field in understanding the clinical pathological mechanism of NAFLD of HCC with cirrhosis.
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Malcher A, Stokowy T, Berman A, Olszewska M, Jedrzejczak P, Sielski D, Nowakowski A, Rozwadowska N, Yatsenko AN, Kurpisz MK. Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia. Andrology 2022; 10:1605-1624. [PMID: 36017582 PMCID: PMC9826517 DOI: 10.1111/andr.13269] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 06/21/2022] [Accepted: 08/17/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Genetic causes that lead to spermatogenetic failure in patients with nonobstructive azoospermia (NOA) have not been yet completely established. OBJECTIVE To identify low-frequency NOA-associated single nucleotide variants (SNVs) using whole-genome sequencing (WGS). MATERIALS AND METHODS Men with various types of NOA (n = 39), including samples that had been previously tested with whole-exome sequencing (WES; n = 6) and did not result in diagnostic conclusions. Variants were annotated using the Ensembl Variant Effect Predictor, utilizing frequencies from GnomAD and other databases to provide clinically relevant information (ClinVar), conservation scores (phyloP), and effect predictions (i.e., MutationTaster). Structural protein modeling was also performed. RESULTS Using WGS, we revealed potential NOA-associated SNVs, such as: TKTL1, IGSF1, ZFPM2, VCX3A (novel disease causing variants), ESX1, TEX13A, TEX14, DNAH1, FANCM, QRICH2, FSIP2, USP9Y, PMFBP1, MEI1, PIWIL1, WDR66, ZFX, KCND1, KIAA1210, DHRSX, ZMYM3, FAM47C, FANCB, FAM50B (genes previously known to be associated with infertility) and ALG13, BEND2, BRWD3, DDX53, TAF4, FAM47B, FAM9B, FAM9C, MAGEB6, MAP3K15, RBMXL3, SSX3 and FMR1NB genes, which may be involved in spermatogenesis. DISCUSSION AND CONCLUSION In this study, we identified novel potential candidate NOA-associated genes in 29 individuals out of 39 azoospermic males. Note that in 5 out of 6 patients subjected previously to WES analysis, which did not disclose potentially causative variants, the WGS analysis was successful with NOA-associated gene findings.
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Affiliation(s)
| | - Tomasz Stokowy
- Scientific Computing GroupIT DivisionUniversity of BergenNorway
| | - Andrea Berman
- Department of Biological SciencesUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Marta Olszewska
- Institute of Human GeneticsPolish Academy of SciencesPoznanPoland
| | - Piotr Jedrzejczak
- Division of Infertility and Reproductive EndocrinologyDepartment of GynecologyObstetrics and Gynecological OncologyPoznan University of Medical SciencesPoznanPoland
| | | | - Adam Nowakowski
- Department of Urology and Urologic Oncology in St. Families HospitalPoznanPoland
| | | | - Alexander N. Yatsenko
- Department of OB/GYN and Reproductive SciencesSchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
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Huang J, Du F, Wang N. Development of a 4-miRNA prognostic signature for endometrial cancer. Medicine (Baltimore) 2022; 101:e30974. [PMID: 36254064 PMCID: PMC9575815 DOI: 10.1097/md.0000000000030974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
To develop an effective uterine corpus endometrial carcinoma (UCEC) risk assessment tool to monitor treatment outcomes. Limma package was used to analyze differentially expressed microRNAs (miRNAs) between UCEC tissues and normal tissues in the TCGA database. According to univariate Cox risk regression, least absolute shrinkage, and selection operator (LASSO) Cox analysis were performed to screen prognostic miRNAs and construct a risk scoring model. The prognostic performance of signature was evaluated by Kaplan-Meier and receiver operating characteristic. Multivariate Cox regression analysis was used to determine the independent prognostic factors of UCEC. Nomogram was constructed according to age, clinical stage, and risk score. A 4-miRNA signature based on miR-31-5p, miR-34a-5p, miR-26a-1-3p and miR-4772-3p was established. Risk scores of each patient were calculated by the 4-miRNA signature. After z-score, the patients were divided into high- and low-risk groups. The overall survival of high-risk patients was significantly shorter than that of low-risk patients, pointing to the high performance and independence of the 4-miRNA signature in predicting UCEC prognosis. The nomogram showed a high accuracy in predicting overall survival of UCEC patients. We developed a 4-miRNA signature that could effectively predict the prognosis of UCEC.
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Affiliation(s)
- Jiazhen Huang
- Department of Obstetrics and Gynecology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Furong Du
- State Development of Key Laboratory of Translational Medicine and Innovative Drug, Jiangsu Simcere Diagnostics Co., Ltd., Nanjing, Jiangsu, China
| | - Ning Wang
- Department of Obstetrics and Gynecology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
- *Correspondence: Ning Wang, Department of Obstetrics and Gynecology, The Second Hospital of Dalian Medical University, Dalian 116000, Liaoning, China (e-mail: )
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He S, Qiao J, Wang L, Yu L. A novel immune-related gene signature predicts the prognosis of hepatocellular carcinoma. Front Oncol 2022; 12:955192. [PMID: 36185203 PMCID: PMC9520462 DOI: 10.3389/fonc.2022.955192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/24/2022] [Indexed: 11/21/2022] Open
Abstract
Immune-related genes play a key role in regulating the cancer immune microenvironment, influencing the overall survival of patients with hepatocellular carcinoma (HCC). Along with the rapid development of immunotherapy, identifying immune-related genes with prognostic value in HCC has attracted increasing attention. Here, we aimed to develop a prognostic signature based on immune-related genes. By investigating the transcriptome landscape of 374 HCC and 160 non-HCC samples in silico, a total of 2251 differentially expressed genes were identified. Among which, 183 differentially expressed immune-related genes were subjected to a univariate Cox proportional hazard model to screen for genes with possible prognostic significance. A 10-gene prognostic signature, including HLA-G, S100A9, S100A10, DCK, CCL14, NRAS, EPO, IL1RN, GHR and RHOA, was generated employing a multivariate Cox proportional hazard model. Kaplan–Meier and Receiver Operator Characteristic (ROC) curves were used to evaluate the prognostic utility of the 10-gene signature. Moreover, the underlying mechanisms of these genes were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. According to the Tumor Immune Estimation Resource (TIMER) database, our prognostic signature was significantly associated with tumor-infiltrating B cells, CD4 T cells, dendritic cells, macrophages and neutrophils. Our study provides a novel prognostic signature based on immune-related genes associated with clinical outco mes of HCC.
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Wang Y, Huang X, Chen S, Jiang H, Rao H, Lu L, Wen F, Pei J. In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma. Curr Oncol 2022; 29:6573-6593. [PMID: 36135086 PMCID: PMC9497598 DOI: 10.3390/curroncol29090517] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 11/25/2022] Open
Abstract
Background: Colon adenocarcinoma (COAD) is the most common subtype of colon cancer, and cuproptosis is a recently newly defined form of cell death that plays an important role in the development of several malignant cancers. However, studies of cuproptosis-related lncRNAs (CRLs) involved in regulating colon adenocarcinoma are limited. The purpose of this study is to develop a new prognostic CRLs signature of colon adenocarcinoma and explore its underlying biological mechanism. Methods: In this study, we downloaded RNA-seq profiles, clinical data and tumor mutational burden (TMB) data from the TCGA database, identified cuproptosis-associated lncRNAs using univariate Cox, lasso regression analysis and multivariate Cox analysis, and constructed a prognostic model with risk score based on these lncRNAs. COAD patients were divided into high- and low-risk subgroups based on the risk score. Cox regression was also used to test whether they were independent prognostic factors. The accuracy of this prognostic model was further validated by receiver operating characteristic curve (ROC), C-index and Nomogram. In addition, the lncRNA/miRNA/mRNA competing endogenous RNA (ceRNA) network and protein−protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). Results: We constructed a prognostic model based on 15 cuproptosis-associated lncRNAs. The validation results showed that the risk score of the model (HR = 1.003, 95% CI = 1.001−1.004; p < 0.001) could serve as an independent prognostic factor with accurate and credible predictive power. The risk score had the highest AUC (0.793) among various factors such as risk score, stage, gender and age, also indicating that the model we constructed to predict patient survival was better than other clinical characteristics. Meanwhile, the possible biological mechanisms of colon adenocarcinoma were explored based on the lncRNA/miRNA/mRNA ceRNA network and PPI network constructed by WGCNA. Conclusion: The prognostic model based on 15 cuproptosis-related lncRNAs has accurate and reliable predictive power to effectively predict clinical outcomes in colon adenocarcinoma patients.
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Affiliation(s)
| | | | | | | | | | | | | | - Jin Pei
- Correspondence: (F.W.); (J.P.)
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20
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Wang L, Qiao C, Cao L, Cai S, Ma X, Song X, Jiang Q, Huang C, Wang J. Significance of HOXD transcription factors family in progression, migration and angiogenesis of cancer. Crit Rev Oncol Hematol 2022; 179:103809. [PMID: 36108961 DOI: 10.1016/j.critrevonc.2022.103809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 10/31/2022] Open
Abstract
The transcription factors (TFs) of the HOX family play significant roles during early embryonic development and cellular processes. They also play a key role in tumorigenesis as tumor oncogenes or suppressors. Furthermore, TFs of the HOXD geFIne cluster affect proliferation, migration, and invasion of tumors. Consequently, dysregulated activity of HOXD TFs has been linked to clinicopathological characteristics of cancer. HOXD TFs are regulated by non-coding RNAs and methylation of DNA on promoter and enhancer regions. In addition, HOXD genes modulate the biological function of cancer cells via the MEK and AKT signaling pathways, thus, making HOXD TFs, a suitable molecular marker for cancer prognosis and therapy. In this review, we summarized the roles of HOXD TFs in different cancers and highlighted its potential as a diagnostic and therapeutic target.
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Affiliation(s)
- Lumin Wang
- Gastroenterology department, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China; Institute of precision medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China
| | - Chenyang Qiao
- Gastroenterology department, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China
| | - Li Cao
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China
| | - Shuang Cai
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China
| | - Xiaoping Ma
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China
| | - Xinqiu Song
- Department of Cell Biology and Genetics, Medical College of Yan'an University, Yan'an, Shaanxi, PR China
| | - Qiuyu Jiang
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China
| | - Chen Huang
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China; Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, PR China.
| | - Jinhai Wang
- Gastroenterology department, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China; Institute of precision medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China.
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Identification of multi-omics biomarkers and construction of the novel prognostic model for hepatocellular carcinoma. Sci Rep 2022; 12:12084. [PMID: 35840618 PMCID: PMC9287549 DOI: 10.1038/s41598-022-16341-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 07/08/2022] [Indexed: 12/05/2022] Open
Abstract
Genome changes play a crucial role in carcinogenesis, and many biomarkers can be used as effective prognostic indicators in various tumors. Although previous studies have constructed many predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance is unsatisfactory. Because multi-omics data can more comprehensively reflect the biological phenomenon of disease, we hope to build a more accurate predictive model by multi-omics analysis. We use the TCGA to identify crucial biomarkers and construct prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. The performances of predictive models were evaluated and validated through survival analysis, Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Multiple mRNAs, lncRNAs, miRNAs, CNV genes, and SNPs were significantly associated with the prognosis of HCC. We constructed five single-omic models, and the mRNA and lncRNA models showed good performance with c-indexes over 0.70. The multi-omics model presented a robust predictive ability with a c-index over 0.77. This study identified many biomarkers that may help study underlying carcinogenesis mechanisms in HCC. In addition, we constructed multiple single-omic models and an integrated multi-omics model that may provide practical and reliable guides for prognosis assessment.
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Screening of Prognostic Markers for Hepatocellular Carcinoma Patients Based on Multichip Combined Analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:6881600. [PMID: 35872941 PMCID: PMC9303125 DOI: 10.1155/2022/6881600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/28/2022] [Indexed: 12/24/2022]
Abstract
Methods GSE (14520, 36376, 57957, 76427) datasets were accessed from GEO database. 55 differential mRNAs (DEGs) were obtained by differential analysis based on the datasets. GO and KEGG analysis results indicated that the DEGs were enriched in xenobiotic metabolic process and other pathways. Expression profiles and clinical data of TCGA-LIHC mRNAs were from TCGA database. We established a prognostic model of HCC through univariate and multivariate Cox risk regression analyses. ROC curve analysis was used to examine the prognostic model performance. GSEA analysis was performed between the high- and low-risk score sample groups. Results A 4-gene HCC prognostic model was constructed, in which the gene expressions correlated to HCC patients' survival. The AUC value presented 0.734 in the ROC analysis for the prognostic model. Conclusion The four-gene model could be introduced as an independent prognostic factors to assess HCC patients' survival status.
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Huang ZL, Xu B, Li TT, Xu YH, Huang XY, Huang XY. Integrative Analysis Identifies Cell-Type-Specific Genes Within Tumor Microenvironment as Prognostic Indicators in Hepatocellular Carcinoma. Front Oncol 2022; 12:878923. [PMID: 35707353 PMCID: PMC9190278 DOI: 10.3389/fonc.2022.878923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/13/2022] [Indexed: 11/13/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, but effective early detection and prognostication methods are lacking. Methods The Cox regression model was built to stratify the HCC patients. The single-cell RNA sequencing data analysis and gene set enrichment analysis were employed to investigate the biological function of identified markers. PLCB1 gain- or loss-of-function experiments were performed, and obtained HCC samples were analyzed using quantitative real-time PCR and immunohistochemistry assay to validate the biological function of identified markers. Results In this study, we developed a model using optimized markers for HCC recurrence prediction. Specifically, we screened out 8 genes through a series of data analyses, and built a multivariable Cox model based on their expression. The risk stratifications using the Eight-Gene Cox (EGC) model were closely associated with the recurrence-free survivals (RFS) in both training and three validation cohorts. We further demonstrated that this risk stratification could serve as an independent predictor in predicting HCC recurrence, and that the EGC model could outperform other models. Moreover, we also investigated the cell-type-specific expression patterns of the eight recurrence-related genes in tumor microenvironment using single-cell RNA sequencing data, and interpreted their functional roles from correlation and gene set enrichment analyses, in vitro and in vivo experiments. Particularly, PLCB1 and SLC22A7 were predominantly expressed in malignant cells, and they were predicted to promote angiogenesis and to help maintain normal metabolism in liver, respectively. In contrast, both FASLG and IL2RB were specifically expressed in T cells, and were highly correlated with T cell marker genes, suggesting that these two genes might assist in maintaining normal function of T cell-mediated immune response in tumor tissues. Conclusion In conclusion, the EGC model and eight identified marker genes could not only facilitate the accurate prediction of HCC recurrence, but also improve our understanding of the mechanisms behind HCC recurrence.
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Affiliation(s)
- Zi-Li Huang
- Department of General Surgery, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China.,Department of Radiology, Xuhui District Central Hospital of Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bin Xu
- Department of General Surgery, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China.,Department of General Surgery, The Tenth People's Hospital of Tongji University, Shanghai, China
| | - Ting-Ting Li
- Department of Infectious Disease, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yong-Hua Xu
- Department of Radiology, Xuhui District Central Hospital of Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xin-Yu Huang
- Department of General Surgery, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Xiu-Yan Huang
- Department of General Surgery, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China
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Chen Y, Huang M, Zhu J, Xu L, Cheng W, Lu X, Yan F. Identification of a DNA Damage Response and Repair-Related Gene-Pair Signature for Prognosis Stratification Analysis in Hepatocellular Carcinoma. Front Pharmacol 2022; 13:857060. [PMID: 35496321 PMCID: PMC9038539 DOI: 10.3389/fphar.2022.857060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 02/24/2022] [Indexed: 12/12/2022] Open
Abstract
Background: Nowadays, although the cause of hepatocellular carcinoma (HCC) mortality and recurrence remains at a high level, the 5-year survival rate is still very low. The DNA damage response and repair (DDR) pathway may affect HCC patients’ survival by influencing tumor development and therapeutic response. It is necessary to identify a prognostic DDR-related gene signature to predict the outcome of patients. Methods: Level 3 mRNA expression and clinical information were extracted from the TCGA website. The GSE14520 datasets, ICGC-LIRI datasets, and a Chinese HCC cohort were served as validation sets. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were performed to construct the DDR-related gene pair (DRGP) signature. Kaplan–Meier survival curves and time-dependent receiver operating characteristic (ROC) analysis curves were calculated to determine the predictive ability of this prognostic model. Then, a prognostic nomogram was established to help clinical management. We investigated the difference in biological processes between HRisk and LRisk by conducting several enrichment analyses. The TIDE algorithm and R package “pRRophetic” were applied to estimate the immunotherapeutic and chemotherapeutic response. Results: We constructed the prognostic signature based on 23 DDR-related gene pairs. The patients in the training datasets were divided into HRisk and LRisk groups at median cut-off. The HRisk group had significantly poorer OS than the LRisk group, and the signature was an independent prognostic indicator in HCC. Furthermore, a nomogram of the riskscore combined with TNM stage was constructed and detected by the calibration curve and decision curve. The LRisk group was associated with higher expression of HBV oncoproteins and metabolism pathways, while DDR-relevant pathways and cell cycle process were enriched in the HRisk group. Moreover, patients in the LRisk group may be more beneficial from immunotherapy. We also found that TP53 gene was more frequently mutated in the HRisk group. As for chemotherapeutic drugs commonly used in HCC, the HRisk group was highly sensitive to 5-fluorouracil, while the LRisk group presented with a significantly higher response to gefitinib and gemcitabine. Conclusion: Overall, we developed a novel DDR-related gene pair signature and nomogram to assist in predicting survival outcomes and clinical treatment of HCC patients. It also helps understand the underlying mechanisms of different DDR patterns in HCC.
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Affiliation(s)
- Yi Chen
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Mengjia Huang
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Junkai Zhu
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Li Xu
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Wenxuan Cheng
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Xiaofan Lu
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Fangrong Yan
- State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
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Wu F, Du Y, Hou X, Cheng W. A prognostic model for oral squamous cell carcinoma using 7 genes related to tumor mutational burden. BMC Oral Health 2022; 22:152. [PMID: 35488327 PMCID: PMC9052477 DOI: 10.1186/s12903-022-02193-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 04/14/2022] [Indexed: 02/06/2023] Open
Abstract
Background Oral squamous cell carcinoma (OSCC) is a rising problem in global public health. The traditional physical and imageological examinations are invasive and radioactive. There is a need for less harmful new biomarkers. Tumor mutational burden (TMB) is a novel prognostic biomarker for various cancers. We intended to explore the relationship between TMB-related genes and the prognosis of OSCC and to construct a prognostic model. Methods TMB-related differential expressed genes (DEGs) were screened by differential analysis and optimized via the univariate Cox and LASSO Cox analyses. Risk Score model was constructed by expression values of screened genes multiplying coefficient of LASSO Cox. Results Seven TMB-related DEGs (CTSG, COL6A5, GRIA3, CCL21, ZNF662, TDRD5 and GSDMB) were screened. Patients in high-risk group (Risk Score > − 0.684511507) had worse prognosis compared to the low-risk group (Risk Score < − 0.684511507). Survival rates of patients in the high-risk group were lower in the gender, age and degrees of differentiation subgroups compared to the low-risk group. Conclusions The Risk Score model constructed by 7 TMB-related genes may be a reliable biomarker for predicting the prognosis of OSCC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12903-022-02193-3.
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Affiliation(s)
- Fei Wu
- Department I of Oral Comprehensive Outpatient, Yantai Stomatological Hospital of Binzhou Medical University, Yantai, 264001, Shandong, China
| | - Yuanyuan Du
- Department of Dental Implant, Yantai Stomatological Hospital of Binzhou Medical University, Yantai, 264001, Shandong, China
| | - Xiujuan Hou
- Department I of Oral Comprehensive Outpatient, Yantai Stomatological Hospital of Binzhou Medical University, Yantai, 264001, Shandong, China
| | - Wei Cheng
- Department of Dental Prosthodontics, Yantai Stomatological Hospital of Binzhou Medical University, No. 142 Zhifu District, Yantai, 264001, Shandong, China.
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Li X, Zhang Z, Liu M, Fu X, A J, Chen G, Wu S, Dong JT. Establishment of a lncRNA-Based Prognostic Gene Signature Associated With Altered Immune Responses in HCC. Front Immunol 2022; 13:880288. [PMID: 35572559 PMCID: PMC9097819 DOI: 10.3389/fimmu.2022.880288] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 04/05/2022] [Indexed: 01/01/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a common malignancy with higher mortality, and means are urgently needed to improve the prognosis. T cell exclusion (TCE) plays a pivotal role in immune evasion, and lncRNAs represent a large group of tumor development and progression modulators. Using the TCGA HCC dataset (n=374), we identified 2752 differentially expressed and 702 TCE-associated lncRNAs, of which 336 were in both groups. As identified using the univariate Cox regression analysis, those associated with overall survival (OS) were subjected to the LASSO-COX regression analysis to develop a prognosis signature. The model, which consisted of 11 lncRNAs and was named 11LNCPS for 11-lncRNA prognosis signature, was validated and performed better than two previous models. In addition to OS and TCE, higher 11LNCPS scores had a significant correlation with reduced infiltrations of CD8+ T cells and dendritic cells (DCs) and decreased infiltrations of Th1, Th2, and pro B cells. As expected, these infiltration alterations were significantly associated with worse OS in HCC. Analysis of published data indicates that HCCs with higher 11LNCPS scores were transcriptomically similar to those that responded better to PDL1 inhibitor. Of the 11LNCPS lncRNAs, LINC01134 and AC116025.2 seem more crucial, as their upregulations affected more immune cell types' infiltrations and were significantly associated with TCE, worse OS, and compromised immune responses in HCC. LncRNAs in the 11LNCPS impacted many cancer-associated biological processes and signaling pathways, particularly those involved in immune function and metabolism. The 11LNCPS should be useful for predicting prognosis and immune responses in HCC.
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Affiliation(s)
- Xiawei Li
- Department of Genetics and Cell Biology, College of Life Sciences, Nankai University, Tianjin, China
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Zhiqian Zhang
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Mingcheng Liu
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Xing Fu
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Jun A
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Guoan Chen
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Shian Wu
- Department of Genetics and Cell Biology, College of Life Sciences, Nankai University, Tianjin, China
| | - Jin-Tang Dong
- Laboratory Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
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Zheng Y, Wu R, Wang X, Yin C. Identification of a Four-Gene Metabolic Signature to Evaluate the Prognosis of Colon Adenocarcinoma Patients. Front Public Health 2022; 10:860381. [PMID: 35462848 PMCID: PMC9021388 DOI: 10.3389/fpubh.2022.860381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 03/14/2022] [Indexed: 11/24/2022] Open
Abstract
Background Colon adenocarcinoma (COAD) is a highly heterogeneous disease, thus making prognostic predictions uniquely challenging. Metabolic reprogramming is emerging as a novel cancer hallmark that may serve as the basis for more effective prognosis strategies. Methods The mRNA expression profiles and relevant clinical information of COAD patients were downloaded from public resources. The least absolute shrinkage and selection operator (LASSO) Cox regression model was exploited to establish a prognostic model, which was performed to gain risk scores for multiple genes in The Cancer Genome Atlas (TCGA) COAD patients and validated in GSE39582 cohort. A forest plot and nomogram were constructed to visualize the data. The clinical nomogram was calibrated using a calibration curve coupled with decision curve analysis (DCA). The association between the model genes' expression and six types of infiltrating immunocytes was evaluated. Apoptosis, cell cycle assays and cell transfection experiments were performed. Results Univariate Cox regression analysis results indicated that ten differentially expressed genes (DEGs) were related with disease-free survival (DFS) (P-value< 0.01). A four-gene signature was developed to classify patients into high- and low-risk groups. And patients with high-risk exhibited obviously lower DFS in the training and validation cohorts (P < 0.05). The risk score was an independent parameter of the multivariate Cox regression analyses of DFS in the training cohort (HR > 1, P-value< 0.001). The same findings for overall survival (OS) were obtained GO enrichment analysis revealed several metabolic pathways with significant DEGs enrichment, G1/S transition of mitotic cell cycle, CD8+ T-cells and B-cells may be significantly associated with COAD in DFS and OS. These findings demonstrate that si-FUT1 inhibited cell migration and facilitated apoptosis in COAD. Conclusion This research reveals that a novel metabolic gene signature could be used to evaluate the prognosis of COAD, and targeting metabolic pathways may serve as a therapeutic alternative.
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Affiliation(s)
- Yang Zheng
- Graduate School, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Institute of Integrative Medicine for Acute Abdominal Diseases, Tianjin Nankai Hospital, Tianjin, China
| | - Rilige Wu
- College of Science, Beijing University of Posts and Telecommunications, Beijing, China
| | - Ximo Wang
- Graduate School, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Institute of Integrative Medicine for Acute Abdominal Diseases, Tianjin Nankai Hospital, Tianjin, China
- Tianjin Haihe Hospital, Tianjin, China
| | - Chengliang Yin
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
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Zhong X, Yu X, Chang H. Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma. Front Oncol 2022; 12:830362. [PMID: 35359370 PMCID: PMC8960170 DOI: 10.3389/fonc.2022.830362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/10/2022] [Indexed: 12/12/2022] Open
Abstract
Background The initiation and progression of tumors were due to variations of gene sets rather than individual genes. This study aimed to identify novel biomarkers based on gene set variation analysis (GSVA) in hepatocellular carcinoma. Methods The activities of 50 hallmark pathways were scored in three microarray datasets with paired samples with GSVA, and differential analysis was performed with the limma R package. Unsupervised clustering was conducted to determine subtypes with the ConsensusClusterPlus R package in the TCGA-LIHC (n = 329) and LIRI-JP (n = 232) cohorts. Differentially expressed genes among subtypes were identified as initial variables. Then, we used TCGA-LIHC as the training set and LIRI-JP as the validation set. A six-gene model calculating the risk scores of patients was integrated with the least absolute shrinkage and selection operator (LASSO) and stepwise regression analyses. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were performed to assess predictive performances. Multivariate Cox regression analyses were implemented to select independent prognostic factors, and a prognostic nomogram was integrated. Moreover, the diagnostic values of six genes were explored with the ROC curves and immunohistochemistry. Results Patients could be separated into two subtypes with different prognoses in both cohorts based on the identified differential hallmark pathways. Six prognostic genes (ASF1A, CENPA, LDHA, PSMB2, SRPRB, UCK2) were included in the risk score signature, which was demonstrated to be an independent prognostic factor. A nomogram including 540 patients was further integrated and well-calibrated. ROC analyses in the five cohorts and immunohistochemistry experiments in solid tissues indicated that CENPA and UCK2 exhibited high and robust diagnostic values. Conclusions Our study explored a promising prognostic nomogram and diagnostic biomarkers in hepatocellular carcinoma.
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Affiliation(s)
- Xiongdong Zhong
- Department of Cardiothoracic Surgery, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Zhuhai, China
| | - Xianchang Yu
- Department of Cardiothoracic Surgery, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Zhuhai, China
| | - Hao Chang
- Department of Protein Modification and Cancer Research, Hanyu Biomed Center Beijing, Beijing, China
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Yang Y, Gao L, Chen J, Xiao W, Liu R, Kan H. Lamin B1 is a potential therapeutic target and prognostic biomarker for hepatocellular carcinoma. Bioengineered 2022; 13:9211-9231. [PMID: 35436411 PMCID: PMC9161935 DOI: 10.1080/21655979.2022.2057896] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 03/17/2022] [Accepted: 03/21/2022] [Indexed: 12/01/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is an aggressive malignancy. Previous studies have found that lamin B1 (LMNB1) contributes to the development of human cancers. However, the biological functions and prognostic values of LMNB1 in HCC have not been adequately elucidated. In our present research, the expression pattern of LMNB1 was analyzed. The prognostic values of LMNB1 were evaluated by Kaplan-Meier survival analysis and Cox proportional hazards regression analysis. The effects of LMNB1 on HCC progression were assessed by Cell Counting Kit-8 (CCK-8), colony formation, wound healing, Transwell and in vivo xenograft assays. The mechanisms of LMNB1 in HCC progression were elucidated by gene set enrichment analysis (GSEA) and loss-of-function assays. Besides, a nomogram for predicting overall survival (OS) was constructed. The results demonstrated that LMNB1 was overexpressed in HCC and that increased LMNB1 expression predicted a dismal prognosis. Further experiments showed that LMNB1 facilitated cell proliferation and metastasis in HCC. Functional enrichment analysis revealed that LMNB1 modulated metastasis-associated biological functions such as focal adhesion, extracellular matrix, cell junctions and cell adhesion. Mechanistically, we revealed that LMNB1 promoted HCC progression by regulating the phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) pathways. Moreover, incorporating LMNB1, Ki67 and Barcelona Clinic Liver Cancer (BCLC) stage into a nomogram showed better predictive accuracy than the Tumor-Node-Metastasis (TNM) stage and BCLC stage. In conclusion, LMNB1 may serve as an effective therapeutic target as well as a reliable prognostic biomarker for HCC.
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Affiliation(s)
- Yongyu Yang
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Lei Gao
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Junzhang Chen
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Wang Xiao
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Ruoqi Liu
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Heping Kan
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
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A Novel Gene Signature Based on CDC20 and FCN3 for Prediction of Prognosis and Immune Features in Patients with Hepatocellular Carcinoma. J Immunol Res 2022; 2022:9117205. [PMID: 35402624 PMCID: PMC8986430 DOI: 10.1155/2022/9117205] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 03/02/2022] [Accepted: 03/05/2022] [Indexed: 11/18/2022] Open
Abstract
Long-term survivals of patients with hepatocellular carcinoma (HCC) remain unfavorable, which is largely attributed to active carcinogenesis. Growing studies have suggested that the reliable gene signature could act as an independent prognosis factor for HCC patients. We tried to screen the survival-related genes and develop a prognostic prediction model for HCC patients based on the expression profiles of the critical survival-related genes. In this study, we analyzed TCGA datasets and identified 280 genes with differential expressions (125 increased genes and 155 reduced genes). We analyzed the prognosis value of the top 10 dysregulated genes in HCC patients and identified three critical genes, including FCN3, CDC20, and E2F1, which were confirmed to be associated with long-term survival in both TCGA and ICGC datasets. The results of the LASSO model screened CDC20 and FCN3 for the development of the prognostic model. The CDC20 expression was distinctly increased in HCC specimens, while the FCN3 expression was distinctly decreased in HCC. At a suitable cutoff, patients were divided into low-risk and high-risk groups. Survival assays revealed that patients in high-risk groups exhibited a shorter overall survival than those in low-risk groups. Finally, we examine the relationships between risk score and immune infiltration abundance in HCC and observed that risk score was positively correlated with infiltration degree of B cells, T cell CD4+ cells, neutrophil, macrophage, and myeloid dendritic cells. Overall, we identified three critical survival-related genes and used CDC20 and FCN3 to develop a novel model for predicting outcomes and immune landscapes for patients with HCC. The above three genes also have a high potential for targeted cancer therapy of patients with HCC.
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Li J, Tao Y, Cong H, Zhu E, Cai T. Predicting liver cancers using skewed epidemiological data. Artif Intell Med 2022; 124:102234. [DOI: 10.1016/j.artmed.2021.102234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 11/26/2021] [Accepted: 12/21/2021] [Indexed: 01/04/2023]
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Song L, Li Q, Lu Y, Feng X, Yang R, Wang S. Cancer Progression Mediated by CAFs Relating to HCC and Identification of Genetic Characteristics Influencing Prognosis. JOURNAL OF ONCOLOGY 2022; 2022:2495361. [PMID: 36299502 PMCID: PMC9590114 DOI: 10.1155/2022/2495361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/09/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is one of the most common malignancies, and although there are several treatment options, the overall results are not satisfactory. Cancer-associated fibroblasts (CAFs) can promote cancer progression through various mechanisms. METHODS HCC-associated mRNA data were sourced from The Cancer Genome Atlas database (TCGA) and International Cancer Genome Consortium (ICGC) database. First, the differentially expressed CAF-related genes (CAF-DEGs) were acquired by difference analysis and weighted gene coexpression network analysis (WGCNA). Moreover, a CAF-related risk model was built by Cox analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were utilized to evaluate the validity of this risk model. Furthermore, enrichment analysis of differentially expressed genes (DEGs) between the high- and low-risk groups was executed to explore the functions relevant to the risk model. Furthermore, this study compared the differences in immune infiltration, immunotherapy, and drug sensitivity between the high- and low-risk groups. Finally, we verified the mRNA expression levels of selected prognostic genes by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS 107 CAF-DEGs were identified in the HCC samples, and five prognosis-related genes (ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1) were obtained by Cox analysis and utilized to build a CAF-related risk model. K-M analysis illustrated a low survival in the high-risk group, and ROC curves revealed that the risk model could accurately predict the 1-, 3-, and 5-year overall survival (OS) of HCC patients. In addition, Cox analysis demonstrated that the risk score was an independent prognostic factor. Enrichment analysis illustrated that DEGs between the high- and low-risk groups were related to immune response, amino acid metabolism, and fatty acid metabolism. Furthermore, risk scores were correlated with the tumor microenvironment, CAF scores, and TIDE scores, and CAF-related marker genes were positively correlated with all five model genes. Notably, the risk model was relevant to the sensitivity of chemotherapy drugs. Finally, the results of qRT-PCR demonstrated that the expression levels of 5 model genes were in accordance with the analysis. CONCLUSION A CAF-related risk model based on ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1 was built and could be utilized to predict the prognosis and treatment of HCC.
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Affiliation(s)
- Li Song
- Academy of Advanced Interdisciplinary Studies, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong Province 250353, China
| | - Qiankun Li
- Department of Tissue Repair and Regeneration, The First Medical Center of Chinese PLA General Hospital, Beijing, Beijing 250353, China
| | - Yao Lu
- Department of Tissue Repair and Regeneration, The First Medical Center of Chinese PLA General Hospital, Beijing, Beijing 250353, China
| | - Xianqi Feng
- Academy of Advanced Interdisciplinary Studies, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong Province 250353, China
| | - Rungong Yang
- Department of Tissue Repair and Regeneration, The First Medical Center of Chinese PLA General Hospital, Beijing, Beijing 250353, China
| | - Shouguo Wang
- Academy of Advanced Interdisciplinary Studies, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong Province 250353, China
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Niu Z, Xu Y, Li Y, Chen Y, Han Y. Construction and validation of a novel pyroptosis-related signature to predict prognosis in patients with cutaneous melanoma. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:688-706. [PMID: 34903008 DOI: 10.3934/mbe.2022031] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Skin cutaneous melanoma (SKCM) is one of the most malignant skin cancers and remains a health concern worldwide. Pyroptosis is a newly recognized form of programmed cell death and plays a vital role in cancer progression. We aim to construct a prognostic model for SKCM patients based on pyroptosis-related genes (PRGs). SKCM patients from The Cancer Genome Atlas (TCGA) were divided into training and validation cohorts. We used GSE65904 downloaded from GEO database as an external validation cohort. We performed Cox regression and the least absolute shrinkage and selection operator (LASSO) regression to identify prognostic genes and built a risk score. Patients were divided into high- and low-risk groups based on the risk score. Differently expressed genes (DEGs), immune cell infiltration and immune-related pathways activation were compared between the two groups. We established a model containing 4 PRGs, i.e., GSDMA, GSDMC, AIM2 and NOD2. The overall survival (OS) time was significantly different between the 2 groups. The risk score was an independent predictor for prognosis in both the uni- and multi-variable Cox regressions. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that DEGs were enriched in immune-related pathways. Most types of immune cells were highly expressed in the low risk group. All immune pathways were significantly up-regulated in the low-risk group. In addition, low-risk patients had a better response to immune checkpoint inhibitors. Our novel pyroptosis-related gene signature could predict the prognosis of SKCM patients and their response to immune checkpoint inhibitors.
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Affiliation(s)
- Zehao Niu
- Medical School of Chinese PLA, Beijing 100853, China
- Department of Plastic and Reconstructive Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Yujian Xu
- Department of Plastic and Reconstructive Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Yan Li
- Medical School of Chinese PLA, Beijing 100853, China
- Department of Plastic and Reconstructive Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Youbai Chen
- Department of Plastic and Reconstructive Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Yan Han
- Department of Plastic and Reconstructive Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
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Identification of MCM4 as a Prognostic Marker of Hepatocellular Carcinoma. BIOMED RESEARCH INTERNATIONAL 2021; 2021:7479326. [PMID: 34961841 PMCID: PMC8710152 DOI: 10.1155/2021/7479326] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 11/09/2021] [Accepted: 11/23/2021] [Indexed: 11/17/2022]
Abstract
Methods MCM4 expression difference in HCC were analyzed from TCGA and GEO data and verified by real-time PCR and western blot. ROC curve was used to analyze the diagnostic value of MCM4 and AFP. Additionally, the relationship between MCM4 and stage or nodal metastasis status or grade or age in TCGA cohort with HCC was observed from the UALCAN website. The univariate and multivariate Cox and functional analyses were done to explore the prognostic value of MCM4 in TCGA cohort. Results It was found that MCM4 was significantly highly expressed in HCC tissues from TCGA, GEO, and experimental data. Furthermore, ROC curve analysis showed that MCM4 was superior to be a diagnostic biomarker than AFP from TCGA (AUCMCM4 = 0.9461, AUCAFP = 0.7056) and GEO (GSE19665: AUCMCM4 = 0.8800, AUCAFP = 0.5100; GSE64041 AUCMCM4 = 0.8038, AUCAFP = 0.6304). AUC of MCM4 from real-time PCR result in 60 pairs of HCC and adjacent tissues was 0.7172, demonstrating the prediction value of MCM4. Besides, different expression tendencies of MCM4 among different stages or nodal metastasis status or grade or age were observed from the UALCAN website. In addition, multiROC analysis showed the advantage of MCM4 as a survival prediction at 1, 3, and 5 years with the higher AUC at 0.69 of 1 year, 0.65 of 3 years, and 0.61 of 5 years. It was shown that MCM4 was independently associated with OS in univariate and multivariate Cox analysis. And GSEA displayed that MCM4 was highly enriched in KEGG_CELL_CYCLE signaling pathway following higher correlation positively with CDC6, PLK1, CRC1, and BUB1B in HCC. Conclusion MCM4 might be a potential biomarker in guiding the prognostic status of HCC patients.
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Guo DZ, Huang A, Wang YP, Cao Y, Fan J, Yang XR, Zhou J. Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma. J Clin Transl Hepatol 2021; 9:898-908. [PMID: 34966653 PMCID: PMC8666363 DOI: 10.14218/jcth.2020.00152] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 03/27/2021] [Accepted: 04/11/2021] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND AND AIMS The overall survival (OS) of hepatocellular carcinoma (HCC) remains dismal. Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision. This study aimed to develop a prognostic gene model for HCC. METHODS GSE14520 was retrieved as a training set to identify differential expressed genes (DEGs) between tumor and adjacent liver tissues in HCC patients with different OS. A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model. The area under the receiver operating characteristic curve (AUC) and hazard ratio (HR) of the model for OS were calculated. A model-based nomogram was established and verified. RESULTS In the training set, differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation. After univariate Cox and LASSO regression, eight genes (LPCAT1, DHRS1, SORBS2, ALDH5A1, SULT1C2, SPP1, HEY1 and GOLM1) were selected to build the prognostic model. The AUC for 1-, 3- and 5-year OS were 0.779, 0.736, 0.754 in training set and 0.693, 0.689, 0.693 in the TCGA-LIHC validation set, respectively. The AUC for 1- and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set. Multivariate analysis confirmed the model was an independent prognostic factor (training set: HR=4.422, p<0.001; TCGA-LIHC validation set: HR=2.561, p<0.001; ICGC-LIRI validation set: HR=3.931, p<0.001). Furthermore, a nomogram combining the model and AJCC stage was established and validated, showing increased OS predictive efficacy compared with the prognostic model (p=0.035) or AJCC stage (p<0.001). CONCLUSIONS Our eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.
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Affiliation(s)
- De-Zhen Guo
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ao Huang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yu-Peng Wang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ya Cao
- Cancer Research Institute, Xiangya School of Medicine, Central South University; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jia Fan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
- Institute of Biomedical Sciences, Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Xin-Rong Yang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
- Correspondence to: Jian Zhou and Xin-Rong Yang, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai 200032, China. ORCID: https://orcid.org/0000-0002-2118-1117 (JZ), https://orcid.org/0000-0002-2716-9338 (XRY). Tel: +86-21-64041990, Fax: +86-21-64037181, E-mail: (JZ) or (XRY)
| | - Jian Zhou
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education; Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China
- Institute of Biomedical Sciences, Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
- Correspondence to: Jian Zhou and Xin-Rong Yang, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai 200032, China. ORCID: https://orcid.org/0000-0002-2118-1117 (JZ), https://orcid.org/0000-0002-2716-9338 (XRY). Tel: +86-21-64041990, Fax: +86-21-64037181, E-mail: (JZ) or (XRY)
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Zhao YJ, Wu LY, Pang JS, Liao W, Chen YJ, He Y, Yang H. Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma. Bioengineered 2021; 12:3978-3992. [PMID: 34288818 PMCID: PMC8806902 DOI: 10.1080/21655979.2021.1948949] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/23/2021] [Indexed: 01/04/2023] Open
Abstract
Splicing factors (SFs) have been increasingly documented to perturb the genome of cancers. However, little is known about the alterations of SFs in hepatocellular carcinoma (HCC). This study comprehensively delineated the genomic and epigenomic characteristics of 404 SFs in HCC based on the multi-omics data from the Cancer Genome Atlas database. The analysis revealed several clinically relevant SFs that could be effective biomarkers for monitoring the onset and prognosis of HCC (such as, HSPB1, DDX39A, and NELFE, which were the three most significant clinically relevant SFs). Functional enrichment analysis of these indicators showed the enrichment of pathways related to splicing and mRNA processes. Furthermore, the study found that SF copy number variation is common in HCC and could be a typical characteristic of hepato-carcinogenesis; the complex expression regulation of SFs was significantly affected by copy number variant and methylation. Several SFs with significant mutation patterns were identified (such as, RNF213, SF3B1, SPEN, NOVA1, and EEF1A1), and the potential regulatory network of SFs was constructed to identify their potential mechanisms for regulating clinically relevant alternative splicing events. Therefore, this study established a foundation to uncover the broad molecular spectrum of SFs for future functional and therapeutic studies of HCC.
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Affiliation(s)
- Yu-jia Zhao
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Lin-Yong Wu
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Jin-shu Pang
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Wei Liao
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Yu-ji Chen
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Yun He
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
| | - Hong Yang
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China
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Shuai C, Yuan F, Liu Y, Wang C, Wang J, He H. Estrogen receptor-positive breast cancer survival prediction and analysis of resistance-related genes introduction. PeerJ 2021; 9:e12202. [PMID: 34760348 PMCID: PMC8555508 DOI: 10.7717/peerj.12202] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 09/02/2021] [Indexed: 12/20/2022] Open
Abstract
Background In recent years, ER+ and HER2- breast cancer of adjuvant therapy has made great progress, including chemotherapy and endocrine therapy. We found that the responsiveness of breast cancer treatment was related to the prognosis of patients. However, reliable prognostic signatures based on ER+ and HER2- breast cancer and drug resistance-related prognostic markers have not been well confirmed, This study in amied to establish a drug resistance-related gene signature for risk stratification in ER+ and HER2- breast cancer. Methods We used the data from The Cancer Genoma Atlas (TCGA) breast cancer dataset and gene expression database (Gene Expression Omnibus, GEO), constructed a risk profile based on four drug resistance-related genes, and developed a nomogram to predict the survival of patients with I-III ER+ and HER2- breast cancer. At the same time, we analyzed the relationship between immune infiltration and the expression of these four genes or risk groups. Results Four drug resistance genes (AMIGO2, LGALS3BP, SCUBE2 and WLS) were found to be promising tools for ER+ and HER2- breast cancer risk stratification. Then, the nomogram, which combines genetic characteristics with known risk factors, produced better performance and net benefits in calibration and decision curve analysis. Similar results were validated in three separate GEO cohorts. All of these results showed that the model can be used as a prognostic classifier for clinical decision-making, individual prediction and treatment, as well as follow-up.
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Affiliation(s)
- Chen Shuai
- Department of Breast and Thyroid Surgery, Yiyang Central Hospital, Yiyang, Hunan, China
| | - Fengyan Yuan
- Hunan Normal University of Medicine, Changsha, Hunan, China
| | - Yu Liu
- Hunan Provincial People's Hospital, Changsha, Hunan, China
| | - Chengchen Wang
- Hunan Provincial People's Hospital, Changsha, Hunan, China
| | - Jiansong Wang
- Hunan Provincial People's Hospital, Changsha, Hunan, China
| | - Hongye He
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
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Luo D, Zhao D, Zhang M, Hu C, Li H, Zhang S, Chen X, Huttad L, Li B, Jin C, Lin C, Han B. Alternative Splicing-Based Differences Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: Genes, Immune Microenvironment, and Survival Prognosis. Front Oncol 2021; 11:731993. [PMID: 34760694 PMCID: PMC8574058 DOI: 10.3389/fonc.2021.731993] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/29/2021] [Indexed: 12/17/2022] Open
Abstract
Alternative splicing (AS) event is a novel biomarker of tumor tumorigenesis and progression. However, the comprehensive analysis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) is lacking. Differentially expressed analysis was used to identify the differentially expressed alternative splicing (DEAS) events between HCC or ICC tissues and their normal tissues. The correlation between DEAS events and functional analyses or immune features was evaluated. The cluster analysis based on DEAS can accurately reflect the differences in the immune microenvironment between HCC and ICC. Forty-five immune checkpoints and 23 immune features were considered statistically significant in HCC, while only seven immune checkpoints and one immune feature in ICC. Then, the prognostic value of DEAS events was studied, and two transcripts with different basic cell functions (proliferation, cell cycle, invasion, and migration) were produced by ADHFE1 through alternative splicing. Moreover, four nomograms were established in conjunction with relevant clinicopathological factors. Finally, we found two most significant splicing factors and further showed their protein crystal structure. The joint analysis of the AS events in HCC and ICC revealed novel insights into immune features and clinical prognosis, which might provide positive implications in HCC and ICC treatment.
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Affiliation(s)
- Dingan Luo
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Deze Zhao
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Mao Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Chuan Hu
- Medical College, Qingdao University, Qingdao, China
| | - Haoran Li
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shun Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiaowu Chen
- Asian Liver Center, Department of Surgery, Medical School of Stanford University, Stanford, CA, United States
| | - Lakshmi Huttad
- Asian Liver Center, Department of Surgery, Medical School of Stanford University, Stanford, CA, United States
| | - Bailiang Li
- Department of Radiation Oncology, Medical School of Stanford University, Stanford, CA, United States
| | - Cheng Jin
- Department of Radiation Oncology, Medical School of Stanford University, Stanford, CA, United States
| | - Changwei Lin
- Department of Gastrointestinal Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Bing Han
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
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Shen J, Liu T, Lv J, Xu S. Identification of an Immune-Related Prognostic Gene CLEC5A Based on Immune Microenvironment and Risk Modeling of Ovarian Cancer. Front Cell Dev Biol 2021; 9:746932. [PMID: 34712666 PMCID: PMC8547616 DOI: 10.3389/fcell.2021.746932] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 09/16/2021] [Indexed: 12/31/2022] Open
Abstract
Objective: To understand the immune characteristics of the ovarian cancer (OC) microenvironment and explore the differences of immune-related molecules and cells to establish an effective risk model and identify the molecules that significantly affected the immune response of OC, to help guide the diagnosis. Methods: First, we calculate the TMEscore which reflects the immune microenvironment, and then analyze the molecular differences between patients with different immune characteristics, and determine the prognostic genes. Then, the risk model was established by least absolute shrinkage and selection operator (LASSO) analysis and combined with clinical data into a nomogram for diagnosis and prediction. Subsequently, the potential gene CLEC5A influencing the immune response of OC was identified from the prognostic genes by integrative immune-stromal analysis. The genomic alteration was explored based on copy number variant (CNV) and somatic mutation data. Results: TMEscore was a prognostic indicator of OC. The prognosis of patients with high TMEscore was better. The risk model based on immune characteristics was a reliable index to predict the prognosis of patients, and the nomogram could comprehensively evaluate the prognosis of patients. Besides, CLEC5A was closely related to the abundance of immune cells, immune response, and the expression of immune checkpoints in the OC microenvironment. OC cells with high expression of CLEC5A increased the polarization of M2 macrophages. CLEC5A expression was significantly associated with TTN and CDK12 mutations and affected the copy number of tumor progression and immune-related genes. Conclusion: The study of immune characteristics in the OC microenvironment and the risk model can reveal the factors affecting the prognosis and guide the clinical hierarchical treatment. CLEC5A can be used as a potential key gene affecting the immune microenvironment remodeling of OC, which provides a new perspective for improving the effect of OC immunotherapy.
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Affiliation(s)
- Jiacheng Shen
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Tingwei Liu
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Jia Lv
- Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Shaohua Xu
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
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Zhu Z, Song M, Li W, Li M, Chen S, Chen B. Identification, Verification and Pathway Enrichment Analysis of Prognosis-Related Immune Genes in Patients With Hepatocellular Carcinoma. Front Oncol 2021; 11:695001. [PMID: 34616672 PMCID: PMC8488301 DOI: 10.3389/fonc.2021.695001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 09/02/2021] [Indexed: 11/21/2022] Open
Abstract
Hepatocellular carcinoma is a common malignant tumor with poor prognosis, poor treatment effect, and lack of effective biomarkers. In this study, bioinformatics analysis of immune-related genes of hepatocellular carcinoma was used to construct a multi-gene combined marker that can predict the prognosis of patients. The RNA expression data of hepatocellular carcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the IMMPORT database. Differential analysis was performed by Wilcox test to obtain differentially expressed genes. Univariate Cox regression analysis, lasso regression analysis and multivariate Cox regression analysis were performed to establish a prognostic model of immune genes, a total of 5 genes (HDAC1, BIRC5, SPP1, STC2, NR6A1) were identified to construct the models. The expression levels of 5 genes in HCC tissues were significantly different from those in paracancerous tissues. The Kaplan-Meier survival curve showed that the risk score calculated according to the prognostic model was significantly related to the overall survival (OS) of HCC. The receiver operating characteristic (ROC) curve confirmed that the prognostic model had high accuracy. Independent prognostic analysis was performed to prove that the risk value can be used as an independent prognostic factor. Then, the gene expression data of hepatocellular carcinoma in the ICGC database was used as a validation data set for the verification of the above steps. In addition, we used the CIBERSORT software and TIMER database to conduct immune infiltration research, and the results showed that the five genes of the model and the risk score have a certain correlation with the content of immune cells. Moreover, through Gene Set Enrichment Analysis (GSEA) and the construction of protein interaction networks, we found that the p53-mediated signal transduction pathway is a potentially important signal pathway for hepatocellular carcinoma and is positively regulated by certain genes in the prognostic model. In conclusion, this study provides potential targets for predicting the prognosis and treatment of hepatocellular carcinoma patients, and also provides new ideas about the correlation between immune genes and potential pathways of hepatocellular carcinoma.
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Affiliation(s)
- Zhipeng Zhu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Department of Clinical Medicine, The First Clinical College, Anhui Medical University, Hefei, China
| | - Mengyu Song
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Department of Clinical Medicine, The First Clinical College, Anhui Medical University, Hefei, China
| | - Wenhao Li
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Department of Clinical Medicine, The First Clinical College, Anhui Medical University, Hefei, China
| | - Mengying Li
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Department of Clinical Medicine, The First Clinical College, Anhui Medical University, Hefei, China
| | - Sihan Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bo Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Deng M, Fang L, Li SH, Zhao RC, Mei J, Zou JW, Wei W, Guo RP. Expression pattern and prognostic value of N6-methyladenosine RNA methylation key regulators in hepatocellular carcinoma. Mutagenesis 2021; 36:369-379. [PMID: 34467992 PMCID: PMC8493108 DOI: 10.1093/mutage/geab032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 09/01/2021] [Indexed: 12/24/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is still one of the most common malignancies worldwide. The accuracy of biomarkers for predicting the prognosis of HCC and the therapeutic effect is not satisfactory. N6-methyladenosine (m6A) methylation regulators play a crucial role in various tumours. Our research aims further to determine the predictive value of m6A methylation regulators and establish a prognostic model for HCC. In this study, the data of HCC from The Cancer Genome Atlas (TCGA) database was obtained, and the expression level of 15 genes and survival was examined. Then we identified two clusters of HCC with different clinical factors, constructed prognostic markers and analysed gene set enrichment, proteins’ interaction and gene co-expression. Three subgroups by consensus clustering according to the expression of the 13 genes were identified. The risk score generated by five genes divided HCC patients into high-risk and low-risk groups. In addition, we developed a prognostic marker that can identify high-risk HCC. Finally, a novel prognostic nomogram was developed to accurately predict HCC patients’ prognosis. The expression levels of 13 m6A RNA methylation regulators were significantly upregulated in HCC samples. The prognosis of cluster 1 and cluster 3 was worse. Patients in the high-risk group show a poor prognosis. Moreover, the risk score was an independent prognostic factor for HCC patients. In conclusion, we reveal the critical role of m6A RNA methylation modification in HCC and develop a predictive model based on the m6A RNA methylation regulators, which can accurately predict HCC patients’ prognosis and provide meaningful guidance for clinical treatment.
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Affiliation(s)
- Min Deng
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Lin Fang
- Guangdong Provincial Key Laboratory of Gastroenterology, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Shao-Hua Li
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Rong-Ce Zhao
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Jie Mei
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Jing-Wen Zou
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Wei Wei
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Rong-Ping Guo
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
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Glycolysis-related gene expression profiling serves as a novel prognosis risk predictor for human hepatocellular carcinoma. Sci Rep 2021; 11:18875. [PMID: 34556750 PMCID: PMC8460833 DOI: 10.1038/s41598-021-98381-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 08/31/2021] [Indexed: 02/07/2023] Open
Abstract
Metabolic pattern reconstruction is an important factor in tumor progression. Metabolism of tumor cells is characterized by abnormal increase in anaerobic glycolysis, regardless of high oxygen concentration, resulting in a significant accumulation of energy from glucose sources. These changes promotes rapid cell proliferation and tumor growth, which is further referenced a process known as the Warburg effect. The current study reconstructed the metabolic pattern in progression of cancer to identify genetic changes specific in cancer cells. A total of 12 common types of solid tumors were included in the current study. Gene set enrichment analysis (GSEA) was performed to analyze 9 glycolysis-related gene sets, which are implicated in the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes showed high area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). The findings of the current study showed that 8 genes (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were correlated with overall survival (OS) and recurrence-free survival (RFS). Further analysis showed that the prediction model accurately distinguished between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics showed good discrimination based on internal and external cohorts. These findings indicate that changes in expression level of metabolic genes implicated in glycolysis can contribute to reconstruction of tumor-related microenvironment.
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43
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Shi X, Tu S, Zhu L. Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma. J Gastrointest Oncol 2021; 12:1884-1894. [PMID: 34532136 DOI: 10.21037/jgo-21-394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 08/16/2021] [Indexed: 11/06/2022] Open
Abstract
Background Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes. Methods Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model. Results Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001). Conclusions In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.
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Affiliation(s)
- Xianqing Shi
- Department of Oncology, Liyang People's Hospital, Liyang, China
| | - Shuhuan Tu
- Department of Oncology, Liyang People's Hospital, Liyang, China
| | - Liqun Zhu
- Department of Oncology, Liyang People's Hospital, Liyang, China
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44
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Zhang Z, Xiong X, Zhang R, Xiong G, Yu C, Xu L. Bioinformatics analysis reveals biomarkers with cancer stem cell characteristics in kidney renal clear cell carcinoma. Transl Androl Urol 2021; 10:3501-3514. [PMID: 34532274 PMCID: PMC8421844 DOI: 10.21037/tau-21-647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 08/16/2021] [Indexed: 11/06/2022] Open
Abstract
Background Kidney renal clear cell carcinoma (KIRC) is a renal cortical tumor. KIRC is the most common subtype of kidney cancer, accounting for 70%-80% of kidney cancer. Early identification of the risk of KIRC patients can facilitate more accurate clinical treatment, but there is a lack of effective prognostic markers. We aimed to identify new prognostic biomarkers for KIRC on the basis of the cancer stem cell (CSC) theory. Methods RNA-sequencing (RNA-seq) data and related clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA) was used to identify significant modules and hub genes, and predictive hub genes were used to construct prognostic characteristics. Results The messenger RNA expression-based stemness index (mRNAsi) in tumor tissues of patients in the TCGA database is higher than that of the corresponding normal tissues. In addition, some clinical features and results are highly correlated with mRNAsi. WGCNA found that the green module is the most prominent module associated with mRNAsi; the genes in the green module are mainly concentration in Notch binding, endothelial cell development, Notch signaling pathway, and Rap 1 signaling pathway. A protein-protein interaction (PPI) network showed that the top 10 central genes were significantly associated with the transcriptional level. Moreover, the 10 hub genes were up-regulated in KIRC. Regarding survival analysis, the nomogram of the prognostic markers of the seven pivotal genes showed a higher predictive value. The classical receiver operating characteristic (ROC) curve analysis showed that risk score biomarkers had the highest accuracy and specificity with an area under the curve (AUC) value of 0.701. Conclusions mRNAsi-related genes may be good prognostic biomarkers for KIRC.
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Affiliation(s)
- Zan Zhang
- College of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xueyang Xiong
- College of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Rufeng Zhang
- College of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Guoliang Xiong
- Department of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Changyuan Yu
- College of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Lida Xu
- College of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China
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45
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Han S, Zhu W, Yang W, Guan Q, Chen C, He Q, Zhong Z, Zhao R, Xiong H, Han H, Li Y, Sun Z, Hu X, Tian J. A Prognostic Signature Constructed by CTHRC1 and LRFN4 in Stomach Adenocarcinoma. Front Genet 2021; 12:646818. [PMID: 34512711 PMCID: PMC8427509 DOI: 10.3389/fgene.2021.646818] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 07/02/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Stomach adenocarcinoma (STAD) is the most common histological type of stomach cancer, which causes a considerable number of deaths worldwide. This study aimed to identify its potential biomarkers with the notion of revealing the underlying molecular mechanisms. METHODS Gene expression profile microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The "limma" R package was used to screen the differentially expressed genes (DEGs) between STAD and matched normal tissues. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for function enrichment analyses of DEGs. The STAD dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another STAD dataset from the GEO database. CIBERSORT algorithm was used to characterize the 22 human immune cell compositions. The expression of LRFN4 and CTHRC1 in tissues was determined by quantitative real-time PCR from the patients recruited to the present study. RESULTS Three public datasets including 90 STAD patients and 43 healthy controls were analyzed, from which 44 genes were differentially expressed in all three datasets. These genes were implicated in biological processes including cell adhesion, wound healing, and extracellular matrix organization. Five out of 44 genes showed significant survival differences. Among them, CTHRC1 and LRFN4 were selected for construction of prognostic signature by univariate Cox regression and stepwise multivariate Cox regression in the TCGA-STAD dataset. The fidelity of the signature was evaluated in another independent dataset and showed a good classification effect. The infiltration levels of multiple immune cells between high-risk and low-risk groups had significant differences, as well as two immune checkpoints. TIM-3 and PD-L2 were highly correlated with the risk score. Multiple signaling pathways differed between the two groups of patients. At the same time, the expression level of LRFN4 and CTHRC1 in tissues analyzed by quantitative real-time PCR were consistent with the in silico findings. CONCLUSION The present study constructed the prognostic signature by expression of CTHRC1 and LRFN4 for the first time via comprehensive bioinformatics analysis, which provided the potential therapeutic targets of STAD for clinical treatment.
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Affiliation(s)
- Songling Han
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Wei Zhu
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
- Changshu Qiushi Technology Co., Ltd., Suzhou, China
| | - Weili Yang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qijie Guan
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Chao Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiang He
- Department of Nephrology, Zhejiang Provincial People’s Hospital, Hangzhou, China
| | - Zhuoheng Zhong
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ruoke Zhao
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Hangming Xiong
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Haote Han
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Yaohan Li
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zijian Sun
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Xingjiang Hu
- Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingkui Tian
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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Ju G, Zhou T, Zhang R, Pan X, Xue B, Miao S. DUSP12 regulates the tumorigenesis and prognosis of hepatocellular carcinoma. PeerJ 2021; 9:e11929. [PMID: 34414037 PMCID: PMC8344690 DOI: 10.7717/peerj.11929] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 07/18/2021] [Indexed: 01/20/2023] Open
Abstract
Background Dual specificity protein phosphatase (DUSP)12 is an atypical member of the protein tyrosine phosphatase family, which are overexpressed in multiple types of malignant tumors. This protein family protect cells from apoptosis and promotes the proliferation and motility of cells. However, the pathological role of DUSP12 in hepatocellular carcinoma (HCC) is incompletely understood. Methods We analyzed mRNA expression of DUSP12 between HCC and normal liver tissues using multiple online databases, and explored the status of DUSP12 mutants using the cBioPortal database. The correlation between DUSP12 expression and tumor-infiltrating immune cells was demonstrated using the Tumor Immune Estimation Resource database and the Tumor and Immune System Interaction Database. Loss of function assay was utilized to evaluate the role of DUSP12 in HCC progression. Results DUSP12 had higher expression along with mRNA amplification in HCC tissues compared with those in normal liver tissues, which suggested that higher DUSP12 expression predicted shorter overall survival. Analyses of functional enrichment of differentially expressed genes suggested that DUSP12 regulated HCC tumorigenesis, and that knockdown of DUSP12 expression by short hairpin (sh)RNA decreased the proliferation and migration of HCC cells. Besides, DUSP12 expression was positively associated with the infiltration of cluster of differentiation (CD)4+ T cells (especially CD4+ regulatory T cells), macrophages, neutrophils and dendritic cells. DUSP12 expression was positively associated with immune-checkpoint moieties, and was downregulated in a C3 immune-subgroup of HCC (which had the longest survival). Conclusion These data suggest that DUSP12 may have a critical role in the tumorigenesis, infiltration of immune cells, and prognosis of HCC.
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Affiliation(s)
- Gaoda Ju
- Department of Medical Oncology, Beijing Cancer Hospital, Peking University, Beijing, China
| | - Tianhao Zhou
- Shanghai First People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui Zhang
- Department of Pathology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Xiaozao Pan
- Department of Pathology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Bing Xue
- Department of Pathology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Sen Miao
- Department of Pathology, Affiliated Hospital of Jining Medical University, Jining, China
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Liu Y, Liu X, Gu Y, Lu H. A novel RNA binding protein-associated prognostic model to predict overall survival in hepatocellular carcinoma patients. Medicine (Baltimore) 2021; 100:e26491. [PMID: 34398005 PMCID: PMC8294901 DOI: 10.1097/md.0000000000026491] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 06/08/2021] [Indexed: 01/04/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is 1 of the deadliest malignancies worldwide. Despite significant advances in diagnosis and treatment, the mortality rate from HCC persists at a substantial level. Construction of a prognostic model that can reliably predict HCC patients' overall survival is urgently needed.Two RNA-seq dataset (the Cancer Genome Atlas and International Cancer Genome Consortium) and 1 microarray dataset (GSE14520) were included in our study. RNA-binding proteins (RBPs) in HCC patients was examined by differentially expressed genes analysis, functional enrichment analysis and protein-protein interaction network analysis. Subsequently, the Cancer Genome Atlas dataset was randomly divided into training and testing cohort with a prognostic model developed in the training cohort. In order to evaluate the prognostic value of the model, a comprehensive survival assessment was conducted.Five RBPs (ribosomal protein L10-like, enhancer of zeste homolog 2 (EZH2), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A), zinc finger protein 239, interferon-induced protein with tetratricopeptide repeats 1) were used to construct the model. The model accurately predicted the prognosis of liver cancer patients in both the training cohort and validation cohort. HCC patients could be assigned into a high-risk group and a low-risk group by this model, and the overall survival of these 2 groups was significantly different (P < .05). Furthermore, the risk scores obtained by this model were highly correlated with immune cell infiltration.The prognostic model helps to identify HCC patients at high risk of mortality, which optimizes decision-making for individualized treatment.
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Affiliation(s)
- Ye Liu
- Department of Hepatobiliary and Pancreatic, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China
| | - Xiaohong Liu
- Department of General Surgery, Wuhan University Zhongnan Hospital, Wuhan, China
| | - Yang Gu
- Department of General Surgery, Wuhan University Zhongnan Hospital, Wuhan, China
| | - Haofeng Lu
- Department of Hepatobiliary and Pancreatic, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China
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Identification of prognostic long non-coding RNA signature with potential drugs in hepatocellular carcinoma. Aging (Albany NY) 2021; 13:18789-18805. [PMID: 34285143 PMCID: PMC8351707 DOI: 10.18632/aging.203322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 07/05/2021] [Indexed: 12/24/2022]
Abstract
Hepatocellular carcinoma (HCC) is the primary malignancy in the liver with high rate of death and recurrence. Novel prognostic model would be crucial for early diagnosis and improved clinical decision. The study aims to provide an effective lncRNA-based signature to predict survival time and tumor recurrence for HCC. Based on public database, lncRNA-based classifiers for overall survival and tumor recurrence were built with regression analysis and cross validation strategy. According to the risk-score of the classifiers, the whole cohorts were divided into groups with high and low risk. Afterwards, the efficiency of the lncRNA-based classifiers was evaluated and compared with other clinical factors. Finally, candidate small molecules for high risk groups were further screened using drug response databases to explore potential drugs for HCC treatment.
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He JJ, Shang L, Yu QW, Jiao N, Qiu S, Zhu WX, Wu DF, Tian YE, Zhang Q. High expression of protein phosphatase 2 regulatory subunit B'' alpha predicts poor outcome in hepatocellular carcinoma patients after liver transplantation. World J Gastrointest Oncol 2021; 13:716-731. [PMID: 34322200 PMCID: PMC8299934 DOI: 10.4251/wjgo.v13.i7.716] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 06/06/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Protein phosphatase 2 regulatory subunit B'' alpha (PPP2R3A) gene has been reported in other tumors, but the influence of PPP2R3A gene expression on the occurrence, development, and prognosis of hepatocellular carcinoma (HCC) remains unclear.
AIM To investigate whether the PPP2R3A gene could be used to predict tumor recurrence and survival of HCC patients after liver transplantation (LT).
METHODS Diseased liver tissues of HCC patients after LT were collected as well as their clinical data and follow-up information. The immunohistochemical method was used to detect the expression of PPP2R3A protein in the tissues of 108 patients with primary liver cancer. The χ2 test was used to analyze the relationship between PPP2R3A protein expression levels and the clinicopathological features of tumors. The Kaplan-Meier method was used to analyze overall postoperative survival. The COX proportional hazard model was used to analyze adverse prognostic factors.
RESULTS Immunohistochemistry showed that the PPP2R3A protein was mainly expressed in the cytoplasm of HCC cells. Compared to corresponding peritumoral tissues, expression was higher in HCC tissues (P ≤ 0.001). Correlation analysis showed that high PPP2R3A expression was correlated with preoperative serum alpha-fetoprotein (AFP) levels (P = 0.003), tumor-node-metastasis-t stage (P ≤ 0.001), and envelope invasion (P = 0.001). Univariate analysis showed that overall survival (P ≤ 0.001) and recurrence-free survival (P = 0.025) of patients with high PPP2R3A expression (≥ 4 points) were poor compared to those with low expression (< 4 points). The overall survival rates or recurrence-free survival rates at 1, 2, and 3 years with high PPP2R3A expression were 73%, 38%, and 23% or 31%, 23%, and 23%, respectively. Multivariate analysis showed that high PPP2R3A expression (hazard ratio = 2.900, 95% confidence interval: 1.411–5.960, P = 0.004) was an independent survival risk factor of HCC patients after LT, and it was also an independent predictor of postoperative tumor recurrence. This study also showed in patients with AFP ≥ 400 ng/mL, the overall survival (P ≤ 0.001) and recurrence-free survival (P = 0.023) of those with high PPP2R3A expression were significantly worse compared to those with low PPP2R3A expression. When PPP2R3A expression was low, the overall survival rate (P = 0.461) or recurrence-free survival rate (P = 0.072) after LT in patients with AFP < 400 ng/mL and ≥ 400 ng/mL was not significantly difference. The 1, 2, and 3 year survival rate of patients with low PPP2R3A expression and AFP < 400 ng/mL were 98%, 80%, and 69%, respectively, while patients who met Hangzhou criteria had a post-transplant 1, 2, and 3 years overall survival rate of 89%, 66%, and 55%, respectively.
CONCLUSION High expression of PPP2R3A might be a potential marker for predicting poor prognosis of HCC after LT. Combined with serum AFP levels, PPP2R3A might enhance the accuracy of predicting HCC outcome in patients after LT and supplement the efficacy of the Hangzhou criteria.
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Affiliation(s)
- Jia-Jia He
- Clinical College of General Hospital of Chinese People's Armed Police Force, Anhui Medical University, Hefei 230032, Anhui, China
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Lei Shang
- Department of Health Statistics, Fourth Military Medical University, Xi'an 710032, Shanxi Province, China
| | - Qun-Wei Yu
- Department of Ophthalmology, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Ning Jiao
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Shuang Qiu
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Wei-Xiong Zhu
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Dong-Feng Wu
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Yun-Er Tian
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Qing Zhang
- Clinical College of General Hospital of Chinese People's Armed Police Force, Anhui Medical University, Hefei 230032, Anhui, China
- Department of Organ Transplantation, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
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He JJ, Shang L, Yu QW, Jiao N, Qiu S, Zhu WX, Wu DF, Tian YE, Zhang Q. High expression of protein phosphatase 2 regulatory subunit B'' alpha predicts poor outcome in hepatocellular carcinoma patients after liver transplantation. World J Gastrointest Oncol 2021. [DOI: 10.4251/wjgo.v13.i7.541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
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