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Wei Q, Hou YC, Mao FF, Feng JK, Wang X, Cheng SQ. Disulfidptosis-Associated lncRNAs are Potential Biomarkers for Predicting Immune Response and Prognosis Within Individuals Diagnosed with Hepatocellular Carcinoma. Hepat Med 2023; 15:249-264. [PMID: 38162389 PMCID: PMC10757809 DOI: 10.2147/hmer.s435726] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024] Open
Abstract
Purpose Hepatocellular carcinoma (HCC) is a prevalent form of cancer that is distributed globally. Disulfidptosis, characterized by the fragility of the actin cytoskeleton, represents a distinct type of cell death and holds promise for novel cancer therapies. Nevertheless, the connection among disulfidptosis-associated long non-coding RNAs (lncRNAs) and HCC is still unexplored. This study uses an in silico approach to provide the novel biomarkers of disulfidptosis-associated lncRNAs for predicting the immune response and prognosis with HCC. Methods In order to address this gap, we integrated transcriptomic data of HCC from The Cancer Genome Atlas (TCGA) and identified genes that exhibit differential expression with disulfidptosis and lncRNAs. Through co-expression analysis, we identified disulfidptosis-related lncRNAs. Afterwards, by employing univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO), a model for disulfidptosis-associated lncRNA was constructed. The risk model underwent assessment through the utilization of diverse analytical methodologies, including functional enrichment annotation, Kaplan-Meier analysis, principal component analysis (PCA), immune infiltration and immune status analysis, as well as tumor mutation analysis. Furthermore, we discussed the implications of the model in predicting drug sensitivity. Results Our study culminated in the construction of a disulfidptosis-related lncRNA model comprising four prognostic disulfidptosis-related lncRNAs (ACYTOR, NRAV, AL080248.1, and AC069307.1). This model demonstrates exceptional diagnostic value for HCC patients and holds practical implications for guiding clinicians in personalizing immunotherapy and drug selection based on individual variations. Conclusion In summary, our research introduces a novel predictive tool utilizing disulfidptosis-related lncRNAs, offering potential guidance for the therapeutic management of HCC.
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Affiliation(s)
- Qian Wei
- The First Clinical Medicine School, Guangdong Pharmaceutical University, Guangzhou, People’s Republic of China
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, People’s Republic of China
| | - Yu-Chao Hou
- Cancer Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Fei-Fei Mao
- Tongji University Cancer Center, Shanghai 10th People’s Hospital, School of Medicine, Tongji University, Shanghai, People’s Republic of China
| | - Jin-Kai Feng
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, People’s Republic of China
| | - Xu Wang
- Cancer Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Shu-Qun Cheng
- The First Clinical Medicine School, Guangdong Pharmaceutical University, Guangzhou, People’s Republic of China
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, People’s Republic of China
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Han T, Wu Z, Zhang Z, Liang J, Xia C, Yan H. Comprehensive analysis of hypoxia-related genes for prognosis value, immune status, and therapy in osteosarcoma patients. Front Pharmacol 2023; 13:1088732. [PMID: 36686667 PMCID: PMC9853159 DOI: 10.3389/fphar.2022.1088732] [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: 11/03/2022] [Accepted: 12/20/2022] [Indexed: 01/09/2023] Open
Abstract
Osteosarcoma is a common malignant bone tumor in children and adolescents. The overall survival of osteosarcoma patients is remarkably poor. Herein, we sought to establish a reliable risk prognostic model to predict the prognosis of osteosarcoma patients. Patients ' RNA expression and corresponding clinical data were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus databases. A consensus clustering was conducted to uncover novel molecular subgroups based on 200 hypoxia-linked genes. A hypoxia-risk models were established by Cox regression analysis coupled with LASSO regression. Functional enrichment analysis, including Gene Ontology annotation and KEGG pathway analysis, were conducted to determine the associated mechanisms. Moreover, we explored relationships between the risk scores and age, gender, tumor microenvironment, and drug sensitivity by correlation analysis. We identified two molecular subgroups with significantly different survival rates and developed a risk model based on 12 genes. Survival analysis indicated that the high-risk osteosarcoma patients likely have a poor prognosis. The area under the curve (AUC) value showed the validity of our risk scoring model, and the nomogram indicates the model's reliability. High-risk patients had lower Tfh cell infiltration and a lower stromal score. We determined the abnormal expression of three prognostic genes in osteosarcoma cells. Sunitinib can promote osteosarcoma cell apoptosis with down-regulation of KCNJ3 expression. In summary, the constructed hypoxia-related risk score model can assist clinicians during clinical practice for osteosarcoma prognosis management. Immune and drug sensitivity analysis can provide essential insights into subsequent mechanisms. KCNJ3 may be a valuable prognostic marker for osteosarcoma development.
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Affiliation(s)
- Tao Han
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China
| | - Zhouwei Wu
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China
| | - Zhe Zhang
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China
| | - Jinghao Liang
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China
| | - Chuanpeng Xia
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China
| | - Hede Yan
- Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China,The Second Clinical Medical College of Wenzhou Medical University, Wenzhou, China,Key Laboratory of Orthopedics of Zhejiang Province, Wenzhou, China,*Correspondence: Hede Yan,
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Hashemi M, Mirzaei S, Zandieh MA, Rezaei S, Amirabbas Kakavand, Dehghanpour A, Esmaeili N, Ghahremanzade A, Saebfar H, Heidari H, Salimimoghadam S, Taheriazam A, Entezari M, Ahn KS. Long non-coding RNAs (lncRNAs) in hepatocellular carcinoma progression: Biological functions and new therapeutic targets. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 177:207-228. [PMID: 36584761 DOI: 10.1016/j.pbiomolbio.2022.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 11/29/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022]
Abstract
Liver is an important organ in body that performs vital functions such as detoxification. Liver is susceptible to development of cancers, and hepatocellular carcinoma (HCC) is among them. 75-85% of liver cancer cases are related to HCC. Therefore, much attention has been directed towards understanding factors mediating HCC progression. LncRNAs are epigenetic factors with more than 200 nucleotides in length located in both nucleus and cytoplasm and they are promising candidates in cancer therapy. Directing studies towards understanding function of lncRNAs in HCC is of importance. LncRNAs regulate cell cycle progression and growth of HCC cells, and they can also induce/inhibit apoptosis in tumor cells. LncRNAs affect invasion and metastasis in HCC mainly by epithelial-mesenchymal transition (EMT) mechanism. Revealing the association between lncRNAs and downstream signaling pathways in HCC is discussed in the current manuscript. Infectious diseases can affect lncRNA expression in mediating HCC development and then, altered expression level of lncRNA is associated with drug resistance and radio-resistance. Biomarker application of lncRNAs and their role in prognosis and diagnosis of HCC are also discussed to pave the way for treatment of HCC patients.
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Affiliation(s)
- Mehrdad Hashemi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Sepideh Mirzaei
- Department of Biology, Faculty of Science, Islamic Azad University, Science and Research Branch, Tehran, Iran
| | - Mohammad Arad Zandieh
- Department of Food Hygiene and Quality Control, Division of Epidemiology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Sahar Rezaei
- Faculty of Veterinary Medicine, Islamic Azad University, Science and Research Branch, Tehran, Iran
| | - Amirabbas Kakavand
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Amir Dehghanpour
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Negin Esmaeili
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Azin Ghahremanzade
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Hamidreza Saebfar
- European University Association, League of European Research Universities, University of Milan, Italy
| | - Hajar Heidari
- Department of Biomedical Sciences, School of Public Health University at Albany State University of New York, Albany, NY, 12208, USA
| | - Shokooh Salimimoghadam
- Department of Biochemistry and Molecular Biology, Faculty of Veterinary Medicine, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Afshin Taheriazam
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Orthopedics, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Maliheh Entezari
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Kwang Seok Ahn
- College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea.
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Wang T, Zhou Z, Wang X, You L, Li W, Zheng C, Zhang J, Wang L, Kong X, Gao Y, Sun X. Comprehensive analysis of nine m7G-related lncRNAs as prognosis factors in tumor immune microenvironment of hepatocellular carcinoma and experimental validation. Front Genet 2022; 13:929035. [PMID: 36081998 PMCID: PMC9445240 DOI: 10.3389/fgene.2022.929035] [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: 04/26/2022] [Accepted: 07/18/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Hepatocellular carcinoma (HCC) remains the most prevalent gastrointestinal malignancy worldwide, with robust drug resistance to therapy. N7-methylguanosine (m7G) mRNA modification has been significantly related to massive human diseases. Considering the effect of m7G-modified long non-coding RNAs (lncRNAs) in HCC progression is unknown, the study aims at investigating a prognostic signature to improve clinical outcomes for patients with HCC.Methods: Two independent databases (TCGA and ICGC) were used to analyze RNAseq data of HCC patients. First, co-expression analysis was applied to obtain the m7G-related lncRNAs. Moreover, consensus clustering analysis was employed to divide HCC patients into clusters. Then, using least absolute shrinkage and selection operator-Cox regression analysis, the m7G-related lncRNA prognostic signature (m7G-LPS) was first tested in the training set and then confirmed in both the testing and ICGC sets. The expression levels of the nine lncRNAs were further confirmed via real-time PCR in cell lines, principal component analysis, and receiver operating characteristic curve. The m7G-LPS could divide HCC patients into two different risk groups with the optimal risk score. Then, Kaplan–Meier curves, tumor mutation burden (TMB), therapeutic effects of chemotherapy agents, and expressions of immune checkpoints were performed to further enhance the availability of immunotherapeutic treatments for HCC patients.Results: A total of 1465 lncRNAs associated with the m7G genes were finally selected from the TCGA database, and through the univariate Cox regression, the expression levels of 22 m7G-related lncRNAs were concerning HCC patients’ overall survival (OS). Then, the whole patients were grouped into two subgroups, and the OS in Cluster 1 was longer than that of patients in Cluster 2. Furthermore, nine prognostic m7G-related lncRNAs were identified to conduct the m7G-LPS, which were further verified. A prognostic nomogram combined age, gender, HCC grade, stage, and m7G-LPS showed strong reliability and accuracy in predicting OS in HCC patients. Finally, immune checkpoint expression, TMB, and several chemotherapy agents were remarkably associated with risk scores. More importantly, the OS of the TMB-high patients was the worst among the four groups.Conclusion: The prognostic model we established was validated by abundant algorithms, which provided a new perspective on HCC tumorigenesis and thus improved individualized treatments for patients.
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Affiliation(s)
- Tao Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhijia Zhou
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xuan Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Liping You
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wenxuan Li
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chao Zheng
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jinghao Zhang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lingtai Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaoni Kong
- Central Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
| | - Yueqiu Gao
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
| | - Xuehua Sun
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
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Zhang G, Sun J, Zhang X. A novel Cuproptosis-related LncRNA signature to predict prognosis in hepatocellular carcinoma. Sci Rep 2022; 12:11325. [PMID: 35790864 PMCID: PMC9256635 DOI: 10.1038/s41598-022-15251-1] [Citation(s) in RCA: 99] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/21/2022] [Indexed: 12/16/2022] Open
Abstract
Increased intracellular toxicity due to an imbalance in copper homeostasis caused by copper ion accumulation could regulate the rate of cancer cell growth and proliferation. The goal of this study was to create a novel Cuproptosis-related lncRNA signature that may be utilized to predict survival and immunotherapy in HCC patients. Cuproptosis-associated lncRNAs and differentially expressed lncRNAs between HCC tumor tissue and normal tissue were discovered first. By LASSO-Cox analysis, the overlapping lncRNAs were then utilized to build a Cuproptosis-associated lncRNA signature, which might be used to predict patient prognosis and responsiveness to immune checkpoint blockade (ICB) therapy. Differences in the infiltration of immune cell subpopulations between high and low-risk score subgroups were also analyzed. Moreover, a nomogram based on the Cuproptosis-associated lncRNA signature and clinical features was developed and demonstrated to have good predictive potential. Finally, qRT-PCR was performed in HerpG2 and MHCC-97H cell lines to explore whether these lncRNAs were indeed involved in the process of Cuproptosis. In summary, we created a prognostic lncRNA profile linked to Cuproptosis to forecast response to immunotherapy, which may provide a new potential non-apoptotic therapeutic perspective for HCC patients.
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Affiliation(s)
- Genhao Zhang
- grid.412633.10000 0004 1799 0733Department of Blood Transfusion, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jianping Sun
- Department of Pathology, Zhengzhou YIHE Hospital, Zhengzhou, China
| | - Xianwei Zhang
- Medical School, Huanghe Science and Technology University, Zhengzhou, China.
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Qu G, Wang D, Xu W, Guo W. Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma. Front Genet 2022; 13:867627. [PMID: 35559014 PMCID: PMC9087742 DOI: 10.3389/fgene.2022.867627] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/25/2022] [Indexed: 01/04/2023] Open
Abstract
Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC. Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic. Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group. Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.
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Affiliation(s)
- Guangzhen Qu
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Dong Wang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Weiyu Xu
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Wei Guo
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, China
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Huang S, Zhang J, Lai X, Zhuang L, Wu J. Identification of Novel Tumor Microenvironment-Related Long Noncoding RNAs to Determine the Prognosis and Response to Immunotherapy of Hepatocellular Carcinoma Patients. Front Mol Biosci 2022; 8:781307. [PMID: 35004851 PMCID: PMC8739902 DOI: 10.3389/fmolb.2021.781307] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/25/2021] [Indexed: 12/12/2022] Open
Abstract
Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. The tumor microenvironment (TME) plays a vital role in HCC progression. Thus, this research was designed to analyze the correlation between the TME and the prognosis of HCC patients and to construct a TME-related long noncoding RNA (lncRNA) signature to determine HCC patients’ prognosis and response to immunotherapy. Methods: We assessed the stromal–immune–estimate scores within the HCC microenvironment using the ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data) algorithm based on The Cancer Genome Atlas database, and their associations with survival and clinicopathological parameters were also analyzed. Thereafter, differentially expressed lncRNAs were filtered out according to the immune and stromal scores. Cox regression analysis was performed to build a TME-related lncRNA risk signature. Kaplan–Meier analysis was used to explore the prognostic value of the risk signature. Furthermore, we explored the biological functions and immune microenvironment features in the high- and low-risk groups. Lastly, we probed the association of the risk model with treatment responses to immune checkpoint inhibitors (ICIs) in HCC. Results: The stromal, immune, and estimate scores were obtained utilizing the ESTIMATE algorithm for patients with HCC. Kaplan–Meier analysis showed that high scores were significantly correlated with better prognosis in HCC patients. Six TME-related lncRNAs were screened to construct the prognostic model. The Kaplan–Meier curves suggested that HCC patients with low risk had better prognosis than those with high risk. Receiver operating characteristic (ROC) curve and Cox regression analyses indicated that the risk model could predict HCC survival exactly and independently. Functional enrichment analysis revealed that some tumor- and immune-related pathways were activated in the high-risk group. We also revealed that some immune cells, which were important in enhancing immune responses toward cancer, were significantly increased in the low-risk group. In addition, there was a close correlation between ICIs and the risk signature, which can be used to predict the treatment responses of HCC patients. Conclusion: We analyzed the influence of the stromal, immune, and estimate scores on the prognosis of HCC patients. A novel TME-related lncRNA risk model was established, which could be effectively applied as an independent prognostic biomarker and predictor of ICIs for HCC patients.
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Affiliation(s)
- Shenglan Huang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Jian Zhang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Xiaolan Lai
- Ningde Municipal Hospital Affiliated to Ningde Normal University, Ningde, China
| | - Lingling Zhuang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Jianbing Wu
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
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Heawchaiyaphum C, Pientong C, Yoshiyama H, Iizasa H, Panthong W, Ekalaksananan T. General Features and Novel Gene Signatures That Identify Epstein-Barr Virus-Associated Epithelial Cancers. Cancers (Basel) 2021; 14:cancers14010031. [PMID: 35008199 PMCID: PMC8750470 DOI: 10.3390/cancers14010031] [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: 11/15/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 11/16/2022] Open
Abstract
Epstein-Barr virus (EBV) is associated with various types of human malignancies, including nasopharyngeal carcinoma (NPC), EBV-associated gastric carcinoma (EBVaGC), and oral squamous cell carcinoma (OSCC). The present study aimed to identify gene signatures and common signaling pathways that can be used to predict the prognosis of EBV-associated epithelial cancers (EBVaCAs) by performing an integrated bioinformatics analysis of cell lines and tumor tissues. We identified 12 differentially expressed genes (DEGs) in the EBVaCA cell lines. Among them, only four DEGs, including BAMBI, SLC26A9, SGPP2, and TMC8, were significantly upregulated. However, SLC26A9 and TMC8, but not BAMBI and SGPP2, were significantly upregulated in EBV-positive tumor tissues compared to EBV-negative tumor tissues. Next, we identified IL6/JAK/STAT3 and TNF-α/NF-κB signaling pathways as common hallmarks of EBVaCAs. The expression of key genes related to the two hallmarks was upregulated in both EBV-infected cell lines and EBV-positive tumor tissues. These results suggest that SLC26A9 and TMC8 might be gene signatures that can effectively predict the prognosis of EBVaCAs and provide new insights into the molecular mechanisms of EBV-driven epithelial cancers.
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Affiliation(s)
- Chukkris Heawchaiyaphum
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand; (C.H.); (C.P.); (W.P.)
- HPV&EBV and Carcinogenesis (HEC) Research Group, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Chamsai Pientong
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand; (C.H.); (C.P.); (W.P.)
- HPV&EBV and Carcinogenesis (HEC) Research Group, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Hironori Yoshiyama
- Department of Microbiology, Shimane University Faculty of Medicine, Izumo 693-8501, Japan; (H.Y.); (H.I.)
| | - Hisashi Iizasa
- Department of Microbiology, Shimane University Faculty of Medicine, Izumo 693-8501, Japan; (H.Y.); (H.I.)
| | - Watcharapong Panthong
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand; (C.H.); (C.P.); (W.P.)
- HPV&EBV and Carcinogenesis (HEC) Research Group, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Tipaya Ekalaksananan
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand; (C.H.); (C.P.); (W.P.)
- HPV&EBV and Carcinogenesis (HEC) Research Group, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Correspondence: ; Tel.: +66-4336-3808; Fax:+66-4334-8385
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