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Wang J, Jia Q, Jiang S, Lu W, Ning H. POU6F1 promotes ferroptosis by increasing lncRNA-CASC2 transcription to regulate SOCS2/SLC7A11 signaling in gastric cancer. Cell Biol Toxicol 2024; 40:3. [PMID: 38267746 PMCID: PMC10808632 DOI: 10.1007/s10565-024-09843-y] [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: 08/18/2023] [Accepted: 11/22/2023] [Indexed: 01/26/2024]
Abstract
OBJECTIVE This study investigated the effect and mechanism of POU6F1 and lncRNA-CASC2 on ferroptosis of gastric cancer (GC) cells. METHODS GC cells treated with erastin and RSL3 were detected for ferroptosis, reactive oxygen species (ROS) level, and cell viability. The expression levels of POU6F1, lncRNA-CASC2, SOCS2, and ferroptosis-related molecules (GPX4 and SLC7A11) were also measured. The regulations among POU6F1, lncRNA-CASC2, FMR1, SOCS2, and SLC7A11 were determined. Subcutaneous tumor models were established, in which the expressions of Ki-67, SOCS2, and GPX4 were detected by immunohistochemistry. RESULTS GC patients with decreased expressions of POU6F1 and lncRNA-CASC2 had lower survival rate. Overexpression of POU6F1 or lncRNA-CASC2 decreased cell proliferation and GSH levels in GC cells, in addition to increasing total iron, Fe2+, MDA, and ROS levels. POU6F1 directly binds to the lncRNA-CASC2 promoter to promote its transcription. LncRNA-CASC2 can target FMR1 and increase SOCS2 mRNA stability to promote SLC7A11 ubiquitination degradation and activate ferroptosis signaling. Knockdown of SOCS2 inhibited the ferroptosis sensitivity of GC cells and reversed the effects of POU6F1 and lncRNA-CASC2 overexpression on ferroptosis in GC cells. CONCLUSION Transcription factor POU6F1 binds directly to the lncRNA-CASC2 promoter to promote its expression, while upregulated lncRNA-CASC2 increases SOCS2 stability and expression by targeting FMR1, thereby inhibiting SLC7A11 signaling to promote ferroptosis in GC cells and inhibit GC progression.
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Affiliation(s)
- Jingyun Wang
- Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe East Road, Erqi District, Zhengzhou, Henan, 450000, People's Republic of China
| | - Qiaoyu Jia
- Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe East Road, Erqi District, Zhengzhou, Henan, 450000, People's Republic of China
| | - Shuqin Jiang
- Department of Child Development and Behavior, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, People's Republic of China
| | - Wenquan Lu
- Department of Gastroenterology, The Second Affiliated Hospital of Zhengzhou University, No.2 JingBa Road, Jinshui District, Zhengzhou, Henan, 450014, People's Republic of China
| | - Hanbing Ning
- Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe East Road, Erqi District, Zhengzhou, Henan, 450000, People's Republic of China.
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Gong H, Li Z, Wu Z, Lian G, Su Z. Modulation of ferroptosis by non‑coding RNAs in cancers: Potential biomarkers for cancer diagnose and therapy. Pathol Res Pract 2024; 253:155042. [PMID: 38184963 DOI: 10.1016/j.prp.2023.155042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/14/2023] [Accepted: 12/16/2023] [Indexed: 01/09/2024]
Abstract
Ferroptosis is a recently discovered cell programmed death. Extensive researches have indicated that ferroptosis plays an essential role in tumorigenesis, development, migration and chemotherapy drugs resistance, which makes it become a new target for tumor therapy. Non-coding RNAs (ncRNAs) are considered to control a wide range of cellular processes by modulating gene expression. Recent studies have indicated that ncRNAs regulate the process of ferroptosis via various pathway to affect the development of cancer. However, the regulation network remains ambiguous. In this review, we outlined the major metabolic processes of ferroptosis and concluded the relationship between ferroptosis-related ncRNAs and cancer progression. In addition, the prospect of ncRNAs being new therapeutic targets and early diagnosis biomarkers for cancer by regulating ferroptosis were presented, and the possible obstacles were also predicted. This could help in discovering novel cancer early diagnostic methods and therapeutic approaches.
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Affiliation(s)
- Huifang Gong
- Department of Biochemistry and Molecular Biology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Zheng Li
- Department of Biochemistry and Molecular Biology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Zhimin Wu
- Department of Biochemistry and Molecular Biology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Gaojian Lian
- Department of Biochemistry and Molecular Biology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
| | - Zehong Su
- Department of Biochemistry and Molecular Biology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
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Mo Y, Adu-Amankwaah J, Qin W, Gao T, Hou X, Fan M, Liao X, Jia L, Zhao J, Yuan J, Tan R. Unlocking the predictive potential of long non-coding RNAs: a machine learning approach for precise cancer patient prognosis. Ann Med 2023; 55:2279748. [PMID: 37983519 DOI: 10.1080/07853890.2023.2279748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 10/31/2023] [Indexed: 11/22/2023] Open
Abstract
The intricate web of cancer biology is governed by the active participation of long non-coding RNAs (lncRNAs), playing crucial roles in cancer cells' proliferation, migration, and drug resistance. Pioneering research driven by machine learning algorithms has unveiled the profound ability of specific combinations of lncRNAs to predict the prognosis of cancer patients. These findings highlight the transformative potential of lncRNAs as powerful therapeutic targets and prognostic markers. In this comprehensive review, we meticulously examined the landscape of lncRNAs in predicting the prognosis of the top five cancers and other malignancies, aiming to provide a compelling reference for future research endeavours. Leveraging the power of machine learning techniques, we explored the predictive capabilities of diverse lncRNA combinations, revealing their unprecedented potential to accurately determine patient outcomes.
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Affiliation(s)
- Yixuan Mo
- Department of Physiology, Basic medical school, Xuzhou Medical University, Xuzhou, China
| | - Joseph Adu-Amankwaah
- Department of Physiology, Basic medical school, Xuzhou Medical University, Xuzhou, China
| | - Wenjie Qin
- Department of Physiology, Basic medical school, Xuzhou Medical University, Xuzhou, China
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Tan Gao
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Xiaoqing Hou
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Mengying Fan
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Xuemei Liao
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Liwei Jia
- Department of Pathology, UT Southwestern Medical Center, Dallas, UT, USA
| | - Jinming Zhao
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China
- Department of Pathology, The First Hospital of China Medical University, Shenyang, China
| | - Jinxiang Yuan
- The Collaborative Innovation Center, Jining Medical University, Jining, Shandong, China
| | - Rubin Tan
- Department of Physiology, Basic medical school, Xuzhou Medical University, Xuzhou, China
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Zhang Q, Huang Y, Xia Y, Liu Y, Gan J. Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma. Clin Exp Med 2023; 23:2051-2064. [PMID: 36153416 DOI: 10.1007/s10238-022-00892-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/09/2022] [Indexed: 11/03/2022]
Abstract
Cuproptosis has been recently used to indicate unique biological processes triggered by Cu action as a new term. This study aimed to explore the relationship between cuproptosis-related lncRNA and hepatocellular carcinoma (HCC) with regard to immunity and prognosis. RNA sequencing and the clinical data were downloaded from the TCGA database. The cuproptosis-related genes were sorted out through literature study. The cuproptosis-related IncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The K-M survival analysis, receiver operating characteristic analysis, and C-index analysis were adopted to evaluate the prognostic prediction performance of the signature. The functional enrichment, immune infiltration and tumor mutation analysis were further analyzed. Subsequently, we predicted the differences in chemosensitivity from tumor gene expression levels for some chemotherapy drugs. The prognostic signature consisting of 5 overall survival-related CUPlncRNAs. It showed an extraordinary ability to predict the prognoses of patients with HCC. The signature can predict the abundance of immune cell infiltration, immune functions, expression of immune checkpoint inhibitors, m6A genes, which was supported by the GO biological process and KEGG analysis. And it may also have a guiding effect in the sensitivity of different chemotherapeutic drugs and tumor mutation burden. We constructed a new cuproptosis-related lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.
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Affiliation(s)
- Qiongyue Zhang
- Department of Infectious Diseases, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Yan Huang
- Department of Infectious Diseases, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Yu Xia
- Department of Orthopaedics, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China
| | - Yumeng Liu
- Department of Infectious Diseases, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Jianhe Gan
- Department of Infectious Diseases, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, People's Republic of China.
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Yang W, Zhao X, Duan L, Niu L, Zhang Y, Zhou W, Li Y, Chen J, Fan A, Xie Q, Liu J, Han Y, Fan D, Hong L. Development and validation of a ligand-receptor pairs signature to predict outcome and provide a therapeutic strategy in gastric cancer. Expert Rev Mol Diagn 2023; 23:619-634. [PMID: 37248704 DOI: 10.1080/14737159.2023.2219843] [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: 12/29/2022] [Accepted: 05/26/2023] [Indexed: 05/31/2023]
Abstract
BACKGROUND An important factor in tumor development and progression is the tumor microenvironment (TME), which is heterogeneous. Previous studies have mainly investigated the expression profile and prognostic values of genes in gastric cancer (GC) at the cell population level but neglected the interactions and heterogeneity between cells. METHODS The pattern of ligand-receptor (LR) interactions was delineated on a scRNA-seq dataset containing 44,953 cells from nine GC patients and a fourth bulk RNA-seq dataset including data from 1159 GC patients. We then constructed an LR.Score scoring model to comprehensively evaluate the influence of LR-pairs on the TME, overall survival, and immunotherapy response in GC patients from several cohorts. RESULTS Cell communication network among 13 cell types was constructed based on the LR-pairs. We proposed a new molecular subtyping model for GC based on the LR-pairs and revealed the differences in prognosis, pathophysiologic features, mutation characteristics, function enrichment, and immunological characteristics among the three subtypes. Finally, an LR.Score model based on LR-pairs was developed and validated on several datasets. CONCLUSIONS Based on the selected LR-pairs, we successfully constructed a novel prediction model and observed its well performance on molecular subtyping, target and pathway screening, prognosis judging, and immunotherapy response predicting.
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Affiliation(s)
- Wanli Yang
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Xinhui Zhao
- Department of Thyroid and Breast Surgery, The Affiliated Hospital of Northwest University & Xi'an No.3 Hospital, Northwest University, Xi'an, Shaanxi Province, China
| | - Lili Duan
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Liaoran Niu
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Yujie Zhang
- Department of Histology and Embryology, School of Basic Medicine, Xi'an Medical University, Xi'an, Shaanxi Province, China
| | - Wei Zhou
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Yiding Li
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Junfeng Chen
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Aqiang Fan
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Qibin Xie
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Jinqiang Liu
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Yu Han
- Department of Otolaryngology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Daiming Fan
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
| | - Liu Hong
- Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, China
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6
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Liu Y, Liu Y, Ye S, Feng H, Ma L. A new ferroptosis-related signature model including messenger RNAs and long non-coding RNAs predicts the prognosis of gastric cancer patients. J Transl Int Med 2023; 11:145-155. [PMID: 38025952 PMCID: PMC10680379 DOI: 10.2478/jtim-2023-0089] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
Background and Objectives Gastric cancer (GC) is among the most malignant tumor types, which causes heavy healthy and economic burden to the people and societies all around the world. Establishment of an effective set of prognostic marker will benefit a lot to the treatment of GC patients clinically. Ferroptosis is a newly identified regulated cell death modality, with tight relevance with GC development. However, its application in the prognosis of GC has not been studied in detail. Deregulated messenger RNA (mRNA) and long non-coding RNA (lncRNA) expression profile in tumor can serve as novel prognostic marker for predicting the survival and cancer relapse in patients. Methods We downloaded ferroptosis-related gene expression microarray data, clinicopathologic information and a list of 259 ferroptosis-related genes from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Ferroptosis database, respectively. Then, correlation analysis, univariate and multivariate Cox regression analysis were used to construct a novel prognostic model for GC. Then, we validated the model in the GEO datasets. Finally, we evaluated the differences in immune microenvironment between high- and low-risk groups. Results We utilized the ferroptosis-related mRNA and lncRNA profile to successfully construct a prognostic model (incorporating 2 mRNAs and 15 lncRNAs) in GC. Our model, integrating diverse clinical traits and critical factors of GC, showed desirable efficacy in the prognosis of GC patients. This model also manifested effectively in validation by using external patients' data. Conclusions Our study developed a novel ferroptosis-related signature to predict the prognosis of gastric cancer patients. The ferroptosis-related signature had a favorable predictive ability. This model may greatly boost the treatment of GC patients in clinical practice.
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Affiliation(s)
- Yang Liu
- Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun130033, Jilin Province, China
| | - Yanqing Liu
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York10032, NY, USA
| | - Shujun Ye
- Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun130033, Jilin Province, China
| | - Huijin Feng
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York10032, NY, USA
| | - Lianjun Ma
- Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun130033, Jilin Province, China
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7
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Ning J, Sun K, Fan X, Jia K, Meng L, Wang X, Li H, Ma R, Liu S, Li F, Wang X. Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer. Sci Rep 2023; 13:7019. [PMID: 37120631 PMCID: PMC10148812 DOI: 10.1038/s41598-023-34291-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 04/27/2023] [Indexed: 05/01/2023] Open
Abstract
Gastric cancer is one of the most common malignancies. Although some patients benefit from immunotherapy, the majority of patients have unsatisfactory immunotherapy outcomes, and the clinical significance of immune-related genes in gastric cancer remains unknown. We used the single-sample gene set enrichment analysis (ssGSEA) method to evaluate the immune cell content of gastric cancer patients from TCGA and clustered patients based on immune cell scores. The Weighted Correlation Network Analysis (WGCNA) algorithm was used to identify immune subtype-related genes. The patients in TCGA were randomly divided into test 1 and test 2 in a 1:1 ratio, and a machine learning integration process was used to determine the best prognostic signatures in the total cohort. The signatures were then validated in the test 1 and the test 2 cohort. Based on a literature search, we selected 93 previously published prognostic signatures for gastric cancer and compared them with our prognostic signatures. At the single-cell level, the algorithms "Seurat," "SCEVAN", "scissor", and "Cellchat" were used to demonstrate the cell communication disturbance of high-risk cells. WGCNA and univariate Cox regression analysis identified 52 prognosis-related genes, which were subjected to 98 machine-learning integration processes. A prognostic signature consisting of 24 genes was identified using the StepCox[backward] and Enet[alpha = 0.7] machine learning algorithms. This signature demonstrated the best prognostic performance in the overall, test1 and test2 cohort, and outperformed 93 previously published prognostic signatures. Interaction perturbations in cellular communication of high-risk T cells were identified at the single-cell level, which may promote disease progression in patients with gastric cancer. We developed an immune-related prognostic signature with reliable validity and high accuracy for clinical use for predicting the prognosis of patients with gastric cancer.
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Affiliation(s)
- Jingyuan Ning
- Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Keran Sun
- Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Xiaoqing Fan
- Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Keqi Jia
- Department of Pathology, Shijiazhuang People's Hospital, Shijiazhuang, People's Republic of China
| | - Lingtong Meng
- Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Xiuli Wang
- Department of Laboratory, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Hui Li
- Department of Oncology, Shijiazhuang Fourth Hospital, Shijiazhuang, People's Republic of China
| | - Ruixiao Ma
- Department of Oncology, Shijiazhuang Fourth Hospital, Shijiazhuang, People's Republic of China
| | - Subin Liu
- Department of Oncology, Shijiazhuang Fourth Hospital, Shijiazhuang, People's Republic of China
| | - Feng Li
- Department of Oncology, Shijiazhuang Fourth Hospital, Shijiazhuang, People's Republic of China
| | - Xiaofeng Wang
- Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China.
- Department of Oncology, Shijiazhuang Fourth Hospital, Shijiazhuang, People's Republic of China.
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8
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Zhao B, Fang F, Liao Y, Chen Y, Wang F, Ma Y, Wei C, Zhao J, Ji H, Wang D, Tang D. Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer. BMC Bioinformatics 2023; 24:100. [PMID: 36935487 PMCID: PMC10024859 DOI: 10.1186/s12859-023-05228-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/13/2023] [Indexed: 03/21/2023] Open
Abstract
Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model's reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS' correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.
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Grants
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. 202011117056Y the Academic Science and Technology Innovation Fund for College Students
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. YZ2021075 the Social Development-Health Care Project of Yangzhou, Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- No. LGY2019034 High-level talent "six one projects" top talent scientific research project of Jiangsu Province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- SJCX22_1816 the Graduate Research- Innovation Project in Jiangsu province
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
- BE2022773 Social development project of key R & D plan of Jiangsu Provincial Department of science and technology
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Affiliation(s)
- Bin Zhao
- Department of Clinical Medical College, The Yangzhou School of Clinical Medicine, Dalian Medical University, Yangzhou, 225001, China
| | - Fang Fang
- Department of General Surgery, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China
| | - Yiqun Liao
- Department of Clinical Medical College, The Yangzhou School of Clinical Medicine, Dalian Medical University, Yangzhou, 225001, China
| | - Yuji Chen
- Department of Clinical Medical College, Yangzhou University, Yangzhou, 225001, China
| | - Fei Wang
- Department of Clinical Medical College, The Yangzhou School of Clinical Medicine, Dalian Medical University, Yangzhou, 225001, China
| | - Yichao Ma
- Department of Clinical Medical College, Yangzhou University, Yangzhou, 225001, China
| | - Chen Wei
- Department of Clinical Medical College, Yangzhou University, Yangzhou, 225001, China
| | - Jiahao Zhao
- Department of Clinical Medical College, Yangzhou University, Yangzhou, 225001, China
| | - Hao Ji
- Department of Clinical Medical College, Yangzhou University, Yangzhou, 225001, China
| | - Daorong Wang
- Department of General Surgery, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China
| | - Dong Tang
- Department of General Surgery, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China.
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Jiang M, Fang C, Ma Y. Prognosis Risk Model Based on Pyroptosis-Related lncRNAs for Gastric Cancer. Biomolecules 2023; 13:biom13030469. [PMID: 36979404 PMCID: PMC10046686 DOI: 10.3390/biom13030469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/29/2023] [Accepted: 02/27/2023] [Indexed: 03/08/2023] Open
Abstract
Gastric cancer (GC) is a malignant tumor with a low survival rate, high recurrence rate, and poor prognosis. With respect to this, pyroptosis is a type of programmed cell death that can affect the occurrence and development of tumors. Indeed, long non-coding RNAs (lncRNAs) were broadly applied for the purposes of early diagnosis, treatment, and prognostic analysis in regard to cancer. Based on the association of these three purposes, we developed a novel prognosis risk model based on pyroptosis-related lncRNAs (PRlncRNAs) for GC. The PRlncRNAs were obtained via univariate and multivariate Cox regression in order to build the predictive signatures. The Kaplan–Meier and gene set enrichment analysis (GSEA) methods were used to evaluate the overall survival (OS) and functional differences between the high- and low-risk groups. Moreover, the correlation of the signatures with immune cell infiltration was determined through single-sample gene set enrichment analysis (ssGSEA). Finally, we analyzed this correlation with the treatment responses in the GC patients; then, we performed quantitative reverse transcription polymerase chain reactions (qRT-PCRs) in order to verify the risk model. The high-risk group received a worse performance in terms of prognosis and OS when compared to the low-risk group. With respect to this, the area under the receiver operating characteristic curve (ROC) was found to be 0.808. Through conducting the GSEA, it was found that the high-risk groups possessed a significant enrichment in terms of tumor–immunity pathways. Furthermore, the ssGSEA revealed that the predictive features possessed strong associations with immune cell infiltration in regard to GC. In addition, we highlighted that anti-immune checkpoint therapy, combined with conventional chemotherapy drugs, may be more suitable for high-risk patients. The expression levels of LINC01315, AP003392.1, AP000695.2, and HAGLR were significantly different between the GC cell lines and the normal cell lines. As such, the six PRlncRNAs could be regarded as important prognostic biomarkers for the purposes of subsequent diagnoses, treatments, prognostic predictions, and the mechanism research of GC.
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Peng Z, Peng N. Microsomal glutathione S-transferase 1 targets the autophagy signaling pathway to suppress ferroptosis in gastric carcinoma cells. Hum Exp Toxicol 2023; 42:9603271231172915. [PMID: 37161854 DOI: 10.1177/09603271231172915] [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: 05/11/2023]
Abstract
OBJECTIVE Ferroptosis is a newly discovered form of programmed cell death; however, the specific mechanisms that regulate ferroptosis have yet to be fully elucidated in gastric carcinoma. In this study, we aimed to investigate how microsomal glutathione S-transferase 1 (MGST1) regulates ferroptosis in gastric carcinoma cells. METHODS Gastric adenocarcinoma (SGC7901) cells that overexpressed MGST1 or expressed only low levels of MGST1, were treated with specific compounds (erastin, sorafenib, RSL3, MK-2206 and SC79). Then, we detected the levels of malondialdehyde (MDA), glutathione (GSH), iron and reactive oxygen species (ROS). Protein expression levels of the non-classical autophagy and protein kinase B (Akt)/glycogen synthase kinase-3β (GSK-3β) pathways were determined by western blotting and cell viability was analyzed by Cell Counting Kit-8 (CCK-8) assays. The expressions of target genes were detected using qRT-PCR. RESULTS We evaluated a range of ferroptosis-inducing compounds and found that MGST1 expression was down-regulated during ferroptosis in SGC7901 cells. The ferroptosis inducer RSL3 played a role in classical ferroptotic events while the overexpression of MGST1 impaired these effects. Interestingly, the overexpression of MGST1 resulted in the inactivation of autophagy by repressing the expression of ATG16L1 and the conversion of LC3-I to LC3-II. The upregulation of ATG16L1 eliminated the inhibitory action of MGST1 on ferroptosis. Notably, the overexpression of MGST1 induced the activation of the Akt/GSK-3β pathway. An Akt inhibitor antagonized the inhibitory effects of MGST1 on autophagy and ferroptosis. CONCLUSION Collectively, our findings demonstrate a novel molecular mechanism and signaling pathway for ferroptosis. We also characterized that the overexpression of MGST1 induces gastric carcinoma cell proliferation by activating the Akt/GSK-3β signaling pathway.
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Affiliation(s)
- Z Peng
- Department of Clinical Laboratory, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, People's Republic of China
- Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention Hubei, Huangshi, People's Republic of China
| | - N Peng
- Department of Clinical Laboratory, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, People's Republic of China
- Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention Hubei, Huangshi, People's Republic of China
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Li J, Kong C, Song W, Fu T. Identification of Cuproptosis-Related Subtypes, Establishment of a Prognostic Signature and Characterization of the Tumor Microenvironment in Gastric Cancer. Int J Gen Med 2023; 16:1631-1652. [PMID: 37168531 PMCID: PMC10164657 DOI: 10.2147/ijgm.s404847] [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: 01/26/2023] [Accepted: 04/19/2023] [Indexed: 05/13/2023] Open
Abstract
Purpose Cuproptosis is a newly identified form of programmed cell death. We aimed to comprehensively discuss the correlation of cuproptosis with gastric cancer (GC) using bioinformatic methods. Patients and Methods This study selected GC bulk and single-cell RNA sequencing profiles from public databases. Based on the enrichment pattern of cuproptosis-related gene sets (CRGSs), GC patients were classified into different cuproptosis subtypes. A series of systematic analyses was performed to investigate the correlation of cuproptosis subtype with biological function and immune cell infiltration. In addition, we established a CRGS risk score signature to quantify GC patients' risk level, and analyzed the signature's relationship with clinical features, tumor microenvironment (TME) and treatment responses. Genes used for the construction of the risk score model were also detected in GC tumor and normal tissues by real-time quantitative polymerase chain reaction (RT-qPCR). Results First, analysis of scRNA-seq data revealed the alterations in CRGS enrichment scores for patients with GC and precancerous diseases. Then, based on large GC patient cohorts, two cuproptosis subtypes with significant differences in survival, biological function and TME were identified. Furthermore, we established a CRGS risk score signature. High-risk patients on the CRGS risk score signature with worse overall survival were characterized by higher immune and stromal contents in the TME, more advanced clinicopathological features, and better sensitivity to a wider range of anti-tumor drugs. Low-risk patients were correlated with higher tumor purity, and demonstrated more favorable clinical outcomes and higher sensitivity to immunotherapy. Conclusion The current work elucidated that cuproptosis plays an important role in the regulation of TME landscapes in GC. Two cuproptosis subtypes with distinct TME characteristics were identified. In addition, the establishment of a CRGS risk score signature could provide novel insights into accurate prediction and personalized treatment for GC patients.
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Affiliation(s)
- Jiazheng Li
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
| | - Can Kong
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
| | - Wei Song
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
| | - Tao Fu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
- Department of General Surgery, Qingdao Municipal Hospital, Qingdao, People’s Republic of China
- Correspondence: Tao Fu, Email
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Zheng Q, Gong Z, Lin S, Ou D, Lin W, Shen P. Integrated Analysis of a Competing Endogenous RNA Network Reveals a Ferroptosis-related 6-LncRNA Prognostic Signature in Clear Cell Renal Cell Carcinoma.. [DOI: 10.21203/rs.3.rs-2294111/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Abstract
Background: This study set out to elucidate the biological functions and prognostic role of ferroptosis-related lncRNAs based on a synthetic analysis of competing endogenous RNA (ceRNA) networks in clear cell renal cell carcinoma (ccRCC).
Methods: Ferroptosis-related genes were obtained from the FerrDb database. The expression data and matched clinical information of lncRNAs, miRNAs, and mRNAs from The Cancer Genome Atlas (TCGA) database were obtained to identify differentially expressed RNAs (DERNAs). The lncRNA-miRNA-mRNA ceRNA network was established utilizing the common miRNAs that were predicted in the RNAHybrid, StarBase, and TargetScan databases. Then, by progressive univariate Cox regression, LASSO,and multivariate Cox regression analysis of gene expression data and clinical information, a ferroptosis-related lncRNA prognosis signature was constructed based on the lncRNAs in ceRNA. Finally, the influence of independent lncRNAs on ccRCC was explored through a series of functional and unsupervised cluster analysis.
Results: A total of 35 ferroptosis-related DEmRNAs, 356 DElncRNAs, and 132 DEmiRNAs were sorted out from the KIRC cohort of TCGA database. Overlapping DElncRNA-DEmiRNA and DEmiRNA-DEmRNA interactions among the RNAHybrid, StarBase, and TargetScan databases were constructed and identified, then a ceRNA network with 77 axes related to ferroptosis was established utilizing mutual DEmiRNAs in two interaction networks as nodes. Through synthetic analysis of the expression data and clinical information of 27 lncRNAs in the ceRNA network, a 6-ferroptosis-lncRNA signature including PVT1, CYTOR, MIAT, SNHG17, LINC00265, and LINC00894 was identified in the training set. Kaplan-Meier, PCA, t-SNE analysis, risk score curve, and ROC curve were performed to confirm the validity of the signature in the training set and secondly verified in the validation set. Finally, ssGSEA and ESTIMATE analysis showed that the signature was related with immune cell infiltration and could predict immune-related phenotypes.
Conclusions: Our research underlines the role of the 6-ferroptosis-lncRNA signature as a predictor of prognosis and a therapeutic alternative for KIRC.
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Affiliation(s)
- Qing Zheng
- The First Affiliated Hospital of Shantou University Medical College
| | - Zhenqi Gong
- The First Affiliated Hospital of Shantou University Medical College
| | - Shaoxiong Lin
- The First Affiliated Hospital of Shantou University Medical College
| | - Dehua Ou
- The First Affiliated Hospital of Shantou University Medical College
| | - Weilong Lin
- The First Affiliated Hospital of Shantou University Medical College
| | - Peilin Shen
- The First Affiliated Hospital of Shantou University Medical College
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13
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Ding D, Zhao Y, Su Y, Yang H, Wang X, Chen L. Prognostic value of antitumor drug targets prediction using integrated bioinformatic analysis for immunogenic cell death-related lncRNA model based on stomach adenocarcinoma characteristics and tumor immune microenvironment. Front Pharmacol 2022; 13:1022294. [PMID: 36313374 PMCID: PMC9614277 DOI: 10.3389/fphar.2022.1022294] [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: 08/18/2022] [Accepted: 09/22/2022] [Indexed: 01/05/2023] Open
Abstract
Stomach adenocarcinoma (STAD) ranks as the fourth prevalent cause of mortality worldwide due to cancer. The prognosis for those suffering from STAD was bleak. Immunogenic cell death (ICD), a form of induced cellular death that causes an adaptive immune response and has increasing in anticancer treatment. However, it has not been ascertained how ICD-related lncRNAs affect STAD. Using univariate Cox regression and the TCGA database, lncRNAs with prognostic value were identified. Thereafter, we created a prognostic lncRNA-based model using LASSO. Kaplan-Meier assessment, time-dependent receiver operating characteristic (ROC) analyzation, independent prognostic investigation, and nomogram were used to assess model correctness. Additional research included evaluations of the immunological microenvironment, gene set enrichment analyses (GSEA), tumor mutation burdens (TMBs), tumor immune dysfunctions and exclusions (TIDEs), and antitumor compounds IC50 predictions. We found 24 ICD-related lncRNAs with prognostic value via univariate Cox analysis (p < 0.05). Subsequently, a risk model was proposed using five lncRNAs relevant to ICD. The risk signature, correlated with immune cell infiltration, had strong predictive performance. Individuals at low-risk group outlived those at high risk (p < 0.001). An evaluation of the 5-lncRNA risk mode including ROC curves, nomograms, and correction curves confirmed its predictive capability. The findings of functional tests revealed a substantial alteration in immunological conditions and the IC50 sensitivity for the two groups. Using five ICD-related lncRNAs, the authors developed a new risk model for STAD patients that could predict their cumulative overall survival rate and guide their individual treatment.
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Affiliation(s)
- Dayong Ding
- Department of Gastrointestinal and Colorectal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Yan Zhao
- Department of Operating Room, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Yanzhuo Su
- Department of Gastrointestinal and Colorectal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Huaixi Yang
- Department of Gastrointestinal and Colorectal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Xuefeng Wang
- Department of Gastrointestinal and Colorectal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Lin Chen
- Department of Gastrointestinal and Colorectal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
- *Correspondence: Lin Chen,
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14
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Zhang X, Wang C, Liu Z, Si Y. Identification of m6A-related long non-coding RNAs for predicting prognosis and immune characterizations in gastric cancer. Front Genet 2022; 13:1011716. [PMID: 36226190 PMCID: PMC9548545 DOI: 10.3389/fgene.2022.1011716] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 09/12/2022] [Indexed: 12/16/2022] Open
Abstract
Background: N6-methyladenosine (m6A) mRNA modification triggers malignant behavior in tumor cells, which promotes malignant progression and migration of gastric cancer (GC). Nevertheless, studies on the prognostic value of m6A-related long non-coding RNA (MRlncRNA) in GC remain quite restricted. The study aimed to develop a reasonable predictive model to explore the prognostic potential of MRlncRNAs in predicting the prognosis of GC patients and monitoring the efficacy of immunotherapy. Methods: Transcriptomic and clinical data for GC were derived from TCGA. Next, univariate Cox, LASSO and multivariate Cox regression analyses were next used to identify prognostic MRlncRNAs, calculate risk scores and build risk assessment models. The predictive power of the risk models was then validated by Kaplan-Meier analysis, ROC curves, DCA, C-index, and nomogram. We attempted to effectively differentiate between groups in terms of immune cell infiltration status, ICI-related genes, immunotherapy responses, and common anti-tumor drug sensitivity. Results: A risk model based on 11 MRlncRNAs was developed with an AUC of 0.850, and the sensitivity and specificity of this model in predicting survival probability is satisfactory. The Kaplan-Meier analysis revealed that the low-risk group in the model had a significantly higher survival rate, and the model was highly associated with survival status, clinical features, and clinical stage. Furthermore, the model was verified to be an independent prognostic risk factor, and the low-risk group in the model had a remarkable positive correlation with a variety of immune cell infiltrates. The expression levels of ICI-related genes differed significantly between the different groups. Lastly, immunotherapy responses and common anti-tumor drug sensitivity also differed significantly between different groups. Conclusion: The risk model on the basis of 11-MRlncRNAs can serve as independent predictors of GC prognosis and may be useful in developing personalized treatment strategies for patients.
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Affiliation(s)
- Xianhui Zhang
- Department of CT, The XingTai People’s Hospital, Xingtai, China
| | - Changjing Wang
- Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zhongxin Liu
- Department of Pathology, The XingTai People’s Hospital, Xingtai, China
| | - Yuan Si
- Endoscopic Center, The XingTai People’s Hospital, Xingtai, China
- *Correspondence: Yuan Si,
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15
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Lu J, Tan J, Yu X. A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer. Front Genet 2022; 13:934196. [PMID: 36118850 PMCID: PMC9470855 DOI: 10.3389/fgene.2022.934196] [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: 05/02/2022] [Accepted: 06/13/2022] [Indexed: 11/28/2022] Open
Abstract
Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed ferroptosis-related lncRNAs using the differential expression and gene co-expression analysis. Then, univariate and multivariate Cox regression analyses were used to identify the effective ferroptosis-related lncRNAs for constructing the prognostic model for CC. Gene set enrichment analysis (GSEA) was conducted to explore the functional enrichment analysis. CIBERSORT and single-sample GSEA were performed to investigate the association between our model and the immune microenvironment. Finally, three ferroptosis-related lncRNAs (XXbac-B476C20.9, TP73-AS1, and SNHG15) were identified to construct the prognostic model. The results of the validation showed that our model was effective in predicting the prognosis of CC patients, which also was an independent prognostic factor for CC. The GSEA analysis showed that several ferroptosis-related pathways were significantly enriched in the low-risk group. Immune infiltration analysis suggested that the level of immune cell infiltration was significantly higher in the high-risk group than that in the low-risk group. In summary, we established a prognostic model based on the ferroptosis-related lncRNAs, which could provide clinical guidance for future laboratory and clinical research on CC.
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16
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Cell death affecting the progression of gastric cancer. Cell Death Dis 2022; 8:377. [PMID: 36038533 PMCID: PMC9424204 DOI: 10.1038/s41420-022-01161-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/04/2022] [Accepted: 08/08/2022] [Indexed: 12/07/2022]
Abstract
Gastric cancer is a gastrointestinal tumor with high morbidity and mortality rates. Several factors influence its progression, cell death being an important element. In this review, we summarized the effects of necrosis, apoptosis, necroptosis, pyroptosis, ferroptosis, and eight less common cell death modalities on gastric cancer cells and the tumor microenvironment, detailed the molecular mechanisms of various cell death and their major regulatory pathways in gastric cancer, explored the prevalence and complexity of cell death in gastric cancer progression and highlighted the potentials of cell death-related therapies in gastric cancer.
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17
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Lu L, Chen B, Xu Y, Zhang X, Jin L, Qian H, Wang Y, Liang ZF. Role of ferroptosis and ferroptosis-related non-coding RNAs in the occurrence and development of gastric cancer. Front Pharmacol 2022; 13:902302. [PMID: 36046827 PMCID: PMC9421149 DOI: 10.3389/fphar.2022.902302] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 06/28/2022] [Indexed: 01/17/2023] Open
Abstract
Gastric cancer (GC) is a malignant cancer of the digestive tract and is a life-threatening disease worldwide. Ferroptosis is a newly discovered form of regulated cell death, which involves the accumulation of iron-dependent lipid peroxides. It has been found that ferroptosis plays an important regulatory role in the occurrence, development, drug resistance, and prognosis of GC. Non-coding RNAs (ncRNAs) play a critical role in the occurrence and progression of a variety of diseases including GC. In recent years, the role of ferroptosis and ferroptosis-related ncRNAs (miRNA, lncRNA, and circRNA) in the occurrence, development, drug resistance, and prognosis of GC has attracted more and more attention. Herein, we briefly summarize the roles and functions of ferroptosis and ferroptosis-related ncRNAs in GC tumorigenesis, development, and prognosis. We also prospected the future research direction and challenges of ferroptosis and ferroptosis-related ncRNAs in GC.
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Affiliation(s)
- Ling Lu
- Child Healthcare Department, The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, JS, China
| | - Bei Chen
- Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, JS, China
- Suzhou Science and Technology Town Hospital, Suzhou, JS, China
| | - Yumeng Xu
- Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, JS, China
| | - Xinyi Zhang
- Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, JS, China
| | - Longtao Jin
- Child Healthcare Department, The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, JS, China
| | - Hui Qian
- Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, JS, China
| | - Yi Wang
- Department of Urology, the Second Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Yi Wang, ; Zhao Feng Liang,
| | - Zhao Feng Liang
- Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, JS, China
- *Correspondence: Yi Wang, ; Zhao Feng Liang,
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18
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Geng H, Qian R, Zhang L, Yang C, Xia X, Wang C, Zhao G, Zhang Z, Zhu C. Clinical outcomes and potential therapies prediction of subgroups based on a ferroptosis-related long non-coding RNA signature for gastric cancer. Aging (Albany NY) 2022; 14:6358-6376. [PMID: 35969182 PMCID: PMC9417219 DOI: 10.18632/aging.204227] [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: 11/10/2021] [Accepted: 07/26/2022] [Indexed: 01/17/2023]
Abstract
Background: Gastric cancer (GC) is one of the most aggressive malignant tumors worldwide. Ferroptosis is a kind of iron-dependent cell death, which is proved to be closely related to tumor progression. In this study, we aim at constructing a ferroptosis-related lncRNAs signature to predict the prognosis of GC and explore potential therapies. Methods: Ferroptosis-Related LncRNAs Signature for GC patients (FRLSG) was constructed through univariate Cox regression, the LASSO algorithm, and multivariate Cox regression. Kaplan–Meier analysis, receiver operating characteristic curves, and risk score plot were applied to verify the predictive power of FRLSG. Gene Set Enrichment Analysis (GSEA) and immune infiltration analyses were conducted to explore the potential clinical value of the FRLSG. In addition, drug sensitivity prediction was applied to identify chemotherapeutic drugs with potential therapeutic effect. Results: Five ferroptosis-related lncRNAs (AC004816.1, AC005532.1, LINC01357, AL355574.1 and AL049840.4) were identified to construct FRLSG, whose expression level in GC were confirmed by experimental validation. Kaplan-Meier curve and ROC curve proved the reliability and effectiveness of the FRLSG in predicting the prognosis for GC patients. Several immune-related pathways were enriched in the high-FRLSG group, and further immune infiltration analyses demonstrated the high immune infiltration status of the high-FRLSG group. In addition, 19 and 24 candidate drugs with potential therapeutic effect were identified for the high- and low-FRLSG groups, respectively. Conclusions: FRLSG was an effective tool in predicting the prognosis of GC, which might help to prioritize potential therapeutics for GC patients.
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Affiliation(s)
- Haigang Geng
- Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ruolan Qian
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Linmeng Zhang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chen Yang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiang Xia
- Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Cun Wang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Gang Zhao
- Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zizhen Zhang
- Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunchao Zhu
- Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:2754836. [PMID: 35965688 PMCID: PMC9372539 DOI: 10.1155/2022/2754836] [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: 02/06/2022] [Revised: 06/26/2022] [Accepted: 06/29/2022] [Indexed: 12/26/2022]
Abstract
Uterine corpus endometrial carcinoma (UCEC) is a malignant disease that, at present, has no well-characterised prognostic biomarker. In this study, two clusters were identified based on 28 N1-methyladenosine- (m1A-) related long noncoding RNAs (lncRNAs), of which cluster 1 was related to immune pathways according to the results of an enrichment analysis. We further observed better prognosis in patients with higher levels of immune cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoint gene expression. In addition, through Cox regression analysis and least absolute shrinkage and selection operator regression analysis, 10 m1A-related lncRNAs (mRLs) were employed to build a prognosis model. We found that people in higher risk categories had a poorer survival probability than those in lower risk. Low-risk samples were enriched with immune-related pathways, while the high-risk group was similar to the definition of the “immune desert” phenotype, which was associated with decreased immune infiltration, T cell failure, and decreased tumor mutation burden, while also being insensitive to immunotherapy and chemotherapy. This mRL-based model has the ability to accurately predict the prognosis of UCEC patients, and the mRLs could become promising therapeutic targets in enhancing the response of immunotherapy.
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20
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Zhou W, Zhang W. A novel pyroptosis-related lncRNA prognostic signature associated with the immune microenvironment in lung squamous cell carcinoma. BMC Cancer 2022; 22:694. [PMID: 35739504 PMCID: PMC9229145 DOI: 10.1186/s12885-022-09790-z] [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: 04/26/2022] [Accepted: 06/16/2022] [Indexed: 11/18/2022] Open
Abstract
Background A growing body of evidence suggests that pyroptosis-related lncRNAs (PRncRNAs) are associated with the prognoses of tumor patients and their tumor immune microenvironments. However, the function of PRlncRNAs in lung squamous cell carcinoma (LUSC) remains unclear. Methods We downloaded the transcriptome and clinical information of 551 LUSC samples from the The Cancer Genome Atlas (TCGA) database and randomly separated patients with complete information into two cohorts. Based on the training cohort, we developed a pyroptosis-related signature. We then examined the signature in the test cohort and all retained patients. We also clustered two risk groups in each cohort according to the signature and performed survival analysis, functional analysis, tumor immune microenvironment analysis and drug sensitivity analysis. Results A prognostic signature containing five PRlncRNAs (AP001189.1, PICART1, LINC02555, AC010422.4, and AL606469.1) was developed. A principal component analysis (PCA) indicated better differentiation between patients with different risk scores. Kaplan–Meier (K–M) analysis demonstrated poorer survival among patients with higher risk scores (P < 0.001). A receiver operating characteristic (ROC) curve analysis provided evidence confirming the accuracy of the signature, and univariate (p = 0.005) and multivariate (p = 0.008) Cox regression analyses confirmed the independent value of the risk score in prognoses. Clinical subgroup validation indicated that the signature was more suitable for patients with early-stage LUSC. We also created a nomogram to increase the accuracy of the prediction. Moreover, functional analysis revealed that pathways related to tumor development and pyroptosis were enriched in the high-risk group. Furthermore, the prognostic signature was proven to be a predictor of sensitivity to immunotherapy and chemotherapy. Conclusions We developed a novel pyroptosis-associated signature with independent value for the prognosis of LUSC patients. PRlncRNAs are closely associated with the tumor immune microenvironment in LUSC and might offer new directions for immunotherapy. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09790-z.
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Affiliation(s)
- Wei Zhou
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, 1 Minde Road, 330006, Nanchang, China.,Jiangxi medical college, Nanchang University, 330006, Nanchang, China
| | - Wenxiong Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, 1 Minde Road, 330006, Nanchang, China.
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21
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The Value of m5C-Related lncRNAs in the Prognostic Assessment and Immunotherapy of Stomach Adenocarcinoma. BIOMED RESEARCH INTERNATIONAL 2022; 2022:2747799. [PMID: 35711526 PMCID: PMC9197623 DOI: 10.1155/2022/2747799] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/24/2022] [Indexed: 12/16/2022]
Abstract
Long noncoding RNAs (lncRNAs) are closely associated with a variety of tumors, including stomach adenocarcinoma (STAD). However, the role of 5-methylcytosine- (m5C-) related lncRNAs in STAD is still uncertain. This study investigated the value of m5C-related lncRNAs in prognostic evaluation and immunotherapy of STAD. STAD transcriptome sequencing data were downloaded from The Cancer Genome Atlas (TCGA) database, and m5C-related lncRNAs were screened by Pearson correlation analysis. A prognostic m5C-related lncRNA signature (m5CRLSig) associated with STAD was established using univariate and multivariate Cox regression analysis. We constructed a prognostic risk model for STAD with six m5C-related lncRNAs. The receiver operating characteristic (ROC) curve was used to examine the predictive efficacy. Univariate and multifactorial Cox regression analysis and principal component analysis (PCA) validated m5CRLSig as an independent factor of STAD prognosis. The clinicopathological characteristics of the model showed higher risk scores for stages II-IV, grade 3, N1-3, and death status. The calibration curve of a nomogram revealed that the nomogram had an excellent predictive function for survival risk. Furthermore, the expression of six m5C-related lncRNAs in STAD and paracancerous tissues was detected by quantitative real-time PCR (qRT-PCR), which verified the feasibility of the m5CRLSig as a prognostic marker for STAD. m5C-related lncRNAs were linked to multiple immune-associated pathways, according to gene set enrichment analysis (GSEA). CIBERSORT analysis indicated that m5CRLSig was involved in immune cell infiltration. Risk score was associated with immune checkpoint gene expression, immune function scores, and chemotherapeutic drug sensitivity. Therefore, m5CRLSig can efficiently assess the prognosis of STAD patients and can be used as a biological marker for immunotherapy.
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22
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Li J, Xiang R, Song W, Wu J, Kong C, Fu T. A Novel Ferroptosis-Related LncRNA Pair Prognostic Signature Predicts Immune Landscapes and Treatment Responses for Gastric Cancer Patients. Front Genet 2022; 13:899419. [PMID: 35795206 PMCID: PMC9250987 DOI: 10.3389/fgene.2022.899419] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 05/04/2022] [Indexed: 12/22/2022] Open
Abstract
Background: The construction of ferroptosis-related lncRNA prognostic models in malignancies has been an intense area of research recently. However, most of the studies focused on the exact expression of lncRNAs and had limited application values. Herein, we aim to establish a novel prognostic model for gastric cancer (GC) patients and discuss its correlation with immune landscapes and treatment responses.Methods: The present study retrieved transcriptional data of GC patients from the Cancer Genome Atlas (TCGA) database. We identified differentially expressed ferroptosis-related lncRNAs between tumor and normal controls of GC samples. Based on a new method of cyclically single pairing, we constructed a 0 or 1 matrix of ferroptosis-related lncRNA pairs (FRLPs). A risk score signature consisting of 10 FRLPs was established using multi-step Cox regression analysis. Next, we performed a series of systematic analyses to investigate the association of the FRLP model and tumor microenvironment, biological function, and treatment responses. An alternative model to the FRLP risk score signature, the gene set score (GS) model was also constructed, which could represent the former when lncRNA expression was not available.Results: We established a novel prognostic signature of 10 ferroptosis-related lncRNA pairs. High-risk patients in our risk score model were characterized by high infiltration of immune cells, upregulated carcinogenic and stromal activities, and heightened sensitivity to a wide range of anti-tumor drugs, whereas low-risk patients were associated with better responses to methotrexate treatment and elevated immunotherapeutic sensitivity. The practicability of the FRLP risk score model was also validated in two independent microarray datasets downloaded from Gene Expression Omnibus (GEO) using the GS model. Finally, two online dynamic nomograms were built to enhance the clinical utility of the study.Conclusion: In this study, we developed a ferroptosis-related lncRNA pair-based risk score model that did not rely on the exact lncRNA expression level. This novel model might provide insights for the accurate prediction and comprehensive management for GC patients.
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23
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Fan Z, Wang Y, Niu R. Identification of the three subtypes and the prognostic characteristics of stomach adenocarcinoma: analysis of the hypoxia-related long non-coding RNAs. Funct Integr Genomics 2022; 22:919-936. [PMID: 35665866 DOI: 10.1007/s10142-022-00867-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 11/29/2022]
Abstract
Stomach adenocarcinoma (STAD) is one of the most commonly diagnosed cancers. This study analyzed the subtypes and characteristics of STAD subtypes by analyzing hypoxia pathway-related lncRNAs. Potential hub lncRNAs were found and a prognostic model was constructed. Expression profiling data and clinical information of STAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Metabolic pathway scores were calculated using single-sample gene set enrichment analysis (ssGSEA) method. Tumor immune microenvironment scores of the samples were assessed by ESTIMATE, MCP-counter, and ssGSEA. Functional analysis of lncRNAs, construction of risk models, and drug sensitivity analysis were performed. Pathway analysis revealed that the hypoxia pathway was a prognostic risk factor. Molecular subtypes were developed based on the hypoxia score-related lncRNAs. Three molecular subtypes (C1, C2, and C3) for gastric STAD were determined. The worst prognosis was in the C2, which was also characterized by the maximum hypoxia pathway-related scores and the maximum immune score. A majority of the immune checkpoints and chemokines were high-expressed in the C2 subtype. Mutations in the C2 subtype were significantly lower than the C1 and C3 subtypes. The subtypes differed in terms of functional and metabolic pathways. Eight hub indicator lncRNAs (MSC-AS1, AC037198.1, LINC00968, AL139393.3, LINC02544, BOLA3-AS1, MIR1915HG, and AC107021.2) capable of predicting patient prognosis were identified. Three hypoxia lncRNA-related molecular subtypes characterized by different prognostic and immune conditions were identified. The results maybe can provide a theoretical basis to improve the clinical diagnosis and treatment of STAD.
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Affiliation(s)
- Zehua Fan
- Information Institute, Huazhong Agricultural University, 1 Shizishan Street, Hongshan District, Wuhan City, 420100, Hubei Province, China. .,School of Information Engineering, Tarim University, 705 Hongqiao Road, Alar City, 659002, Xinjiang Uygur Autonomous Region, China.
| | - Yanqun Wang
- Information Institute, Huazhong Agricultural University, 1 Shizishan Street, Hongshan District, Wuhan City, 420100, Hubei Province, China.,School of Information Engineering, Tarim University, 705 Hongqiao Road, Alar City, 659002, Xinjiang Uygur Autonomous Region, China
| | - Rong Niu
- Information Institute, Huazhong Agricultural University, 1 Shizishan Street, Hongshan District, Wuhan City, 420100, Hubei Province, China.,School of Information Engineering, Tarim University, 705 Hongqiao Road, Alar City, 659002, Xinjiang Uygur Autonomous Region, China
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24
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Yang X, Mei M, Yang J, Guo J, Du F, Liu S. Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma. Aging (Albany NY) 2022; 14:4069-4084. [PMID: 35550563 PMCID: PMC9134948 DOI: 10.18632/aging.204073] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 05/02/2022] [Indexed: 11/25/2022]
Abstract
Background: Hepatocellular Carcinoma (HCC) is a highly heterogeneous malignant tumor, and its prognostic prediction is extremely challenging. Ferroptosis is a cell mechanism dependent on iron, which is very significant for HCC development. Long non-coding RNA (lncRNA) is also linked to HCC progression. This work aimed to establish a prognosis risk model for HCC and to discover a possible biomarker and therapeutic target. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq transcriptome data and clinic information of HCC patients. Firstly, univariate Cox was utilized to identify 66 prognostic ferroptosis-related lncRNAs. Then, the identified lncRNAs were further included in the multivariate Cox analysis to construct the prognostic model. Eventually, we performed quantitative polymerase chain reaction (q-PCR) to validate the risk model. Results: We established a prognostic seventeen-ferroptosis-related lncRNA signature model. The signature could categorize patients into two risk subgroups, with the low-risk subgroup associated with a better prognosis. Additionally, the area under the curve (AUC) of the lncRNAs signature was 0.801, indicating their reliability in forecasting HCC prognosis. Risk score was an independent prognostic factor by regression analyses. Gene set enrichment analysis (GSEA) analyses demonstrated a remarkable enrichment of cancer-related and immune-related pathways in the high-risk group. Besides, the immune status was decreased in the high-risk group. Eventually, three prognostic lncRNAs were validated in human HCCLM3 cell lines. Conclusions: The risk model based on seventeen-ferroptosis-related lncRNA has significant prognostic value for HCC and may be therapeutic targets associated with ferroptosis in clinical ways.
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Affiliation(s)
- Xin Yang
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Minhui Mei
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingze Yang
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinlu Guo
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fan Du
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shi Liu
- Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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25
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Liang X, Yu G, Zha L, Guo X, Cheng A, Qin C, Zhang H, Wang Z. Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer. Front Cell Dev Biol 2022; 9:797341. [PMID: 35096827 PMCID: PMC8795836 DOI: 10.3389/fcell.2021.797341] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/28/2021] [Indexed: 12/19/2022] Open
Abstract
Gastric cancer (GC) is a malignant tumor with poor survival outcomes. Immunotherapy can improve the prognosis of many cancers, including GC. However, in clinical practice, not all cancer patients are sensitive to immunotherapy. Therefore, it is essential to identify effective biomarkers for predicting the prognosis and immunotherapy sensitivity of GC. In recent years, chemokines have been widely reported to regulate the tumor microenvironment, especially the immune landscape. However, whether chemokine-related lncRNAs are associated with the prognosis and immune landscape of GC remains unclear. In this study, we first constructed a novel chemokine-related lncRNA risk model to predict the prognosis and immune landscape of GC patients. By using various algorithms, we identified 10 chemokine-related lncRNAs to construct the risk model. Then, we determined the prognostic efficiency and accuracy of the risk model. The effectiveness and accuracy of the risk model were further validated in the testing set and the entire set. In addition, our risk model exerted a crucial role in predicting the infiltration of immune cells, immune checkpoint genes expression, immunotherapy scores and tumor mutation burden of GC patients. In conclusion, our risk model has preferable prognostic performance and may provide crucial clues to formulate immunotherapy strategies for GC.
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Affiliation(s)
- Xiaolong Liang
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Gangfeng Yu
- Institute of Life Sciences, Chongqing Medical University, Chongqing, China
| | - Lang Zha
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiong Guo
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Anqi Cheng
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chuan Qin
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Digestive Oncology, Three Gorges Hospital, Chongqing University, Chongqing, China
| | - Han Zhang
- Department of Digestive Oncology, Three Gorges Hospital, Chongqing University, Chongqing, China
| | - Ziwei Wang
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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