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Zhang L, Wang Y, Gao J, Zhou X, Huang M, Wang X, He Z. Non‑coding RNA: A promising diagnostic biomarker and therapeutic target for esophageal squamous cell carcinoma (Review). Oncol Lett 2024; 27:255. [PMID: 38646493 PMCID: PMC11027111 DOI: 10.3892/ol.2024.14388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 03/22/2024] [Indexed: 04/23/2024] Open
Abstract
Esophageal cancer (EC) is a common form of malignant tumor in the digestive system that is classified into two types: Esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinoma. ESCC is known for its early onset of symptoms, which can be difficult to identify, as well as its rapid progression and tendency to develop drug resistance to chemotherapy and radiotherapy. These factors contribute to the high incidence of disease and low cure rate. Therefore, a diagnostic biomarker and therapeutic target need to be identified for ESCC. Non-coding RNAs (ncRNAs) are a class of molecules that are transcribed from DNA but do not encode proteins. Initially, ncRNAs were considered to be non-functional segments generated during transcription. However, with advancements in high-throughput sequencing technologies in recent years, ncRNAs have been associated with poor prognosis, drug resistance and progression of ESCC. The present study provides a comprehensive overview of the biogenesis, characteristics and functions of ncRNAs, particularly focusing on microRNA, long ncRNAs and circular RNAs. Furthermore, the ncRNAs that could potentially be used as diagnostic biomarkers and therapeutic targets for ESCC are summarized to highlight their application value and prospects in ESCC.
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Affiliation(s)
- Longze Zhang
- Department of Immunology, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Yanyang Wang
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Department of Cell Engineering Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Jianmei Gao
- School of Pharmacy, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Xue Zhou
- Department of Immunology, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Minglei Huang
- Department of Immunology, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Xianyao Wang
- Department of Immunology, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Zhixu He
- Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Department of Cell Engineering Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
- Department of Pediatrics, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Yu XW, She PW, Chen FC, Chen YY, Zhou S, Wang XM, Lin XR, Liu QL, Huang ZJ, Qiu Y. Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies. BMC Cancer 2024; 24:230. [PMID: 38373930 PMCID: PMC10875771 DOI: 10.1186/s12885-024-11890-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND This study aimed to identify metabolic subtypes in ESCA, explore their relationship with immune landscapes, and establish a metabolic index for accurate prognosis assessment. METHODS Clinical, SNP, and RNA-seq data were collected from 80 ESCA patients from the TCGA database and RNA-seq data from the GSE19417 dataset. Metabolic genes associated with overall survival (OS) and progression-free survival (PFS) were selected, and k-means clustering was performed. Immune-related pathways, immune infiltration, and response to immunotherapy were predicted using bioinformatic algorithms. Weighted gene co-expression network analysis (WGCNA) was conducted to identify metabolic genes associated with co-expression modules. Lastly, cell culture and functional analysis were performed using patient tissue samples and ESCA cell lines to verify the identified genes and their roles. RESULTS Molecular subtypes were identified based on the expression profiles of metabolic genes, and univariate survival analysis revealed 163 metabolic genes associated with ESCA prognosis. Consensus clustering analysis classified ESCA samples into three distinct subtypes, with MC1 showing the poorest prognosis and MC3 having the best prognosis. The subtypes also exhibited significant differences in immune cell infiltration, with MC3 showing the highest scores. Additionally, the MC3 subtype demonstrated the poorest response to immunotherapy, while the MC1 subtype was the most sensitive. WGCNA analysis identified gene modules associated with the metabolic index, with SLC5A1, NT5DC4, and MTHFD2 emerging as prognostic markers. Gene and protein expression analysis validated the upregulation of MTHFD2 in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA. CONCLUSION The established metabolic index and identified metabolic genes offer potential for prognostic assessment and personalized therapeutic interventions for ESCA, underscoring the importance of targeting metabolism-immune interactions in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.
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Affiliation(s)
- Xiao-Wan Yu
- Clinical Laboratory Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China.
| | - Pei-Wei She
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, 350001, P. R. China
- Center for Experimental Research in Clinical Medicine, Fujian Provincial Hospital, 350001, Fuzhou, Fujian, P. R. China
| | - Fang-Chuan Chen
- Stomatology Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Ya-Yu Chen
- Stomatology Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Shuang Zhou
- Central Laboratory, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Xi-Min Wang
- Clinical Laboratory Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Xiao-Rong Lin
- Clinical Laboratory Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Qiao-Ling Liu
- Clinical Laboratory Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Zhi-Jun Huang
- Esophageal Surgery Department, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China
| | - Yu Qiu
- Reproductive Center, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, Fujian, P. R. China.
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Long Y, Mao C, Liu S, Tao Y, Xiao D. Epigenetic modifications in obesity-associated diseases. MedComm (Beijing) 2024; 5:e496. [PMID: 38405061 PMCID: PMC10893559 DOI: 10.1002/mco2.496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/27/2024] Open
Abstract
The global prevalence of obesity has reached epidemic levels, significantly elevating the susceptibility to various cardiometabolic conditions and certain types of cancer. In addition to causing metabolic abnormalities such as insulin resistance (IR), elevated blood glucose and lipids, and ectopic fat deposition, obesity can also damage pancreatic islet cells, endothelial cells, and cardiomyocytes through chronic inflammation, and even promote the development of a microenvironment conducive to cancer initiation. Improper dietary habits and lack of physical exercise are important behavioral factors that increase the risk of obesity, which can affect gene expression through epigenetic modifications. Epigenetic alterations can occur in early stage of obesity, some of which are reversible, while others persist over time and lead to obesity-related complications. Therefore, the dynamic adjustability of epigenetic modifications can be leveraged to reverse the development of obesity-associated diseases through behavioral interventions, drugs, and bariatric surgery. This review provides a comprehensive summary of the impact of epigenetic regulation on the initiation and development of obesity-associated cancers, type 2 diabetes, and cardiovascular diseases, establishing a theoretical basis for prevention, diagnosis, and treatment of these conditions.
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Affiliation(s)
- Yiqian Long
- Department of Pathology, Xiangya HospitalCentral South UniversityChangshaHunanChina
- Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Pathology, School of Basic MedicineCentral South UniversityChangshaHunanChina
| | - Chao Mao
- Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Pathology, School of Basic MedicineCentral South UniversityChangshaHunanChina
- NHC Key Laboratory of Carcinogenesis (Central South University), Cancer Research Institute and School of Basic MedicineCentral South UniversityChangshaChina
| | - Shuang Liu
- Department of Pathology, Xiangya HospitalCentral South UniversityChangshaHunanChina
- Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Pathology, School of Basic MedicineCentral South UniversityChangshaHunanChina
- Department of Oncology, Institute of Medical Sciences, National Clinical Research Center for Geriatric DisordersXiangya HospitalCentral South UniversityChangshaHunanChina
| | - Yongguang Tao
- Department of Pathology, Xiangya HospitalCentral South UniversityChangshaHunanChina
- Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Pathology, School of Basic MedicineCentral South UniversityChangshaHunanChina
- NHC Key Laboratory of Carcinogenesis (Central South University), Cancer Research Institute and School of Basic MedicineCentral South UniversityChangshaChina
- Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer, Department of Thoracic SurgerySecond Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Desheng Xiao
- Department of Pathology, Xiangya HospitalCentral South UniversityChangshaHunanChina
- Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Pathology, School of Basic MedicineCentral South UniversityChangshaHunanChina
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 841] [Impact Index Per Article: 841.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Xie T, Liu B, Liu D, Zhou Y, Yang Q, Wang D, Tang M, Liu W. Cuproptosis-related lncRNA signatures predict prognosis and immune relevance of kidney renal papillary cell carcinoma. Front Pharmacol 2022; 13:1103986. [PMID: 36618928 PMCID: PMC9810632 DOI: 10.3389/fphar.2022.1103986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
Kidney renal papillary cell carcinoma (KIRP) has a high mortality rate and a poor prognosis. Cu concentrations differed significantly between renal cancer tissues and adjacent normal tissues. Cuproptosis is a newly identified cell death. Long non-coding RNAs (lncRNAs) play a crucial role in the progression of KIRP. In this study, we focused on constructing and validating cuproptosis-related lncRNA signatures to predict the prognosis of KIRP patients and their immune correlation. We created prognosis models using Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. We found that patients in the high-risk group had poorer overall survival (OS) and progression-free survival (PFS) and higher mortality. Risk score and stage are prognosis factors independent of other clinical features. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and C-index curves showed that cuproptosis-related lncRNA signatures could more accurately predict the prognosis of patients. Functional enrichment analysis suggests that the function of differentially expressed genes (DEGs) is associated with KIRP development and immunity. In immune-related function analysis, we found a significant difference in parainflammation responses between high-risk and low-risk groups. The mutation frequencies of TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D genes in the high-risk group were higher than those in the low-risk group, but the mutation frequencies of MUC16, KIAA109, CUBN, USH2A, DNAH8 and HERC2 genes were significantly lower than those in the low-risk group. Survival analysis of tumor mutation burden (TMB) and combined TMB-risk showed better OS in patients with high TMB. Immune infiltration and immune checkpoint analysis assessed the immune association of six high mutation frequency genes (TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D) with KIRP. Finally, we performed a drug sensitivity analysis and screened 15 potential drugs that differed between high-risk and low-risk patients. In this study, we constructed and validated cuproptosis-related lncRNA signatures that can more accurately predict the prognosis of KIRP patients and provide new potential therapeutic targets and prognosis markers for KIRP patients.
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Affiliation(s)
- Tongjin Xie
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Bin Liu
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Dongbo Liu
- Department of Pharmacy, Zunyi Medical University, Zunyi, China
| | - Yusong Zhou
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Qingping Yang
- Department of Pharmacy, Zunyi Medical University, Zunyi, China
| | - Dai Wang
- Xiangya School of Pharmacy, Central South University, Changsha, China
| | - Mengjie Tang
- Department of Pathology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Wei Liu
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China,*Correspondence: Wei Liu,
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Zhao L, Teng Q, Liu Y, Chen H, Chong W, Du F, Xiao K, Sang Y, Ma C, Cui J, Shang L, Zhang R. Machine learning-based identification of a novel prognosis-related long noncoding RNA signature for gastric cancer. Front Cell Dev Biol 2022; 10:1017767. [PMID: 36438557 PMCID: PMC9691877 DOI: 10.3389/fcell.2022.1017767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/26/2022] [Indexed: 08/30/2023] Open
Abstract
Gastric cancer (GC) is one of the most common malignancies with a poor prognosis. Immunotherapy has attracted much attention as a treatment for a wide range of cancers, including GC. However, not all patients respond to immunotherapy. New models are urgently needed to accurately predict the prognosis and the efficacy of immunotherapy in patients with GC. Long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and progression of cancers. Recent studies have identified a variety of prognosis-related lncRNA signatures in multiple cancers. However, these studies have some limitations. In the present study, we developed an integrative analysis to screen risk prediction models using various feature selection methods, such as univariate and multivariate Cox regression, least absolute shrinkage and selection operator (LASSO), stepwise selection techniques, subset selection, and a combination of the aforementioned methods. We constructed a 9-lncRNA signature for predicting the prognosis of GC patients in The Cancer Genome Atlas (TCGA) cohort using a machine learning algorithm. After obtaining a risk model from the training cohort, we further validated the model for predicting the prognosis in the test cohort, the entire dataset and two external GEO datasets. Then we explored the roles of the risk model in predicting immune cell infiltration, immunotherapeutic responses and genomic mutations. The results revealed that this risk model held promise for predicting the prognostic outcomes and immunotherapeutic responses of GC patients. Our findings provide ideas for integrating multiple screening methods for risk modeling through machine learning algorithms.
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Affiliation(s)
- Linli Zhao
- Department of Ultrasound, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Qiong Teng
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yuan Liu
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Hao Chen
- Clinical Epidemiology Unit, Clinical Research Center of Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Wei Chong
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Key Laboratory of Engineering of Shandong Province, Shandong Provincial Hospital, Jinan, Shandong, China
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Fengying Du
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Kun Xiao
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yaodong Sang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Chenghao Ma
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Jian Cui
- BioGeniusCloud, Shanghai BioGenius Biotechnology Center, Shanghai, China
| | - Liang Shang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Ronghua Zhang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
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Zhu J, Zhao Y, Wu G, Zhang X, Chen Q, Yang B, Guo X, Ji S, Gu K, Ghose J. Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma. Oxidative Medicine and Cellular Longevity 2022; 2022:1-29. [PMID: 35903713 PMCID: PMC9315452 DOI: 10.1155/2022/7465880] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 06/27/2022] [Indexed: 12/17/2022]
Abstract
Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.
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Liu Y, Li C, Fang L, Wang L, Liu H, Tian H, zheng Y, Fan T, He J. Lipid metabolism-related lncRNA SLC25A21-AS1 promotes the progression of oesophageal squamous cell carcinoma by regulating the NPM1/c-Myc axis and SLC25A21 expression. Clin Transl Med 2022; 12:e944. [PMID: 35735113 PMCID: PMC9218933 DOI: 10.1002/ctm2.944] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 05/31/2022] [Accepted: 06/07/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Obesity alters metabolic microenvironment and is thus associated with several tumours. The aim of the present study was to investigate the role, molecular mechanism of action, and potential clinical value of lipid metabolism-related long non-coding RNA (lncRNA) SLC25A21-AS1 in oesophageal squamous cell carcinoma (ESCC). METHODS A high-fat diets (HFDs)-induced obesity nude mouse model was established, and targeted metabolomics analysis was used to identify critical medium-long chain fatty acids influencing the growth of ESCC cells. Transcriptomic analysis of public dataset GSE53625 confirmed that lncRNA SLC25A21-AS1 was a lipid metabolism-related lncRNA. The biological function of lncRNA SLC25A21-AS1 in ESCC was investigated both in vivo and in vitro. Chromatin immunoprecipitation(ChIP)assay, RNA-pull down, mass spectrometry, co-IP, and RNA IP(RIP) were performed to explore the molecular mechanism. Finally, an ESCC cDNA microarray was used to determine the clinical prognostic value of SLC25A21-AS1 by RT-qPCR. RESULTS Palmitic acid (PA) is an important fatty acid component of HFD and had an inhibitory effect on ESCC cell lines. LncRNA SLC25A21-AS1 expression was downregulated by PA and associated with the proliferation and migration of ESCC cells in vitro and in vivo. Mechanistically, SLC25A21-AS1 interacted with nucleophosmin-1 (NPM1) protein to promote the downstream gene transcription of the c-Myc in the nucleus. In the cytoplasm, SLC25A21-AS1 maintained the stability of SLC25A21 mRNA and reduced the intracellular NAD+ /NADH ratio by influencing tryptophan catabolism. Finally, we demonstrated that high expression of SLC25A21-AS1 promoted resistance to cisplatin-induced apoptosis and was correlated with poor tumour grade and overall survival. CONCLUSIONS HFD/PA has an inhibitory effect on ESCC cells and SLC25A21-AS1 expression. SLC25A21-AS1 promotes the proliferation and migration of ESCC cells by regulating the NPM1/c-Myc axis and SLC25A21 expression. In addition, lncRNA SLC25A21-AS1 may serve as a favourable prognostic biomarker and a potential therapeutic target for ESCC.
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Affiliation(s)
- Yu Liu
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Chunxiang Li
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Lingling Fang
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Liyu Wang
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Hengchang Liu
- Department of Colorectal SurgeryNational Cancer Center/Natbibional Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - He Tian
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yujia zheng
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Tao Fan
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Jie He
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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10
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Wang H, Cui J, Yu J, Huang J, Li M. Identification of Fatty Acid Metabolism-Related lncRNAs as Biomarkers for Clinical Prognosis and Immunotherapy Response in Patients With Lung Adenocarcinoma. Front Genet 2022; 13:855940. [PMID: 35464865 PMCID: PMC9023759 DOI: 10.3389/fgene.2022.855940] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 03/21/2022] [Indexed: 12/18/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with poor prognosis. Fatty acid metabolism is associated with cancer progression and a poor prognosis. We searched for long noncoding RNAs (lncRNAs) associated with fatty acid metabolism to predict the overall survival (OS) of patients with LUAD. We obtained lncRNA expression profiles and clinical follow-up data related to fatty acid metabolism in patients with LUAD from The Cancer Genome Atlas and Molecular Signatures database. Patients were randomly divided into training, experimental, and combination groups. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression models were used to construct fatty acid metabolism-related prognostic markers, Kaplan-Meier analysis was used to compare the prognosis of each group, and receiver operating characteristic (ROC) analysis was used to evaluate the accuracy of the prognostic model. We used the pRRophetic algorithm to assess the treatment response based on the half-maximal inhibitory concentration (IC50) of each sample in the Genomics of Cancer Drug Sensitivity (GDSC) database. A fatty acid metabolism-related prognostic marker containing seven lncRNAs was constructed to predict OS in LUAD. In the training, test and combination groups, the patients were divided into high- and low-risk groups according to a formula. K–M analysis showed that patients in the high-risk group had poorer prognosis, with significant differences in the subgroup analysis. ROC analysis showed that the predictive ability of the model was more accurate. A clinical prediction nomogram combining lncRNA and clinical features was constructed to accurately predict OS and had high clinical application value. Therapeutics were screened based on the IC50 values of each sample in the GDSC database. We found that A.443654, AUY922, AZ628, A.770041, AZD.0530, AMG.706, and AG.014699 were more effective in high-risk patients. We constructed a 7-lncRNA prognostic model to predict the OS of patients with LUAD. In addition, the predictive nomogram model based on our established seven fatty acid metabolism-related lncRNA signatures provides better clinical value than that of the traditional TNM staging system in predicting the prognosis of patients with LUAD and presents new insights for personalized treatment.
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Affiliation(s)
- Helin Wang
- Departments of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Junwei Cui
- Departments of Tuberculosis, The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Jian Yu
- Departments of Pathology, The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Jian Huang
- Departments of Tuberculosis, The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Mingying Li
- Departments of Tuberculosis, The First Affiliated Hospital of Xinxiang Medical University, Henan, China
- *Correspondence: Mingying Li,
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11
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Huai Q, Guo W, Han L, Kong D, Zhao L, Song P, Peng Y, Gao S. Identification of prognostic genes and tumor-infiltrating immune cells in the tumor microenvironment of esophageal squamous cell carcinoma and esophageal adenocarcinoma. Transl Cancer Res 2022; 10:1787-1803. [PMID: 35116502 PMCID: PMC8797718 DOI: 10.21037/tcr-20-3078] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 02/07/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Esophageal cancer (EC) is a highly aggressive malignancy that is classified as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Infiltrating stromal/immune cells, a major component of the tumor immune microenvironment (TIME), have prognostic significance in various cancers. METHODS In this study we investigated genes and immune factors in the tumor microenvironment (TME) of ESCC and EAC that can serve as prognostic biomarkers. Stromal and immune scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm based on gene expression profiles of patient-derived tumor tissues in The Cancer Genome Atlas database. The correlation between ESTIMATE scores and survival rates in EC were analyzed. A comparison of high and low stromal/immune score groups revealed multiple differentially expressed genes (DEGs) as candidate prognostic genes; their role in immune-related biological processes was evaluated by functional and protein-protein interaction (PPI) network analyses, and the genes were validated using Gene Expression Omnibus datasets. Additionally, 22 tumor-infiltrating immune cell (TIIC) subsets were analyzed using the CIBERSORT algorithm. RESULTS Median stromal score was higher whereas immune score was lower in ESCC than in EAC (both P<0.01). Stromal score was lower in female as compared to male ESCC patients (P<0.05), and was significantly correlated with T stage (P<0.05). In EAC, median immune score was higher in female as compared to male patients (P<0.05) and was correlated with tumor-node-metastasis stage (P<0.05). The identified DEGs were mainly involved in lymphocyte (especially T-lymphocyte) activation and carbohydrate binding. Moreover, the levels of infiltrating resting-stage dendritic cells, CD8+ T cells, naïve B cells, activated mast cells, and resting memory CD4+ T cells were significantly correlated with EC prognosis (P<0.05). CONCLUSIONS The immune microenvironment of ESCC and EAC are quite different. We have found genes with prognostic value in multiple tumor databases.
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Affiliation(s)
- Qilin Huai
- Department of Graduate School, Zunyi Medical University, Zunyi, China.,Department of Thoracic Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Wei Guo
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liankui Han
- Department of Thoracic Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Demiao Kong
- Department of Thoracic Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Liang Zhao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Peng Song
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yue Peng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shugeng Gao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2135] [Impact Index Per Article: 1067.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Suo RY, Wang ZY, Wang JS, Zhang GJ, Zhang J. Role of long non-coding RNA in regulating polarization of gastric cancer macrophages. Shijie Huaren Xiaohua Zazhi 2021; 29:1096-1101. [DOI: 10.11569/wcjd.v29.i19.1096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Tumor-associated macrophages (TAMs) are an important part of the tumor microenvironment. They are distributed in tumor tissues and distant metastatic sites, and are related to tumor progression and prognosis. TAMs M2 can promote tumor biological processes such as tumor proliferation, invasion, and metastasis, and inhibit apoptosis, and are obviously related to the poor prognosis of tumor patients. In recent years, the role of long non-coding RNAs (lncRNAs) in regulating the polarization of macrophages has gradually been revealed, which can affect the occurrence and development of tumors by adjusting the polarization of macrophages. Studies have shown that lncRNAs play an important role in the polarization process of gastric cancer macrophages. This article summarizes the related research reports, hoping to provide ideas for studies that interfere with the polarization process of TAMs to inhibit tumor progression.
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Affiliation(s)
- Rui-Yang Suo
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China,Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Zhi-Yu Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China,Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Jian-Sheng Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Guang-Jian Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Jia Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
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14
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Xi ZH, Ma XX, Chen HY, Yu YH, Li L, Huang T. A Metabolic-associated Nomogram Predicts Recurrence Survival of Thyroid Cancer. Curr Med Sci 2021; 41:1004-1011. [PMID: 34510328 DOI: 10.1007/s11596-021-2399-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 02/01/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE Various studies have suggested that metabolic genes play a significant role in papillary thyroid cancer (PTC). The current study aimed to identify a metabolic signature related biomarker to predict the prognosis of patients with PTC. METHODS We conducted a comprehensive analysis on the data obtained from the Cancer Genome Atlas (TCGA) database. The correlation between survival result and metabolic genes was evaluated based on the univariate Cox analyses, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses. The performance of a 7-gene signature was assessed according to Kaplan-Meier and receiver operating characteristic (ROC) analysis. Multivariate Cox regression analysis was adopted to unearth clinical factors related to the recurrence free survival (RFS) of patients with PTC. Finally, a prognostic nomogram was developed based on risk score, cancer status and cancer width to improve the prediction for RFS of PTC patients. RESULTS Seven metabolic genes were used to establish the prognostic model. The ROC curve and C-index exhibited high value in training, testing and the whole TCGA datasets. The established nomogram, incorporating the 7-metabolic gene signature and clinical factors, was able to predict the RFS with high effectiveness. The 7-metabolic gene signature-based nomogram had a good performance to predict the RFS of patients with PTC. CONCLUSION Our study identified a 7-metabolic gene signature and established a prognostic nomogram, which were useful in predicting the RFS of PTC.
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Affiliation(s)
- Zi-Han Xi
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xian-Xiong Ma
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Heng-Yu Chen
- Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.,NHC Key Laboratory of Hormones and Development, Tianjin Institute of Endocrinology, Tianjin Medical University Chu Hsien-I Memorial Hospital, Tianjin, 300134, China
| | - Yuan-Hang Yu
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Lei Li
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Tao Huang
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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15
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Zou W, Wang Z, Wang F, Li L, Liu R, Hu M. A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma. BMC Cancer 2021; 21:608. [PMID: 34034689 PMCID: PMC8152356 DOI: 10.1186/s12885-021-08322-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 05/06/2021] [Indexed: 01/10/2023] Open
Abstract
Background Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA. Methods The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort. Results We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA. Conclusion We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08322-5.
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Affiliation(s)
- Wenbo Zou
- Medical School of Chinese PLA, Beijing, China.,Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China.,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China
| | - Zizheng Wang
- Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China.,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China
| | - Fei Wang
- Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China.,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China
| | - Lincheng Li
- Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China.,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China
| | - Rong Liu
- Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China. .,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China. .,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.
| | - Minggen Hu
- Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China. .,Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China. .,Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.
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16
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Luan S, Yang Y, Zhou Y, Zeng X, Xiao X, Liu B, Yuan Y. The emerging role of long noncoding RNAs in esophageal carcinoma: from underlying mechanisms to clinical implications. Cell Mol Life Sci 2021; 78:3403-3422. [PMID: 33464385 DOI: 10.1007/s00018-020-03751-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/16/2020] [Accepted: 12/28/2020] [Indexed: 02/08/2023]
Abstract
Long noncoding RNAs (lncRNAs), a type of transcriptional product more than 200 nucleotides in length, have emerged as crucial regulators in human cancers. Accumulating data have recently indicated relationships between lncRNAs and esophageal carcinoma (EC). Of note, lncRNAs act as decoys/sponges, scaffolds, guides, and signals to regulate the expression of oncogenes or tumor suppressors at epigenetic, post-transcriptional, and protein levels, through which they exert their unique EC-driving or EC-suppressive functions. Moreover, the features of EC-related lncRNAs have been gradually exploited for developing novel diagnostic and therapeutic strategies in clinical scenarios. LncRNAs have the potential to be used as diagnostic and prognostic indicators individually or in combination with other clinical variables. Beyond these, although the time is not yet ripe, therapeutically targeting EC-related lncRNAs via gene editing, antisense oligonucleotides, RNA interference, and small molecules is likely one of the most promising therapeutic strategies for the next generation of cancer treatment. Herein, we focus on summarizing EC-driving/suppressive lncRNAs, as well as discussing their different features regarding expression profiles, modes of action, and oncological effects. Moreover, we further discuss current challenges and future developing possibilities of capitalizing on lncRNAs for EC early diagnosis and treatment.
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Affiliation(s)
- Siyuan Luan
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yushang Yang
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yuxin Zhou
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xin Xiao
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Bo Liu
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China.
| | - Yong Yuan
- Department of Thoracic Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China.
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Li M, Liang M, Lan T, Wu X, Xie W, Wang T, Chen Z, Shen S, Peng B. Four Immune-Related Long Non-coding RNAs for Prognosis Prediction in Patients With Hepatocellular Carcinoma. Front Mol Biosci 2020; 7:566491. [PMID: 33364253 PMCID: PMC7752774 DOI: 10.3389/fmolb.2020.566491] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 10/23/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Long non-coding RNA (LncRNA) plays an important role in the occurrence and development of hepatocellular carcinoma (HCC). This study aims to establish an immune-related LncRNA model for risk assessment and prognosis prediction in HCC patients. METHODS Hepatocellular carcinoma patient samples with complete clinical data and corresponding whole transcriptome expression were obtained from the Cancer Genome Atlas (TCGA). Immune-related genes were acquired from the Gene Set Enrichment Analysis (GSEA) website and matched with LncRNA in the TCGA to get immune-related LncRNA. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for screening the candidate LncRNAs and calculating the risk coefficient to establish the prognosis model. Patients were divided into a high-risk group and a low-risk group depending on the median risk score. The reliability of the prediction was evaluated in the validation cohort and the whole cohort. GSEA and principal component analysis were used for function evaluation. RESULTS A total of 319 samples met the screening criteria and were randomly distributed across the training cohort and the validation cohort. After comparison with the IMMUNE_RESPONSE gene set and the IMMUNE_SYSTEM_PROCESS gene set, a total of 3094 immune-related LncRNAs were screened. Ultimately, four immune-related LncRNAs were used to construct a formula using LASSO regression. According to the formula, the low-risk group showed a higher survival rate than the high-risk group in the validation cohort and the whole cohort. The receiver operating characteristic curves data demonstrated that the risk score was more specific than other traditional clinical characteristics in predicting the 5-year survival rate for HCC. CONCLUSION The four-immune-related-LncRNA model can be used for survival prediction in HCC and guide clinical therapy.
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Affiliation(s)
- Muqi Li
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Minni Liang
- Center of Surgery and Anaesthiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Tian Lan
- Department of Pancreatobiliary Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiwen Wu
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wenxuan Xie
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Tielong Wang
- Organ Transplant Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China
- Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Zhitao Chen
- Organ Transplant Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China
- Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Shunli Shen
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Baogang Peng
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Chen Q, Hu L, Chen K. Construction of a Nomogram Based on a Hypoxia-Related lncRNA Signature to Improve the Prediction of Gastric Cancer Prognosis. Front Genet 2020; 11:570325. [PMID: 33193668 PMCID: PMC7641644 DOI: 10.3389/fgene.2020.570325] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 09/29/2020] [Indexed: 12/24/2022] Open
Abstract
Background Gastric cancer is one of the most common malignant tumors and has a poor prognosis. Hypoxia is related to the poor prognosis of cancer patients. We searched for hypoxia-related long non-coding RNAs (lncRNAs) to predict both overall survival (OS) and disease-free survival (DFS) of gastric cancer patients. Methods We obtained hypoxia-related lncRNA expression profiles and clinical follow-up data of patients with gastric cancer from The Cancer Genome Atlas and the Molecular Signatures Database. The patients were randomly divided into a training group, test group and combined group. The hypoxia-related prognostic signature was constructed by Lasso regression and Cox regression models, the prognoses in different groups were compared by Kaplan-Meier (K-M) analysis, and the accuracy of the prognostic model was assessed by receiver operating characteristic (ROC) analysis. Results A hypoxia-related prognostic signature comprising 10 lncRNAs was constructed to predict both OS and DFS in gastric cancer. In the training, test and combined groups, patients were divided into high- and low-risk groups according to the formula. Kaplan-Meier analysis showed that patients in the high-risk group have poor prognoses, and the difference was significant in the subgroup analyses. Receiver operating characteristic analysis revealed that the predictive power of the model prediction is more accurate than that of standard benchmarks. The signature differed across Helicobacter pylori (Hp) status and T stages. Multivariate Cox analysis showed that the signature is an independent risk factor for both OS and DFS. A clinically predictive nomogram combining the lncRNA signature and clinical features was constructed; the nomogram accurately predicted both OS and DFS and had high clinical application value. Weighted correlation network analysis combined with enrichment analysis showed that the primary pathways were the PI3K-Akt, JAK-STAT, and IL-17 signaling pathways. The target genes NOX4, COL8A1, and CHST1 were associated with poor prognosis in the Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus, and K-M Plotter databases. Conclusions Our 10-lncRNA prognostic signature and nomogram are accurate, reliable tools for predicting both OS and DFS in gastric cancer.
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Affiliation(s)
- Qian Chen
- Department of Research, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Lang Hu
- Department of Research, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Kaihua Chen
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, China
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