1
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Chen K, Li WD, Li XQ. The role of m6A in angiogenesis and vascular diseases. iScience 2024; 27:110082. [PMID: 39055919 PMCID: PMC11269316 DOI: 10.1016/j.isci.2024.110082] [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] [Indexed: 07/28/2024] Open
Abstract
Angiogenesis, whether physiological or pathological, plays a pivotal role in various physiological and disease conditions. This intricate process relies on a complex and meticulously orchestrated signal transduction network that connects endothelial cells, their associated parietal cells (VSMCs and pericytes), and various other cell types, including immune cells. Given the significance of m6A and its connection to angiogenesis and vascular disease, researchers must adopt a comprehensive and ongoing approach to their investigations. This study aims to ascertain whether a common key mechanism of m6A exists in angiogenesis and vascular diseases and to elucidate the potential application of m6A in treating vascular diseases.
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Affiliation(s)
- Ke Chen
- Department of Vascular Surgery, The Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China
| | - Wen-Dong Li
- Department of Vascular Surgery, The Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China
| | - Xiao-Qiang Li
- Department of Vascular Surgery, The Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China
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2
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Liu S, Wang Z, Hu L, Ye C, Zhang X, Zhu Z, Li J, Shen Q. Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer. Transl Oncol 2024; 45:101982. [PMID: 38718436 PMCID: PMC11097084 DOI: 10.1016/j.tranon.2024.101982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 04/18/2024] [Accepted: 04/30/2024] [Indexed: 05/19/2024] Open
Abstract
Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1's tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.
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Affiliation(s)
- Shaojun Liu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Zhaohui Wang
- Department of Pathology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Lei Hu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Chao Ye
- Department of Gastroenterology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Xubin Zhang
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Zhiqiang Zhu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Jiaqiu Li
- Clinical Research Center, Affiliated Hospital of Shandong Second Medical University, Shandong Second Medical University, Weifang 261031, Shandong, China.
| | - Qi Shen
- Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China.
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3
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Xun S, Li X, Zhuang Q, Zhu Y, Qu L. Basement membrane-related lncRNA signature for the prognosis of hepatocellular carcinoma. Heliyon 2024; 10:e30439. [PMID: 38765049 PMCID: PMC11096898 DOI: 10.1016/j.heliyon.2024.e30439] [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: 01/15/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 05/21/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is the main type of primary liver cancer. This study aimed to develop a basement membrane (BM) related lncRNAs risk signature to evaluate the prognosis of HCC patients. We screened differentially expressed BM-related lncRNAs (DE-BMRlncRNAs) for risk evaluation, and identified six DE-BMRlncRNAs (AC072054.1, NUP50-DT, AC026412.3, AC109322.2, POLH-AS1 and LINC00595) for prognostic risk signature. HCC patients were divided to high or low risk according to median risk score. Our prognostic model predicted that patients with higher risk score had worse prognosis. We also created a nomogram to assist clinical decision-making according to risk score and clinicopathological features. Meanwhile, we confirmed the expression of six lncRNAs in HCC tissue and cells. POLH-AS1 knockdown inhibited the migration and invasion of HCC cells. In conclusion, we established a predictive model based on BMRlncRNAs to predict the prognosis of HCC. Our findings offer a rationale to further explore BM-related biomarkers for HCC.
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Affiliation(s)
- Shenmei Xun
- The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaocui Li
- Department of Gastroenterology, QingPu Branch of Zhongshan Hospital Affiliated to Fudan University,1158 Park Road(E) , Qingpu, Shanghai 201700, China
| | | | - Yefei Zhu
- The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lili Qu
- The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
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4
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Bao L, Ye Y, Zhang X, Xu X, Wang W, Jiang B. Identification and verification of a PANoptosis-related long noncoding ribonucleic acid signature for predicting the clinical outcomes and immune landscape in lung adenocarcinoma. Heliyon 2024; 10:e29869. [PMID: 38681588 PMCID: PMC11053219 DOI: 10.1016/j.heliyon.2024.e29869] [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: 03/30/2023] [Revised: 03/01/2024] [Accepted: 04/16/2024] [Indexed: 05/01/2024] Open
Abstract
PANoptosis is a type of programmed cell death (PCD) characterised by apoptosis, necroptosis and pyroptosis. Long non-coding ribonucleic acids (lncRNAs) are participating in the malignant behaviour of tumours regulated by PCD. Nevertheless, the function of PANoptosis-associated lncRNAs in lung adenocarcinoma remains to be investigated. In this work, a PANoptosis-related lncRNA signature (PRLSig) was developed based on the least absolute shrinkage and selection operator algorithm. The stability and fitness of PRLSig were confirmed by systematic evaluation of Kaplan-Meier, Cox analysis algorithm, receiver operating characteristic analysis, stratification analysis. In addition, ESTIMATE, single sample gene set enrichment analysis, immune checkpoints and the cancer immunome database confirmed the predictive value of the PRLSig in immune microenvironment and helped to identify populations for which immunotherapy is advantageous. The present research provides novel insights to facilitate risk stratification and optimise personalised treatment for LUAD.
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Affiliation(s)
- Lingling Bao
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
| | - Yingquan Ye
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xuede Zhang
- Department of Oncology, Weifang People's Hospital, Weifang, China
| | - Xin Xu
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
| | - Wenjuan Wang
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
| | - Bitao Jiang
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
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5
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Syed RU, Afsar S, Aboshouk NAM, Salem Alanzi S, Abdalla RAH, Khalifa AAS, Enrera JA, Elafandy NM, Abdalla RAH, Ali OHH, Satheesh Kumar G, Alshammari MD. LncRNAs in necroptosis: Deciphering their role in cancer pathogenesis and therapy. Pathol Res Pract 2024; 256:155252. [PMID: 38479121 DOI: 10.1016/j.prp.2024.155252] [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: 01/13/2024] [Revised: 03/02/2024] [Accepted: 03/04/2024] [Indexed: 04/14/2024]
Abstract
Necroptosis, a controlled type of cell death that is different from apoptosis, has become a key figure in the aetiology of cancer and offers a possible target for treatment. A growing number of biological activities, including necroptosis, have been linked to long noncoding RNAs (lncRNAs), a varied family of RNA molecules with limited capacity to code for proteins. The complex interactions between LncRNAs and important molecular effectors of necroptosis, including mixed lineage kinase domain-like pseudokinase (MLKL) and receptor-interacting protein kinase 3 (RIPK3), will be investigated. We will explore the many methods that LncRNAs use to affect necroptosis, including protein-protein interactions, transcriptional control, and post-transcriptional modification. Additionally, the deregulation of certain LncRNAs in different forms of cancer will be discussed, highlighting their dual function in influencing necroptotic processes as tumour suppressors and oncogenes. The goal of this study is to thoroughly examine the complex role that LncRNAs play in controlling necroptotic pathways and how that regulation affects the onset and spread of cancer. In the necroptosis for cancer treatment, this review will also provide insight into the possible therapeutic uses of targeting LncRNAs. Techniques utilising LncRNA-based medicines show promise in controlling necroptotic pathways to prevent cancer from spreading and improve the effectiveness of treatment.
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Affiliation(s)
- Rahamat Unissa Syed
- Department of Pharmaceutics, College of Pharmacy, University of Ha'il, Hail 81442, Saudi Arabia.
| | - S Afsar
- Department of Virology, Sri Venkateswara University, Tirupathi, Andhra Pradesh 517502, India.
| | - Nayla Ahmed Mohammed Aboshouk
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | | | | | - Amna Abakar Suleiman Khalifa
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | - Jerlyn Apatan Enrera
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | - Nancy Mohammad Elafandy
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | - Randa Abdeen Husien Abdalla
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | - Omar Hafiz Haj Ali
- Department of Clinical laboratory Sciences, College of Applied Medical Sciences, University of Hail, Hail 81442, Saudi Arabia
| | - G Satheesh Kumar
- Department of Pharmaceutical Chemistry, College of Pharmacy, Seven Hills College of Pharmacy, Venkataramapuram, Tirupati, India
| | - Maali D Alshammari
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Hail, Hail 81442, Saudi Arabia
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6
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He X, Xu Z, Ren R, Wan P, Zhang Y, Wang L, Han Y. A novel sphingolipid metabolism-related long noncoding RNA signature predicts the prognosis, immune landscape and therapeutic response in pancreatic adenocarcinoma. Heliyon 2024; 10:e23659. [PMID: 38173505 PMCID: PMC10761810 DOI: 10.1016/j.heliyon.2023.e23659] [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: 03/26/2023] [Revised: 11/23/2023] [Accepted: 12/09/2023] [Indexed: 01/05/2024] Open
Abstract
Sphingolipid metabolism affects prognosis and resistance to immunotherapy in patients with cancer and is an emerging target in cancer therapy with promising diagnostic and prognostic value. Long noncoding ribonucleic acids (lncRNAs) broadly regulate tumour-associated metabolic reprogramming. However, the potential of sphingolipid metabolism-related lncRNAs in pancreatic adenocarcinoma (PAAD) is poorly understood. In this study, coexpression algorithms were employed to identify sphingolipid metabolism-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a sphingolipid metabolism-related lncRNA signature (SMLs). The prognostic predictive stability of the SMLs was validated using Kaplan-Meier. Univariate and multivariate Cox, receiver operating characteristic (ROC) and clinical stratification analyses were used to comprehensively assess the SMLs. Gene set variation analysis (GSVE), gene ontology (GO) and tumor mutation burden (TMB) analysis explored the potential mechanisms. Additionally, single sample gene set enrichment analysis (ssGSEA), ESTIMATE, immune checkpoints and drug sensitivity analysis were used to investigate the potential predictive function of the SMLs. Finally, an SMLs-based consensus clustering algorithm was utilized to differentiate patients and determine the suitable population for immunotherapy. The results showed that the SMLs consists of seven sphingolipid metabolism-related lncRNAs, which can well determine the clinical outcome of individuals with PAAD, with high stability and general applicability. In addition, the SMLs-based consensus clustering algorithm divided the TCGA-PAAD cohort into two clusters, with Cluster 1 showing better survival than Cluster 2. Additionally, Cluster 1 had a higher level of immune cell infiltration than Cluster 2, which combined with the higher levels of immune checkpoints in Cluster 1 suggests that Cluster 1 is more consistent with an immune 'hot tumor' profile and may respond better to immune checkpoint inhibitors (ICIs). This study offers new insights regarding the potential role of sphingolipid metabolism-related lncRNAs as biomarkers in PAAD. The constructed SMLs and the SMLs-based clustering are valuable tools for predicting clinical outcomes in PAAD and provide a basis for clinical selection of individualized treatments.
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Affiliation(s)
- Xiaolan He
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Zhengyang Xu
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Ruiping Ren
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Peng Wan
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Yu Zhang
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Liangliang Wang
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Ying Han
- Department of Chemoradiotherapy, The Affiliated People's Hospital of Ningbo University, Ningbo, China
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7
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Zhou C, Gan X, Sun S, Wang L, Zhang Y, Zhang J. Construction of an efferocytosis-related long non-coding ribonucleic acid scoring system to predict clinical outcome and immunotherapy response in pancreatic adenocarcinoma. Biochem Biophys Rep 2023; 35:101540. [PMID: 37692763 PMCID: PMC10482751 DOI: 10.1016/j.bbrep.2023.101540] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/30/2023] [Accepted: 08/30/2023] [Indexed: 09/12/2023] Open
Abstract
Background Efferocytosis suppresses antitumour immune responses by inducing the release and secretion of cytokines. Long non-coding ribonucleic acids (lncRNAs) have various functions in different forms of programmed cell death and in immune regulation. This study aims to explore the potential role of efferocytosis-related lncRNAs as biomarkers in pancreatic adenocarcinoma (PAAD). Methods Transcriptome profiles, simple nucleotide variations and clinical data of patients with PAAD were extracted from The Cancer Genome Atlas (TCGA) database. Co-expression algorithms identified efferocytosis-related lncRNAs. The efferocytosis-related lncRNA scoring system (ERLncSys) was established using Cox regression and the Least Absolute Shrinkage and Selection Operator algorithm. Additionally, Kaplan-Meier (K-M) curves, Cox regression, receiver operating characteristic (ROC) curves and clinical parameter stratification analyses were used to evaluate ERlncSys. Moreover, ERlncSys was explored through Gene Set Variation Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the TIMER platform, ESTIMATE algorithm, single sample Gene Set Enrichment Analysis and immune checkpoint analysis were utilised to explore the predictive power of ERlncSys for the tumour immune microenvironment (TIME). Finally, a consensus clustering algorithm identified distinct molecular profiles among patients with PAAD, aiding in the identification of potential beneficiaries for immunotherapy. Results K-M, Cox regression and ROC analyses confirmed the robust prognostic efficacy of ERlncSys. Clinical stratification analysis indicated the broad applicability of ERlncSys in PAAD. Additionally, mmunological analyses indicated that ERlncSys can determine immune cell infiltration status in the TIME. Furthermore, consensus clustering analysis based on ERlncSys divided the TCGA-PAAD cohort into two clusters. Cluster 1 exhibited characteristics consistent with an immune 'hot tumour' compared to cluster 2, suggesting cluster 1 is a more suitable population for immune checkpoint inhibitor therapy. Conclusion The established ErlncSys aids in predicting the prognosis and understanding the TIME landscape of patients with PAAD. In turn, it facilitates the identification of optimal candidates for immunotherapy. This study introduces novel insights into the potential value of efferocytosis-related lncRNAs as biomarkers in PAAD.
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Affiliation(s)
| | - Xiaoshuang Gan
- Suzhou Traditional Chinese Medicine Hospital of Anhui Province, Suzhou, 234000, China
| | - Shandong Sun
- Suzhou Traditional Chinese Medicine Hospital of Anhui Province, Suzhou, 234000, China
| | - Lei Wang
- Suzhou Traditional Chinese Medicine Hospital of Anhui Province, Suzhou, 234000, China
| | - Yong Zhang
- Suzhou Traditional Chinese Medicine Hospital of Anhui Province, Suzhou, 234000, China
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Chen L, He Y, Zhu J, Zhao S, Qi S, Chen X, Zhang H, Ni Z, Zhou Y, Chen G, Liu S, Xie T. The roles and mechanism of m 6A RNA methylation regulators in cancer immunity. Biomed Pharmacother 2023; 163:114839. [PMID: 37156113 DOI: 10.1016/j.biopha.2023.114839] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/10/2023] Open
Abstract
N6-methyladenosine (m6A), the most common internal modification in RNA, can be regulated by three types of regulators, including methyltransferases (writers), demethylases (erasers), and m6A binding proteins (readers). Recently, immunotherapy represented by immune checkpoint blocking has increasingly become an effective cancer treatment, and increasing shreds of evidence show that m6A RNA methylation affects cancer immunity in various cancers. Until now, there have been few reviews about the role and mechanism of m6A modification in cancer immunity. Here, we first summarized the regulation of m6A regulators on the expression of target messenger RNAs (mRNA) and their corresponding roles in inflammation, immunity response, immune process and immunotherapy in various cancer cells. Meanwhile, we described the roles and mechanisms of m6A RNA modification in tumor microenvironment and immune response by affecting the stability of non-coding RNA (ncRNA). Moreover, we also discussed the m6A regulators or its target RNAs which might be used as predictor of cancer diagnosis and prognosis, and shed light on the potentiality of m6A methylation regulators as therapeutic targets in cancer immunity.
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Affiliation(s)
- Lu Chen
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Ying He
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Jinyu Zhu
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Shujuan Zhao
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Shasha Qi
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Xudong Chen
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Hao Zhang
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Ziheng Ni
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Yuan Zhou
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China
| | - Gongxing Chen
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China.
| | - Shuiping Liu
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China.
| | - Tian Xie
- School of Pharmacy and Department of Respiratory Medicine, the Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China.
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Wu LH, Wang XX, Wang Y, Wei J, Liang ZR, Yan X, Wang J. Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer. Front Surg 2023; 10:1088292. [PMID: 37066015 PMCID: PMC10102374 DOI: 10.3389/fsurg.2023.1088292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 03/02/2023] [Indexed: 04/03/2023] Open
Abstract
BackgroundGastric cancer (GC) is an aggressive malignant tumor with a high degree of heterogeneity, and its immune microenvironment is closely associated with tumor growth, development and drug resistance. Therefore, a classification system of gastric cancer based explicitly on the immune microenvironment context might enrich the strategy for gastric cancer prognosis and therapy.MethodsA total of 668 GC patients were collected from TCGA-STAD (n = 350), GSE15459 (n = 192), GSE57303 (n = 70) and GSE34942 (n = 56) datasets. Three immune-related subtypes (immunity-H, -M, and -L) were identified by hierarchical cluster analysis based on the ssGSEA score of 29 immune microenvironment-related gene sets. The immune microenvironment-related prognosis signature (IMPS) was constructed via univariate Cox regression, Lasso-Cox regression and multivariate Cox regression, and nomogram model combining IMPS and clinical variables was further constructed by the “rms” package. RT-PCR was applied to validate the expression of 7 IMPS genes between two human GC cell lines (AGS and MKN45) and one normal gastric epithelial cell line (GES-1).ResultsThe patients classified as immunity-H subtype exhibited highly expressed immune checkpoint and HLA-related genes, with enriched naïve B cells, M1 macrophages and CD8 T cells. We further constructed and validated a 7-gene (CTLA4, CLDN6, EMB, GPR15, ENTPD2, VWF and AKR1B1) prognosis signature, termed as IMPS. The patients with higher IMPS expression were more likely to be associated with higher pathology grade, more advanced TNM stages, higher T and N stage, and higher ratio of death. In addition, the prediction values of the combined nomogram in predicting 1-year (AUC = 0.750), 3-year (AUC = 0.764) and 5-year (AUC = 0.802) OS was higher than IMPS and individual clinical characteristics.ConclusionsThe IMPS is a novel prognosis signature associated with the immune microenvironment and clinical characteristics. The IMPS and the combined nomogram model provide a relatively reliable predictive index for predicting the survival outcomes of gastric cancer.
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Affiliation(s)
- Li-Hong Wu
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
| | - Xiang-Xu Wang
- Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yan Wang
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
| | - Jing Wei
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
| | - Zi-Rong Liang
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
| | - Xi Yan
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
- Correspondence: Jun Wang Xi Yan
| | - Jun Wang
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, China
- Correspondence: Jun Wang Xi Yan
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Wang W, Ye Y, Zhang X, Sun W, Bao L. An angiogenesis-related three-long non-coding ribonucleic acid signature predicts the immune landscape and prognosis in hepatocellular carcinoma. Heliyon 2023; 9:e13989. [PMID: 36873490 PMCID: PMC9982620 DOI: 10.1016/j.heliyon.2023.e13989] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 02/12/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
The tumour microenvironment is a key determinant of the efficacy of immunotherapy. Angiogenesis is closely linked to tumour immunity. We aimed to screen long non-coding ribonucleic acids (lncRNAs) associated with angiogenesis to predict the prognosis of individuals with hepatocellular carcinoma (HCC) and characterise the tumour immune microenvironment (TIME). Patient data, including transcriptome and clinicopathological parameters, were retrieved from The Cancer Genome Atlas database. Moreover, co-expression algorithm was utilized to obtain angiogenesis-related lncRNAs. Additionally, survival-related lncRNAs were identified using Cox regression and the least absolute shrinkage and selection operator algorithm, which aided in constructing an angiogenesis-related lncRNA signature (ARLs). The ARLs was validated using Kaplan-Meier method, time-dependent receiver operating characteristic analyses, and Cox regression. Additionally, an independent external HCC dataset was used for further validation. Then, gene set enrichment analysis, immune landscape, and drug sensitivity analyses were implemented to explore the role of the ARLs. Finally, cluster analysis divided the entire HCC dataset into two clusters to distinguish different subtypes of TIME. This study provides insight into the involvement of angiogenesis-associated lncRNAs in predicting the TIME characteristics and prognosis for individuals with HCC. Furthermore, the developed ARLs and clusters can predict the prognosis and TIME characteristics in HCC, thereby aiding in selecting the appropriate therapeutic strategies involving immune checkpoint inhibitors and targeted drugs.
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Affiliation(s)
- Wenjuan Wang
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
| | - Yingquan Ye
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xuede Zhang
- Department of Oncology, Weifang People's Hospital, Weifang, China
| | - Weijie Sun
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lingling Bao
- Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, China
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