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Li M, Lu M, Li J, Gui Q, Xia Y, Lu C, Shu H. Classification of molecular subtypes for colorectal cancer and development of a prognostic model based on necroptosis-related genes. Heliyon 2024; 10:e26781. [PMID: 38439879 PMCID: PMC10909728 DOI: 10.1016/j.heliyon.2024.e26781] [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: 07/19/2023] [Revised: 02/18/2024] [Accepted: 02/20/2024] [Indexed: 03/06/2024] Open
Abstract
Background Necroptosis could regulate immunity in cancers, and stratification of colorectal cancer (CRC) subtypes based on key genes related to necroptosis might be a novel strategy for CRC treatment. Method The RNA-sequencing data of CRC and other 31 types of cancers were obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed based on protein-coding genes (PCGs) related to necroptosis score calculated by single sample gene set enrichment analysis (ssGSEA). Module genes showing a significant positive correlation with the necroptosis score were identified by weighted correlation network analysis (WGCNA) and further used to develop a risk stratification model applying least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The risks score for each sample in CRC cohorts, immunotherapy cohorts and pan-cancer study cohorts was calculated. Result Two subgroups (C1 cluster and C2 cluster) of CRC were identified based on the necroptosis score. Compared with C1 cluster, the survival possibility of C2 cluster was greatly reduced, the levels of necroptosis score, immune cell infiltration, immune score and expression of immune checkpoint molecules were significantly increased and immunotherapy response was less active. Low-risk patients defined by the risk model had a significant survival advantage than high-risk counterparts in both CRC and the other 31 cancer types. Furthermore, the risk model was also more efficient than the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting OS and immunotherapy response for the samples in the immunotherapy cohort. Conclusion CRC patients were classified by necroptosis score-related PCGs, and a risk model was designed to evaluate the immunotherapy and prognosis of patients with CRC. The current molecular subtype and prognostic model could help stratify patients with different risks and predict their prognosis and immunotherapy sensitivity.
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Affiliation(s)
- Mengling Li
- Department of General Practice, Shangrao People's Hospital, Shangrao, 334000, China
| | - Ming Lu
- Health Service Center, Shangrao Municipal Health Commission, Shangrao, 334000, China
| | - Jun Li
- Physical Examination Center, Shangrao People's Hospital, Shangrao, 334000, China
| | - Qingqing Gui
- Academic Department, HaploX Genomics Center, Shangrao, 334000, China
| | - Yibin Xia
- Academic Department, HaploX Genomics Center, Shangrao, 334000, China
| | - Chao Lu
- Academic Department, HaploX Genomics Center, Shangrao, 334000, China
| | - Hongchun Shu
- Digestive System Department, Shangrao People's Hospital, 334000, China
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2
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Zhang Y, Liu K, Wang J. Identification of TNFRSF1A as a potential biomarker for osteosarcoma. Cancer Biomark 2024; 39:299-312. [PMID: 38250759 DOI: 10.3233/cbm-230086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
BACKGROUND Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively. OBJECTIVE The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS. METHODS TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated using nomogram and decision curve analyses (DCA). RESULTS Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669). Conclusion TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis.
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Affiliation(s)
- Yuke Zhang
- Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
- Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Kai Liu
- Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
- Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Jianzhong Wang
- Department of Orthopedics and Traumatology, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
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Wang Y, Pan KH, Chen M. Necroptosis-related genes are associated with prognostic features of kidney renal clear cell carcinoma. Discov Oncol 2023; 14:192. [PMID: 37878133 PMCID: PMC10600093 DOI: 10.1007/s12672-023-00794-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/18/2023] [Indexed: 10/26/2023] Open
Abstract
INTRODUCTION Renal clear cell carcinoma is a common type of cancer in the adult urological system. It has a high mortality rate, with 30% of patients developing metastasis and 60% dying within 1-2 years of diagnosis. Recent advancements in tumor immunology and necroptosis have provided new insights into kidney cancer therapy. Therefore, it is crucial to identify potential targets for combining immunotherapy with necroptosis. MATERIALS AND METHODS Using the GSE168845 dataset and necroptosis-related genes, we identified genes that are differentially expressed in relation to necroptosis. We analyzed the prognostic value of these genes through differential expression analysis, prognostic analysis, and Cox regression analysis. The expression levels of the MYCN and CDKN2A genes were verified using the GSE53757 dataset. We also examined the association between the differentially expressed genes and clinicopathological features, as well as overall survival in our cohorts. In addition, we constructed a lasso Cox regression model to assess the correlation between these genes and immune score, ICP, and OCLR score. We conducted qRT-PCR to detect the expression of MYCN, CDKN2A, and ZBP1 in different samples of kidney renal clear cell carcinoma (KIRC). The expression levels of these genes were verified in a normal kidney cell line (HK-2 cells) and two KIRC cell lines (786-O, ACHN). The protein levels of MYCN and CDKN2A were detected using immunohistochemistry (IHC). SiRNA was used to silence the expression of MYCN and CDKN2A in the ACHN cell line, and wound healing assays were performed to measure cell migration. RESULTS MYCN, CDKN2A, and ZBP1 were identified as necroptosis-related genes with independent prognostic value, leading to the development of a risk prognostic model. The expression of the CDKN2A gene was significantly higher in KIRC tissues compared to normal tissues, while the expression of the MYCN gene was significantly lower in KIRC tissues. The expression of MYCN and CDKN2A was associated with tumor stage, metastasis, and overall survival in our cohort. Furthermore, MYCN, CDKN2A, and ZBP1 were significantly correlated with immune score, ICP, and OCLR score. The expression levels of CDKN2A and ZBP1 were higher in KIRC cells compared to normal kidney cells, while the expression of MYCN was lower in KIRC cells. The protein expression of MYCN and CDKN2A was also higher in KIRC tissues, as confirmed by IHC. The results of the wound healing assay indicated that silencing CDKN2A inhibited cell migration, while silencing MYCN enhanced cell migration. CONCLUSIONS MYCN and CDKN2A are potential targets and valuable prognostic biomarkers for combining immunotherapy with necroptosis in kidney renal clear cell carcinoma. CDKN2A promotes the migration of renal cancer cells, while MYCN inhibits their migration.
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Affiliation(s)
- Yiduo Wang
- Affiliated Zhongda Hospital of Southeast University, Southeast University, 87 Dingjia Bridge Hunan Road, Nanjing, China
| | - Ke-Hao Pan
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Ming Chen
- Affiliated Zhongda Hospital of Southeast University, Southeast University, 87 Dingjia Bridge Hunan Road, Nanjing, China.
- Department of Urology, Lishui District People's Hospital, Affiliated Zhongda Hospital of Southeast University, 87 Dingjia Bridge Hunan Road, Nanjing, China.
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4
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Liu Y, Zhou H, Tang X. STUB1/CHIP: New insights in cancer and immunity. Biomed Pharmacother 2023; 165:115190. [PMID: 37506582 DOI: 10.1016/j.biopha.2023.115190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 07/12/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
The STUB1 gene (STIP1 homology and U-box-containing protein 1), located at 16q13.3, encodes the CHIP (carboxyl terminus of Hsc70-interacting protein), an essential E3 ligase involved in protein quality control. CHIP comprises three domains: an N-terminal tetratricopeptide repeat (TPR) domain, a middle coiled-coil domain, and a C-terminal U-box domain. It functions as a co-chaperone for heat shock protein (HSP) via the TPR domain and as an E3 ligase, ubiquitinating substrates through its U-box domain. Numerous studies suggest that STUB1 plays a crucial role in various physiological process, such as aging, autophagy, and bone remodeling. Moreover, emerging evidence has shown that STUB1 can degrade oncoproteins to exert tumor-suppressive functions, and it has recently emerged as a novel player in tumor immunity. This review provides a comprehensive overview of STUB1's role in cancer, including its clinical significance, impact on tumor progression, dual roles, tumor stem cell-like properties, angiogenesis, drug resistance, and DNA repair. In addition, we explore STUB1's functions in immune cell differentiation and maturation, inflammation, autoimmunity, antiviral immune response, and tumor immunity. Collectively, STUB1 represents a promising and valuable therapeutic target in cancer and immunology.
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Affiliation(s)
- Yongshuo Liu
- Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China.
| | - Honghong Zhou
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaolong Tang
- Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China.
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5
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Gan L, Xiao Q, Zhou Y, Fu Y, Tang M. Role of anoikis-related gene PLK1 in kidney renal papillary cell carcinoma: a bioinformatics analysis and preliminary verification on promoting proliferation and migration. Front Pharmacol 2023; 14:1211675. [PMID: 37456749 PMCID: PMC10339314 DOI: 10.3389/fphar.2023.1211675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
Background: Kidney renal papillary cell carcinoma (KIRP) is a rare malignancy with a very poor prognosis. Anoikis is a specific form of apoptosis involved in carcinogenesis, but the role of anoikis in KIRP has not been explored. Methods: Anoikis-related genes (ARGs) were obtained from the GeneCards database and Harmonizome database and were used to identify different subtypes of KIRP and construct a prognostic model of KIRP. In addition, we also explored the immune microenvironment and enrichment pathways among different subtypes by consensus clustering into different subtypes. Drug sensitivity analysis was used to screen for potential drugs. Finally, we verified the mRNA and protein expression of the independent prognostic gene PLK1 in patient tissues and various cells and further verified the changes in relevant prognostic functions after constructing a PLK1 stable knockdown model using ShRNA. Results: We identified 99 differentially expressed anoikis-related genes (DEGs) associated with KIRP survival, and selected 3 genes from them to construct a prognostic model, which can well predict the prognosis of KIRP patients. Consensus clustering divided KIRP into two subtypes, and there was a significant difference in survival rates between the two subtypes. Immune profiling revealed differing immune statuses between the two subtypes, and functional analysis reveals the differential activity of different functions in different subtypes. Drug sensitivity analysis screened out 15 highly sensitive drugs in the high-risk group and 11 highly sensitive drugs in the low-risk group. Univariate and multivariate Cox regression analysis confirmed that PLK1 was an independent prognostic factor in KIRP, and its mRNA and protein expression levels were consistent with gene differential expression levels, both of which were highly expressed in KIRP. Functional verification of PLK1 in KIRP revealed significant results. Specifically, silencing PLK1 inhibited cell proliferation, clonogenicity, and migration, which indicated that PLK1 plays an important role in the proliferation and migration of KIRP. Conclusion: The prognosis model constructed by ARGs in this study can accurately predict the prognosis of KIRP patients. ARGs, especially PLK1, play an important role in the development of KIRP. This research can help doctors provide individualized treatment plans for KIRP patients and provide researchers with new research ideas.
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Affiliation(s)
- Li Gan
- Department of Anesthesiology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Qiyu Xiao
- Department of Nuclear Medicine, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Yusong Zhou
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Ying Fu
- Department of Nuclear Medicine, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, 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
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Wang YF, Hu YQ, Hu YN, Bai YC, Wang H, Zhang Q. Expression and clinical significance of DOK3 in renal clear cell carcinoma. J Int Med Res 2023; 51:3000605231174974. [PMID: 37235715 DOI: 10.1177/03000605231174974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2023] Open
Abstract
OBJECTIVES Docking Protein 3 (DOK3) is an adapter protein that has been implicated in various cellular processes relevant to diseases, such as cancer. In this study, we aimed to evaluate the role of DOK3 in kidney renal clear cell carcinoma (KIRC) by examining how its expression levels are correlated with patient characteristics and prognosis. METHODS We analyzed KIRC-related data from The Cancer Genome Atlas and used several bioinformatics tools, such as LinkedOmics and Oncomine, to evaluate DOK3 mRNA expression in KIRC. DOK3 protein expression was examined in 150 clinical KIRC samples and 100 non-cancerous renal tissues with immunohistochemistry assays. The prognostic value of DOK3 mRNA expression on patient overall survival was analyzed retrospectively using Kaplan-Meier survival and Cox regression analyses. RESULTS DOK3 mRNA expression was notably higher in KIRC samples compared with normal tissues. Significant correlations were found between DOK3 mRNA expression levels and tumor size, lymph node metastasis, distant metastasis, and pathological grade using the bioinformatics data. This was confirmed at the protein level with immunohistochemistry data. Survival analyses indicated that elevated DOK3 expression is linked to a lower overall survival rate in KIRC patients. CONCLUSIONS DOK3 is a potential biomarker for determining KIRC patient clinical prognosis.
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Affiliation(s)
- Yi-Fan Wang
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
- Graduate Department, Bengbu Medical College, Bengbu, China
| | - Yu-Qi Hu
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yu-Ning Hu
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yu-Chen Bai
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
| | - Heng Wang
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
| | - Qi Zhang
- Urology & Nephrology Center, Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
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Luo P, Shi Z, He C, Chen G, Feng J, Zhu L, Song X. Predicting the Clinical Outcome of Triple-Negative Breast Cancer Based on the Gene Expression Characteristics of Necroptosis and Different Molecular Subtypes. Stem Cells Int 2023; 2023:8427767. [PMID: 37274025 PMCID: PMC10234373 DOI: 10.1155/2023/8427767] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/21/2022] [Accepted: 10/12/2022] [Indexed: 08/06/2023] Open
Abstract
Necroptosis, a kind of programmed necrotic cell apoptosis, is the gatekeeper for the host to defend against the invasion of pathogens. It helps to regulate different biological processes regarding human cancer. Nevertheless, studies that determine the impact of death on triple-negative breast cancer (TNBC) are scarce. Therefore, this paper has comprehensively examined the expression as well as clinical significance of necroptosis in TNBC. ConsensusClusterPlus was used to establish a stable molecular classification that used the expression regarding the necroptosis-linked genes. The clinical and immune characteristics of different subclasses were evaluated. Then, the weighted gene coexpression network analysis (WGCNA) assisted in determining key modules, and we selected the genes exhibiting obvious association with necroptosis prognosis through the relationship with prognosis. The univariate Cox regression analysis together with least absolute shrinkage and selection operator (LASSO) techniques served for the construction of the necroptosis-related prognostic risk score (NPRS) model, and the pathway characteristics of NPRS model grouping were further studied. Finally, the NPRS, taking into account the clinicopathological features, used the decision tree model for enhancing the prognostic model as well as the survival prediction. First, two stable molecular subtypes with different prognosis and immune characteristics were identified using necroptosis marker genes. Then, the key modules were identified, and 10 genes significantly related to the prognosis of necroptosis were selected. Then, the clinical prognostic model of NPRS was developed considering the prognosis-linked necroptosis genes. Finally, the NPRS model, taking into account the clinicopathological features, adopted the decision tree model for enhancing the prognostic model as well as the survival prediction. Herein, two new molecular subgroups considering necroptosis-linked genes are proposed, and an NPRS model composed of 10 genes is developed, which maybe assist in the personalized treatment and clinical treatment guidance of TNBC patients.
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Affiliation(s)
- Peng Luo
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Zhaoqi Shi
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Changshou He
- Department of Oncology, HaploX Biotechnology, Shenzhen 518000, China
| | - Guojun Chen
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Ji Feng
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Linghua Zhu
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Xiangyang Song
- Department of Surgical Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
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Kaur S, Awad D, Finney RP, Meyer TJ, Singh SP, Cam MC, Karim BO, Warner AC, Roberts DD. CD47-Dependent Regulation of Immune Checkpoint Gene Expression and MYCN mRNA Splicing in Murine CD8 and Jurkat T Cells. Int J Mol Sci 2023; 24:2612. [PMID: 36768931 PMCID: PMC9916813 DOI: 10.3390/ijms24032612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/13/2023] [Accepted: 01/21/2023] [Indexed: 01/31/2023] Open
Abstract
Elevated expression of CD47 in some cancers is associated with poor survival related to its function as an innate immune checkpoint when expressed on tumor cells. In contrast, elevated CD47 expression in cutaneous melanomas is associated with improved survival. Previous studies implicated protective functions of CD47 expressed by immune cells in the melanoma tumor microenvironment. RNA sequencing analysis of responses induced by CD3 and CD28 engagement on wild type and CD47-deficient Jurkat T lymphoblast cells identified additional regulators of T cell function that were also CD47-dependent in mouse CD8 T cells. MYCN mRNA expression was upregulated in CD47-deficient cells but downregulated in CD47-deficient cells following activation. CD47 also regulated alternative splicing that produces two N-MYC isoforms. The CD47 ligand thrombospondin-1 inhibited expression of these MYCN mRNA isoforms, as well as induction of the oncogenic decoy MYCN opposite strand (MYCNOS) RNA during T cell activation. Analysis of mRNA expression data for melanomas in The Cancer Genome Atlas identified a significant coexpression of MYCN with CD47 and known regulators of CD8 T cell function. Thrombospondin-1 inhibited the induction of TIGIT, CD40LG, and MCL1 mRNAs following T cell activation in vitro. Increased mRNA expression of these T cell transcripts and MYCN in melanomas was associated with improved overall survival.
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Affiliation(s)
- Sukhbir Kaur
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Duha Awad
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Richard P. Finney
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Thomas J. Meyer
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Satya P. Singh
- Inflammation Biology Section, Laboratory of Molecular Immunology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Margaret C. Cam
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Baktiar O. Karim
- Molecular Histopathology Laboratory, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA
| | - Andrew C. Warner
- Molecular Histopathology Laboratory, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA
| | - David D. Roberts
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
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Wang Z, Huang Z, Cao X, Zhang F, Cai J, Tang P, Yang C, Li S, Yu D, Yan Y, Shen B. A prognostic model based on necroptosis-related genes for prognosis and therapy in bladder cancer. BMC Urol 2023; 23:10. [PMID: 36709279 PMCID: PMC9883845 DOI: 10.1186/s12894-023-01175-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/09/2023] [Indexed: 01/30/2023] Open
Abstract
Bladder cancer, one of the most prevalent malignant cancers, has high rate of recurrence and metastasis. Owing to genomic instability and high-level heterogeneity of bladder cancer, chemotherapy and immunotherapy drugs sensitivity and lack of prognostic markers, the prognosis of bladder cancer is unclear. Necroptosis is a programmed modality of necrotic cell death in a caspase-independent form. Despite the fact that necroptosis plays a critical role in tumor growth, cancer metastasis, and cancer patient prognosis, necroptosis-related gene sets have rarely been studied in bladder cancer. As a result, the development of new necroptosis-related prognostic indicators for bladder cancer patients is critical. Herein, we assessed the necroptosis landscape of bladder cancer patients from The Cancer Genome Atlas database and classified them into two unique necroptosis-related patterns, using the consensus clustering. Then, using five prognosis-related genes, we constructed a prognostic model (risk score), which contained 5 genes (ANXA1, DOK7, FKBP10, MAP1B and SPOCD1). And a nomogram model was also developed to offer the clinic with a more useful prognostic indicator. We found that risk score was significantly associated with clinicopathological characteristics, TIME, and tumor mutation burden in patients with bladder cancer. Moreover, risk score was a valid guide for immunotherapy, chemotherapy, and targeted drugs. In our study, DOK7 was chosen to further verify our prognosis model, and functional assays indicated that knockdown the expression of DOK7 could prompt bladder cancer proliferation and migration. Our work demonstrated the potential role of prognostic model based on necroptosis genes in the prognosis, immune landscape and response efficacy of immunotherapy of bladder cancer.
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Affiliation(s)
- Zeyi Wang
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital of Nanjing Medical University, Shanghai, 200080 China
| | - Zhengnan Huang
- grid.24516.340000000123704535Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065 China
| | - Xiangqian Cao
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Fang Zhang
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Jinming Cai
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Pengfei Tang
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital of Nanjing Medical University, Shanghai, 200080 China
| | - Chenkai Yang
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Shengzhou Li
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Dong Yu
- grid.73113.370000 0004 0369 1660Department of Precision Medicine, Center of Translation Medicine, Naval Medical University, Shanghai, 200082 China
| | - Yilin Yan
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
| | - Bing Shen
- grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital of Nanjing Medical University, Shanghai, 200080 China ,grid.412478.c0000 0004 1760 4628Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080 China
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Identification and Validation of a Necroptosis-Related Prognostic Signature for Kidney Renal Clear Cell Carcinoma. Stem Cells Int 2023; 2023:8446765. [PMID: 36910333 PMCID: PMC10005877 DOI: 10.1155/2023/8446765] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/07/2022] [Accepted: 09/21/2022] [Indexed: 03/06/2023] Open
Abstract
Background Necroptosis is progressively becoming an important focus of research because of its role in the pathogenesis of cancer and other inflammatory diseases. Our study is designed to anticipate the survival time of kidney renal clear cell carcinoma (KIRC) by constructing a prognostic signature of necroptosis-related genes. Materials Clinical information and RNA-seq data were acquired from Renal Cell Cancer-European Union (RECA-EU) and The Cancer Genome Atlas- (TCGA-) KIRC, respectively. ConsensusClusterPlus was used to identify molecular subtypes, and the distribution of immune cell infiltration, anticancer drug sensitivity, and somatic gene mutations was studied in these subtypes. Subsequently, LASSO-Cox regression and univariate Cox regression were also carried out to construct a necroptosis-related signature. Cox regression, survival analysis, clinicopathological characteristic correlation analysis, nomogram, cancer stem cell analysis, and receiver operating characteristic (ROC) curve were some tools employed to study the prognostic power of the signature. Results Based on the expression patterns of 66 survival-related necroptosis genes, we classified the KIRC into three subtypes (C1, C2, and C3) that are associated with necroptosis, which had significantly different tumor stem cell components. Among these, C2 patients had a longer survival time and enhanced immune status and were more sensitive to conventional chemotherapeutic drugs. Moreover, in order to predict the prognosis of KIRC patients, five genes (BMP8A, TLCD1, CLGN, GDF7, and RARB) were used to develop a necroptosis-related prognostic signature, which had an acceptable predictive potency. The results from Cox regression and stratified survival analysis revealed that the signature was an independent prognostic factor, whereas the nomogram and calibration curve demonstrated satisfactory survival time prediction based on the risk score. Conclusions Three molecular subtypes and five necroptosis-related genes were discovered in KIRC using data from TCGA-KIRC and RECA-EU. Thus, a new biomarker and a potentially effective therapeutic approach for KIRC patients were provided in the current study.
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Ji C, He Y, Wang Y. Identification of necroptosis subtypes and development of necroptosis-related risk score model for in ovarian cancer. Front Genet 2022; 13:1043870. [PMID: 36568363 PMCID: PMC9773578 DOI: 10.3389/fgene.2022.1043870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/23/2022] [Indexed: 12/13/2022] Open
Abstract
Background: ith the ongoing development of targeted therapy, non-apoptotic cell death, including necroptosis, has become a popular topic in the field of prevention and treatment. The purpose of this study was to explore the effect of necroptosis-related genes (NRGs) on the classification of ovarian cancer (OV) subtypes and to develop a necroptosis-related risk score (NRRS) classification system. Methods: 74 NRGs were obtained from the published studies, and univariate COX regression analysis was carried out between them and OV survival. Consensus clustering analysis was performed on OV samples according to the expression of NRGs related to prognosis. Furthermore, the NRRS model was developed by combining Weighted Gene Co-Expression Network Analysis (WGCNA) with least absolute shrinkage and selection operator (Lasso)-penalized Cox regression and multivariate Cox regression analysis. And the decision tree model was constructed based on the principle of random forest screening factors principle. Results: According to the post-related NRGs, OV was divided into two necroptosis subtypes. Compared with Cluster 1 (C1), the overall survival (OS) of Cluster 2 (C2) was significantly shorter, stromal score and immune score, the infiltration level of tumor associated immune cells and the expression of 20 immune checkpoints were significantly higher. WGCNA identified the blue module most related to necroptosis subtype, and 12 genes in the module were used to construct NRRS. NRRS was an independent prognostic variable of OV. The OS of samples with lower NRRS was significantly longer, and tumor mutation burden and homologous recombination defect were more obvious. Conclusion: This study showed that necroptosis plays an important role in the classification, prognosis, immune infiltration and biological characteristics of OV subtypes. The evaluation of tumor necroptosis may provide a new perspective for OV treatment.
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Tang H, Chen H, Yuan H, Jin X, Chen G. Comprehensive analysis of necroptosis-related long noncoding RNA to predict prognosis, immune status, and immunotherapeutic response in clear cell renal cell carcinoma. Transl Cancer Res 2022; 11:4254-4271. [PMID: 36644185 PMCID: PMC9834578 DOI: 10.21037/tcr-22-1764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 10/21/2022] [Indexed: 12/23/2022]
Abstract
Background Necroptosis has been found to be associated with tumorigenesis and tumor progression. However, the prognostic effect of long noncoding RNAs (lncRNAs) associated with necroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. Methods Pearson correlation analysis was used to identify necroptosis-related genes and lncRNAs obtained from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression analyses were used to identify a novel necroptosis-associated lncRNAs signature that significantly correlated with survival of ccRCC. Next, single sample gene set enrichment analysis (ssGSEA) was employed to assess the extent of infiltration with immune cells. Analyses to predict the half-maximal inhibitory concentration (IC50) of patients in different risk groups were also conducted. Moreover, follow-up data of an immunotherapy cohort were used to test for differences in the immunotherapeutic efficiency between two risk groups. Finally, patients with ccRCC were divided into two groups based on 6 prognostic lncRNAs. Results We developed a signature of necroptosis-related lncRNAs, which was verified as an independent prognostic factor that can predict prognosis up to 7 years. Patients with higher risk scores were shown to have higher immune suppressive cell infiltration levels and expression of immune checkpoint genes, which suggests that these patients were in a state of immunosuppression. Patients in the low-risk group were found to have an increased response to immunotherapy. A prognostic prediction nomogram was conducted to predict long-term survival of patients. Cluster A tumors were considered hot tumors, since they were correlated with higher levels of immune infiltration and were more sensitive to immunotherapy. Conclusions A comprehensive bioinformatics analysis was conducted, which found that the necroptosis-associated lncRNA signature might be a potent prognostic factor for patients with ccRCC, which could contribute to improved prognosis of these patients.
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Affiliation(s)
- Haibin Tang
- Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hualin Chen
- Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Heng Yuan
- Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaoxiang Jin
- Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Gang Chen
- Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Wu G, Feng D, Zhang Z, Zhang G, Zhang W. Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes. Front Genet 2022; 13:1037011. [PMID: 36452156 PMCID: PMC9702361 DOI: 10.3389/fgene.2022.1037011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 10/26/2022] [Indexed: 03/14/2024] Open
Abstract
Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its potential regulatory mechanisms for diagnosing and treating LUAD. According to the expression profile data along with the clinical information related to LUAD from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a consistency matrix through consistency clustering, and used the ConsensusClusterPlus as the measurement distance to cluster and subtype the samples, and performed gene set enrichment analysis and immune infiltration analysis. Least absolute shrinkage and selection operator (Lasso) regression was utilized for obtaining prognostic significant necroptosis phenotype-related genes. Finally, we measured each patient's riskscore (RS) and build a risk model, and predicted the effect of immunotherapy for different groups of risk factors in the model. Three molecular subtypes of LUAD were obtained by cluster analysis of necroptosis-related genes in LUAD samples. Compared with C1, C3 had a better prognosis and higher immune cell infiltration. The prognosis of the C1 subtype was poor and had a high clinical grade. The proportion of Stage II, Stage III, and Stage IV was much more in comparison with that of the other two subtypes. TP53 gene had a high mutation frequency in the C1 subtype. Gene Set Enrichment Analysis (GSEA) indicated that the aberrant pathways in the C1 and C3 subtypes mainly included some cell cycle-related pathways. In addition, seven genes were identified as related genes of necroptosis phenotype affecting prognosis. High RS had a poor prognosis, while low RS had a good prognosis. The RS was verified to have a strong ability to predict survival. LUAD can be classified by the genes linked with cell necrosis and apoptosis. The difference among various types is helpful to deepen the understanding of LUAD. In addition, a risk model was constructed based. In conclusion, this study provides potential detection targets and treatment methods for LUAD from a new perspective.
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Affiliation(s)
- Guodong Wu
- Department of Thoracic and Cardiovascular Surgery, The First Hospital of Fangshan District, Beijing, China
| | - Dingwei Feng
- Department of Thoracic Surgery, Beijing Yanhua Hospital, Beijing, China
| | - Ziyu Zhang
- Department of Thoracic and Cardiovascular Surgery, The First Hospital of Fangshan District, Beijing, China
| | - Gao Zhang
- Department of Thoracic and Cardiovascular Surgery, The First Hospital of Fangshan District, Beijing, China
| | - Wei Zhang
- Department of Thoracic and Cardiovascular Surgery, The First Hospital of Fangshan District, Beijing, China
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Qualification of Necroptosis-Related lncRNA to Forecast the Treatment Outcome, Immune Response, and Therapeutic Effect of Kidney Renal Clear Cell Carcinoma. JOURNAL OF ONCOLOGY 2022; 2022:3283343. [PMID: 36226251 PMCID: PMC9550517 DOI: 10.1155/2022/3283343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/16/2022] [Accepted: 08/24/2022] [Indexed: 11/18/2022]
Abstract
Background Kidney renal clear cell carcinoma (KIRC) is considered as a highly immune infiltrative tumor. Necroptosis is an inflammatory programmed cell death associated with a wide range of diseases. Long noncoding RNAs (lncRNAs) play important roles in gene regulation and immune function. lncRNA associated with necroptosis could systematically explore the prognostic value, regulate tumor microenvironment (TME), etc. Method The patients' data was collected from TCGA datasets. We used the univariate Cox regression (UCR) to select prediction lncRNAs that are related to necroptosis. Meanwhile, risk models were constructed using LASSO Cox regression (LCR). Kaplan–Meier (KM) analysis, accompanied with receiver operating characteristic (ROC) curves, was performed to assess the independent risk factors of different clinical characteristics. The evaluated factors are age, gender, disease staging, grade, and their related risk score. Databases such as Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to search the probable biological characteristics that could influence the risk groups, containing signaling pathway and immue-related pathways. The single-sample gene set enrichment analysis (ssGSEA) was chosen to perform gene set variation analysis (GSVA), and the GSEABase package was selected to detect the immune and inflammatory infiltration profiles. The TIDE and IC50 evaluation were used to estimate the effectiveness of clinical treatment on KIRC. Results Based on the above analysis, we have got a conclusion that patients who show high risk had higher immune infiltration, immune checkpoint expression, and poorer prognosis. We identified 19 novel prognostic necroptosis-related lncRNAs, which could offer opinions for a deeper study of KIRC. Conclusion The risk model we constructed makes it possible to predict the prognosis of KIRC patients and offers directions for further research on the prognostication and treatment strategies for KIRC.
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Li J, Liu X, Qi Y, Liu Y, Du E, Zhang Z. A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma. Front Immunol 2022; 13:922929. [PMID: 36189275 PMCID: PMC9524857 DOI: 10.3389/fimmu.2022.922929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 08/26/2022] [Indexed: 11/13/2022] Open
Abstract
Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients’ prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients.
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Affiliation(s)
| | | | | | | | - E. Du
- *Correspondence: E. Du, ; Zhihong Zhang,
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Miao Y, Liu J, Liu X, Yuan Q, Li H, Zhang Y, Zhan Y, Feng X. Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma. Front Genet 2022; 13:951239. [PMID: 36186436 PMCID: PMC9524234 DOI: 10.3389/fgene.2022.951239] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 08/15/2022] [Indexed: 11/29/2022] Open
Abstract
Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.
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Affiliation(s)
- Ye Miao
- Department of Neurosurgery, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Jifeng Liu
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xishu Liu
- Department of Neurosurgery, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Qihang Yuan
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hanshuo Li
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yunshu Zhang
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yibo Zhan
- Department of Thoracic Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xiaoshi Feng
- Department of Endocrinology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China
- *Correspondence: Xiaoshi Feng,
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Zhang G, Chen X, Fang J, Tai P, Chen A, Cao K. Cuproptosis status affects treatment options about immunotherapy and targeted therapy for patients with kidney renal clear cell carcinoma. Front Immunol 2022; 13:954440. [PMID: 36059510 PMCID: PMC9437301 DOI: 10.3389/fimmu.2022.954440] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/05/2022] [Indexed: 01/10/2023] Open
Abstract
The development of immunotherapy has changed the treatment landscape of advanced kidney renal clear cell carcinoma (KIRC), offering patients more treatment options. Cuproptosis, a novel cell death mode dependent on copper ions and mitochondrial respiration has not yet been studied in KIRC. We assembled a comprehensive cohort of The Cancer Genome Atlas (TCGA)-KIRC and GSE29609, performed cluster analysis for typing twice using seven cuproptosis-promoting genes (CPGs) as a starting point, and assessed the differences in biological and clinicopathological characteristics between different subtypes. Furthermore, we explored the tumor immune infiltration landscape in KIRC using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) and the potential molecular mechanisms of cuproptosis in KIRC using enrichment analysis. We constructed a cuproptosis score (CUS) using the Boruta algorithm combined with principal component analysis. We evaluated the impact of CUS on prognosis, targeted therapy, and immunotherapy in patients with KIRC using survival analysis, the predictions from the Cancer Immunome Atlas database, and targeted drug susceptibility analysis. We found that patients with high CUS levels show poor prognosis and efficacy against all four immune checkpoint inhibitors, and their immunosuppression may depend on TGFB1. However, the high-CUS group showed higher sensitivity to sunitinib, axitinib, and elesclomol. Sunitinib monotherapy may reverse the poor prognosis and result in higher progression free survival. Then, we identified two potential CPGs and verified their differential expression between the KIRC and the normal samples. Finally, we explored the effect of the key gene FDX1 on the proliferation of KIRC cells and confirmed the presence of cuproptosis in KIRC cells. We developed a targeted therapy and immunotherapy strategy for advanced KIRC based on CUS. Our findings provide new insights into the relationship among cuproptosis, metabolism, and immunity in KIRC.
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Affiliation(s)
| | | | | | | | | | - Ke Cao
- *Correspondence: Ke Cao, ;
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18
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Ren H, Zheng J, Cheng Q, Yang X, Fu Q. Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma. Front Genet 2022; 13:900713. [PMID: 35957699 PMCID: PMC9357940 DOI: 10.3389/fgene.2022.900713] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 06/17/2022] [Indexed: 12/14/2022] Open
Abstract
Background: Hepatocellular carcinoma (HCC) is a common type of primary liver cancer and has a poor prognosis. In recent times, necroptosis has been reported to be involved in the progression of multiple cancers. However, the role of necroptosis in HCC prognosis remains elusive.Methods: The RNA-seq data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes (DEGs) and prognosis-related genes were explored, and the nonnegative matrix factorization (NMF) clustering algorithm was applied to divide HCC patients into different subtypes. Based on the prognosis-related DEGs, univariate Cox and LASSO Cox regression analyses were used to construct a necroptosis-related prognostic model. The relationship between the prognostic model and immune cell infiltration, tumor mutational burden (TMB), and drug response were explored.Results: In this study, 13 prognosis-related DEGs were confirmed from 18 DEGs and 24 prognostic-related genes. Based on the prognosis-related DEGs, patients in the TCGA cohort were clustered into three subtypes by the NMF algorithm, and patients in C3 had better survival. A necroptosis-related prognostic model was established according to LASSO analysis, and HCC patients in TCGA and ICGC were divided into high- and low-risk groups. Kaplan–Meier (K–M) survival analysis revealed that patients in the high-risk group had a shorter survival time compared to those in the low-risk group. Using univariate and multivariate Cox analyses, the prognostic model was identified as an independent prognostic factor and had better survival predictive ability in HCC patients compared with other clinical biomarkers. Furthermore, the results revealed that the high-risk patients had higher stromal, immune, and ESTIMATE scores; higher TP53 mutation rate; higher TMB; and lower tumor purities compared to those in the low-risk group. In addition, there were significant differences in predicting the drug response between the high- and low-risk groups. The protein and mRNA levels of these prognostic genes were upregulated in HCC tissues compared to normal liver tissues.Conclusion: We established a necroptosis-related prognostic signature that may provide guidance for individualized drug therapy in HCC patients; however, further experimentation is needed to validate our results.
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Affiliation(s)
- Huili Ren
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianglin Zheng
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Cheng
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyan Yang
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory for Drug Target Research and Pharmacodynamic Evaluation of Hubei Province, Wuhan, China
| | - Qin Fu
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory for Drug Target Research and Pharmacodynamic Evaluation of Hubei Province, Wuhan, China
- *Correspondence: Qin Fu,
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Dai J, Fu Y. Identification of necroptosis‐related gene signature and characterization of tumour microenvironment infiltration in non‐small‐cell lung cancer. J Cell Mol Med 2022; 26:4698-4709. [PMID: 35871768 PMCID: PMC9443942 DOI: 10.1111/jcmm.17494] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/26/2022] [Accepted: 07/05/2022] [Indexed: 11/30/2022] Open
Abstract
Necroptosis is a programmed necrosis in a caspase‐independent fashion. The role of necroptosis‐related genes (NRGs) in lung cancer remains unknow. Herein, we classified TCGA‐LUAD cohort into two necroptosis‐related subtypes (C1 and C2) by consensus clustering analysis. The result showed that subtype C1 had a favourable prognosis and higher infiltration levels of immune cells. Moreover, subtype C1 was more activated in immune‐associated pathways. Then, we established an NRG prognosis model (NRG score) composed of six NRGs (RIPK3, MLKL, TLR2, TLR4, TNFRSF1A, NDRG2) and divided the cohort into low‐ and high‐risk group. We found that the NRG score was associated with prognosis, tumour immune microenvironment and tumour mutation burden. We also constructed an accurate nomogram model to improve the clinical applicability of NRG score. The result indicated that NRG score may be an independent prognostic marker for lung cancer patients. Taken together, we established a prognosis model that may deepen the understanding of NRGs in lung cancer and provide a basis for developing more effective immunotherapy strategies.
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Affiliation(s)
- Juji Dai
- Department of Colorectal and Anal Surgery the First Affiliated Hospital of Wenzhou Medical University Wenzhou China
| | - Yangyang Fu
- Division of Pulmonary Medicine The First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Heart and Lung Wenzhou China
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Wang W, Ye Y, Zhang X, Ye X, Liu C, Bao L. Construction of a Necroptosis-Associated Long Non-Coding RNA Signature to Predict Prognosis and Immune Response in Hepatocellular Carcinoma. Front Mol Biosci 2022; 9:937979. [PMID: 35911976 PMCID: PMC9326067 DOI: 10.3389/fmolb.2022.937979] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 06/23/2022] [Indexed: 12/20/2022] Open
Abstract
Background: Necroptosis is a form of programmed cell death, and studies have shown that long non-coding RNA molecules (lncRNAs) can regulate the process of necroptosis in various cancers. We sought to screen lncRNAs associated with necroptosis to predict prognosis and tumor immune infiltration status in patients with hepatocellular carcinoma (HCC). Methods: Transcriptomic data from HCC tumor samples and normal tissues were extracted from The Cancer Genome Atlas database. Necroptosis-associated lncRNAs were obtained by co-expression analysis. Necroptosis-associated lncRNAs were then screened by Cox regression and least absolute shrinkage and selection operator methods to construct a risk model for HCC. The models were also validated and evaluated by Kaplan-Meier analysis, univariate and multivariate Cox regression, and time-dependent receiver operating characteristic (ROC) curves. In addition, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment, gene set enrichment, principal component, immune correlation, and drug sensitivity analyses were applied to assess model risk groups. To further differentiate the immune microenvironment of different HCC subtypes, the entire dataset was divided into three clusters, based on necroptosis-associated lncRNAs, and a series of analyses performed. Results: We constructed a model comprising four necroptosis-associated lncRNAs: POLH-AS1, DUXAP8, AC131009.1, and TMCC1-AS1. Overall survival (OS) duration was significantly longer in patients classified as low-risk than those who were high-risk, according to our model. Univariate and multivariate Cox regression analyses further confirmed risk score stability. The analyzed models had area under the ROC curve values of 0.786, 0.713, and 0.639 for prediction of 1-, 3-, and 5-year OS, respectively, and risk score was significantly associated with immune cell infiltration and ESTIMATE score. In addition, differences between high and low-risk groups in predicted half-maximal inhibitory concentration values for some targeted and chemical drugs, providing a potential basis for selection of treatment approach. Finally, cluster analysis facilitated more refined differentiation of the immune microenvironment in patients with HCC and may allow prediction of the effectiveness of immune checkpoint inhibitors. Conclusions: This study contributes to understanding of the function of necroptosis-related lncRNAs in predicting the prognosis and immune infiltration status of HCC. The risk model constructed and cluster analysis provide a basis for predicting the prognosis of patients with HCC and to inform the selection of immunotherapeutic strategies.
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Affiliation(s)
- Wenjuan Wang
- Department of Hematology and Oncology, Beilun District People’s Hospital, Ningbo, China
| | - Yingquan Ye
- Oncology Department of Integrated Traditional Chinese and Western Medicine, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xuede Zhang
- Department of Hematology and Oncology, Beilun District People’s Hospital, Ningbo, China
| | - Xiaojuan Ye
- Department of Hematology and Oncology, Beilun District People’s Hospital, Ningbo, China
| | - Chaohui Liu
- Department of Hematology and Oncology, Beilun District People’s Hospital, Ningbo, China
| | - Lingling Bao
- Department of Hematology and Oncology, Beilun District People’s Hospital, Ningbo, China
- *Correspondence: Lingling Bao,
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Liu D, Xu S, Chang T, Ma S, Wang K, Sun G, Chen S, Xu Y, Zhang H. Predicting Prognosis and Distinguishing Cold and Hot Tumors in Bladder Urothelial Carcinoma Based on Necroptosis-Associated lncRNAs. Front Immunol 2022; 13:916800. [PMID: 35860239 PMCID: PMC9289196 DOI: 10.3389/fimmu.2022.916800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 06/06/2022] [Indexed: 12/24/2022] Open
Abstract
Background In reference to previous studies, necroptosis played an important role in cancer development. Our team decided to explore the potential prognostic values of long non-coding RNAs (lncRNAs) associated with necroptosis in bladder urothelial carcinoma (BLCA) and their relationship with the tumor microenvironment (TME) and the immunotherapeutic response for accurate dose. Methods To obtain the required data, bladder urothelial carcinoma transcriptome data were searched from Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/). We used co-expression analysis, differential expression analysis, and univariate Cox regression to screen out prognostic lncRNAs associated with necroptosis in BLCA. Then the least absolute shrinkage and selection operator (LASSO) was conducted to construct the necroptosis-associated lncRNAs model. Based on this model, we also performed the Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC) to estimate the prognostic power of risk score. Multivariate and univariate Cox regression analysis were performed to build up a nomogram. Calibration curves, and time-dependent ROC were also conducted to evaluate nomogram. Principal component analysis (PCA) revealed a difference between high- and low-risk groups. In addition, we explored immune analysis, gene set enrichment analyses (GSEA), and evaluation of the half-maximal inhibitory concentration (IC50) in constructed model. Finally, the entire samples were divided into three clusters based on model of necroptosis-associated lncRNAs to further compare immunotherapy in cold and hot tumors. Results A model was built up based on necroptosis-associated lncRNAs. The model revealed good consistence between calibration plots and prognostic prediction. The area of 1-, 3-, and 5-year OS under the ROC curve (AUC) were 0.707, 0.679, and 0.675. Risk groups could be helpful for systemic therapy due to the markedly diverse IC50 between risk groups. To our delight, clusters could effectively identify cold and hot tumors, which would be beneficial to accurate mediation. Clusters 2 and 3 were considered the hot tumor, which was more sensitive to immunotherapeutic drugs. Conclusions The outcomes of our study suggested that necroptosis-associated lncRNAs could effectively predict patients with BLCA prognosis, which may be helpful for distinguishing the cold and hot tumors and improving individual treatment of BLCA.
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Liu T, Guo L, Liu G, Xie F, Zhang J, Dai Z, Wang J, Zhang J. Identification of necroptosis-related signature and tumor microenvironment infiltration characteristics in lung adenocarcinoma. Lung Cancer 2022; 172:75-85. [DOI: 10.1016/j.lungcan.2022.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 07/11/2022] [Accepted: 07/25/2022] [Indexed: 11/24/2022]
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Luo Y, Zhang G. Identification of a Necroptosis-Related Prognostic Index and Associated Regulatory Axis in Kidney Renal Clear Cell Carcinoma. Int J Gen Med 2022; 15:5407-5423. [PMID: 35685693 PMCID: PMC9173730 DOI: 10.2147/ijgm.s367173] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/20/2022] [Indexed: 01/10/2023] Open
Affiliation(s)
- Yong Luo
- Department of Urology, the Second People’s Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, Foshan, 528000, People’s Republic of China
- Correspondence: Yong Luo, Department of Urology, the Second People’s Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, 78 Weiguo Road, Foshan, 528000, People’s Republic of China, Tel +86-15625093895, Fax +86-0757-88032009, Email
| | - Guian Zhang
- School of Medicine, South China University of Technology, Guangzhou, 510006, People’s Republic of China
- Guian Zhang, School of Medicine, South China University of Technology, Guangzhou, 510006, People’s Republic of China, Tel +86-13246808932, Email
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