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Ye Z, Li W, Ouyang H, Ruan Z, Liu X, Lin X, Chen X. Natural killer (NK) cells-related gene signature reveals the immune environment heterogeneity in hepatocellular carcinoma based on single cell analysis. Discov Oncol 2024; 15:406. [PMID: 39231877 PMCID: PMC11374944 DOI: 10.1007/s12672-024-01287-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 08/28/2024] [Indexed: 09/06/2024] Open
Abstract
The early diagnosis of liver cancer is crucial for the treatment and depends on the coordinated use of several test procedures. Early diagnosis is crucial for precision therapy in the treatment of the hepatocellular carcinoma (HCC). Therefore, in this study, the NK cell-related gene prediction model was used to provide the basis for precision therapy at the gene level and a novel basis for the treatment of patients with liver cancer. Natural killer (NK) cells have innate abilities to recognize and destroy tumor cells and thus play a crucial function as the "innate counterpart" of cytotoxic T cells. The natural killer (NK) cells is well recognized as a prospective approach for tumor immunotherapy in treating patients with HCC. In this research, we used publicly available databases to collect bioinformatics data of scRNA-seq and RNA-seq from HCC patients. To determine the NK cell-related genes (NKRGs)-based risk profile for HCC, we isolated T and natural killer (NK) cells and subjected them to analysis. Uniform Manifold Approximation and Projection plots were created to show the degree of expression of each marker gene and the distribution of distinct clusters. The connection between the immunotherapy response and the NKRGs-based signature was further analyzed, and the NKRGs-based signature was established. Eventually, a nomogram was developed using the model and clinical features to precisely predict the likelihood of survival. The prognosis of HCC can be accurately predicted using the NKRGs-based prognostic signature, and thorough characterization of the NKRGs signature of HCC may help to interpret the response of HCC to immunotherapy and propose a novel tumor treatment perspective.
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Affiliation(s)
- Zhirong Ye
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Guangdong Medical University, No. 12, Minyou Road, Xiashan District, Zhanjiang, 524000, Guangdong, China
| | - Wenjun Li
- Department of Anesthesia, Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, China
| | - Hao Ouyang
- Department of Clinical Laboratory, Dongguan Binhaiwan Central Hospital, Dongguan, 523903, Guangdong, China
| | - Zikang Ruan
- Department of Hepatobiliary Surgery, The People's Hospital of Gaozhou, No. 89, Xiguan Road, Gaozhou, Maoming, 525200, Guangdong, China
| | - Xun Liu
- Department of Clinical Laboratory, The People's Hospital of Xingning, Meizhou, 514500, Guangdong, China
| | - Xiaoxia Lin
- Department of Hepatobiliary Surgery, The People's Hospital of Gaozhou, No. 89, Xiguan Road, Gaozhou, Maoming, 525200, Guangdong, China.
| | - Xuanting Chen
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Guangdong Medical University, No. 12, Minyou Road, Xiashan District, Zhanjiang, 524000, Guangdong, China.
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Xia X, Xu F, Dai D, Xiong A, Sun R, Ling Y, Qiu L, Wang R, Ding Y, Lin M, Li H, Xie Z. VDR is a potential prognostic biomarker and positively correlated with immune infiltration: a comprehensive pan-cancer analysis with experimental verification. Biosci Rep 2024; 44:BSR20231845. [PMID: 38639057 PMCID: PMC11065647 DOI: 10.1042/bsr20231845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 03/08/2024] [Accepted: 04/17/2024] [Indexed: 04/20/2024] Open
Abstract
The vitamin D receptor (VDR) is a transcription factor that mediates a variety of biological functions of 1,25-dihydroxyvitamin D3. Although there is growing evidence of cytological and animal studies supporting the suppressive role of VDR in cancers, the conclusion is still controversial in human cancers and no systematic pan-cancer analysis of VDR is available. We explored the relationships between VDR expression and prognosis, immune infiltration, tumor microenvironment, or gene set enrichment analysis (GSEA) in 33 types of human cancers based on multiple public databases and R software. Meanwhile, the expression and role of VDR were experimentally validated in papillary thyroid cancer (PTC). VDR expression decreased in 8 types and increased in 12 types of cancer compared with normal tissues. Increased expression of VDR was associated with either good or poor prognosis in 13 cancer types. VDR expression was positively correlated with the infiltration of cancer-associated fibroblasts, macrophages, or neutrophils in 20, 12, and 10 cancer types respectively and this correlation was experimentally validated in PTC. Increased VDR expression was associated with increased percentage of stromal or immune components in tumor microenvironment (TME) in 24 cancer types. VDR positively and negatively correlated genes were enriched in immune cell function and energy metabolism pathways, respectively, in the top 9 highly lethal tumors. Additionally, VDR expression was increased in PTC and inhibited cell proliferation and migration. In conclusion, VDR is a potential prognostic biomarker and positively correlated with immune infiltration as well as stromal or immune components in TME in multiple human cancers.
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MESH Headings
- Receptors, Calcitriol/genetics
- Receptors, Calcitriol/metabolism
- Humans
- Tumor Microenvironment/immunology
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Prognosis
- Gene Expression Regulation, Neoplastic
- Thyroid Cancer, Papillary/immunology
- Thyroid Cancer, Papillary/genetics
- Thyroid Cancer, Papillary/pathology
- Thyroid Cancer, Papillary/metabolism
- Tumor-Associated Macrophages/immunology
- Tumor-Associated Macrophages/metabolism
- Thyroid Neoplasms/immunology
- Thyroid Neoplasms/genetics
- Thyroid Neoplasms/pathology
- Thyroid Neoplasms/metabolism
- Neoplasms/immunology
- Neoplasms/genetics
- Neoplasms/metabolism
- Neoplasms/pathology
- Cell Line, Tumor
- Cancer-Associated Fibroblasts/metabolism
- Cancer-Associated Fibroblasts/immunology
- Cancer-Associated Fibroblasts/pathology
- Databases, Genetic
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Affiliation(s)
- Xuedi Xia
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Feng Xu
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Dexing Dai
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - An Xiong
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Ruoman Sun
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Yali Ling
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Lei Qiu
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Rui Wang
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Ya Ding
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Miaoying Lin
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Haibo Li
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
| | - Zhongjian Xie
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory of Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, 139 Middle Renmin Road, Changsha 410011, Hunan, China
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Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis. Stem Cells Int 2023; 2023:3827999. [PMID: 36818162 PMCID: PMC9931490 DOI: 10.1155/2023/3827999] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/19/2022] [Accepted: 11/25/2022] [Indexed: 02/10/2023] Open
Abstract
Background Pyroptosis is closely related to the programmed death of cancer cells as well as the tumor immune microenvironment (TIME) via the host-tumor crosstalk. However, the role of pyroptosis-related genes as prognosis and TIME-related biomarkers in skin cutaneous melanoma (SKCM) patients remains unknown. Methods We evaluated the expression profiles, copy number variations, and somatic mutations (CNVs) of 27 genes obtained from MSigDB database regulating pyroptosis among TCGA-SKCM patients. Thereafter, we conducted single-sample gene set enrichment analysis (ssGSEA) for evaluating pyroptosis-associated expression patterns among cases and for exploring the associations with clinicopathological factors and prognostic outcome. In addition, a prognostic pyroptosis-related signature (PPRS) model was constructed by performing Cox regression, weighted gene coexpression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis to score SKCM patients. On the other hand, we plotted the ROC and survival curves for model evaluation and verified the robustness of the model through external test sets (GSE22153, GSE54467, and GSE65904). Meanwhile, we examined the relations of clinical characteristics, oncogene mutations, biological processes (BPs), tumor stemness, immune infiltration degrees, immune checkpoints (ICs), and treatment response with PPRS via multiple methods, including immunophenoscore (IPS) analysis, gene set variation analysis (GSVA), ESTIMATE, and CIBERSORT. Finally, we constructed a nomogram incorporating PPRS and clinical characteristics to improve risk evaluation of SKCM. Results Many pyroptosis-regulated genes showed abnormal expression within SKCM. TP53, TP63, IL1B, IL18, IRF2, CASP5, CHMP4C, CHMP7, CASP1, and GSDME were detected with somatic mutations, among which, a majority displayed CNVs at high frequencies. Pyroptosis-associated profiles established based on pyroptosis-regulated genes showed markedly negative relation to low stage and superior prognostic outcome. Blue module was found to be highly positively correlated with pyroptosis. Later, this study established PPRS based on the expression of 8 PAGs (namely, GBP2, HPDL, FCGR2A, IFITM1, HAPLN3, CCL8, TRIM34, and GRIPAP1), which was highly associated with OS, oncogene mutations, tumor stemness, immune infiltration degrees, IC levels, treatment responses, and multiple biological processes (including cell cycle and immunoinflammatory response) in training and test set samples. Conclusions Based on our observations, analyzing modification patterns associated with pyroptosis among diverse cancer samples via PPRS is important, which can provide more insights into TIME infiltration features and facilitate immunotherapeutic development as well as prognosis prediction.
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Wang Q, Huang X, Zeng S, Zhou R, Wang D. Identification and validation of a TTN-associated immune prognostic model for skin cutaneous melanoma. Front Genet 2023; 13:1084937. [PMID: 36704353 PMCID: PMC9871619 DOI: 10.3389/fgene.2022.1084937] [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: 10/31/2022] [Accepted: 12/27/2022] [Indexed: 01/12/2023] Open
Abstract
TTN is the most commonly mutated gene in skin cutaneous melanoma (SKCM). Tumor mutational burden (TMB) can generate new antigens that regulate the recognition of T cells, which will significantly affect the prognosis of patients. The TTN gene has a long coding sequence and a high number of mutant sites, which allows SKCM patients to produce higher TMB and may influence the immune response. It has been found that the overall survival (OS) of SKCM patients with TTN mutation was significantly higher than that of wild-type patients. However, the effect of TTN mutation on the immune microenvironment of SKCM has not been fully investigated. Here, we systematically explored the relationship and potential mechanisms between TTN mutation status and the immune response. We first revealed that TTN mutated SKCM were significantly associated with four immune-related biological processes. Next, 115 immune genes differentially expressed between TTN mutation and wild-type SKCM patients were found to significantly affect the OS of SKCM patients. Then, we screened four immune-related genes (CXCL9, PSMB9, CD274, and FCGR2A) using LASSO regression analysis and constructed a TTN mutation-associated immune prognostic model (TM-IPM) to distinguish the SKCM patients with a high or low risk of poor prognosis, independent of multiple clinical characteristics. SKCM in the low-risk group highly expressed a large number of immune-related genes, and functional enrichment analysis of these genes showed that this group was involved in multiple immune processes and pathways. Furthermore, the nomogram constructed by TM-IPM with other clinicopathological parameters can provide a predictive tool for clinicians. Moreover, we found that CD8+ T cells were significantly enriched in the low-risk group. The expression level of immune checkpoints was higher in the low-risk group than in the high-risk group. Additionally, the response to chemotherapeutic agents was higher in the low-risk group than in the high-risk group, which may be related to the long survival in the low-risk group. Collectively, we constructed and validated a TM-IPM using four immune-related genes and analyzed the potential mechanisms of TM-IPM to predict patient prognosis and response to immunotherapy from an immunological perspective.
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Affiliation(s)
- Qirui Wang
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingtai Huang
- Shanghai Key Laboratory of Stomatology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, Department of Orthodontics, College of Stomatology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Siyi Zeng
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Renpeng Zhou
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Danru Wang
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Xing J, Guo L, Jia Z, Li Y, Han Y. The Multi-Omics Landscape and Clinical Relevance of the Immunological Signature of Phagocytosis Regulators: Implications for Risk Classification and Frontline Therapies in Skin Cutaneous Melanoma. Cancers (Basel) 2022; 14:cancers14153582. [PMID: 35892841 PMCID: PMC9331497 DOI: 10.3390/cancers14153582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/09/2022] [Accepted: 07/20/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary In this study, we focused on exploring phagocytosis regulators’ expression and mutational characteristics in skin cutaneous melanoma samples and delineating two molecular subtypes based on expression characteristics. We determined the relationship between phagocytosis regulators and survival by survival analysis of molecular subtypes. We then constructed a survival model (PRRS) to further quantify the criteria. Moreover, we combined pathway analysis, immune infiltration analysis, and mutation analysis to deeply explore the effects of phagocytosis regulators on skin cutaneous melanoma samples. Abstract Tumor-associated macrophages (TAMs) have gained considerable attention as therapeutic targets. Monoclonal antibody treatments directed against tumor antigens contribute significantly to cancer cell clearance by activating macrophages to phagocytose tumor cells. Due to its complicated genetic and molecular pathways, skin cutaneous melanoma (SKCM) has not yet attained the expected clinical efficacy and prognosis when compared to other skin cancers. Therefore, we chose TAMs as an entrance point. This study aimed to thoroughly assess the dysregulation and regulatory role of phagocytosis regulators in SKCM, as well as to understand their regulatory patterns in SKCM. This study subtyped prognosis-related phagocytosis regulators to investigate prognostic differences between subtypes. Then, we screened prognostic factors and constructed phagocytosis-related scoring models for survival prediction using differentially expressed genes (DEGs) between subtypes. Additionally, we investigated alternative treatment options using chemotherapeutic drug response data and clinical cohort treatment data. We first characterized and generalized phagocytosis regulators in SKCM and extensively examined the tumor immune cell infiltration. We created two phagocytosis regulator-related system (PRRS) phenotypes and derived PRRS scores using a principal component analysis (PCA) technique. We discovered that subtypes with low PRRS scores had a poor prognosis and decreased immune checkpoint-associated gene expression levels. We observed significant therapeutic and clinical improvements in patients with higher PRRS scores. Our findings imply that the PRRS scoring system can be employed as an independent and robust prognostic biomarker, serving as a critical reference point for developing novel immunotherapeutic methods.
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Affiliation(s)
- Jiahua Xing
- The First Medical Center, Department of Plastic and Reconstructive Surgery, Chinese PLA General Hospital, Beijing 100853, China; (J.X.); (L.G.); (Y.L.)
- School of Medicine, Nankai University, Tianjin 300071, China
| | - Lingli Guo
- The First Medical Center, Department of Plastic and Reconstructive Surgery, Chinese PLA General Hospital, Beijing 100853, China; (J.X.); (L.G.); (Y.L.)
| | - Ziqi Jia
- Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China;
| | - Yan Li
- The First Medical Center, Department of Plastic and Reconstructive Surgery, Chinese PLA General Hospital, Beijing 100853, China; (J.X.); (L.G.); (Y.L.)
| | - Yan Han
- The First Medical Center, Department of Plastic and Reconstructive Surgery, Chinese PLA General Hospital, Beijing 100853, China; (J.X.); (L.G.); (Y.L.)
- Correspondence:
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Chen Y, Feng Y, Yan F, Zhao Y, Zhao H, Guo Y. A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study. Front Immunol 2022; 13:922195. [PMID: 35935989 PMCID: PMC9351622 DOI: 10.3389/fimmu.2022.922195] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/01/2022] [Indexed: 11/14/2022] Open
Abstract
Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease.
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Affiliation(s)
- Yun Chen
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yunzhi Feng
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fei Yan
- Hunan Key Laboratory of Oral Health Research, Hunan 3D Printing Engineering Research Center of Oral Care, Hunan Clinical Research Center of Oral Major Diseases and Oral Health, Xiangya Stomatological Hospital, Xiangya School of Stomatology, Central South University, Changsha, China
| | - Yaqiong Zhao
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Han Zhao
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, National Health Commission (NHC) Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
- Shanghai Key Laboratory of Visual Impairment and Restoration, Fudan University, Shanghai, China
- *Correspondence: Han Zhao, ; Yue Guo,
| | - Yue Guo
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Han Zhao, ; Yue Guo,
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Xu Y, Chen Y, Niu Z, Xing J, Yang Z, Yin X, Guo L, Zhang Q, Qiu H, Han Y. A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies. Front Med (Lausanne) 2022; 9:841568. [PMID: 35492358 PMCID: PMC9053829 DOI: 10.3389/fmed.2022.841568] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/04/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThe purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients.MethodsGene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines.ResultsA total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues.ConclusionOur novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.
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Affiliation(s)
- Yujian Xu
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Youbai Chen
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zehao Niu
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jiahua Xing
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zheng Yang
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiangye Yin
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Lingli Guo
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Qixu Zhang
- Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Haixia Qiu
- Department of Laser Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Haixia Qiu
| | - Yan Han
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
- Yan Han
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Zhang W, Kong Y, Li Y, Shi F, Lyu J, Sheng C, Wang S, Wang Q. Novel Molecular Determinants of Response or Resistance to Immune Checkpoint Inhibitor Therapies in Melanoma. Front Immunol 2022; 12:798474. [PMID: 35087523 PMCID: PMC8787219 DOI: 10.3389/fimmu.2021.798474] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 12/16/2021] [Indexed: 12/13/2022] Open
Abstract
Background Immune checkpoint inhibitor (ICI) therapy dramatically prolongs melanoma survival. Currently, the identified ICI markers are sometimes ineffective. The objective of this study was to identify novel determinants of ICI efficacy. Methods We comprehensively curated pretreatment somatic mutational profiles and clinical information from 631 melanoma patients who received blockade therapy of immune checkpoints (i.e., CTLA-4, PD-1/PD-L1, or a combination). Significantly mutated genes (SMGs), mutational signatures, and potential molecular subtypes were determined. Their association with ICI responses was assessed simultaneously. Results We identified 27 SMGs, including four novel SMGs (COL3A1, NRAS, NARS2, and DCC) that are associated with ICI efficacy and well-known driver genes. COL3A1 mutations were associated with improved ICI overall survival (hazard ratio (HR): 0.64, 95% CI: 0.45-0.91, p = 0.012), whereas immune resistance was observed in patients with NRAS mutations (HR: 1.42, 95% CI: 1.10-1.82, p = 0.006). The presence of the tobacco smoking-related signature was significantly correlated with inferior prognoses (HR: 1.42, 95% CI: 1.11-1.82, p = 0.005). In addition, the signature resembling that of alkylating agents and a newly discovered signature both exhibited extended prognoses (both HR < 1, p < 0.05). Based on the activities of the extracted 6 mutational signatures, we identified one immune subtype that was significantly associated with better ICI outcomes (HR: 0.44, 95% CI: 0.23-0.87, p = 0.017). Conclusion We uncovered several novel SMGs and re-annotated mutational signatures that are linked to immunotherapy response or resistance. In addition, an immune subtype was found to exhibit favorable prognoses. Further studies are required to validate these findings.
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Affiliation(s)
- Wenjing Zhang
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
| | - Yujia Kong
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
| | - Yuting Li
- Tianjin Cancer Institute, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Fuyan Shi
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
| | - Juncheng Lyu
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
| | - Chao Sheng
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Suzhen Wang
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
| | - Qinghua Wang
- Department of Health Statistics, Key Laboratory of Medicine and Health in Shandong Province, School of Public Health, Weifang Medical University, Weifang, China
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9
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Shi Y, Li Z, Zhou Z, Liao S, Wu Z, Li J, Yin J, Wang M, Weng M. Identification and validation of an epithelial mesenchymal transition-related gene pairs signature for prediction of overall survival in patients with skin cutaneous melanoma. PeerJ 2022; 10:e12646. [PMID: 35116193 PMCID: PMC8785661 DOI: 10.7717/peerj.12646] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 11/26/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND We aimed to construct a novel epithelial-mesenchymal transition (EMT)-related gene pairs (ERGPs) signature to predict overall survival (OS) in skin cutaneous melanoma (CM) patients. METHODS Expression data of the relevant genes, corresponding clinicopathological parameters, and follow-up data were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis was utilized to identify ERGPs significantly associated with OS, and LASSO analysis was used to identify the genes used for the construction of the ERGPs signature. The optimal cutoff value determined by the receiver operating characteristic curve was used to classify patients into high-risk and low-risk groups. Survival curves were generated using the Kaplan-Meier method, and differences between the two groups were estimated using the log-rank test. The independent external datasets GSE65904 and GSE19234 were used to verify the performance of the ERGPs signature using the area under the curve (AUC) values. In addition, we also integrated clinicopathological parameters and risk scores to develop a nomogram that can individually predict the prognosis of patients with CM. RESULTS A total of 104 ERGPs related to OS were obtained, of which 21 ERGPs were selected for the construction of the signature. All CM patients were stratified into high-and low-risk groups based on an optimal risk score cutoff value of 0.281. According to the Kaplan-Meier analysis, the mortality rate in the low-risk group was lower than that in the high-risk group in the TCGA cohort (P < 0.001), GSE65904 cohort (P = 0.006), and GSE19234 cohort (P = 0.002). Multivariate Cox regression analysis indicated that our ERGP signature was an independent risk factor for OS in CM patients in the three cohorts (for TCGA: HR, 2.560; 95% CI [1.907-3.436]; P < 0.001; for GSE65904: HR = 2.235, 95% CI [1.492-3.347], P < 0.001; for GSE19234: HR = 2.458, 95% CI [1.065-5.669], P = 0.035). The AUC value for predicting the 5-year survival rate of patients with CM of our developed model was higher than that of two previously established prognostic signatures. Both the calibration curve and the C-index (0.752, 95% CI [0.678-0.826]) indicated that the developed nomogram was highly accurate. Most importantly, the decision curve analysis results showed that the nomogram had a higher net benefit than that of the American Joint Committee on Cancer stage system. CONCLUSION Our study established an ERGPs signature that could be potentially used in a clinical setting as a genetic biomarker for risk stratification of CM patients. In addition, the ERGPs signature could also predict which CM patients will benefit from PD-1 and PD-L1 inhibitors.
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Affiliation(s)
- Yucang Shi
- Department of Plastic Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zhanpeng Li
- Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Zhihong Zhou
- Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Simu Liao
- Department of Plastic Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zhiyuan Wu
- Department of Plastic Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Jie Li
- Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Jiasheng Yin
- Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Meng Wang
- Department of Plastic Surgery, Longhua District People’s Hospital, Shenzhen, China
| | - Meilan Weng
- Graduate School of Guangdong Medical University, Zhanjiang, China
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10
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Liu J, Zhang X, Ye T, Dong Y, Zhang W, Wu F, Bo H, Shao H, Zhang R, Shen H. Prognostic modeling of patients with metastatic melanoma based on tumor immune microenvironment characteristics. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:1448-1470. [PMID: 35135212 DOI: 10.3934/mbe.2022067] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs. Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT and Xcell in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 demonstrated the visible difference in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes from the nine-IRG prognostic model, and the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, the expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 were analyzed between metastatic melanoma and normal samples. Overall, a prognostic model for metastatic melanoma based on the tumor immune microenvironment characteristics was established, which left plenty of space for further studies. It could function well in helping people to understand characteristics of the immune microenvironment in metastatic melanoma.
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Affiliation(s)
- Jing Liu
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Xuefang Zhang
- Department of Radiation Oncology, Dongguan People's Hospital, Affiliated Dongguan Hospital of Southern Medical University, Dongguan, Guangdong 523059, China
| | - Ting Ye
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Yongjian Dong
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Wenfeng Zhang
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Fenglin Wu
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Huaben Bo
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Hongwei Shao
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Rongxin Zhang
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
| | - Han Shen
- Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, China
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Liu L, Zhu J, Jin T, Huang M, Chen Y, Xu L, Chen W, Jiang B, Yan F. Identification of Immune Function-Related Subtypes in Cutaneous Melanoma. Life (Basel) 2021; 11:life11090925. [PMID: 34575074 PMCID: PMC8467264 DOI: 10.3390/life11090925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/24/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
Tumour immunotherapy combined with molecular typing is a new therapy to help select patients. However, molecular typing algorithms related to tumour immune function have not been thoroughly explored. We herein proposed a single sample immune signature network (SING) method to identify new immune function-related subtypes of cutaneous melanoma of the skin. A sample-specific network and tumour microenvironment were constructed based on the immune annotation of cutaneous melanoma samples. Then, the differences and heterogeneity of immune function among different subtypes were analysed and verified. A total of 327 cases of cutaneous melanoma were divided into normal and immune classes; the immune class had more immune enrichment characteristics. After further subdividing the 327 cases into three immune-related subtypes, the degree of immune enrichment in the "high immune subtype" was greater than that in other subtypes. Similar results were validated in both tumour samples and cell lines. Sample-specific networks and the tumour microenvironment based on immune annotation contribute to the mining of cutaneous melanoma immune function-related subtypes. Mutations in B2M and PTEN are considered potential therapeutic targets that can improve the immune response. Patients with a high immune subtype can generally obtain a better immune prognosis effect, and the prognosis may be improved when combined with TGF-β inhibitors.
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12
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Wu XR, Chen Z, Liu Y, Chen ZZ, Tang F, Chen ZZ, Li JJ, Liao JL, Cao K, Chen X, Zhou J. Prognostic signature and immune efficacy of m 1 A-, m 5 C- and m 6 A-related regulators in cutaneous melanoma. J Cell Mol Med 2021; 25:8405-8418. [PMID: 34288419 PMCID: PMC8419166 DOI: 10.1111/jcmm.16800] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/18/2021] [Accepted: 07/06/2021] [Indexed: 12/13/2022] Open
Abstract
Cutaneous melanoma (CM) is an aggressive cancer; given that initial and specific signs are lacking, diagnosis is often late and the prognosis is poor. RNA modification has been widely studied in tumour progression. Nevertheless, little progress has been made in the signature of N1 -methyladenosine (m1 A), 5-methylcytosine (m5 C), N6 -methyladenosine (m6 A)-related regulators and the tumour microenvironment (TME) cell infiltration in CM. Our study identified the characteristics of m1 A-, m5 C- and m6 A-related regulators based on 468 CM samples from the public database. Using univariate, multivariate and LASSO Cox regression analysis, a risk model of regulators was established and validated by a nomogram on independent prognostic factors. The gene set variation analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) clarified the involved functional pathways. A combined single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT approach revealed TME of regulator-related prognostic signature. The nine-gene signature stratified the patients into distinct risk subgroups for personalized prognostic assessment. Additionally, functional enrichment, immune infiltration and immunotherapy response analysis indicated that the high-risk group was correlated with T-cell suppression, while the low-risk group was more sensitive to immunotherapy. The findings presented here contribute to our understanding of the TME molecular heterogeneity in CM. Nine m1 A-, m5 C- and m6 A-related regulators may also be promising biomarkers for future research.
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Affiliation(s)
- Xian rui Wu
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zheng Chen
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Yang Liu
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zi zi Chen
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Fengjie Tang
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zhi zhao Chen
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Jing jing Li
- Department of Plastic Surgery of Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Jun lin Liao
- Departments of Medical CosmetologyThe First Affiliated HospitalUniversity of South ChinaHengyangHunanChina
| | - Ke Cao
- Department of Oncology of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Xiang Chen
- Department of DermatologyThe Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Jianda Zhou
- Department of Plastic Surgery of Third Xiangya HospitalCentral South UniversityChangshaHunanChina
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Zhang E, Chen Y, Bao S, Hou X, Hu J, Mu OYN, Song Y, Shan L. Identification of subgroups along the glycolysis-cholesterol synthesis axis and the development of an associated prognostic risk model. Hum Genomics 2021; 15:53. [PMID: 34384498 PMCID: PMC8359075 DOI: 10.1186/s40246-021-00350-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/26/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Skin cutaneous melanoma (SKCM) is one of the most highly prevalent and complicated malignancies. Glycolysis and cholesterogenesis pathways both play important roles in cancer metabolic adaptations. The main aims of this study are to subtype SKCM based on glycolytic and cholesterogenic genes and to build a clinical outcome predictive algorithm based on the subtypes. METHODS A dataset with 471 SKCM specimens was downloaded from The Cancer Genome Atlas (TCGA) database. We extracted and clustered genes from the Molecular Signatures Database v7.2 and acquired co-expressed glycolytic and cholesterogenic genes. We then subtyped the SKCM samples and validated the efficacy of subtypes with respect to simple nucleotide variations (SNVs), copy number variation (CNV), patients' survival statuses, tumor microenvironment, and proliferation scores. We also constructed a risk score model based on metabolic subclassification and verified the model using validating datasets. Finally, we explored potential drugs for high-risk SKCM patients. RESULTS SKCM patients were divided into four subtype groups: glycolytic, cholesterogenic, mixed, and quiescent subgroups. The glycolytic subtype had the worst prognosis and MGAM SNV extent. Compared with the cholesterogenic subgroup, the glycolytic subgroup had higher rates of DDR2 and TPR CNV and higher proliferation scores and MK167 expression levels, but a lower tumor purity proportion. We constructed a forty-four-gene predictive signature and identified MST-321, SB-743921, Neuronal Differentiation Inducer III, romidepsin, vindesine, and YM-155 as high-sensitive drugs for high-risk SKCM patients. CONCLUSIONS Subtyping SKCM patients via glycolytic and cholesterogenic genes was effective, and patients in the glycolytic-gene enriched group were found to have the worst outcome. A robust prognostic algorithm was developed to enhance clinical decisions in relation to drug administration.
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Affiliation(s)
- Enchong Zhang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China
| | - Yijing Chen
- Department of Otolaryngology Head and Neck Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
- School of Postgraduate, China Medical University, Shenyang, Liaoning, China
| | - Shurui Bao
- Department of Breast Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xueying Hou
- School of Postgraduate, China Medical University, Shenyang, Liaoning, China
| | - Jing Hu
- School of Postgraduate, China Medical University, Shenyang, Liaoning, China
| | | | - Yongsheng Song
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China
| | - Liping Shan
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
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14
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Wang J. Prognostic score model-based signature genes for predicting the prognosis of metastatic skin cutaneous melanoma. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:5125-5145. [PMID: 34517481 DOI: 10.3934/mbe.2021261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
PURPOSE Cutaneous melanoma (SKCM) is the most invasive malignancy of skin cancer. Metastasis to distant lymph nodes or other system is an indicator of poor prognosis in melanoma patients. The aim of this study was to identify reliable prognostic biomarkers for SKCMs. METHODS Four RNA-sequencing datasets associated with SKCMs were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database as well as corresponding clinical information. Differentially expressed genes (DEGs) were screened between primary and metastatic samples by using MetaDE tool. Weighted gene co-expression network analysis (WGCNA) was conducted to screen functional modules. A prognostic score (PS)-based predictive model and nomogram model were constructed to identify signature genes and independent clinicopathologic factors. RESULTS Based on MetaDE analysis and WGCNA, a total of 456 overlapped genes were identified as hub genes related to SKCMs progression. Functional enrichment analysis revealed these genes were mainly involved in the hippo signaling pathway, signaling pathways regulating pluripotency of stem cells, pathways in cancer. In addition, eight optimal DEGs (RFPL1S, CTSV, EGLN3, etc.) were identified as signature genes by using PS model. Cox regression analysis revealed that pathologic stage T, N and recurrence were independent prognostic factors. Three clinical factors and PS status were incorporated to construct a nomogram predictive model for estimating the three years and five-year survival probability of individuals. CONCLUSIONS The prognosis prediction model of this study may provide a promising method for decision making in clinic and prognosis predicting of SKCM patients.
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Affiliation(s)
- Jiaping Wang
- Laboratory Medicine, Donghai County People's Hospital, Lianyungang City, Jiangsu 222300, China
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