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Cheng H, Miller D, Southwell N, Fischer JL, Taylor I, Salbaum JM, Kappen C, Hu F, Yang C, Gross SS, D'Aurelio M, Chen Q. Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575105. [PMID: 38370710 PMCID: PMC10871215 DOI: 10.1101/2024.01.10.575105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of structurally identified and yet-undefined metabolites across tissue cryosections. While numerous software packages enable pixel-by-pixel imaging of individual metabolites, the research community lacks a discovery tool that images all metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs informs discovery of unanticipated molecules contributing to shared metabolic pathways, uncovers hidden metabolic heterogeneity across cells and tissue subregions, and indicates single-timepoint flux through pathways of interest. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling and instrument drift, markedly enhances spatial image resolution, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
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Xie J, Zhang P, Ma C, Tang Q, Zhou X, Xu X, Zhang M, Zhao S, Zhou L, Qi M. Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism. Exp Dermatol 2024; 33:e15119. [PMID: 38881438 DOI: 10.1111/exd.15119] [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: 02/02/2024] [Revised: 05/07/2024] [Accepted: 05/29/2024] [Indexed: 06/18/2024]
Abstract
This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE22153, and GSE65904 cohorts from GEO database were processed and harmonized to mitigate batch effects. Lactate metabolism scores were assigned to individual cells using the 'AUCell' package. Weighted Co-expression Network Analysis (WGCNA) was employed to identify gene modules correlated with lactate metabolism. Machine learning algorithms were applied to construct a prognostic model, and its performance was evaluated in multiple cohorts. Immune correlation, mutation analysis, and enrichment analysis were conducted to further characterize the prognostic model's biological implications. Finally, the function of key gene NDUFS7 was verified by cell experiments. Machine learning resulted in an optimal prognostic model, demonstrating significant prognostic value across various cohorts. In the different cohorts, the high-risk group showed a poor prognosis. Immune analysis indicated differences in immune cell infiltration and checkpoint gene expression between risk groups. Mutation analysis identified genes with high mutation loads in SKCM. Enrichment analysis unveiled enriched pathways and biological processes in high-risk SKCM patients. NDUFS7 was found to be a hub gene in the protein-protein interaction network. After the expression of NDUFS7 was reduced by siRNA knockdown, CCK-8, colony formation, transwell and wound healing tests showed that the activity, proliferation and migration of A375 and WM115 cell lines were significantly decreased. This study offers insights into the prognostic significance of lactate metabolism-related genes in SKCM.
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Affiliation(s)
- Jiaheng Xie
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Pengpeng Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Chenfeng Ma
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Qikai Tang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, Jiangsu, China
| | - Xinxin Zhou
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaolong Xu
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Min Zhang
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Songyun Zhao
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Liping Zhou
- Emergency Department of Xiangya Hospital, Central South University, Changsha, China
| | - Min Qi
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
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Nie W, Zhao Z, Liu Y, Wang Y, Zhang J, Hu Y, Liu Y, Wang Y, Wang Z. Integrative Single-Cell Analysis of Cardiomyopathy Identifies Differences in Cell Stemness and Transcriptional Regulatory Networks among Fibroblast Subpopulations. Cardiol Res Pract 2024; 2024:3131633. [PMID: 38799173 PMCID: PMC11127766 DOI: 10.1155/2024/3131633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 03/31/2024] [Accepted: 04/30/2024] [Indexed: 05/29/2024] Open
Abstract
Background Cardiomyopathy encompasses a broad spectrum of diseases affecting myocardial tissue, characterized clinically by abnormalities in cardiac structure, heart failure, and/or arrhythmias. Clinically heterogeneous, major types include dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RM), ischemic cardiomyopathy (ICM), among which DCM is more prevalent, while ICM exhibits higher incidence and mortality rates. Myocardial injury during cardiomyopathy progression may lead to myocardial fibrosis. Failure to intervene early and inhibit the process of myocardial fibrosis may culminate in heart failure. Cardiac fibroblasts constitute crucial cellular components determining the extent and quality of myocardial fibrosis, with various subpopulations exerting diverse roles in cardiomyopathy progression. Despite this, understanding of the cellular plasticity and transcriptional regulatory networks of cardiac fibroblasts in cardiomyopathy remains limited. Therefore, in this study, we conducted comprehensive single-cell analysis of cardiac fibroblasts in cardiomyopathy to explore differences in cellular plasticity and transcriptional regulatory networks among fibroblast subpopulations, with the aim of providing as many useful references as possible for the diagnosis, prognosis, and treatment of cardiomyopathy. Materials and Methods Cells with mitochondrial gene expression comprising >20% of total expressed genes were excluded. Differential expression genes (DEGs) and stemness genes within cardiac fibroblast subpopulations were subjected to Gene Ontology (GO) analysis of biological processes (BP) and AUCell analysis. Monocle software was employed to analyze the pseudo-temporal trajectory of cardiac fibroblasts in cardiomyopathy. Additionally, the Python package SCENIC was utilized to assess enrichment of transcription factors and activity of regulators within cardiac fibroblast subpopulations in cardiomyopathy. Results Following batch effect correction, 179,927 cells were clustered into 32 clusters, designated as T_NK cells, endothelial cells, myeloid cells, fibroblasts, pericytes, SMCs, CMs, proliferating cells, EndoCs, and EPCs. Among them, 8148 fibroblasts were further subdivided into 4 subpopulations, namely C0 THBS4+ Fibroblasts, C1 LINC01133+ Fibroblasts, C2 FGF7+ Fibroblasts, and C3 AGT + Fibroblasts. Results from GO_BP and AUCell analyses suggest that C3 AGT + Fibroblasts may be associated with immune response activation, protein transport, and myocardial contractile function, correlating with disease progression in cardiomyopathy. Transcription factor enrichment analysis indicates that FOS is the most significant TF in C3 AGT + Fibroblasts, also associated with the M1 module, possibly implicated in protein hydrolysis, intracellular DNA replication, and cell proliferation. Moreover, correlation analysis of transcriptional regulatory activity between fibroblast subpopulations reveals a more pronounced heterogeneity within C3 AGT + Fibroblasts in cardiomyopathy. Conclusion C3 AGT + Fibroblasts exhibit increased sensitivity towards adverse outcomes in cardiomyopathy, such as myocardial fibrosis and impaired cardiac contractile function, compared to other cardiac fibroblast subpopulations. The differential cellular plasticity and transcriptional regulatory activity between C3 AGT + Fibroblasts and other subgroups offer new perspectives for targeting fibroblast subpopulation activity to treat cardiomyopathy. Additionally, stemness genes EPAS1 and MYC, along with the regulator FOS, may play roles in modulating the biological processes of cardiac fibroblasts in cardiomyopathy.
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Affiliation(s)
- Wenyang Nie
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Zhijie Zhao
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, 639 Zhi Zao Ju Rd, Shanghai 200011, China
- Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Rd, Shanghai 200025, China
| | - Yuhang Liu
- School of Acupuncture, Moxibustion and Tuina, Shandong University of Traditional Chinese Medicine, 4655 University Rd, Jinan 250355, China
| | - Youcao Wang
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Jingwen Zhang
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Ying Hu
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Yang Liu
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Yong Wang
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
| | - Zhen Wang
- Department of Cardiovascular Diseases, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jing 10 Rd, Jinan 250000, China
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Qin Y, Sheng Y, Ren M, Hou Z, Xiao L, Chen R. Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer. Sci Rep 2024; 14:11133. [PMID: 38750159 PMCID: PMC11096311 DOI: 10.1038/s41598-024-61849-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 05/10/2024] [Indexed: 05/18/2024] Open
Abstract
Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes-C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)-emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.
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Affiliation(s)
- Yuling Qin
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Yawen Sheng
- Shandong University of Traditional Chinese Medicine, Jinan, 250014, Shandong, China
| | - Mengxue Ren
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Zitong Hou
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Lu Xiao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China
| | - Ruixue Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixiange Road, Xicheng District, Beijing, 100053, China.
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Zhang Q, Luo Y, Qian B, Cao X, Xu C, Guo K, Wan R, Jiang Y, Wang T, Mei Z, Liu J, Lv C. A systematic pan-cancer analysis identifies LDHA as a novel predictor for immunological, prognostic, and immunotherapy resistance. Aging (Albany NY) 2024; 16:8000-8018. [PMID: 38709280 PMCID: PMC11132014 DOI: 10.18632/aging.205800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 03/18/2024] [Indexed: 05/07/2024]
Abstract
Lactate dehydrogenase A (LDHA), a critical enzyme involved in glycolysis, is broadly involved multiple biological functions in human cancers. It is reported that LDHA can impact tumor immune surveillance and induce the transformation of tumor-associated macrophages, highlighting its unnoticed function of LDHA in immune system. However, in human cancers, the role of LDHA in prognosis and immunotherapy hasn't been investigated. In this study, we analyzed the expression pattern and prognostic value of LDHA in pan-cancer and explored its association between tumor microenvironment (TME), immune infiltration subtype, stemness scores, tumor mutation burden (TMB), and immunotherapy resistance. We found that LDHA expression is tumor heterogeneous and that its high expression is associated with poor prognosis in multiple human cancers. In addition, LDHA expression was positively correlated with the presence of mononuclear/macrophage cells, and also promoted the infiltration of a range of immune cells. Genomic alteration of LDHA was common in different types of cancer, while with prognostic value in pan-cancers. Pan-cancer analysis revealed that the significant correlations existed between LDHA expression and tumor microenvironment (including stromal cells and immune cells) as well as stemness scores (DNAss and RNAss) across cancer types. Drug sensitivity analysis also revealed that LDHA was able to predict response to chemotherapy and immunotherapy. Furthermore, it was confirmed that knockdown of LDHA reduced proliferation and migration ability of lung cancer cells. Taken together, LDHA could serve as a prognostic biomarker and a potential immunotherapy marker.
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Affiliation(s)
- Qiqi Zhang
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Southwest Medical University, Luzhou, P.R. China
| | - Yuanning Luo
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, P.R. China
| | - Bingshuo Qian
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, P.R. China
- School of Pharmacy, Henan University, Kaifeng, P.R. China
| | - Xiuhua Cao
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou, P.R. China
| | - Caijun Xu
- Southwest Medical University, Luzhou, P.R. China
| | - Kan Guo
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Southwest Medical University, Luzhou, P.R. China
| | - Runlan Wan
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, P.R. China
| | - Yaling Jiang
- Southwest Medical University, Luzhou, P.R. China
| | - Tiecheng Wang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, P.R. China
| | - Zhiqiang Mei
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Southwest Medical University, Luzhou, P.R. China
| | - Jinbiao Liu
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, P.R. China
| | - Chaoxiang Lv
- The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, P.R. China
- Southwest Medical University, Luzhou, P.R. China
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, P.R. China
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Zhao S, Zhang P, Niu S, Xie J, Liu Y, Liu Y, Zhao N, Cheng C, Lu P. Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data. Funct Integr Genomics 2024; 24:72. [PMID: 38594466 PMCID: PMC11004054 DOI: 10.1007/s10142-024-01356-5] [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: 02/21/2024] [Revised: 03/21/2024] [Accepted: 04/02/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Colorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancer METHODS: For single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments. RESULTS In both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC. CONCLUSION In this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.
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Affiliation(s)
- Songyun Zhao
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China
- Department of Neurosurgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
| | - Pengpeng Zhang
- Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Sen Niu
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China
- Department of General Surgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
| | - Jiaheng Xie
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Yuankun Liu
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China
- Department of Neurosurgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
| | - Yuan Liu
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China
- Department of General Surgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
| | - Ning Zhao
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China
| | - Chao Cheng
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China.
- Department of Neurosurgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
| | - Peihua Lu
- Wuxi Medical Center of Nanjing Medical University, Wuxi, China.
- Department of Clinical Research Center, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
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Xie J, Wu D, Zhang P, Zhao S, Qi M. Deciphering cutaneous melanoma prognosis through LDL metabolism: Single-cell transcriptomics analysis via 101 machine learning algorithms. Exp Dermatol 2024; 33:e15070. [PMID: 38570935 DOI: 10.1111/exd.15070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/14/2024] [Accepted: 03/20/2024] [Indexed: 04/05/2024]
Abstract
Cutaneous melanoma poses a formidable challenge within the field of oncology, marked by its aggressive nature and capacity for metastasis. Despite extensive research uncovering numerous genetic and molecular contributors to cutaneous melanoma development, there remains a critical knowledge gap concerning the role of lipids, notably low-density lipoprotein (LDL), in this lethal skin cancer. This article endeavours to bridge this knowledge gap by delving into the intricate interplay between LDL metabolism and cutaneous melanoma, shedding light on how lipids influence tumour progression, immune responses and potential therapeutic avenues. Genes associated with LDL metabolism were extracted from the GSEA database. We acquired and analysed single-cell sequencing data (GSE215120) and bulk-RNA sequencing data, including the TCGA data set, GSE19234, GSE22153 and GSE65904. Our analysis unveiled the heterogeneity of LDL across various cell types at the single-cell sequencing level. Additionally, we constructed an LDL-related signature (LRS) using machine learning algorithms, incorporating differentially expressed genes and highly correlated genes. The LRS serves as a valuable tool for assessing the prognosis, immunity and mutation status of patients with cutaneous melanoma. Furthermore, we conducted experiments on A375 and WM-115 cells to validate the function of PPP2R1A, a pivotal gene within the LRS. Our comprehensive approach, combining advanced bioinformatics analyses with an extensive review of current literature, presents compelling evidence regarding the significance of LDL within the cutaneous melanoma microenvironment.
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Affiliation(s)
- Jiaheng Xie
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Dan Wu
- Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, China
| | - Pengpeng Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Songyun Zhao
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Min Qi
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
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Zhu S, Cheng Q, Zou M, Li C, Tang Y, Xia L, Jiang Y, Gong Z, Tang Z, Tang Y, Luo H, Peng N, Wang X, Dong X. Combining bulk and scRNA-seq to explore the molecular mechanisms governing the distinct efferocytosis activities of a macrophage subpopulation in PDAC. J Cell Mol Med 2024; 28:e18266. [PMID: 38501838 PMCID: PMC10949604 DOI: 10.1111/jcmm.18266] [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: 01/22/2024] [Revised: 02/25/2024] [Accepted: 03/11/2024] [Indexed: 03/20/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the diagnostic phase leading to a quite dismal prognosis. The onset of metastatic processes has a crucial role in the elevated mortality rates linked to PDAC. Individuals with metastatic advances receive only palliative therapy and have a grim prognosis. It is essential to carefully analyse the intricacies of the metastatic process to enhance the prognosis for individuals with PDAC. Malignancy development is greatly impacted by the process of macrophage efferocytosis. Our current knowledge about the complete range of macrophage efferocytosis activities in PDAC and their intricate interactions with tumour cells is still restricted. This work aims to resolve communication gaps and pinpoint the essential transcription factor that is vital in the immunological response of macrophage populations. We analysed eight PDAC tissue samples sourced from the gene expression omnibus. We utilized several software packages such as Seurat, DoubletFinder, Harmony, Pi, GSVA, CellChat and Monocle from R software together with pySCENIC from Python, to analyse the single-cell RNA sequencing (scRNA-seq) data collected from the PDAC samples. This study involved the analysis of a comprehensive sample of 22,124 cells, which were classified into distinct cell types. These cell types encompassed endothelial and epithelial cells, PDAC cells, as well as various immune cells, including CD4+ T cells, CD8+ T cells, NK cells, B cells, plasma cells, mast cells, monocytes, DC cells and different subtypes of macrophages, namely C0 macrophage TGM2+, C1 macrophage PFN1+, C2 macrophage GAS6+ and C3 macrophage APOC3+. The differentiation between tumour cells and epithelial cells was achieved by the implementation of CopyKat analysis, resulting in the detection and categorization of 1941 PDAC cells. The amplification/deletion patterns observed in PDAC cells on many chromosomes differ significantly from those observed in epithelial cells. The study of Pseudotime Trajectories demonstrated that the C0 macrophage subtype expressing TGM2+ had the lowest level of differentiation. Additionally, the examination of gene set scores related to efferocytosis suggested that this subtype displayed higher activity during the efferocytosis process compared to other subtypes. The most active transcription factors for each macrophage subtype were identified as BACH1, NFE2, TEAD4 and ARID3A. In conclusion, the examination of human PDAC tissue samples using immunofluorescence analysis demonstrated the co-localization of CD68 and CD11b within regions exhibiting the presence of keratin (KRT) and alpha-smooth muscle actin (α-SMA). This observation implies a spatial association between macrophages, fibroblasts, and epithelial cells. There is variation in the expression of efferocytosis-associated genes between C0 macrophage TGM2+ and other macrophage cell types. This observation implies that the diversity of macrophage cells might potentially influence the metastatic advancement of PDAC. Moreover, the central transcription factor of different macrophage subtypes offers a promising opportunity for targeted immunotherapy in the treatment of PDAC.
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Affiliation(s)
- Shaoliang Zhu
- Department of Hepatobiliary, Pancreas and Spleen SurgeryThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Quan Cheng
- Department of General SurgeryThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Mengjie Zou
- Department of NephrologyThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Chunxing Li
- Department of Operating RoomThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Yi Tang
- Department of Hepatobiliary, Pancreas and Spleen SurgeryThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Longjie Xia
- Department of Cosmetology and Plastic Surgery CenterThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Yanming Jiang
- Department of GynecologyThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Zheng Gong
- Department of AnesthesiologyThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Zhenyong Tang
- Department of Hepatobiliary, Pancreas and Spleen SurgeryThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Yuntian Tang
- Department of Hepatobiliary, Pancreas and Spleen SurgeryThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Honglin Luo
- Institute of Oncology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
| | - Ningfu Peng
- Department of Hepatobiliary SurgeryGuangxi Medical University Cancer HospitalNanningChina
| | - Xiaojing Wang
- Department of Rheumatology and Immunology, Tongren Hospital, School of MedicineShanghai Jiao Tong UniversityShanghaiChina
| | - Xiaofeng Dong
- Department of Hepatobiliary, Pancreas and Spleen SurgeryThe People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical SciencesNanningChina
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Huang W, Kim BS, Zhang Y, Lin L, Chai G, Zhao Z. Regulatory T cells subgroups in the tumor microenvironment cannot be overlooked: Their involvement in prognosis and treatment strategy in melanoma. ENVIRONMENTAL TOXICOLOGY 2024. [PMID: 38530049 DOI: 10.1002/tox.24247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 03/03/2024] [Accepted: 03/14/2024] [Indexed: 03/27/2024]
Abstract
BACKGROUND Melanoma, the most lethal form of skin cancer, presents substantial challenges despite effective surgical interventions for in situ lesions. Regulatory T cells (Tregs) wield a pivotal immunomodulatory influence within the tumor microenvironment, yet their impact on melanoma prognosis and direct molecular interactions with melanoma cells remain elusive. This investigation employs single-cell analysis to unveil the intricate nature of Tregs in human melanoma. METHODS Single-cell RNA and bulk sequencing data, alongside clinical information, were obtained from public repositories. Initially, GO and GSEA analyses were employed to delineate functional disparities among distinct cell subsets. Pseudotime and cell-cell interconnection analyses were conducted, followed by an endeavor to construct a prognostic model grounded in Treg-associated risk scores. This model's efficacy was demonstrated via PCA and K-M analyses, with multivariate Cox regression affirming its independent prognostic value in melanoma patients. Furthermore, immune infiltration analysis, immune checkpoint gene expression scrutiny, and drug sensitivity assessments were performed to ascertain the clinical relevance of this prognostic model. RESULTS Following batch effect correction, 80 025 cells partitioned into 31 clusters, encompassing B cells, plasma cells, endothelial cells, fibroblasts, melanoma cells, monocytes, macrophages, and T_NK cells. Within these, 4240 CD4+ T cells were subclassified into seven distinct types. Functional analysis underscored the immunomodulatory function of Tregs within the melanoma tumor microenvironment, elucidating disparities among Treg subpopulations. Notably, the ITGB2 signaling pathway emerged as a plausible molecular nexus linking Tregs to melanoma cells. Our prognostic signature exhibited robust predictive capacities for melanoma prognosis and potential implications in evaluating immunotherapy response. CONCLUSION Tregs exert a critical role in immune suppression within the melanoma tumor microenvironment, revealing a potential molecular-level association with melanoma cells. Our innovative Treg-centered signature introduces a promising prognostic marker for melanoma, holding potential for future clinical prognostic assessments.
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Affiliation(s)
- Wenyi Huang
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Byeong Seop Kim
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yichi Zhang
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Lin
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Stomatology, First Affiliated Hospital of Soochow University, Suzhou, China
- National Center for Translational Medicine(Shanghai) SHU Branch, Shanghai University, Shanghai, China
| | - Gang Chai
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhijie Zhao
- Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Zhou W, Lin Z, Tan W. Deciphering the molecular landscape: integrating single-cell transcriptomics to unravel myofibroblast dynamics and therapeutic targets in clear cell renal cell carcinomas. Front Immunol 2024; 15:1374931. [PMID: 38562930 PMCID: PMC10982338 DOI: 10.3389/fimmu.2024.1374931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/05/2024] [Indexed: 04/04/2024] Open
Abstract
Background Clear cell renal cell carcinomas (ccRCCs) epitomize the most formidable clinical subtype among renal neoplasms. While the impact of tumor-associated fibroblasts on ccRCC progression is duly acknowledged, a paucity of literature exists elucidating the intricate mechanisms and signaling pathways operative at the individual cellular level. Methods Employing single-cell transcriptomic analysis, we meticulously curated UMAP profiles spanning substantial ccRCC populations, delving into the composition and intrinsic signaling pathways of these cohorts. Additionally, Myofibroblasts were fastidiously categorized into discrete subpopulations, with a thorough elucidation of the temporal trajectory relationships between these subpopulations. We further probed the cellular interaction pathways connecting pivotal subpopulations with tumors. Our endeavor also encompassed the identification of prognostic genes associated with these subpopulations through Bulk RNA-seq, subsequently validated through empirical experimentation. Results A notable escalation in the nFeature and nCount of Myofibroblasts and EPCs within ccRCCs was observed, notably enriched in oxidation-related pathways. This phenomenon is postulated to be closely associated with the heightened metabolic activities of Myofibroblasts and EPCs. The Myofibroblasts subpopulation, denoted as C3 HMGA1+ Myofibroblasts, emerges as a pivotal subset, displaying low differentiation and positioning itself at the terminal point of the temporal trajectory. Intriguingly, these cells exhibit a high degree of interaction with tumor cells through the MPZ signaling pathway network, suggesting that Myofibroblasts may facilitate tumor progression via this pathway. Prognostic genes associated with C3 were identified, among which TUBB3 is implicated in potential resistance to tumor recurrence. Finally, experimental validation revealed that the knockout of the key gene within the MPZ pathway, MPZL1, can inhibit tumor activity, proliferation, invasion, and migration capabilities. Conclusion This investigation delves into the intricate mechanisms and interaction pathways between Myofibroblasts and ccRCCs at the single-cell level. We propose that targeting MPZL1 and the oxidative phosphorylation pathway could serve as potential key targets for treating the progression and recurrence of ccRCC. This discovery paves the way for new directions in the treatment and prognosis diagnosis of ccRCC in the future.
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Affiliation(s)
- Wenqian Zhou
- Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhiheng Lin
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Wang Tan
- Xiangya Boai Rehabilitation Hospital, Changsha, Hunan, China
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11
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Liu P, Liu J, Liu J, Yu X. Investigating the mechanisms of drug resistance and prognosis in ovarian cancer using single-cell RNA sequencing and bulk RNA sequencing. Aging (Albany NY) 2024; 16:4736-4758. [PMID: 38461424 DOI: 10.18632/aging.205628] [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: 10/16/2023] [Accepted: 02/02/2024] [Indexed: 03/12/2024]
Abstract
Ovarian cancer stands as a prevalent malignancy within the realm of gynecology, and the emergence of resistance to chemotherapeutic agents remains a pivotal impediment to both prognosis and treatment. Through a single-cell level investigation, we scrutinize the drug resistance and mitotic activity of the core tumor cells in ovarian cancer. Our study revisits the interrelationships and temporal trajectories of distinct epithelial cells (EPCs) subpopulations, while identifying genes associated with ovarian cancer prognosis. Notably, our findings establish a strong association between the drug resistance of EPCs and oxidative phosphorylation pathways. Subsequently, through subpopulation and temporal trajectory analysis, we confirm the intermediate position of EPCs subpopulation C0. Furthermore, we delve into the immunological functions and differentially expressed genes associated with the prognosis of C0, shedding light on the potential for constructing novel ovarian cancer prognosis models and identifying new therapeutic targets.
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Affiliation(s)
- Pengfei Liu
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jinbao Liu
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jinxing Liu
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xiao Yu
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
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Liu P, Xing N, Xiahou Z, Yan J, Lin Z, Zhang J. Unraveling the intricacies of glioblastoma progression and recurrence: insights into the role of NFYB and oxidative phosphorylation at the single-cell level. Front Immunol 2024; 15:1368685. [PMID: 38510250 PMCID: PMC10950940 DOI: 10.3389/fimmu.2024.1368685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 02/19/2024] [Indexed: 03/22/2024] Open
Abstract
Background Glioblastoma (GBM), with its high recurrence and mortality rates, makes it the deadliest neurological malignancy. Oxidative phosphorylation is a highly active cellular pathway in GBM, and NFYB is a tumor-associated transcription factor. Both are related to mitochondrial function, but studies on their relationship with GBM at the single-cell level are still scarce. Methods We re-analyzed the single-cell profiles of GBM from patients with different subtypes by single-cell transcriptomic analysis and further subdivided the large population of Glioma cells into different subpopulations, explored the interrelationships and active pathways among cell stages and clinical subtypes of the populations, and investigated the relationship between the transcription factor NFYB of the key subpopulations and GBM, searching for the prognostic genes of GBM related to NFYB, and verified by experiments. Results Glioma cells and their C5 subpopulation had the highest percentage of G2M staging and rGBM, which we hypothesized might be related to the higher dividing and proliferating ability of both Glioma and C5 subpopulations. Oxidative phosphorylation pathway activity is elevated in both the Glioma and C5 subgroup, and NFYB is a key transcription factor for the C5 subgroup, suggesting its possible involvement in GBM proliferation and recurrence, and its close association with mitochondrial function. We also identified 13 prognostic genes associated with NFYB, of which MEM60 may cause GBM patients to have a poor prognosis by promoting GBM proliferation and drug resistance. Knockdown of the NFYB was found to contribute to the inhibition of proliferation, invasion, and migration of GBM cells. Conclusion These findings help to elucidate the key mechanisms of mitochondrial function in GBM progression and recurrence, and to establish a new prognostic model and therapeutic target based on NFYB.
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Affiliation(s)
- Pulin Liu
- Shandong University of Traditional Chinese Medicine, Jinan, China
- Shanxi Key Laboratory of Chinese Medicine Encephalopathy, Shanxi University of Chinese Medicine, Jinzhong, China
- National International Joint Research Center of Molecular Traditional Chinese Medicine, Shanxi University of Chinese Medicine, Jinzhong, China
| | - Naifei Xing
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Zhikai Xiahou
- China Institute of Sport and Health Science, Beijing Sport University, Beijing, China
| | - Jingwei Yan
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Zhiheng Lin
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Junlong Zhang
- Shandong University of Traditional Chinese Medicine, Jinan, China
- Shanxi Key Laboratory of Chinese Medicine Encephalopathy, Shanxi University of Chinese Medicine, Jinzhong, China
- National International Joint Research Center of Molecular Traditional Chinese Medicine, Shanxi University of Chinese Medicine, Jinzhong, China
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Lin Z, Li X, Shi H, Cao R, Zhu L, Dang C, Sheng Y, Fan W, Yang Z, Wu S. Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses. Front Immunol 2024; 15:1351287. [PMID: 38482016 PMCID: PMC10933018 DOI: 10.3389/fimmu.2024.1351287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/13/2024] [Indexed: 04/13/2024] Open
Abstract
Background Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated. Methods We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes. Results Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines. Conclusion This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.
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Affiliation(s)
- Zhiheng Lin
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Xinhan Li
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Hengmei Shi
- Department of Obstetrics and Gynecology, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China
| | - Renshuang Cao
- Wangjing Hospital of Chinese Academy of Chinese Medical Sciences, Beijing, China
| | - Lijun Zhu
- Longhua Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chunxiao Dang
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yawen Sheng
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Weisen Fan
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | | | - Siyu Wu
- Department of Gynecology and Obstetrics, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Qingdao, China
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Cai HB, Zhao MY, Li XH, Li YQ, Yu TH, Wang CZ, Wang LN, Xu WY, Liang B, Cai YP, Zhang F, Hong WM. Single cell sequencing revealed the mechanism of CRYAB in glioma and its diagnostic and prognostic value. Front Immunol 2024; 14:1336187. [PMID: 38274814 PMCID: PMC10808695 DOI: 10.3389/fimmu.2023.1336187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/26/2023] [Indexed: 01/27/2024] Open
Abstract
Background We explored the characteristics of single-cell differentiation data in glioblastoma and established prognostic markers based on CRYAB to predict the prognosis of glioblastoma patients. Aberrant expression of CRYAB is associated with invasive behavior in various tumors, including glioblastoma. However, the specific role and mechanisms of CRYAB in glioblastoma are still unclear. Methods We assessed RNA-seq and microarray data from TCGA and GEO databases, combined with scRNA-seq data on glioma patients from GEO. Utilizing the Seurat R package, we identified distinct survival-related gene clusters in the scRNA-seq data. Prognostic pivotal genes were discovered through single-factor Cox analysis, and a prognostic model was established using LASSO and stepwise regression algorithms. Moreover, we investigated the predictive potential of these genes in the immune microenvironment and their applicability in immunotherapy. Finally, in vitro experiments confirmed the functional significance of the high-risk gene CRYAB. Results By analyzing the ScRNA-seq data, we identified 28 cell clusters representing seven cell types. After dimensionality reduction and clustering analysis, we obtained four subpopulations within the oligodendrocyte lineage based on their differentiation trajectory. Using CRYAB as a marker gene for the terminal-stage subpopulation, we found that its expression was associated with poor prognosis. In vitro experiments demonstrated that knocking out CRYAB in U87 and LN229 cells reduced cell viability, proliferation, and invasiveness. Conclusion The risk model based on CRYAB holds promise in accurately predicting glioblastoma. A comprehensive study of the specific mechanisms of CRYAB in glioblastoma would contribute to understanding its response to immunotherapy. Targeting the CRYAB gene may be beneficial for glioblastoma patients.
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Affiliation(s)
- Hua-Bao Cai
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Meng-Yu Zhao
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xin-Han Li
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yu-Qing Li
- Department of Pathology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
- Department of Pathology, Anhui Medical University, Hefei, Anhui, China
| | - Tian-Hang Yu
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Cun-Zhi Wang
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Li-Na Wang
- School of Nursing, Anhui Medical University, Hefei, China
| | - Wan-Yan Xu
- School of Nursing, Anhui Medical University, Hefei, China
| | - Bo Liang
- Department of Dermatology and Venereology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yong-Ping Cai
- Department of Pathology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
- Department of Pathology, Anhui Medical University, Hefei, Anhui, China
| | - Fang Zhang
- School of Nursing, Anhui Medical University, Hefei, China
| | - Wen-Ming Hong
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
- Open Project of Key Laboratory of Dermatology, Ministry of Education, Anhui Medical University, Hefei, China
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Wang Q, Zheng C, Hou H, Bao X, Tai H, Huang X, Li Z, Li Z, Wang Q, Pan Q, Wang L, Zhou S, Bian Y, Pan Q, Gong A, Xu M. Interplay of Sphingolipid Metabolism in Predicting Prognosis of GBM Patients: Towards Precision Immunotherapy. J Cancer 2024; 15:275-292. [PMID: 38164288 PMCID: PMC10751665 DOI: 10.7150/jca.89338] [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: 08/21/2023] [Accepted: 10/16/2023] [Indexed: 01/03/2024] Open
Abstract
Background: In spite of numerous existing bio-surveillance systems for predicting glioma (GBM) prognosis, enhancing the efficacy of immunotherapy remains an ongoing conundrum. The continual scrutiny of the dynamic interplay between the sphingolipid metabolic pathway and tumor immunophenotypes has unveiled potential implications. However, the intricate orchestration of functional and regulatory mechanisms by long non-coding RNAs (lncRNAs) in GBM, particularly in the context of sphingolipid metabolism, remains cryptic. Methods: We harnessed established R packages to intersect gene expression profiles of GBM patients within the The Cancer Genome Atlas (TCGA) database with the compilation of sphingolipid metabolism genes from GeneCards. This enabled us to discern markedly distinct lncRNAs, which were subsequently deployed to construct a robust prognostic model utilizing Lasso-Cox regression analysis. We then scrutinized the immune microenvironment across various risk strata using the ssGSEA and CIBERSORT algorithms. To evaluate mutation patterns and drug resistance profiles within patient subgroups, we devised the "Prophytic" and "Maftools" packages, respectively. Results: Our investigation scrutinized lncRNAs linked to sphingolipid metabolism, utilizing glioma specimens from TCGA. We meticulously curated 1224 sphingolipid-associated genes gleaned from GeneCards and pinpointed 272 differentially expressed mRNAs via transcriptomic analysis. Enrichment analyses underscored their significance in sphingolipid processes. A prognostic model founded on 17 meticulously selected lncRNAs was systematically constructed and validated. This model adeptly stratified GBM patients into high- and low-risk categories, yielding highly precise prognostic insights. We also discerned correlations between immune cell infiltration and genetic mutation discrepancies, along with distinct therapeutic responses through drug sensitivity analysis. Notably, computational findings were corroborated through experimental validation by RT-PCR. Conclusion: In summation, our exhaustive inquiry underscores the multifaceted utility of the sphingolipid metabolic pathway as an autonomous diagnostic and prognostic indicator for glioma patients. Furthermore, we amalgamate a profusion of substantiated evidence concerning immune infiltration and gene mutations, thereby reinforcing the proposition that sphingolipid metabolism may function as a pivotal determinant in the panorama of immunotherapeutic interventions.
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Affiliation(s)
- Qi Wang
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
| | - Chuanhua Zheng
- Department of Neurosurgery, the Affiliated Hospital of Youjiang Medical University for Nationalities, Guangxi, China
| | - Hanjin Hou
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Xin Bao
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Huading Tai
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Xufeng Huang
- Faculty of Dentistry, University of Debrecen, Debrecen, Hungary
| | - Zhengrui Li
- Department of Oral and Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology & National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Zhangzuo Li
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Qiaowei Wang
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Qi Pan
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Longbin Wang
- Department of Clinical Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Shujing Zhou
- Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Yanjie Bian
- Xinxiang Medical University, Xinxiang, China
| | - Qier Pan
- Department of Endocrinology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
| | - Aihua Gong
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Min Xu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
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Zhu J, Yuan J, Arya S, Du Z, Liu X, Jia J. Exploring the immune microenvironment of osteosarcoma through T cell exhaustion-associated gene expression: a study on prognosis prediction. Front Immunol 2023; 14:1265098. [PMID: 38169731 PMCID: PMC10758463 DOI: 10.3389/fimmu.2023.1265098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024] Open
Abstract
Background Osteosarcoma is a highly aggressive type of bone cancer with a poor prognosis. In the tumor immune microenvironment, T-cell exhaustion can occur due to various factors, leading to reduced tumor-killing ability. The purpose of this study was to construct a prognostic model based on T-cell exhaustion-associated genes in osteosarcoma. Methods Patient data for osteosarcoma were retrieved from the TARGET and GEO databases. Consensus clustering was employed to identify two novel molecular subgroups. The dissimilarities in the tumor immune microenvironment between these subgroups were evaluated using the "xCell" algorithm. GO and KEGG analyses were conducted to elucidate the underlying mechanisms of gene expression. Predictive risk models were constructed using the least absolute shrinkage and selection operator algorithm and Cox regression analysis. To validate the prognostic significance of the risk gene expression model at the protein level, immunohistochemistry assays were performed on osteosarcoma patient samples. Subsequently, functional analysis of the key risk gene was carried out through in vitro experimentation. Results Four gene expression signatures (PLEKHO2, GBP2, MPP1, and VSIG4) linked to osteosarcoma prognosis were identified within the TARGET-osteosarcoma cohort, categorizing patients into two subgroups. The resulting prognostic model showed strong predictive capability, with area under the receiver operating characteristic curve (AUC) values of 0.728/0.740, 0.781/0.658, and 0.788/0.642 for 1, 3, and 5-year survival in both training and validation datasets. Notably, patients in the low-risk group had significantly higher stromal, immune, and ESTIMATE scores compared to high-risk counterparts. Additionally, a nomogram was developed, exhibiting high accuracy in predicting the survival outcome of osteosarcoma patients. Immunohistochemistry, Kaplan-Meier, and time-dependent AUC analyses consistently supported the prognostic value of the risk model within our osteosarcoma patient cohort. In vitro experiments provided additional validation by demonstrating that the downregulation of GBP2 promoted the proliferation, migration, and invasion of osteosarcoma cells while inhibiting apoptosis. Conclusion The current study established a prognostic signature associated with TEX-related genes and elucidated the impact of the pivotal gene GBP2 on osteosarcoma cells via in vitro experiments. Consequently, it introduces a fresh outlook for clinical prognosis prediction and sets the groundwork for targeted therapy investigations in osteosarcoma.
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Affiliation(s)
- Junchao Zhu
- Department of Orthopedics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Jinghong Yuan
- Department of Orthopedics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Shahrzad Arya
- Division of Surgical Oncology, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Zhi Du
- Department of Orthopedics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Xijuan Liu
- Department of Pediatrics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Jingyu Jia
- Department of Orthopedics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
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Song B, Wang K, Peng Y, Zhu Y, Cui Z, Chen L, Yu Z, Song B. Combined signature of G protein-coupled receptors and tumor microenvironment provides a prognostic and therapeutic biomarker for skin cutaneous melanoma. J Cancer Res Clin Oncol 2023; 149:18135-18160. [PMID: 38006451 DOI: 10.1007/s00432-023-05486-4] [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: 08/24/2023] [Accepted: 10/19/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND G protein-coupled receptors (GPCRs) have been shown to have an important role in tumor development and metastasis, and abnormal expression of GPCRs is significantly associated with poor prognosis of tumor patients. In this study, we analyzed the GPCRs-related gene (GPRGs) and tumor microenvironment (TME) in skin cutaneous melanoma (SKCM) to construct a prognostic model to help SKCM patients obtain accurate clinical treatment strategies. METHODS SKCM expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression analysis, LASSO algorithm, and univariate and multivariate cox regression analysis were used to screen prognosis-related genes (GPR19, GPR146, S1PR2, PTH1R, ADGRE5, CXCR3, GPR143, and OR2I1P) and multiple prognosis-good immune cells; the data set was analyzed according to above results and build up a GPR-TME classifier. The model was further subjected to immune infiltration, functional enrichment, tumor mutational load, immunotherapy prediction, and scRNA-seq data analysis. Finally, cellular experiments were conducted to validate the functionality of the key gene GPR19 in the model. RESULTS The findings indicate that high expression of GPRGs is associated with a poor prognosis in patients with SKCM, highlighting the significant role of GPRGs and the tumor microenvironment (TME) in SKCM development. Notably, the group characterized by low GPR expression and a high TME exhibited the most favorable prognosis and immunotherapeutic efficacy. Furthermore, cellular assays demonstrated that knockdown of GPR19 significantly reduced the proliferation, migration, and invasive capabilities of melanoma cells in A375 and A2058 cell lines. CONCLUSION This study provides novel insights for the prognosis evaluation and treatment of melanoma, along with the identification of a new biomarker, GPR19.
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Affiliation(s)
- Binyu Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Kai Wang
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Yixuan Peng
- School of Basic Medicine, The Fourth Military Medical University, 169 Changle West Road, Xi'an, 710032, China
| | - Yuhan Zhu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Zhiwei Cui
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Lin Chen
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
| | - Zhou Yu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
| | - Baoqiang Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
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Zhu Y, Song B, Yang Z, Peng Y, Cui Z, Chen L, Song B. Integrative lactylation and tumor microenvironment signature as prognostic and therapeutic biomarkers in skin cutaneous melanoma. J Cancer Res Clin Oncol 2023; 149:17897-17919. [PMID: 37955686 DOI: 10.1007/s00432-023-05483-7] [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: 08/14/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND The incidence of skin cutaneous melanoma (SKCM), one of the most aggressive and lethal skin tumors, is increasing worldwide. However, for advanced SKCM, we still lack an accurate and valid way to predict its prognosis, as well as novel theories to guide the planning of treatment options for SKCM patients. Lactylation (LAC), a novel post-translational modification of histones, has been shown to promote tumor growth and inhibit the antitumor response of the tumor microenvironment (TME) in a variety of ways. We hope that this study will provide new ideas for treatment options for SKCM patients, as well as research on the molecular mechanisms of SKCM pathogenesis and development. METHODS At the level of the RNA sequencing set (TCGA, GTEx), we used differential expression analysis, LASSO regression analysis, and multifactor Cox regression analysis to screen for prognosis-related genes and calculate the corresponding LAC scores. The content of TME cells in the tumor tissue was calculated using the CIBERSORT algorithm, and the TME score was calculated based on its results. Finally, the LAC-TME classifier was established and further analyzed based on the two scores, including the construction of a prognostic model, analysis of clinicopathological characteristics, and correlation analysis of tumor mutation burden (TMB) and immunotherapy. Based on single-cell RNA sequencing data, this study analyzed the cellular composition in SKCM tissues and explored the role of LAC scores in intercellular communication. To validate the functionality of the pivotal gene CLPB in the model, cellular experiments were ultimately executed. RESULTS We screened a total of six prognosis-related genes (NDUFA10, NDUFA13, CLPB, RRM2B, HPDL, NARS2) and 7 TME cells with good prognosis. According to Kaplan-Meier survival analysis, we found that the LAClow/TMEhigh group had the highest overall survival (OS) and the LAChigh/TMElow group had the lowest OS (p value < 0.05). In further analysis of immune infiltration, tumor microenvironment (TME), functional enrichment, tumor mutational load and immunotherapy, we found that immunotherapy was more appropriate in the LAClow/TMEhigh group. Moreover, the cellular assays exhibited substantial reductions in proliferation, migration, and invasive potentials of melanoma cells in both A375 and A2058 cell lines upon CLPB knockdown. CONCLUSIONS The prognostic model using the combined LAC score and TME score was able to predict the prognosis of SKCM patients more consistently, and the LAC-TME classifier was able to significantly differentiate the prognosis of SKCM patients across multiple clinicopathological features. The LAC-TME classifier has an important role in the development of immunotherapy regimens for SKCM patients.
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Affiliation(s)
- Yuhan Zhu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Binyu Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Ziyi Yang
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Yixuan Peng
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Zhiwei Cui
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Lin Chen
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China.
| | - Baoqiang Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Chanle West Road, Xi'an, 710032, Shaanxi Province, China.
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Ding Y, Zhao Z, Cai H, Zhou Y, Chen H, Bai Y, Liu Z, Liu S, Zhou W. Single-cell sequencing analysis related to sphingolipid metabolism guides immunotherapy and prognosis of skin cutaneous melanoma. Front Immunol 2023; 14:1304466. [PMID: 38077400 PMCID: PMC10701528 DOI: 10.3389/fimmu.2023.1304466] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
Background We explore sphingolipid-related genes (SRGs) in skin melanoma (SKCM) to develop a prognostic indicator for patient outcomes. Dysregulated lipid metabolism is linked to aggressive behavior in various cancers, including SKCM. However, the exact role and mechanism of sphingolipid metabolism in melanoma remain partially understood. Methods We integrated scRNA-seq data from melanoma patients sourced from the GEO database. Through the utilization of the Seurat R package, we successfully identified distinct gene clusters associated with patient survival in the scRNA-seq data. Key prognostic genes were identified through single-factor Cox analysis and used to develop a prognostic model using LASSO and stepwise regression algorithms. Additionally, we evaluated the predictive potential of these genes within the immune microenvironment and their relevance to immunotherapy. Finally, we validated the functional significance of the high-risk gene IRX3 through in vitro experiments. Results Analysis of scRNA-seq data identified distinct expression patterns of 4 specific genes (SRGs) in diverse cell subpopulations. Re-clustering cells based on increased SRG expression revealed 7 subgroups with significant prognostic implications. Using marker genes, lasso, and Cox regression, we selected 11 genes to construct a risk signature. This signature demonstrated a strong correlation with immune cell infiltration and stromal scores, highlighting its relevance in the tumor microenvironment. Functional studies involving IRX3 knockdown in A375 and WM-115 cells showed significant reductions in cell viability, proliferation, and invasiveness. Conclusion SRG-based risk signature holds promise for precise melanoma prognosis. An in-depth exploration of SRG characteristics offers insights into immunotherapy response. Therapeutic targeting of the IRX3 gene may benefit melanoma patients.
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Affiliation(s)
- Yantao Ding
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Zhijie Zhao
- Department of Plastic Surgery, The Ninth Affiliated Hospital of Shanghai Jiaotong University, Shanghai, China
| | - Huabao Cai
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yi Zhou
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - He Chen
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yun Bai
- Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Zhenran Liu
- Department of Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Shengxiu Liu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Wenming Zhou
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
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Song B, Zhu Y, Zhao Y, Wang K, Peng Y, Chen L, Yu Z, Song B. Machine learning and single-cell transcriptome profiling reveal regulation of fibroblast activation through THBS2/TGFβ1/P-Smad2/3 signalling pathway in hypertrophic scar. Int Wound J 2023; 21:e14481. [PMID: 37986676 PMCID: PMC10898374 DOI: 10.1111/iwj.14481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 10/19/2023] [Accepted: 10/22/2023] [Indexed: 11/22/2023] Open
Abstract
Hypertrophic scar (HS) is a chronic inflammatory skin disorder characterized by excessive deposition of extracellular matrix, and the mechanisms underlying their formation remain poorly understood. We analysed scRNA-seq data from samples of normal skin and HS. Using the hdWGCNA method, key gene modules of fibroblasts in HS were identified. Non-negative matrix factorization was employed to perform subtype analysis of HS patients using these gene modules. Multiple machine learning algorithms were applied to screen and validate accurate gene signatures for identifying and predicting HS, and a convolutional neural network (CNN) based on deep learning was established and validated. Quantitative reverse transcription-polymerase chain reaction and western blotting were performed to measure mRNA and protein expression. Immunofluorescence was used for gene localization analysis, and biological features were assessed through CCK8 and wound healing assay. Single-cell sequencing revealed distinct subpopulations of fibroblasts in HS. HdWGCNA identified key gene characteristics of this population, and pseudotime analysis was conducted to investigate gene variation during fibroblast differentiation. By employing various machine learning algorithms, the gene range was narrowed down to three key genes. A CNN was trained using the expression of these key genes and immune cell infiltration, enabling diagnosis and prediction of HS. Functional experiments demonstrated that THBS2 is associated with fibroblast proliferation and migration in HS and affects the formation and development of HS through the TGFβ1/P-Smad2/3 pathway. Our study identifies unique fibroblast subpopulations closely associated with HS and provides biomarkers for the diagnosis and treatment of HS.
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Affiliation(s)
- Binyu Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yuhan Zhu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Ying Zhao
- Department of Anesthesiology and Perioperative Medicine, Xi'an People's Hospital (Xi'an Fourth Hospital), Northwest University, Xi'an, China
| | - Kai Wang
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yixuan Peng
- School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Lin Chen
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhou Yu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Baoqiang Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Lin S, Zhou S, Han X, Yang Y, Zhou H, Chang X, Zhou Y, Ding Y, Lin H, Hu Q. Single-cell analysis reveals exosome-associated biomarkers for prognostic prediction and immunotherapy in lung adenocarcinoma. Aging (Albany NY) 2023; 15:11508-11531. [PMID: 37878007 PMCID: PMC10637798 DOI: 10.18632/aging.205140] [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: 07/12/2023] [Accepted: 10/03/2023] [Indexed: 10/26/2023]
Abstract
BACKGROUND Exosomes play a crucial role in tumor initiation and progression, yet the precise involvement of exosome-related genes (ERGs) in lung adenocarcinoma (LUAD) remains unclear. METHODS We conducted a comprehensive investigation of ERGs within the tumor microenvironment (TME) of LUAD using single-cell RNA sequencing (scRNA-seq) analysis. Multiple scoring methods were employed to assess exosome activity (EA). Differences in cell communication were examined between high and low EA groups, utilizing the "CellChat" R package. Subsequently, we leveraged multiple bulk RNA-seq datasets to develop and validate exosome-associated signatures (EAS), enabling a multifaceted exploration of prognosis and immunotherapy outcomes between high- and low-risk groups. RESULTS In the LUAD TME, epithelial cells demonstrated the highest EA, with even more elevated levels observed in advanced LUAD epithelial cells. The high-EA group exhibited enhanced intercellular interactions. EAS were established through the analysis of multiple bulk RNA-seq datasets. Patients in the high-risk group exhibited poorer overall survival (OS), reduced immune infiltration, and decreased expression of immune checkpoint genes. Finally, we experimentally validated the high expression of SEC61G in LUAD cell lines and demonstrated that knockdown of SEC61G reduced the proliferative capacity of LUAD cells using colony formation assays. CONCLUSION The integration of single-cell and bulk RNA-seq analyses culminated in the development of the profound and significant EAS, which imparts invaluable insights for the clinical diagnosis and therapeutic management of LUAD patients.
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Affiliation(s)
- Shengrong Lin
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Shengjie Zhou
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Xin Han
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Yang Yang
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Hao Zhou
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Xuejiao Chang
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Yefeng Zhou
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Yuqin Ding
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
| | - Huihui Lin
- Department of Hematology, Dongtai People’s Hospital, Dongtai 224299, China
| | - Qing Hu
- Department of Thoracic Surgery, Dongtai People’s Hospital, Dongtai 224299, China
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Zhang P, Zhang H, Tang J, Ren Q, Zhang J, Chi H, Xiong J, Gong X, Wang W, Lin H, Li J, Huang C. The integrated single-cell analysis developed an immunogenic cell death signature to predict lung adenocarcinoma prognosis and immunotherapy. Aging (Albany NY) 2023; 15:10305-10329. [PMID: 37796202 PMCID: PMC10599752 DOI: 10.18632/aging.205077] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/06/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND Research on immunogenic cell death (ICD) in lung adenocarcinoma (LUAD) has been relatively limited. This study aims to create ICD-related signatures for accurate survival prognosis prediction in LUAD patients, addressing the challenge of lacking reliable early prognostic indicators for this type of cancer. METHODS Using single-cell RNA sequencing (scRNA-seq) analysis, ICD activity in cells was calculated by AUCell algorithm, divided into high- and low-ICD groups according to median values, and key ICD regulatory genes were identified through differential analysis, and these genes were integrated into TCGA data to construct prognostic signatures using LASSO and COX regression analysis, and multi-dimensional analysis of ICD-related signatures in terms of prognosis, immunotherapy, tumor microenvironment (TME), and mutational landscape. RESULTS The constructed signature reveals a pronounced disparity in prognosis between the high- and low-risk groups of LUAD patients. The statistical discrepancies in survival times among LUAD patients from both the TCGA and GEO databases further corroborate this observation. Additionally, heightened levels of immune cell infiltration expression are evidenced in the low-risk group, suggesting a potential benefit from immunotherapeutic interventions for these patients. The expression levels of pivotal risk-associated genes in tissue samples were assessed utilizing qRT-PCR, thereby unveiling PITX3 as a plausible therapeutic target in the context of LUAD. CONCLUSIONS Our constructed ICD-related signatures provide help in predicting the prognosis and immunotherapy of LUAD patients, and to some extent guide the clinical treatment of LUAD patients.
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Affiliation(s)
- Pengpeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Haotian Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Junjie Tang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jingwen Xiong
- Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
| | - Xiangjin Gong
- Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
| | - Wei Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Haoran Lin
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jun Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chenjun Huang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Zhang X, Zhang P, Cong A, Feng Y, Chi H, Xia Z, Tang H. Unraveling molecular networks in thymic epithelial tumors: deciphering the unique signatures. Front Immunol 2023; 14:1264325. [PMID: 37849766 PMCID: PMC10577431 DOI: 10.3389/fimmu.2023.1264325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/14/2023] [Indexed: 10/19/2023] Open
Abstract
Thymic epithelial tumors (TETs) are a rare and diverse group of neoplasms characterized by distinct molecular signatures. This review delves into the complex molecular networks of TETs, highlighting key aspects such as chromosomal abnormalities, molecular subtypes, aberrant gene mutations and expressions, structural gene rearrangements, and epigenetic changes. Additionally, the influence of the dynamic tumor microenvironment on TET behavior and therapeutic responses is examined. A thorough understanding of these facets elucidates TET pathogenesis, offering avenues for enhancing diagnostic accuracy, refining prognostic assessments, and tailoring targeted therapeutic strategies. Our review underscores the importance of deciphering TETs' unique molecular signatures to advance personalized treatment paradigms and improve patient outcomes. We also discuss future research directions and anticipated challenges in this intriguing field.
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Affiliation(s)
- Xiao Zhang
- State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengpeng Zhang
- Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ansheng Cong
- Division of Nephrology, Nanfang Hospital, Southern Medical University, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, China
| | - Yanlong Feng
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hao Chi
- School of Clinical Medical Sciences, Southwest Medical University, Luzhou, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians University Munich, Munich, Germany
| | - Hailin Tang
- State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
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Zhang S, Jiang C, Jiang L, Chen H, Huang J, Zhang J, Wang R, Chi H, Yang G, Tian G. Uncovering the immune microenvironment and molecular subtypes of hepatitis B-related liver cirrhosis and developing stable a diagnostic differential model by machine learning and artificial neural networks. Front Mol Biosci 2023; 10:1275897. [PMID: 37808522 PMCID: PMC10556489 DOI: 10.3389/fmolb.2023.1275897] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 09/14/2023] [Indexed: 10/10/2023] Open
Abstract
Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of cirrhosis can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient's quality of life decreases dramatically and drug therapy is ineffective. Liver transplantation is the most effective treatment, but the lack of donor required for transplantation, the high cost of the procedure and post-transplant rejection make this method unsuitable for most patients. Methods: The aim of this study was to find potential diagnostic biomarkers associated with HBV-LC by bioinformatics analysis and to classify HBV-LC into specific subtypes by consensus clustering. This will provide a new perspective for early diagnosis, clinical treatment and prevention of HCC in HBV-LC patients. Two study-relevant datasets, GSE114783 and GSE84044, were retrieved from the GEO database. We screened HBV-LC for feature genes using differential analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) for a total of five methods. After that, we constructed an artificial neural network (ANN) model. A cohort consisting of GSE123932, GSE121248 and GSE119322 was used for external validation. To better predict the risk of HBV-LC development, we also built a nomogram model. And multiple enrichment analyses of genes and samples were performed to understand the biological processes in which they were significantly enriched. And the different subtypes of HBV-LC were analyzed using the Immune infiltration approach. Results: Using the data downloaded from GEO, we developed an ANN model and nomogram based on six feature genes. And consensus clustering of HBV-LC classified them into two subtypes, C1 and C2, and it was hypothesized that patients with subtype C2 might have milder clinical symptoms by immune infiltration analysis. Conclusion: The ANN model and column line graphs constructed with six feature genes showed excellent predictive power, providing a new perspective for early diagnosis and possible treatment of HBV-LC. The delineation of HBV-LC subtypes will facilitate the development of future clinical treatment of HBV-LC.
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Affiliation(s)
- Shengke Zhang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Chenglu Jiang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Lai Jiang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Haiqing Chen
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jinbang Huang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Rui Wang
- Department of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Hao Chi
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, United States
| | - Gang Tian
- Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Molecular Diagnosis of Clinical Diseases Key Laboratory of Luzhou, Luzhou, China
- Sichuan Province Engineering Technology Research Center of Molecular Diagnosis of Clinical Diseases, Luzhou, China
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Zhao S, Wang Q, Ni K, Zhang P, Liu Y, Xie J, Ji W, Cheng C, Zhou Q. Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients. Front Immunol 2023; 14:1263329. [PMID: 37727789 PMCID: PMC10505933 DOI: 10.3389/fimmu.2023.1263329] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 08/17/2023] [Indexed: 09/21/2023] Open
Abstract
Background Glioblastoma (GBM) is a malignant primary brain tumor. This study focused on exploring the exosome-related features of glioblastoma to better understand its cellular composition and molecular characteristics. Methods Single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) were used to analyze the heterogeneity of glioblastomas. After data integration, cell clustering, and annotation, five algorithms were used to calculate scores for exosome-related genes(ERGs). Cell trajectory analysis and intercellular communication analysis were performed to explore exosome-related communication patterns. Spatial transcriptome sequencing data were analyzed to validate the findings. To further utilize exosome-related features to aid in clinical decision-making, a prognostic model was constructed using GBM's bulk RNA-seq. Results Different cell subpopulations were observed in GBM, with Monocytes/macrophages and malignant cells in tumor samples showing higher exosome-related scores. After identifying differentially expressed ERGs in malignant cells, pseudotime analysis revealed the cellular status of malignant cells during development. Intercellular communication analysis highlighted signaling pathways and ligand-receptor interactions. Spatial transcriptome sequencing confirmed the high expression of exosome-related gene features in the tumor core region. A prognostic model based on six ERGs was shown to be predictive of overall survival and immunotherapy outcome in GBM patients. Finally, based on the results of scRNA-seq and prognostic modeling as well as a series of cell function experiments, BARD1 was identified as a novel target for the treatment of GBM. Conclusion This study provides a comprehensive understanding of the exosome-related features of GBM in both scRNA-seq and stRNA-seq, with malignant cells with higher exosome-related scores exhibiting stronger communication with Monocytes/macrophages. In terms of spatial data, highly scored malignant cells were also concentrated in the tumor core region. In bulk RNA-seq, patients with a high exosome-related index exhibited an immunosuppressive microenvironment, which was accompanied by a worse prognosis as well as immunotherapy outcomes. Prognostic models constructed using ERGs are expected to be independent prognostic indicators for GBM patients, with potential implications for personalized treatment strategies for GBM. Knockdown of BARD1 in GBM cell lines reduces the invasive and value-added capacity of tumor cells, and thus BARD1-positively expressing malignant cells are a risk factor for GBM patients.
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Affiliation(s)
- Songyun Zhao
- Department of Neurosurgery, Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Qi Wang
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Kaixiang Ni
- Department of Neurosurgery, Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Pengpeng Zhang
- Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yuan Liu
- Department of General Surgery, Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Jiaheng Xie
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Wei Ji
- Department of Neurosurgery, Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Chao Cheng
- Department of Neurosurgery, Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Qiang Zhou
- Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, China
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