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Chen JY, Li JD, He RQ, Huang ZG, Chen G, Zou W. Bibliometric analysis of phosphoglycerate kinase 1 expression in breast cancer and its distinct upregulation in triple-negative breast cancer. World J Clin Oncol 2024; 15:867-894. [PMID: 39071464 PMCID: PMC11271732 DOI: 10.5306/wjco.v15.i7.867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/27/2024] [Accepted: 06/24/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Phosphoglycerate kinase 1 (PGK1) has been identified as a possible biomarker for breast cancer (BC) and may play a role in the development and advancement of triple-negative BC (TNBC). AIM To explore the PGK1 and BC research status and PGK1 expression and mechanism differences among TNBC, non-TNBC, and normal breast tissue. METHODS PGK1 and BC related literature was downloaded from Web of Science Core Collection Core Collection. Publication counts, key-word frequency, cooperation networks, and theme trends were analyzed. Normal breast, TNBC, and non-TNBC mRNA data were gathered, and differentially expressed genes obtained. Area under the summary receiver operating characteristic curves, sensitivity and specificity of PGK1 expression were determined. Kaplan Meier revealed PGK1's prognostic implication. PGK1 co-expressed genes were explored, and Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Disease Ontology applied. Protein-protein interaction networks were constructed. Hub genes identified. RESULTS PGK1 and BC related publications have surged since 2020, with China leading the way. The most frequent keyword was "Expression". Collaborative networks were found among co-citations, countries, institutions, and authors. PGK1 expression and BC progression were research hotspots, and PGK1 expression and BC survival were research frontiers. In 16 TNBC vs non-cancerous breast and 15 TNBC vs non-TNBC datasets, PGK1 mRNA levels were higher in 1159 TNBC than 1205 non-cancerous breast cases [standardized mean differences (SMD): 0.85, 95% confidence interval (95%CI): 0.54-1.16, I² = 86%, P < 0.001]. PGK1 expression was higher in 1520 TNBC than 7072 non-TNBC cases (SMD: 0.25, 95%CI: 0.03-0.47, I² = 91%, P = 0.02). Recurrence free survival was lower in PGK1-high-expression than PGK1-low-expression group (hazard ratio: 1.282, P = 0.023). PGK1 co-expressed genes were concentrated in ATP metabolic process, HIF-1 signaling, and glycolysis/gluconeogenesis pathways. CONCLUSION PGK1 expression is a research hotspot and frontier direction in the BC field. PGK1 may play a strong role in promoting cancer in TNBC by mediating metabolism and HIF-1 signaling pathways.
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Affiliation(s)
- Jing-Yu Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jian-Di Li
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Rong-Quan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Zhi-Guang Huang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Wen Zou
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
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Zhan Y, Ma S, Zhang T, Zhang L, Zhao P, Yang X, Liu M, Cheng W, Li Y, Wang J. Identification of a novel monocyte/macrophage-related gene signature for predicting survival and immune response in acute myeloid leukemia. Sci Rep 2024; 14:14012. [PMID: 38890346 PMCID: PMC11189543 DOI: 10.1038/s41598-024-64567-7] [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: 12/30/2023] [Accepted: 06/11/2024] [Indexed: 06/20/2024] Open
Abstract
Acute myeloid leukemia (AML) is a heterogeneous hematological tumor with poor immunotherapy effect. This study was to develop a monocyte/macrophage-related prognostic risk score (MMrisk) and identify new therapeutic biomarkers for AML. We utilized differentially expressed genes (DEGs) in combination with single-cell RNA sequencing to identify monocyte/macrophage-related genes (MMGs). Eight genes were selected for the construction of a MMrisk model using univariate Cox regression analysis and LASSO regression analysis. We then validated the MMrisk on two GEO datasets. Lastly, we investigated the immunologic characteristics and advantages of immunotherapy and potential targeted drugs for MMrisk groups. Our study identified that the MMrisk is composed of eight MMGs, including HOPX, CSTB, MAP3K1, LGALS1, CFD, MXD1, CASP1 and BCL2A1. The low MMrisk group survived longer than high MMrisk group (P < 0.001). The high MMrisk group was positively correlated with B cells, plasma cells, CD4 memory cells, Mast cells, CAFs, monocytes, M2 macrophages, Endothelial, tumor mutation, and most immune checkpoints (PD1, Tim-3, CTLA4, LAG3). Furthermore, drug sensitivity analysis showed that AZD.2281, Axitinib, AUY922, ABT.888, and ATRA were effective in high-risk MM patients. Our research shows that MMrisk is a potential biomarker which is helpful to identify the molecular characteristics of AML immunology.
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Affiliation(s)
- Yun Zhan
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Department of Clinical Medical School, Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Sixing Ma
- Department of Clinical Medical School, Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Department of Vascular Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Tianzhuo Zhang
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Luxin Zhang
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Peng Zhao
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Xueying Yang
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Min Liu
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Weiwei Cheng
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Ya Li
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China
| | - Jishi Wang
- Department of Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China.
- Department of Clinical Medical School, Guizhou Medical University, Guiyang, 550004, People's Republic of China.
- Guizhou Province Institute of Hematology, Guizhou Province Hematopoietic Stem Cell Transplantation Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, People's Republic of China.
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Xin H, Chen Y, Niu H, Li X, Gai X, Cui G. Integrated Analysis Construct a Tumor-Associated Macrophage Novel Signature with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Gastric Cancer Patients. Dig Dis Sci 2024; 69:2055-2073. [PMID: 38573378 DOI: 10.1007/s10620-024-08365-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 02/09/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Gastric cancer (GC) remains one of the most prevalent malignant tumors worldwide. At present, tumor-associated macrophages (TAMs) are essential in the progression, metastasis, and drug resistance of tumors. Therefore, TAMs can be a crucial target for tumor treatment. AIMS We intended to investigate the TAM characteristics in GC and develop a risk signature based on TAM to predict the prognosis of GC patients. METHODS The single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were acquired from a publicly available database. We utilized the Seurat pipeline to process the scRNA-seq data and determine TAM cell types using marker genes. Univariate Cox regression analysis was utilized to examine TAM-related prognostic genes, and then we employed Lasso-Cox regression analysis, and Multivariate Cox regression analysis established a novel risk profile to forecast the clinical value of the model with a new nomogram combining risk profiles and clinicopathological characteristics. RESULTS The current study employed scRNA-seq data to identify five TAM clusters in GC, among which four were significantly associated with GC prognosis. Accordingly, we further developed a TAM-related risk signature utilizing nine genes. After evaluation, our model accurately predicted the prognosis of gastric cancer. Generally, GC patients with low TAMS scores exhibited a more favorable prognosis, greater benefits from immunotherapy, and higher levels of immune cell infiltration. CONCLUSIONS The prognosis of GC can be effectively predicted by TAM-based risk signatures, and the signature may provide a new perspective for comprehensively guiding clinical diagnosis, prediction, and immunotherapy for gastric cancer.
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Affiliation(s)
- Hua Xin
- Laboratory Medicine, The First Affiliated Hospital of Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China
| | - Yu Chen
- Clinical Medicine Department, Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China
| | - Honglin Niu
- Clinical Medicine Department, Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China
| | - Xuebin Li
- Clinical Medicine Department, Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China
| | - Xuejie Gai
- Clinical Medicine Department, Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China
| | - Guoli Cui
- Laboratory Medicine, The First Affiliated Hospital of Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China.
- Clinical Medicine Department, Jiamusi University, Jiamusi, 154000, Heilongjiang Province, China.
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Mao F, Wan N. Creating a multifaceted prognostic model for cutaneous melanoma: the convergence of single-cell and bulk sequencing with machine learning. Front Cell Dev Biol 2024; 12:1401945. [PMID: 38770150 PMCID: PMC11102988 DOI: 10.3389/fcell.2024.1401945] [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: 03/16/2024] [Accepted: 04/15/2024] [Indexed: 05/22/2024] Open
Abstract
Background Cutaneous melanoma is a highly heterogeneous cancer, and understanding the role of inflammation-related genes in its progression is crucial. Methods The cohorts used include the TCGA cohort from TCGA database, and GSE115978, GSE19234, GSE22153 cohort, and GSE65904 cohort from GEO database. Weighted Gene Coexpression Network Analysis (WGCNA) identified key inflammatory modules. Machine learning techniques were employed to construct prognostic models, which were validated across multiple cohorts, including the TCGA cohort, GSE19234, GSE22153, and GSE65904. Immune cell infiltration, tumor mutation load, and immunotherapy response were assessed. The hub gene STAT1 was validated through cellular experiments. Results Single-cell analysis revealed heterogeneity in inflammation-related genes, with NK cells, T cells, and macrophages showing elevated inflammation-related scores. WGCNA identified a module highly associated with inflammation. Machine learning yielded a CoxBoost + GBM prognostic model. The model effectively stratified patients into high-risk and low-risk groups in multiple cohorts. A nomogram and Receiver Operating Characteristic (ROC) curves confirmed the model's accuracy. Low-risk patients exhibited increased immune cell infiltration, higher Tumor Mutational Burden (TMB), and potentially better immunotherapy response. Cellular experiments validated the functional role of STAT1 in melanoma progression. Conclusion Inflammation-related genes play a critical role in cutaneous melanoma progression. The developed prognostic model, nomogram, and validation experiments highlight the potential clinical relevance of these genes and provide a basis for further investigation into personalized treatment strategies for melanoma patients.
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Affiliation(s)
- Fei Mao
- Department of Urology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huai’an, China
| | - Neng Wan
- Department of Plastic Surgery, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huai’an, China
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Zhu X, Wang F, Wang M, Lv L, Fang L, Song J, Wang X, Ding F. Development of a breast cancer prognostic model based on vesicle-mediated transport-related genes to predict immune landscape and clinical drug therapy. Hum Mol Genet 2024; 33:553-562. [PMID: 38129105 DOI: 10.1093/hmg/ddad204] [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] [Revised: 11/14/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Vesicle-mediated transport, vital for substance exchange and intercellular communication, is linked to tumor initiation and progression. This work was designed to study the role of vesicle-mediated transport-related genes (VMTRGs) in breast cancer (BC)prognosis. METHODS Univariate Cox analysis was utilized to screen prognosis-related VMTRGs. BC samples underwent unsupervised clustering based on VMTRGs to analyze survival, clinical factors, and immune cell abundance across different subtypes. We constructed a risk model using univariate Cox and LASSO regression analysis, with validation conducted using GEO datasets. Subsequently, we performed tumor mutational burden analysis, and immune landscape analysis on both groups. Ultimately, we conducted immunophenoscore (IPS) scoring to forecast immunotherapy and performed drug sensitivity analysis. RESULTS We identified 102 VMTRGs associated with BC prognosis. Using these 102 VMTRGs, BC patients were classified into 3 subtypes, with Cluster3 patients showing significantly better survival rates. We constructed a prognostic model for BC based on 12 VMTRGs that effectively predicted patient survival. Riskscore was an independent prognostic factor for BC patients. According to median risk score, high-risk group (HRG) had higher TMB values. The immune landscape of the HRG exhibited characteristics of cold tumor, with higher immune checkpoint expression levels and lower IPS scores, whereas Gemcitabine, Nilotinib, and Oxaliplatin were more suitable for treating low-risk group. CONCLUSION We classified BC subtypes and built a prognostic model based on VMTRGs. The genes in the prognostic model may serve as potential targets for BC therapy.
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Affiliation(s)
- Xiaotao Zhu
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Fan Wang
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Mingzhen Wang
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Lin Lv
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Linghui Fang
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Jialu Song
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Xiaohui Wang
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
| | - Fengsheng Ding
- Department of Breast and Thyroid Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 365 Renmin East Rd, Jinhua, Zhejiang 321000, China
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Ma H, Xiong L, Zhao B, Hahan Z, Wei M, Shi H, Yang S, Ren Q. Comprehensive investigation into the influence of glycosylation on head and neck squamous cell carcinoma and development of a prognostic model for risk assessment and anticipating immunotherapy. Front Immunol 2024; 15:1364082. [PMID: 38562924 PMCID: PMC10982401 DOI: 10.3389/fimmu.2024.1364082] [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: 01/01/2024] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Background It has been well established that glycosylation plays a pivotal role in initiation, progression, and therapy resistance of several cancers. However, the correlations between glycosylation and head and neck squamous cell carcinoma (HNSCC) have not been elucidated in detail. Methods The paramount genes governing glycosylation were discerned via the utilization of the Protein-Protein Interaction (PPI) network and correlation analysis, coupled with single-cell RNA sequencing (scRNA-seq) analysis. To construct risk models exhibiting heightened predictive efficacy, cox- and lasso-regression methodologies were employed, and the veracity of these models was substantiated across both internal and external datasets. Subsequently, an exploration into the distinctions within the tumor microenvironment (TME), immunotherapy responses, and enriched pathways among disparate risk cohorts ensued. Ultimately, cell experiments were conducted to validate the consequential impact of SMS in Head and Neck Squamous Cell Carcinoma (HNSCC). Results A total of 184 genes orchestrating glycosylation were delineated for subsequent scrutiny. Employing cox- and lasso-regression methodologies, we fashioned a 3-gene signature, proficient in prognosticating the outcomes for patients afflicted with HNSCC. Noteworthy observations encompassed distinctions in the Tumor Microenvironment (TME), levels of immune cell infiltration, and the presence of immune checkpoint markers among divergent risk cohorts, holding potentially consequential implications for the clinical management of HNSCC patients. Conclusion The prognosis of HNSCC can be proficiently anticipated through risk signatures based on Glycosylation-related genes (GRGs). A thorough delineation of the GRGs signature in HNSCC holds the potential to facilitate the interpretation of HNSCC's responsiveness to immunotherapy and provide innovative strategies for cancer treatment.
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Affiliation(s)
- Heng Ma
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Ludan Xiong
- Department of GCP Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Bohui Zhao
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Zhuledesi Hahan
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Minghui Wei
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Hengmei Shi
- Department of Obstetrics and Gynecology, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Susu Yang
- Department of Breast 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
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Zhao X, Zhang X, Li F, Lu C. Exploration of the prognostic prediction value of the PANoptosis-based risk score and its correlation with tumor immunity in lung adenocarcinoma. J Gene Med 2024; 26:e3682. [PMID: 38508210 DOI: 10.1002/jgm.3682] [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: 09/08/2023] [Revised: 02/19/2024] [Accepted: 02/24/2024] [Indexed: 03/22/2024] Open
Abstract
Lung adenocarcinoma (LUAD) is a common cancer with high mortality worldwide. PANoptosis is a novel inflammatory programmed cell death modality with the characteristics of pyroptosis, apoptosis and necroptosis. It is necessary to explore PANoptosis-related genes in LUAD patients and offer evidence for prognosis prediction and therapeutic strategies. Single-cell RNA sequencing data and RNA expression profiles of LUAD patients from The Cancer Genome Atlas and Gene Expression Omnibus databases are used to screen PANoptosis-related differential genes for the construction of a risk model. Fifteen PANoptosis-related markers with prognostic value were identified by Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression analysis. Kaplan-Meier analysis and receiver operating characteristic curve analysis further demonstrated the significant predictive capability. Immune infiltration, Single Nucleotide Variants (SNV) mutations, and clinical drug susceptibility were analyzed. In conclusion, a risk model of 15 PANoptosis-related genes has significant value in prognostic prediction for LUAD and has potential to direct clinical therapeutic strategies during the treatment.
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Affiliation(s)
- Xiaojian Zhao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Xuefeng Zhang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Feng Li
- Department of Thoracic and Cardiac Surgery, Neijiang Traditional Chinese Medicine Hospital, Sichuan Province, People's Republic of China
| | - Caiping Lu
- Department of Endocrinology, Shijiazhuang people's Hospital, Shijiazhuang, Hebei Province, People's Republic of 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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Yuan Q, Lu X, Guo H, Sun J, Yang M, Liu Q, Tong M. Low-density lipoprotein receptor promotes crosstalk between cell stemness and tumor immune microenvironment in breast cancer: a large data-based multi-omics study. J Transl Med 2023; 21:871. [PMID: 38037058 PMCID: PMC10691045 DOI: 10.1186/s12967-023-04699-y] [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: 07/15/2023] [Accepted: 11/03/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Tumor cells with stemness in breast cancer might facilitate the immune microenvironment's suppression process and led to anti-tumor immune effects. The primary objective of this study was to identify potential targets to disrupt the communication between cancer cell stemness and the immune microenvironment. METHODS In this study, we initially isolated tumor cells with varying degrees of stemness using a spheroid formation assay. Subsequently, we employed RNA-seq and proteomic analyses to identify genes associated with stemness through gene trend analysis. These stemness-related genes were then subjected to pan-cancer analysis to elucidate their functional roles in a broader spectrum of cancer types. RNA-seq data of 3132 patients with breast cancer with clinical data were obtained from public databases. Using the identified stemness genes, we constructed two distinct stemness subtypes, denoted as C1 and C2. We subsequently conducted a comprehensive analysis of the differences between these subtypes using pathway enrichment methodology and immune infiltration algorithms. Furthermore, we identified key immune-related stemness genes by employing lasso regression analysis and a Cox survival regression model. We conducted in vitro experiments to ascertain the regulatory impact of the key gene on cell stemness. Additionally, we utilized immune infiltration analysis and pan-cancer analysis to delineate the functions attributed to this key gene. Lastly, single-cell RNA sequencing (scRNA-seq) was employed to conduct a more comprehensive examination of the key gene's role within the microenvironment. RESULTS In our study, we initially identified a set of 65 stemness-related genes in breast cancer cells displaying varying stemness capabilities. Subsequently, through survival analysis, we pinpointed 41 of these stemness genes that held prognostic significance. We observed that the C2 subtype exhibited a higher stemness capacity compared to the C1 subtype and displayed a more aggressive malignancy profile. Further analysis using Lasso-Cox algorithm identified LDLR as a pivotal immune-related stemness gene. It became evident that LDLR played a crucial role in shaping the immune microenvironment. In vitro experiments demonstrated that LDLR regulated the cell stemness of breast cancer. Immune infiltration analysis and pan-cancer analysis determined that LDLR inhibited the proliferation of immune cells and might promote tumor cell progression. Lastly, in our scRNA-seq analysis, we discovered that LDLR exhibited associations with stemness marker genes within breast cancer tissues. Moreover, LDLR demonstrated higher expression levels in tumor cells compared to immune cells, further emphasizing its relevance in the context of breast cancer. CONCLUSION LDLR is an important immune stemness gene that regulates cell stemness and enhances the crosstalk between breast cancer cancer cell stemness and tumor immune microenvironment.
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Affiliation(s)
- Qihang Yuan
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiaona Lu
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China
| | - Hui Guo
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jiaao Sun
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Mengying Yang
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China
| | - Quentin Liu
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China.
- State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen University, Guangzhou, China.
| | - Mengying Tong
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China.
- Department of Ultrasound, First Affiliated Hospital of Dalian Medical University, Dalian, China.
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10
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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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11
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Shi T, Li M, Yu Y. Machine learning-enhanced insights into sphingolipid-based prognostication: revealing the immunological landscape and predictive proficiency for immunomotherapy and chemotherapy responses in pancreatic carcinoma. Front Mol Biosci 2023; 10:1284623. [PMID: 38028544 PMCID: PMC10643633 DOI: 10.3389/fmolb.2023.1284623] [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: 08/28/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023] Open
Abstract
Background: With a poor prognosis for affected individuals, pancreatic adenocarcinoma (PAAD) is known as a complicated and diverse illness. Immunocytes have become essential elements in the development of PAAD. Notably, sphingolipid metabolism has a dual function in the development of tumors and the invasion of the immune system. Despite these implications, research on the predictive ability of sphingolipid variables for PAAD prognosis is strikingly lacking, and it is yet unclear how they can affect PAAD immunotherapy and targeted pharmacotherapy. Methods: The investigation process included SPG detection while also being pertinent to the prognosis for PAAD. Both the analytical capability of CIBERSORT and the prognostic capability of the pRRophetic R package were used to evaluate the immunological environments of the various HCC subtypes. In addition, CCK-8 experiments on PAAD cell lines were carried out to confirm the accuracy of drug sensitivity estimates. The results of these trials, which also evaluated cell survival and migratory patterns, confirmed the usefulness of sphingolipid-associated genes (SPGs). Results: As a result of this thorough investigation, 32 SPGs were identified, each of which had a measurable influence on the dynamics of overall survival. This collection of genes served as the conceptual framework for the development of a prognostic model, which was carefully assembled from 10 chosen genes. It should be noted that this grouping of patients into cohorts with high and low risk was a sign of different immune profiles and therapy responses. The increased abundance of SPGs was identified as a possible sign of inadequate responses to immune-based treatment approaches. The careful CCK-8 testing carried out on PAAD cell lines was of the highest importance for providing clear confirmation of drug sensitivity estimates. Conclusion: The significance of Sphingolipid metabolism in the complex web of PAAD development is brought home by this study. The novel risk model, built on the complexity of sphingolipid-associated genes, advances our understanding of PAAD and offers doctors a powerful tool for developing personalised treatment plans that are specifically suited to the unique characteristics of each patient.
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Affiliation(s)
| | | | - Yabin Yu
- Department of Hepatobiliary Surgery, The Affiliated Huaian No 1 People’s Hospital of Nanjing Medical University, Huaian, China
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12
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Chen X, Yuan Q, Guan H, Shi X, Sun J, Wu Z, Ren J, Xia S, Shang D. Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer. Front Oncol 2023; 13:1227606. [PMID: 37941546 PMCID: PMC10628740 DOI: 10.3389/fonc.2023.1227606] [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: 05/23/2023] [Accepted: 10/03/2023] [Indexed: 11/10/2023] Open
Abstract
Background Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development. Methodology Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model. Results We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues. Conclusion This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.
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Affiliation(s)
- Xu Chen
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Qihang Yuan
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hewen Guan
- Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xueying Shi
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Jiaao Sun
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Zhiqiang Wu
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Jie Ren
- Department of Oncology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Shilin Xia
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Dong Shang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
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13
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Chi H, Huang J, Yan Y, Jiang C, Zhang S, Chen H, Jiang L, Zhang J, Zhang Q, Yang G, Tian G. Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms. Front Mol Biosci 2023; 10:1254232. [PMID: 37916187 PMCID: PMC10617599 DOI: 10.3389/fmolb.2023.1254232] [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: 07/06/2023] [Accepted: 10/03/2023] [Indexed: 11/03/2023] Open
Abstract
Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.
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Affiliation(s)
- Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jinbang Huang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Yang Yan
- The Third Affiliated Hospital of Guizhou Medical University, Duyun, China
| | - Chenglu Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Shengke Zhang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Haiqing Chen
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Lai Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Qinghong Zhang
- Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Gang Tian
- Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
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Moro K, Ichikawa H, Koyama Y, Abe S, Uchida H, Naruse K, Obata Y, Tsuchida J, Toshikawa C, Ikarashi M, Muneoka Y, Miura K, Tajima Y, Shimada Y, Kobayashi T, Sakata J, Takabe K, Wakai T. Oral Administration of Glucosylceramide Suppresses Tumor Growth by Affecting the Ceramide/Sphingosine-1-Phosphate Balance in Breast Cancer Tissue. World J Oncol 2023; 14:430-437. [PMID: 37869237 PMCID: PMC10588502 DOI: 10.14740/wjon1656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/24/2023] [Indexed: 10/24/2023] Open
Abstract
Background Ceramide and sphingosine-1-phosphate (S1P) play opposing roles in cell death and survival, and maintain a dynamic balance called the sphingolipid rheostat. Glucosylceramide is a substrate to generate ceramide but its effect on breast cancer by oral administration was never tested. The purpose of this study was to reveal the anticancer activity of glucosylceramide and its potential as a new therapeutic agent in breast cancer. Methods E0771 cells were inoculated into the breast tissue of female C57BL/6NJcl mice. Glucosylceramide was administered orally to the mice for nine consecutive days. The concentrations of sphingolipid mediators including ceramide, glucosylceramide, and S1P in tumor tissues and serum were determined by mass spectrometry. Results Oral administration of glucosylceramide significantly suppressed E0771 tumor growth compared with the control group (P = 0.006). There were no significant differences in the serum concentrations of sphingolipid mediators including ceramide and S1P between the mice treated with glucosylceramide and control-treated mice. The ceramide concentration was significantly lower in tumor tissues (P = 0.026), and the S1P concentration was significantly higher than that in paired non-tumor tissues (P = 0.009). The S1P concentration in tumor tissues was significantly lower in mice treated with glucosylceramide than in control-treated mice (P = 0.001). The ceramide-to-S1P concentration ratio in tumor tissues was significantly higher in mice treated with glucosylceramide than in control-treated mice (P = 0.034). Conclusions Breast tumors could enhance their survival by increasing S1P conversion from ceramide. Oral administration of glucosylceramide suppressed tumor growth by affecting the ceramide/S1P balance. Oral administration of glucosylceramide is a promising basis for a new therapeutic approach.
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Affiliation(s)
- Kazuki Moro
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Hiroshi Ichikawa
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Yu Koyama
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
- Department of Nursing, Graduate School of Health Sciences, Niigata University, Niigata, Japan
| | - Shun Abe
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Haruka Uchida
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Kana Naruse
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Yasuo Obata
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Junko Tsuchida
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Chie Toshikawa
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Mayuko Ikarashi
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Yusuke Muneoka
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Kohei Miura
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Yosuke Tajima
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Yoshifumi Shimada
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Takashi Kobayashi
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Jun Sakata
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Kazuaki Takabe
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Surgery, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, The State University of New York, Buffalo, NY, USA
| | - Toshifumi Wakai
- Division of Digestive and General Surgery, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
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Ren Q, Li Q, Shao C, Zhang P, Hu Z, Li J, Wang W, Yu Y. Establishing a prognostic model based on immune-related genes and identification of BIRC5 as a potential biomarker for lung adenocarcinoma patients. BMC Cancer 2023; 23:897. [PMID: 37741993 PMCID: PMC10517491 DOI: 10.1186/s12885-023-11249-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 08/03/2023] [Indexed: 09/25/2023] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) is an extraordinarily malignant tumor, with rapidly increasing morbidity and poor prognosis. Immunotherapy has emerged as a hopeful therapeutic modality for lung adenocarcinoma. Furthermore, a prognostic model (based on immune genes) can fulfill the purpose of early diagnosis and accurate prognostic prediction. METHODS Immune-related mRNAs (IRmRNAs) were utilized to construct a prognostic model that sorted patients into high- and low-risk groups. Then, the prediction efficacy of our model was evaluated using a nomogram. The differences in overall survival (OS), the tumor mutation landscape, and the tumor microenvironment were further explored between different risk groups. In addition, the immune genes comprising the prognostic model were subjected to single-cell RNA sequencing to investigate the expression of these immune genes in different cells. Finally, the functions of BIRC5 were validated through in vitro experiments. RESULTS Patients in different risk groups exhibited sharply significant variations in OS, pathway activity, immune cell infiltration, mutation patterns, and immune response. Single-cell RNA sequencing revealed that the expression level of BIRC5 was significantly high in T cells. Cell experiments further revealed that BIRC5 knockdown markedly reduced LUAD cell proliferation. CONCLUSION This model can function as an instrumental variable in the prognostic, molecular, and therapeutic prediction of LUAD, shedding new light on the optimal clinical practice guidelines for LUAD patients.
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Affiliation(s)
- Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qifan Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Chenye Shao
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Pengpeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhuangzhuang Hu
- Department of Urology, Shuyang First People's Hospital, Suqian, China
| | - Jun Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Wei Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Yue Yu
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Xu W, Zhang W, Zhao D, Wang Q, Zhang M, Li Q, Zhu W, Xu C. Unveiling the role of regulatory T cells in the tumor microenvironment of pancreatic cancer through single-cell transcriptomics and in vitro experiments. Front Immunol 2023; 14:1242909. [PMID: 37753069 PMCID: PMC10518406 DOI: 10.3389/fimmu.2023.1242909] [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: 06/23/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023] Open
Abstract
Background In order to investigate the impact of Treg cell infiltration on the immune response against pancreatic cancer within the tumor microenvironment (TME), and identify crucial mRNA markers associated with Treg cells in pancreatic cancer, our study aims to delve into the role of Treg cells in the anti-tumor immune response of pancreatic cancer. Methods The ordinary transcriptome data for this study was sourced from the GEO and TCGA databases. It was analyzed using single-cell sequencing analysis and machine learning. To assess the infiltration level of Treg cells in pancreatic cancer tissues, we employed the CIBERSORT method. The identification of genes most closely associated with Treg cells was accomplished through the implementation of weighted gene co-expression network analysis (WGCNA). Our analysis of single-cell sequencing data involved various quality control methods, followed by annotation and advanced analyses such as cell trajectory analysis and cell communication analysis to elucidate the role of Treg cells within the pancreatic cancer microenvironment. Additionally, we categorized the Treg cells into two subsets: Treg1 associated with favorable prognosis, and Treg2 associated with poor prognosis, based on the enrichment scores of the key genes. Employing the hdWGCNA method, we analyzed these two subsets to identify the critical signaling pathways governing their mutual transformation. Finally, we conducted PCR and immunofluorescence staining in vitro to validate the identified key genes. Results Based on the results of immune infiltration analysis, we observed significant infiltration of Treg cells in the pancreatic cancer microenvironment. Subsequently, utilizing the WGCNA and machine learning algorithms, we ultimately identified four Treg cell-related genes (TRGs), among which four genes exhibited significant correlations with the occurrence and progression of pancreatic cancer. Among them, CASP4, TOB1, and CLEC2B were associated with poorer prognosis in pancreatic cancer patients, while FYN showed a correlation with better prognosis. Notably, significant differences were found in the HIF-1 signaling pathway between Treg1 and Treg2 cells identified by the four genes. These conclusions were further validated through in vitro experiments. Conclusion Treg cells played a crucial role in the pancreatic cancer microenvironment, and their presence held a dual significance. Recognizing this characteristic was vital for understanding the limitations of Treg cell-targeted therapies. CASP4, FYN, TOB1, and CLEC2B exhibited close associations with infiltrating Treg cells in pancreatic cancer, suggesting their involvement in Treg cell functions. Further investigation was warranted to uncover the mechanisms underlying these associations. Notably, the HIF-1 signaling pathway emerged as a significant pathway contributing to the duality of Treg cells. Targeting this pathway could potentially revolutionize the existing treatment approaches for pancreatic cancer.
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Affiliation(s)
- Wei Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Wenjia Zhang
- Shanghai Clinical College, Anhui Medical University, Shanghai, China
- Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Dongxu Zhao
- Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Qi Wang
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
| | - Man Zhang
- Department of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
- The Laboratory of Emergency Medicine, School of the Secondary Clinical Medicine, Xuzhou Medical University, Xuzhou, China
| | - Qiang Li
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Wenxin Zhu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
- Department of Gastroenterology, Kunshan Third People’s Hospital, Suzhou, Jiangsu, China
| | - Chunfang Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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Guan H, Chen X, Liu J, Sun J, Guo H, Jiang Y, Zhang H, Zhang B, Lin J, Yuan Q. Molecular characteristics and therapeutic implications of Toll-like receptor signaling pathway in melanoma. Sci Rep 2023; 13:13788. [PMID: 37666853 PMCID: PMC10477197 DOI: 10.1038/s41598-023-38850-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 07/16/2023] [Indexed: 09/06/2023] Open
Abstract
Melanoma is a malignant tumor of melanocytes and is often considered immunogenic cancer. Toll-like receptor-related genes are expressed differently in most types of cancer, depending on the immune microenvironment inside cancer, and the key function of Toll-like receptors (TLRs) for melanoma has not been fully elucidated. Based on multi-omics data from TCGA and GEO databases, we first performed pan-cancer analysis on TLR, including CNV, SNV, and mRNA changes in TLR-related genes in multiple human cancers, as well as patient prognosis characterization. Then, we divided melanoma patients into three subgroups (clusters 1, 2, and 3) according to the expression of the TLR pathway, and explored the correlation between TLR pathway and melanoma prognosis, immune infiltration, metabolic reprogramming, and oncogene expression characteristics. Finally, through univariate Cox regression analysis and LASSO algorithm, we selected six TLR-related genes to construct a survival prognostic model, divided melanoma patients into the training set, internal validation set 1, internal validation set 2, and external validation set for multiple validations, and discussed the correlation between model genes and clinical features of melanoma patients. In conclusion, we constructed a prognostic survival model based on TLR-related genes that precisely and independently demonstrated the potential to assess the prognosis and immune traits of melanoma patients, which is critical for patients' survival.
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Affiliation(s)
- Hewen Guan
- Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xu Chen
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Jifeng Liu
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Jiaao Sun
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hui Guo
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yuankuan Jiang
- Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Huimin Zhang
- Department of Oncology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Biao Zhang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
| | - Jingrong Lin
- Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
| | - Qihang Yuan
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
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Xu W, Jiang T, Shen K, Zhao D, Zhang M, Zhu W, Liu Y, Xu C. GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer. Front Endocrinol (Lausanne) 2023; 14:1224832. [PMID: 37608794 PMCID: PMC10441793 DOI: 10.3389/fendo.2023.1224832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/18/2023] [Indexed: 08/24/2023] Open
Abstract
Background Gastric cancer continues to be a significant global healthcare challenge, and its burden remains substantial. The development of gastric cancer (GC) is closely linked to chronic atrophic gastritis (CAG), yet there is a scarcity of research exploring the underlying mechanisms of CAG-induced carcinogenesis. Methods In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. Our approach employed hdWGCNA to identify pathogenic genes specific to CAG, with non-atrophic gastritis (NAG) serving as the control group. Additionally, we compared CAG with GC, using normal gastric tissue as the control group in the single-cell transcriptome analysis. By intersecting the identified pathogenic genes, we pinpointed key network molecules through protein interaction network analysis. To further refine the gene selection, we applied LASSO, SVM-RFE, and RF techniques, which resulted in a set of cancer-related genes (CRGs) associated with CAG. To identify CRGs potentially linked to gastric cancer progression, we performed a univariate COX regression analysis on the gene set. Subsequently, we explored the relationship between CRGs and immune infiltration, drug sensitivity, and clinical characteristics in gastric cancer patients. We employed GSVA to investigate how CRGs regulated signaling pathways in gastric cancer cells, while an analysis of cell communication shed light on the impact of CRGs on signal transmission within the gastric cancer tumor microenvironment. Lastly, we analyzed changes in metabolic pathways throughout the progression of gastric cancer. Results Using hdWGCNA, we have identified a total of 143 pathogenic genes that were shared by CAG and GC. To further investigate the underlying mechanisms, we conducted protein interaction network analysis and employed machine learning screening techniques. As a result, we have identified 15 oncogenes that are specifically associated with chronic atrophic gastritis. By performing ROC reanalysis and prognostic analysis, we have determined that GADD45B is the most significant gene involved in the carcinogenesis of CAG. Immunohistochemical staining and differential analysis have revealed that GADD45B expression was low in GC tissues while high in normal gastric tissues. Moreover, based on prognostic analysis, high expression of GADD45B has been correlated with poor prognosis in GC patients. Additionally, an analysis of immune infiltration has shown a relationship between GADD45B and the infiltration of various immune cells. By correlating GADD45B with clinical characteristics, we have found that it primarily affects the depth of invasion in GC. Through cell communication analysis, we have discovered that the CD99 signaling pathway network and the CDH signaling pathway network are the main communication pathways that significantly alter the microenvironment of gastric tissue during the development of chronic atrophic gastritis. Specifically, GADD45B-low GC cells were predominantly involved in the network communication of the CDH signaling pathway, while GADD45B-high GC cells played a crucial role in both signaling pathways. Furthermore, we have identified several metabolic pathways, including D-Glutamine and D-glutamate metabolism and N-Glycan biosynthesis, among others, that played important roles in the occurrence and progression of GC, in addition to the six other metabolic pathways. In summary, our study highlighted the discovery of 143 pathogenic genes shared by CAG and GC, with a specific focus on 15 oncogenes associated with CAG. We have identified GADD45B as the most important gene in the carcinogenesis of CAG, which exhibited differential expression in GC tissues compared to normal gastric tissues. Moreover, GADD45B expression was correlated with patient prognosis and is associated with immune cell infiltration. Our findings also emphasized the impact of the CD99 and CDH signaling pathway networks on the microenvironment of gastric tissue during the development of CAG. Additionally, we have identified key metabolic pathways involved in GC progression. Conclusion GADD45B, an oncogene implicated in chronic atrophic gastritis, played a critical role in GC development. Decreased expression of GADD45B was associated with the onset of GC. Moreover, GADD45B expression levels were closely tied to poor prognosis in GC patients, influencing the infiltration patterns of various cells within the tumor microenvironment, as well as impacting the metabolic pathways involved in GC progression.
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Affiliation(s)
- Wei Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Tianxiao Jiang
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Kanger Shen
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Dongxu Zhao
- Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Man Zhang
- Department of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Wenxin Zhu
- Department of Gastroenterology, Kunshan Third People’s Hospital, Suzhou, Jiangsu, China
| | - Yunfei Liu
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Chunfang Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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Chi H, Chen H, Wang R, Zhang J, Jiang L, Zhang S, Jiang C, Huang J, Quan X, Liu Y, Zhang Q, Yang G. Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model. Front Oncol 2023; 13:1244578. [PMID: 37601672 PMCID: PMC10437932 DOI: 10.3389/fonc.2023.1244578] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 07/18/2023] [Indexed: 08/22/2023] Open
Abstract
Background Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications. Methods In this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method. Results Our analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age. Conclusion Our study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.
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Affiliation(s)
- Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Haiqing Chen
- Clinical Medical College, Southwest Medical University, Luzhou, 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
| | - 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
| | - Lai Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Shengke Zhang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Chenglu Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jinbang Huang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xiaomin Quan
- Beijing University of Chinese Medicine, Beijing, China
- Beijing University of Chinese Medicine Second Affiliated DongFang Hospital, Beijing, China
| | - Yunfei Liu
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Qinhong Zhang
- Shenzhen Frontiers in Chinese Medicine Research Co., Ltd., Shenzhen, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
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Kuang T, Zhang L, Chai D, Chen C, Wang W. Construction of a T-cell exhaustion-related gene signature for predicting prognosis and immune response in hepatocellular carcinoma. Aging (Albany NY) 2023; 15:5751-5774. [PMID: 37354485 PMCID: PMC10333082 DOI: 10.18632/aging.204830] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 06/12/2023] [Indexed: 06/26/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with a rising prevalence worldwide. Immunotherapy has been shown to improve treatment outcomes for HCC. We aimed to construct a T-cell exhaustion-related gene prognostic model (TEXPM) for HCC and to elucidate the immunologic characteristics and advantages of immunotherapy in T-cell exhaustion-Related Gene-defined HCC groups. METHODS Single-cell RNA sequencing data were used in conjunction with TCGA Differentially expressed genes (DEGs) to screen for T-cell exhaustion-Related Genes (TEXGs) for subsequent evaluation. Using univariate Cox regression analysis and LASSO regression analysis, five genes (FTL, GZMA, CD14, NPC2, and IER3) were subsequently selected for the construction of a TEXPM. Then, we evaluated the immunologic characteristics and advantages of immunotherapy in groups identified by TEXPM. RESULTS The TEXPM was formed with FTL, GZMA, CD14, NPC2, and IER3. The results of the training and validation team studies were consistent, with the low TEXPM group surviving longer than the high TEXPM group (P < 0.001). Multivariate Cox regression analysis demonstrated that TEXPM (HR: 2.347, 95%CI: 1.844-2.987; HR: 2.172, 95% CI: 1.689-2.793) was an independent prognostic variable for HCC patients. The low-TEXPM group was linked to active immunity, less aggressive phenotypes, strong infiltration of CD8+ T cells, CD4 + T cells, and M1 macrophages, and a better response to ICI treatment. A high TEXPM group, on the other hand, was associated with suppressive immunity, more aggressive phenotypes, a significant infiltration of B cells, M0 macrophages, and M2 macrophages, and a reduced response to ICI treatment. FTL is an independent prognostic variable in HCC patients and the knockdown of FTL can affect the biological behavior of hepatocellular carcinoma cells. CONCLUSIONS TEXPM is a promising prognostic biomarker connected to the immune system. Differentiating immunological and molecular features and predicting patient outcomes may be facilitated by TEXPM grouping. Furthermore, the expression of FTL was found to be an independent prognostic factor for HCC. Knockdown of FTL significantly inhibited proliferation, migration, and invasive activity in liver cancer cells.
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Affiliation(s)
- Tianrui Kuang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lilong Zhang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - Dongqi Chai
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chen Chen
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Weixing Wang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
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Ren Q, Zhang P, Lin H, Feng Y, Chi H, Zhang X, Xia Z, Cai H, Yu Y. A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts. Front Immunol 2023; 14:1201573. [PMID: 37325647 PMCID: PMC10264584 DOI: 10.3389/fimmu.2023.1201573] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 05/17/2023] [Indexed: 06/17/2023] Open
Abstract
Background Extensive research has established the significant correlations between cancer-associated fibroblasts (CAFs) and various stages of cancer development, including initiation, angiogenesis, progression, and resistance to therapy. In this study, we aimed to investigate the characteristics of CAFs in lung adenocarcinoma (LUAD) and develop a risk signature to predict the prognosis of patients with LUAD. Methods We obtained single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the public database. The Seurat R package was used to process the scRNA-seq data and identify CAF clusters based on several biomarkers. CAF-related prognostic genes were further identified using univariate Cox regression analysis. To reduce the number of genes, Lasso regression was performed, and a risk signature was established. A novel nomogram that incorporated the risk signature and clinicopathological features was developed to predict the clinical applicability of the model. Additionally, we conducted immune landscape and immunotherapy responsiveness analyses. Finally, we performed in vitro experiments to verify the functions of EXO1 in LUAD. Results We identified 5 CAF clusters in LUAD using scRNA-seq data, of which 3 clusters were significantly associated with prognosis in LUAD. A total of 492 genes were found to be significantly linked to CAF clusters from 1731 DEGs and were used to construct a risk signature. Moreover, our immune landscape exploration revealed that the risk signature was significantly related to immune scores, and its ability to predict responsiveness to immunotherapy was confirmed. Furthermore, a novel nomogram incorporating the risk signature and clinicopathological features showed excellent clinical applicability. Finally, we verified the functions of EXP1 in LUAD through in vitro experiments. Conclusions The risk signature has proven to be an excellent predictor of LUAD prognosis, stratifying patients more appropriately and precisely predicting immunotherapy responsiveness. The comprehensive characterization of LUAD based on the CAF signature can predict the response of LUAD to immunotherapy, thus offering fresh perspectives into the management of LUAD patients. Our study ultimately confirms the role of EXP1 in facilitating the invasion and growth of tumor cells in LUAD. Nevertheless, further validation can be achieved by conducting in vivo experiments.
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Affiliation(s)
- Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengpeng Zhang
- 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
| | - Yanlong Feng
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xiao Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University, Munich, Germany
| | - Huabao Cai
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yue Yu
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Ren Q, Zhang P, Zhang X, Feng Y, Li L, Lin H, Yu Y. A fibroblast-associated signature predicts prognosis and immunotherapy in esophageal squamous cell cancer. Front Immunol 2023; 14:1199040. [PMID: 37313409 PMCID: PMC10258351 DOI: 10.3389/fimmu.2023.1199040] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 05/19/2023] [Indexed: 06/15/2023] Open
Abstract
Background Current paradigms of anti-tumor therapies are not qualified to evacuate the malignancy ascribing to cancer stroma's functions in accelerating tumor relapse and therapeutic resistance. Cancer-associated fibroblasts (CAFs) has been identified significantly correlated with tumor progression and therapy resistance. Thus, we aimed to probe into the CAFs characteristics in esophageal squamous cancer (ESCC) and construct a risk signature based on CAFs to predict the prognosis of ESCC patients. Methods The GEO database provided the single-cell RNA sequencing (scRNA-seq) data. The GEO and TCGA databases were used to obtain bulk RNA-seq data and microarray data of ESCC, respectively. CAF clusters were identified from the scRNA-seq data using the Seurat R package. CAF-related prognostic genes were subsequently identified using univariate Cox regression analysis. A risk signature based on CAF-related prognostic genes was constructed using Lasso regression. Then, a nomogram model based on clinicopathological characteristics and the risk signature was developed. Consensus clustering was conducted to explore the heterogeneity of ESCC. Finally, PCR was utilized to validate the functions that hub genes play on ESCC. Results Six CAF clusters were identified in ESCC based on scRNA-seq data, three of which had prognostic associations. A total of 642 genes were found to be significantly correlated with CAF clusters from a pool of 17080 DEGs, and 9 genes were selected to generate a risk signature, which were mainly involved in 10 pathways such as NRF1, MYC, and TGF-Beta. The risk signature was significantly correlated with stromal and immune scores, as well as some immune cells. Multivariate analysis demonstrated that the risk signature was an independent prognostic factor for ESCC, and its potential in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the CAF-based risk signature and clinical stage was developed, which exhibited favorable predictability and reliability for ESCC prognosis prediction. The consensus clustering analysis further confirmed the heterogeneity of ESCC. Conclusion The prognosis of ESCC can be effectively predicted by CAF-based risk signatures, and a comprehensive characterization of the CAF signature of ESCC may aid in interpreting the response of ESCC to immunotherapy and offer new strategies for cancer treatment.
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Affiliation(s)
- Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengpeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yanlong Feng
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Long Li
- Department of Thoracic Surgery, Nanjing Gaochun People’s Hospital, Nanjing, China
| | - Haoran Lin
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Yu
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Chi H, Gao X, Xia Z, Yu W, Yin X, Pan Y, Peng G, Mao X, Teichmann AT, Zhang J, Tran LJ, Jiang T, Liu Y, Yang G, Wang Q. FAM family gene prediction model reveals heterogeneity, stemness and immune microenvironment of UCEC. Front Mol Biosci 2023; 10:1200335. [PMID: 37275958 PMCID: PMC10235772 DOI: 10.3389/fmolb.2023.1200335] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients. Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs. Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy. Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.
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Affiliation(s)
- Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xinrui Gao
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Wanying Yu
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xisheng Yin
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Yifan Pan
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Gaoge Peng
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xinrui Mao
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Alexander Tobias Teichmann
- Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jing Zhang
- Division of Basic Biomedical Sciences, The University of South Dakota Sanford School of Medicine, Vermillion, SD, United States
| | - Lisa Jia Tran
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Tianxiao Jiang
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Yunfei Liu
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Qin Wang
- Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
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