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Dong L, Qiu X, Li Z, Ge W, Tang X, Zhou R, Chen W, Xu X, Wang K. Potential crosstalk between Naïve CD4 + T cells and SPP1 + Macrophages is associated with clinical outcome and therapeutic response in hepatocellular carcinoma. Int Immunopharmacol 2024; 142:113231. [PMID: 39332093 DOI: 10.1016/j.intimp.2024.113231] [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: 07/05/2024] [Revised: 09/06/2024] [Accepted: 09/19/2024] [Indexed: 09/29/2024]
Abstract
BACKGROUND The highly heterogeneity of the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) results in diverse clinical outcomes and therapeutic responses. This study aimed to investigate potential intercellular crosstalk and its impact on clinical outcomes and therapeutic responses. METHODS Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST) and bulk RNA sequencing (RNA-seq) datasets were integrated to comprehensively analyze the intercellular interactions within the TME. Multiplex immunohistochemistry was conducted to validate the intercellular interactions. A machine learning-based integrative procedure was used in bulk RNA-seq datasets to generate a risk model to predict prognosis and therapeutic responses. RESULTS Survival analyses based on the bulk RNA-seq datasets revealed the negative impact of the naïve Cluster of Differentiation 4+ (CD4) T cells and Secreted Phosphoprotein 1+ (SPP1) macrophages on prognosis. Furthermore, their intricate intercellular crosstalk and spatial colocalization were also observed by scRNA-seq and ST analyses. Based on this crosstalk, a machine learning model, termed the naïve CD4+ T cell and SPP1+ macrophage prognostic score (TMPS), was established in the bulk-RNA seq datasets for prognostic prediction. The TMPS achieved C-index values of 0.785, 0.715, 0.692 and 0.857, respectively, across 4 independent cohorts. A low TMPS was associated with a significantly increased survival rates, improved response to immunotherapy and reduced infiltration of immunosuppressive cells, such as. regulatory T cells. Finally, 8 potential sensitive drugs and 6 potential targets were predicted for patients based on their TMPS. CONCLUSION The crosstalk between naïve CD4+ T cells and SPP1+ macrophages play a crucial role in the TME. TMPS can reflect this crosstalk and serve as a valuable tool for prognostic stratification and guiding clinical decision-making.
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Affiliation(s)
- Libin Dong
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xun Qiu
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Zekuan Li
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China
| | - Wenwen Ge
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xiao Tang
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Ruhong Zhou
- Institute of Quantitative Biology, Shanghai Institute for Advanced Study, College of Life Sciences, Zhejiang University, Hangzhou 310027, Zhejiang, China
| | - Wei Chen
- Department of Cell Biology, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xiao Xu
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China; School of Clinical Medicine, Hangzhou Medical College, Hangzhou 310059, Zhejiang, China.
| | - Kai Wang
- School of Clinical Medicine, Hangzhou Medical College, Hangzhou 310059, Zhejiang, China.
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Dai YJ, Tang HD, Jiang GQ, Xu ZY. The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients. Transl Oncol 2024; 49:102110. [PMID: 39182362 PMCID: PMC11388017 DOI: 10.1016/j.tranon.2024.102110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 08/10/2024] [Accepted: 08/21/2024] [Indexed: 08/27/2024] Open
Abstract
This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.
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Affiliation(s)
- Ya-Jie Dai
- Department of General Surgery, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; Department of Surgery, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, PR China.
| | - Hao-Dong Tang
- Department of General Surgery, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; Department of Surgery, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, PR China
| | - Guang-Qing Jiang
- Department of General Surgery, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; Department of Surgery, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, PR China
| | - Zhai-Yue Xu
- Department of General Surgery, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; Department of Surgery, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, PR China
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3
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Zhou K, Zhang M, Zhai D, Wang Z, Liu T, Xie Y, Shi Y, Shi H, Chen Q, Li X, Xu J, Cai Z, Zhang Y, Shao N, Lin Y. Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers. Breast Cancer Res Treat 2024; 208:441-459. [PMID: 39030466 DOI: 10.1007/s10549-024-07437-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 07/11/2024] [Indexed: 07/21/2024]
Abstract
PURPOSE Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC. METHODS Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics. RESULTS Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment. CONCLUSION We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.
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Affiliation(s)
- Kaiwen Zhou
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Mengmeng Zhang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Duanyang Zhai
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zilin Wang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Ting Liu
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yubin Xie
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yawei Shi
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Huijuan Shi
- Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Qianjun Chen
- Department of Breast Oncology, Traditional Chinese Medicine Hospital of Guangdong Province, Guangzhou, Guangdong, China
| | - Xiaoping Li
- Department of Breast Oncology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Juan Xu
- Department of Breast Oncology, Maternal and Child Health Care Hospital of Guangdong Province, Guangzhou, China
| | - Zhenhai Cai
- Department of Breast Oncology, Jieyang People's Hospital, Jieyang, Guangdong, China
| | - Yunjian Zhang
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Nan Shao
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Ying Lin
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
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Hu Y, He Z, Liu S, Ying W, Chen Y, Zhao M, He M, Wu X, Tang Y, Gu W, Ying M, Wang J, Tao T. Patient-derived rhabdomyosarcoma cells recapitulate the genetic and transcriptomic landscapes of primary tumors. iScience 2024; 27:110862. [PMID: 39319271 PMCID: PMC11417342 DOI: 10.1016/j.isci.2024.110862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/29/2024] [Accepted: 08/29/2024] [Indexed: 09/26/2024] Open
Abstract
Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in childhood and adolescence. The availability of appropriate and well-characterized preclinical models for RMS is limited, posing a challenge for investigating the molecular mechanisms and evaluating new targeted compounds in preclinical settings. Here, we collected 51 RMS specimens (referred to as ZJUCH-RMS cohort) and established 9 patient-derived cells (PDCs) and validated the identity of these cells by the expression of RMS-specific markers. Whole-transcriptome analysis identified high-confidence mutations in ZJUCH-RMS cohort including RAS, TP53, ARID1A, MYOD1, and MYCN. Further studies showed that RMS PDCs retained the genetic alterations and the expression of RMS hallmark and dependency genes in matched primary tumors and acted as valuable tools to assess drug responses and pharmacogenomic interactions. Our study provides unique PDCs that are available for preclinical studies of RMS and further advances the feasibility of RMS PDCs as valuable tools for developing personalized treatments for patients.
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Affiliation(s)
- Yuxiang Hu
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- The First Clinical Institute, Zunyi Medical University, Zunyi 563000, China
| | - Ziqi He
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- The First Clinical Institute, Zunyi Medical University, Zunyi 563000, China
| | - Shuangai Liu
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- The First Clinical Institute, Zunyi Medical University, Zunyi 563000, China
| | - Wenwen Ying
- Institute of Pharmacology and Toxicology, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yifan Chen
- Institute of Pharmacology and Toxicology, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Manli Zhao
- Department of Pathology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Min He
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Xuan Wu
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Yinbing Tang
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Weizhong Gu
- Department of Pathology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Meidan Ying
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Institute of Pharmacology and Toxicology, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
- Cancer Center, Zhejiang University, Hangzhou 310058, China
| | - Jinhu Wang
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Key Laboratory of Diagnosis and Treatment of Neonatal Diseases of Zhejiang Province, Hangzhou 310052, China
- Cancer Center, Zhejiang University, Hangzhou 310058, China
| | - Ting Tao
- Pediatric Cancer Research Center, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Surgical Oncology, Children’s Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Key Laboratory of Diagnosis and Treatment of Neonatal Diseases of Zhejiang Province, Hangzhou 310052, China
- Cancer Center, Zhejiang University, Hangzhou 310058, China
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Su W, Shi X, Wen X, Li X, Zhou J, Zhou Y, Ren F, Kang K. Integrative analysis of multiple cell death model for precise prognosis and drug response prediction in gastric cancer. Discov Oncol 2024; 15:532. [PMID: 39377861 PMCID: PMC11461726 DOI: 10.1007/s12672-024-01411-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Accepted: 10/01/2024] [Indexed: 10/09/2024] Open
Abstract
BACKGROUND Gastric cancer (GC) is a common upper gastrointestinal tumor. However, the evaluation of prognosis and treatment response in patients with gastric cancer remains a challenge. Programmed cell death (PCD) is one of the important terminal paths for the cells of metazoans, and is involved in a variety of biological events that include morphogenesis, maintenance of tissue homeostasis, and elimination of harmful cells. The objective of this project is to investigate the predictive significance of cell death pathways and create prognostic signatures associated to cell death, with the purpose of forecasting prognosis and providing guidance for the treatment of gastric cancer. METHODS Gene transcription profiles and corresponding clinical data of gastric cancer patients were collected from The Cancer Genome Atlas (TCGA-STAD, n = 448) and the Gene Expression Comprehensive Database (GSE84437, n = 483). Thirteen types of cell death-related genes, including apoptosis, necroptosis, pyroptosis, ferroptosis, autophagy, cuprotosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, were analysed. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Patients were categorized into high and low-risk groups based on the median risk score for survival difference analysis. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Additionally, the response to immunotherapy in the high-risk and low-risk groups was calculated using the oncoPredict algorithm. Futhermore, the model genes were validated in the GEO validation set. RESULTS A total of 324 differential programmed cell death (PCD)-related genes were identified, and 65 were selected through single-factor Cox analysis. Six PCD-related genes were ultimately identified by Lasso regression to construct a prognostic risk score model. The log-rank test revealed that patients in the high-risk group had inferior survival time compared with those in the low-risk group. The area under the ROC curve (AUC) for the training group at years 1, 3, and 5 were 0.684, 0.713, 0.743, respectively, while the AUC for the validation cohort at years 1, 3, and 5 were 0.695, 0.704, and 0.707, respectively. Unsupervised clustering identified potential subtypes included in the model, and a survival difference was also observed between the two subgroups. Multifactor Cox results, combined with clinical information, demonstrated that the prognostic risk score can serve as an independent prognostic factor, irrespective of other clinical features. CONCLUSION By comprehensively analyzing multiple cell death patterns, we have established a novel model that accurately forecasts the clinical prognosis and drug sensitivity of gastric cancer. It was found that all 12 representative drugs may not be suitable for patients in high-risk groups.
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Affiliation(s)
- Weiping Su
- Department of Orthopedics, The Third Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xunyang Shi
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xinhua Wen
- Department of General Surgery, The Third People's Hospital of Hengyang City (Hengyang Public Health Clinical Center), Hengyang, 417600, Hunan, China
| | - Xuanxuan Li
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Jingyu Zhou
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yangying Zhou
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Feng Ren
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Kuo Kang
- Department of General Surgery, Xiangya Hospital Central South University, Changsha, 410008, Hunan, China.
- Hunan Key Laboratory of Precise Diagnosis and Treatment of Gastrointestinal Tumor, Xiangya Hospital Central South University, Changsha, 410008, Hunan, China.
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6
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Wang W, Jiao Y, Du X, Ye Z. Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma. Gene 2024; 933:148985. [PMID: 39369757 DOI: 10.1016/j.gene.2024.148985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 10/02/2024] [Accepted: 10/03/2024] [Indexed: 10/08/2024]
Abstract
Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type's preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs' risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.
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Affiliation(s)
- Wen Wang
- Zhejiang University, Hangzhou, Zhejiang 310058, China; Department of Orthopedics, Fenghua People's Hospital, 36 Gongyuan Road, Ningbo, Zhejiang 315502, China; Department of Orthopedics, Musculoskeletal Tumor Center, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yunjia Jiao
- Clinical Laboratory, Minhang Hospital, Fudan University, No. 170, Xinsong Road, Shanghai 201199, China
| | - Xiaojing Du
- Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
| | - Zhaoming Ye
- Zhejiang University, Hangzhou, Zhejiang 310058, China; Department of Orthopedics, Musculoskeletal Tumor Center, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
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Yang J, Shen L, Zhou J, Wu J, Yue C, Wang T, Chai S, Cai Y, Xu D, Lei Y, Zhao J, Zhou Y, Mei Z, Xiong N. A Novel Mitochondrial-Related Gene Signature for the Prediction of Prognosis and Therapeutic Efficacy in Lower-Grade Glioma. Biochem Genet 2024:10.1007/s10528-024-10928-w. [PMID: 39356352 DOI: 10.1007/s10528-024-10928-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 09/15/2024] [Indexed: 10/03/2024]
Abstract
Lower-grade glioma (LGG) is a common primary brain tumor with a highly heterogeneous clinical presentation, and its prognosis cannot be accurately predicted by current histopathology. It has been found that mitochondria play an important role in hypoxia, angiogenesis, and energy metabolism in glioma, and mitochondrial function may have an important impact on LGG prognosis. The goal of this study was to develop a novel prognostic model based on Mitochondrial-related genes (MRGs). We first analyzed the somatic alterations profiles of MRGs in patients with LGG and found that somatic alterations were common in LGG and correlated with prognosis. Using RNA-seq data from TCGA and CGGA, 12 prognosis-related MRGs were identified to construct a mitochondrial activation score (MiAS) model by combining univariate regression and LASSO regression analysis. The model and nomogram were evaluated using the area under the ROC curve with AUC = 0.910. The model was closely correlated with the clinical characteristics of LGG patients and performed well in predicting the prognosis of LGG patients with significantly shorter overall survival (OS) time in the high-MiAS group. GSVA and GSEA results showed that oxidative stress, pro-cancer, and immune-related pathways were significantly enriched in the high-MiAS group. CIBERSORT results showed that MiAS was significantly associated with immune cell infiltration in LGG. Macrophage M1 and follicular helper T cells had increased infiltration in the high-MiAS group. TIDE predicted a better immunotherapy outcome in patients in the low-MiAS group. Finally, using data from the CTRPv2 and GDSC2 datasets to assess chemotherapy response in LGG, it was predicted that the chemotherapeutic agents AZD6482, MG-132, and PLX-4720 might be potential agents for patients in the high-MiAS group of LGG. In addition, we performed in vitro experiments and found that knockdown of OCIAD2 expression reduced the abilities of glioma cells to proliferate, migrate, and invade. In contrast, overexpression of OCIAD2 enhanced these abilities of glioma cells. This study found that MRGs were correlated with LGG patient prognosis, which is expected to provide new treatment strategies for LGG patients with different MiAS.
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Affiliation(s)
- Jingyi Yang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Lei Shen
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Jiabin Zhou
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Ji Wu
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Chuqiao Yue
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Tiansheng Wang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Songshan Chai
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Yuankun Cai
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Dongyuan Xu
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Yu Lei
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Jingwei Zhao
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Yixuan Zhou
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Zhimin Mei
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China
| | - Nanxiang Xiong
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, No.169, Donghu Road, Wuhan, 430071, Hubei, China.
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Li K, Guo C, Li R, Yao Y, Qiang M, Chen Y, Tu K, Xu Y. Pan-cancer characterization of cellular senescence reveals its inter-tumor heterogeneity associated with the tumor microenvironment and prognosis. Comput Biol Med 2024; 182:109196. [PMID: 39362000 DOI: 10.1016/j.compbiomed.2024.109196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2024] [Revised: 09/17/2024] [Accepted: 09/22/2024] [Indexed: 10/05/2024]
Abstract
Cellular senescence (CS) is characterized by the irreversible cell cycle arrest and plays a key role in aging and diseases, such as cancer. Recent years have witnessed the burgeoning exploration of the intricate relationship between CS and cancer, with CS recognized as either a suppressing or promoting factor and officially acknowledged as one of the 14 cancer hallmarks. However, a comprehensive characterization remains absent from elucidating the divergences of this relationship across different cancer types and its involvement in the multi-facets of tumor development. Here we systematically assessed the cellular senescence of over 10,000 tumor samples from 33 cancer types, starting by defining a set of cancer-associated CS signatures and deriving a quantitative metric representing the CS status, called CS score. We then investigated the CS heterogeneity and its intricate relationship with the prognosis, immune infiltration, and therapeutic responses across different cancers. As a result, cellular senescence demonstrated two distinct prognostic groups: the protective group with eleven cancers, such as LIHC, and the risky group with four cancers, including STAD. Subsequent in-depth investigations between these two groups unveiled the potential molecular and cellular mechanisms underlying the distinct effects of cellular senescence, involving the divergent activation of specific pathways and variances in immune cell infiltrations. These results were further supported by the disparate associations of CS status with the responses to immuno- and chemo-therapies observed between the two groups. Overall, our study offers a deeper understanding of inter-tumor heterogeneity of cellular senescence associated with the tumor microenvironment and cancer prognosis.
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Affiliation(s)
- Kang Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China; Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Chen Guo
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Rufeng Li
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Yufei Yao
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Min Qiang
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Yuanyuan Chen
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China
| | - Kangsheng Tu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
| | - Yungang Xu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China; Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China; Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Ministry of Education, Xi'an, Shaanxi, 710061, China.
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9
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Mo W, Deng L, Cheng Y, Ge S, Wang J. IGFBP7 regulates cell proliferation and migration through JAK/STAT pathway in gastric cancer and is regulated by DNA and RNA methylation. J Cell Mol Med 2024; 28:e70080. [PMID: 39351597 PMCID: PMC11443158 DOI: 10.1111/jcmm.70080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 06/06/2024] [Accepted: 08/22/2024] [Indexed: 10/04/2024] Open
Abstract
New biomarkers for early diagnosis of gastric cancer (GC), the second leading cause of cancer-related death, are urgently needed. IGFBP7, known to play various roles in multiple tumours, is complexly regulated across diverse cancer types, as evidenced by our pancancer analysis. Bioinformatics analysis revealed that IGFBP7 expression was related to patient prognosis, tumour clinicopathological characteristics, tumour stemness, microsatellite instability and immune cell infiltration, as well as the expression of oncogenes and immune checkpoints. GSEA links IGFBP7 to several cancer-related pathways. IGFBP7 deficiency inhibited GC cell proliferation and migration in vitro. Furthermore, an in vivo nude mouse model revealed that IGFBP7 downregulation suppressed the tumorigenesis of GC cells. Western blotting analysis showed that the JAK1/2-specific inhibitor ruxolitinib could rescue alterations induced by IGFBP7 overexpression in GC cells. Additionally, our bioinformatics analysis and in vitro assays suggested that IGFBP7 is regulated by DNA methylation at the genetic level and that the RNA m6A demethylase FTO modulates it at the posttranscriptional level. This study emphasizes the clinical relevance of IGFBP7 in GC and its influence on cell proliferation and migration via the JAK/STAT signalling pathway. This study also highlights the regulation of IGFBP7 in GC by DNA and m6A RNA methylation.
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Affiliation(s)
- Weilie Mo
- Department of General Surgery, Changzhou No.7 People's Hospital, Changzhou, China
- Department of General Surgery, Changzhou Geriatric Hospital affiliated to Soochow University, Changzhou, China
| | - Lijian Deng
- Department of Oncology, Changzhou No.7 People's Hospital, Changzhou, China
- Department of Oncology, Changzhou Geriatric Hospital affiliated to Soochow University, Changzhou, China
| | - Yun Cheng
- Department of General Surgery, Changzhou No.7 People's Hospital, Changzhou, China
- Department of General Surgery, Changzhou Geriatric Hospital affiliated to Soochow University, Changzhou, China
| | - Sen Ge
- Department of General Surgery, Changzhou No.7 People's Hospital, Changzhou, China
- Department of General Surgery, Changzhou Geriatric Hospital affiliated to Soochow University, Changzhou, China
| | - Jin Wang
- School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
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10
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Pu K, Gao J, Feng Y, Hu J, Tang S, Yang G, Xu C. Comprehensive evaluation of immunological attributes and immunotherapy responses of positive T cell function regulators in colorectal cancer. BMC Gastroenterol 2024; 24:339. [PMID: 39354362 PMCID: PMC11443709 DOI: 10.1186/s12876-024-03409-2] [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: 02/23/2024] [Accepted: 09/09/2024] [Indexed: 10/03/2024] Open
Abstract
BACKGROUND Positive regulators of T-cell function (PTFRs), integral to T-cell proliferation and activation, have been identified as potential prognostic markers in colorectal cancer (CRC). Despite this, their role within the tumor microenvironment (TME) and their response to immunotherapy are not yet fully understood. METHODS This study delved into PTFR-related CRC subtypes by analyzing four independent transcriptome datasets, emphasizing the most significant prognostic PTFRs. We identified differentially expressed genes (DEGs) between two subtypes and developed a PTFR risk model using LASSO and Cox regression methods. The model's associations with survival time, clinical features, TME characteristics, tumor mutation profiles, microsatellite instability (MSI), cancer stem cell (CSC) index, and responses to chemotherapy, targeted therapy, and immunotherapy were subsequently explored. RESULTS The PTFR risk model demonstrated a strong predictive capacity for CRC. It facilitated the estimation of immune cell composition, HLA expression levels, immune checkpoint expression, mutation burden, CSC index features, and the effectiveness of immunotherapy. CONCLUSIONS This study enhances our understanding of the role of PTFRs in CRC progression and introduces an innovative assessment framework for CRC immunotherapy. This framework improves the prediction of treatment outcomes and aids in the customization of therapeutic strategies.
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Affiliation(s)
- Ke Pu
- Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, China
| | - Jingyuan Gao
- Department of Immunology, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, 712046, China
| | - Yang Feng
- Department of Neurosurgery, Xi'an No.3 Hospital, the Affiliated Hospital of Northwest University, Xi'an, Shaanxi, 710018, China
| | - Jian Hu
- Department of Thoracic and Cardiovascular Surgery, Dazhou Second People's Hospital, Integrated TCM & Western Medicine Hospital, Dazhou, 635000, China
| | - Shunli Tang
- Department of Pathology, Dazhou Second People's Hospital, Integrated TCM & Western Medicine Hospital, Dazhou, 635000, China
| | - Guodong Yang
- Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, China.
| | - Chuan Xu
- Department of Oncology & Cancer Institute, Sichuan Provincial People's Hospital, Sichuan Academy of Medical Sciences, University of Electronic Science and Technology of China, Chengdu, 610072, China.
- Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
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11
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Qiu J, Fu Y, Liu T, Wang J, Liu Y, Zhang Z, Ye Z, Cao Z, Su D, Luo W, Tao J, Weng G, Ye L, Zhang F, Liang Z, Zhang T. Single-cell RNA-seq reveals heterogeneity in metastatic renal cell carcinoma and effect of anti-angiogenesis therapy in the pancreas metastatic lesion. Cancer Lett 2024; 601:217193. [PMID: 39159881 DOI: 10.1016/j.canlet.2024.217193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 08/12/2024] [Accepted: 08/13/2024] [Indexed: 08/21/2024]
Abstract
Metastatic clear cell renal cell carcinoma has heterogenous tumor microenvironment (TME). Among the metastatic lesions, pancreas metastasis is rare and controversy in treatment approaches. Here, extensive primary and metastatic lesion samples were included by single-cell RNA-seq to decipher the distinct metastasis TME. The hypoxic and inflammatory TME of pancreas metastasis was decoded in this study, and the activation of PAX8-myc signaling, and metabolic reprogramming were observed. The active components including endothelial cells, fibroblasts and T cells were profiled. Meanwhile, we also evaluated the effect of anti-angiogenesis treatment in the pancreas metastasis patient. The potential mechanisms of pancreatic tropism, instability of genome, and the response of immunotherapy were also discussed in this work. Taken together, our findings suggest a clue to the heterogeneity in metastasis TME and provide evidence for the treatment of pancreas metastasis in renal cell carcinoma patients.
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Affiliation(s)
- Jiangdong Qiu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Yifan Fu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China; 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Tao Liu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Jun Wang
- Department of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Yueze Liu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Zeyu Zhang
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Ziwen Ye
- Department of Urology, The Fist Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Zhe Cao
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Dan Su
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Wenhao Luo
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Jinxin Tao
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Guihu Weng
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Liyuan Ye
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Feifan Zhang
- Department of Computer Science, University College London, UK.
| | - Zhiyong Liang
- Department of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Taiping Zhang
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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12
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Ma H, Shi L, Zheng J, Zeng L, Chen Y, Zhang S, Tang S, Qu Z, Xiong X, Zheng X, Yin Q. Advanced machine learning unveils CD8 + T cell genetic markers enhancing prognosis and immunotherapy efficacy in breast cancer. BMC Cancer 2024; 24:1222. [PMID: 39354417 PMCID: PMC11446097 DOI: 10.1186/s12885-024-12952-w] [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: 05/19/2024] [Accepted: 09/13/2024] [Indexed: 10/03/2024] Open
Abstract
BACKGROUND Breast cancer (BC) is the most common cancer in women and poses a significant health burden, especially in China. Despite advances in diagnosis and treatment, patient variability and limited early detection contribute to poor outcomes. This study examines the role of CD8 + T cells in the tumor microenvironment to identify new biomarkers that improve prognosis and guide treatment strategies. METHODS CD8 + T-cell marker genes were identified using single-cell RNA sequencing (scRNA-seq), and a CD8 + T cell-related gene prognostic signature (CTRGPS) was developed using 10 machine-learning algorithms. The model was validated across seven independent public datasets from the GEO database. Clinical features and previously published signatures were also analyzed for comparison. The clinical applications of CTRGPS in biological function, immune microenvironment, and drug selection were explored, and the role of hub genes in BC progression was further investigated. RESULTS We identified 71 CD8 + T cell-related genes and developed the CTRGPS, which demonstrated significant prognostic value, with higher risk scores linked to poorer overall survival (OS). The model's accuracy and robustness were confirmed through Kaplan-Meier and ROC curve analyses across multiple datasets. CTRGPS outperformed existing prognostic signatures and served as an independent prognostic factor. The role of the hub gene TTK in promoting malignant proliferation and migration of BC cells was validated. CONCLUSION The CTRGPS enhances early diagnosis and treatment precision in BC, improving clinical outcomes. TTK, a key gene in the signature, shows promise as a therapeutic target, supporting the CTRGPS's potential clinical utility.
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Affiliation(s)
- Haodi Ma
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - LinLin Shi
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital, College of Clinical Medicine, Medical College of Henan University of Science and Technology, Luoyang, China
| | - Jiayu Zheng
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Li Zeng
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Youyou Chen
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Shunshun Zhang
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Siya Tang
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Zhifeng Qu
- Radiology Department, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, China
| | - Xin Xiong
- Department of Pathology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Xuewei Zheng
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
- School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
| | - Qinan Yin
- Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
- School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
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Shen Y, Chen J, Zhou Z, Wu J, Hu X, Xu Y, Li J, Wang L, Wang S, Yu S, Feng L, Xu X. Matrix stiffness-related extracellular matrix signatures and the DYNLL1 protein promote hepatocellular carcinoma progression through the Wnt/β-catenin pathway. BMC Cancer 2024; 24:1211. [PMID: 39350022 PMCID: PMC11440708 DOI: 10.1186/s12885-024-12973-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024] Open
Abstract
BACKGROUND In hepatocellular carcinoma (HCC) treatment, first-line targeted therapy in combination with immune checkpoint inhibitors (ICIs) has improved patient prognosis, but the 5-year survival rate is far from satisfactory. Studies have shown that the extracellular matrix (ECM) is an essential part of the tumour microenvironment (TME) and participates in the progression of malignant tumours. ECM remodelling can enhance matrix stiffness in cirrhosis patients, induce an immunosuppressive microenvironment network, and affect the efficacy of targeted therapies and ICIs for treating HCC. However, the exact mechanism is still unclear. METHODS We downloaded data from public databases, selected differentially expressed ECM proteins associated with matrix stiffness, constructed and validated a prognostic model of HCC using Lasso Cox regression, and investigated the roles and mechanism of one of the ECM proteins, dynein light chain LC8-type 1 (DYNLL1), in HCC proliferation, migration, and apoptosis via in vitro experiments. RESULTS In this study, the risk score of the matrix stiffness-related ECM protein model effectively predicted the prognosis of HCC patients. The high- and low-risk subgroups of the model also showed differences in immune cells, immune functions, and drug sensitivity. DYNLL1 promoted HCC cell progression and migration and inhibited HCC cell apoptosis through the Wnt/β-catenin pathway in vitro. CONCLUSION The expression of matrix stiffness-related ECM proteins could be an independent predictor of HCC prognosis. DYNLL1, an oncogenic gene in HCC, has the potential to be a new target for HCC treatment.
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Affiliation(s)
- Yang Shen
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Jiayu Chen
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Zhuolin Zhou
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Jingyu Wu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Xinyao Hu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Yangtao Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Jiayi Li
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Ling Wang
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Siyu Wang
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Shuhong Yu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Ling Feng
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
| | - Ximing Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
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14
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Han C, Feng Z, Wang Y, Hu M, Xu S, Jiang F, Han Y, Liu Z, Li Y. Copper metabolism-related signature for prognosis prediction and MMP13 served as malignant factor for breast cancer. Heliyon 2024; 10:e36445. [PMID: 39315182 PMCID: PMC11417231 DOI: 10.1016/j.heliyon.2024.e36445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 08/13/2024] [Accepted: 08/15/2024] [Indexed: 09/25/2024] Open
Abstract
Objectives To comprehensively analyze the copper metabolism in Breast cancer, we established a prognostic signature for breast cancer (BC) related to copper metabolism. Methods Copper metabolism-related genes were sourced from previous literatures and were selected by the Univariate Cox regression. Cu-enrichment scores were calculated via ssGSEA. Differentially expressed genes were identified with limma between high and low Cu-enrichment scores group, then we used the Random Survival Forest and LASSO to build the CuScore for BC. Kaplan-Meier analysis, ROC curves, and Cox regression were used to evaluate CuScore. Genomic mutations were analyzed with GISTIC. Immune cells were examined using ESTIMATE, ssGSEA and TIMER. Enrichment analysis used clusterProfiler and GSVA. The GDSC database and oncoPredict package analyzed chemotherapeutic sensitivity. MMP13 was selected for in vitro assays. Results Four copper metabolism-related genes (UBE2D2, SLC31A1, ATP7A, and MAPK1) with prognostic value were identified. Higher expression levels of these genes were associated with higher Cu-enrichment scores, a factor of malignancy in breast cancer. Among 115 differentially expressed genes, 19 prognostic genes were identified, with three (CEACAM5, MMP13, and CRISP3) highlighted by Random Survival Forest and LASSO. Higher CuScores correlated with worse prognoses and were effective in predicting breast cancer outcomes. CuScore and metastasis were independent prognostic factors. Tumor-infiltrating immune cells were associated with lower CuScores. GO-GSEA analysis indicated six immune-related pathways might be regulated by CuScore. Patients with higher CuScores had lower TMB and were more sensitive to Sapitinib and LCL161, while those with lower CuScores might respond better to anti-PD1 therapy. High MMP13 expression in breast cancer was linked to malignancy, affecting cell proliferation and migration. Conclusion The identified copper metabolism-related gene signature has the potential to predict prognosis and guide clinical treatment for BC. Among these genes, MMP13 may act as a malignant factor in BC.
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Affiliation(s)
- Chaojie Han
- Institutes of Biology and Medical Sciences, Soochow University, 333 East Ganjiang Road, Suzhou, Jiangsu, 215127, China
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
- Zhejiang Zhenyuan Biotech Co., LTD, 61 Yuedongbei Road, Shaoxing, Zhejiang, 312000, China
| | - Zhangyang Feng
- Institutes of Biology and Medical Sciences, Soochow University, 333 East Ganjiang Road, Suzhou, Jiangsu, 215127, China
| | - Yingjian Wang
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Mengsi Hu
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Shoufang Xu
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Feiyu Jiang
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Yetao Han
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Zhiwei Liu
- Department of Blood Transfusion, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, China
| | - Yunsen Li
- Institutes of Biology and Medical Sciences, Soochow University, 333 East Ganjiang Road, Suzhou, Jiangsu, 215127, China
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15
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Liu YX, Song JL, Li XM, Lin H, Cao YN. Identification of target genes co-regulated by four key histone modifications of five key regions in hepatocellular carcinoma. Methods 2024; 231:165-177. [PMID: 39349287 DOI: 10.1016/j.ymeth.2024.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 08/27/2024] [Accepted: 09/27/2024] [Indexed: 10/02/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is a cancer with high morbidity and mortality. Studies have shown that histone modification plays an important regulatory role in the occurrence and development of HCC. However, the specific regulatory effects of histone modifications on gene expression in HCC are still unclear. This study focuses on HepG2 cell lines and hepatocyte cell lines. First, the distribution of histone modification signals in the two cell lines was calculated and analyzed. Then, using the random forest algorithm, we analyzed the effects of different histone modifications and their modified regions on gene expression in the two cell lines, four key histone modifications (H3K36me3, H3K4me3, H3K79me2, and H3K9ac) and five key regions that co-regulate gene expression were obtained. Subsequently, target genes regulated by key histone modifications in key regions were screened. Combined with clinical data, Cox regression analysis and Kaplan-Meier survival analysis were performed on the target genes, and four key target genes (CBX2, CEBPZOS, LDHA, and UMPS) related to prognosis were identified. Finally, through immune infiltration analysis and drug sensitivity analysis of key target genes, the potential role of key target genes in HCC was confirmed. Our results provide a theoretical basis for exploring the occurrence of HCC and propose potential biomarkers associated with histone modifications, which may be potential drug targets for the clinical treatment of HCC.
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Affiliation(s)
- Yu-Xian Liu
- School of Artificial Intelligence, Anhui University of Science and Technology, Huainan 232001, China.
| | - Jia-Le Song
- School of Artificial Intelligence, Anhui University of Science and Technology, Huainan 232001, China
| | - Xiao-Ming Li
- School of Artificial Intelligence, Anhui University of Science and Technology, Huainan 232001, China
| | - Hao Lin
- Key Laboratory for Neuro-Information of Ministry of Education, Center for Informational Biology, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Yan-Ni Cao
- School of Artificial Intelligence, Anhui University of Science and Technology, Huainan 232001, China.
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16
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Tang J, Wang W, Tang G. ENO2 in progression and treatment of colon adenocarcinoma: integrative bioinformatics analysis on non-apoptotic cell death. Discov Oncol 2024; 15:478. [PMID: 39331182 PMCID: PMC11436658 DOI: 10.1007/s12672-024-01208-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Accepted: 07/30/2024] [Indexed: 09/28/2024] Open
Abstract
Colon adenocarcinoma (COAD) is one of the most common types of cancer. The interconnection between non-apoptotic cell death and COAD has not been adequately addressed. In our study, an integrative bioinformatics analysis was performed to explore non-apoptotic cell death-related biomarkers in COAD. ENO2 was determined as a potent biomarker for prognosis, drug response, immunity, and immunotherapy prediction. We used EdU and RT-qPCR assays to test our hypothesis and investigate how the ENO2 gene may influence or regulate cancer-related processes. ENO2 was expected to be a potential target in COAD.
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Affiliation(s)
- Jia Tang
- Department of Gastroenterology, The Seventh People's Hospital of Chongqing, Chongqing, 401320, People's Republic of China
| | - Weiqiang Wang
- Department of Gastroenterology, The Seventh People's Hospital of Chongqing, Chongqing, 401320, People's Republic of China
| | - Guangming Tang
- Department of Gastroenterology, The Seventh People's Hospital of Chongqing, Chongqing, 401320, People's Republic of China.
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17
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Wang B, Wei Z, Xu M, Shu H, Fan Z. Identification of key ferroptosis genes and subtypes in kidney renal clear cell carcinoma. Discov Oncol 2024; 15:492. [PMID: 39331243 PMCID: PMC11436560 DOI: 10.1007/s12672-024-01363-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 09/18/2024] [Indexed: 09/28/2024] Open
Abstract
Tumour immunity is highly important for the occurrence and development of tumours, and many cancers are resistant to ferroptosis. This study aims to explore the relationship between ferroptosis-related genes (FRGs) and the immunological characteristics of kidney renal clear cell carcinoma (KIRC). We obtained RNA-seq profiles and clinical data of KIRC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and identified CD44 and GLRX5 as the key FRGs involved in KIRC immune infiltration through Spearman's correlation analysis. Based on the expression of CD44 and GLRX5, the consensus clustering algorithm was used to classify the TCGA-KIRC samples into two clusters. A nomogram was constructed to evaluate the prognosis of KIRC patients. ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate immune infiltration between the two clusters. A weighted gene co-expression network analysis (WGCNA) was used to identify the most relevant genes to the clusters and immunity. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The external dataset GSE53757 was used to validate the immunological features between the two clusters. Cluster 2 patients had more active immune infiltration and might be more sensitive to immunotherapy; Cluster 2 patients also had a worse prognosis and might be at a more advanced stage of KIRC. We identified key ferroptosis-related genes and subgroups involved in the immune infiltration of KIRC, which is highly important for exploring the molecular mechanisms and treatments of KIRC.
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Affiliation(s)
- Biao Wang
- Department of Urology, The Central Hospital of Xiaogan, Xiaogan, 432000, Hubei, China
| | - Zhuo Wei
- Department of Urology, The Central Hospital of Xiaogan, Xiaogan, 432000, Hubei, China
| | - Man Xu
- Affiliated Eye Hospital of Nanchang University, Nanchang, 330000, Jiangxi, China
| | - Hui Shu
- Department of Urology, The Central Hospital of Xiaogan, Xiaogan, 432000, Hubei, China.
| | - Zheqi Fan
- Department of Urology, The Central Hospital of Xiaogan, Xiaogan, 432000, Hubei, China.
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Wu C, Qin W, Lu W, Lin J, Yang H, Li C, Mao Y. Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches. Discov Oncol 2024; 15:470. [PMID: 39331252 PMCID: PMC11436577 DOI: 10.1007/s12672-024-01396-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 09/24/2024] [Indexed: 09/28/2024] Open
Abstract
Lung adenocarcinoma (LUAD), a prevalent type of non-small cell lung cancer (NSCLC), was known for its diversity and intricate tumor microenvironment (TME). Comprehending the interaction among human immune-related genes (IRGs) and the TME is vital in the creation of accurate predictive models and specific treatments. We created a risk score based on IRGs and designed a nomogram to predict the prognosis of LUAD accurately. This involved a thorough examination of TME and the infiltration of immune cells in both high-risk and low-risk LUAD groups. Furthermore, the examination of the association between characteristic genes (BIRC5 and BMP5) and immune cells, along with immune checkpoints in the TME, was also conducted. The findings of our research unveiled unique immune profiles and interactions among individuals in the high- and low-risk categories, which contribute to variations in prognosis. LUAD demonstrated significant associations between BIRC5, BMP5, immune cells, and checkpoints, suggesting their involvement in disease advancement and resistance to medication. Furthermore, by correlating our findings with a multidrug database, we identified specific LUAD patient subsets that might benefit from tailored treatments. Our study establishes a groundbreaking prognostic model for LUAD, which not only underscores the importance of the immune context in LUAD but also paves the way for advancing precision medicine strategies in this complex malignancy.
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Affiliation(s)
- Changjiang Wu
- Department of Intensive Care Unit, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, Jiangsu, China
| | - Wangshang Qin
- Genetic and Metabolic Central Laboratory, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530003, Guangxi, China
| | - Wenqiang Lu
- Department of Thoracic Surgery, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, Jiangsu, China
| | - Jingyu Lin
- Department of Science & Education, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, Jiangsu, China
| | - Hongwei Yang
- Department of Clinical Laboratory, Suzhou BOE Hospital, Suzhou, 215028, Jiangsu, China
| | - Chunhong Li
- Central Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
- Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
| | - Yiming Mao
- Department of Thoracic Surgery, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, Jiangsu, China.
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Li C, Mao Y, Hu J, Su C, Li M, Tan H. Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma. Immunol Res 2024:10.1007/s12026-024-09544-y. [PMID: 39320693 DOI: 10.1007/s12026-024-09544-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Accepted: 09/13/2024] [Indexed: 09/26/2024]
Abstract
Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given that abnormal reprogramming of asparagine metabolism (AM) has emerged as an emerging therapeutic target for anti-tumor therapy. However, the clinical significance of abnormal reprogramming of AM in LUAD patients is unclear. In this study, we collected 864 asparagine metabolism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Through the utilization of median AMII scores, LUAD patients were segregated into either a low-AMII group or a high-AMII group. We observed outstanding performance of AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745, and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C-index analysis and decision analysis showed that AMII-based nomograms had a robust performance in terms of accuracy of prognostic prediction and net clinical benefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group were more sensitive to commonly used chemotherapeutic drugs. Consequently, AMII is expected to be a novel diagnostic tool for clinical classification, providing valuable insights for clinical decision-making and personalized management of LUAD patients.
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Affiliation(s)
- Chunhong Li
- Central Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin , 541199, Guangxi, China.
- Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
| | - Yuhua Mao
- Department of Obstetrics, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Jiahua Hu
- Central Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin , 541199, Guangxi, China
- Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Chunchun Su
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Mengqin Li
- College of Pharmacy, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Haiyin Tan
- School of Medical Laboratory Medicine, Guilin Medical University, Guilin, 541004, Guangxi, China
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20
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Zheng S, Su Z, He Y, You L, Zhang G, Chen J, Lu L, Liu Z. Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment. Front Immunol 2024; 15:1454977. [PMID: 39380994 PMCID: PMC11458406 DOI: 10.3389/fimmu.2024.1454977] [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: 06/26/2024] [Accepted: 09/05/2024] [Indexed: 10/10/2024] Open
Abstract
Background Hepatocellular carcinoma (HCC) is highly aggressive, with delayed diagnosis, poor prognosis, and a lack of comprehensive and accurate prognostic models to assist clinicians. This study aimed to construct an HCC prognosis-related gene signature (HPRGS) and explore its clinical application value. Methods TCGA-LIHC cohort was used for training, and the LIRI-JP cohort and HCC cDNA microarray were used for validation. Machine learning algorithms constructed a prognostic gene label for HCC. Kaplan-Meier (K-M), ROC curve, multiple analyses, algorithms, and online databases were used to analyze differences between high- and low-risk populations. A nomogram was constructed to facilitate clinical application. Results We identified 119 differential genes based on transcriptome sequencing data from five independent HCC cohorts, and 53 of these genes were associated with overall survival (OS). Using 101 machine learning algorithms, the 10 most prognostic genes were selected. We constructed an HCC HPRGS with four genes (SOCS2, LCAT, ECT2, and TMEM106C). Good predictive performance of the HPRGS was confirmed by ROC, C-index, and K-M curves. Mutation analysis showed significant differences between the low- and high-risk patients. The low-risk group had a higher response to transcatheter arterial chemoembolization (TACE) and immunotherapy. Treatment response of high- and low-risk groups to small-molecule drugs was predicted. Linifanib was a potential drug for high-risk populations. Multivariate analysis confirmed that HPRGS were independent prognostic factors in TCGA-LIHC. A nomogram provided a clinical practice reference. Conclusion We constructed an HPRGS for HCC, which can accurately predict OS and guide the treatment decisions for patients with HCC.
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Affiliation(s)
- Shengzhou Zheng
- Department of Emergency, Fujian Medical University Union Hospital, Fuzhou, China
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Zhixiong Su
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Yufang He
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Lijie You
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Guifeng Zhang
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Jingbo Chen
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
| | - Lihu Lu
- Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zhenhua Liu
- Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China
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Chen Z, Liu C, Zhang C, Xia Y, Peng J, Miao C, Luo Q. Machine learning-based discovery of UPP1 as a key oncogene in tumorigenesis and immune escape in gliomas. Front Immunol 2024; 15:1475206. [PMID: 39380997 PMCID: PMC11458454 DOI: 10.3389/fimmu.2024.1475206] [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: 08/03/2024] [Accepted: 08/30/2024] [Indexed: 10/10/2024] Open
Abstract
Introduction Gliomas are the most common and aggressive type of primary brain tumor, with a poor prognosis despite current treatment approaches. Understanding the molecular mechanisms underlying glioma development and progression is critical for improving therapies and patient outcomes. Methods The current study comprehensively analyzed large-scale single-cell RNA sequencing and bulk RNA sequencing of glioma samples. By utilizing a series of advanced computational methods, this integrative approach identified the gene UPP1 (Uridine Phosphorylase 1) as a novel driver of glioma tumorigenesis and immune evasion. Results High levels of UPP1 were linked to poor survival rates in patients. Functional experiments demonstrated that UPP1 promotes tumor cell proliferation and invasion and suppresses anti-tumor immune responses. Moreover, UPP1 was found to be an effective predictor of mutation patterns, drug response, immunotherapy effectiveness, and immune characteristics. Conclusions These findings highlight the power of combining diverse machine learning methods to identify valuable clinical markers involved in glioma pathogenesis. Identifying UPP1 as a tumor growth and immune escape driver may be a promising therapeutic target for this devastating disease.
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Affiliation(s)
- Zigui Chen
- Department of Neurosurgery, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China
| | - Chao Liu
- Department of Neurosurgery, Central Hospital of Zhuzhou, Zhuzhou, Hunan, China
| | - Chunyuan Zhang
- Department of Neurosurgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, China
- Guangxi Engineering Research Center for Biomaterials in Bone and Joint Degenerative Diseases, Baise, Guangxi, China
| | - Ying Xia
- Department of Neurosurgery, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China
| | - Jun Peng
- Department of Neurosurgery, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China
| | - Changfeng Miao
- Department of Neurosurgery Second Branche, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China
| | - Qisheng Luo
- Department of Neurosurgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, China
- Guangxi Engineering Research Center for Biomaterials in Bone and Joint Degenerative Diseases, Baise, Guangxi, China
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22
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Wang A, Zhang C, Wang Y, Diao P, Cheng J. Leveraging programmed cell death patterns to predict prognosis and therapeutic sensitivity in OSCC. Oral Dis 2024. [PMID: 39315471 DOI: 10.1111/odi.15139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 07/13/2024] [Accepted: 09/06/2024] [Indexed: 09/25/2024]
Abstract
OBJECTIVES Intricate associations between programmed cell death (PCD) and cancer development and treatment outcomes have been increasingly appreciated. Here, we integrated 12 PCD patterns to construct a novel biomarker, cell death index (CDI), for oral squamous cell carcinoma (OSCC) prognostication and therapeutic prediction. MATERIALS AND METHODS Univariate Cox regression, Kaplan-Meier survival, and LASSO analyses were performed to construct the CDI. A nomogram combining CDI and selected clinicopathological parameters was established by multivariate Cox regression. The associations between CDI and immune landscape and therapeutic sensitivity were estimated. Single-cell RNA-seq data of OSCC was used to infer CDI genes in selected cell types and determine their expression along cell differentiation trajectory. RESULTS Ten selected PCD genes derived a novel prognostic signature for OSCC. The predictive prognostic performance of CDI and nomogram was robust and superior across multiple independent patient cohorts. CDI was negatively associated with tumor-infiltrating immune cell abundance and immunotherapeutic outcomes. Moreover, scRNA-seq data reanalysis revealed that GSDMB, IL-1A, PRKAA2, and SFRP1 from this signature were primarily expressed in cancer cells and involved in cell differentiation. CONCLUSIONS Our findings established CDI as a novel powerful predictor for prognosis and therapeutic response for OSCC and suggested its potential involvement in cancer cell differentiation.
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Affiliation(s)
- An Wang
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chi Zhang
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuhan Wang
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Pengfei Diao
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jie Cheng
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
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Zeng L, Zhang L, Li L, Liao X, Yin C, Zhang L, Chen X, Sun J. RNA sequencing identifies lung cancer lineage and facilitates drug repositioning. PeerJ 2024; 12:e18159. [PMID: 39346064 PMCID: PMC11430167 DOI: 10.7717/peerj.18159] [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: 05/27/2024] [Accepted: 09/02/2024] [Indexed: 10/01/2024] Open
Abstract
Recent breakthrough therapies have improved survival rates in non-small cell lung cancer (NSCLC), but a paradigm for prospective confirmation is still lacking. Patientdatasets were mainly downloaded from TCGA, CPTAC and GEO. We conducted downstream analysis by collecting metagenes and generated 42-gene subtype classifiers to elucidate biological pathways. Subsequently, scRNA, eRNA, methylation, mutation, and copy number variation were depicted from a phenotype perspective. Enhancing the clinical translatability of molecular subtypes, preclinical models including CMAP, CCLE, and GDSC were utilized for drug repositioning. Importantly, we verified the presence of previously described three phenotypes including bronchioid, neuroendocrine, and squamoid. Poor prognosis was seen in squamoid and neuroendocrine clusters for treatment-naive and immunotherapy populations. The neuroendocrine cluster was dominated by STK11 mutations and 14q13.3 amplifications, whose related methylated loci are predictive of immunotherapy. And the greatest therapeutic potential lies in the bronchioid cluster. We further estimated the relative cell abundance of the tumor microenvironment (TME), specific cell types could be reflected among three clusters. Meanwhile, the higher portion of immune cell infiltration belonged to bronchioid and squamoid, not the neuroendocrine cluster. In drug repositioning, MEK inhibitors resisted bronchioid but were squamoid-sensitive. To conceptually validate compounds/targets, we employed RNA-seq and CCK-8/western blot assays. Our results indicated that dinaciclib and alvocidib exhibited similar activity and sensitivity in the neuroendocrine cluster. Also, a lineage factor named KLF5 recognized by inferred transcriptional factors activity could be suppressed by verteporfin.
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Affiliation(s)
- Longjin Zeng
- Department of Basic Medicine, Army Medical University, Chongqing, China
| | - Longyao Zhang
- Cancer Institute, Xinqiao Hospital, Chongqing, China
| | - Lingchen Li
- Cancer Institute, Xinqiao Hospital, Chongqing, China
| | - Xingyun Liao
- Affiliated Tumor Hospital, Department of Oncology, Chongqing, China
| | - Chenrui Yin
- Cancer Institute, Xinqiao Hospital, Chongqing, China
| | - Lincheng Zhang
- Department of Basic Medicine, Army Medical University, Chongqing, China
| | - Xiewan Chen
- Department of Basic Medicine, Army Medical University, Chongqing, China
| | - Jianguo Sun
- Cancer Institute, Xinqiao Hospital, Chongqing, China
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Xiao X, Qing L, Li Z, Ye F, Dong Y, Mi J, Tian J. Identification and validation of diagnostic and prognostic biomarkers in prostate cancer based on WGCNA. Discov Oncol 2024; 15:131. [PMID: 39304557 DOI: 10.1007/s12672-024-00983-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 04/15/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND Prostate cancer (PCa) represents a significant health challenge for men, and the advancement of the disease often results in a grave prognosis for patients. Therefore, the identification of biomarkers associated with the diagnosis and prognosis of PCa holds paramount importance in patient health management. METHODS The datasets pertaining to PCa were retrieved from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to investigate the modules specifically associated with the diagnosis of PCa. The hub genes were identified using the LASSO regression analysis. The expression levels of these hub genes were further validated by qRT-PCR experiments. Receiver operating characteristic (ROC) curves and nomograms were employed as evaluative measures for assessing the diagnostic value. RESULTS The blue module identified by WGCNA exhibited a strong association with PCa. Six hub genes (SLC14A1, COL4A6, MYOF, FLRT3, KRT15, and LAMB3) were identified by LASSO regression analysis. Further verification confirmed that these six genes were significantly downregulated in tumor tissues and cells. The six hub genes and the nomogram demonstrated substantial diagnostic value, with area under the curve (AUC) values ranging from 0.754 to 0.961. Moreover, patients with low expression levels of these six genes exhibited elevated T/N pathological stage and Gleason score, implying a more advanced disease state. Meanwhile, their progression-free survival (PFS) was observed to be potentially poorer. Finally, a significant association could be observed between the expression of these genes and the dysregulation of immune cells, along with drug sensitivity. CONCLUSIONS In summary, our study identified six hub genes, namely SLC14A1, COL4A6, MYOF, FLRT3, KRT15, and LAMB3, which can be utilized to establish a diagnostic model for PCa. The discovery may offer potential molecular targets for clinical diagnosis and treatment of PCa.
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Affiliation(s)
- Xi Xiao
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Liangliang Qing
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Zonglin Li
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Fuxiang Ye
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Yajia Dong
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Jun Mi
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
| | - Junqiang Tian
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
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Bai W. Protocol to develop a chemotherapy drug screening process by constructing a cancer prognostic model using public databases. STAR Protoc 2024; 5:103158. [PMID: 38943649 PMCID: PMC11261125 DOI: 10.1016/j.xpro.2024.103158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 05/07/2024] [Accepted: 06/06/2024] [Indexed: 07/01/2024] Open
Abstract
Drug resistance is currently the biggest challenge in cancer chemotherapy. Here, we present a protocol to develop a chemotherapy drug screening process by constructing a cancer prognostic model (PM) using public databases. We describe steps for downloading code and data, preparing the expression matrix and metadata for analysis, screening modeling genes, and constructing a PM. We then detail procedures for constructing predictive websites for cancer patients' survival based on their age, tumor stage, gene expression levels, and risk scores. For complete details on the use and execution of this protocol, please refer to Bai et al.1.
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Affiliation(s)
- Weiyu Bai
- Center for Life Sciences, School of Life Sciences, State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan University, Kunming 650091, China.
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Wang S, Zi H, Li M, Kong J, Fan C, Bai Y, Sun J, Wang T. Development and validation of a mitotic catastrophe-related genes prognostic model for breast cancer. PeerJ 2024; 12:e18075. [PMID: 39314848 PMCID: PMC11418815 DOI: 10.7717/peerj.18075] [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: 05/16/2024] [Accepted: 08/19/2024] [Indexed: 09/25/2024] Open
Abstract
Background Breast cancer has become the most common malignant tumor in women worldwide. Mitotic catastrophe (MC) is a way of cell death that plays an important role in the development of tumors. However, the exact relationship between MC-related genes (MCRGs) and the development of breast cancer is still unclear, and further research is needed to elucidate this complexity. Methods Transcriptome data and clinical data of breast cancer were downloaded from the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We identified differential expression of MCRGs by comparing tumor tissue with normal tissue. Subsequently, we used COX regression analysis and LASSO regression analysis to construct the prognosis risk model of MCRGs. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the predictive ability of prognostic model. Moreover, the clinical relevance, gene set enrichment analysis (GSEA), immune landscape, tumor mutation burden (TMB), and immunotherapy and drug sensitivity analysis between high-risk and low-risk groups were systematically investigated. Finally, we validated the expression levels of genes involved in constructing the prognostic model through real-time quantitative polymerase chain reaction (RT-qPCR) at the cellular and tissue levels. Results We identified 12 prognostic associated MCRGs, four of which were selected to construct prognostic model. The Kaplan-Meier analysis suggested that patients in the high-risk group had a shorter overall survival (OS). The Cox regression analysis and ROC analysis indicated that risk model had independent and excellent ability in predicting prognosis of breast cancer patients. Mechanistically, a remarkable difference was observed in clinical relevance, GSEA, immune landscape, TMB, immunotherapy response, and drug sensitivity analysis. RT-qPCR results showed that genes involved in constructing the prognostic model showed significant abnormal expressions and the expression change trends were consistent with the bioinformatics results. Conclusions We established a prognosis risk model based on four MCRGs that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for breast cancer.
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Affiliation(s)
- Shuai Wang
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Haoyi Zi
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Mengxuan Li
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Jing Kong
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Cong Fan
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Yujie Bai
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Jianing Sun
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
| | - Ting Wang
- The First Affiliated Hospital of Air Force Medical University, Department of Thyroid, Breast and Vascular Surgery, Xi’an, Shaanxi, China
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Ke Y, Ge W. Identification of prognostic biomarkers in neuroblastoma using WGCNA and multi-omics analysis. Discov Oncol 2024; 15:469. [PMID: 39302522 DOI: 10.1007/s12672-024-01334-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Accepted: 09/10/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND Neuroblastoma (NB) is one of the most frequent parenchymal tumors among children, with a high degree of heterogeneity and wide variation in clinical presentation. Despite significant therapeutic advances in recent years, long-term survival in high-risk patients remains low, emphasizing the urgent need to find new biomarkers and construct reliable prognostic models. METHODS In this study, data from neuroblastoma samples in the ArrayExpress database were utilized to identify key gene modules and pivotal genes associated with NB prognosis by weighted gene co-expression network analysis (WGCNA). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis was performed using the DAVID database. Based on these hub genes, survival prognosis models were constructed and validated on an independent validation set in the Gene Expression Omnibus (GEO) database. Differences in biological functions and immune microenvironments and the sensitivity to pharmacological and immunotherapeutic treatments of patients in the high- and low-risk groups were examined by gene set enrichment analysis (GSEA) and immune infiltration analysis. RESULTS WGCNA identified 14 gene modules and screened the module with the highest relevance to the International Neuroblastoma Staging System (INSS), containing 60 pivotal genes. GO and KEGG analyses demonstrated that these pivotal genes were mainly implicated in biological processes and signaling pathways including DNA replication, cell division, mitotic cell cycle, and cell cycle. Based on Lasso regression and COX regression analysis, a prognostic model containing DHFR, GMPS and E2F3 was constructed, and the RiskScore was significantly correlated with the 1-, 3- and 5-year survival of the patients. GSEA and immune infiltration analyses revealed significant differences in the levels of cell cycle-related pathways and immune cell infiltration between the high and low RiskScore groups. In particular, patients in the high-risk group are less likely to benefit from immunotherapy and may be better suited for treatment with drugs such as Oxaliplatin and Alpelisib. CONCLUSION This research systematically identified biomarkers related to NB prognosis and developed a reliable prognostic model applying WGCNA and multiple bioinformatics methods. The model has important application value in predicting patients' prognosis, evaluating drug sensitivity and immunotherapy effect, and provides new ideas and directions for precise treatment of neuroblastoma.
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Affiliation(s)
- Yuhan Ke
- Department of Pediatric Surgery, Affiliated Hospital of Nantong University, Nantong, 226001, China.
- Department of Pediatric Surgery, Medical School of Nantong University, Nantong, 226001, China.
| | - Wenliang Ge
- Department of Pediatric Surgery, Affiliated Hospital of Nantong University, Nantong, 226001, China.
- Department of Pediatric Surgery, Medical School of Nantong University, Nantong, 226001, China.
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Jiang Q, Yang X, Deng T, Yan J, Guo F, Mo L, An S, Huang Q. Comprehensive machine learning-based integration develops a novel prognostic model for glioblastoma. MOLECULAR THERAPY. ONCOLOGY 2024; 32:200838. [PMID: 39072291 PMCID: PMC11278295 DOI: 10.1016/j.omton.2024.200838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 04/09/2024] [Accepted: 06/14/2024] [Indexed: 07/30/2024]
Abstract
In this study, we developed a new prognostic model for glioblastoma (GBM) based on an integrated machine learning algorithm. We used univariate Cox regression analysis to identify prognostic genes by combining six GBM cohorts. Based on the prognostic genes, 10 machine learning algorithms were integrated into 117 algorithm combinations, and the artificial intelligence prognostic signature (AIPS) with the greatest average C-index was chosen. The AIPS was compared with 10 previously published models by univariate Cox analysis and the C-index. We compared the differences in prognosis, tumor immune microenvironment (TIME), and immunotherapy sensitivity between the high and low AIPS score groups. The AIPS based on the random survival forest algorithm with the highest average C-index (0.868) was selected. Compared with the previous 10 prognostic models, our AIPS has the highest C-index. The AIPS was closely linked to the clinical features of GBM. We discovered that patients in the low score group had improved prognoses, a more active TIME, and were more sensitive to immunotherapy. Finally, we verified the expression of several key genes by western blotting and immunohistochemistry. We identified an ideal prognostic signature for GBM, which might provide new insights into stratified treatment approaches for GBM patients.
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Affiliation(s)
- Qian Jiang
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Xiawei Yang
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Teng Deng
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Jun Yan
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Fangzhou Guo
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Ligen Mo
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Sanqi An
- Biosafety Level-3 Laboratory, Life Sciences Institute & Guangxi Collaborative Innovation Center for Biomedicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Qianrong Huang
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
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Sun W, Su Y, Zhang Z. Characterizing m6A modification factors and their interactions in colorectal cancer: implications for tumor subtypes and clinical outcomes. Discov Oncol 2024; 15:457. [PMID: 39292326 PMCID: PMC11411059 DOI: 10.1007/s12672-024-01298-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 09/02/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND The study aims to comprehensively combine colorectal cancer data cohorts in order to analyze the effects of various DNA methylation-coding genes on colorectal cancer patients. The annual incidence and mortality of colorectal cancer are very high, and there are no effective treatments for advanced colorectal cancer. DNA methylation is a method widely used to regulate epigenetics in the molecular mechanism study of tumors. METHOD Three single-cell cohorts GSE166555, GSE146771, and EMTAB8107, and five transcriptome cohorts GSE17536, GSE39582, GSE72970, and TCGA-CRC (TCGA-COAD and TCGA-READ) were applied in this study. 2 erasers (ALKBH5 and FTO), There are 7 writers (METTL3, METTL14, WTAP, VIRMA, RBM15, RBM15B, and ZC3H13) and 11 readers (YTHDC1, IGF2BP1, IGF2BP2, IGF2BP3, YTHDF1, YTHDF3, YTHDC2, and HNRNPA2B1, YTHDF2, HNRNPC and RBMX), a total of 20 M6A regulators, were used as the basis of the dataset in this study and were applied to the construction of molecular typing and prognostic models. Drugs that are differentially sensitive in methylation-regulated gene-related prognostic models were identified using the ConsensusClusterPlus package, which was also used to identify distinct methylation regulatory expression patterns in colorectal cancer and to model the relationship between tissue gene expression profiles and drug IC50 values. Finally, TISCH2 assessed which immune cells were significantly expressed with M6A scores. The immunosuppression of M6A methylation is spatially explained. RESULTS This study used data from 583 CRC patients in the TCGA-CRC cohort. Firstly, the mutation frequency and CNV variation frequency of 20 m6A modification-related factors were analyzed, and the corresponding histogram and heat map were drawn. The study next analyzed the expression variations between mutant and wild forms of the VIRMA gene and explored differences in the expression of these variables in tumor and normal tissues. In addition, the samples were divided into different subgroups by molecular clustering method based on m6A modification, and each subgroup's expression and clinicopathological characteristics were analyzed. Finally, we compared prognostic differences, tumor microenvironment (TME) characteristics, immune cell infiltration, and gene function enrichment among different subpopulations. We also developed a colorectal cancer m6A-associated gene signature and validated its prognostic effects across multiple cohorts. Finally, using single-cell RNA sequencing data, we confirmed that tumor cells show elevated expression of m6A-related gene signatures. DISCUSSION This study explored the mutation frequency, expression differences, interactions, molecular clustering, prognostic effect, and association with tumor characteristics of m6A modification-related factors in CRC and validated them at the single-cell level. These results clarify the association between m6A alteration and colorectal cancer (CRC) and offer important insights into the molecular recognition and management of cancer.
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Affiliation(s)
- Weidong Sun
- Department of Colorectal Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150000, China
| | - Yingchao Su
- Department of Neurology, Xinqiao Hospital, Army Medical University, No. 183 Xinqiao Road, Chongqing, 400037, China
| | - Zhiqiang Zhang
- Department of General Surgery, Xinqiao Hospital, Army Medical University, No. 183 Xinqiao Road, Chongqing, 400037, China.
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Deng Z, Liu J, Yu YV, Jin YN. Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma. Front Immunol 2024; 15:1451103. [PMID: 39355255 PMCID: PMC11442245 DOI: 10.3389/fimmu.2024.1451103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 08/27/2024] [Indexed: 10/03/2024] Open
Abstract
Background Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variability due to tumor heterogeneity necessitates robust biomarkers for predicting immunotherapy response. Methods We used weighted gene co-expression network analysis (WGCNA), consensus clustering, and 10 machine learning algorithms to develop the immunotherapy-related gene model (ITRGM) signature. Multi-omics analyses included bulk and single-cell RNA sequencing of melanoma patients, mouse bulk RNA sequencing, and pathology sections of melanoma patients. Results We identified 66 consensus immunotherapy prognostic genes (CITPGs) using WGCNA and differentially expressed genes (DEGs) from two melanoma cohorts. The CITPG-high group showed better prognosis and enriched immune activities. DEGs between CITPG-high and CITPG-low groups in the TCGA-SKCM cohort were analyzed in three additional melanoma cohorts using univariate Cox regression, resulting in 44 consensus genes. Using 101 machine learning algorithm combinations, we constructed the ITRGM signature based on seven model genes. The ITRGM outperformed 37 published signatures in predicting immunotherapy prognosis across the training cohort, three testing cohorts, and a meta-cohort. It effectively stratified patients into high-risk or low-risk groups for immunotherapy response. The low-risk group, with high levels of model genes, correlated with increased immune characteristics such as tumor mutation burden and immune cell infiltration, indicating immune-hot tumors with a better prognosis. The ITRGM's relationship with the tumor immune microenvironment was further validated in our experiments using pathology sections with GBP5, an important model gene, and CD8 IHC analysis. The ITRGM also predicted better immunotherapy response in eight cohorts, including urothelial carcinoma and stomach adenocarcinoma, indicating broad applicability. Conclusions The ITRGM signature is a stable and robust predictor for stratifying melanoma patients into 'immune-hot' and 'immune-cold' tumors, enhancing prognosis and response to immunotherapy.
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Affiliation(s)
- Zaidong Deng
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan
University, Wuhan University, Wuhan, China
| | - Jie Liu
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan
University, Wuhan University, Wuhan, China
| | - Yanxun V. Yu
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan
University, Wuhan University, Wuhan, China
- Frontier Science Center for Immunology and Metabolism, Wuhan University,
Wuhan, China
| | - Youngnam N. Jin
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan
University, Wuhan University, Wuhan, China
- Frontier Science Center for Immunology and Metabolism, Wuhan University,
Wuhan, China
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Duan L, Xia Y, Fan R, Shuai Y, Li C, Hou X. Prognostic aging gene-based score for colorectal cancer: unveiling links to drug resistance, mutation burden, and personalized treatment strategies. Discov Oncol 2024; 15:454. [PMID: 39287898 PMCID: PMC11408439 DOI: 10.1007/s12672-024-01350-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Accepted: 09/13/2024] [Indexed: 09/19/2024] Open
Abstract
OBJECTIVE Colorectal cancer (CRC) is characterized by high incidence and mortality rates worldwide. In this study, we present a novel aging-related gene-based risk scoring system (Aging score) as a predictive tool for CRC prognosis. METHOD We identified prognostic aging-related genes using univariate Cox regression analysis, revealing key biological processes in CRC progression. We then constructed a robust prognostic model using LASSO and multivariate Cox regression analyses, including four critical genes: CAV1, FOXM1, MAD2L1, and WT1. RESULT The Aging score demonstrated high prognostic performance across the training, testing, and entire TCGA-CRC datasets, proving its reliability. High-risk patients identified by the Aging score had significantly shorter overall survival times than low-risk patients, indicating its potential for patient stratification and personalized treatment. The Aging score remained an independent prognostic factor compared to age, gender, and tumor stage. Additionally, the score was linked to tumor mutation burden and microsatellite instability, indicators of immune checkpoint inhibitor response. High-risk patients also showed higher estimated IC50 values for common chemotherapeutic drugs, suggesting possible treatment resistance. CONCLUSION Our findings highlight the Aging score's potential to enhance clinical decision-making and pave the way for personalized CRC management.
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Affiliation(s)
- Ling Duan
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Yang Xia
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
- Department of Hematology, The First People's Hospital of Lanzhou, Lanzhou, Gansu, China
| | - Rui Fan
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Yuxi Shuai
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Chunmei Li
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Xiaoming Hou
- Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
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Meng K, Zhao Z, Gao Y, Wu K, Liu W, Wang X, Zheng Y, Zhao W, Wang B. The synergistic effects of anoikis-related genes and EMT-related genes in the prognostic prediction of Wilms tumor. Front Mol Biosci 2024; 11:1469775. [PMID: 39351154 PMCID: PMC11439783 DOI: 10.3389/fmolb.2024.1469775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 09/03/2024] [Indexed: 10/04/2024] Open
Abstract
Wilms tumor (WT) is the most common type of malignant abdominal tumor in children; it exhibits a high degree of malignancy, grow rapidly, and is prone to metastasis. This study aimed to construct a prognosis model based on anoikis-related genes (ARGs) and epithelial-mesenchymal transition (EMT)-related genes (ERGs) for WT patients; we assessed the characteristics of the tumor microenvironment and treatment efficacy, as well as identifying potential therapeutic targets. To this end, we downloaded transcriptome sequencing data and clinical data for WT and normal renal cortices and used R to construct and validate the prognostic model based on ARGs and ERGs. Additionally, we performed clinical feature analysis, nomogram construction, mutation analysis, drug sensitivity analysis, Connectivity Map (cMAP) analysis, functional enrichment analysis, and immune infiltration analysis. Finally, we screened the hub gene using the STRING database and validated it via experiments. In this way, we constructed a model with good accuracy and robustness, which was composed of seven anoikis- and EMT-related genes. Paclitaxel and mesna were selected as potential chemotherapeutic drugs and adjuvant chemotherapeutic drugs for the WT high-risk group by using the Genomics of Drug Sensitivity in Cancer (GDSC) and cMAP compound libraries, respectively. We proved the existence of a strong correlation between invasive immune cells and prognostic genes and risk scores. Next, we selected NTRK2 as the hub gene, and in vitro experiments confirmed that its inhibition can significantly inhibit the proliferation and migration of tumor cells and promote late apoptosis. In summary, we screened out the potential biomarkers and chemotherapeutic drugs that can improve the prognosis of patients with WT.
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Affiliation(s)
- Kexin Meng
- Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medical and Health Key Laboratory of Abdominal Medical Imaging, Jinan, China
| | - Zerui Zhao
- Department of Clinical Pharmacy, Clinical Trial Center, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan, China
- Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Shandong University, Jinan, China
| | - Yaqing Gao
- Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medical and Health Key Laboratory of Abdominal Medical Imaging, Jinan, China
| | - Keliang Wu
- Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Shandong University, Jinan, China
| | - Wei Liu
- Department of Pediatric Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xiaoqing Wang
- Department of Pediatric Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yi Zheng
- Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Shandong University, Jinan, China
| | - Wei Zhao
- Department of Clinical Pharmacy, Clinical Trial Center, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan, China
- Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Shandong University, Jinan, China
| | - Bei Wang
- Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medical and Health Key Laboratory of Abdominal Medical Imaging, Jinan, China
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Li M, Wang S, Huang H, Li L. Reliable estrogen-related prognostic signature for uterine corpus endometrial carcinoma. Comput Biol Chem 2024; 113:108216. [PMID: 39326337 DOI: 10.1016/j.compbiolchem.2024.108216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 09/04/2024] [Accepted: 09/15/2024] [Indexed: 09/28/2024]
Abstract
BACKGROUND Uterine corpus endometrial carcinoma (UCEC) is a predominant gynecological malignancy worldwide. Overdosed estrogen exposure has been widely known as a crucial risk factor for UCEC patients. The purpose of this work is to explore crucial estrogen-related genes (ERGs) in UCEC. METHODS UCEC scRNA-seq data, bulk RNA data, and ERGs were obtained from GEO, TCGA, and Molecular Signature Database, respectively. Differential expression analysis and cross analysis determined the candidate genes, and optimal genes in risk score were obtained after univariate Cox regression analysis, LASSO Cox regression analysis, and multivariate Cox regression analysis. The functional information was revealed by GO, KEGG, and GSVA enrichment analyses. CCK8 assay was used to detect the drug sensitivity. RESULTS After cross analysis of the differentially expressed genes and the 8734 ERGs, 86 differentially expressed ERGs were identified in UCEC, which were significantly enriched in some immune related pathways and microbiota related pathways. Of them, the most optimal 8 ERGs were obtained to build prognostic risk score, including GAL, PHGDH, SLC7A2, HNMT, CLU, AREG, MACC1, and HMGA1. The risk score could reliably predict patient prognosis, and high-risk patients had worse prognosis. Higher HMGA1 gene expression exhibited higher sensitivity to Osimertinib. CONCLUSIONS Predictive risk score based on 8 ERGs exhibited excellent prognostic value in UCEC patients, and high-risk patients had inferior survival. UCEC patients with distinct prognoses showed different tumor immune microenvironment.
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Affiliation(s)
- Mojuan Li
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 511500, China; Department of Obstetrics and Gynecology, the Sixth Affiliated Hospital, South China University of Technology, Foshan, Guangdong 528000, China
| | - Shuai Wang
- Department of Obstetrics and Gynecology, Guangdong Women and Children Hospital, Guangzhou, Guangdong 511500, China
| | - Hao Huang
- Department of Obstetrics and Gynecology, the Sixth Affiliated Hospital, South China University of Technology, Foshan, Guangdong 528000, China
| | - Li Li
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 511500, China; Department of Obstetrics and Gynecology, Guangdong Women and Children Hospital, Guangzhou, Guangdong 511500, China.
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Zhang H, Zhu H, Sheng Y, Cheng Z, Peng H. A novel prognostic model based on pyroptosis signature in AML. Heliyon 2024; 10:e36624. [PMID: 39263179 PMCID: PMC11387551 DOI: 10.1016/j.heliyon.2024.e36624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/17/2024] [Accepted: 08/20/2024] [Indexed: 09/13/2024] Open
Abstract
Acute myeloid leukemia (AML), a highly heterogeneous myeloid malignancy, remains a challenge in terms of proper risk stratification. In this study, we developed a novel pyroptosis prognostic model based on pyroptosis-related gene pairs, which exhibited excellent prognostic performance across multiple cohorts (N = 1506) and accurately predicted both adult and pediatric AML prognosis. Additionally, we integrated the pyroptosis risk model with other clinical risk factors to construct a highly operational nomogram. Moreover, our findings indicate a significant correlation between elevated pyroptosis risk scores and increased stemness of AML. Using CIBERSORT immune analysis, we found a decreased proportion of resting NK cells and activated mast cells in the high-risk group. Through analyzing the correlation between chemotherapy drug response sensitivity and risk scores, we found that AZD1332 and BPD-0008900 were extremely sensitive in the high-risk group.
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Affiliation(s)
- Huifang Zhang
- Department of Hematology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR China
| | - Hongkai Zhu
- Department of Hematology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR China
| | - Yue Sheng
- Department of Hematology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR China
| | - Zhao Cheng
- Department of Hematology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR China
| | - Hongling Peng
- Department of Hematology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR China
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Linazi G, Maimaiti A, Abulaiti Z, Shi H, Zhou Z, Aisa MY, Kang Y, Abulimiti A, Dilimulati X, Zhang T, Wusiman P, Wang Z, Abulaiti A. Prognostic value of anoikis-related genes revealed using multi-omics analysis and machine learning based on lower-grade glioma features and tumor immune microenvironment. Heliyon 2024; 10:e36989. [PMID: 39286119 PMCID: PMC11402926 DOI: 10.1016/j.heliyon.2024.e36989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 08/25/2024] [Accepted: 08/26/2024] [Indexed: 09/19/2024] Open
Abstract
Background The investigation explores the involvement of anoikis-related genes (ARGs) in lower-grade glioma (LGG), seeking to provide fresh insights into the disease's underlying mechanisms and to identify potential targets for therapy. Methods We applied unsupervised clustering techniques to categorize LGG patients into distinct molecular subtypes based on ARGs with prognostic significance. Additionally, various machine learning algorithms were employed to pinpoint genes most strongly correlated with patient outcomes, which were then used to develop and assess risk profiles. Results Our analysis identified two distinct molecular subtypes of LGG, each with significantly different prognoses. Patients in Cluster 2 had a median survival of 2.036 years, markedly shorter than the 7.994 years observed in Cluster 1 (P < 0.001). We also constructed a six-gene ARG signature that efficiently classified patients into two risk categories, showing median survival durations of 4.084 years for the high-risk group and 10.304 years for the low-risk group (P < 0.001). Significantly, the immune profiles, tumor mutation characteristics, and drug sensitivity varied greatly among these risk groups. The high-risk group was characterized by a "cold" tumor microenvironment (TME), a lower IDH1 mutation rate (61.7 % vs. 91.4 %), a higher TP53 mutation rate (53.7 % vs. 38.9 %), and greater sensitivity to targeted therapies such as QS11 and PF-562271. Furthermore, our nomogram, integrating risk scores with clinicopathological features, demonstrated strong predictive accuracy for clinical outcomes in LGG patients, with an AUC of 0.903 for the first year. The robustness of this prognostic model was further validated through internal cross-validation and across three external cohorts. Conclusions The evidence from our research suggests that ARGs could potentially serve as reliable indicators for evaluating immunotherapy effectiveness and forecasting clinical results in patients with LGG.
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Affiliation(s)
- Gu Linazi
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Aierpati Maimaiti
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Zulihuma Abulaiti
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Hui Shi
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Zexin Zhou
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Mizhati Yimiti Aisa
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Yali Kang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Ayguzaili Abulimiti
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Xierzhati Dilimulati
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Tiecheng Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Patiman Wusiman
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Zengliang Wang
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
| | - Aimitaji Abulaiti
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, China
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Deng R, Qin J, Wang L, Li H, Wen N, Qin K, Dong J, Wu J, Zhu D, Sun X. Energy metabolism-related GLUD1 contributes to favorable clinical outcomes of IDH-mutant glioma. BMC Neurol 2024; 24:344. [PMID: 39272024 PMCID: PMC11395857 DOI: 10.1186/s12883-024-03787-w] [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: 11/17/2023] [Accepted: 07/30/2024] [Indexed: 09/15/2024] Open
Abstract
BACKGROUND Glioma is the most common brain tumor. IDH mutations occur frequently in glioma, indicating a more favorable prognosis. We aimed to explore energy metabolism-related genes in glioma to promote the research and treatment. METHODS Datasets were obtained from TCGA and GEO databases. Candidate genes were screened by differential gene expression analysis, then functional enrichment analysis was conducted on the candidate genes. PPI was also carried out to help determine the target gene. GSEA and DO analysis were conducted in the different expression level groups of the target gene. Survival analysis and immune cell infiltrating analysis were performed as well. RESULTS We screened 34 candidate genes and selected GLUD1 as the target gene. All candidate genes were significantly enriched in 10 KEGG pathways and 330 GO terms. GLUD1 expression was higher in IDH-mutant samples than IDH-wildtype samples, and higher in normal samples than tumor samples. Low GLUD1 expression was related to poor prognosis according to survival analysis. Most types of immune cells were negatively related to GLUD1 expression, but monocytes and activated mast cells exhibited significantly positive correlation with GLUD1 expression. GLUD1 expression was significantly related to 119 drugs and 6 immune checkpoint genes. GLUD1 was able to serve as an independent prognostic indicator of IDH-mutant glioma. CONCLUSION In this study, we identified an energy metabolism-related gene GLUD1 potentially contributing to favorable clinical outcomes of IDH-mutant glioma. In glioma, GLUD1 related clinical outcomes and immune landscape were clearer, and more valuable information was provided for immunotherapy.
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Affiliation(s)
- Renzhi Deng
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Jianying Qin
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Lei Wang
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Haibin Li
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Ning Wen
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Ke Qin
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Jianhui Dong
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Jihua Wu
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Dandan Zhu
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China
| | - Xuyong Sun
- Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, No.166 Daxuedong Road, Nanning, Guangxi, 530007, P.R. China.
- Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, Guangxi, 530007, P.R. China.
- Guangxi Transplantation Medicine Research Center of Engineering Technology, Nanning, Guangxi, 530007, P.R. China.
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Guo Q, Qiu P, Pan K, Liang H, Liu Z, Lin J. Integrated machine learning algorithms identify KIF15 as a potential prognostic biomarker and correlated with stemness in triple-negative breast cancer. Sci Rep 2024; 14:21449. [PMID: 39271768 PMCID: PMC11399402 DOI: 10.1038/s41598-024-72406-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 09/06/2024] [Indexed: 09/15/2024] Open
Abstract
Cancer stem cells (CSCs) have the potential to self-renew and induce cancer, which may contribute to a poor prognosis by enabling metastasis, recurrence, and therapy resistance. Hence, this study was performed to identify the association between CSC-related genes and triple-negative breast cancer (TNBC) development. Stemness gene sets were downloaded from StemChecker. Based on the online databases, a consensus clustering algorithm was conducted for unsupervised classification of TNBC samples. The variations between subtypes were assessed with regard to prognosis, tumor immune microenvironment (TIME), and chemotherapeutic sensitivity. The stemness-related gene signature was established and random survival forest analysis was employed to identify the core gene for validation experiments and tumor sphere formation assays. 499 patients with TNBC were classified into three subgroups and the Cluster 1 had a better OS than others. After that, WGCNA study was performed to identify genes important for Cluster 1 subtype. Out of all 8 modules, the subtype of Cluster 1 and the yellow module with 103 genes demonstrated the largest positive association. After that, a four-gene stemness-related signature was established. Based on the yellow module, the 39 potential pivotal genes were subjected to the random forest survival analysis to find out the gene that was relatively important for OS. KIF15 was confirmed as the targeted gene by LASSO and random survival forest analyses. In vitro experiments, the downregulation of KIF15 promoted the stemness of TNBC cells. The expression levels of stem cell markers Nanog, SOX2, and OCT4 were found to be elevated in TNBC cell lines after KIF15 inhibition. A stemness-associated risk model was constructed to forecast the clinical outcomes of TNBC patients. The downregulation of KIF15 expression in a subpopulation of TNBC stem cells may promote stemness and possibly TNBC progression.
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Affiliation(s)
- Qiaonan Guo
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Pengjun Qiu
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Kelun Pan
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Huikai Liang
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Zundong Liu
- Stem Cell Laboratory, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
| | - Jianqing Lin
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
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Liu S, Jiang R, Wang X, Zhang Q, Li S, Sun X, Feng Y, Du F, Zheng P, Tian Y, Li Z, Liu S. Comprehensive identification of a disulfidptosis-associated long non-coding RNA signature to predict the prognosis and treatment options in ovarian cancer. Front Endocrinol (Lausanne) 2024; 15:1434705. [PMID: 39345881 PMCID: PMC11427372 DOI: 10.3389/fendo.2024.1434705] [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: 05/18/2024] [Accepted: 07/29/2024] [Indexed: 10/01/2024] Open
Abstract
Purpose Distinguished from cuproptosis and ferroptosis, disulfidptosis has been described as a newly discovered form of non-programmed cell death tightly associated with glucose metabolism. However, the prognostic profile of disulfidptosis-related lncRNAs (DRLRs) in ovarian cancer (OC) and their biological mechanisms need to be further elucidated. Materials and methods First, we downloaded the profiles of RNA transcriptome, clinical information for OC patients from the TCGA database. Generated from Cox regression analysis, prognostic lncRNAs were utilized to identify the risk signature by least absolute shrinkage and selection operator analysis. Then, we explored the intimate correlations between disulfidptosis and lncRNAs. What's more, we performed a series of systemic analyses to assess the robustness of the model and unravel its relationship with the immune microenvironment comprehensively. Results We identified two DRLR clusters, in which OC patients with low-risk scores exhibited a favorable prognosis, up-regulated immune cell infiltrations and enhanced sensitivity to immunotherapy. Furthermore, validation of the signature by clinical features and Cox analysis demonstrated remarkable consistency, suggesting the universal applicability of our model. It's worth noting that high-risk patients showed more positive responses to immune checkpoint inhibitors and potential chemotherapeutic drugs. Conclusion Our findings provided valuable insights into DRLRs in OC for the first time, which indicated an excellent clinical value in the selection of management strategies, spreading brilliant horizons into individualized therapy.
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Affiliation(s)
- Shouze Liu
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Rulan Jiang
- Department of Pain, Cangzhou Hospital of Integrated Traditional Chinese Medicine and Western Medicine (TCM-WM) Hebei, Cangzhou, Hebei, China
| | - Xinxin Wang
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Qianqian Zhang
- Department of Gynecology and Obstetrics, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Shumei Li
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Xiaoxue Sun
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Yajun Feng
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Feida Du
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Pengtao Zheng
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yanpeng Tian
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zhongkang Li
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Shikai Liu
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei, China
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Cao Y, Guan L, Yang L, Wei C. PANoptosis-related molecular clustering and prognostic signature associated with the immune landscape and therapy response in breast cancer. Medicine (Baltimore) 2024; 103:e39511. [PMID: 39287311 PMCID: PMC11404910 DOI: 10.1097/md.0000000000039511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/19/2024] Open
Abstract
Breast cancer (BC) remains one of the most pervasive and complex malignancies. PANoptosis represents a recently identified cellular mechanism leading to programmed cell death. However, the prognostic implications and influence on the immune microenvironment of BC pertaining to PANoptosis-related genes (PRGs) remain significantly understudied. We conducted differential expression analysis to identify prognostic-Related PRGs by the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Next, we identified the PANoptosis-related molecular subtype using the consensus clustering analysis, and constructed and validated the PANoptosis-related prognostic signature using LASSO and Cox regression analyses. ROC curves were employed to assess the performance of the signatures. Furthermore, drug sensitivity between low- and high-risk group were analysis. Finally, we conducted RT-qPCR to assess the gene expression levels involved in this signature. We categorized BC patients into 2 distinct molecular clusters based on PRGs and identified differentially expressed genes associated with prognosis. Subsequently, BC patients were then divided into 2 gene clusters. The identified PRGs molecular clusters and gene clusters demonstrated association with patient survival, immune system functions, and biological processes and pathways of BC. A prognostic signature comprising 5 genes was established, and BC patients were classified into low- and high-risk groups based on the risk scores. The ROC curves demonstrated that those in the low-risk category exhibited notably extended survival compared to the high-risk group. A nomogram model for patient survival was constructed based on the risk score in conjunction with other clinical features. High-risk group had higher tumor burden mutation, CSC index and lower StomalScore, ImmuneScore, and ESTIMATEScore. Subsequently, we established a correlation between the risk score and drug sensitivity among BC patients. Finally, qRT-PCR results showed that the expression of CXCL1, PIGR, and TNFRSF14 significantly decreased, while CXCL13 and NKAIN were significantly increased in BC tissues. We have developed a molecular clustering and prognostic signature based on PANoptosis to improve the prediction of BC prognosis. This discovery has the potential to not only assist in assessing overall patient prognosis but also to deepen our understanding of the underlying mechanisms of PANoptosis in BC pathogenesis.
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Affiliation(s)
- Yiming Cao
- Department of Breast Surgery, Guangxi Medical University Cancer Hospital, Nanning, P.R. China
- Department of Breast and Thyroid Surgery, Liuzhou People's Hospital, Liuzhou, P.R. China
| | - LinJing Guan
- Department of Abdomen Ultrasound, Nanning Sixth People's Hospital, Nanning, P.R. China
| | - Li Yang
- Department of Pathology, Liuzhou People's Hospital, Liuzhou, P.R. China
| | - Changyuan Wei
- Department of Breast Surgery, Guangxi Medical University Cancer Hospital, Nanning, P.R. China
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Jia R, Liang X, Tu J, Yang H. A scoring model for the expression of genes related to programmed cell death predicts immunotherapy response and prognosis in lung adenocarcinoma. Discov Oncol 2024; 15:435. [PMID: 39264392 PMCID: PMC11393378 DOI: 10.1007/s12672-024-01319-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 09/05/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) continues to be the leading cause of cancer death worldwide, driven by environmental factors like smoking and genetic predispositions. LUAD has a high mortality rate, and new biomarkers are urgently needed to improve treatment strategies and patient management. Programmed cell death (PCD) is involved in tumor progression and response to treatment. Therefore, there is a need for an extensive study of the role and functions of PCD-related genes (PCDRGs) in lung adenocarcinoma so as to understand the pathophysiologic features of lung adenocarcinoma. METHODS Based on TCGA and GEO databases, this research is aimed at screening differentially expressed PCD-related genes in lung adenocarcinoma. We conducted GO, and KEGG analysis to establish the link between these genes and biological processes. By applying various machine learning algorithms such as CoxBoost analysis, we developed PCD-related indices (PCDI) that were used to verify their ability to predict prognosis with the use of other datasets. This was done in addition to exploring the biological functions of PCD genes associated with lung adenocarcinoma by assessing the relationship between immune cell components of tumor microenvironment and PCD genes together with examining how they affect drug sensitivity. RESULTS The research presented in this article offers significant insights into LUAD. The authors identified 113 PCDRGs that were differentially expressed in LUAD. These genes are implicated in various biological functions, including High risk ing apoptosis, ferroptosis, and pathways specific to non-small cell lung cancer. Notably, the PCDI proved effective in distinguishing between High risk and Low risk LUAD patients, demonstrating a higher accuracy in prognosis prediction compared to traditional clinical indicators such as age and gender. This high prediction accuracy was validated in both test and validation cohorts. Additionally, these genes showed significant correlations with immune cell infiltration and drug sensitivity in LUAD patients. CONCLUSION We analysed the expression and function of PCDRGs in LUAD and revealed their correlation with patient survival, the immune microenvironment and drug sensitivity. The constructed PCDI model provides a scientific basis for the personalised treatment of lung adenocarcinoma, and future optimisation of treatment strategies based on these genes may improve patient clinical outcomes.
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Affiliation(s)
- Runan Jia
- Cancer Center, Lishui Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical College, Zhejiang University Lishui Hospital, Lishui Central Hospital, 289 Kuangcang Road, Lishui City, 323000, Zhejiang Province, China
| | - Xiaolong Liang
- Pharmacy Department, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, No.150 Ximen Street, Linhai City, Taizhou City, 317000, Zhejiang Province, China
| | - Jianfei Tu
- Cancer Center, Lishui Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical College, Zhejiang University Lishui Hospital, Lishui Central Hospital, 289 Kuangcang Road, Lishui City, 323000, Zhejiang Province, China.
| | - Hongyuan Yang
- Cancer Center, Lishui Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical College, Zhejiang University Lishui Hospital, Lishui Central Hospital, 289 Kuangcang Road, Lishui City, 323000, Zhejiang Province, China.
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Zhang H, Zhang X, Huang Z, Zhang H. Integrative genomics unveils basement membrane-related diagnostic markers and therapeutic targets in esophageal squamous cell carcinoma. Biol Direct 2024; 19:79. [PMID: 39256753 PMCID: PMC11389425 DOI: 10.1186/s13062-024-00529-3] [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: 07/24/2024] [Accepted: 09/04/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Esophageal squamous cell carcinoma (ESCC) is often diagnosed at advanced stages due to the inherent limitations of current screening methodologies. Central to evaluating tumor invasion and prognostic assessment in ESCC is the integrity of the basement membrane (BM). However, current research on the implications of BM-related genes (BMRGs) in diagnosing ESCC remains sparse. METHODS We performed a comprehensive analysis using single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, alongside gene expression profiles acquired from GEO and The Cancer Genome Atlas (TCGA) databases. This identified differentially expressed BMRGs in ESCC. Employing LASSO, RF, and SVM-RFE, we selected potential BM biomarkers and crafted a diagnostic nomogram for ESCC, validated by ROC curves and AUC values. We also explored immune infiltration and biological mechanisms through consensus clustering and GSVA, and utilized single cell trajectory analysis and GSCALite to study gene distributions and pathways. In vitro experiments further elucidated the role of these genes in ESCC carcinogenesis. RESULTS Here, we discovered that ESCC cell types exhibited markedly elevated BM-related scores. Our analysis pinpointed seven BM genes upregulated and linked to immune infiltration, showcasing unique gene expression profiles and varying immune cell densities across the BM-related subtypes. Furthermore, a robust positive correlation was observed between these genes expression and EMT activity. The knockdown of BGN significantly suppressed cell proliferation, migration, invasion, while also augmenting cell viability following chemotherapy drug treatment. CONCLUSION Our study identified seven key BMRGs (BGN, LAMB3, SPARC, MMP1, LUM, COL4A1, and NELL2) and established a diagnostic nomogram for ESCC. Of noteworthy significance is the discovery of BGN as a promising drug target, indicating a novel strategy for future clinical combination therapies in ESCC.
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Affiliation(s)
- Han Zhang
- Department of Central Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China.
| | - Xia Zhang
- Department of Central Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Zhenyu Huang
- Department of Central Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Hao Zhang
- Department of Geriatrics, Medical Center On Aging of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People's Republic of China.
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Feng J, Rouse CD, Coogan I, Byrd O, Nguyen E, Taylor L, Garcia S, Lee H, Berchuck A, Murphy SK, Huang Z. Regulation of Age-Related Lipid Metabolism in Ovarian Cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.06.611709. [PMID: 39314468 PMCID: PMC11418935 DOI: 10.1101/2024.09.06.611709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Although a lot of effort has been dedicated to ovarian cancer (OC) research, the mortality rate is still among the highest in female gynecologic malignancies. The effects of the aged tumor microenvironment are still being undermined despite age being the highest risk factor in ovarian cancer development and progression. In this study, we have conducted RNA sequencing and lipidomics analysis of gonadal adipose tissues from young and aged rat xenografts before and after ovarian cancer formation. We have found significantly higher tumor formation rates and volumes in aged OC xenograft rat models compared to their young counterparts (p<0.05), suggesting the aged adipose microenvironment (AME) is more susceptible to OC outgrowth. We have revealed significant shifts in the gene expression enrichment from groups of young vs. aged rats before tumor formation, groups of young vs. aged rats when the tumor formed, and groups of aged rats before and after tumor formation. We also observed shifts in the lipid components of the gonadal adipose tissues between young and aged rat xenografts when tumors were generated. Additionally, we found that the aged AME was associated with age-related changes in the immune cell composition, especially inflammation-related cells. The top hits showing the most differences between aged and young adipose tissues were eight genes including S100a8, S100a9, Il1rl1, Lcn2, C3, Hba-a1, Fcna, and Pnpla3, 22 lipids including multiple isoforms of free fatty acids (FFA) and triglyceride (TG), as well as four immune cells including neutrophil, myeloid dendritic cell, T cell CD4+ (non-regulatory), and mast cell activation. The functional correlation among S100a8, S100a9, neutrophil, and FFA (18:3) was also determined. Furthermore, FFA (18:3), which was shown to be downregulated in aged xenograft rats, was capable of inhibiting OC cell proliferation. In conclusion, our study suggested that aging promoted OC proliferation through changes in genes/pathways, lipid metabolism, and immune cells. Targeting the aging adipose microenvironment, particularly lipid metabolism reprogramming, holds promise as a therapeutic strategy for OC, which warrants further investigation. Significance Aging microenvironment of OC may be regulated by S100a8 and S100a9 secreted by adipocytes, preadipocytes, or neutrophils through affecting the lipid metabolism, such as FFA (18:3).
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Wang Z, Chen DN, Huang XY, Zhu JM, Lin F, You Q, Lin YZ, Cai H, Wei Y, Xue XY, Zheng QS, Xu N. Machine learning-based autophagy-related prognostic signature for personalized risk stratification and therapeutic approaches in bladder cancer. Int Immunopharmacol 2024; 138:112623. [PMID: 38991630 DOI: 10.1016/j.intimp.2024.112623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 06/21/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024]
Abstract
OBJECTIVE Bladder cancer (BCa) is a highly lethal urological malignancy characterized by its notable histological heterogeneity. Autophagy has swiftly emerged as a diagnostic and prognostic biomarker in diverse cancer types. Nonetheless, the currently accessible autophagy-related signature specific to BCa remains limited. METHODS A refined autophagy-related signature was developed through a 10-fold cross-validation framework, incorporating 101 combinations of machine learning algorithms. The performance of this signature in predicting prognosis and response to immunotherapy was thoroughly evaluated, along with an exploration of potential drug targets and compounds. In vitro and in vivo experiments were conducted to verify the regulatory mechanism of hub gene. RESULTS The autophagy-related prognostic signature (ARPS) has exhibited superior performance in predicting the prognosis of BCa compared to the majority of clinical features and other developed markers. Higher ARPS is associated with poorer prognosis and reduced sensitivity to immunotherapy. Four potential targets and five therapeutic agents were screened for patients in the high-ARPS group. In vitro and vivo experiments have confirmed that FKBP9 promotes the proliferation, invasion, and metastasis of BCa. CONCLUSIONS Overall, our study developed a valuable tool to optimize risk stratification and decision-making for BCa patients.
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Affiliation(s)
- Zhen Wang
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Dong-Ning Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Xu-Yun Huang
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Jun-Ming Zhu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Fei Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Qi You
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Yun-Zhi Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Hai Cai
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Yong Wei
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Xue-Yi Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
| | - Qing-Shui Zheng
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.
| | - Ning Xu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China; Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China.
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Sun Z, Liu H, Zhao Q, Li JH, Peng SF, Zhang Z, Yang JH, Fu Y. Immune-related cell death index and its application for hepatocellular carcinoma. NPJ Precis Oncol 2024; 8:194. [PMID: 39245753 PMCID: PMC11381516 DOI: 10.1038/s41698-024-00693-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 08/28/2024] [Indexed: 09/10/2024] Open
Abstract
Regulated cell death (RCD) plays a crucial role in the immune microenvironment, development, and progression of hepatocellular carcinoma (HCC). However, reliable immune-related cell death signatures have not been explored. In this study, we collected 12 RCD modes (e.g., apoptosis, ferroptosis, and cuproptosis), including 1078 regulators, to identify immune-related cell death genes based on HCC immune subgroups. Using a developed competitive machine learning framework, nine genes were screened to construct the immune-related cell death index (IRCDI), which is available for online application. Multi-omics data, along with clinical features, were analyzed to explore the HCC malignant heterogeneity. To validate the efficacy of this model, more than 18 independent cohorts, including survival and diverse treatment cohorts and datasets, were utilized. These findings were further validated using in-house samples and molecular biological experiments. Overall, the IRCDI may have a wide application in individual therapeutic decision-making and improving outcomes for HCC patients.
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Affiliation(s)
- Zhao Sun
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Hao Liu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Qian Zhao
- Clinical Systems Biology Key Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jie-Han Li
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - San-Fei Peng
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zhen Zhang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jing-Hua Yang
- Clinical Systems Biology Key Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
| | - Yang Fu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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Yang L, Wei Q, Chen X, Yang Y, Huang Q, Wang B, Ma X. Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis. Diagn Pathol 2024; 19:120. [PMID: 39237939 PMCID: PMC11378624 DOI: 10.1186/s13000-024-01493-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 05/06/2024] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND Clear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood. METHOD Bulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The 'oncoPredict' algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2'-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients. RESULT Two machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ). CONCLUSION Our study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.
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Affiliation(s)
- Luojia Yang
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Qin Wei
- The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, China
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200125, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200125, China
| | - Xinran Chen
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Yang Yang
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Qingbo Huang
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Baojun Wang
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Xin Ma
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
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Cheng G, Xu J, Wang H, Chen J, Huang L, Qian ZR, Fan Y. mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence. Front Genet 2024; 15:1430565. [PMID: 39296545 PMCID: PMC11408181 DOI: 10.3389/fgene.2024.1430565] [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: 05/10/2024] [Accepted: 08/22/2024] [Indexed: 09/21/2024] Open
Abstract
Background This research seeks to formulate a prognostic model for forecasting prostate cancer recurrence by examining the interaction between mitochondrial function and programmed cell death (PCD). Methods The research involved analyzing four gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) using univariate Cox regression. These analyses identified genes linked with mitochondrial function and PCD that correlate with recurrence prognosis. Various machine learning algorithms were then employed to construct an optimal predictive model. Results A key outcome was the creation of a mitochondrial-related programmed cell death index (mtPCDI), which effectively predicts the prognosis of prostate cancer patients. It was observed that individuals with lower mtPCDI exhibited higher immune activity, correlating with better recurrence outcomes. Conclusion The study demonstrates that mtPCDI can be used for personalized risk assessment and therapeutic decision-making, highlighting its clinical significance and providing insights into the biological processes affecting prostate cancer recurrence.
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Affiliation(s)
- Guoliang Cheng
- Department of Urology Surgery, The Fourth People's Hospital of Jinan, Jinan, Shandong, China
| | - Junrong Xu
- Department of Urology Surgery, The Fourth People's Hospital of Jinan, Jinan, Shandong, China
| | - Honghua Wang
- Department of Urology Surgery, The Fourth People's Hospital of Jinan, Jinan, Shandong, China
| | - Jingzhao Chen
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Liwei Huang
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Zhi Rong Qian
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Yong Fan
- Department of Urology Surgery, The Fourth People's Hospital of Jinan, Jinan, Shandong, China
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Xie D, Han Z, Wang Y, Shi H, Wu X, Wu J, Dai Y. Integrative analysis of bulk and single-cell RNA sequencing reveals sphingolipid metabolism and immune landscape in clear cell renal cell carcinoma. ENVIRONMENTAL TOXICOLOGY 2024. [PMID: 39230203 DOI: 10.1002/tox.24319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/12/2024] [Accepted: 04/22/2024] [Indexed: 09/05/2024]
Abstract
Clear cell renal cell carcinoma (ccRCC) is characterized by its aggressive behavior and complex molecular heterogeneity, posing significant challenges for treatment and prognostication. This study offers a comprehensive analysis of ccRCC by leveraging both bulk and single-cell RNA sequencing data, with a specific aim to unravel the complexities of sphingolipid metabolism and the intricate dynamics within the tumor microenvironment (TME). By examining ccRCC samples sourced from public databases, our investigation delves deep into the genetic and transcriptomic landscape of this cancer type. Employing advanced analytical techniques, we have identified pivotal patterns in gene expression and cellular heterogeneity, with a special focus on the roles and interactions of various immune cells within the TME. Significantly, our research has unearthed insights into the dynamics of sphingolipid metabolism in ccRCC, shedding light on its potential implications for tumor progression and strategies for immune evasion. A novel aspect of this study is the development of a risk score model designed to enhance prognostic predictions for ccRCC patients, which is currently pending external validation to ascertain its clinical utility. Despite its contributions, the study is mindful of its limitations, including a reliance on observational data from public sources and a primary focus on RNA sequencing data, which may constrain the depth and generalizability of the findings. The study does not encompass critical aspects, such as protein expression, posttranslational modifications, and comprehensive metabolic profiles. Moreover, its retrospective design underscores the necessity for future prospective studies to solidify these preliminary conclusions. Our findings illuminate the intricate interplay between genetic alterations, sphingolipid metabolism, and immune responses in ccRCC. This research not only enhances our understanding of the molecular foundations of ccRCC but also paves the way for the development of targeted therapies and personalized treatment modalities. The study underlines the importance of cautious interpretation of results and champions ongoing research using diverse methodologies to thoroughly comprehend and effectively combat this formidable cancer type.
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Affiliation(s)
- Dongdong Xie
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China
| | - Zhitao Han
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China
| | - Yu Wang
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China
| | - Haoyu Shi
- Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xiang Wu
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China
| | - Jiaqing Wu
- Department of Kidney Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Yingbo Dai
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China
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Wei Z, Liu C, Liang J, Zhou X, Xue K, Wang K, Zhang X. Characterization of Mitoribosomal Small Subunit unit genes related immune and pharmacogenomic landscapes in renal cell carcinoma. IUBMB Life 2024; 76:647-665. [PMID: 38551358 DOI: 10.1002/iub.2818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 02/23/2024] [Indexed: 08/31/2024]
Abstract
Mitoribosomes are essential for the production of biological energy. The Human Mitoribosomal Small Subunit unit (MRPS) family, responsible for encoding mitochondrial ribosomal small subunits, is actively engaged in protein synthesis within the mitochondria. Intriguingly, MRPS family genes appear to play a role in cancer. A multistep process was employed to establish a risk model associated with MRPS genes, aiming to delineate the immune and pharmacogenomic landscapes in clear cell renal cell carcinoma (ccRCC). MRPScores were computed for individual patients to assess their responsiveness to various treatment modalities and their susceptibility to different therapeutic targets and drugs. While MRPS family genes have been implicated in various cancers as oncogenes, our findings reveal a contrasting tumor suppressor role for MRPS genes in ccRCC. Utilizing an MRPS-related risk model, we observed its excellent prognostic capability in predicting survival outcomes for ccRCC patients. Remarkably, the subgroup with high MRPS-related scores (MRPScore) displayed poorer prognosis but exhibited a more robust response to immunotherapy. Through in silico screening of 2183 drug targets and 1646 compounds, we identified two targets (RRM2 and OPRD1) and eight agents (AZ960, carmustine, lasalocid, SGI-1776, AZD8055_1059, BPD.00008900_1998, MK.8776_2046, and XAV939_1268) with potential therapeutic implications for high-MRPScore patients. Our study represents the pioneering effort in proposing that molecular classification, diagnosis, and treatment strategies can be formulated based on MRPScores. Indeed, a high MRPScore profile appears to elevate the risk of tumor progression and mortality, potentially through its influence on immune regulation. This suggests that the MRPS-related risk model holds promise as a prognostic predictor and may offer novel insights into personalized therapeutic strategies.
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Affiliation(s)
- Zhihao Wei
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chenchen Liu
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaqian Liang
- Department of Urology, Wuhan No.1 Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuan Zhou
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kaming Xue
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Keshan Wang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Zhang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Li C, Hu J, Jiang X, Tan H, Mao Y. Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma. Clin Transl Oncol 2024; 26:2274-2295. [PMID: 38563847 DOI: 10.1007/s12094-024-03439-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: 01/23/2024] [Accepted: 03/01/2024] [Indexed: 04/04/2024]
Abstract
OBJECTIVES Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated. METHODS Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed an immune-derived multiple programmed cell death index (MPCDI) based on machine learning methods. RESULTS Using the median MPCDI scores, we categorized the LUAD patients into two groups: low-MPCDI and high-MPCDI. Our analysis of the TCGA-LUAD training cohort and three external GEO cohorts (GSE37745, GSE30219, and GSE68465) revealed that patients with high-MPCDI experienced a more unfavorable prognosis, whereas those with low-MPCDI had a better prognosis. Furthermore, the results of both univariate and multivariate Cox regression analyses further confirmed that MPCDI serves as a novel independent risk factor. By combining clinical characteristics with the MPCDI, we constructed a nomogram that provides an accurate and reliable quantitative tool for personalized clinical management of LUAD patients. The findings obtained from the analysis of C-index and the decision curve revealed that the nomogram outperformed various clinical variables in terms of net clinical benefit. Encouragingly, the low-MPCDI patients are more sensitive to commonly used chemotherapy drugs, which suggests that MPCDI scores have a guiding role in chemotherapy for LUAD patients. CONCLUSION Therefore, MPCDI can be used as a novel clinical diagnostic classifier, providing valuable insights into the clinical management and clinical decision-making for LUAD patients.
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Affiliation(s)
- Chunhong Li
- Central Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
- Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
| | - Jiahua Hu
- Central Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China
- Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Xiling Jiang
- School of Medical Laboratory Medicine, Guilin Medical University, Guilin, 541004, Guangxi, China
| | - Haiyin Tan
- School of Medical Laboratory Medicine, Guilin Medical University, Guilin, 541004, Guangxi, China
| | - Yiming Mao
- Department of Thoracic Surgery, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, China.
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50
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Jézéquel P, Lasla H, Gouraud W, Basseville A, Michel B, Frenel JS, Juin PP, Ben Azzouz F, Campone M. Mesenchymal-like immune-altered is the fourth robust triple-negative breast cancer molecular subtype. Breast Cancer 2024; 31:825-840. [PMID: 38777987 DOI: 10.1007/s12282-024-01597-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 05/16/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Robust molecular subtyping of triple-negative breast cancer (TNBC) is a prerequisite for the success of precision medicine. Today, there is a clear consensus on three TNBC molecular subtypes: luminal androgen receptor (LAR), basal-like immune-activated (BLIA), and basal-like immune-suppressed (BLIS). However, the debate about the robustness of other subtypes is still open. METHODS An unprecedented number (n = 1942) of TNBC patient data was collected. Microarray- and RNAseq-based cohorts were independently investigated. Unsupervised analyses were conducted using k-means consensus clustering. Clusters of patients were then functionally annotated using different approaches. Prediction of response to chemotherapy and targeted therapies, immune checkpoint blockade, and radiotherapy were also screened for each TNBC subtype. RESULTS Four TNBC subtypes were identified in the cohort: LAR (19.36%); mesenchymal stem-like (MSL/MES) (17.35%); BLIA (31.06%); and BLIS (32.23%). Regarding the MSL/MES subtype, we suggest renaming it to mesenchymal-like immune-altered (MLIA) to emphasize its specific histological background and nature of immune response. Treatment response prediction results show, among other things, that despite immune activation, immune checkpoint blockade is probably less or completely ineffective in MLIA, possibly caused by mesenchymal background and/or an enrichment in dysfunctional cytotoxic T lymphocytes. TNBC subtyping results were included in the bc-GenExMiner v5.0 webtool ( http://bcgenex.ico.unicancer.fr ). CONCLUSION The mesenchymal TNBC subtype is characterized by an exhausted and altered immune response, and resistance to immune checkpoint inhibitors. Consensus for molecular classification of TNBC subtyping and prediction of cancer treatment responses helps usher in the era of precision medicine for TNBC patients.
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Affiliation(s)
- Pascal Jézéquel
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France.
- Nantes Université, Univ Angers, INSERM, CNRS, CRCI2NA, 44000, Nantes, France.
- Équipe Labellisée LIGUE Contre Le Cancer CRCI2NA, 44000, Nantes, France.
| | - Hamza Lasla
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France
| | - Wilfried Gouraud
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France
| | - Agnès Basseville
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France
| | - Bertrand Michel
- Nantes Université, École Centrale Nantes, CNRS, Laboratoire de Mathématiques Jean Leray, LMJL, UMR 6629, 44000, Nantes, France
| | - Jean-Sébastien Frenel
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France
- Nantes Université, Univ Angers, INSERM, CNRS, CRCI2NA, 44000, Nantes, France
- Équipe Labellisée LIGUE Contre Le Cancer CRCI2NA, 44000, Nantes, France
| | - Philippe P Juin
- Nantes Université, Univ Angers, INSERM, CNRS, CRCI2NA, 44000, Nantes, France
- Équipe Labellisée LIGUE Contre Le Cancer CRCI2NA, 44000, Nantes, France
| | | | - Mario Campone
- Institut de Cancérologie de l'Ouest, 44805, Saint Herblain, France
- Nantes Université, Univ Angers, INSERM, CNRS, CRCI2NA, 44000, Nantes, France
- Équipe Labellisée LIGUE Contre Le Cancer CRCI2NA, 44000, Nantes, France
- Université d'Angers, 49000, Angers, France
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