{"title":"Regulatory T cell-associated gene signature correlates with prognostic risk and immune infiltration in patients with breast cancer.","authors":"Jie Wu, Gaiping Zhao, Yan Cai","doi":"10.21037/tcr-24-1118","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Regulatory T cells (Tregs) play a pivotal role in the development, prognosis, and treatment of breast cancer. This study aimed to develop a Treg-associated gene signature that contributes to predict prognosis and therapy benefits in breast cancer.</p><p><strong>Methods: </strong>Treg-associated genes were screened based on single-cell RNA-sequencing (RNA-seq) in TISCH2 database and the bulk RNA-seq in The Cancer Genome Atlas (TCGA) database. Treg-associated gene signature was identified via survival analysis, univariate cox, least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses. Immune status was assessed using single-sample gene set enrichment analysis (ssGSEA) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithms. Drug sensitivity was estimated using pRRophetic. Gene set enrichment analysis (GSEA) was conducted to explore the changed pathways.</p><p><strong>Results: </strong>A total of 169 genes were identified as Treg-associated genes, and close interactions existed among these genes. Kaplan-Meier (KM) survival and univariate cox revealed 29 prognostic genes (all P<0.05), and finally a six-gene prognostic signature including <i>TBC1D4</i>, <i>PMAIP1</i>, <i>IFNG</i>, <i>LEF1</i>, <i>MZB1</i> and <i>EZR</i> was identified by LASSO and multivariable Cox. Based on this signature, patients in high-risk group exhibited a worse survival probability than those in low-risk group in the TCGA training dataset (P<0.001). Additionally, this signature showed a moderate predictive power for 1-, 3- and 5-year survival for breast cancer patients in both training dataset [area under the curve (AUC) =0.705, 0.678 and 0.668, respectively]. Similar predictive power for 1-, 3- and 5-year survival was also observed in validation datasets. Risk scores significantly differed between subgroups divided by clinicopathologic features, especially by molecular subtypes. Patients in high- and low-risk groups showed significant differences on infiltration abundance of multiple types of immune cells (such as, activated B cells/CD8+ T cells/CD4+ T cells), immune and stromal scores (all P<0.05). Moreover, sensitivity to 83 chemotherapeutic drugs such as lapatinib, methotrexate, and gefitinib were significantly differed between the two risk groups (all P<0.001).</p><p><strong>Conclusions: </strong>This is the first to develop a Treg-associated gene signature for breast cancer, which could predict prognosis of patients and help to identify patients who might be benefit from immunotherapy and/or chemotherapy.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 12","pages":"6766-6781"},"PeriodicalIF":1.5000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729763/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-24-1118","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/27 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Regulatory T cells (Tregs) play a pivotal role in the development, prognosis, and treatment of breast cancer. This study aimed to develop a Treg-associated gene signature that contributes to predict prognosis and therapy benefits in breast cancer.
Methods: Treg-associated genes were screened based on single-cell RNA-sequencing (RNA-seq) in TISCH2 database and the bulk RNA-seq in The Cancer Genome Atlas (TCGA) database. Treg-associated gene signature was identified via survival analysis, univariate cox, least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses. Immune status was assessed using single-sample gene set enrichment analysis (ssGSEA) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithms. Drug sensitivity was estimated using pRRophetic. Gene set enrichment analysis (GSEA) was conducted to explore the changed pathways.
Results: A total of 169 genes were identified as Treg-associated genes, and close interactions existed among these genes. Kaplan-Meier (KM) survival and univariate cox revealed 29 prognostic genes (all P<0.05), and finally a six-gene prognostic signature including TBC1D4, PMAIP1, IFNG, LEF1, MZB1 and EZR was identified by LASSO and multivariable Cox. Based on this signature, patients in high-risk group exhibited a worse survival probability than those in low-risk group in the TCGA training dataset (P<0.001). Additionally, this signature showed a moderate predictive power for 1-, 3- and 5-year survival for breast cancer patients in both training dataset [area under the curve (AUC) =0.705, 0.678 and 0.668, respectively]. Similar predictive power for 1-, 3- and 5-year survival was also observed in validation datasets. Risk scores significantly differed between subgroups divided by clinicopathologic features, especially by molecular subtypes. Patients in high- and low-risk groups showed significant differences on infiltration abundance of multiple types of immune cells (such as, activated B cells/CD8+ T cells/CD4+ T cells), immune and stromal scores (all P<0.05). Moreover, sensitivity to 83 chemotherapeutic drugs such as lapatinib, methotrexate, and gefitinib were significantly differed between the two risk groups (all P<0.001).
Conclusions: This is the first to develop a Treg-associated gene signature for breast cancer, which could predict prognosis of patients and help to identify patients who might be benefit from immunotherapy and/or chemotherapy.
期刊介绍:
Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.