Identification of a novel immune checkpoint-related gene signature predicts prognosis and immunotherapy in breast cancer and experiment verification

Breast cancer (BRCA) is one of the pivotal causes of female death worldwide. And the morbidity and mortality of breast cancer have increased rapidly. Immune checkpoints are important to maintain immune tolerance and are regarded as important therapeutic targets. However, research for BRCA were limited to single immune checkpoint-related gene (ICG) and few studies have systematically explored expression profile of Immune checkpoint-related genes or attempted to construct a prognostic gene risk model based on immune checkpoint-related genes. We identified immune checkpoint-related differentially expressed genes (DEGs) in BRCA and normal breast tissues from TCGA database. A 7-gene signature was created by utilizing the univariate Cox regression model with least absolute shrinkage and selection operator (LASSO) Cox regression method. In addition, we conducted a nomogram to predict the prognostic significance. This tool enables quantitative prediction of patient prognosis, serving as a valuable reference for clinical decision-making, thereby improving patient outcomes. Relationships between our risk model and clinical indicators, TME (Tumor Microenvironment), immune cell infiltration, immune response and drug susceptibility were investigated. A set of in vitro cell assays was conducted to decipher the relationship between MAP2K6 and proliferation, invasion, migration, colony formation and apoptosis rate of breast cancer cells. As a result, we established a prognostic model composed of seven ICGs in BRCA. Based on the median risk score, BRCA patients were equally assigned into two groups of high- and low-risk. High-risk BRCA patients have poorer OS (overall survival) than low-risk patients. In addition, there were remarkable differences between these two groups in clinicopathological features, TME, immune cell infiltration, immune response and drug susceptibility. The results of GO and KEGG analyses indicated that DEGs between the high- and low-risk groups were involved in immune-related biological processes and pathways. GSEA analysis also showed that a number of immune-related pathways were notably enriched in the low-risk group. Finally, results of cell-based assays indicated that MAP2K6 may play a pivotal role in the initiation and progression of breast cancer as a tumor suppressor gene. In conclusion, we created a novel ICG signature that has the potential to predict the survival and drug sensitivity of BRCA patients. Furthermore, this study indicated that MAP2K6 may serve as a novel target for BRCA therapy.

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Publication Details

Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82266-1
Citations
4
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
1.13
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article

Identification of a novel immune checkpoint-related gene signature predicts prognosis and immunotherapy in breast cancer and experiment verification

Shenchao Guo, Dai Yong-ping, Chen Dai, Jinqiu Wang et al.
4 citations
Scientific Reports
Cancer Immunotherapy and Biomarkers
1.13
article

Identification of a novel immune checkpoint-related gene signature predicts prognosis and immunotherapy in breast cancer and experiment verification

Shenchao Guo, Dai Yong-ping, Chen Dai, Jinqiu Wang, Yu Guo, Yin Ke, Chunxu Zhang, Yangyang Guo
article en
4 citations

Abstract

Breast cancer (BRCA) is one of the pivotal causes of female death worldwide. And the morbidity and mortality of breast cancer have increased rapidly. Immune checkpoints are important to maintain immune tolerance and are regarded as important therapeutic targets. However, research for BRCA were limited to single immune checkpoint-related gene (ICG) and few studies have systematically explored expression profile of Immune checkpoint-related genes or attempted to construct a prognostic gene risk model based on immune checkpoint-related genes. We identified immune checkpoint-related differentially expressed genes (DEGs) in BRCA and normal breast tissues from TCGA database. A 7-gene signature was created by utilizing the univariate Cox regression model with least absolute shrinkage and selection operator (LASSO) Cox regression method. In addition, we conducted a nomogram to predict the prognostic significance. This tool enables quantitative prediction of patient prognosis, serving as a valuable reference for clinical decision-making, thereby improving patient outcomes. Relationships between our risk model and clinical indicators, TME (Tumor Microenvironment), immune cell infiltration, immune response and drug susceptibility were investigated. A set of in vitro cell assays was conducted to decipher the relationship between MAP2K6 and proliferation, invasion, migration, colony formation and apoptosis rate of breast cancer cells. As a result, we established a prognostic model composed of seven ICGs in BRCA. Based on the median risk score, BRCA patients were equally assigned into two groups of high- and low-risk. High-risk BRCA patients have poorer OS (overall survival) than low-risk patients. In addition, there were remarkable differences between these two groups in clinicopathological features, TME, immune cell infiltration, immune response and drug susceptibility. The results of GO and KEGG analyses indicated that DEGs between the high- and low-risk groups were involved in immune-related biological processes and pathways. GSEA analysis also showed that a number of immune-related pathways were notably enriched in the low-risk group. Finally, results of cell-based assays indicated that MAP2K6 may play a pivotal role in the initiation and progression of breast cancer as a tumor suppressor gene. In conclusion, we created a novel ICG signature that has the potential to predict the survival and drug sensitivity of BRCA patients. Furthermore, this study indicated that MAP2K6 may serve as a novel target for BRCA therapy.

Scientific ReportsVol. 14(1)
Ningbo University (CN), Sun Yat-sen University (CN), The Seventh Affiliated Hospital of Sun Yat-sen University (CN), Ningbo First Hospital (CN)
Good health and well-being
Openalex Percentile: Top 17%
Cancer Immunotherapy and Biomarkers
1.13
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