{"title":"Characterization of 5-inflammatory-gene signature to affect the immune status and predict prognosis in breast cancer.","authors":"Hongyan Zang, Gaofeng Ni, Liguo Gong","doi":"10.5114/ceji.2022.121046","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Breast cancer (BC) is associated with an inflammatory microenvironment. In BC, epidemiological evidence suggests that inflammation is associated with a poor prognosis. However, approaches to determine the extent of inflammation in the tumor microenvironment remain unclear.</p><p><strong>Material and methods: </strong>We downloaded the expression profiles and corresponding clinicopathological information of 1050 BC tissues and 59 cases of normal breast tissue from The Cancer Genome Atlas (TCGA) dataset. Similarly, data of 1050 BC tissues were downloaded from Gene Expression Omnibus (GEO) and 200 inflammation-related genes were downloaded from the MSigDB database. We developed an inflammatory risk model to reflect the immune microenvironment in BC.</p><p><strong>Results: </strong>Multivariate Cox analysis showed that the risk score was an independent predictor of overall survival (OS). Inflammatory signature was significantly associated with clinical and molecular features and could serve as an independent prognostic factor for BC patients. Furthermore, most immune cells were significantly less infiltrated in the high-risk group than in the low-risk group. There was a significant difference in survival time between the group with a high and low tumor mutational burden (TMB) score, and the survival time of the patients with a low TMB was significantly higher than that of the high-risk group. The risk scores were significantly lower in patients who responded to immunotherapy (complete response/partial response - CR/PR) than in patients who did not respond to immunotherapy (stable disease/progressive disease - SD/PD).</p><p><strong>Conclusions: </strong>We developed and validated an inflammatory risk model, which served as an independent prognostic indicator and reflected immune response intensity in the BC microenvironment.</p>","PeriodicalId":9694,"journal":{"name":"Central European Journal of Immunology","volume":"47 3","pages":"218-233"},"PeriodicalIF":1.5000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/6e/86/CEJI-47-48153.PMC9896988.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central European Journal of Immunology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5114/ceji.2022.121046","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Breast cancer (BC) is associated with an inflammatory microenvironment. In BC, epidemiological evidence suggests that inflammation is associated with a poor prognosis. However, approaches to determine the extent of inflammation in the tumor microenvironment remain unclear.
Material and methods: We downloaded the expression profiles and corresponding clinicopathological information of 1050 BC tissues and 59 cases of normal breast tissue from The Cancer Genome Atlas (TCGA) dataset. Similarly, data of 1050 BC tissues were downloaded from Gene Expression Omnibus (GEO) and 200 inflammation-related genes were downloaded from the MSigDB database. We developed an inflammatory risk model to reflect the immune microenvironment in BC.
Results: Multivariate Cox analysis showed that the risk score was an independent predictor of overall survival (OS). Inflammatory signature was significantly associated with clinical and molecular features and could serve as an independent prognostic factor for BC patients. Furthermore, most immune cells were significantly less infiltrated in the high-risk group than in the low-risk group. There was a significant difference in survival time between the group with a high and low tumor mutational burden (TMB) score, and the survival time of the patients with a low TMB was significantly higher than that of the high-risk group. The risk scores were significantly lower in patients who responded to immunotherapy (complete response/partial response - CR/PR) than in patients who did not respond to immunotherapy (stable disease/progressive disease - SD/PD).
Conclusions: We developed and validated an inflammatory risk model, which served as an independent prognostic indicator and reflected immune response intensity in the BC microenvironment.