A novel twelve-gene signature to predict neoadjuvant chemotherapy response and prognosis in breast cancer

乳腺癌 肿瘤科 医学 内科学 化疗 比例危险模型 癌症 单变量 多元分析 弗雷明翰风险评分 多元统计 疾病 机器学习 计算机科学
作者
Jin Wu,Yuan Tian,Wei Liu,Hong Zheng,Yuanyin Xi,Yuzhao Yan,Ying Hu,Bin Liao,Minghao Wang,Peng Tang
出处
期刊:Frontiers in Immunology [Frontiers Media SA]
卷期号:13
标识
DOI:10.3389/fimmu.2022.1035667
摘要

Accurate evaluation of the response to neoadjuvant chemotherapy (NAC) provides important information about systemic therapies for breast cancer, which implies pharmacological response, prognosis, and guide further therapy. Gene profiles overcome the shortcomings of the relatively limited detection indicators of the classical pathological evaluation criteria and the subjectivity of observation, but are complicated and expensive. Therefore, it is essential to develop a more accurate, repeatable, and economical evaluation approach for neoadjuvant chemotherapy responses.We analyzed the transcriptional profiles of chemo-resistant breast cancer cell lines and tumors of chemo-resistant breast cancer patients in the GSE25066 dataset. We preliminarily screened out common significantly differentially expressed genes and constructed a NAC response risk model using LASSO regression and univariate and multivariate analyses. The differences in bioinformatic features of tumor cells, immune characteristics, and prognosis were compared between high and low-risk group. The potential drugs that could reverse chemotherapy resistance in breast cancer were screened by the CMap database.Thirty-six genes were commonly up/down-regulated in both NAC chemo-resistant tumors and cells compared to the sensitive tumors and wild-type cells. Through LASSO regression, we obtained a risk model composed of 12 genes. The risk model divided patients into high and low-risk groups. Univariate and multivariate Cox regression analyses suggested that the risk score is an independent prognostic factor for evaluating NAC response in breast cancer. Tumors in risk groups exhibited significant differences in molecular biological characteristics, tumor-infiltrating lymphocytes, and immunosuppressive molecule expression. Our results suggested that the risk score was also a good prognostic factor for breast cancer. Finally, we screened potential drugs that could reverse chemotherapy resistance in breast cancer.A novel 12 gene-signature could be used to predict NAC response and predict prognosis in breast cancer.
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