A novel signature incorporating genes related to lipid metabolism and immune for prognostic and functional prediction of breast cancer
作者全名：Zhao, Xiao; Yan, Lvjun; Yang, Zailin; Zhang, Hui; Kong, Lingshuang; Zhang, Na; He, Yongpeng
作者地址：[Yang, Zailin; Zhang, Hui; Kong, Lingshuang; Zhang, Na; He, Yongpeng] Peoples Hosp Xinjin Dist, Clin Lab, Chengdu 611430, Peoples R China; [Yang, Zailin; Zhang, Hui; Kong, Lingshuang; Zhang, Na; He, Yongpeng] Chongqing Univ Canc Hosp, Chongqing Key Lab Translat Res Canc Metastasis & I, Chongqing 400030, Peoples R China; [Yang, Zailin; Zhang, Hui; Kong, Lingshuang; Zhang, Na; He, Yongpeng] Chongqing Canc Inst, Chongqing 401331, Peoples R China; [Yang, Zailin; Zhang, Hui; Kong, Lingshuang; Zhang, Na; He, Yongpeng] Chongqing Canc Hosp, Chongqing 400030, Peoples R China; [Yan, Lvjun] Univ Town Hosp, Chongqing Med Univ, Dept Nephrot, Chongqing 401331, Peoples R China
通信作者：Kong, LS; Zhang, N; He, YP (通讯作者)，Chongqing Univ Canc Hosp, Chongqing Key Lab Translat Res Canc Metastasis & I, Chongqing 400030, Peoples R China.; Kong, LS; Zhang, N; He, YP (通讯作者)，Chongqing Canc Inst, Chongqing 401331, Peoples R China.; Kong, LS; Zhang, N; He, YP (通讯作者)，Chongqing Canc Hosp, Chongqing 400030, Peoples R China.
来源：AGING-US
ESI学科分类：MOLECULAR BIOLOGY & GENETICS
WOS号：WOS:001238829900014
JCR分区：Q2
影响因子：3.9
年份：2024
卷号：16
期号：10
开始页：8611
结束页：8629
文献类型：Article
关键词：lipid metabolism; immunity; breast cancer; IL18; prognosis; RT-PCR
摘要：Purpose: Breast cancer prognosis and functioning have not been thoroughly examined in relation to immunological and lipid metabolism. However, there is a lack of prognostic and functional analyses of the relationship between lipid metabolism and immunity in breast cancer. Methods: DEGs in breast cancer were obtained from UCSC database, and lipid metabolism and immune-related genes were obtained from GSEA and Immune databases. A predictive signature was constructed using univariate Cox and LASSO regression on lipid metabolism and immune-related DEGs. The signature's prognostic significance was assessed using Kaplan-Meier, time-dependent ROC, and risk factor survival scores. Survival prognosis, therapeutic relevance, and functional enrichment were used to mine model gene biology. We selected IL18, which has never been reported in breast cancer before, in the signature to learn more about its function, potential to predict outcome, and immune system role. RT-PCR was performed to verify the true expression level of IL18. Results: A total of 136 DEGs associated with breast cancer responses to both immunity and lipid metabolism. Nine key genes (CALR, CCL5, CEPT, FTT3, CXCL13, FLT3, IL12B, IL18, and IL24, p < 1.6e-2) of breast cancer were identified, and a prognostic was successfully constructed with a good predictive ability. IL18 in the model also had good clinical prognostic guidance value and immune regulation and therapeutic potential. Furthermore, the expression of IL18 was higher than that in paracancerous tissue. Conclusions: A unique predictive signature model could effectively predict the prognosis of breast cancer, which can not only achieve survival prediction, but also screen out key genes with important functional mechanisms to guide clinical drug experiments.
基金机构：Natural Science Foundation of Chongqing [CSTB2023NSCQ- MSX0821]; Scientific research project of Chongqing Medical Biotechnology Association [cmba2022kyym-zkxmQ0012]
基金资助正文：<BOLD>Funding</BOLD> This research was supported by the Natural Science Foundation of Chongqing (No. CSTB2023NSCQ- MSX0821) and Scientific research project of Chongqing Medical Biotechnology Association (No. cmba2022kyym-zkxmQ0012) .
