Comprehensive Analysis of a Novel Lipid Metabolism-Related Gene Signature for Predicting the Prognosis and Immune Landscape in Uterine Corpus Endometrial Carcinoma.
Comprehensive Analysis of a Novel Lipid Metabolism-Related Gene Signature for Predicting the Prognosis and Immune Landscape in Uterine Corpus Endometrial Carcinoma.
复制标题
DOI：
10.1155/2022/8028825
复制
发表时间：
2022
影响因子：
--
通讯作者：
Ding J
中科院分区：
文献类型：
--
作者：
Tan X;Liu S;Yao L;Cui G;Liu J;Ding J
脂质代谢在各种癌症中都很重要。然而，脂质代谢与子宫肌体子宫内膜癌（UCEC）之间的关系尚不清楚。在这项研究中，我们收集了来自癌症基因组图谱（TCGA）的临床病理参数和脂质代谢相关基因（LMRGs）的表达。建立并验证脂质代谢相关风险模型。风险评分是根据11个选定的lmrg制定的。通过qRT-PCR在临床样品中证实了11个LMRGs的表达。在多变量分析中，我们发现该模型是UCEC的独立预测因素。低危组总生存率（OS）高于高危组。GSEA结果显示，高危组MAPK信号通路、ERBB信号通路、ECM受体相互作用、WNT信号通路、TGF-β信号通路富集。低危组肿瘤突变负荷（TMB）高，对免疫治疗和化疗反应敏感。总之，我们建立了一个基于脂质代谢基因表达的风险标志，可以反映UCEC患者的预后以及他们对化疗和免疫治疗的反应。
Lipid metabolism is important in various cancers. However, the association between lipid metabolism and uterine corpus endometrial carcinoma (UCEC) is still unclear. In this study, we collected clinicopathologic parameters and the expression of lipid metabolism-related genes (LMRGs) from the Cancer Genome Atlas (TCGA). A lipid metabolism-related risk model was built and verified. The risk score was developed based on 11 selected LMRGs. The expression of 11 LMRGs was confirmed by qRT-PCR in clinical samples. We found that the model was an independent prediction factor of UCEC in terms of multivariate analysis. The overall survival (OS) of low-risk group was higher than that in the high-risk group. GSEA revealed that MAPK signaling pathway, ERBB signaling pathway, ECM receptor interaction, WNT pathway, and TGF-β signaling pathway were enriched in the high-risk group. Low-risk group was characterized by high tumor mutation burden (TMB) and showed sensitive response to immunotherapy and chemotherapy. In brief, we built a lipid metabolism gene expression-based risk signature which can reflect the prognosis of UCEC patients and their response to chemotherapeutics and immune therapy.
登录
查看更多内容
影响因子：
4.7
作者：
Ayakannu, Thangesweran;Taylor, Anthony H.;Konje, Justin C.
通讯作者：
Konje, Justin C.
影响因子：
5.5
作者：
Kang Y;Huang J;Liu Y;Zhang N;Cheng Q;Zhang Y
通讯作者：
Zhang Y
影响因子：
7.3
作者：
Chen, Yongyuan;Xin, Zhongwei;Chai, Ying
通讯作者：
Chai, Ying
影响因子：
11.2
作者：
Ganesan, Kumaresan;Ivanova, Tatiana;Tan, Patrick
通讯作者：
Tan, Patrick
影响因子：
4.8
作者：
Iamaroon, Anak;Krisanaprakornkit, Suttichai
通讯作者：
Krisanaprakornkit, Suttichai