Table_3_Inflammation-Related LncRNAs Signature for Prognosis and Immune Response Evaluation in Uterine Corpus Endometrial Carcinoma.docx

BackgroundsUterine corpus endometrial carcinoma (UCEC) is one of the greatest threats on the female reproductive system. The aim of this study is to explore the inflammation-related LncRNA (IRLs) signature predicting the clinical outcomes and response of UCEC patients to immunotherapy and chemotherapy.
MethodsConsensus clustering analysis was employed to determine inflammation-related subtype. Cox regression methods were used to unearth potential prognostic IRLs and set up a risk model. The prognostic value of the prognostic model was calculated by the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. Differential abundance of immune cell infiltration, expression levels of immunomodulators, the status of tumor mutation burden (TMB), the response to immune checkpoint inhibitors (ICIs), drug sensitivity, and functional enrichment in different risk groups were also explored. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the expression patterns of model IRLs in clinical specimens.
ResultsAll UCEC cases were divided into two clusters (C1 = 454) and (C2 = 57) which had significant differences in prognosis and immune status. Five hub IRLs were selected to develop an IRL prognostic signature (IRLPS) which had value in forecasting the clinical outcome of UCEC patients. Biological processes related to tumor and immune response were screened. Function enrichment algorithm showed tumor signaling pathways (ERBB signaling, TGF-β signaling, and Wnt signaling) were remarkably activated in high-risk group scores. In addition, the high-risk group had a higher infiltration level of M2 macrophages and lower TMB value, suggesting patients with high risk were prone to a immunosuppressive status. Furthermore, we determined several potential molecular drugs for UCEC.
ConclusionWe successfully identified a novel molecular subtype and inflammation-related prognostic model for UCEC. Our constructed risk signature can be employed to assess the survival of UCEC patients and offer a valuable reference for clinical treatment regimens.

背景：子宫体子宫内膜癌（Uterine corpus endometrial carcinoma，UCEC）是威胁女性生殖系统的重大恶性肿瘤之一。本研究旨在探索可预测UCEC患者临床结局及免疫治疗、化疗响应的炎症相关长链非编码RNA（long non-coding RNA，LncRNA）特征。
方法：本研究采用共识聚类分析确定炎症相关亚型；通过Cox回归法挖掘潜在的预后相关炎症相关LncRNA（inflammation-related LncRNA，IRLs）并构建风险模型。采用Kaplan-Meier法、受试者工作特征曲线（receiver operating characteristic，ROC）以及单因素、多因素分析评估该预后模型的预后价值。此外，本研究还分析了不同风险组间免疫细胞浸润丰度差异、免疫调节因子表达水平、肿瘤突变负荷（tumor mutation burden，TMB）状态、免疫检查点抑制剂（immune checkpoint inhibitors，ICIs）响应、药物敏感性及功能富集情况。最后，通过实时定量聚合酶链反应（quantitative real-time PCR，qRT-PCR）验证模型所包含的IRLs在临床标本中的表达模式。
结果：本研究将所有UCEC病例分为两个亚型簇（C1=454例，C2=57例），二者在预后及免疫状态上均存在显著差异。筛选出5个核心IRLs，构建了IRLs预后特征（IRL prognostic signature，IRLPS），该特征可有效预测UCEC患者的临床结局。本研究还筛选出与肿瘤及免疫应答相关的生物学过程；功能富集分析显示，高风险组中肿瘤信号通路（ERBB信号通路、转化生长因子-β信号通路、Wnt信号通路）显著激活。此外，高风险组的M2巨噬细胞浸润水平更高，TMB值更低，提示高风险患者更易出现免疫抑制状态。本研究同时筛选出数种针对UCEC的潜在分子治疗药物。
结论：本研究成功鉴定出UCEC的新型分子亚型及炎症相关预后模型。本研究构建的风险特征可用于评估UCEC患者的生存情况，可为临床治疗方案制定提供重要参考依据。