Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Thorac Cancer. 2023 Jan;14(3):320-330. doi: 10.1111/1759-7714.14766. Epub 2022 Dec 11.
Lung adenocarcinoma (LUAD) is the most prevalent histotype of non-small cell lung cancer. Anoikis, an alternative form of programmed cell death, plays a pivotal role in cancer invasion and metastasis, preventing the detached cancer cells from readhering to other substrates for abnormal proliferation. The aim of this study was to conduct a comprehensive analyses of the prognostic implications of anoikis-related genes (ARGs) in LUAD.
ARGs were selected from The Cancer Genome Atlas (TCGA) database and Genecards dataset using differential expression analysis. The signature incorporating ARGs was identified using univariate Cox regression analysis and LASSO regression analysis. Furthermore, a nomogram containing the signature and clinical information was developed through univariate and multivariate Cox regression analysis. Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were applied to evaluate the predictive validity of these risk models. Finally, functional analysis of the selected ARGs in signature and analysis of immune landscape were also conducted.
A 16-gene signature was integrated to stratify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and TNM stage were identified as independent prognostic factors and utilized to develop a nomogram. Both the signature and the nomogram showed satisfactory prediction performance in predicting overall survival (OS) of LUAD patients. The ARGs were enriched in several biological functions and signaling pathways. Finally, differences of immune landscape were investigated among the high- and low-risk groups stratified by the signature.
This study revealed potential relationships between ARGs and prognosis of LUAD. The prognostic predictors identified in present study could be utilized as potential biomarkers for clinical applications.
肺腺癌（LUAD）是非小细胞肺癌中最常见的组织学类型。失巢凋亡，一种细胞程序性死亡的替代形式，在癌症的侵袭和转移中起着关键作用，防止分离的癌细胞重新附着在其他异常增殖的基质上。本研究旨在对 LUAD 中与失巢凋亡相关的基因（ARGs）的预后意义进行全面分析。
使用差异表达分析从癌症基因组图谱（TCGA）数据库和 Genecards 数据集选择 ARGs。使用单变量 Cox 回归分析和 LASSO 回归分析确定包含 ARGs 的特征。此外，通过单变量和多变量 Cox 回归分析，开发了一个包含特征和临床信息的列线图。 Kaplan-Meier 生存分析和接受者操作特征（ROC）曲线用于评估这些风险模型的预测有效性。最后，还对特征中选择的 ARGs 进行了功能分析，并分析了免疫景观。
整合了一个 16 基因特征，将 LUAD 患者分为不同的生存风险组。从特征和 TNM 阶段生成的预后风险评分被确定为独立的预后因素，并用于开发列线图。特征和列线图都在预测 LUAD 患者的总生存期（OS）方面表现出良好的预测性能。ARGs 富集在几个生物学功能和信号通路中。最后，根据特征对高风险和低风险组进行分层，研究了免疫景观的差异。
本研究揭示了 ARGs 与 LUAD 预后之间的潜在关系。本研究中确定的预后预测因子可作为临床应用的潜在生物标志物。
