Cao Lixue, Zhang Shaofen, Peng Haojie, Lin Yongqing, Xi Zhihui, Lin Wumei, Guo Jialing, Wu Geyan, Yu Fei, Zhang Hui, Ye Haiyan
Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.
Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China.
Aging (Albany NY). 2024 Jan 15;16(2):1463-1483. doi: 10.18632/aging.205439.
Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and metastasis. However, the potential roles of anoikis-related long non-coding RNAs (arlncRNAs) in the tumor microenvironment are not well understood. In this study, five candidate lncRNAs were screened through least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis based on differentially expressed lncRNAs associated with anoikis-related genes (ARGs) from TCGA and GSE40595 datasets. The prognostic accuracy of the risk model was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) analyses revealed significant differences in immune-related hallmarks and signal transduction pathways between the high-risk and low-risk groups. Additionally, immune infiltrate analysis showed significant differences in the distribution of macrophages M2, follicular T helper cells, plasma cells, and neutrophils between the two risk groups. Lastly, silencing the expression of PRR34_AS1 and SPAG5_AS1 significantly increased anoikis-induced cell death in ovarian cancer cells. In conclusion, our study constructed a risk model that can predict clinicopathological features, tumor microenvironment characteristics, and prognosis of ovarian cancer patients. The immune-related pathways identified in this study may offer new treatment strategies for ovarian cancer.
失巢凋亡是一种由于细胞与基质相互作用不足而导致的凋亡性细胞死亡形式，通过调节肿瘤血管生成和转移参与肿瘤进展。然而，与失巢凋亡相关的长链非编码RNA（arlncRNAs）在肿瘤微环境中的潜在作用尚未完全明确。在本研究中，通过最小绝对收缩和选择算子（LASSO）以及基于来自TCGA和GSE40595数据集的与失巢凋亡相关基因（ARGs）相关的差异表达lncRNAs进行多变量Cox回归分析，筛选出5个候选lncRNAs。使用Kaplan-Meier生存分析和受试者工作特征（ROC）曲线评估风险模型的预后准确性。此外，京都基因与基因组百科全书（KEGG）和基因集富集分析（GSEA）分析显示，高风险组和低风险组在免疫相关特征和信号转导途径方面存在显著差异。此外，免疫浸润分析表明，两个风险组在M2巨噬细胞、滤泡辅助性T细胞、浆细胞和中性粒细胞的分布上存在显著差异。最后，沉默PRR34_AS1和SPAG5_AS1的表达显著增加了卵巢癌细胞中失巢凋亡诱导的细胞死亡。总之，我们的研究构建了一个可以预测卵巢癌患者临床病理特征、肿瘤微环境特征和预后的风险模型。本研究中确定的免疫相关途径可能为卵巢癌提供新的治疗策略。
