Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
J Cancer Res Clin Oncol. 2023 Oct;149(13):11661-11678. doi: 10.1007/s00432-023-05012-6. Epub 2023 Jul 5.
Clear cell renal cell carcinomas (ccRCCs) are the most common form of renal cancer in the world. The loss of extracellular matrix (ECM) stimulates cell apoptosis, known as anoikis. A resistance to anoikis in cancer cells is believed to contribute to tumor malignancy, particularly metastasis; however, the potential influence of anoikis on the prognosis of ccRCC patients is not fully understood.
In this study, anoikis-related genes (ARGs) with discrepant expression were selected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The anoikis-related gene signature (ARS) was built using a combination of the univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. ARS was also evaluated for their prognostic value. We explored the tumor microenvironment and enrichment pathways between different clusters of ccRCC. We also examined differences in clinical characteristics, immune cell infiltration and drug sensitivity between the high- and low-risk sets. In addition, we utilized three external databases and quantitative real-time polymerase chain reaction (qRT-PCR) to validate the expression and prognosis of ARGs.
Eight ARGs (PLAUR, HMCN1, CDKN2A, BID, GLI2, PLG, PRKCQ and IRF6) were identified as anoikis-related prognostic factors. According to Kaplan-Meier (KM) analysis, ccRCC patients with high-risk ARGs have a worse prognosis. The risk score was found to be a significant independent prognostic indicator. According to tumor microenvironment (TME) scores, stromal score, immune score, and estimated score of the high-risk group were superior to those of the low-risk group. There were significant differences between the two groups regarding the amount of infiltrated immune cells, immune checkpoint expression as well as drug sensitivity. A nomogram was constructed using ccRCC clinical features and risk scores. The signature and the nomogram both performed well in predicting overall survival (OS) for ccRCC patients. According to a decision curve analysis (DCA), clinical treatment options for patients with ccRCC could be improved using this model.
The results of validation from external databases and qRT-PCR were basically agreement with findings in TCGA and GEO databases. The ARS serving as biomarkers may provide an important reference for individual therapy of ccRCC patients.
透明细胞肾细胞癌（ccRCC）是世界上最常见的肾癌类型。细胞外基质（ECM）的丢失会刺激细胞凋亡，即 anoikis。人们认为癌细胞对 anoikis 的抵抗力有助于肿瘤的恶性程度，特别是转移；然而，anoikis 对 ccRCC 患者预后的潜在影响尚未完全了解。
本研究从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中选择了差异表达的 anoikis 相关基因（ARGs）。使用单变量 Cox 和最小绝对收缩和选择算子（LASSO）分析相结合的方法构建 anoikis 相关基因特征（ARS）。还评估了 ARS 的预后价值。我们探讨了不同 ccRCC 簇之间的肿瘤微环境和富集途径。我们还检查了高风险和低风险组之间的临床特征、免疫细胞浸润和药物敏感性的差异。此外，我们利用三个外部数据库和实时定量聚合酶链反应（qRT-PCR）验证了 ARGs 的表达和预后。
确定了 8 个 ARGs（PLAUR、HMCN1、CDKN2A、BID、GLI2、PLG、PRKCQ 和 IRF6）为 anoikis 相关的预后因素。根据 Kaplan-Meier（KM）分析，ccRCC 患者的高风险 ARGs 预后较差。风险评分被发现是一个显著的独立预后指标。根据肿瘤微环境（TME）评分，高危组的基质评分、免疫评分和估计评分均优于低危组。两组之间在浸润免疫细胞数量、免疫检查点表达以及药物敏感性方面存在显著差异。使用 ccRCC 临床特征和风险评分构建了列线图。该特征和列线图均能很好地预测 ccRCC 患者的总生存期（OS）。根据决策曲线分析（DCA），该模型可改善 ccRCC 患者的临床治疗选择。
外部数据库和 qRT-PCR 的验证结果与 TCGA 和 GEO 数据库的结果基本一致。作为生物标志物的 ARS 可能为 ccRCC 患者的个体化治疗提供重要参考。
