摘要
出身背景
众所周知，影响癌症患者预后的因素很多。然而，失巢细胞凋亡对GC患者预后的潜在影响尚不清楚。
方法
根据癌症基因组图谱（TCGA）数据库，我们选择了差异表达的失巢相关基因（ARG）。应用单变量cox和最小绝对收缩和选择算子（lasso）分析来构建ARGs签名。还评估了ARGs信号对预后的影响。执行了一系列算法来评估免疫微环境中的差异。此外，还分析了药物敏感性与ARGs特征之间的相关性。我们还进行了实时聚合酶链式反应（RT-PCR）来探测信号。
后果
构建了9个基因的ARGs标记，这与预后明显相关。通过将ARGs特征与临床病理特征相结合来建立列线图。我们发现，预测能力明显优于其他个体预测因子。免疫微环境分析表明，低风险组的ESTIMATEscore、ImmuneScore、StromalScores、肿瘤免疫功能障碍和排除（TIDE）评分较低，而免疫表型评分（IPS）则相反。两组间的浸润免疫细胞和免疫检查点（ICP）表达水平有显著差异。此外，有9种药物与ARGs特征评分呈正相关。RT-PCR分析的结果与我们之前的差异表达分析一致。
结论
所开发的ARGs信号可以作为生物标志物，并为GC患者的个体治疗提供重要参考。
Abstract
Background
It is well known that the prognosis of Gastric cancer (GC) patient is affected by many factors. However, the latent impact of anoikis on the prognosis of GC patients is insufficient understood.

Methods
According to the Cancer Genome Atlas (TCGA) database, we elected discrepantly expressed anoikis-related genes (ARGs). Univariate cox and the least absolute shrinkage and selection operator (lasso) analysis were applied to build the ARGs signature. The prognostic effect of the ARGs signature was also evaluated. A series of algorithms were performed to evaluate the discrepancies in the immune microenvironment. Moreover, the correlation between drug sensitivity and ARGs signature was analyzed. We also performed Real-Time Polymerase Chain Reaction (RT-PCR) to probe the signature.

Results
The ARGs signature of 9 genes was constructed, which was apparently interrelated with the prognosis. The nomogram was established by combining the ARGs signature with clinicopathological characteristics. We found that the predictive power was noteworthily superior to other individual predictors. The immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, StromalScores, tumor immune dysfunction and exclusion (TIDE) score were lower in the low-risk group, while immunophenoscore (IPS) was on the contrary. The infiltrated immune cells and immune checkpoint (ICP) expression levels were significantly different between the two groups. Furthermore, nine drugs were positively associated with the ARGs signature score. The results of RT-PCR analysis were consistent with our previous differential expression analysis.

Conclusion
The developed ARGs signature could act as the biomarker and provide a momentous reference for Individual therapy of GC patients.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878391/