A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer
A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer
复制标题
与肿瘤微环境相关的九个基因特征可预测卵巢癌的总体生存率
DOI：
10.18632/aging.102914
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发表时间：
2020-03-31
期刊：
影响因子：
5.2
通讯作者：
Zeng, Yong
中科院分区：
文献类型：
--
作者：
Ding, Qi;Dong, Shanshan;Zeng, Yong
越来越多的证据表明，肿瘤微环境（TME）中的免疫细胞浸润是卵巢癌（OC）中致癌和治疗效果的关键调节因子。在这项研究中，593名来自TCGA的OC患者根据使用ESTIMATE算法分析得出的免疫/基质评分分为高分组和低分组。差异表达分析显示294个交叉基因同时影响免疫和间质评分。进一步的考克斯回归分析确定了34个差异表达基因（DEG）为与乳腺癌相关的基因。最后，使用最小绝对收缩和选择算子（LASSO）和考克斯回归从突变相关基因导出九基因标签。这种九基因标签可以有效区分训练（TCGA数据库）和验证（GSE 17260）组群中的高风险患者（所有p < 0.01）。时间依赖性受试者工作特征（ROC）分析显示，9个基因签名在两个队列中具有合理的预测准确性（AUC = 0.707，AUC =0.696）。此外，通过基因集变异分析（GSVA），这九个基因签名与TME中的免疫浸润相关，并且可以用于预测OC患者的生存。
Mounting evidence suggests that immune cell infiltration within the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in ovarian cancer (OC). In this study, 593 OC patients from TCGA were divided into high and low score groups based on their immune/stromal scores resulting from analysis utilizing the ESTIMATE algorithm. Differential expression analysis revealed 294 intersecting genes that influencing both the immune and stromal scores. Further Cox regression analysis identified 34 differentially expressed genes (DEGs) as prognostic-related genes. Finally, the nine-gene signature was derived from the prognostic-related genes using a Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression. This nine-gene signature could effectively distinguish the high-risk patients in the training (TCGA database) and validation (GSE17260) cohorts (all p < 0.01). A time-dependent receiver operating characteristic (ROC) analysis showed that the nine-gene signature had a reasonable predictive accuracy (AUC = 0.707, AUC =0.696) in both cohorts. In addition, this nine-gene signature is associated with immune infiltration in TME by Gene Set Variation Analysis (GSVA), and can be used to predict the survival of patients with OC.