Assessment for prognostic value of differentially expressed genes in immune microenvironment of clear cell renal cell carcinoma.
Assessment for prognostic value of differentially expressed genes in immune microenvironment of clear cell renal cell carcinoma.
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发表时间：
2020-09
影响因子：
2.2
通讯作者：
X. Yin;Xingming Zhang;Zhenhua Liu;G. Sun;Xudong Zhu;Haoran Zhang;Sha Zhu;Jinge Zhao;Junru Chen-J
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文献类型：
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作者：
X. Yin;Xingming Zhang;Zhenhua Liu;G. Sun;Xudong Zhu;Haoran Zhang;Sha Zhu;Jinge Zhao;Junru Chen-J
肿瘤浸润性免疫细胞已被认为与预后和免疫治疗反应有关；然而，与透明细胞肾细胞癌（ccRCC）免疫微环境相关的基因尚不清楚。为了更好地了解免疫和基质细胞相关基因对预后的影响，我们使用Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma （TCGA-KIRC）、DAVID数据库和ESTMATE算法，根据免疫评分（中位数：1038.45）和基质评分（中位数：667.945）将患者分为低组和高组。我们发现免疫评分与临床病理参数和总生存期（OS）显著相关。根据免疫评分，在1433个上调基因中，890个基因与OS显著相关。从前10个基因序列（IL10RA、FCER1G、SASH3、TIGIT、RHOH、IL12RB1、AIF1、LPXN、LAPTM5、SP140）来看，上调基因数≥5个的患者OS较差（P = 0.002）。此外，CD8 T细胞（11.32%）、CD4记忆性静息T细胞（-4.52%）和肥大静息细胞（-3.55%）在低、高免疫评分间的平均差异最为显著。因此，这些基因的组合可以用来预测免疫治疗的疗效。需要进一步分析这些基因，以探索它们与ccRCC预后的潜在关联。
Tumor-infiltrating immune cells have been recognized to be associated with prognosis and response to immunotherapy; however, genes related to immune microenvironment of clear cell renal cell carcinoma (ccRCC) remains unclear. To better understand the effects of genes involved in immune and stromal cells on prognosis, we used Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), DAVID database and ESTMATE algorithm, and divided the patients into low and high groups according to immune (median: 1038.45) and stromal scores (median: 667.945), respectively. We found the immune scores were significantly correlated with clinicopathological parameters and overall survival (OS). Based on immune scores, 890 DEGs were significantly associated with OS among the 1433 up-regulated genes. Based on top 10 DEGs (IL10RA, FCER1G, SASH3, TIGIT, RHOH, IL12RB1, AIF1, LPXN, LAPTM5 and SP140), cases with number of up-regulated genes ≥ 5 were associated poor OS (P = 0.002). In addition, the mean differences of percentages of CD8 T cells (11.32%), CD4 memory resting T cells (-4.52%) and mast resting cells (-3.55%) between low and high immune scores were the most significant. Thus, combination of these genes might use to predict the efficacy of immunotherapy. Further analyses of these genes were warrant to explore their potential association with the prognosis of ccRCC.