Identification of an independent immune-genes prognostic index for renal cell carcinoma.
Identification of an independent immune-genes prognostic index for renal cell carcinoma.
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DOI：
10.1186/s12885-021-08367-6
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发表时间：
2021-06-29
期刊：
影响因子：
3.8
通讯作者：
Qin C
中科院分区：
文献类型：
--
作者：
Li G;Wei X;Su S;Wang S;Wang W;Wang Y;Meng X;Xia J;Song N;Qin C
大量证据表明ccRCC中免疫微环境与临床结果之间存在关联。本研究的目的是广泛了解肿瘤免疫相关基因对ccRCC患者预后的影响。从免疫学数据库和分析门户（ImmPort）获得包含2498个免疫相关基因的文件，并从TCGA数据库中识别和下载与ccRCC患者相关的转录组数据和临床信息。采用单因素和多因素考克斯回归分析筛选预后免疫相关基因。根据生存率与中枢免疫相关基因的回归系数建立免疫风险评分模型。我们最终建立了一个诺模图，用于预测ccRCC的总生存期。采用Kaplan-Meier（K-M）法和ROC曲线评价模型的预测价值。P值< 0.05表示在整个数据分析中存在统计学显著差异。通过差异分析，我们发现556个免疫相关基因在肿瘤组织和正常组织中有差异表达（p < 0. 05）。05）。单因素考克斯回归分析显示，43个免疫基因与ccRCC患者生存风险相关（p < 0.05）。通过Lasso-Cox回归分析，建立了基于18个免疫相关基因的免疫遗传风险评分模型。K-M分析显示高危组预后不良。（p < 0.001）。ROC曲线显示免疫风险评分模型预测生存风险（5年生存期，AUC = 0.802）是可靠的。该模型在验证数据集中显示了令人满意的AUC和生存相关性（5年OS，曲线下面积= 0.705，p < 0.05）。多元回归分析显示，免疫风险评分模型在预测ccRCC预后中起独立作用。在多变量Cox回归分析下，我们建立了一个综合预测ccRCC患者生存率的诺模图。最后，确定了18个免疫相关基因和风险评分不仅与临床预后密切相关，而且包含在多种致癌途径中。一般来说，肿瘤免疫相关基因在ccRCC的发展和进展中发挥重要作用。我们的研究建立了一个不等的18个免疫基因的风险指数来预测ccRCC的预后。发现该指数是ccRCC的独立预测因子。在线版本包含补充材料，可通过10.1186/s12885-021-08367-6获得。
Considerable evidence has indicated an association between the immune microenvironment and clinical outcome in ccRCC. The purpose of this study is to extensively figure out the influence of immune-related genes of tumors on the prognosis of patients with ccRCC. Files containing 2498 immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort), and the transcriptome data and clinical information relevant to patients with ccRCC were identified and downloaded from the TCGA data-base. Univariate and multivariate Cox regression analyses were used to screen out prognostic immune genes. The immune risk score model was established in light of the regression coefficient between survival and hub immune-related genes. We eventually set up a nomogram for the prediction of the overall survival for ccRCC. Kaplan-Meier (K-M) and ROC curve was used in evaluating the value of the predictive risk model. A P value of < 0.05 indicated statistically significant differences throughout data analysis. Via differential analysis, we found that 556 immune-related genes were expressed differentially between tumor and normal tissues (p < 0. 05). The analysis of univariate Cox regression exhibited that there was a statistical correlation between 43 immune genes and survival risk in patients with ccRCC (p < 0.05). Through Lasso-Cox regression analysis, we established an immune genetic risk scoring model based on 18 immune-related genes. The high-risk group showed a bad prognosis in K-M analysis. (p < 0.001). ROC curve showed that it was reliable of the immune risk score model to predict survival risk (5 year over survival, AUC = 0.802). The model indicated satisfactory AUC and survival correlation in the validation data set (5 year OS, Area Under Curve = 0.705, p < 0.05). From Multivariate regression analysis, the immune-risk score model plays an isolated role in the prediction of the prognosis of ccRCC. Under multivariate-Cox regression analysis, we set up a nomogram for comprehensive prediction of ccRCC patients’ survival rate. At last, it was identified that 18 immune-related genes and risk scores were not only tremendously related to clinical prognosis but also contained in a variety of carcinogenic pathways. In general, tumor immune-related genes play essential roles in ccRCC development and progression. Our research established an unequal 18-immune gene risk index to predict the prognosis of ccRCC visually. This index was found to be an independent predictive factor for ccRCC. The online version contains supplementary material available at 10.1186/s12885-021-08367-6.
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影响因子：
4.6
作者：
Khadirnaikar, Seema;Kumar, Pranjal;Shukla, Sudhanshu Kumar
通讯作者：
Shukla, Sudhanshu Kumar
影响因子：
12.4
作者：
Giuliano, Sandy;Dufies, Maeva;Pages, Gilles
通讯作者：
Pages, Gilles
影响因子：
16.6
作者：
Wang, Xiang-Ming;Lu, Yang;Ma, Lu-Lin
通讯作者：
Ma, Lu-Lin
影响因子：
4.8
作者：
Murphy, Katherine A.;James, Britnie R.;Griffith, Thomas S.
通讯作者：
Griffith, Thomas S.
DOI：
10.1016/j.urolonc.2018.07.013
发表时间：
2018-11-01
影响因子：
2.7
作者：
Steven, Andre;Leisz, Sandra;Kroeger, Nils
通讯作者：
Kroeger, Nils