Kang Zhen, Li Wei, Yu Yan-Hong, Che Meng, Yang Mao-Lin, Len Jin-Jun, Wu Yue-Rong, Yang Jun-Feng
The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China.
Department of Urology, The First People's Hospital of Yunnan Province, Kunming, China.
Front Genet. 2021 Nov 26;12:763590. doi: 10.3389/fgene.2021.763590. eCollection 2021.
To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis.
We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data.
Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients ( < 0.01), of which 5 genes, including and , increased the risk of the prognosis, while the rest, including and decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model.
We had identified nine genes, including , , and , which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.
基于免疫学特征鉴定膀胱癌（BLCA）的免疫相关基因，并探讨其与预后的相关性。
我们从癌症基因组图谱（TCGA）下载BLCA的基因和临床数据作为训练组，并从免疫数据库（Immport）获得免疫相关基因。我们从基因表达综合数据库（GEO）下载GSE31684和GSE39281作为外部验证组。使用R（版本4.0.5）和Perl分析所有数据。
单因素Cox回归分析和Lasso回归分析显示，差异表达免疫基因（DEIGs）中的9个预后相关免疫基因（PIMGs）与BLCA患者的生存显著相关（<0.01），其中包括[具体基因1]和[具体基因2]在内的5个基因增加了预后风险，而包括[具体基因3]和[具体基因4]在内的其余基因降低了预后风险。然后，我们使用这些基因建立了一个预后模型。我们在训练组中绘制了受试者工作特征（ROC）曲线，并估计该模型1年、3年和5年生存率的曲线下面积（AUC）分别为0.688、0.719和0.706。通过校准图验证了预后模型的准确性。结合临床因素，我们建立了一个列线图。外部验证组中的ROC曲线表明，列线图对生存率具有良好的预测能力，准确性高，1年、3年和5年生存率的AUC值分别为0.744、0.770和0.782。校准图表明列线图与理想模型表现相似。
我们鉴定出了包括[具体基因1]、[具体基因2]、[具体基因3]和[具体基因4]在内的9个基因，它们在BLCA的发生和发展中起重要作用。基于这些基因的预后模型在预测患者总生存期方面具有良好的准确性，可能是有前景的治疗靶点候选者。本研究可能从免疫学角度为BLCA的诊断、治疗和预后提供新的见解。然而，需要进一步的实验研究来揭示这些基因介导BLCA进展的潜在机制。
