Lin Gaoteng, Guo Baoyin, Wei Yulei, Lan Tianjie, Wen Simeng, Li Gang
Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Department of Urology, Tianjin Baodi Hospital, Baodi Clinical College of Tianjin Medical University, Tianjin, China.
Front Genet. 2020 Nov 12;11:567200. doi: 10.3389/fgene.2020.567200. eCollection 2020.
Cumulative evidence from several tumor studies, including bladder cancer, emphasizes the importance of the tumor microenvironment (TME) in tumorigenesis, development, and metastasis, which can be regulated by long non-coding RNAs (lncRNAs). This study aims to identify bladder cancer (BC) microenvironment-associated lncRNAs for their prognostic value predicting the survival of BC patients.
The data of BC patients regarding lncRNA expression and corresponding clinical characteristics were obtained from The Cancer Genome Atlas (TCGA). The Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis were performed to screen lncRNAs following the calculation of the immune score for each sample. For the screened lncRNAs, a risk score model was constructed to predict the survival, and 3- and 5-year overall survival (OS) rates were assessed using a nomogram. The calibration curve and concordance index (C-index) validated the performance of the nomogram. Finally, to explore the potential function related to the screened lncRNAs, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed.
The multivariate Cox regression analysis screened five TME-associated lncRNAs regarded as independent factors influencing the tumor progression. The corresponding risk score model was established as follows: (-0.15816 AC064805.1) + (0.10015 AC084033.3) + (-0.17977 AC092112.1) + (-0.05673AC103691.1) + (0.17789 AL391704.1) + (-0.16258 LINC00892). The C-index for the nomogram was 0.63 (95% CI: 0.625-0.635). Also, the calibration curve verified the predictive effectiveness by showing a good concordance between the nomogram prediction and the actual observation. GO and KEGG analysis demonstrated that six TME-associated lncRNAs were most likely linked to tumor metastasis and progression.
The present study determined six lncRNAs as independent immuno-biomarkers in the TME, constructed a nomogram to predict their prognostic value, and investigated the potential biological processes to understand their regulatory roles in the progression of BC.
包括膀胱癌在内的多项肿瘤研究的累积证据强调了肿瘤微环境(TME)在肿瘤发生、发展和转移中的重要性,而肿瘤微环境可由长链非编码RNA(lncRNA)调控。本研究旨在鉴定与膀胱癌(BC)微环境相关的lncRNA,以评估其预测BC患者生存的预后价值。
从癌症基因组图谱(TCGA)获取BC患者的lncRNA表达数据及相应临床特征。在计算每个样本的免疫评分后,进行Cox回归分析和最小绝对收缩和选择算子(LASSO)回归分析以筛选lncRNA。对于筛选出的lncRNA,构建风险评分模型来预测生存情况,并使用列线图评估3年和5年总生存率(OS)。校准曲线和一致性指数(C指数)验证了列线图的性能。最后,为探究与筛选出的lncRNA相关的潜在功能,进行了基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析。
多变量Cox回归分析筛选出5个与TME相关的lncRNA,它们被视为影响肿瘤进展的独立因素。相应的风险评分模型如下:(-0.15816 AC064805.1)+(0.10015 AC084033.3)+(-0.17977 AC092112.1)+(-0.05673AC103691.1)+(0.17789 AL391704.1)+(-0.16258 LINC00892)。列线图的C指数为0.63(95%CI:0.625 - 0.635)。此外,校准曲线通过显示列线图预测与实际观察之间的良好一致性,验证了预测有效性。GO和KEGG分析表明,6个与TME相关的lncRNA最有可能与肿瘤转移和进展相关。
本研究确定了6个lncRNA作为TME中的独立免疫生物标志物,构建了列线图以预测其预后价值,并研究了潜在的生物学过程,以了解它们在BC进展中的调控作用。