Construction of a novel prognostic model based on lncRNAs-related to DNA damage repair for predicting the prognosis of clear cell renal cell carcinoma

CcRCC has the characteristics of high aggression, high metastasis, high mortality, wide tumour heterogeneity and variable clinical course. The purpose of this study was to explore the potential value of lncRNAs-related to DNA damage repair (DDR) in predicting the prognosis of ccRCC by construction and verification a novel prognostic model. RNA-seq data and clinical data of ccRCC were downloaded from public databases. Subsequently, Pearson correlation analysis and differential expression analysis were performed to identify DElncRNAs-related to DDR. Then, through univariate Cox analysis and LASSO analysis, the DElncRNAs-related to DDR associated with prognosis were screened for the construction of novel risk score prognostic model. In addition, functional annotation, tumour mutation burden, immune correlation and drug sensitivity analyses were performed based on risk score to assess the characteristics of patients in different risk score groups. Based on univariate Cox analysis and LASSO analysis, four best DElncRNAs-related to DDR were selected. Subsequently, a novel risk score prognostic model based on these four DElncRNAs was constructed through LASSO. Multivariate Cox analysis showed that risk score and age were independent prognostic factors for ccRCC (<i>p</i> &lt; 0.05). Functional enrichment analysis showed that DDR-related biological processes were mainly enriched in the high risk group. The highly mutated genes in the high and low risk groups were the same (VHL, PBRM1 and TTN), but they also had their own unique mutated genes. Pearson correlation analysis showed that the risk score was significantly (<i>p</i> &lt; 0.05) positively correlated with the infiltration degree of CD8 T cells evaluated by six algorithms. In addition, it was found that the high and low risk groups had different sensitivities to the drugs Etoposide, Imatinib, Sorafenib, Bosutinib and Sunitinib. A novel prognostic model was constructed based on four DElncRNAs-related to DDR. The model has satisfactory accuracy in predicting survival of ccRCC patients.

透明细胞肾细胞癌（clear cell Renal Cell Carcinoma，ccRCC）具有侵袭性强、转移率高、致死率高、肿瘤异质性广泛且临床病程多变的特征。本研究旨在通过构建并验证一种新型预后模型，探讨与DNA损伤修复（DNA Damage Repair，DDR）相关的长链非编码RNA（long non-coding RNA，lncRNAs）在预测ccRCC患者预后中的潜在价值。本研究从公共数据库中下载了ccRCC的RNA测序（RNA-seq）数据与临床资料。随后通过Pearson相关分析与差异表达分析，筛选出与DDR相关的差异表达lncRNAs（differentially expressed lncRNAs，DElncRNAs）。继而采用单因素Cox分析与最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator，LASSO）分析，筛选出与预后相关的DDR相关DElncRNAs，用于构建新型风险评分预后模型。此外，本研究基于风险评分开展功能注释、肿瘤突变负荷、免疫相关性及药物敏感性分析，以评估不同风险评分组患者的临床特征。经单因素Cox分析与LASSO分析，最终筛选出4个最优的DDR相关DElncRNAs。随后基于这4个DElncRNAs，通过LASSO分析构建了新型风险评分预后模型。多因素Cox分析结果显示，风险评分与年龄均为ccRCC的独立预后因素（p<0.05）。功能富集分析结果表明，DDR相关生物学过程主要富集于高风险组。高、低风险组的高频突变基因均为VHL、PBRM1与TTN，但两组亦存在各自独特的突变基因。Pearson相关分析显示，经6种算法评估的CD8阳性T细胞浸润程度与风险评分呈显著正相关（p<0.05）。此外，本研究发现高、低风险组对依托泊苷（Etoposide）、伊马替尼（Imatinib）、索拉非尼（Sorafenib）、博舒替尼（Bosutinib）与舒尼替尼（Sunitinib）的药物敏感性存在差异。本研究基于4个DDR相关DElncRNAs构建了新型预后模型，该模型在预测ccRCC患者生存情况中具有良好的准确性。