Comprehensive analysis to identify DNA damage response-related lncRNA pairs as a prognostic and therapeutic biomarker in gastric cancer.
Comprehensive analysis to identify DNA damage response-related lncRNA pairs as a prognostic and therapeutic biomarker in gastric cancer.
复制标题
DOI：
10.3934/mbe.2022026
复制
发表时间：
2021-11
期刊：
影响因子：
--
通讯作者：
Yuan Yang;Lingsha Zhou;Xi Gou;Guozhi Wu;Ya Zheng;Min Liu;Zhaofeng Chen;Yuping Wang;R. Ji;Qinghong Guo;Yongning Zhou
中科院分区：
文献类型：
--
作者：
Yuan Yang;Lingsha Zhou;Xi Gou;Guozhi Wu;Ya Zheng;Min Liu;Zhaofeng Chen;Yuping Wang;R. Ji;Qinghong Guo;Yongning Zhou
目的 胃癌（GC）是全球第五大常见恶性肿瘤，也是癌症相关死亡的第四大原因。鉴定有价值的预测特征以改善GC患者的预后正在成为一个现实的前景。 DNA 损伤反应相关的长链非编码核糖核酸 (drlncRNA) 在癌症的发展中发挥着重要作用。然而，它们在胃癌（GC）中的预后和治疗价值仍然很少。方法 我们从癌症基因组图谱胃癌腺癌 (TCGA-STAD) 队列中获得了转录组数据和临床信息。使用 igaph 包进行共表达网络分析以发现功能模块。随后，通过生物信息分析鉴定lncRNA对，并分别通过单变量分析确定预后对。此外，我们利用最小绝对收缩和选择算子（LASSO）cox回归分析来构建基于lncRNA对的风险模型。然后，我们根据最佳模型区分GC患者的高风险组和低风险组。最后，我们重新评估了风险评分与总体生存率、肿瘤免疫微环境、特定肿瘤浸润免疫细胞相关生物标志物以及化疗药物敏感性之间的关联。结果 获得了 32 个 drlncRNA 对，并构建了 17 个 drlncRNA 对签名来预测 GC 患者的总生存期。第 1、2、3 年的 ROC 分别为 0.797、0.812 和 0.821。将这些患者重新分类为不同的风险组后，我们可以根据阴性总体生存结果、特殊的肿瘤免疫浸润状态、较高表达的免疫细胞相关生物标志物和较低的化疗敏感性来区分他们。与之前的模型相比，我们的模型表现出更好的性能和更高的 ROC 值。结论 由新型 lncRNA 对建立的预后和治疗特征可以提供有希望的预测价值，并指导未来的个体治疗策略。
OBJECTIVE Gastric cancer (GC) is the fifth most common malignancy and the fourth leading cause of cancer-related mortality worldwide. The identification of valuable predictive signatures to improve the prognosis of patients with GC is becoming a realistic prospect. DNA damage response-related long noncoding ribonucleic acids (drlncRNAs) play an important role in the development of cancers. However, their prognostic and therapeutic values remain sparse in gastric cancer (GC). METHODS We obtained the transcriptome data and clinical information from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort. Co-expression network analyses were performed to discover functional modules using the igaph package. Subsequently, lncRNA pairs were identified by bioinformation analysis, and prognostic pairs were determined by univariate analysis, respectively. In addition, we utilized least absolute shrinkage and selection operator (LASSO) cox regression analysis to construct the risk model based on lncRNA pairs. Then, we distinguished between the high- or low- risk groups from patients with GC based on the optimal model. Finally, we reevaluated the association between risk score and overall survival, tumor immune microenvironment, specific tumor-infiltrating immune cells related biomarkers, and the sensitivity of chemotherapeutic agents. RESULTS 32 drlncRNA pairs were obtained, and a 17-drlncRNA pairs signature was constructed to predict the overall survival of patients with GC. The ROC was 0.797, 0.812 and 0.821 at 1, 2, 3 years, respectively. After reclassifying these patients into different risk-groups, we could differentiate between them based on negative overall survival outcome, specialized tumor immune infiltration status, higher expressed immune cell related biomarkers, and a lower chemotherapeutics sensitivity. Compared with previous models, our model showed better performance with a higher ROC value. CONCLUSION The prognostic and therapeutic signature established by novel lncRNA pairs could provide promising prediction value, and guide individual treatment strategies in the future.