微卫星不稳定性
基因组不稳定性
生物
队列
计算生物学
基因组
转录组
肾细胞癌
肿瘤科
体细胞
肾透明细胞癌
生物信息学
癌症研究
内科学
基因
医学
遗传学
微卫星
基因表达
DNA
等位基因
DNA损伤
作者
Huixin Zhu,Wen‐Cai Zheng,Hang Chen,Jia‐Yin Chen,Fei Lin,Shao‐Hao Chen,Xue‐Yi Xue,Qing‐Shui Zheng,Min Liang,Ning Xu,Dong‐Ning Chen,Xiong‐Lin Sun
出处
期刊:Combinatorial Chemistry & High Throughput Screening
[Bentham Science]
日期:2024-08-01
卷期号:27 (12): 1788-1807
标识
DOI:10.2174/0113862073258779231020052115
摘要
Objective: Genomic instability can drive clonal evolution, continuous modification of tumor genomes, and tumor genomic heterogeneity. The molecular mechanism of genomic instability still needs further investigation. This study aims to identify novel genome instabilityassociated lncRNAs (GI-lncRNAs) and investigate the role of genome instability in pan-Renal cell carcinoma (RCC). Materials and Methods: A mutator hypothesis was employed, combining the TCGA database of somatic mutation (SM) information, to identify GI-lncRNAs. Subsequently, a training cohort (n = 442) and a testing cohort (n = 439) were formed by randomly dividing all RCC patients. Based on the training cohort dataset, a multivariate Cox regression analysis lncRNAs risk model was created. Further validations were performed in the testing cohort, TCGA cohort, and different RCC subtypes. To confirm the relative expression levels of lncRNAs in HK-2, 786-O, and 769-P cells, qPCR was carried out. Functional pathway enrichment analyses were performed for further investigation. Results: A total of 170 novel GI-lncRNAs were identified. The lncRNA prognostic risk model was constructed based on LINC00460, AC073218.1, AC010789.1, and COLCA1. This risk model successfully differentiated patients into distinct risk groups with significantly different clinical outcomes. The model was further validated in multiple independent patient cohorts. Additionally, functional and pathway enrichment analyses revealed that GI-lncRNAs play a crucial role in GI. Furthermore, the assessments of immune response, drug sensitivity, and cancer stemness revealed a significant relationship between GI-lncRNAs and tumor microenvironment infiltration, mutational burden, microsatellite instability, and drug resistance. Conclusions: In this study, we discovered four novel GI-lncRNAs and developed a novel signature that effectively predicted clinical outcomes in pan-RCC. The findings provide valuable insights for pan-RCC immunotherapy and shed light on potential underlying mechanisms.
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