| 杨莉,李海文.基于坏死性凋亡相关长链非编码RNA在肾透明细胞癌中的预后模型构建和分析[J].安徽医药,待发表. |
| 基于坏死性凋亡相关长链非编码RNA在肾透明细胞癌中的预后模型构建和分析 |
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| 投稿时间：2025-03-13 录用日期：2025-04-16 |
| DOI： |
| 中文关键词: 坏死性凋亡 RNA, 长链非编码 癌, 肾细胞 预后 肿瘤微环境 |
| 英文关键词: |
| 基金项目:湛江市非资助科技攻关专题(2020B01231和2022B01209)；院内资助类临床研究项目(LCYJ2023B002)；广东省高等教育十四五规划课题(24GYB25)；广东医科大学高等教育教学研究课题(2FY24006)； |
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| 中文摘要: |
| 目的：筛选肾透明细胞癌(kidney renal clear cell carcinoma,KIRC)预后坏死性凋亡相关长非编码RNA(Necroptosis-related long non-coding RNA,NRL),并构建基于NRL的预后模型,以预测KIRC患者的预后和筛选其预后生物标志物。方法：从TCGA数据库获取KIRC患者RNA测序数据、临床及预后信息。通过GeneCards筛选坏死性凋亡相关基因,利用“limma”包筛选差异表达基因并进行功能富集分析；通过 Pearson 相关性分析、LASSO和Cox回归分析筛选NRL构建预后模型；采用 Kaplan-Meier生存分析、 Cox 回归、临床病理特征相关性研究和受试者工作特征谱评价预后模型对KIRC生存率的预测能力；使用药物敏感性分析风险评分和抗癌药物敏感性之间的相关性；最后,采用RT-qPCR检测从临床收集的6例癌和癌旁组织NRL的表达水平。结果：共筛选出50个与坏死性凋亡相关的差异表达基因,包括37个上调基因和13个下调基因,这些基因在坏死性凋亡过程和免疫相关通路中显著富集；进一步分析筛选出5个与预后显著相关的NRL(AC084876.1、AC093797.1、DLGAP1-AS2、LINC01605、AC093895.1)并构建预后风险模型；Kaplan-Meier生存分析显示低风险组的总生存率显著优于高风险组(P<0.001),预后风险模型的AUC值为0.846；Cox 回归和分层生存分析提示风险评分是KIRC 患者的独立预测因子。此外,高风险组在免疫细胞浸润和免疫检查点表达水平上显著高于低风险组,且对A-443654和ABT-888更为敏感(P<0.05)；AC084876.1、DLGAP1-AS2、LINC01605和AC093895.1在癌组织表达量高于癌旁组织,相反AC093797.1在癌旁组织表达量高于癌组织。结论：基于AC093797.1、AC084876.1、DLGAP1-AS2、LINC01605、AC093895.1构建的预后模型可有效预测KIRC患者的预后,为临床诊断和个性化治疗提供了新的生物标志物和潜在治疗靶点。 |
| 英文摘要: |
| Objective: To screen for necroptosis-related long non-coding RNAs (NRLs) associated with the prognosis of kidney renal clear cell carcinoma (KIRC) and construct a prognosis model based on NRLs to predict the prognosis of KIRC patients and screen for prognostic biomarkers. Methods: RNA sequencing data, clinical and prognostic information of KIRC patients were obtained from the TCGA database. Necroptosis-related genes were obtained from GeneCards, and differentially expressed genes were identified using the "limma" package and subjected to functional enrichment analysis. NRLs were selected for constructing the prognostic model through Pearson correlation analysis, LASSO, and Cox regression analysis. The predictive ability of the prognostic model for KIRC overall survival rates was evaluated using Kaplan-Meier analysis, Cox regression, correlation studies with clinical pathological characteristics, and receiver operating characteristic (ROC) curve analysis. Additionally, the correlation between risk scores and tumor immune cell infiltration and anti-cancer drug sensitivity was studied. Finally, the expression levels of NRLs in six pairs of cancerous and adjacent normal tissues collected from the clinic were detected by RT-qPCR. Results: A total of 50 differentially expressed genes related to necroptosis were identified, including 37 up-regulated and 13 down-regulated genes, which were significantly enriched in necroptosis processes and immune-related pathways. Further analysis identified 5 NRLs (AC084876.1, AC093797.1, DLGAP1-AS2, LINC01605, AC093895.1) significantly associated with prognosis and used to construct the prognostic model. Kaplan-Meier analysis showed that the overall survival rate of the low-risk group was significantly better than that of the high-risk group (P<0.001), with the model's risk score AUC value being 0.846. Cox regression and stratified survival analysis indicated that the risk score is an independent predictor for KIRC patients. Additionally, the high-risk group had significantly higher levels of immune cell infiltration and immune checkpoint expression and was more sensitive to A-443654 and ABT-888 (P<0.05). The expression levels of AC084876.1, DLGAP1-AS2, LINC01605 and AC093895.1 were higher in cancerous tissues than in adjacent normal tissues. Conversely, AC093797.1 was more highly expressed in adjacent normal tissues than in cancerous tissues. Conclusion: The prognostic model constructed based on AC093797.1, AC084876.1, DLGAP1-AS2, LINC01605, and AC093895.1 can effectively predict the prognosis of KIRC patients, providing new biomarkers and a theoretical basis for clinical diagnosis and personalized treatment. |
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