The role of radiotherapy-related autophagy genes in the prognosis and immune infiltration in lung adenocarcinoma.
The role of radiotherapy-related autophagy genes in the prognosis and immune infiltration in lung adenocarcinoma.
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放疗相关自噬基因在肺腺癌预后和免疫浸润中的作用
DOI：
10.3389/fimmu.2022.992626
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发表时间：
2022
影响因子：
7.3
通讯作者：
Li, Wenhui
中科院分区：
文献类型：
--
作者：
Gao, Jingyan;Lu, Fei;Yan, Jiawen;Wang, Run;Xia, Yaoxiong;Wang, Li;Li, Lan;Chang, Li;Li, Wenhui
背景放射治疗与肿瘤自噬密切相关，但放射治疗相关自噬基因(RRAGs)在肺腺癌(LUAD)中的预后作用尚不清楚。方法本研究使用的数据来自癌症基因组图谱(TCGA)和基因表达总表(GEO)数据库。加权基因共表达网络分析(WGCNA)用于识别与放射治疗相关的模块基因。Edger软件包筛选不同放疗反应组间差异表达基因(Deg)。通过将模块基因、DEGS和自噬基因(ATGs)重叠，获得差异表达的放射治疗相关自噬基因(DERRAGs)。然后，通过Cox分析筛选出预测自噬的基因，并随后建立风险模型和诺模图。基因集浓缩分析(GSEA)和单样本基因集浓缩分析(SsGSEA)被用来研究预见性自噬信号调节LUAD的潜在机制。放射抗性细胞系(A549IR和PC9IR)是在次分割照射后建立的。用实时定量聚合酶链式反应(qRT-PCR)检测不同细胞系的mRNA表达，并用免疫印迹法检测不同细胞系的相关蛋白水平。结果LUAD共鉴定出11个DERRAG。经Cox分析后，筛选出SHC1、NAPSA和AURKA作为LUAD的预后标志。然后，利用预后特征信号构建风险评分模型，从受试者的操作特征曲线上可以看出，该模型对预后有较好的预测效果。COX回归分析显示，危险评分是影响LUAD预后的独立因素。此外，GSEA和ssGSEA结果显示，预后相关的RRAGs可能通过调节免疫微环境和影响细胞增殖来调节LUAD。克隆形成实验表明，耐辐射细胞系对辐射的敏感性低于原代细胞。Western印迹分析发现，放射耐药细胞系的自噬水平升高。DERRAGs(SHC1、AURKA)在放疗耐药细胞中的表达高于原代细胞。结论本研究探讨了RRAGs在LUAD预后中的作用，并确定了3种生物标志物。这些发现加深了对LUAD患者放射治疗、自噬和预后之间关系的了解，并为LUAD患者提供了潜在的治疗靶点。
Background There is a close relationship between radiotherapy and autophagy in tumors, but the prognostic role of radiotherapy-related autophagy genes (RRAGs) in lung adenocarcinoma (LUAD) remains unclear. Methods Data used in the current study were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) was executed to recognize module genes associated with radiotherapy. The differentially expressed genes (DEGs) between different radiotherapy response groups were filtered via edgeR package. The differentially expressed radiotherapy-related autophagy genes (DERRAGs) were obtained by overlapping the module genes, DEGs, and autophagy genes (ATGs). Then, prognostic autophagy genes were selected by Cox analyses, and a risk model and nomogram were subsequently built. Gene Set Enrichment Analysis (GSEA) and single-sample Gene Set Enrichment Analysis (ssGSEA) were performed to investigate potential mechanisms through which prognostic autophagy signatures regulate LUAD. Radiotherapy-resistant cell lines (A549IR and PC9IR) were established after exposure to hypo-fractionated irradiation. Ultimately, mRNA expression was validated by quantitative real-time PCR (qRT-PCR), and relative protein levels were measured in different cell lines by western blot. Results A total of 11 DERRAGs were identified in LUAD. After Cox analyses, SHC1, NAPSA, and AURKA were filtered as prognostic signatures in LUAD. Then, the risk score model was constructed using the prognostic signatures, which had a good performance in predicting the prognosis, as evidenced by receiver operating characteristics curves. Furthermore, Cox regression analyses demonstrated that risk score was deemed as an independent prognostic factor in LUAD. Moreover, GSEA and ssGSEA results revealed that prognostic RRAGs may regulate LUAD by modulating the immune microenvironment and affecting cell proliferation. The colony formation assay showed that the radiosensitivity of radiation-resistant cell lines was lower than that of primary cells. The western blot assay found that the levels of autophagy were elevated in the radiotherapy-resistant cell lines. Moreover, the expression of DERRAGs (SHC1, AURKA) was higher in the radiotherapy-resistant cells than in primary cells. Conclusion Our study explored the role of RRAGs in the prognosis of LUAD and identified three biomarkers. The findings enhanced the understanding of the relationship between radiotherapy, autophagy, and prognosis in LUAD and provided potential therapeutic targets for LUAD patients.
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影响因子：
6.2
作者：
Fernando M;Duijf PHG;Proctor M;Stevenson AJ;Ehmann A;Vora S;Skalamera D;Adams M;Gabrielli B
通讯作者：
Gabrielli B
影响因子：
9
作者：
He H;Song X;Yang Z;Mao Y;Zhang K;Wang Y;Su B;Li Q;Chen H;Li Y
通讯作者：
Li Y
影响因子：
--
作者：
Ma, Yunfan;Fan, Mengying;Chen, Keneng
通讯作者：
Chen, Keneng
影响因子：
5.6
作者：
Inamura, K;Satoh, Y;Ishikawa, Y
通讯作者：
Ishikawa, Y
影响因子：
4.8
作者：
Le, S;Connors, TJ;Maroney, AC
通讯作者：
Maroney, AC