Objectives. Radiosensitivity Index (RSI) can predict intrinsic radiotherapy sensitivity. We analyzed multiomics characteristics in lung squamous cell carcinoma between high and low RSI groups, which may help understand the underlying molecular mechanism of radiosensitivity and guide optional treatment for patients in the future. Methods. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data were used to download clinical data, mRNA, microRNA, and lncRNA expression. Differential analyses, including mRNA, miRNA, lncRNA, and G.O. and KEGG, and GSVA analyses, were performed with R. Gene set enrichment analysis was done by GSEA. miRNA-differentially expressed gene network and ceRNA network were analyzed and graphed by the Cytoscape software. Results. In TCGA data, 542 patients were obtained, including 171 in the low RSI group (LRSI) and 371 in the high RSI group (HRSI). In RNAseq, 558 significantly differentially expressed genes (DEGs) were obtained. KRT6A was the most significantly upregulated gene and IDO1 was the most significantly downregulated gene. In miRNAseq, miR-1269a was the most significantly upregulated. In lncRNAseq, LINC01871 was the most upregulated. A 66-pair interaction between differentially expressed genes and miRNAs and an 11-pair interaction between differential lncRNAs and miRNAs consisted of a ceRNA network, of which miR-184 and miR-490-3p were located in the center. In the GEO data, there were 40 DEGs. A total of 17 genes were founded in both databases, such as ADAM23, AHNAK2, BST2, COL11A1, CXCL13, FBN2, IFI27, IFI44L, MAGEA6, and PTGR1. GSVA analysis revealed 31 significant pathways. GSEA found 87 gene sets enriched in HRSI and 91 gene sets in LRSI. G.O. and KEGG of RNA expression levels revealed that these genes were most enriched in T cell activation and cytokine−cytokine receptor interaction. Conclusions. Patients with lung squamous cell carcinoma have different multiomics characteristics between two groups. These differences may have an essential significance with radiotherapy effect.

中文翻译：

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放射敏感性指数高与放射敏感性指数低的肺鳞状细胞癌患者的多组学差异

目标。放射敏感性指数 (RSI) 可以预测内在放射治疗敏感性。我们分析了高、低 RSI 组肺鳞状细胞癌的多组学特征，这可能有助于了解放射敏感性的潜在分子机制，并指导未来患者的可选治疗。方法。癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 数据用于下载临床数据、mRNA、microRNA 和 lncRNA 表达。使用 R 进行差异分析，包括 mRNA、miRNA、lncRNA 和 GO 和 KEGG，以及 GSVA 分析。基因集富集分析由 GSEA 完成。miRNA差异表达基因网络和ceRNA网络通过Cytoscape软件进行分析和绘图。结果. 在 TCGA 数据中，获得了 542 名患者，其中低 RSI 组 (LRSI) 中的 171 名和高 RSI 组 (HRSI) 中的 371 名。在 RNAseq 中，获得了 558 个显着差异表达的基因 (DEG)。KRT6A 是最显着上调的基因，IDO1 是最显着下调的基因。在 miRNAseq 中，miR-1269a 是最显着上调的。在 lncRNAseq 中，LINC01871 上调最多。差异表达基因与miRNA之间的66对相互作用和差异lncRNA与miRNA之间的11对相互作用组成一个ceRNA网络，其中miR-184和miR-490-3p位于中心。在 GEO 数据中，有 40 度。两个数据库共建立了17个基因，如ADAM23、AHNAK2、BST2、COL11A1、CXCL13、FBN2、IFI27、IFI44L、MAGEA6和PTGR1。GSVA 分析揭示了 31 条重要途径。GSEA 在 HRSI 中发现了 87 个基因集，在 LRSI 中发现了 91 个基因集。RNA 表达水平的 GO 和 KEGG 显示，这些基因在 T 细胞活化和细胞因子-细胞因子受体相互作用中最为丰富。结论。肺鳞状细胞癌患者在两组之间具有不同的多组学特征。这些差异可能对放疗效果具有本质意义。