The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, China.
Cancer Control. 2024 Jan-Dec;31:10732748241237414. doi: 10.1177/10732748241237414.
The aim of this retrospective research was to develop an immune-related genes significantly associated with m5C methylation methylation (m5C-IRGs)-related signature associated with lung adenocarainoma (LUAD).
We introduced transcriptome data to screen out m5C-IRGs in The Cancer Genome Atlas (TCGA)-LUAD dataset. Subsequently, the m5C-IRGs associated with survival were certificated by Kaplan Meier (K-M) analysis. The univariate Cox, least absolute shrinkage and selection operator (LASSO) regression, and xgboost.surv tool were adopted to build a LUAD prognostic signature. We further conducted gene functional enrichment, immune microenvironment and immunotherapy analysis between 2 risk subgroups. Finally, we verified m5C-IRGs-related prognostic gene expression in transcription level.
A total of 76 m5C-IRGs were identified in TCGA-LUAD dataset. Furthermore, 27 m5C-IRGs associated with survival were retained. Then, a m5C-IRGs prognostic signature was build based on the 3 prognostic genes (HLA-DMB, PPIA, and GPI). Independent prognostic analysis suggested that stage and RiskScore could be used as independent prognostic factors. We found that 4104 differentially expressed genes (DEGs) between the 2 risk subgroups were mainly concerned in immune receptor pathways. We found certain distinction in LUAD immune microenvironment between the 2 risk subgroups. Then, immunotherapy analysis and chemotherapeutic drug sensitivity results indicated that the m5C-IRGs-related gene signature might be applied as a therapy predictor. Finally, we found significant higher expression of PPIA and GPI in LUAD group compared to the normal group.
The prognostic signature comprised of HLA-DMB, PPIA, and GPI based on m5C-IRGs was established, which might provide theoretical basis and reference value for the research of LUAD.
TCGA-LUAD dataset was collected from the TCGA (https://portal.gdc.cancer.gov/) database, GSE31210 (validation set) was retrieved from GEO (https://www.ncbi.nlm.nih.gov/geo/) database.
本回顾性研究旨在开发与 m5C 甲基化（m5C-IRGs）相关的基因特征，以关联肺腺癌（LUAD）。
我们引入转录组数据从癌症基因组图谱（TCGA）-LUAD 数据集中筛选 m5C-IRGs。随后，通过 Kaplan-Meier（K-M）分析验证与生存相关的 m5C-IRGs。采用单变量 Cox、最小绝对值收缩和选择算子（LASSO）回归和 xgboost.surv 工具构建 LUAD 预后签名。我们进一步在 2 个风险亚组之间进行基因功能富集、免疫微环境和免疫治疗分析。最后，我们在转录水平验证 m5C-IRGs 相关的预后基因表达。
在 TCGA-LUAD 数据集中鉴定出 76 个 m5C-IRGs，其中 27 个 m5C-IRGs 与生存相关。然后，基于 3 个预后基因（HLA-DMB、PPIA 和 GPI）构建了 m5C-IRGs 预后签名。独立预后分析表明，分期和风险评分可以作为独立的预后因素。我们发现，2 个风险亚组之间有 4104 个差异表达基因（DEGs），主要涉及免疫受体途径。我们发现，2 个风险亚组之间的 LUAD 免疫微环境存在一定差异。然后，免疫治疗分析和化疗药物敏感性结果表明，m5C-IRGs 相关基因特征可能作为治疗预测指标。最后，我们发现 LUAD 组中 PPIA 和 GPI 的表达明显高于正常组。
基于 m5C-IRGs 构建的 HLA-DMB、PPIA 和 GPI 预后签名，为 LUAD 的研究提供了理论依据和参考价值。
TCGA-LUAD 数据集从 TCGA（https://portal.gdc.cancer.gov/）数据库收集，GSE31210（验证集）从 GEO（https://www.ncbi.nlm.nih.gov/geo/）数据库检索。
