Lou Xixian, Xia Hui, Shangguan Zongxiao, Bao Lianmin, Lin Heping
Department of Respiratory Medicine, The Third Affiliated Hospital of Wenzhou Medical University, Rui'an, China.
Ultrasound Imaging Department, The Third Affiliated Hospital of Wenzhou Medical University, Rui'an, China.
Int J Genomics. 2025 Jul 11;2025:9950674. doi: 10.1155/ijog/9950674. eCollection 2025.
Lung adenocarcinoma (LUAD) exhibits a high recurrence rate and an unfavorable prognosis. The role of the starvation-induced tumor microenvironment (TME), which is closely linked to metabolism, remains poorly understood in LUAD. LUAD patient samples were collected from public databases, and starvation response-related genes (SRRGs) were acquired from the MSigDB database. As starvation response may enhance autophagy in cancer cells, the Human Autophagy Database (HADb) was accessed to collect autophagy-related genes (ARGs). Next, the association between the expressions of ARGs and SRRGs was analyzed applying Pearson's algorithm. The SRRG score was calculated by GSVA package for each sample, and WGCNA package was utilized to screen SRRG-related module genes. Differentially expressed lncRNAs between LUAD and control samples were screened by the limma package. Subsequently, the lncRNAs associated with SRRG-related module genes were intersected with differentially expressed lncRNAs to obtain key SRRG-correlated lncRNAs. The number of key lncRNAs in the risk model was optimized by performing univariate and multivariate Cox regression analyses. Next, immune profiling between different LUAD risk groups was conducted using single-sample GSEA (ssGSEA), MCP-counter, and ESTIMATE algorithms. The Mutect2 software and clusterProfiler R package were employed to analyze the mutation profiles and pathway enrichment of patients in different risk groups, respectively. In addition, the expressions of key lncRNAs in LUAD cells were verified by qRT-PCR, and the migratory and invasive capabilities of the cells were measured by wound healing and transwell assays. We identified 162 potential SRRGs linked to autophagy, glycolysis, and starvation responses. In addition, 102 candidate SRRG-related lncRNAs were selected from SRRG-related module genes. Three key SRRG-related lncRNAs (AC023421.1, AL034397.3, and LINC01537) were screened for developing an accurate risk model. Notably, the high-risk group showed a significantly higher mutation rate and oncogenic pathway scores and markedly worse immune infiltration and overall survival (OS). In vitro experiments revealed that LINC01537 was highly expressed in A549 cells, and that after knockdown of LINC01537, the migration and invasion of LUAD cells were suppressed. This study identified three key lncRNAs related to starvation response and created a risk model that can accurately assess the prognosis and immune characteristics in LUAD, offering novel biomarkers and a theoretical basis for the precision immunotherapy and targeted intervention in LUAD.
肺腺癌（LUAD）具有较高的复发率和不良预后。与代谢密切相关的饥饿诱导肿瘤微环境（TME）在LUAD中的作用仍知之甚少。从公共数据库收集LUAD患者样本，并从MSigDB数据库获取饥饿反应相关基因（SRRG）。由于饥饿反应可能增强癌细胞中的自噬，因此访问人类自噬数据库（HADb）以收集自噬相关基因（ARG）。接下来，应用Pearson算法分析ARG和SRRG表达之间的关联。使用GSVA软件包为每个样本计算SRRG评分，并利用WGCNA软件包筛选与SRRG相关的模块基因。通过limma软件包筛选LUAD样本和对照样本之间差异表达的lncRNA。随后，将与SRRG相关模块基因相关的lncRNA与差异表达的lncRNA进行交集分析，以获得关键的与SRRG相关的lncRNA。通过进行单变量和多变量Cox回归分析优化风险模型中关键lncRNA的数量。接下来，使用单样本GSEA（ssGSEA）、MCP-counter和ESTIMATE算法对不同LUAD风险组之间进行免疫分析。分别使用Mutect2软件和clusterProfiler R软件包分析不同风险组患者的突变谱和通路富集情况。此外，通过qRT-PCR验证LUAD细胞中关键lncRNA的表达，并通过伤口愈合实验和Transwell实验检测细胞的迁移和侵袭能力。我们鉴定出162个与自噬、糖酵解和饥饿反应相关的潜在SRRG。此外，从与SRRG相关的模块基因中选择了102个候选的与SRRG相关的lncRNA。筛选出三个关键的与SRRG相关的lncRNA（AC023421.1、AL034397.3和LINC01537）以建立准确的风险模型。值得注意的是，高风险组显示出明显更高的突变率和致癌通路评分，以及明显更差的免疫浸润和总生存期（OS）。体外实验表明，LINC01537在A549细胞中高表达，敲低LINC01537后，LUAD细胞的迁移和侵袭受到抑制。本研究鉴定出三个与饥饿反应相关的关键lncRNA，并创建了一个可以准确评估LUAD预后和免疫特征的风险模型，为LUAD的精准免疫治疗和靶向干预提供了新的生物标志物和理论依据。
