Background:Lung adenocarcinoma (LUAD) presents a significant clinical challenge due to its high heterogeneity and limited treatment efficacy, creating an urgent need for reliable prognostic biomarkers and novel therapeutic targets. Integrating functional genomic vulnerabilities with patient multi-omics data offers a promising approach.Methods:We identified genes essential for LUAD cell proliferation from genome-scale CRISPR-Cas9 screening data (DepMap). These were integrated with transcriptomic data from the TCGA-LUAD cohort to select candidate genes. A prognostic risk-score model was constructed using LASSO and multivariate Cox regression analyses and validated in independent GEO datasets. We analyzed the model’s association with clinical features, signaling pathways, tumor immune microenvironment, and drug sensitivity. The predictive value for immunotherapy response was assessed using a real-world cohort. The core gene SPC25 was further validated through in vitro and in vivo experiments and single-cell RNA-seq analysis.Results:A robust 7-gene risk-score model was established. This model effectively stratified patient prognosis in training and validation sets and was an independent prognostic factor. A high-risk score correlated with advanced tumor stage and an immunosuppressive microenvironment. High expression of the signature genes predicted poor immunotherapy response. Functional experiments confirmed that SPC25 knockdown significantly inhibited LUAD cell proliferation, migration, and colony formation. Critically, in vivo xenograft experiments demonstrated that SPC25 depletion markedly suppressed tumor growth. Single-cell sequencing revealed high SPC25 expression in tumor cells and specific immunosuppressive T-cell subsets.Conclusions:We developed a potent prognostic model for LUAD and validated SPC25 as a key oncogene and promising therapeutic target.
背景：肺腺癌（LUAD）因其高度异质性和有限治疗效果而构成重大临床挑战，亟需可靠的预后生物标志物及新型治疗靶点。整合功能基因组学脆弱性与患者多组学数据为此提供了可行路径。 方法：我们基于全基因组CRISPR-Cas9筛选数据（DepMap）鉴定出对LUAD细胞增殖至关重要的基因，并将其与TCGA-LUAD队列的转录组数据整合以筛选候选基因。通过LASSO回归与多变量Cox回归分析构建预后风险评分模型，并在独立GEO数据集中进行验证。进一步分析该模型与临床特征、信号通路、肿瘤免疫微环境及药物敏感性的关联，并利用真实世界队列评估其对免疫治疗反应的预测价值。核心基因SPC25通过体外与体内实验及单细胞RNA测序分析进行深入验证。 结果：成功构建包含7个基因的稳健风险评分模型。该模型在训练集与验证集中均能有效分层患者预后，且为独立预后因素。高风险评分与晚期肿瘤分期及免疫抑制微环境显著相关，特征基因高表达预示免疫治疗反应不佳。功能实验证实敲低SPC25可显著抑制LUAD细胞增殖、迁移及克隆形成能力。关键体内实验表明，SPC25缺失能明显抑制移植瘤生长。单细胞测序分析揭示SPC25在肿瘤细胞及特定免疫抑制性T细胞亚群中高表达。 结论：本研究构建了有效的LUAD预后模型，并验证SPC25作为关键致癌基因及潜在治疗靶点的重要价值。
肿瘤(癌症)患者之家