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BACKGROUND

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality. Protein succinylation, a key post-translational modification, is implicated in tumor progression. However, its comprehensive landscape and clinical significance in LUAD remain largely unexplored.

METHODS

We integrated multi-omics data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts. A set of core succinylation-related genes was identified through differential expression and univariable Cox regression analyses. Molecular subtypes based on succinylation were determined by principal component analysis (PCA). A succinylation prognostic model was constructed via least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression. The differences of tumor microenvironment (TME), tumor mutation burden and drug sensitivity in different risk groups were further explored. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics revealed effects of succinylation on TME. High-dimensional weighted gene co-expression networks analysis (hdWGCNA) was used to identify potential succinylation-related therapeutic targets. The function of therapeutic targets was further validated through scRNA-seq, spatial transcriptomics, and experiments.

RESULTS

We identified 31 core succinylation-related genes and defined three molecular subtypes with distinct prognostic and TME characteristics. A robust 7-gene succinylation-based prognostic signature was developed and validated across 7 independent GEO cohorts, effectively stratifying patients into high- and low-risk groups with significant differences in survival, demonstrating high predictive accuracy, consistency, and clinical utility. The low-risk group exhibited an immunoreactive TME with enhanced immune cell infiltration and superior response to immunotherapy. scRNA-seq and spatial transcriptomics revealed enhanced succinylation in LUAD. Kallikrein-related peptidase 6 (KLK6) was identified as a potential therapeutic target. KLK6 was significantly upregulated in LUAD, correlated with poor prognosis and therapy resistance. KLK6 promoted global succinylation, proliferation, migration, and invasion of LUAD cells . Mechanistically, KLK6-positive tumor cells might foster an immunosuppressive TME by driving fibroblast-to-myofibroblast differentiation, enhancing extracellular matrix (ECM) deposition, and inhibiting CD8 T cell infiltration.

CONCLUSION

Our study delineates the succinylation landscape in LUAD, establishes a novel prognostic model for risk stratification and immunotherapy prediction. Meanwhile, we identified KLK6 as a potential promoter of tumor progression and immunosuppression. Targeting the succinylation pathway, particularly KLK6, may represent a promising therapeutic strategy for LUAD.

BACKGROUND

METHODS

RESULTS

CONCLUSION

背景

肺腺癌（LUAD）是癌症相关死亡的主要原因。蛋白质琥珀酰化是一种关键的翻译后修饰，与肿瘤进展有关。然而，其在LUAD中的全面概况和临床意义在很大程度上仍未得到探索。

方法

我们整合了来自癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）队列的多组学数据。通过差异表达和单变量Cox回归分析确定了一组核心琥珀酰化相关基因。基于琥珀酰化的分子亚型通过主成分分析（PCA）确定。通过最小绝对收缩和选择算子（LASSO）和多变量Cox回归构建了琥珀酰化预后模型。进一步探讨了不同风险组中肿瘤微环境（TME）、肿瘤突变负担和药物敏感性的差异。单细胞RNA测序（scRNA-seq）和空间转录组学揭示了琥珀酰化对TME的影响。高维加权基因共表达网络分析（hdWGCNA）用于识别潜在的琥珀酰化相关治疗靶点。通过scRNA-seq、空间转录组学和实验进一步验证了治疗靶点的功能。

结果

我们确定了31个核心琥珀酰化相关基因，并定义了三种具有不同预后和TME特征的分子亚型。开发了一个强大的基于7个基因的琥珀酰化预后特征，并在7个独立的GEO队列中进行了验证，有效地将患者分为高风险和低风险组，生存率有显著差异，显示出高预测准确性、一致性和临床实用性。低风险组表现出免疫反应性TME，免疫细胞浸润增强，对免疫治疗反应更佳。scRNA-seq和空间转录组学揭示了LUAD中琥珀酰化增强。激肽释放酶相关肽酶6（KLK6）被确定为一个潜在的治疗靶点。KLK6在LUAD中显著上调，与预后不良和治疗耐药相关。KLK6促进LUAD细胞的整体琥珀酰化、增殖、迁移和侵袭。从机制上讲，KLK6阳性肿瘤细胞可能通过驱动成纤维细胞向肌成纤维细胞分化、增强细胞外基质（ECM）沉积和抑制CD8 T细胞浸润来促进免疫抑制性TME。