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单细胞转录组分析揭示KRAS/TP53驱动的肺腺癌中性粒细胞重编程:多基因预后模型及RHOV的治疗靶点

Single-Cell Transcriptomic Profiling Reveals KRAS/TP53-Driven Neutrophil Reprogramming in Luad: A Multi-Gene Prognostic Model and Therapeutic Targeting of RHOV.

作者信息

Ye Yinghui, Luo Yulou, Sun Yutian, Zhang Yujie, Lin Jiaxin, Yang Ziling, Xu Anping, Xue Bei

机构信息

Department of Laboratory Medicine, Xinhua Hospital, Shenzhen, 518000, China.

Department of Breast Surgery, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, 830000, China.

出版信息

Oncol Res. 2025 May 29;33(6):1383-1404. doi: 10.32604/or.2025.062584. eCollection 2025.


DOI:10.32604/or.2025.062584
PMID:40486872
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12144629/
Abstract

OBJECTIVES: The tumorigenic progression of Lung adenocarcinoma (LUAD), the predominant NSCLC subtype, is predominantly driven by co-occurring mutations in KRAS proto-oncogene (KRAS)/Tumor protein p53 (TP53). However, their impact on tumor microenvironment (TME) heterogeneity, particularly neutrophil dynamics, remains poorly understood. This present study aims to elucidate how KRAS/TP53 mutations reprogram the TME and develop a neutrophil-centric prognostic signature for LUAD. METHODS: Leveraging single-cell RNA sequencing data and transcriptome data, neutrophil subpopulations were identified using Seurat and CellChat R packages, with trajectory analysis via Monocle2 R package. High-dimensional weighted gene co-expression network analysis (hdWGCNA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to generate a prognostic signature. Functional validation included Ras homolog family member V (RHOV) knockdown in A549/H1299 cells using siRNA, were assessed by cell counting kit 8 (CCK8) assay, wound healing assay, and transwell assay. RESULTS: KRAS/TP53-mutated LUAD exhibited increased neutrophil infiltration, particularly IS MUT subtypes with enhanced OSM/CALCR/IL-1 signaling. A five-gene prognostic signature (MS4A1, ANLN, FAM83A, RHOV, KRT6A) stratified patients into high- and low-risk groups with divergent overall survival in the TCGA-LUAD cohort ( < 0.0001). AUCs achieved 0.73, 0.70, and 0.66 at 1-, 3-, and 5-year, respectively. External validation in immunotherapy cohorts (IMvigor210, GSE78220) confirmed the fine predictive capability of the prognostic signature in predicting treatment response. An integrated prognostic nomogram combining clinicopathological features and risk score further improved its clinical utility. Pseudotime analysis found that RHOV was essential for the growth of lung epithelial cells. RHOV knockdown significantly reduced the proliferation, migration, and invasion capabilities of A549/H1299 cells . CONCLUSION: KRAS/TP53 mutations may drive neutrophil heterogeneity in the TME of LUAD, addressing prognostic and therapeutic value. The five-gene signature and RHOV targeting offer translational relevance for risk stratification and therapy. These findings bridge genomic alterations with TME remodeling, advancing precision oncology in LUAD.

摘要

目的:肺腺癌(LUAD)是主要的非小细胞肺癌亚型,其致瘤进展主要由KRAS原癌基因(KRAS)/肿瘤蛋白p53(TP53)的共同突变驱动。然而,它们对肿瘤微环境(TME)异质性的影响,尤其是中性粒细胞动态变化,仍知之甚少。本研究旨在阐明KRAS/TP53突变如何重塑TME,并为LUAD开发以中性粒细胞为中心的预后特征。 方法:利用单细胞RNA测序数据和转录组数据,使用Seurat和CellChat R包鉴定中性粒细胞亚群,并通过Monocle2 R包进行轨迹分析。采用高维加权基因共表达网络分析(hdWGCNA)、单变量Cox回归和最小绝对收缩和选择算子(LASSO)回归分析来生成预后特征。功能验证包括使用小干扰RNA(siRNA)敲低A549/H1299细胞中的Ras同源家族成员V(RHOV),通过细胞计数试剂盒8(CCK8)检测、伤口愈合检测和Transwell检测进行评估。 结果:KRAS/TP53突变的LUAD表现出中性粒细胞浸润增加,特别是具有增强的OSM/CALCR/IL-1信号的IS MUT亚型。一个五基因预后特征(MS4A1、ANLN、FAM83A、RHOV、KRT6A)将TCGA-LUAD队列中的患者分为高风险和低风险组,两组的总生存期存在差异(<0.0001)。1年、3年和5年的受试者工作特征曲线下面积(AUC)分别达到0.73、0.70和0.66。在免疫治疗队列(IMvigor210、GSE78220)中的外部验证证实了该预后特征在预测治疗反应方面的良好预测能力。结合临床病理特征和风险评分的综合预后列线图进一步提高了其临床实用性。伪时间分析发现RHOV对肺上皮细胞的生长至关重要。RHOV敲低显著降低了A549/H1299细胞的增殖、迁移和侵袭能力。 结论:KRAS/TP

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本文引用的文献

[1]
ScRNA-seq reveals novel immune-suppressive T cells and investigates CMV-TCR-T cells cytotoxicity against GBM.

J Immunother Cancer. 2024-4-30

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Integrated analysis of single-cell and bulk RNA-sequencing reveals a novel signature based on NK cell marker genes to predict prognosis and immunotherapy response in gastric cancer.

Sci Rep. 2024-4-1

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Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing.

Lipids Health Dis. 2023-12-2

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Applying machine learning algorithms to develop a survival prediction model for lung adenocarcinoma based on genes related to fatty acid metabolism.

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