Yang Jiajin, Xu Qiuping, Lu Yanjun
Department of Oncology, Fengcheng People's Hospital, Yichun, 331100, Jiangxi Province, China.
Department of Oncology, Ganzhou People's Hospital, No. 17 Hongqi Avenue, Zhanggong District, Ganzhou City, 341000, Jiangxi Province, China.
J Cancer Res Clin Oncol. 2025 Jul 24;151(7):221. doi: 10.1007/s00432-025-06250-6.
Lung adenocarcinoma (LUAD) exhibits significant cellular heterogeneity, yet the precise interactions between epithelial and stromal cells remain unclear. This study integrates single-cell and spatial transcriptomics to delineate tumor microenvironment dynamics, aiming to uncover key cellular subpopulations and their roles in LUAD progression.
We analyzed single-cell RNA sequencing (scRNA-seq) data from 21 LUAD patients and performed spatial transcriptomic deconvolution. Epithelial and fibroblast subpopulations were identified using Seurat and Harmony. Cell-cell communication was inferred via CellChat, while metabolic interactions were assessed using MEBOCOST. Copy number variation (CNV) analysis distinguished malignant cells, and trajectory inference mapped differentiation states. Spatial colocalization was examined via CellTrek. Prognostic signatures were derived from Cox regression, and a six-gene MCI score was validated using survival analysis.
We identified eight epithelial (e.g., MUC21 + Epi, ASCL1 + Epi) and nine fibroblast subpopulations (e.g., Fb_IGFBP4, Fb_COL11A1), with tumor-enriched subsets showing elevated CNVs and metabolic crosstalk. Fb_IGFBP4 correlated with poor prognosis, while MUC21 + Epi exhibited amplified COL1A1/SDC4-mediated interactions with fibroblasts. Pathway analysis highlighted tumor-specific MK and collagen signaling between fibroblasts and epithelial cells, suggesting stromal-epithelial synergy drives progression. Spatial analysis revealed colocalization of epithelial and fibroblast subclusters in tumors, contrasting with normal tissue. The MCI score, derived from six genes (e.g., ADAM10, MARVELD1), independently predicted survival and stratified high-risk patients (AUC > 0.6).
This study identifies key stromal-epithelial subset interactions in LUAD, proposing prognostic biomarkers and therapeutic targets.
肺腺癌（LUAD）表现出显著的细胞异质性，然而上皮细胞和基质细胞之间的确切相互作用仍不清楚。本研究整合单细胞和空间转录组学来描绘肿瘤微环境动态，旨在揭示关键细胞亚群及其在LUAD进展中的作用。
我们分析了来自21例LUAD患者的单细胞RNA测序（scRNA-seq）数据，并进行了空间转录组反卷积分析。使用Seurat和Harmony软件识别上皮细胞和成纤维细胞亚群。通过CellChat推断细胞间通讯，同时使用MEBOCOST评估代谢相互作用。通过拷贝数变异（CNV）分析区分恶性细胞，并通过轨迹推断描绘分化状态。通过CellTrek检查空间共定位。从Cox回归得出预后特征，并使用生存分析验证了六基因MCI评分。
我们识别出8个上皮细胞亚群（例如，MUC21+Epi、ASCL1+Epi）和9个成纤维细胞亚群（例如，Fb_IGFBP4、Fb_COL11A1），肿瘤富集亚群显示出更高的CNV和代谢串扰。Fb_IGFBP4与预后不良相关，而MUC21+Epi表现出COL1A1/SDC4介导的与成纤维细胞相互作用增强。通路分析突出了成纤维细胞和上皮细胞之间肿瘤特异性的MK和胶原蛋白信号传导，表明基质-上皮协同作用驱动肿瘤进展。空间分析揭示了肿瘤中上皮细胞和成纤维细胞亚簇的共定位，与正常组织形成对比。由六个基因（例如，ADAM10、MARVELD1）得出的MCI评分可独立预测生存率，并对高危患者进行分层（AUC>0.6）。
本研究识别出LUAD中关键的基质-上皮亚群相互作用，提出了预后生物标志物和治疗靶点。
