肺腺癌单细胞数据集GSE189357复现系列之十：联合bulk数据进行细胞亚群预后验证

TL;DR - This tutorial integrates lung adenocarcinoma single-cell dataset GSE189357 with TCGA-LUAD bulk RNA-seq and survival data to assess the prognostic relevance of tumor epithelial subpopulations. It provides a reproducible GSVA and Kaplan–Meier workflow for translating cell-level signatures into clinically testable biomarkers.

• Single-cell epithelial-subcluster marker genes are converted into gene sets and scored across TCGA-LUAD tumors using GSVA.
• Clinical validation uses Kaplan–Meier analyses with both median-based and optimized cutoffs after excluding samples with missing survival data or follow-up under 30 days.
• The workflow separately evaluates UBE2C, associated with a proliferative tumor subpopulation, as a candidate overall-survival marker.
• The article presents methodology and code but does not provide enough reported statistics here to establish prognostic significance.