Single-cell data analysis of malignant epithelial cell heterogeneity in lung adenocarcinoma for patient classification and prognosis prediction

肺腺癌恶性上皮细胞异质性的单细胞数据分析用于患者分类和预后预测

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作者:Xu Ran, Lu Tong, Wang Chenghao, Li Qi, Peng Bo, Zhao Jiaying, Wang Jun, Zhang Linyou

Abstract

Lung cancer is one of the leading causes of cancer-related death. Most advanced lung adenocarcinoma (LUAD) patients have poor survival because of drug resistance and relapse. Neglecting intratumoral heterogeneity might be one of the reasons for treatment insensitivity, while single-cell RNA sequencing (scRNA-seq) technologies can provide transcriptome information at the single-cell level. Herein, we combined scRNA-seq and bulk RNA-seq data of LUAD and identified a novel cluster of malignant epithelial cells - KRT81+ malignant epithelial cells - associated with worse prognoses. Further analysis revealed that the hypoxia and EMT pathways of these cells were activated to predispose them to differentiate into metastatic lung adenocarcinoma cells. Finally, we also studied the role of these tumor cells in the immune microenvironment and their role in the classification and prognosis prediction of lung adenocarcinoma patients.

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