Single-cell data analysis of malignant epithelial cell heterogeneity in lung adenocarcinoma for patient classification and prognosis prediction
Xu Ran,
Lu Tong,
Wang Chenghao,
Li Qi,
Peng Bo,
Zhao Jiaying,
Wang Jun,
Zhang Linyou
Affiliations
Xu Ran
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; The Second Clinical Medical College, Harbin Medical University, Harbin, China
Lu Tong
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; The Second Clinical Medical College, Harbin Medical University, Harbin, China
Wang Chenghao
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; The Second Clinical Medical College, Harbin Medical University, Harbin, China
Li Qi
Department of Child and Adolescent Health, School of Public Health, Harbin Medical University, Harbin, China
Peng Bo
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; The Second Clinical Medical College, Harbin Medical University, Harbin, China
Zhao Jiaying
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; The Second Clinical Medical College, Harbin Medical University, Harbin, China
Wang Jun
Department of Thoracic Surgery, Baoji Central Hospital, Baoji, China
Zhang Linyou
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Corresponding author.
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.
