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

doi:10.1016/j.heliyon.2023.e20164

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

Heliyon. 2023 Sep 18;9(9):e20164. doi: 10.1016/j.heliyon.2023.e20164. eCollection 2023 Sep.

Authors

Xu Ran^{1

2}, Lu Tong^{1

2}, Wang Chenghao^{1

2}, Li Qi³, Peng Bo^{1

2}, Zhao Jiaying^{1

2}, Wang Jun⁴, Zhang Linyou¹

Affiliations

¹ Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
² The Second Clinical Medical College, Harbin Medical University, Harbin, China.
³ Department of Child and Adolescent Health, School of Public Health, Harbin Medical University, Harbin, China.
⁴ Department of Thoracic Surgery, Baoji Central Hospital, Baoji, China.

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.

Keywords: Lung adenocarcinoma; Lung cancer; Prognosis prediction; Single-cell RNA-Seq.