Research Paper Volume 15, Issue 14 pp 7023—7037
Single-cell transcriptomics reveals the drivers and therapeutic targets of lymph node metastasis in lung adenocarcinoma
- 1 Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
- 2 Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- 3 Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Received: May 6, 2023 Accepted: June 30, 2023 Published: July 22, 2023
https://doi.org/10.18632/aging.204890How to Cite
Copyright: © 2023 Ji et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Lymph node metastasis (LNM) is usually the most common metastatic pathway in lung adenocarcinoma (LUAD) and is associated with a poorer prognosis and higher possibility of recurrence. Therefore, discovering the drivers and therapeutic targets of LNM is important for early and non-invasive detection of patients with a high risk of LNM and guiding individualized therapy. Various cell constitutions of the primary tumor and lymph node microenvironment was characterized based on scRNA-seq data. The copy number variation (CNV) analysis was performed to probe clonal structures and origins of metastatic lymph nodes, and found 6q loss and 20q gain may drive LNM in LUAD. Then a LNM-related cell subset, named Scissor+ cells, was identified using the Scissor algorithm. And cell-cell communication network among Scissor+ cells and microenvironment was further analyzed. Besides, a pro-LNM signature was subsequently constructed based on 27 genes using pseudotime trajectory analysis and gene set variation analysis. The pro-LNM signature showed a significant correlation with N stage and a good predictive ability of LUAD survival. At last, we identified that erastin and gefitinib could potentially inhibit LNM by targeting Scissor+ cells based on the drug sensitivity data of the cancer cell lines, which provided new insights for LUAD therapy.
Abbreviations
asLN: lymph node in advanced stage lung adenocarcinoma; asPT: primary tumor in advanced stage lung adenocarcinoma; AUC: area under the curve; BEAM: branch expression analysis modeling; CCL: cancer cell line; CNV: copy number variation; CTRP: Cancer Therapeutics Response Portal; DEG: differential expressed gene; EC: epithelial cell; esLN: lymph node in early stage LUAD; esPT: primary tumor in early stage LUAD; FC: fold change; GEO: Gene Expression Omnibus; GSVA: gene set variation analysis; HMM: hidden Markov model; LN: Lymph node; LNM: lymph node metastasis; LUAD: lung adenocarcinoma; maEC: malignant epithelial cell; NSCLC: non-small-cell lung cancer; OS: overall survival; PCA: principle component analysis; PT: primary tumor; ScRNA-seq: Single-cell RNA sequencing; ssGSEA: Single sample gene set enrichment analysis; t-SNE: t-distributed stochastic neighbor embedding.