Abstract
Cancer metastasis accounts for the majority of cancer-related deaths and lymph node metastasis is critical in cancer staging and prognosis. However, the mechanisms involved in lymph node metastatic non-small cell lung cancer (NSCLC) remain unclear. Here, we delineate the cellular and spatial landscape of metastatic lymph nodes and their matched primary tumors in NSCLC using multimodal omics. In results, tumor core and peripheral regions respectively exhibit high stemness and elevated expression of immunoglobulins. Increased expressions of CD274 (PD-L1) are observed in the immunoglobulin-high malignant cells and SPP1+IFI30+ macrophages. Notably, residual and tertiary lymphoid structures are identified. However, their anti-tumor immunity is compromised by CXCL13+ T cell exhaustion and immune exclusion. Furthermore, we identify the ferroptosis signaling, with its key factor FTH1 showing strong associations with cancer cell stemness and metastasis. This study elucidates the mechanisms of metastasis and immune evasion in lymph node metastatic NSCLC, providing insights for targeted therapies.
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Data availability
The raw scRNA-seq and ST data generated in this study have been deposited at the Genome Sequence Archive at the National Genomics Data Center (Beijing, China)136 under accession ID HRA009872. The raw sequencing data are available under restricted access for research purposes only, access can be obtained by the DAC (Data Access Committees) of the GSA-human database. According to the guidelines of GSA-human (https://ngdc.cncb.ac.cn/gsa-human/policy), all non-profit researchers can obtain access to the data, and the Principle Investigator of any research group is allowed to apply the data. The access authority can be obtained for Research Use Only. The user can also contact the corresponding author directly. Access requests are typically processed within 2 weeks. Once access has been approved, the data will be available to download for 2 months. The pre-processed scRNA-seq and ST data were deposited on Science Data Bank (https://doi.org/10.57760/sciencedb.19197; https://doi.org/10.57760/sciencedb.19202). The public single-cell RNA sequencing datasets used in this study can be found in Gene Expression Omnibus (GEO) with the accession number GSE127465, GSE123904, GSE131907 and GSE117529, in BioStudies with accession number E-MTAB-13526, from Zenodo (https://zenodo.org/records/8227624) or in the LungCancer website (https://lungcancer.chenlulab.com/#/download). The public ST data of NSCLC can be found in BioStudies with accession number E-MTAB-13530. The public ST data of mLNs in breast cancer can be found in GEO with accession number GSE190811. The ST data of nLN was from 10X Genomics website (https://www.10xgenomics.com/datasets/human-lymph-node-1-standard-1-1-0). Bulk RNA-seq data was from the cancer genome atlas (TCGA) and GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30219; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE68465). Source data are provided with this paper.
Code availability
Code is available from GitHub (https://github.com/diChen310/mLN_NSCLC/, https://doi.org/10.5281/zenodo.18690124)137.
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Acknowledgements
This study is supported by National Natural Science Foundation of China grants (No. 32470832 to H.-l.P., No. 82073286 to H.-X.L.), Liaoning Revitalization Talents Program (XLYC2002035 to H.-l.P.); Liaoning Science and Technology Innovation Funding (20230101-JH2/1013 to H.-l.P.); The Construction of Liaoning Cancer Research Center (Lung Cancer) (2019JH6/10200011 to H.-X.L.); Technological Special Project of Liaoning Province of China (2019020176-JH1/103 to H.-X.L.); Liaoning Provincial Joint Science and Technology Program (Technical R&D Project) (2024JH2/102600187 to S.L.); Innovation program of science and research from the DICP, CAS (DICP I202209 to H-l.P., DICP I202414 to D.C.).
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H.-l.P., D.C. and H.-X.L. conceived the project, H.-l.P. and H.-X.L. supervised the project. D.C., Yawei W., H-.X.L. and H.-l.P. the designed project and Y.L., D.S., S.L. and D.C. performed most of the experiments, D.C. performed computational data analysis, D.C., H.-X.L. and H.-l.P. analyzed data. Q.W., T.F., S.P., Yuhan W., Y.Z., X.S., Z.H., J.L., Y.Z., N.S., W.W., L.Z. and Y.M. provided significant intellectual input. D.C., H.-X.L. and H.-l.P. wrote the manuscript with input from all other authors.
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Chen, D., Liu, Y., Shi, D. et al. Dissecting origin factors of lymph node metastasis in non-small cell lung cancer via multimodal omics. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71819-9
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DOI: https://doi.org/10.1038/s41467-026-71819-9
