Single-cell transcriptomics analysis of primary lung adenocarcinoma and lymph node metastatic tumors

Single-cell transcriptomics analysis of primary lung adenocarcinoma and lymph node metastatic tumors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Single-cell transcriptomics analysis of primary lung adenocarcinoma and lymph node metastatic tumors Shuai Zhang, Xiaoying Jin, Changzheng Li, Yuechao Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6456043/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Although the microenvironment of lymph node metastatic tumors (LNMTs) plays a critical role in the pathogenesis of cancer, systematic studies on the microenvironment of LNMTs in lung adenocarcinoma (LUAD) are lacking. The present study analyzed the single-cell profiles of primary tumors (PTs) and LNMTs in patients with LUAD. The abnormalities in LUAD cells, B cells, T cells, and macrophages in LUAD were additionally analyzed at the single-cell level. The findings revealed that compared to that of the PTs group, the proportion of B cells and macrophages was elevated in the LNMTs group, while the proportion of T and LUAD cells was reduced. These results demonstrated the occurrence of immunosuppression in the microenvironment of LNMTs, and the cell subpopulations were subsequently analyzed to elucidate the underlying changes and associated pathways. The results showed that the abundance of the CREM + CD8 + T cell subset was significantly reduced in LNMTs, whereas the proportion of HP + LUAD cells was significantly increased. In conclusion, the present study characterized the microenvironment of PTs and LNMTs, which may aid in the development of personalized therapeutic strategies for patients with LUAD presenting with lymph node metastases. Biological sciences/Cancer/Cancer genomics Biological sciences/Cancer/Lung cancer/Non small cell lung cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction According to the latest statistics, lung cancer is the leading cause of cancer-related deaths worldwide [ 1 ] . Lung cancer is primarily categorized into two types, namely, small cell lung cancer (SCLC) and non-SCLC (NSCLC) [ 2 ] . NSCLC can be further subdivided into three distinct subtypes, namely, adenocarcinoma, squamous cell carcinoma, and large cell carcinoma [ 3 ] . Lung adenocarcinoma(LUAD) is the most common type of lung cancer, and accounts for approximately 35–40% of all cases of lung cancer [ 4 ] . Despite significant improvements in therapeutic strategies, less than 20% of patients with LUAD have a 5-year survival rate [ 5 ] . Metastasis is a hallmark of cancer cells, and is one of the leading causes of mortality in patients with cancer [ 6 ] . Lymph nodes (LNs) are typically the first sites for metastasis in lung cancer, and the infiltration of tumor cells into lymphatic vessels often implies poor prognosis and a higher rate of local and/or distant recurrence [ 7 ] . The microenvironment of LN metastatic tumors (LNMTs) is considered immunosuppressive; however, the characteristics of the various immune cells within the microenvironment and the precise mechanisms of action remain to be elucidated [ 8 ] . It has been observed that metastasized LNs can affect the immune response of the tumor [ 9 ] . It is therefore imperative to perform comparative analyses and summarize the characteristics of the microenvironments of LNMTs and primary tumors (PTs) by characterizing and identifying the differences between the respective microenvironments. The single-cell sequencing technology is used to sequence and analyze genomes, transcriptomes, and epigenomes at the single-cell level [ 10 ] . This novel approach addresses the limitations of traditional sequencing technologies and enables a more precise investigation of the genetic heterogeneities associated with tumorigenesis, tumor progression, and metastasis [ 11 ] . By mapping single cells in the tumor microenvironment (TME), identifying new cell subtypes, and analyzing cell-cell interactions within tumors, the investigators provided insights into advanced NSCLC [ 12 ] . Based on multi-group data, the present study investigated the differences between the microenvironments of PTs and LNMTs in patients with LUAD, and elucidated the regulatory mechanisms within the TME that induce the metastasis and colonization of LNs by tumor cells. The findings revealed that the population of B cells, macrophages, and other cells was significantly elevated in the microenvironment of LNMTs, compared to that of PTs. The underlying molecular regulatory mechanisms were subsequently analyzed herein, and the findings may provide novel insights for inhibiting LNs metastases in LUAD. Materials and methods Data source The single-cell transcriptomic data for LUAD were retrieved from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), accession number: GSE131907. The dataset had been generated using the GPL16791 microarray platform, and consists of data pertaining to 58 samples from 44 patients with a pathological diagnosis of LUAD. Of these 58 tissue samples, 11 tumor tissues, 11 distant normal lung tissues, 10 normal LNs, and 10 metastatic brain tissue specimens had been obtained from patients with LUAD who had not received prior treatment. The dataset also comprised 7 metastatic LNs and 4 samples of lung tumor tissue obtained from patients with advanced LUAD by endobronchial ultrasound and bronchoscopy, as well as 5 samples of pleural fluid obtained from patients with LUAD who presented with malignant pleural effusion. The dataset additionally contained 4 samples of primary LUAD and 7 samples of LNMT. Processing of ScRNA-Seq data In this study, the single-cell expression profiles in the target dataset were combined using the IntegrateData function in the Seurat package of R software. The cells were analyzed based on the RNA-Seq data using the Seurat package of R software, and visualized using the UMAP method. The clusters with similar marker gene profiles were consolidated into a single cell type for defining the marker genes in the respective clusters. Construction of a single-cell maps The single-cell maps were constructed for cell clustering using the Seurat package of R software, with default parameters. The single-cell data were integrated using the Integrate Data function and subsequently clustered using the Find Clusters function. The Find Clusters function first computes the k-nearest neighbors and constructs a shared nearest neighbor (SNN) graph using the SNN clustering algorithm. It then optimizes the modularity function to establish the final clusters. The results of clustering were uniformly visualized using the UMAP method. Re-clustering of LUAD cells, macrophages , and T and B cells The LUAD cells, macrophages, T cells, and B cells were reintegrated and reaggregated using the Seurat package of R software. These cell types were subjected to a second clustering step using the same methodology in Seurat. The re-clustering was performed in adherence to the same procedural framework as the first clustering step, and the resolution ranged from 1 to 7. The resultant cell types were subsequently annotated based on established subcluster labels. Analysis of different gene expression Differential gene expression analysis was conducted using the Find Markers function in the Seurat package of R software. The genes that were differentially expressed between LNMTs and PTs, across the various cell types, were subsequently identified. A significance threshold of P < 0.05 was established for identifying the significant differences in gene expression. Identification of marker genes The marker genes were subsequently identified using the FindAllMarker function in the Seurat package of R software. The potential marker genes were identified by comparing the individual cell clusters against all the other cell clusters using the FindAllMarker function. The cells within each cluster were treated as duplicates for effective analyses of differential gene expression using statistical tests. By default, the Wilcoxon Rank Sum test was used for analyzing differential gene expression. Functional enrichment analysis The differentially expressed genes were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the clusterProfiler package in R for identifying the potential functions of the respective cell subsets. The functions or pathways were deemed significantly enriched when P < 0.05. The Benjamin-Hochberg procedure was employed to ensure that the false discovery rate remained within a certain range. The results of functional enrichment analyses were visualized using cluster bubble plots. Data analyses and statistical evaluation The data were analyzed in this study using the cloud-based Bioinforcloud platform (http://www.bioinforcloud.org.cn). Results Single-Cell Mapping of LUAD For constructing the single-cell profiles, the data obtained by single-cell sequencing were initially subjected to quality control analysis and normalization studies. The IntegrateData function was used for single-cell clustering, and the Uniform Manifold Approximation and Projection (UMAP) strategy was employed for dimensionality reduction and visualization. The expression profiles of 108,341 high-quality single cells were finally obtained, which were subsequently delineated into 36 cell clusters (Fig. 1 A). The genes that were differentially expressed between the PTs and LNMTs across the various cell types were identified by differential expression analysis (Fig. 1 B). The findings revealed that the cell clusters primarily comprised B cells, macrophages, T cells, and LUAD cells, and they expressed the corresponding cellular markers (Fig. 1 C, D). The alterations in the proportions of various progressed cell types between PTs and LNMTs were subsequently analyzed, and the findings revealed that compared to those of the PT group, the proportion of B cells and macrophages was higher in the LNMT group, while the proportion of T and LUAD cells was lower (Fig. 1 E). It has been demonstrated that LN metastasis can suppress T cell-mediated cytotoxicity and generate tumor-specific immune tolerance to promote the colonization of distant tumors, which was validated by the findings obtained herein. Abnormal Components of LUAD cells in Patients with LUAD Metastasis is a biological process that ensures the continued growth of cancer cells [ 13 ] . Cancer cells primarily metastasize via two systems, namely, the circulatory and the lymphatic system [ 14 ] . The potential mechanisms underlying hematogenous metastasis have been extensively studied and documented in the past decades; however, the molecular mechanisms driving lymphatic metastasis are yet to be elucidated. In order to ensure the heterogeneity of LUAD in the different groups, LUAD cells were re-clustered in this study to obtain 10 cellular clusters (Fig. 2 A). The abundance of the different subpopulations of LUAD cells in the different tumor tissues was subsequently mapped by single-cell mapping (Fig. 2 B). The differences in the cellular composition of LUAD between PTs and LNMTs were comparatively analyzed, which revealed that the cellular makeup of LUAD in patients with LNMTs varied considerably from those with PTs, as reflected in the variations in cell subpopulations (Fig. 2 C). The single-cell profiles of the subpopulations that expressed specific marker genes are depicted in Fig. 2 D and Fig. S1, and the findings indicated that the marker genes were highly expressed in specific cell subpopulations (Fig. 2 E and Fig. S1). Among them, the proportions of HP + LUAD and AIF1 + LUAD cell subpopulations were significantly higher and the proportion of SETPC + LUAD cell subpopulations was significantly lower in LNMTs compared with PTs, revealing a new potential molecular mechanism for inhibiting lymph node metastasis in LUAD. Functional enrichment analysis of genes has become a standard approach for analyzing high-throughput genomics data, and provides key insights into the underlying molecular mechanisms in biomedical analyses. In this study, the differentially expressed genes were subjected to KEGG enrichment analyses for determining the potential functions of the different cellular subpopulations. The HP + LUAD cells may be involved in regulating the formation of Focal Adhesion, which is thought to modulate a variety of functions that regulate tumor cells, including proliferation, survival, migration, invasion, and stemness (Fig. 2 F) [ 15 ] . Consistently, the AIF1 + LUAD cells were predicted to modulate the expression of cell adhesion molecules, revealing its facilitating role in tumor cell metastasis to lymph nodes (Fig. 2 F). It has been demonstrated that cancer stem cells play critical roles in tumor initiation, growth, metastasis, recurrence, and drug resistance in various types of cancer [ 16 ] .Cell subpopulations with varying degrees of stemness may exhibit different metastatic characteristics. Therefore, the stemness counts of the different LUAD cell subpopulations were estimated in this study by single-cell mapping (Fig. 2 G). Cells undergo state transitions throughout their life processes, and their gene expression profiles vary across these different states [ 17 ] . The developmental trajectories of the LUAD cell subgroups were subsequently inferred based on the changes in gene expression (Fig. 2 H). Abnormal Components of CD8 + T cells in Patients with LUAD CD8 + T cells play an essential role in anti-tumor immunity, and their depletion is frequently associated with a reduction in anti-cancer efficacy [ 18 ] . The reduced infiltration of CD8 + T cells is thought to be associated with LNs metastasis in a variety of tumors [ 19 ] . In this study, the CD8 + T cells were delineated into 10 cell clusters, and the resulting single-cell mapping data were plotted and visualized (Fig. 3 A). Analysis of the CD8 + T cell projections demonstrated heterogeneity between patients with PTs and those with LNMTs (Fig. 3 B). The differences in the proportions of CD8 + T cells in LUAD tissues between the PTs and LNMTs groups are presented in Fig. 3 C. The findings revealed that compared to that of the PTs group, the expression of FGFBP2 and CD160 increased significantly in the LNMTs group, while that of CREM decreased significantly, indicating their involvement in LNs metastasis in LUAD (Fig. 3 D). The other markers of CD8 + T cell subpopulations were additionally mapped by single-cell mapping (Fig. S2). The expression levels of specific genes in the different cell subpopulations are depicted in Fig. 3 E and Fig. S2. Furthermore, functional analyses revealed that these specific subpopulations were predominantly involved in pathways related to tumor metastasis, including cell adhesion, NK cell-mediated cytotoxicity, and the TNF signaling pathway. The pathways involved in the regulation of different CD8 + T cell clusters were additionally determined (Fig. 3 F). The stemness counts of the CD8 + T cell subpopulations and their developmental trajectories were additionally plotted based on the single-cell mapping data (Fig. 3 G–H). Abnormal Components of CD4 + T cells in Patients with LUAD CD4 + T cells represent a specialized subset of lymphocytes that are produced by the thymus, and they play crucial roles in the immune response. These cells can independently eliminate tumors, but their primary function is to activate other cells and generate a prolonged memory CTL response [ 20 ] . The re-clustering of CD4 + T cells led to the identification of 9 cell clusters (Fig. 4 A), and the distribution of these different cell clusters in PTs and LNMTs was determined by single-cell mapping (Fig. 4 B). The differences in the abundance of the different cell subpopulations between PTs and LNMTs were comparatively analyzed using stacked bar graphs (Fig. 4 C). Specifically, when compared to PTs, certain cell subpopulations such as CCL4, CD14, CXCL9, SPP1, and S100B exhibited a significant elevation in LNMTs. In contrast, the subpopulations of CORO1A, CCL18, RETN, and PDLIM1 were markedly reduced in LNMTs. The different markers specifically expressed by the different cell subpopulations were determined by single-cell mapping and depicted using violin plots (Fig. 4 D–E and S3 ). The KEGG pathways that were significantly enriched in the different CD4 + T cell subpopulations were depicted using bubble plots (Fig. 4 F). The NF-κB, TNF, IL-17, and chemokine signaling pathways are recognized as crucial signaling pathways that are regulated by CD4 + T cell subpopulations in LUAD. The stemness counts of the different CD4 + T cell subsets were further determined by single-cell mapping (Fig. 4 G). The developmental trajectories of the different subsets of CD4 + T cells are depicted in Fig. 4 H. Abnormal Components of B cells in Patients with LUAD B cells play a significant role in tumor metastasis by facilitating the dissemination of cancer cells via the enhancement of tumor cell motility, invasion, angiogenesis, and other related processes [ 21 ] . Conversely, it has been demonstrated that B cells can also exhibit anti-metastatic effects. For instance, they have been shown to play a critical role in enhancing antigen presentation, which in turn activates anti-cancer immune responses. The present study revealed that unlike CD8 + T cells, the proportion of B cells decreased in LNMTs, suggesting that they may promote the metastases of tumor cells to LNs. The B cells were categorized into 9 clusters (Fig. 5 A), and the differences in the proportion B cell subpopulations between PTs and LNMTs were additionally investigated (Fig. 5 B–C). Specifically, the expression of TCL1A and HLA-DRB5 were found to be upregulated in the LNMTs, while the expression of IL-32 was downregulated, compared to that of the PTs. Analysis of the single-cell expression profiles of the marker genes (Fig. 5 D and Fig. S4) revealed that their expression levels were upregulated in specific cell subsets (Fig. 5 E and S4 ). Pre-concentration analysis of the cells revealed that certain subpopulations were involved in multiple processes (Fig. 5 F). The stemness scores of the different B cell subpopulations were determined by single-cell mapping (Fig. 5 G). The developmental trajectories of the B cell subpopulations were additionally constructed and analyzed in this study (Fig. 5 H). Abnormal Components of macrophages in Patients with LUAD Tumor-associated macrophages (TAMs) constitute a major immune cell population in the TME, and can enhance the proliferative and migratory potential of tumor cells. They can also promote the invasion and metastasis of tumor cells via various mechanisms, including polarization, release of pro-migratory factors, and induction of angiogenesis and immunosuppression [ 22 ] . In this study, the macrophages were delineated into 9 clusters (Fig. 6 A), and analysis of the macrophage projections revealed heterogeneity between PTs and LNMTs (Fig. 6 B). The differences in the proportions of different cells between the PT and LNMT groups are depicted in Fig. 6 C. The markers that were specifically expressed in the different cell clusters are depicted in Fig. 6 D–E and Fig. S5. Pathways regulated by different macrophage subpopulations are mainly involved in protein production and transport, metabolic diseases (Fig. 6 F). The stemness scores of the macrophage subpopulations were determined by single-cell mapping (Fig. 6 G). The developmental trajectories of macrophage subpopulations were additionally determined and analyzed (Fig. 6 H). Discussions The single-cell sequencing technique provides a robust and sophisticated approach for advancing fundamental research in tumor biology, and is being increasingly employed for exploring the cellular and molecular characteristics linked to tumor progression and the TME [ 23 ] . The ongoing interactions between tumor cells and the TME play crucial roles in tumorigenesis, tumor progression, metastasis, and therapeutic response [ 24 ] . The TME has been extensively researched and has attracted significant clinical attention as a therapeutic target for various tumors [ 25 ] . The previous studies that employed the single-cell sequencing strategy for exploring the characteristics of the TME in LUAD have focused on the molecular features of tumorigenesis and tumor progression [ 26 ] . However, the microenvironment of metastasized LNs in LUAD has not been examined at the single-cell level to date. Therefore, the present study systematically analyzed the characteristics and differences between the TME of LNMTs and paired PTs in LUAD. During cancer progression, the TME transforms into an immunosuppressive environment that is more conducive to tumor growth [ 27 ] .Immune infiltration is a prominent focus in tumor research, and the findings may hold immense clinical significance [ 28 ] . Immune infiltration is associated with the metastasis of tumor cells into LNs [ 29 ] . Although the clinical and pathological characteristics associated with immune cell infiltration have been explored [ 30 ] , the processes that drive immune cell infiltration and the mechanisms underlying the differences in the degree of infiltration between PTs and LNMTs remain to be elucidated. Although several studies have confirmed that the activity of CD8 + T cells is lower in LNMTs than in PTs [ 31 ] , the present study further characterized the differences in the phenotypes and features of CD8 + T cells, including the variations in CD8 + T cell subsets and developmental pathways, between LNMTs and PTs. Our findings revealed that the abundance of CD8 + CREM + T cells reduced significantly in LNMT. CREM is predominantly expressed in fatigued CD8 + T cells, and primarily promotes the depletion of T cells in the TME [ 32 ] . However, the mechanisms underlying the depletion of CD8 + T cells by CREM and the subsequent induction of tumor cell metastasis to LNs remain to be elucidated to date. In addition, cell adhesion contributed to lymph nodes metastasis in varies kinds of cancers which was in accord with our present study [ 33 ] . Thus, our data suggest a novel sight in LNMTs in CD8 + T cell subpopulation which was relate to LUAD progression. In this study, the proportion of CD4 + T cells also decreased significantly in LNMTs, which induced the development of an immunosuppressive environment. Further analysis of the single-cell sequencing data revealed that the CD4 + CXCL9 + cells promoted the metastasis of tumor cells into LNs, which was consistent with the findings of previous studies on other tumors [ 34 ] . The B cell subpopulations in the PTs and LNMTs were additionally analyzed herein, and the differentially expressed genes were subsequently identified. The obtained findings provided a basis for subsequent investigation of the mechanisms underlying the inhibition of tumor metastasis by targeting B cells [ 35 ] . Despite the observable decrease in the proportion of LUAD cells, a more in-depth investigation into the alterations induced by specific markers can enhance our understanding of the complex mechanisms underlying tumor cell metastasis. The significant increase in the proportion of HP + LUAD cells implies that HP may play an important role in promoting tumor cell metastasis; however, further molecular biology studies and in vivo experiments are necessary for validation. To sum up, the present study on LUAD revealed that the activity of immune cells in LNMTs is reduced compared to that of PTs, and the molecular mechanisms underlying the differences in immune activity were further analyzed. However, further mechanistic studies are essential for obtaining precise insights into the increased invasive and proliferative potential of tumor cells within LNs. The findings highlight the distinct characteristics of the TMEs of LNMTs and PTs, which may facilitate the development of personalized therapies for TME-specific targeting in patients with LUAD. Conclusion By integrating and analyzing single-cell sequencing data, we found that the activity of immune cells in LNMTs is reduced compared to that of PTs. The CD8 + CREM + T cells and CD4 + CXCL9 + cells are major drivers of tumor cell metastasis from the PTs to the LNs. The HP + LUAD cells may also play an important role in promoting tumor cell metastasis. Declarations Data availability statement All data generated or analyzed during this study are included in the published article or are available from the corresponding author upon reasonable request. Author contributions Shuai Zhang: Writing – review & editing, Writing – original draft, Formal analysis, Data curation, Conceptualization. Xiaoying Jin: Project administration, Methodology, Formal analysis. Changzheng Li: Writing – original draft, Visualization, Investigation, Conceptualization. Yuechao Liu: Writing – original draft, Visualization, Investigation, Funding acquisition, Data curation, Conceptualization. Funding This work was supported by grants from the Young Talent Cultivation Project of Cancer Hospital of Shandong First Medical University (2024-QH07). 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Front Cell Dev Biol, 2021,9: 697748. Meves A, Nikolova E, Heim JB, Squirewell EJ, Cappel MA, Pittelkow MR, Otley CC, Behrendt N, Saunte DM, Lock-Andersen J, Schenck LA, Weaver AL, Suman VJ. Tumor Cell Adhesion As a Risk Factor for Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma. J Clin Oncol, 2015,33(23): 2509-2515. Su X, Liang C, Chen R, Duan S. Deciphering tumor microenvironment: CXCL9 and SPP1 as crucial determinants of tumor-associated macrophage polarity and prognostic indicators. Mol Cancer, 2024,23(1): 13. Additional Declarations No competing interests reported. Supplementary Files SuppFig.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6456043","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":451593629,"identity":"ca7b8144-090a-4ca1-a9e0-cff8c646cc4f","order_by":0,"name":"Shuai Zhang","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Zhang","suffix":""},{"id":451593630,"identity":"9ff8e639-cc3c-44de-a477-91bc5dc8b8ca","order_by":1,"name":"Xiaoying Jin","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xiaoying","middleName":"","lastName":"Jin","suffix":""},{"id":451593631,"identity":"abb7900f-386e-4c04-bf45-830bef1436cc","order_by":2,"name":"Changzheng Li","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Changzheng","middleName":"","lastName":"Li","suffix":""},{"id":451593632,"identity":"b156ade1-0de7-4f99-b249-4618e22020a3","order_by":3,"name":"Yuechao Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYBACPmYIncDAwNj44EOFDQ8/fwN+LWwILczNhjPOpMlIzjhAQAsDXAt7mzRv22Ebg4YEAlrYecykeSrs8vjbG9ukedjO8xgwHGD88DEHn8NAWs4kF0ucOdhsOYfnNo85cwOz5MxtBLTwth1IbLiR2HjjjcRtHsuGA2zMvAS1/DuQOP9GYoMEj8E5HoMDCcRoaTiQuOFGYpMkT8IBYrSwFVvOOZacuBHoF8MZB5J5JGccbMbrF37+wxtvvKmxS5x3vP3hg4//7Oz5+ZsPfviIRwsQsEigCTA24FUPBMwfCKkYBaNgFIyCEQ4ACXNQdU5M/jgAAAAASUVORK5CYII=","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Yuechao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-04-15 14:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6456043/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6456043/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82143519,"identity":"04b4d26f-6965-4ed9-a118-c2587cd71772","added_by":"auto","created_at":"2025-05-07 06:41:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2263836,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal single-cell spectrum of LUAD. \u003c/strong\u003eA. The comprehensive global single-cell spectrum of LUAD, comprising 108,341 cells distributed across 36 distinct clusters. B. Volcano plots depicting the genes that were differentially expressed between PTs and LNMTs across the different cell subsets. C. A total of 36 clusters comprising distinct cell types were categorized based on established marker genes. D. Cell clusters expressing specific marker genes are depicted with bubble plots. E.The proportions of different cell subpopulations in the PTs and LNMTs are compared in the bar graph.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/1dabda682a7ec755f8d5c670.png"},{"id":82146900,"identity":"ab473978-ebe4-403d-b590-590818b316dc","added_by":"auto","created_at":"2025-05-07 06:57:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2365198,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormal components of LUAD cells in patients with LUAD. \u003c/strong\u003eA. Single-cell mapping of LUAD cell subpopulations. B. Single-cell mapping of LUAD cells during disease progression. C. Alterations in the components and LUAD cell subsets during the progression of LUAD. D, E. Expression profiles of marker genes across the different subpopulations of LUAD cells. F. Biological pathways associated with specific changes in LUAD cell subpopulations. G. Single-cell analysis of the stemness characteristics of LUAD cells. \u0026nbsp;H. Results of single-cell mapping depicting the developmental trajectory of LUAD cells.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/fdebb8450f805bc6b4b5a99d.png"},{"id":82143522,"identity":"7a538f89-af55-45da-a26f-5c9063a565ce","added_by":"auto","created_at":"2025-05-07 06:41:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2894479,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormal components of CD8\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eT cells in patients with LUAD. \u003c/strong\u003eA. Single-cell mapping of CD8\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. B. Single-cell mapping of LUAD cells during disease progression. C. Components and alterations in CD8\u003csup\u003e+ \u003c/sup\u003eT cell subsets during the progression of LUAD. D, E. Expression profiles of marker genes across different CD8\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. F. Biological pathways associated with specific alterations in CD8\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. G. Single-cell analysis of the stemness characteristics of CD8\u003csup\u003e+ \u003c/sup\u003eT cells. \u0026nbsp;H. Results of single-cell mapping depicting the developmental trajectory of CD8\u003csup\u003e+ \u003c/sup\u003eT cells.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/96f33549c0d968ae4c1dc79e.png"},{"id":82144998,"identity":"45b2c7ae-e321-4cd9-b0e4-6e21dd943147","added_by":"auto","created_at":"2025-05-07 06:49:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2626639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormal components of CD4\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eT cells in patients with LUAD. \u003c/strong\u003eA. Single-cell mapping of CD4\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. B. Single-cell mapping of CD4\u003csup\u003e+ \u003c/sup\u003eT cells during disease progression. C. Components and alterations in CD4\u003csup\u003e+ \u003c/sup\u003eT cell subsets during the progression of LUAD. D, E. Expression profiles of marker genes across different CD4\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. F. Biological pathways associated with specific alterations in CD4\u003csup\u003e+ \u003c/sup\u003eT cell subpopulations. G. Single-cell analysis of the stemness characteristics of CD4\u003csup\u003e+ \u003c/sup\u003eT cells. H. Results of single-cell mapping depicting the developmental trajectory of CD4\u003csup\u003e+ \u003c/sup\u003eT cells.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/5fb44c498cc0c68397d92bdf.png"},{"id":82145006,"identity":"8d3aca50-a9fa-44d3-a227-1fc690811c21","added_by":"auto","created_at":"2025-05-07 06:49:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2876416,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormal components of B cells in patients with LUAD. \u003c/strong\u003eA. Single-cell mapping of B cell subpopulations. B. Single-cell mapping of B cells during disease progression. C. Components and alterations in B cell subsets during the progression of LUAD. D, E. Expression profiles of marker genes across different B cell subpopulations. F. Biological pathways associated with specific alterations in B cell subpopulations. G. Single-cell analysis of the stemness characteristics of B cells. H. Results of single-cell mapping depicting the developmental trajectory of B cells.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/e9a4add8bdea263cd0f15954.png"},{"id":82143527,"identity":"79a71f2e-89c9-4fd7-9eb6-1480f8bccac7","added_by":"auto","created_at":"2025-05-07 06:41:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3434187,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormal components of macrophages in patients with LUAD. \u003c/strong\u003eA. Single-cell mapping of macrophage subpopulations. B. Single-cell mapping of macrophages during disease progression. C. Components and alterations in macrophage subsets during the progression of LUAD. D, E. Expression profiles of marker genes across different macrophages subpopulations. F. Biological pathways associated with specific alterations in macrophage subpopulations. G. Single-cell analysis of the stemness characteristics of macrophages. H. Results of single-cell mapping depicting the developmental trajectory of macrophages.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/efd0ebb6dc461eb0ac90cdf2.png"},{"id":100378761,"identity":"06951a49-c6c8-4e37-966c-a1b52cc39654","added_by":"auto","created_at":"2026-01-16 08:58:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14804017,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/ef9c1f24-4646-446a-aa4b-ba5bca10af84.pdf"},{"id":82143517,"identity":"12b46a36-dbbe-4b28-a439-bf2cddc5f5ec","added_by":"auto","created_at":"2025-05-07 06:41:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1767872,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFig.docx","url":"https://assets-eu.researchsquare.com/files/rs-6456043/v1/7d891b3516d4f6a10a04c410.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Single-cell transcriptomics analysis of primary lung adenocarcinoma and lymph node metastatic tumors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the latest statistics, lung cancer is the leading cause of cancer-related deaths worldwide\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Lung cancer is primarily categorized into two types, namely, small cell lung cancer (SCLC) and non-SCLC (NSCLC)\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. NSCLC can be further subdivided into three distinct subtypes, namely, adenocarcinoma, squamous cell carcinoma, and large cell carcinoma\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Lung adenocarcinoma(LUAD) is the most common type of lung cancer, and accounts for approximately 35\u0026ndash;40% of all cases of lung cancer\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Despite significant improvements in therapeutic strategies, less than 20% of patients with LUAD have a 5-year survival rate\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMetastasis is a hallmark of cancer cells, and is one of the leading causes of mortality in patients with cancer\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Lymph nodes (LNs) are typically the first sites for metastasis in lung cancer, and the infiltration of tumor cells into lymphatic vessels often implies poor prognosis and a higher rate of local and/or distant recurrence\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The microenvironment of LN metastatic tumors (LNMTs) is considered immunosuppressive; however, the characteristics of the various immune cells within the microenvironment and the precise mechanisms of action remain to be elucidated\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. It has been observed that metastasized LNs can affect the immune response of the tumor\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. It is therefore imperative to perform comparative analyses and summarize the characteristics of the microenvironments of LNMTs and primary tumors (PTs) by characterizing and identifying the differences between the respective microenvironments.\u003c/p\u003e \u003cp\u003eThe single-cell sequencing technology is used to sequence and analyze genomes, transcriptomes, and epigenomes at the single-cell level\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. This novel approach addresses the limitations of traditional sequencing technologies and enables a more precise investigation of the genetic heterogeneities associated with tumorigenesis, tumor progression, and metastasis\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. By mapping single cells in the tumor microenvironment (TME), identifying new cell subtypes, and analyzing cell-cell interactions within tumors, the investigators provided insights into advanced NSCLC\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Based on multi-group data, the present study investigated the differences between the microenvironments of PTs and LNMTs in patients with LUAD, and elucidated the regulatory mechanisms within the TME that induce the metastasis and colonization of LNs by tumor cells. The findings revealed that the population of B cells, macrophages, and other cells was significantly elevated in the microenvironment of LNMTs, compared to that of PTs. The underlying molecular regulatory mechanisms were subsequently analyzed herein, and the findings may provide novel insights for inhibiting LNs metastases in LUAD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eData source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe single-cell transcriptomic data for LUAD were retrieved from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), accession number: GSE131907. The dataset had been generated using the GPL16791 microarray platform, and consists of data pertaining to 58 samples from 44 patients with a pathological diagnosis of LUAD. Of these 58 tissue samples, 11 tumor tissues, 11 distant normal lung tissues, 10 normal LNs, and 10 metastatic brain tissue specimens had been obtained from patients with LUAD who had not received prior treatment. The dataset also comprised 7 metastatic LNs and 4 samples of lung tumor tissue obtained from patients with advanced LUAD by endobronchial ultrasound and bronchoscopy, as well as 5 samples of pleural fluid obtained from patients with LUAD who presented with malignant pleural effusion. The dataset additionally contained 4 samples of primary LUAD and 7 samples of LNMT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcessing of ScRNA-Seq data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the single-cell expression profiles in the target dataset were combined using the IntegrateData function in the Seurat package of R software. The cells were analyzed based on the RNA-Seq data using the Seurat package of R software, and visualized using the UMAP method. The clusters with similar marker gene profiles were consolidated into a single cell type for defining the marker genes in the respective clusters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of a single-cell maps\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe single-cell\u0026nbsp;maps were constructed for cell clustering using the Seurat package of R software, with default parameters. The single-cell data were integrated using the Integrate Data function and subsequently clustered using the Find Clusters function. The Find Clusters function first computes the k-nearest neighbors and constructs a shared nearest neighbor (SNN) graph using the SNN clustering algorithm. It then optimizes the modularity function to establish the final clusters. The results of clustering were uniformly visualized using the UMAP method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRe-clustering of LUAD cells,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emacrophages\u003c/strong\u003e\u003cstrong\u003e, and T and B cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe LUAD cells, macrophages, T cells, and B cells were reintegrated and reaggregated using the Seurat package of R software. These cell types were subjected to a second clustering step using the same methodology in Seurat. The re-clustering was performed in adherence to the same procedural framework as the first clustering step, and the resolution ranged from 1 to 7. The resultant cell types were subsequently annotated based on established subcluster labels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of different gene expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferential gene expression analysis was conducted using the Find Markers function in the Seurat package of R software. The genes that were differentially expressed between LNMTs and PTs, across the various cell types, were subsequently identified. A significance threshold of \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 was established for identifying the significant differences in gene expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of marker genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe marker genes were subsequently identified using the FindAllMarker function in the Seurat package of R software. The potential marker genes were identified by comparing the individual cell clusters against all the other cell clusters using the FindAllMarker function. The cells within each cluster were treated as duplicates for effective analyses of differential gene expression using statistical tests. By default, the Wilcoxon Rank Sum test was used for analyzing differential gene expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional enrichment analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe differentially expressed genes were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the clusterProfiler package in R for identifying the potential functions of the respective cell subsets. The functions or pathways were deemed significantly enriched when \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. The Benjamin-Hochberg procedure was employed to ensure that the false discovery rate remained within a certain range. The results of functional enrichment analyses were visualized using cluster bubble plots.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analyses and statistical evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were analyzed in this study using the cloud-based Bioinforcloud platform (http://www.bioinforcloud.org.cn).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSingle-Cell Mapping of LUAD\u003c/h2\u003e \u003cp\u003eFor constructing the single-cell profiles, the data obtained by single-cell sequencing were initially subjected to quality control analysis and normalization studies. The IntegrateData function was used for single-cell clustering, and the Uniform Manifold Approximation and Projection (UMAP) strategy was employed for dimensionality reduction and visualization. The expression profiles of 108,341 high-quality single cells were finally obtained, which were subsequently delineated into 36 cell clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The genes that were differentially expressed between the PTs and LNMTs across the various cell types were identified by differential expression analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The findings revealed that the cell clusters primarily comprised B cells, macrophages, T cells, and LUAD cells, and they expressed the corresponding cellular markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D). The alterations in the proportions of various progressed cell types between PTs and LNMTs were subsequently analyzed, and the findings revealed that compared to those of the PT group, the proportion of B cells and macrophages was higher in the LNMT group, while the proportion of T and LUAD cells was lower (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). It has been demonstrated that LN metastasis can suppress T cell-mediated cytotoxicity and generate tumor-specific immune tolerance to promote the colonization of distant tumors, which was validated by the findings obtained herein.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAbnormal Components of LUAD cells in Patients with LUAD\u003c/h2\u003e \u003cp\u003eMetastasis is a biological process that ensures the continued growth of cancer cells\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Cancer cells primarily metastasize via two systems, namely, the circulatory and the lymphatic system\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The potential mechanisms underlying hematogenous metastasis have been extensively studied and documented in the past decades; however, the molecular mechanisms driving lymphatic metastasis are yet to be elucidated. In order to ensure the heterogeneity of LUAD in the different groups, LUAD cells were re-clustered in this study to obtain 10 cellular clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The abundance of the different subpopulations of LUAD cells in the different tumor tissues was subsequently mapped by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The differences in the cellular composition of LUAD between PTs and LNMTs were comparatively analyzed, which revealed that the cellular makeup of LUAD in patients with LNMTs varied considerably from those with PTs, as reflected in the variations in cell subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The single-cell profiles of the subpopulations that expressed specific marker genes are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and Fig. S1, and the findings indicated that the marker genes were highly expressed in specific cell subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and Fig. S1). Among them, the proportions of HP\u003csup\u003e+\u003c/sup\u003e LUAD and AIF1\u003csup\u003e+\u003c/sup\u003e LUAD cell subpopulations were significantly higher and the proportion of SETPC\u003csup\u003e+\u003c/sup\u003eLUAD cell subpopulations was significantly lower in LNMTs compared with PTs, revealing a new potential molecular mechanism for inhibiting lymph node metastasis in LUAD. Functional enrichment analysis of genes has become a standard approach for analyzing high-throughput genomics data, and provides key insights into the underlying molecular mechanisms in biomedical analyses. In this study, the differentially expressed genes were subjected to KEGG enrichment analyses for determining the potential functions of the different cellular subpopulations. The HP\u003csup\u003e+\u003c/sup\u003e LUAD cells may be involved in regulating the formation of Focal Adhesion, which is thought to modulate a variety of functions that regulate tumor cells, including proliferation, survival, migration, invasion, and stemness (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF)\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Consistently, the AIF1\u003csup\u003e+\u003c/sup\u003e LUAD cells were predicted to modulate the expression of cell adhesion molecules, revealing its facilitating role in tumor cell metastasis to lymph nodes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). It has been demonstrated that cancer stem cells play critical roles in tumor initiation, growth, metastasis, recurrence, and drug resistance in various types of cancer\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.Cell subpopulations with varying degrees of stemness may exhibit different metastatic characteristics. Therefore, the stemness counts of the different LUAD cell subpopulations were estimated in this study by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). Cells undergo state transitions throughout their life processes, and their gene expression profiles vary across these different states\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The developmental trajectories of the LUAD cell subgroups were subsequently inferred based on the changes in gene expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAbnormal Components of CD8\u003csup\u003e+\u003c/sup\u003e T cells in Patients with LUAD\u003c/h2\u003e \u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells play an essential role in anti-tumor immunity, and their depletion is frequently associated with a reduction in anti-cancer efficacy\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. The reduced infiltration of CD8\u003csup\u003e+\u003c/sup\u003e T cells is thought to be associated with LNs metastasis in a variety of tumors\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In this study, the CD8\u003csup\u003e+\u003c/sup\u003e T cells were delineated into 10 cell clusters, and the resulting single-cell mapping data were plotted and visualized (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Analysis of the CD8\u003csup\u003e+\u003c/sup\u003e T cell projections demonstrated heterogeneity between patients with PTs and those with LNMTs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The differences in the proportions of CD8\u003csup\u003e+\u003c/sup\u003e T cells in LUAD tissues between the PTs and LNMTs groups are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC. The findings revealed that compared to that of the PTs group, the expression of FGFBP2 and CD160 increased significantly in the LNMTs group, while that of CREM decreased significantly, indicating their involvement in LNs metastasis in LUAD (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). The other markers of CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulations were additionally mapped by single-cell mapping (Fig. S2). The expression levels of specific genes in the different cell subpopulations are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and Fig. S2. Furthermore, functional analyses revealed that these specific subpopulations were predominantly involved in pathways related to tumor metastasis, including cell adhesion, NK cell-mediated cytotoxicity, and the TNF signaling pathway. The pathways involved in the regulation of different CD8\u003csup\u003e+\u003c/sup\u003e T cell clusters were additionally determined (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). The stemness counts of the CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulations and their developmental trajectories were additionally plotted based on the single-cell mapping data (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eG\u0026ndash;H).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAbnormal Components of CD4\u003csup\u003e+\u003c/sup\u003e T cells in Patients with LUAD\u003c/h2\u003e \u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells represent a specialized subset of lymphocytes that are produced by the thymus, and they play crucial roles in the immune response. These cells can independently eliminate tumors, but their primary function is to activate other cells and generate a prolonged memory CTL response\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. The re-clustering of CD4\u003csup\u003e+\u003c/sup\u003e T cells led to the identification of 9 cell clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), and the distribution of these different cell clusters in PTs and LNMTs was determined by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The differences in the abundance of the different cell subpopulations between PTs and LNMTs were comparatively analyzed using stacked bar graphs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Specifically, when compared to PTs, certain cell subpopulations such as CCL4, CD14, CXCL9, SPP1, and S100B exhibited a significant elevation in LNMTs. In contrast, the subpopulations of CORO1A, CCL18, RETN, and PDLIM1 were markedly reduced in LNMTs. The different markers specifically expressed by the different cell subpopulations were determined by single-cell mapping and depicted using violin plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u0026ndash;E and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). The KEGG pathways that were significantly enriched in the different CD4\u003csup\u003e+\u003c/sup\u003e T cell subpopulations were depicted using bubble plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). The NF-κB, TNF, IL-17, and chemokine signaling pathways are recognized as crucial signaling pathways that are regulated by CD4\u003csup\u003e+\u003c/sup\u003e T cell subpopulations in LUAD. The stemness counts of the different CD4\u003csup\u003e+\u003c/sup\u003e T cell subsets were further determined by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eG). The developmental trajectories of the different subsets of CD4\u003csup\u003e+\u003c/sup\u003e T cells are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAbnormal Components of B cells in Patients with LUAD\u003c/h2\u003e \u003cp\u003eB cells play a significant role in tumor metastasis by facilitating the dissemination of cancer cells via the enhancement of tumor cell motility, invasion, angiogenesis, and other related processes\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Conversely, it has been demonstrated that B cells can also exhibit anti-metastatic effects. For instance, they have been shown to play a critical role in enhancing antigen presentation, which in turn activates anti-cancer immune responses. The present study revealed that unlike CD8\u003csup\u003e+\u003c/sup\u003e T cells, the proportion of B cells decreased in LNMTs, suggesting that they may promote the metastases of tumor cells to LNs. The B cells were categorized into 9 clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), and the differences in the proportion B cell subpopulations between PTs and LNMTs were additionally investigated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u0026ndash;C). Specifically, the expression of TCL1A and HLA-DRB5 were found to be upregulated in the LNMTs, while the expression of IL-32 was downregulated, compared to that of the PTs. Analysis of the single-cell expression profiles of the marker genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eD and Fig. S4) revealed that their expression levels were upregulated in specific cell subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eE and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Pre-concentration analysis of the cells revealed that certain subpopulations were involved in multiple processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The stemness scores of the different B cell subpopulations were determined by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). The developmental trajectories of the B cell subpopulations were additionally constructed and analyzed in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAbnormal Components of macrophages in Patients with LUAD\u003c/h2\u003e \u003cp\u003eTumor-associated macrophages (TAMs) constitute a major immune cell population in the TME, and can enhance the proliferative and migratory potential of tumor cells. They can also promote the invasion and metastasis of tumor cells via various mechanisms, including polarization, release of pro-migratory factors, and induction of angiogenesis and immunosuppression\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. In this study, the macrophages were delineated into 9 clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), and analysis of the macrophage projections revealed heterogeneity between PTs and LNMTs (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The differences in the proportions of different cells between the PT and LNMT groups are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eC. The markers that were specifically expressed in the different cell clusters are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eD\u0026ndash;E and Fig. S5. Pathways regulated by different macrophage subpopulations are mainly involved in protein production and transport, metabolic diseases (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). The stemness scores of the macrophage subpopulations were determined by single-cell mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). The developmental trajectories of macrophage subpopulations were additionally determined and analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussions","content":"\u003cp\u003eThe single-cell sequencing technique provides a robust and sophisticated approach for advancing fundamental research in tumor biology, and is being increasingly employed for exploring the cellular and molecular characteristics linked to tumor progression and the TME\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The ongoing interactions between tumor cells and the TME play crucial roles in tumorigenesis, tumor progression, metastasis, and therapeutic response\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. The TME has been extensively researched and has attracted significant clinical attention as a therapeutic target for various tumors\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. The previous studies that employed the single-cell sequencing strategy for exploring the characteristics of the TME in LUAD have focused on the molecular features of tumorigenesis and tumor progression\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. However, the microenvironment of metastasized LNs in LUAD has not been examined at the single-cell level to date. Therefore, the present study systematically analyzed the characteristics and differences between the TME of LNMTs and paired PTs in LUAD.\u003c/p\u003e \u003cp\u003eDuring cancer progression, the TME transforms into an immunosuppressive environment that is more conducive to tumor growth\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e.Immune infiltration is a prominent focus in tumor research, and the findings may hold immense clinical significance\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Immune infiltration is associated with the metastasis of tumor cells into LNs\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Although the clinical and pathological characteristics associated with immune cell infiltration have been explored\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, the processes that drive immune cell infiltration and the mechanisms underlying the differences in the degree of infiltration between PTs and LNMTs remain to be elucidated.\u003c/p\u003e \u003cp\u003eAlthough several studies have confirmed that the activity of CD8\u003csup\u003e+\u003c/sup\u003e T cells is lower in LNMTs than in PTs\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, the present study further characterized the differences in the phenotypes and features of CD8\u003csup\u003e+\u003c/sup\u003e T cells, including the variations in CD8\u003csup\u003e+\u003c/sup\u003e T cell subsets and developmental pathways, between LNMTs and PTs. Our findings revealed that the abundance of CD8\u003csup\u003e+\u003c/sup\u003e CREM\u003csup\u003e+\u003c/sup\u003e T cells reduced significantly in LNMT. CREM is predominantly expressed in fatigued CD8\u003csup\u003e+\u003c/sup\u003e T cells, and primarily promotes the depletion of T cells in the TME\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. However, the mechanisms underlying the depletion of CD8\u003csup\u003e+\u003c/sup\u003e T cells by CREM and the subsequent induction of tumor cell metastasis to LNs remain to be elucidated to date. In addition, cell adhesion contributed to lymph nodes metastasis in varies kinds of cancers which was in accord with our present study\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Thus, our data suggest a novel sight in LNMTs in CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulation which was relate to LUAD progression. In this study, the proportion of CD4\u003csup\u003e+\u003c/sup\u003e T cells also decreased significantly in LNMTs, which induced the development of an immunosuppressive environment. Further analysis of the single-cell sequencing data revealed that the CD4\u003csup\u003e+\u003c/sup\u003e CXCL9\u003csup\u003e+\u003c/sup\u003e cells promoted the metastasis of tumor cells into LNs, which was consistent with the findings of previous studies on other tumors\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe B cell subpopulations in the PTs and LNMTs were additionally analyzed herein, and the differentially expressed genes were subsequently identified. The obtained findings provided a basis for subsequent investigation of the mechanisms underlying the inhibition of tumor metastasis by targeting B cells\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Despite the observable decrease in the proportion of LUAD cells, a more in-depth investigation into the alterations induced by specific markers can enhance our understanding of the complex mechanisms underlying tumor cell metastasis. The significant increase in the proportion of HP\u003csup\u003e+\u003c/sup\u003e LUAD cells implies that HP may play an important role in promoting tumor cell metastasis; however, further molecular biology studies and \u003cem\u003ein vivo\u003c/em\u003e experiments are necessary for validation.\u003c/p\u003e \u003cp\u003eTo sum up, the present study on LUAD revealed that the activity of immune cells in LNMTs is reduced compared to that of PTs, and the molecular mechanisms underlying the differences in immune activity were further analyzed. However, further mechanistic studies are essential for obtaining precise insights into the increased invasive and proliferative potential of tumor cells within LNs. The findings highlight the distinct characteristics of the TMEs of LNMTs and PTs, which may facilitate the development of personalized therapies for TME-specific targeting in patients with LUAD.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBy integrating and analyzing single-cell sequencing data, we found that the activity of immune cells in LNMTs is reduced compared to that of PTs. The CD8\u003csup\u003e+\u003c/sup\u003e CREM\u003csup\u003e+\u003c/sup\u003e T cells and CD4\u003csup\u003e+\u003c/sup\u003e CXCL9\u003csup\u003e+\u003c/sup\u003e cells are major drivers of tumor cell metastasis from the PTs to the LNs. The HP\u003csup\u003e+\u003c/sup\u003e LUAD cells may also play an important role in promoting tumor cell metastasis.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in the published article or are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShuai Zhang:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Formal analysis, Data curation, Conceptualization.\u003cstrong\u003e\u0026nbsp;Xiaoying Jin:\u0026nbsp;\u003c/strong\u003eProject\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eadministration, Methodology, Formal analysis. \u003cstrong\u003eChangzheng Li:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; original draft, Visualization, Investigation, Conceptualization. \u003cstrong\u003eYuechao Liu:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; original draft, Visualization, Investigation, Funding acquisition, Data curation, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Young Talent Cultivation Project of Cancer Hospital of Shandong First Medical University (2024-QH07).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause no clinical samples were included in this study, ethics approval was not required.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHendriks LEL, Remon J, Faivre-Finn C, Garassino MC, Heymach JV, Kerr KM, Tan DSW, Veronesi G, Reck M. 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Mol Cancer, 2024,23(1): 13.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6456043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6456043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough the microenvironment of lymph node metastatic tumors (LNMTs) plays a critical role in the pathogenesis of cancer, systematic studies on the microenvironment of LNMTs in lung adenocarcinoma (LUAD) are lacking. The present study analyzed the single-cell profiles of primary tumors (PTs) and LNMTs in patients with LUAD. The abnormalities in LUAD cells, B cells, T cells, and macrophages in LUAD were additionally analyzed at the single-cell level. The findings revealed that compared to that of the PTs group, the proportion of B cells and macrophages was elevated in the LNMTs group, while the proportion of T and LUAD cells was reduced. These results demonstrated the occurrence of immunosuppression in the microenvironment of LNMTs, and the cell subpopulations were subsequently analyzed to elucidate the underlying changes and associated pathways. The results showed that the abundance of the CREM\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e T cell subset was significantly reduced in LNMTs, whereas the proportion of HP\u003csup\u003e+\u003c/sup\u003e LUAD cells was significantly increased. In conclusion, the present study characterized the microenvironment of PTs and LNMTs, which may aid in the development of personalized therapeutic strategies for patients with LUAD presenting with lymph node metastases.\u003c/p\u003e","manuscriptTitle":"Single-cell transcriptomics analysis of primary lung adenocarcinoma and lymph node metastatic tumors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:41:34","doi":"10.21203/rs.3.rs-6456043/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1813329-a3da-46c0-b53c-0407a57341b1","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48037212,"name":"Biological sciences/Cancer/Cancer genomics"},{"id":48037213,"name":"Biological sciences/Cancer/Lung cancer/Non small cell lung cancer"}],"tags":[],"updatedAt":"2026-01-16T05:24:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:41:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6456043","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6456043","identity":"rs-6456043","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}