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Integrative Single‐Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma
by
Zhang, Zhenfa
, Jiang, Shuai
, Yu, Yue
, Zhang, Lianmin
, Feng, Jiaqi
, Huang, Chenjun
, Zhao, Jinhan
in
Adenocarcinoma
/ Adenocarcinoma of Lung - genetics
/ Adenocarcinoma of Lung - immunology
/ Adenocarcinoma of Lung - pathology
/ Algorithms
/ Analysis
/ Animals
/ Antigen presenting cells
/ Cells
/ Communication
/ Datasets
/ Dendritic cells
/ Epithelial cells
/ Feature selection
/ Female
/ Gene expression
/ Gene Expression Regulation, Neoplastic
/ Genes
/ Humans
/ Immunogenicity
/ Immunotherapy
/ Infiltration
/ Learning algorithms
/ Leukocyte migration
/ lung adenocarcinoma
/ Lung cancer
/ Lung Neoplasms - genetics
/ Lung Neoplasms - immunology
/ Lung Neoplasms - pathology
/ lymph node metastasis
/ Lymph nodes
/ Lymph Nodes - immunology
/ Lymph Nodes - pathology
/ Lymphatic Metastasis - immunology
/ Lymphatic Metastasis - pathology
/ Lymphatic system
/ Lymphocytes T
/ Machine Learning
/ Macrophages
/ Macrophages - immunology
/ Male
/ Medical prognosis
/ Metastases
/ Metastasis
/ Monocytes
/ Prediction models
/ Prognosis
/ Quality control
/ Risk groups
/ risk prediction model
/ RNA
/ RNA sequencing
/ Signal transduction
/ Single-Cell Analysis - methods
/ single‐cell sequencing
/ Survival analysis
/ T cells
/ Tumor microenvironment
/ Tumor Microenvironment - genetics
/ Tumor Microenvironment - immunology
/ Tumors
/ tumour microenvironment
2025
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Integrative Single‐Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma
by
Zhang, Zhenfa
, Jiang, Shuai
, Yu, Yue
, Zhang, Lianmin
, Feng, Jiaqi
, Huang, Chenjun
, Zhao, Jinhan
in
Adenocarcinoma
/ Adenocarcinoma of Lung - genetics
/ Adenocarcinoma of Lung - immunology
/ Adenocarcinoma of Lung - pathology
/ Algorithms
/ Analysis
/ Animals
/ Antigen presenting cells
/ Cells
/ Communication
/ Datasets
/ Dendritic cells
/ Epithelial cells
/ Feature selection
/ Female
/ Gene expression
/ Gene Expression Regulation, Neoplastic
/ Genes
/ Humans
/ Immunogenicity
/ Immunotherapy
/ Infiltration
/ Learning algorithms
/ Leukocyte migration
/ lung adenocarcinoma
/ Lung cancer
/ Lung Neoplasms - genetics
/ Lung Neoplasms - immunology
/ Lung Neoplasms - pathology
/ lymph node metastasis
/ Lymph nodes
/ Lymph Nodes - immunology
/ Lymph Nodes - pathology
/ Lymphatic Metastasis - immunology
/ Lymphatic Metastasis - pathology
/ Lymphatic system
/ Lymphocytes T
/ Machine Learning
/ Macrophages
/ Macrophages - immunology
/ Male
/ Medical prognosis
/ Metastases
/ Metastasis
/ Monocytes
/ Prediction models
/ Prognosis
/ Quality control
/ Risk groups
/ risk prediction model
/ RNA
/ RNA sequencing
/ Signal transduction
/ Single-Cell Analysis - methods
/ single‐cell sequencing
/ Survival analysis
/ T cells
/ Tumor microenvironment
/ Tumor Microenvironment - genetics
/ Tumor Microenvironment - immunology
/ Tumors
/ tumour microenvironment
2025
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Integrative Single‐Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma
by
Zhang, Zhenfa
, Jiang, Shuai
, Yu, Yue
, Zhang, Lianmin
, Feng, Jiaqi
, Huang, Chenjun
, Zhao, Jinhan
in
Adenocarcinoma
/ Adenocarcinoma of Lung - genetics
/ Adenocarcinoma of Lung - immunology
/ Adenocarcinoma of Lung - pathology
/ Algorithms
/ Analysis
/ Animals
/ Antigen presenting cells
/ Cells
/ Communication
/ Datasets
/ Dendritic cells
/ Epithelial cells
/ Feature selection
/ Female
/ Gene expression
/ Gene Expression Regulation, Neoplastic
/ Genes
/ Humans
/ Immunogenicity
/ Immunotherapy
/ Infiltration
/ Learning algorithms
/ Leukocyte migration
/ lung adenocarcinoma
/ Lung cancer
/ Lung Neoplasms - genetics
/ Lung Neoplasms - immunology
/ Lung Neoplasms - pathology
/ lymph node metastasis
/ Lymph nodes
/ Lymph Nodes - immunology
/ Lymph Nodes - pathology
/ Lymphatic Metastasis - immunology
/ Lymphatic Metastasis - pathology
/ Lymphatic system
/ Lymphocytes T
/ Machine Learning
/ Macrophages
/ Macrophages - immunology
/ Male
/ Medical prognosis
/ Metastases
/ Metastasis
/ Monocytes
/ Prediction models
/ Prognosis
/ Quality control
/ Risk groups
/ risk prediction model
/ RNA
/ RNA sequencing
/ Signal transduction
/ Single-Cell Analysis - methods
/ single‐cell sequencing
/ Survival analysis
/ T cells
/ Tumor microenvironment
/ Tumor Microenvironment - genetics
/ Tumor Microenvironment - immunology
/ Tumors
/ tumour microenvironment
2025
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Integrative Single‐Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma
Journal Article
Integrative Single‐Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma
2025
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Overview
Lymph node metastasis is a pivotal determinant of prognosis in lung adenocarcinoma, yet its impact on tumour microenvironment remodelling remains insufficiently characterised. In this study, we employed single‐cell RNA sequencing to compare metastatic and non‐metastatic lymph nodes, delineating metastasis‐associated immune and stromal alterations. Metastatic nodes exhibited marked reductions in dendritic cell and T cell infiltration alongside increases in monocytes and SPP1+ macrophages, indicative of an immunosuppressive milieu. Intercellular communication analysis revealed strengthened interactions among SPP1+ macrophages, monocytes, and epithelial cells, suggesting coordinated signalling that may further enforce immune suppression. Integrating differentially expressed genes with multi‐omic features, we developed an ensemble machine learning model, LNRScore, which robustly stratified patients into distinct risk groups. A high LNRScore was associated with poorer prognosis and reduced immune infiltration, whereas a low LNRScore correlated with higher immunogenicity and greater predicted responsiveness to immunotherapy based on TCIA assessments. Further analyses identified HMGA1 as a core gene within the model, closely linked to adverse outcomes; functional assays demonstrated that high HMGA1 expression promotes the proliferation and migration of the LLC cell line, supporting its role in metastatic progression. Collectively, this study defines the immune microenvironmental remodelling associated with lymph node metastasis, establishes an effective risk prediction model (LNRScore), and highlights HMGA1 as a potential target for precision diagnosis and therapy in lung adenocarcinoma.
Publisher
John Wiley & Sons, Inc
Subject
/ Adenocarcinoma of Lung - genetics
/ Adenocarcinoma of Lung - immunology
/ Adenocarcinoma of Lung - pathology
/ Analysis
/ Animals
/ Cells
/ Datasets
/ Female
/ Gene Expression Regulation, Neoplastic
/ Genes
/ Humans
/ Lymphatic Metastasis - immunology
/ Lymphatic Metastasis - pathology
/ Male
/ RNA
/ Single-Cell Analysis - methods
/ T cells
/ Tumor Microenvironment - genetics
/ Tumor Microenvironment - immunology
/ Tumors
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