Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma
Abstract Background Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD. Methods We employed broad-panel next-ge...
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BMC
2024-10-01
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| Series: | Experimental Hematology & Oncology |
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| Online Access: | https://doi.org/10.1186/s40164-024-00574-8 |
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| author | Fanjie Meng Hao Li Ruoyi Jin Airong Yang Hao Luo Xiao Li Peiyu Wang Yaxing Zhao Olga Chervova Kaicheng Tang Sida Cheng Bin Hu Yun Li Jianpeng Sheng Fan Yang David Carbone Kezhong Chen Jun Wang |
| author_facet | Fanjie Meng Hao Li Ruoyi Jin Airong Yang Hao Luo Xiao Li Peiyu Wang Yaxing Zhao Olga Chervova Kaicheng Tang Sida Cheng Bin Hu Yun Li Jianpeng Sheng Fan Yang David Carbone Kezhong Chen Jun Wang |
| author_sort | Fanjie Meng |
| collection | DOAJ |
| description | Abstract Background Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD. Methods We employed broad-panel next-generation sequencing (NGS) on a cohort of 257 surgically treated LUAD patients to delineate the molecular landscape of primary tumors and identify actionable driver-gene alterations. Additionally, we used multiplex immunohistochemistry (mIHC) on a propensity score-matched cohort, which enabled us to profile the immune microenvironment of primary tumors in detail while preserving cellular metaclusters, interactions, and neighborhood functional units. By integrating data from NGS and mIHC, we successfully identified spatial immunogenomic patterns and developed a predictive model for LN metastasis, which was subsequently validated independently. Results Our analysis revealed distinct immunogenomic alteration patterns associated with LN metastasis stages. Specifically, we observed increased mutation frequencies in genes such as PIK3CG and ATM in LN metastatic primary tumors. Moreover, LN positive primary tumors exhibited a higher presence of macrophage and regulatory T cell metaclusters, along with their enriched neighborhood units (p < 0.05), compared to LN negative tumors. Furthermore, we developed a novel predictive model for LN metastasis likelihood, designed to inform non-surgical treatment strategies, optimize personalized therapy plans, and potentially improve outcomes for patients who are ineligible for surgery. Conclusions This study offers a comprehensive analysis of the genetic and immune profiles in LUAD primary tumors with LN metastasis, identifying key immunogenomic patterns linked to metastatic progression. The predictive model derived from these insights marks a substantial advancement in personalized treatment, underscoring its potential to improve patient management. |
| format | Article |
| id | doaj-art-2683ea35546c410cb5f1b08f5774a4ac |
| institution | OA Journals |
| issn | 2162-3619 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | BMC |
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| series | Experimental Hematology & Oncology |
| spelling | doaj-art-2683ea35546c410cb5f1b08f5774a4ac2025-08-20T02:18:20ZengBMCExperimental Hematology & Oncology2162-36192024-10-0113111710.1186/s40164-024-00574-8Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinomaFanjie Meng0Hao Li1Ruoyi Jin2Airong Yang3Hao Luo4Xiao Li5Peiyu Wang6Yaxing Zhao7Olga Chervova8Kaicheng Tang9Sida Cheng10Bin Hu11Yun Li12Jianpeng Sheng13Fan Yang14David Carbone15Kezhong Chen16Jun Wang17Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao Yang Hospital, Capital Medical UniversityDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalKanghui Biotechnology Co., LtdCancer Center, Daping Hospital Army Medical UniversityDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalInfinity Scope Biotechnology Co., Ltd.University College London Cancer Institute, University College LondonInfinity Scope Biotechnology Co., Ltd.Department of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalDepartment of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao Yang Hospital, Capital Medical UniversityDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalCollege of Artificial Intelligence, Nanjing University of Aeronautics and AstronauticsDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalJames Thoracic Oncology Center, Ohio State UniversityDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalDepartment of Thoracic Surgery, Institution of Thoracic Oncology, Peking University People’s HospitalAbstract Background Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD. Methods We employed broad-panel next-generation sequencing (NGS) on a cohort of 257 surgically treated LUAD patients to delineate the molecular landscape of primary tumors and identify actionable driver-gene alterations. Additionally, we used multiplex immunohistochemistry (mIHC) on a propensity score-matched cohort, which enabled us to profile the immune microenvironment of primary tumors in detail while preserving cellular metaclusters, interactions, and neighborhood functional units. By integrating data from NGS and mIHC, we successfully identified spatial immunogenomic patterns and developed a predictive model for LN metastasis, which was subsequently validated independently. Results Our analysis revealed distinct immunogenomic alteration patterns associated with LN metastasis stages. Specifically, we observed increased mutation frequencies in genes such as PIK3CG and ATM in LN metastatic primary tumors. Moreover, LN positive primary tumors exhibited a higher presence of macrophage and regulatory T cell metaclusters, along with their enriched neighborhood units (p < 0.05), compared to LN negative tumors. Furthermore, we developed a novel predictive model for LN metastasis likelihood, designed to inform non-surgical treatment strategies, optimize personalized therapy plans, and potentially improve outcomes for patients who are ineligible for surgery. Conclusions This study offers a comprehensive analysis of the genetic and immune profiles in LUAD primary tumors with LN metastasis, identifying key immunogenomic patterns linked to metastatic progression. The predictive model derived from these insights marks a substantial advancement in personalized treatment, underscoring its potential to improve patient management.https://doi.org/10.1186/s40164-024-00574-8Lung adenocarcinoma lymph node metastasisGenomic signaturesTumor immune microenvironmentSpatial immunogenomic patterns |
| spellingShingle | Fanjie Meng Hao Li Ruoyi Jin Airong Yang Hao Luo Xiao Li Peiyu Wang Yaxing Zhao Olga Chervova Kaicheng Tang Sida Cheng Bin Hu Yun Li Jianpeng Sheng Fan Yang David Carbone Kezhong Chen Jun Wang Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma Experimental Hematology & Oncology Lung adenocarcinoma lymph node metastasis Genomic signatures Tumor immune microenvironment Spatial immunogenomic patterns |
| title | Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| title_full | Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| title_fullStr | Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| title_full_unstemmed | Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| title_short | Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| title_sort | spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma |
| topic | Lung adenocarcinoma lymph node metastasis Genomic signatures Tumor immune microenvironment Spatial immunogenomic patterns |
| url | https://doi.org/10.1186/s40164-024-00574-8 |
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