AI Article Synopsis
- This study investigates the immunogenomic characteristics of lung adenocarcinoma (LUAD) with lymph node (LN) metastasis, aiming to better understand its connection to poor patient prognosis.
- Researchers utilized next-generation sequencing and multiplex immunohistochemistry on a large patient cohort to map genetic alterations and analyze the immune environment in LUAD tumors.
- The findings highlight specific mutations and immune cell profiles linked to LN metastasis, allowing researchers to create a predictive model that could enhance personalized treatment strategies for patients who cannot undergo surgery.
Article 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.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514955 | PMC |
| http://dx.doi.org/10.1186/s40164-024-00574-8 | DOI Listing |
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