Spatial Immunogenomic Patterns Associated with Lymph Node Metastasis in Lung Adenocarcinoma

Abstract Background Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is associated with poor prognosis, yet the specific mechanisms involved remain unclear. The objective of this investigation is to elucidate the immunogenomic landscape associated with LUAD with LN metastasis. Methods We utilized broad-panel next-generation sequencing (NGS) on a cohort of 257 LUAD patients who underwent surgical treatment. This approach allowed us to understand the molecular landscape of tumors and identify targetable driver-gene alterations. We also employed multiplex immunohistochemistry (mIHC) on the propensity score matching cohort, which enables comprehensive profiling of the tumor immune microenvironment while preserving cellular metaclusters, interactions and neighborhood functional units. By integrating data from both NGS and mIHC, we not only discerned spatial immunogenomic patterns within this meticulously matched cohort but also developed and independently validated a predictive model for LN stage. Results Our analysis revealed distinct patterns of immunogenomic alterations correlated with LN metastasis stages. Specifically, increased mutation frequencies in genes such as PIK3CG, ATM, BRD4, and KMT2B were observed alongside LN metastasis. Additionally, an enrichment of macrophages and regulatory T cells was associated with the immunogenomic patterns. Furthermore, a novel predictive model for LN metastasis likelihood was developed, offering potential benefits for patients ineligible for surgery. Conclusions This study offers an in-depth analysis of the genetic and immune profiles in LUAD with LN metastasis, identifying key immunogenomic patterns linked to metastasis. The creation of a predictive model from these insights marks a critical advancement in personalized treatment, underscoring its promise for enhancing patient management.