Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma

肺腺癌淋巴结转移相关的空间免疫基因组模式

阅读:15
作者: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 Wang5

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.

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.

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。