Abstract

Abstract Introduction: Lymph node metastasis evaluation in solid tumors is mainly complicated by the diagnostic yield of standard imaging modalities and tumor size contradictions. Exploring clinical/molecular features that complement the use of radiologic and bronchoscopy findings may provide significant values for a more accurate pathologic determination of nodal metastasis. Methods: We analyzed surgery-resected tumor samples from 72 treatment-naïve lung adenocarcinoma (LUAD) patients via whole-exome sequencing (WES). Mutational profiles of patients categorized based on their pathologic lymph node metastasis (pN) status were assessed, and the association between metastatic-driving features and overall survival (OS) was then explored in both the study cohort and the Cancer Genome Atlas Program (TCGA) external cohort. Results: Among all 72 patients, 41 (56.9%) were pathologically confirmed as positive for lymph node metastasis (pN-positive), while 31 (43.1%) were categorized as pN-negative. The most frequently mutated gene was TP53 in both subgroups (54.8% and 53.7%, respectively), and the aberrant KEAP1-NRF2 signaling pathway was found significantly more enriched in pN-negative patients. Copy-number variant analysis showed that chromosome 7p amplifications (X7p_amp) at the arm level and EGFR amplifications at the focal gene level were more frequently identified in pN-positive patients (P=0.008 and P=0.004, respectively). Importantly, these amplifications were associated with worse OS in both the study cohort and the TCGA external dataset. Consistent with the unfavorable prognosis, pN-positive patients demonstrated a higher chromosome instability score (CIS) (median: 0.32 vs. 0.14, P=0.14) and a lower tumor mutation burden (TMB) (median: 1.83 vs. 3.85 muts/Mb, P=0.048) compared to pN-negative patients. Conclusion: Our findings suggest that X7p_amp, particularly EGFR amplification, might be associated with pathologic involvement of lymph nodes and an unfavorable prognosis in LUAD patients. Our study highlights the importance of integrating clinical and genomic data into conventional radiologic modalities for a more accurate determination of pathologic nodal involvement. Citation Format: Shijie Wang, Zhiwei Zhou, Song Wang, Rongyun Guo, Zeming Ma, Dachuan Zhao, Liang Wang, Yinan Liu, Yuanyuan Ma, Jianzhi Zhang, Sha Wang, Yedan Chen, Haimeng Tang, Qiuxiang Ou, Jinfeng Chen. Identifying genomic features associated with pathologic lymph node metastasis in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5047.

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