Background

Lung cancer presents a significant global health challenge, with disparities in incidence and outcomes across races and ethnicities. These disparities underscore the need to explore the molecular landscapes of lung cancer in relation to ancestry. Here, we leverage data from a real-world clinico-genomic database to discover associations between molecular profiles and genetic ancestry or race/ethnicity categories.

Methods

We utilized data from a cohort of 13,196 primarily late-stage non-small cell lung adenocarcinoma (LUAD) patients, sequenced with the Tempus xT NGS 648-gene panel, of which normal tissue was also sequenced for 6,520 cases. Genetic ancestry proportions were estimated using ancestry informative markers. Race and ethnicity categories were imputed using an ancestry-backed method, resulting in the assignment of 568 Hispanic/Latino, 892 non-Hispanic (NH) Asian, 1,581 NH Black, and 10,063 NH White individuals. Multiple imputation addressed missing data on smoking status. Logistic regression models assessed associations between ancestry proportions and somatic variants in 23 LUAD-related genes, adjusting for a false discovery rate of 5%. Analyzed mutations included copy number alterations, gene fusions, protein-altering SNVs and indels, and actionable or predicted driver mutations.

Results

Our analysis confirmed previously reported associations, such as a positive correlation between East Asian (EAS) ancestry and EGFR (OR per doubling ancestry=1.1) and a negative correlation with KRAS driver mutations (OR=0.96), while European ancestry exhibited the opposite relationship (OR=0.93 and 1.08, correspondingly; all p<0.0001). We also verified a positive association with EGFR driver mutations (OR=2) and a negative one with KRAS (OR=0.46; p<0.001) among Hispanic/Latino patients and American Indigenous (AMR) genetic ancestry (OR=1.03 and 0.97, correspondingly; p<0.05). Novel associations were identified between African (AFR) and South Asian (SAS) ancestries and LUAD genes. Some associations are explained by differences in smoking status (e.g., ATM and ALK fusions), while others persist even after adjusting for smoking (e.g., EGFR, KRAS, and CDKN2A copy-number alterations). Notably, we identified a positive association between EAS ancestry and the imputed NH Asian category with driver mutations in CTNNB1 (OR=1.05 and 2.2, respectively; p<0.01), independent of smoking. These mutations are rare in NH White patients (2.4%) but are more prevalent in never-smoker NH Asian patients with predominant EAS ancestry (8.5%).

Conclusion

This study underscores the value of clinico-genomic databases in revealing associations between LUAD mutational profiles and genetic ancestry, shedding light on lung cancer disparities. Identification of a previously unappreciated association between EAS with CTNNB1, a potential biomarker for spindle assembly checkpoint kinase (TTK) inhibitors effectiveness and prognosis in LUAD, emphasizes the value of studying diverse populations in cancer research, paving the way for more equitable lung cancer treatments.

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