Neil E. Caporaso

The paper develops and validates multi-ancestry polygenic risk scores for LUAD in East Asian never-smokers, showing improved risk prediction compared to East Asian-only models.

This study analyzes 1024 lung adenocarcinomas to identify evolutionary patterns and mutational mechanisms, revealing distinct trajectories linked to smoking, ancestry, and retrotransposition.

The paper identifies two lung cancer subtypes defined by APOBEC mutagenesis levels and shows their association with different genetic mutations, aging, and immune responses.

This study shows that time to first cigarette strongly influences lung tumor mutational burden, signatures, and survival in smokers.

The paper identifies novel genetic loci associated with nicotine dependence and shows genetic correlations with other smoking traits and comorbidities using genome-wide association studies.

This study assesses polygenicity and risk prediction using common variants across 14 cancers, finding varying numbers of susceptibility variants and risk score effectiveness.

This study quantifies genetic and epigenetic intratumor heterogeneity in lung adenocarcinoma and links it to poor prognosis.

The paper identifies genetic links between impaired pulmonary function and increased lung cancer risk, showing causal relationships through Mendelian randomization and highlighting immune-related pathways.

This study quantifies genetic correlations between six solid cancers and other diseases using GWAS data, finding shared heritability and functional enrichment in regulatory regions.

The paper introduces MEGSA, a framework for analyzing mutual exclusivity of tumor mutations, identifying novel gene sets and associations in cancer types like AML and breast cancer.

This paper improves polygenic risk scores by applying winners curse correction and variable thresholds to GWAS summary data, enhancing prediction accuracy for some diseases.