Paul Brennan

The paper identifies and validates a previously missed mutational signature in microsatellite-stable colorectal cancer, showing it is distinct from known signatures and not caused by canonical DNA repair defects.

This study identifies novel genetic risk loci for pancreatic ductal adenocarcinoma in African ancestry individuals through admixture mapping and GWAS.

The paper identifies mutational signatures in normal kidney cells from multiple countries, revealing exposure to exogenous mutagens including aristolochic acids and unknown agents prevalent in Japan.

This study identifies three distinct evolutionary trajectories in lung adenocarcinomas using whole-genome sequencing, revealing that some never-smoking tumors follow smoking-like paths driven by KRAS mutations.

This study conducts a cross-ancestral GWAS and fine mapping of head and neck squamous cell carcinoma subsites, identifying 29 novel variants and highlighting gene-environment interactions.

The paper identifies three subtypes of NS-LUAD using RNA-seq data and develops a 60-gene signature that predicts survival across subgroups.

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

This study identifies 40 circulating proteins associated with cancer risk using MR and colocalization, highlighting potential therapeutic targets and adverse effects of protein-altering interventions.

SigProfilerAssignment refits known substitution, doublet, indel and copy-number mutational signatures to single samples and probabilistically to individual mutations, outperforming four refitting tools on 2,700 synthetic genomes.

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

This study investigates the relationship between genetically predicted leukocyte telomere length and lung cancer risk, finding a causal association and novel susceptibility loci.

This study identifies eight novel lung cancer susceptibility loci and shows that germline variants related to smoking and DNA repair influence somatic mutation burden in lung tumors.

This study uses Mendelian randomization to assess the causal effect of sexual behavior on oropharyngeal cancer risk, finding attenuated associations after adjusting for confounders.

The paper uses a genetic variant to assess cancer risk associated with TYK2 inhibition, finding increased risks for lung cancer and non-Hodgkin lymphoma.

This study identifies IL-18 as a biomarker for reduced lung cancer risk using genetic, pre-diagnostic, and tumor expression data, with potential therapeutic implications.

This paper develops a Bayesian method to detect copy number variants and assess their association with disease in large-scale studies, finding deletions near MYC and TUSC3 linked to pancreatic cancer.

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

Needlestack is a variant caller that improves sensitivity for low abundance mutations by learning sequencing error rates from multi-sample data.

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.