Katherine L. Nathanson

This paper identifies 116 risk loci for melanoma through GWAS, links susceptibility to immunity and Wnt signaling, and develops a PRS improving risk prediction.

This study identifies two cell-of-origin-driven subtypes of BRCA1-associated TNBC, showing that tumor subtype depends on the cell type initiating the cancer.

The paper identifies reversion mutations in homologous recombination genes across cancers, showing they restore DNA repair and confer PARP inhibitor resistance through specific structural alterations.

This paper maps 6,888 RAD51D variants to identify biochemical functions critical for homologous recombination and olaparib response, revealing key regions and mechanisms of variant impact.

This study quantifies cancer risk and penetrance in CHEK2 heterozygotes using genomic data from two large biobanks, finding increased risks for several cancers and younger age of onset.

G4mer identifies G-quadruplexes and disease variants from population-scale genetic data, improving accuracy and highlighting sequence features affecting rG4 formation.

This study analyzes genetic testing outcomes and utilization patterns in 10,000 adult patient encounters, finding high diagnostic yield and indication-specific variation in test results.

This study compares genomic features of gBRCA1 and gBRCA2 breast cancers, finding distinct mutational patterns and therapeutic implications for PARP and CDK4/6 inhibitors.

This study identifies a unique mutational signature, SBS87, in testicular germ cell tumors (TGCTs) that resembles thiopurine-induced DNA damage and is associated with tumor latency and telomere elongation.

The paper uses case-control data from over 400,000 women to classify BRCA1 and BRCA2 variants, finding high consistency with ClinVar annotations for 785 previously unclassified variants.

This study evaluates breast cancer risks associated with pathogenic variant type and location in BRCA2 and other genes, finding differential risks based on variant position.

The paper identifies a higher prevalence of NF1 pathogenic variants using a genotype-first approach, finding many cases with somatic mosaicism and increased cancer risk.

The paper recommends a standardized multigene germline panel for breast cancer patients based on cancer mortality benefit, including specific genes and excluding others.

This study evaluates deep learning models for classifying pathogenic germline variants in hereditary breast cancer using UK Biobank data, finding limited clinical utility for variants of uncertain significance.

The paper identifies how germline and somatic mutations interact to cause resistance to CDK4/6 inhibitors in breast cancer and proposes a sequential treatment strategy using PARP inhibitors.

HRDex calculates HRD scores from whole exome sequencing data to identify BRCA-deficient tumors, showing high accuracy in breast cancer and moderate in ovarian cancer.

This paper develops polygenic risk scores for breast cancer prediction in women of African ancestry by combining African and European ancestry datasets, improving prediction accuracy.

This study evaluates polygenic risk scores (PRS) for cancer prediction in a racially diverse biobank, finding moderate improvements in discriminatory accuracy for European ancestry but limited gains for African ancestry.

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

CODEX2 improves CNV detection sensitivity and reduces false discoveries in whole-exome and targeted sequencing data.