Anna DeFazio

This paper develops a large biobank of patient-derived MOC organoids and screens them for drug efficacy, finding resistance to standard therapies and effectiveness of less commonly used drugs.

ProCanFDL uses federated deep learning to subtype cancers using proteomic data while preserving privacy, achieving performance gains over local models.

This study shows that DNMT1 inhibitors reduce BRCA1 promoter methylation in HGSOC, leading to BRCA1 re-expression and PARP inhibitor resistance.

This study uses exome sequencing to identify HELB as a novel susceptibility gene for non-high grade serous epithelial ovarian cancer, with a strong association found in genetic analyses.

This study identifies seven novel genetic loci associated with high-grade serous ovarian cancer risk using a large-scale GWAS and develops polygenic scores for improved risk prediction.

This study combines DNA sequencing and gene-expression profiling with clinical data to improve diagnosis of cancer of unknown primary (CUP), identifying potential tissue origins in over a third of cases.

This study improves transcriptome-wide association studies by integrating pleiotropy-guided methods with GWAS data to identify new cancer susceptibility genes.

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