Ayelet Borgida

The paper identifies four epithelial transcription states in pancreatic cancer and links their origins to early developmental processes.

This study analyzes ctDNA shedding in pancreatic cancer using paired tissue and plasma whole genomes, finding that subclones contribute significantly to early dissemination and ctDNA levels.

This study integrates spatial proteomics and genomics in PDAC to identify tumour-immune-stroma interactions and their genomic associations, showing multi-omics models improve patient survival prediction.

This study identifies cell-free DNA methylation markers for early detection and prognosis of pancreatic cancer with high accuracy and survival stratification.

The paper develops a prognostic model for pancreatic ductal adenocarcinoma using meta-analysis of transcriptomic data, identifying gene pairs associated with early mortality after surgery.