Claudia Arnedo-Pac

This study shows that genetic background and environmental factors determine the trajectory of cancer evolution in mice, with distinct mutational paths despite similar final tumor states.

This study uses whole genome sequencing of endometrial cancers to identify novel subgroups, drivers, and actionable alterations, improving precision medicine approaches.

The paper introduces a scalable method for profiling FFPE tissue microarrays using spatial single-cell transcriptomics, achieving subcellular resolution in human liver samples.

The paper investigates how strand-asymmetric processes like replication and transcription influence DNA damage, repair, and mutagenesis, revealing mechanisms that shape cancer genome evolution.

This paper identifies mutational processes with high hotspot propensity in tumors and normal tissues, showing that SBS1 and SBS17a/b have distinct genomic factors influencing their hotspot formation.

OncodriveCLUSTL identifies cancer drivers by detecting mutation clustering signals in genomic data, outperforming existing methods across tumor whole-exomes.