Hikmat A Al‐Ahmadie

The paper develops Mosaic, a machine learning system that classifies tumors into detailed subtypes and identifies molecular phenotypes using histopathologic and genomic data from a large patient cohort.

The paper examines how somatic structural variations affect TAD boundaries and gene regulation in human cancers using whole genome sequencing data.

This study identifies germline genetic variants influencing somatic mutation patterns in 2,642 cancer genomes across 39 cancer types.

This study characterizes mitochondrial genomes in 2,700 cancer patients across 37 types using whole-genome sequencing and RNA-seq, revealing mutational patterns, truncating mutations, and nuclear transfer of mitochondrial DNA.

This study analyzes chromothripsis in 2,658 cancers using whole-genome sequencing, finding it prevalent across multiple cancer types with complex structural alterations.

This study explores factors influencing response and resistance to atezolizumab in urothelial cancer using multi-omic data, finding associations between TCR clonality and clinical outcomes.