Colin C. Pritchard

This paper constructs a unified transcriptional landscape of breast cancer using bulk RNA-seq data from multiple cohorts, identifying subtype and microenvironmental programs associated with therapeutic resistance.

The paper constructs a unified transcriptomic landscape of lung cancer using RNA-seq data from 1,824 tumors, identifying nine molecular clusters with distinct biological and clinical features.

This paper introduces a 3D microdissection method combining CNC milling and light-sheet microscopy to study tumor evolution in complex 3D structures.

This paper develops a machine learning model to identify molecularly distinct DDR subgroups in prostate cancer, revealing concurrent repair deficiencies and improving therapeutic stratification.

This study shows that acute CDK12 loss in prostate cancer causes HR deficiency via polyadenylation, but chronic loss leads to adaptation, making PARP inhibitors ineffective and suggesting CDK13 targeting as a new therapeutic approach.

The paper uses ddPCR to analyze PI3K-AKT-MTOR mutations in pediatric epilepsy cases, finding associations between specific mutations and clinical phenotypes.

The paper designs single molecule molecular inversion probes targeting clinically relevant variants using the CIViC database, demonstrating high sensitivity and discovering missed variants in cancer samples.

This study reports that 17% of advanced cancer patients have clinically relevant germline variants, with higher rates of cancer-associated variants compared to control cohorts.