Colm M. Morrissey

This study identifies proteomic signatures of prostate cancer bone metastasis subtypes, revealing distinct molecular states of bone-tumor microenvironment remodeling.

This paper develops a deep learning framework to infer gene expression from cell-free DNA, improving reliability and enabling functional genomics in precision oncology.

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 reprograms AR-active prostate cancer to NEPC using ASCL1 and NeuroD1, revealing their role in silencing AR and altering chromatin structure.

This study shows EphA2 overexpression and loss of its ligands in prostate cancer promote bone metastasis through noncanonical signaling in a ligand-deficient bone microenvironment.

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 single-cell analysis to study how cell surface antigen expression changes in treatment-resistant prostate cancer, revealing transcriptional heterogeneity and shared gene regulatory networks between NEPC and SCLC.

This study uses PS-OCT to differentiate bone tissue types in prostate cancer metastases by analyzing collagen organization and quantifying structural features.

This study shows MYC overexpression disrupts AR transcriptional pause release, promoting aggressive prostate cancer progression.