Wouter R. Karthaus

Generative modeling reveals the connection between nuclear morphology and gene expression

COSMIC, a generative model, quantifies the relationship between nuclear morphology and gene expression using paired single-cell data, revealing morphology-associated genes in prostate cancer and spatial transcriptomics of zebrafish embryos.

Single-cell phenomics through integrated imaging and molecular profiling

The paper introduces IRIS, a platform integrating high-resolution imaging and single-cell RNA sequencing to link morphology with transcriptomes, revealing new nuclear-ER architectures in CD8+ T cells.

TRIM24 Degradation Counteracts Adaptation to Androgen Receptor Inhibition in Prostate Cancer

This study identifies TRIM24 as a target for preventing prostate cancer progression by degrading it to counteract AR inhibition adaptation and tumor relapse.

BRCA2 reversion mutation-independent resistance to PARP inhibition in prostate cancer through loss of function perturbations in the DNA pre-replication complex

This study identifies loss of function mutations in the DNA pre-replication complex as a mechanism for PARP inhibitor resistance in BRCA-mutant prostate cancer, independent of reversion mutations.

Reconstructing tumor evolution without chromosomal instability reveals in vivo determinants of therapeutic response

This study develops an in vivo platform called SETs to reconstruct tumor evolution without chromosomal instability, identifying therapeutic response determinants in prostate cancer.

Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function

The paper introduces a topological framework to detect and disentangle multiple cyclic processes from single-cell transcriptomic data, validated on synthetic datasets and biological samples.

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

This study identifies ASCL1 as a critical driver of neuroendocrine lineage transition in prostate cancer using an in vivo model and spatial transcriptomics.

Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies

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.

Tumor mutational landscape is a record of the pre-malignant state

The paper predicts cancer cell-of-origin from DNA sequences by matching mutational landscapes to chromatin modification patterns in normal tissues.