J. H. Chuang

Spatiotemporal profiling defines persistence and resistance dynamics during targeted treatment of melanoma

This study uses spatial transcriptomics and deep learning to analyze melanoma treatment resistance, identifying persister states and resistance mechanisms with spatiotemporal resolution.

Development and application of genetic ancestry reconstruction methods to study diversity of patient-derived models in the NCI PDXNet Consortium

The paper develops a genetic ancestry pipeline to assess diversity in PDX models and finds overrepresentation of European ancestry models, highlighting gaps in minority representation for cancer research.

Integrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality

This paper develops an integrative deep learning model combining image, clinical, and genomic data to improve risk stratification for colon adenocarcinoma patients, showing better performance than models using single data types.

PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery

The paper introduces the PDXNet Portal, a centralized resource for PDX models and data, offering analysis workflows and facilitating cancer research collaboration.

A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology

The paper develops patient-derived xenografts and organoids for breast cancer to enable drug screening and precision oncology, showing efficacy of an FDA-approved drug in a clinical case.

Defects in translation-dependent quality control pathways lead to convergent molecular and neurodevelopmental pathology

This study shows that defects in translation-dependent quality control pathways like NGD, NSD, and NMD lead to similar molecular and neurodevelopmental issues in cerebellar development.