Y. H. Chang

This study creates a multimodal tumor atlas to analyze how metastatic HR+ breast cancers adapt to CDK4/6 inhibitors, revealing mechanisms like mTORC1 activation and immune microenvironment changes.

This paper develops a novel mouse model of TNBC by combining MYC amplification and PTEN deletion, showing it recapitulates human TNBC heterogeneity through omic analyses.

The paper shows that T cell egress via lymphatic vessels limits intratumoral T cell diversity, and that CXCR4 inhibition enhances T cell retention and improves immunotherapy response.

This study examines cardiac anatomy in shrews, finding that most traits scale to their small size, but they have unique features like large coronary vessels and extended pulmonary venous myocardium.

This paper uses transfer learning to predict metastatic origin from H&E-stained tumor images, achieving higher accuracy than models trained on primary or metastatic tumors alone.

This study identifies circulating hybrid cells (CHCs) as a novel biomarker for metastatic solid tumors, showing they outnumber CTCs and exhibit tumor-initiating properties across multiple cancer types.

This paper presents an OMS Atlas from serial biopsies of a metastatic breast cancer patient, linking clinical data to multi-omic and spatial profiles to study therapy-associated heterogeneity and resistance mechanisms.

The paper introduces a deep learning model to predict the metastatic origin of secondary liver cancer from H&E stained tissue sections, achieving 90.2% accuracy comparable to expert pathologists.

This study investigates how HER2 dynamics in filopodia regulate protrusion growth and signaling in breast cancer cells, revealing distinct motion patterns and functional roles in protrusion-based signaling.

This study uses single-particle tracking to show that KRas diffusion and trafficking are regulated by nested membrane nanodomains in U2OS cells.