E. Shelley Hwang

The paper identifies ECM proteomic signatures associated with disease-free survival in DCIS and IBC, showing reduced collagen peptides correlate with poorer outcomes.

This study identifies immune mimicry in breast cancer cells, where neoplastic cells express leukocyte receptors, enhancing tumor aggressiveness and therapy resistance.

This paper estimates the age of breast cancers using an epigenetic clock based on methylation data, finding that younger tumors are more aggressive while older tumors show higher immune infiltration.

This study uses scRNA-seq to analyze DCIS and normal breast tissue, identifying clonal heterogeneity and cell state changes associated with progression to invasive cancer.

This study identifies breast cancer subtypes and their lineage origins by analyzing chromatin accessibility and transcriptional dynamics using multi-omic techniques.

The paper analyzes molecular differences in ductal carcinoma in situ (DCIS) by self-reported race and outcome groups, identifying variations in gene expression, tumor microenvironment, and copy number variations between Black and White women.

This study reconstructs DCIS growth dynamics using somatic mutation topography, revealing a multiclonal, branching morphogenesis-like pattern consistent with a new Comet model of tumorigenesis.

The paper uses genomic profiling to show that some invasive breast cancers are clonally unrelated to their preceding DCIS, suggesting DCIS may act as both a precursor and independent risk factor.

This study uses ResolveOME to analyze genomic and transcriptomic data in individual cells, revealing mutations and gene expression changes linked to drug resistance and oncogenic mechanisms.

This paper develops and validates a new bioinformatic algorithm to accurately identify somatic SNVs from small DNA amounts in FFPE breast cancer samples, showing improved performance over existing methods.