Jeffrey R. Marks

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

The paper shows that bulk transcriptomic subtypes in HGSC reflect tumor composition rather than intrinsic biology, with composition predicting subtype and prognosis.

This study estimates tumor mitotic ages in neuroblastoma patients to show aggressive tumors start growing after infancy, making them undetectable by infant screening.

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.

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 identifies molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms, finding similar subtype-specific survival rates despite differences in subtype prevalence.

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.