Victoria L. Seewaldt

Spatial Landscape of Pregnancy-Associated Triple Negative Breast Cancer and Mammary Gland Involution

This study compares transcriptional differences between pre- and post-involution PA-TNBC tissues using spatial transcriptomics, identifying distinct inflammatory and chromatin remodeling patterns in post-involution tumors.

MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells

This paper develops MechanoAge, a machine learning tool that identifies breast cancer risk based on single-cell mechanical properties and introduces mechano-RISQ to quantify risk-related mechanical deviations.

Spatially distinct cellular and molecular landscapes define prognosis in triple negative breast cancer

This study uses spatial transcriptomics to identify molecular and cellular differences between good and poor prognosis triple-negative breast cancer subtypes, revealing distinct gene signatures that could inform therapy.

The Breakome of BRCA1 and BRCA2 Pathway Mutation Carriers Reveals Early Processes in Breast Oncogenesis

This study identifies DSB patterns in BRCAmut carriers to reveal early oncogenic processes linked to HR deficiency.

A novel subtyping method for TNBC with implications for prognosis and therapy

This paper identifies three subtypes of TNBC based on transcriptomic profiles and cell-type composition, linking them to potential therapeutic targets and clinical outcomes.

Hyperinsulinemia promotes aberrant histone acetylation in triple negative breast cancer

This study shows hyperinsulinemia increases histone acetylation and promotes tumor growth in TNBC via the PI3K/AKT/mTOR pathway.