Natasha Rekhtman

P-selectin-targeted fucoidan nanoparticles carrying Navitoclax or dBET6 deplete a senescent-like, lipid-associated macrophage subset, reverse mouse liver and lung fibrosis with less toxicity, and restore checkpoint therapy response in fibrotic tumors.

The paper analyzes the evolutionary trajectories of high-level copy-number amplifications in cancer cell genomes to distinguish between extrachromosomal and intrachromosomal amplification mechanisms.

The paper develops Mosaic, a machine learning system that classifies tumors into detailed subtypes and identifies molecular phenotypes using histopathologic and genomic data from a large patient cohort.

The paper uses single-cell analysis to study how cell surface antigen expression changes in treatment-resistant prostate cancer, revealing transcriptional heterogeneity and shared gene regulatory networks between NEPC and SCLC.

This paper uses optical spectroscopy and machine learning to rapidly identify malignant tissue in cancer biopsies, achieving high sensitivity and specificity.