Elisabetta Marangoni

The paper introduces OneCell CUT&Tag, a single-cell multi-omics method that captures chromatin, transcriptome, and surface marker data, revealing epigenomic reprogramming during mammary gland basal-to-luminal transition.

This study develops a Tumor-on-Chip platform for rapid drug testing in breast cancer, showing high concordance with patient-derived xenografts and potential for clinical use.

DIANNeR improves detection of GR interactomes in normal tissues by integrating DIA, ion mobility, and library-free analysis, revealing context-specific networks and previously undetected interactions.

This study uses spatial transcriptomics to analyze tumor microenvironment remodeling dynamics in triple-negative breast cancer, identifying early stromal programs as potential therapeutic targets.

The paper identifies a shared persistence program in triple-negative breast cancer across treatments and patients, revealing key drivers and mechanisms of drug resistance.

This study identifies force transmission as a key factor in cell competition, showing that stronger intercellular adhesion leads to cell elimination through mechanical stress fluctuations.

This paper develops chemotherapy-specific predictors for triple-negative breast cancer using patient-derived xenografts and multi-omic data, achieving high AUROC scores for response prediction.