Hunter Savignano

This study investigates how transcription factor subtypes in small cell lung cancer influence response and resistance to DLL3-targeted therapy, revealing subtype-specific mechanisms of resistance.

APEX infers cancer gene expression from plasma cfChIP-seq data, outperforming existing methods and enabling subtype classification and biomarker identification.

This paper detects and monitors translocation renal cell carcinoma (tRCC) using plasma cell-free epigenomic profiling, achieving high accuracy in distinguishing tRCC from other cancers and healthy controls.

SNAP improves classification performance for cell-free chromatin data while maintaining data retention through optimized quality filters and modular design.

The paper infers enhancer activity from cfDNA fragmentation patterns and proposes a chromatin fiber model to explain these signatures.

The paper identifies epigenomic signatures in sarcomatoid renal cell carcinoma (sRCC) that predict response to immune checkpoint inhibitors and are detectable in plasma, enabling non-invasive diagnosis.