Join us to explore the cutting-edge field of deep visual proteomics, where AI-assisted cell segmentation, laser microdissection, and mass spectrometry converge to offer new insights into disease mechanisms.
This webinar will highlight how spatial proteomics is transforming our understanding of disease biology and enabling impactful therapeutic breakthroughs.

Our presentation will showcase how Deep Visual Proteomics (DVP) technology has been applied to study the molecular progression of high-grade serous ovarian cancer from fallopian tube precursor lesions including p53 signatures, STILs, and STICs through to invasive ovarian cancer and metastasis. Using DVP's combination of AI-powered cell segmentation, laser capture microdissection, and ultra-sensitive mass spectrometry, Andreas and colleagues analyzed epithelial and stromal compartments separately with single-cell type resolution. Their analysis identified a total of over 8,500 unique protein groups in epithelial samples and 6,600 in stromal regions, confirming that secretory (and not ciliated) fallopian tube cells are the origin of dysplastic lesions. The research demonstrated that while p53 signatures appear similar to normal cells, STICs have distinct proteomes, very similar to those of invasive disease. Particularly notable was the finding that tumor stroma undergoes massive extracellular matrix remodeling with distinct collagen regulation patterns. This work provides unprecedented molecular insights into early ovarian cancer development with potential implications for early detection and therapeutic intervention.