How do some patients develop resistance to cancer treatment? The new method known as 'Deep Visual Proteomics' may be able to help doctors get closer to an answer and identify cancer tumor vulnerabilities. It is never easy for doctors to figure out why certain illnesses develop in our bodies. Old
Deep Visual Proteomics concept and workflow Clockwise: Deep Visual Proteomics combines high-resolution imaging, artificial intelligence -guided image analysis for single-cell classification and isolation with a novel ultra-sensitive proteomics workflow. DVP links data-rich imaging of cell culture or archived patient biobank tissues with deep learning-based cell segmentation and machine learning-based identification of cell types and states.
It is never easy for doctors to figure out why certain illnesses develop in our bodies. Old age, risky habits such as smoking, and genetics can all play a role.Now, a groundbreaking method known as “Deep Visual Proteomics” may be able to help change that. An international team of researchers led by “We do this by taking a tissue sample and analyzing just the tumor cells in it. This ‘list’ of proteins is called proteome. These proteomes reveal the mechanisms that drive tumor development and directly expose new therapeutic targets from a single tissue slice of a cancer patient biopsy.
In the new study, the researchers applied “Deep Visual Proteomics” to cells from patients with acinic cell carcinoma and melanoma. This was done in collaboration with researchers at the Zealand University Hospital, Roskilde.
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