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A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells

ABSTRACT: A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells

PROVIDER: PRJNA896190 | ENA |

REPOSITORIES: ENA

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A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells

Project description:A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells.

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A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells

Project description:Human cancer cell lines were pulsed with thymidine analogues EdU and BrdU, sequenced on the Oxford Nanopore platform, and analysed with our DNAscent software to measure DNA replication stress.

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RNA-seq of S. cerevisiae with DOPAC and 4-nitrocatechol to investigate how Artificial Intelligence uncovers human carcinogenic metabolites

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Project description:Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) plays a pivotal role in preventing autoimmunity and fostering anticancer immunity by interacting with B7 proteins CD80 and CD86. CTLA-4 is the first immune checkpoint targeted with a monoclonal antibody inhibitor. Checkpoint inhibitors have generated durable responses in many cancer patients, representing a revolutionary milestone in cancer immunotherapy. However, therapeutic efficacy is limited to a small portion of patients, and immune-related adverse events are noteworthy, especially for monoclonal antibodies directed against CTLA-4. Previously, small molecules have been developed to impair the CTLA-4: CD80 interaction; however, they directly targeted CD80 and not CTLA-4. In this study, we performed artificial intelligence (AI)-powered virtual screening of approximately ten million compounds to target CTLA-4. We validated primary hits with biochemical, biophysical, immunological, and experimental animal assays. We then optimized lead compounds and obtained inhibitors with an inhibitory concentration of 1 micromole in disrupting the interaction between CTLA-4 and CD80. Unlike ipilimumab, these small molecules did not degrade CTLA-4. Several compounds inhibited tumor development prophylactically and therapeutically in syngeneic and CTLA-4-humanized mice. This project supports an AI-based framework in designing small molecules targeting immune checkpoints for cancer therapy.

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