(1080-A) NanoBeacon.AI: AI-enhanced nanodiamond biosensor for automated sensitivity prediction to oxidative phosphorylation inhibitors

Abstract: Spalt-like transcription factor 4 (SALL4) is an oncofetal protein that has been identified to drive cancer progression in hepatocellular carcinoma (HCC) and hematological malignancies. Furthermore, high SALL4 expression level is correlated to poor prognosis in these cancers. However, SALL4 lacks well-structured small molecule binding pockets, making it difficult to design targeted inhibitors. SALL4-induced expression of oxidative phosphorylation (OXPHOS) genes may serve as a therapeutically targetable vulnerability in HCC through OXPHOS inhibition. Because OXPHOS functions through a set of genes with intertumoral heterogenous expression, identifying therapeutic sensitivity to OXPHOS inhibitors may not rely on a single clear biomarker. Here, we developed a workflow that utilized molecular beacons, nucleic-acid-based, activatable sensors with high specificity to the target mRNA, delivered by nanodiamonds, to establish an artificial intelligence (AI)-assisted platform for rapid evaluation of patient-specific drug sensitivity. Specifically, when the HCC cells were treated with the nanodiamond-medicated OXPHOS biosensor, high sensitivity and specificity of the sensor allowed for improved identification of OXPHOS expression in cells. Assisted by a trained convolutional neural network, drug sensitivity of cells towards an OXPHOS inhibitor, IACS-010759, could be accurately predicted. AI-assisted OXPHOS drug sensitivity assessment could be accomplished within one day, enabling rapid and efficient clinical decision support for HCC treatment. The work proposed here serves as a foundation for the patient-based subtype-specific therapeutic research platform and is well suited for precision medicine.