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Abstract Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds’ known modes-of-action (MoA) were enriched among the compounds’ CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles. 

Abstract Aggressive cancers, characterized by high metastatic potential and resistance to conventional therapies, present a significant challenge in oncology. Current treatments often fail to effectively target metastasis, recurrence, and the immunosuppressive tumor microenvironment, while causing significant off‐target toxicity. Here, superparamagnetic copper iron oxide nanoparticles (SCIONs) as a multifunctional platform that integrates magnetic hyperthermia therapy, immune modulation, and targeted chemotherapeutic delivery, aiming to provide a more comprehensive cancer treatment is presented. Specifically, SCIONs generate localized hyperthermia under an alternating magnetic field while delivering a copper‐based anticancer agent, resulting in a synergistic anticancer effect. The hyperthermia induced by SCIONs caused ER stress and ROS production, leading to significant tumor cell death, while the copper complex further enhanced oxidative stress, ferroptosis, and apoptosis. Beyond direct cytotoxicity, SCIONs disrupted the tumor microenvironment by inhibiting cancer‐associated fibroblasts, downregulating epithelial‐mesenchymal transition markers, and reducing cell migration and invasion, thereby limiting metastasis. Additionally, SCION‐based therapy reprogrammed the immune microenvironment by inducing immunogenic cell death and enhancing dendritic cell activation, resulting in increased CD8+ T cell infiltration and amplified antitumor immunity. This integrated approach targets primary and metastatic tumors while mitigating immunosuppression, offering a promising next‐generation therapy for combating cancer with enhanced efficacy and reduced side effects. 

We propose new methods for learning control policies and neural network Lyapunov functions for nonlinear control problems, with provable guarantee of stability. The framework consists of a learner that attempts to find the control and Lyapunov functions, and a falsifier that finds counterexamples to quickly guide the learner towards solutions. The procedure terminates when no counterexample is found by the falsifier, in which case the controlled nonlinear system is provably stable. The approach significantly simplifies the process of Lyapunov control design, provides end-to-end correctness guarantee, and can obtain much larger regions of attraction than existing methods such as LQR and SOS/SDP. We show experiments on how the new methods obtain high-quality solutions for challenging robot control problems such as path tracking for wheeled vehicles and humanoid robot balancing.