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Aerobic glycolysis in cancer cells, also known as the ‘Warburg effect’, is driven by hyperactivity of lactate dehydrogenase A (LDHA). LDHA is thought to be a substrate-regulated enzyme, but it is unclear whether a dedicated intracellular protein also regulates its activity. Here, we identify the human tumor suppressor folliculin (FLCN) as a binding partner and uncompetitive inhibitor of LDHA. A flexible loop within the amino terminus of FLCN controls movement of the LDHA active-site loop, tightly regulating its enzyme activity and, consequently, metabolic homeostasis in normal cells. Cancer cells that experience the Warburg effect show FLCN dissociation from LDHA. Treatment of these cells with a decapeptide derived from the FLCN loop region causes cell death. Our data suggest that the glycolytic shift of cancer cells is the result of FLCN inactivation or dissociation from LDHA. Together, FLCN-mediated inhibition of LDHA provides a new paradigm for the regulation of glycolysis.

We identified a set of thiosemicarbazone (TSC) metal ion chelators that reactivate specific zinc-deficient p53 mutants using a mechanism called zinc metallochaperones (ZMCs) that restore zinc binding by shuttling zinc into cells. We defined biophysical and cellular assays necessary for structure–activity relationship studies using this mechanism. We investigated an alternative class of zinc scaffolds that differ from TSCs by substitution of the thiocarbamoyl moiety with benzothiazolyl, benzoxazolyl, and benzimidazolyl hydrazones. Members of this series bound zinc with similar affinity and functioned to reactivate mutant p53 comparable to the TSCs. Acute toxicity and efficacy assays in rodents demonstrated C1to be significantly less toxic than the TSCs while demonstrating equivalent growth inhibition. We identified C85as a ZMC with diminished copper binding that functions as a chemotherapy and radiation sensitizer. We conclude that the benzothiazolyl, benzoxazolyl, and benzimidazolyl hydrazones can function as ZMCs to reactivate mutant p53 in vitroand in vivo.

Antibodies are the most prolific biologics in research and clinical environments because of their ability to bind targets with high affinity and specificity. However, antibodies also carry liabilities. A significant portion of the life-science reproducibility crisis is driven by inconsistent performance of research-grade antibodies, and clinical antibodies are often unstable and require costly cold-chain management to reach their destinations in active form. In biotechnology, antibodies are also limited by difficulty integrating them in many recombinant systems due to their size and structural complexity. A switch to small, stable, sequence-verified binding scaffolds may overcome these barriers. Here we present such a scaffold, RPtag, based on a ribose-binding protein (RBP) from extremophile Caldanaerobacter subterraneus. RPtag binds an optimized peptide with pM affinity, is stable to extreme temperature, pH, and protease treatment, readily refolds after denaturation, is effective in common laboratory applications, was rationally engineered to bind bioactive PDGF-β, and was formulated as a gut-stable orally bioavailable preparation.

Although fundamentally significant in structural, chemical, and membrane biology, the interfacial protein-detergent complex (PDC) interactions have been modestly examined because of the complicated behavior of both detergents and membrane proteins in aqueous phase. Membrane proteins are prone to unproductive aggregation resulting from poor detergent solvation, but the participating forces in this phenomenon remain ambiguous. Here, we show that using rational membrane protein design, targeted chemical modification, and steady-state fluorescence polarization spectroscopy, the detergent desolvation of membrane proteins can be quantitatively evaluated. We demonstrate that depleting the detergent in the sample well produced a two-state transition of membrane proteins between a fully detergent-solvated state and a detergent-desolvated state, the nature of which depended on the interfacial PDC interactions. Using a panel of six membrane proteins of varying hydrophobic topography, structural fingerprint, and charge distribution on the solvent-accessible surface, we provide direct experimental evidence for the contributions of the electrostatic and hydrophobic interactions to the protein solvation properties. Moreover, all-atom molecular dynamics simulations report the major contribution of the hydrophobic forces exerted at the PDC interface. This semiquantitative approach might be extended in the future to include studies of the interfacial PDC interactions of other challenging membrane protein systems of unknown structure. This would have practical importance in protein extraction, solubilization, stabilization, and crystallization.

Advances in imaging and spectroscopic technologies have enabled the optimization of many therapeutic modalities in cancer and noncancer pathologies either by earlier disease detection or by allowing therapy monitoring. Amongst the therapeutic options benefiting from developments in imaging technologies, photodynamic therapy (PDT) is exceptional. PDT is a photochemistry-based therapeutic approach where a light-sensitive molecule (photosensitizer) is activated with light of appropriate energy (wavelength) to produce reactive molecular species such as free radicals and singlet oxygen. These molecular entities then react with biological targets such as DNA, membranes and other cellular components to impair their function and lead to eventual cell and tissue death. Development of PDT-based imaging also provides a platform for rapid screening of new therapeutics in novel in vitro models prior to expensive and labor-intensive animal studies. In this study we demonstrate how an imaging platform can be used for strategizing a novel combination treatment strategy for multifocal ovarian cancer. Using an in vitro 3D model for micrometastatic ovarian cancer in conjunction with quantitative imaging we examine dose and scheduling strategies for PDT in combination with carboplatin, a chemotherapeutic agent presently in clinical use for management of this deadly form of cancer.

Three-dimensional in vitro tumor models have emerged as powerful research tools in cancer biology, though the vast potential of these systems as high-throughput, biologically relevant reporters of treatment response has yet to be adequately explored. Here, building on previous studies, we demonstrate the utility of using 3D models for ovarian and pancreatic cancers in conjunction with quantitative image processing to reveal aspects of growth behavior and treatment response that would not be evident without either modeling or quantitative analysis component. In this report we specifically focus on recent improvements in the imaging component of this integrative research platform and emphasize analysis to establish reproducible growth properties in 3D tumor arrays, a key consideration in establishing the utility of this platform as a reliable reporter of therapeutic response. Building on previous studies using automated segmentation of low magnification image fields containing large numbers of nodules to study size dependent treatment effects, we introduce an improvement to this method using multiresolution decomposition to remove gradient background from transmitted light images for more reliable feature identification. This approach facilitates the development of a new treatment response metric, disruption fraction (Dfrac), which quantifies dose dependent distribution shifts from nodular fragmentation induced by cytotoxic therapies. Using this approach we show that PDT treatment is associated with significant dose-dependent increases in Dfrac, while this is not observed with carboplatin treatment. The ability to quantify this response to therapy could play a key role in design of combination regimens involving these two modalities.