Discovery and validation of small-molecule heat-shock protein 90 inhibitors through multimodality molecular imaging in living subjects

Up-regulation of the folding machinery of the heat-shock protein 90 (Hsp90) chaperone protein is crucial for cancer progression. The two Hsp90 isoforms (α and β) play different roles in response to chemotherapy. To identify isoform-selective inhibitors of Hsp90(α/β)/cochaperone p23 interactions, we developed a dual-luciferase (Renilla and Firefly) reporter system for high-throughput screening (HTS) and monitoring the efficacy of Hsp90 inhibitors in cell culture and live mice. HTS of a 30,176 small-molecule chemical library in cell culture identified a compound, N-(5-methylisoxazol-3-yl)-2-[4-(thiophen-2-yl)-6-(trifluoromethyl)pyrimidin-2-ylthio]acetamide (CP9), that binds to Hsp90(α/β) and displays characteristics of Hsp90 inhibitors, i.e., degradation of Hsp90 client proteins and inhibition of cell proliferation, glucose metabolism, and thymidine kinase activity, in multiple cancer cell lines. The efficacy of CP9 in disrupting Hsp90(α/β)/p23 interactions and cell proliferation in tumor xenografts was evaluated by non-invasive, repetitive Renilla luciferase and Firefly luciferase imaging, respectively. At 38 h posttreatment (80 mg/kg × 3, i.p.), CP9 led to selective disruption of Hsp90α/p23 as compared with Hsp90β/p23 interactions. Small-animal PET/CT in the same cohort of mice showed that CP9 treatment (43 h) led to a 40% decrease in 18F-fluorodeoxyglucose uptake in tumors relative to carrier control-treated mice. However, CP9 did not lead to significant degradation of Hsp90 client proteins in tumors. We performed a structural activity relationship study with 62 analogs of CP9 and identified A17 as the lead compound that outperformed CP9 in inhibiting Hsp90(α/β)/p23 interactions in cell culture. Our efforts demonstrated the power of coupling of HTS with multimodality molecular imaging and led to identification of Hsp90 inhibitors

Thermodynamics of Aryl-Dihydroxyphenyl-Thiadiazole Binding to Human Hsp90

The design of specific inhibitors against the Hsp90 chaperone and other enzyme relies on the detailed and correct understanding of both the thermodynamics of inhibitor binding and the structural features of the protein-inhibitor complex. Here we present a detailed thermodynamic study of binding of aryl-dihydroxyphenyl-thiadiazole inhibitor series to recombinant human Hsp90 alpha isozyme. The inhibitors are highly potent, with the intrinsic Kd approximately equal to 1 nM as determined by isothermal titration calorimetry (ITC) and thermal shift assay (TSA). Dissection of protonation contributions yielded the intrinsic thermodynamic parameters of binding, such as enthalpy, entropy, Gibbs free energy, and the heat capacity. The differences in binding thermodynamic parameters between the series of inhibitors revealed contributions of the functional groups, thus providing insight into molecular reasons for improved or diminished binding efficiency. The inhibitor binding to Hsp90 alpha primarily depended on a large favorable enthalpic contribution combined with the smaller favorable entropic contribution, thus suggesting that their binding was both enthalpically and entropically optimized. The enthalpy-entropy compensation phenomenon was highly evident when comparing the inhibitor binding enthalpies and entropies. This study illustrates how detailed thermodynamic analysis helps to understand energetic reasons for the binding efficiency and develop more potent inhibitors that could be applied for therapeutic use as Hsp90 inhibitors

17-allyamino-17-demethoxygeldanamycin treatment results in a magnetic resonance spectroscopy-detectable elevation in choline-containing metabolites associated with increased expression of choline transporter SLC44A1 and phospholipase A2

Abstract Introduction 17-allyamino-17-demethoxygeldanamycin (17-AAG), a small molecule inhibitor of Hsp90, is currently in clinical trials in breast cancer. However, 17-AAG treatment often results in inhibition of tumor growth rather than shrinkage, making detection of response a challenge. Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are noninvasive imaging methods than can be used to monitor metabolic biomarkers of drug-target modulation. This study set out to examine the MRS-detectable metabolic consequences of Hsp90 inhibition in a breast cancer model. Methods MCF-7 breast cancer cells were investigated, and MRS studies were performed both on live cells and on cell extracts. 31P and 1H MRS were used to determine total cellular metabolite concentrations and 13C MRS was used to probe the metabolism of [1,2-13C]-choline. To explain the MRS metabolic findings, microarray and RT-PCR were used to analyze gene expression, and in vitro activity assays were performed to determine changes in enzymatic activity following 17-AAG treatment. Results Treatment of MCF-7 cells with 17-AAG for 48 hours caused a significant increase in intracellular levels of choline (to 266 ± 18% of control, P = 0.05) and phosphocholine (PC; to 181 ± 10% of control, P = 0.001) associated with an increase in expression of choline transporter SLC44A1 and an elevation in the de novo synthesis of PC. We also detected an increase in intracellular levels of glycerophosphocholine (GPC; to 176 ± 38% of control, P = 0.03) associated with an increase in PLA2 expression and activity. Conclusions This study determined that in the MCF-7 breast cancer model inhibition of Hsp90 by 17-AAG results in a significant MRS-detectable increase in choline, PC and GPC, which is likely due to an increase in choline transport into the cell and phospholipase activation. 1H MRSI can be used in the clinical setting to detect levels of total choline-containing metabolite (t-Cho, composed of intracellular choline, PC and GPC). As Hsp90 inhibitors enter routine clinical use, t-Cho could thus provide an easily detectable, noninvasive metabolic biomarker of Hsp90 inhibition in breast cancer patients

Estimation of a Tobit model with unknown censoring threshold

Conventional wisdom suggests that only the estimated intercept is affected by imposition of a zero censoring threshold on a Tobit model. This is true for Heckman-Lee estimation. For maximum likelihood (ML) estimation, however, it is only true if the censoring threshold is known and is subtracted from the dependent variable. Failure to properly transform the dependent variable prior to ML estimation of a zero threshold Tobit model will generally bias the coefficient estimates. A long neglected topic is ML estimation of a Tobit model with common, but unknown, censoring threshold. This paper shows that the ML estimator of the censoring threshold is the minimum order statistic from the observed subsample, and that existing software for estimation of a zero-threshold Tobit model is easily adapted to include estimation of the censoring threshold.

Analysis of competing awards that were solicited for HE and NIH (excluding HE) research from FY2010 to FY2020.

Award counts were divided by the total number of awards for HE and non-HE research for each Fiscal Year. (TIF)</p