Novel STAT3 Inhibitors Targeting STAT3 Dimerization by Binding to the STAT3 SH2 Domain.

Our drug discovery model has identified two novel STAT3 SH2 domain inhibitors 323-1 and 323-2 (delavatine A stereoisomers) in a series of experiments. In silico computational modeling, drug affinity responsive target stability (DARTS), and fluorescence polarization (FP) assays altogether determined that 323-1 and 323-2 directly target the STAT3 SH2 domain and inhibited both phosphorylated and non-phosphorylated STAT3 dimerization. Computational docking predicted that compound 323s bind to three subpockets of the STAT3 SH2 domain. The 323s inhibition of STAT3 dimerization was more potent than the commercial STAT3 SH2 domain inhibitor S3I-201 in the co-immunoprecipitation assay, correlating with computational docking data. The fluorescence polarization assay further confirmed that the compound 323s target the STAT3 SH2 domain by competitively abrogating the interaction between STAT3 and the SH2-binding peptide GpYLPQTV. Compared with S3I-201, the 323 compounds exhibited stronger inhibition of STAT3 and reduced the level of IL-6-stimulated phosphorylation of STAT3 (Tyr705) in LNCaP cells over the phosphorylation of STAT1 (Tyr701) induced by IFN-É£ in PC3 cells or the phosphorylation of STAT1 (Ser727) in DU145 cells. Both compounds downregulated STAT3 target genes MCL1 and cyclin D1. Thus, the two compounds are promising lead compounds for the treatment of cancers with hyper-activated STAT3.

Ex vivo drug sensitivity screening in multiple myeloma identifies drug combinations that act synergistically.

The management of multiple myeloma (MM) is challenging: An assortment of available drug combinations adds complexity to treatment selection, and treatment resistance frequently develops. Given the heterogeneous nature of MM, personalized testing tools are required to identify drug sensitivities. To identify drug sensitivities in MM cells, we established a drug testing pipeline to examine ex vivo drug responses. MM cells from 44 patients were screened against 30 clinically relevant single agents and 44 double- and triple-drug combinations. We observed variability in responses across samples. The presence of gain(1q21) was associated with low sensitivity to venetoclax, and decreased ex vivo responses to dexamethasone reflected the drug resistance observed in patients. Less heterogeneity and higher efficacy was detected with many combinations compared to the corresponding single agents. We identified new synergistic effects of melflufen plus panobinostat using low concentrations (0.1-10 nm and 8 nm, respectively). In agreement with clinical studies, clinically approved combinations, such as triple combination of selinexor plus bortezomib plus dexamethasone, acted synergistically, and synergies required low drug concentrations (0.1 nm bortezomib, 10 nm selinexor and 4 nm dexamethasone). In summary, our drug screening provided results within a clinically actionable 5-day time frame and identified synergistic drug efficacies in patient-derived MM cells that may aid future therapy choices.

Differential array sensing for cancer cell classification and novelty detection.

A series of semi-specific peptides reported in the literature to bind various epitopes on cell surfaces were used in a differential sensing array to pattern cell line identity. The peptides were conjugated to thiazole orange to act as both a fluorescence reporter and a DNA intercalator. Fluorescence data for the peptides exposed to cells, with and without exogenous double stranded DNA (dsDNA), led to chemometric fingerprints for eight cancer cell lines. In contrast to the use of structures meant to act in completely non-specific ways, the use of a limited level of specificity generated linear discriminant score plots with high dimensionality, i.e. several principle components carrying significant variance. The arrays were found to correctly classify the cell lines from 60% to 100% depending upon the cell line. Due to the high dimensionality score plots, the identification of cell lines that were not part of the training set was examined. Support vector machines were used as a novelty detection routine and showed that a cancer line not part of the original training set could be correctly identified as being novel.

Next-generation sequencing as input for chemometrics in differential sensing routines.

Differential sensing (DS) methods traditionally use spatially arrayed receptors and optical signals to create score plots from multivariate data which classify individual analytes or complex mixtures. Herein, a new approach is described, in which nucleic acid sequences and sequence counts are used as the multivariate data without the necessity of a spatial array. To demonstrate this approach to DS, previously selected aptamers, identified from the literature, were used as semi-specific receptors, Next-Gen DNA sequencing was used to generate data, and cell line differentiation was the test-bed application. The study of a principal component analysis loading plot revealed cross-reactivity between the aptamers. The technique generates high-dimensionality score plots, and should be applicable to any mixture of complex and subtly different analytes for which nucleic acid-based receptors exist.

Chiral amine enantiomeric excess determination using self-assembled octahedral Fe(II)-imine complexes.

A receptor assembly composed of iron(II) triflate and pyridine-2,6-dicarbaldehyde was used to determine the enantiomeric excess (ee) of alpha-chiral primary amines using circular dichroism spectroscopy. The alpha chiral amines condense with the dialdehyde to form a diimine, which forms a 2:1 octahedral complex with iron(II). The ee values of unknown concentrations of alpha-chiral amines were determined by constructing calibration curves for each amine and then measuring the ellipticity at 600 nm. This improves our previously reported assay for ee determination of chiral primary amines by further increasing the wavelength at which CD is measured and reducing the absolute error of the assay.