Paradoxical androgen receptor regulation by small molecule enantiomers.

Small molecules that target the androgen receptor (AR) are the mainstay of therapy for lethal castration-resistant prostate cancer (CRPC), yet existing drugs lose their efficacy during continued treatment. This evolution of resistance is due to heterogenous mechanisms which include AR mutations causing the identical drug to activate instead of inhibit the receptor. Understanding in molecular detail the paradoxical phenomenon wherein an AR antagonist is transformed into an agonist by structural mutations in the target receptor is thus of paramount importance. Herein, we describe a reciprocal paradox: opposing antagonist and agonist AR regulation determined uniquely by enantiomeric forms of the same drug structure. The antiandrogen BMS-641988, which has (R)-chirality at C-5 encompasses a previously uncharacterized (S)-stereoisomer that is, surprisingly, a potent agonist of AR, as demonstrated by transcriptional assays supported by cell imaging studies. This duality was reproduced in a series of novel compounds derived from the BMS-641988 scaffold. Coupled with in silico modeling studies, the results inform an AR model that explains the switch from potent antagonist to high-affinity agonist in terms of C-5 substituent steric interactions with helix 12 of the ligand binding site. They imply strategies to overcome AR drug resistance and demonstrate that insufficient enantiopurity in this class of AR antagonist can confound efforts to correlate structure with function.

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response.

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.

Monitoring dynamic cytotoxic chemotherapy response in castration-resistant prostate cancer using plasma cell-free DNA (cfDNA).

OBJECTIVE: Cell-free DNA (cfDNA) is an attractive cancer biomarker, as it is thought to reflect a component of the underlying genetic makeup of the tumor and is readily accessible in serial fashion. Because chemotherapy regimens are expected to act rapidly on cancer and cfDNA is cleared from the blood within minutes, we hypothesized that cfDNA would reflect immediate effects of treatment. Here, we developed a method for monitoring long cfDNA fragments, and report dynamic changes in response to cytotoxic chemotherapy. RESULTS: Peripheral blood was obtained from 15 patients with metastatic castration-resistant prostate cancer (CRPC) immediately before and after cytotoxic chemotherapy infusion. cfDNA was extracted and quantified for long interspersed nuclear elements (LINE1; 297 bp) using qPCR. Targeted deep sequencing was performed to quantify the frequency of mutations in exon 8 of the androgen receptor (AR), a mutational hotspot region in CRPC. Single nucleotide mutations in AR exon 8 were found in 6 subjects (6/15 = 40%). Analytical variability was minimized by pooling independent PCR reactions for each library. In 5 patients, tumor-derived long cfDNA levels were found to change immediately after infusion. Detailed analysis of one subject suggests that cytotoxic chemotherapy can produce rapidly observable effects on cfDNA.

Image-Based Tracking of Heterogeneous Single-Cell Phenotypes.

Cells display broad heterogeneity across multiple phenotypic features, including motility, morphology, and cell signaling. Live-cell imaging techniques are beginning to capture the importance and interdependence of these phenomena. However, existing image analysis pipelines often fail to capture the intricate changes that occur in small subpopulations, either due to poor segmentation protocols or cell tracking errors. Here we report a pipeline designed to image and track single-cell dynamic phenotypes in heterogeneous cell populations. We provide step-by-step instructions for three phenotypically different cell lines across two time scales as well as recommendations for adaptation to custom data sets. Our protocols include steps for quality control that can be used to filter out erroneous tracks and improve assessment of heterogeneity. We demonstrate possible phenotypic readouts including motility, nuclear receptor translocation, and mitosis.

Single cell dynamic phenotyping.

Live cell imaging has improved our ability to measure phenotypic heterogeneity. However, bottlenecks in imaging and image processing often make it difficult to differentiate interesting biological behavior from technical artifact. Thus there is a need for new methods that improve data quality without sacrificing throughput. Here we present a 3-step workflow to improve dynamic phenotype measurements of heterogeneous cell populations. We provide guidelines for image acquisition, phenotype tracking, and data filtering to remove erroneous cell tracks using the novel Tracking Aberration Measure (TrAM). Our workflow is broadly applicable across imaging platforms and analysis software. By applying this workflow to cancer cell assays, we reduced aberrant cell track prevalence from 17% to 2%. The cost of this improvement was removing 15% of the well-tracked cells. This enabled detection of significant motility differences between cell lines. Similarly, we avoided detecting a false change in translocation kinetics by eliminating the true cause: varied proportions of unresponsive cells. Finally, by systematically seeking heterogeneous behaviors, we detected subpopulations that otherwise could have been missed, including early apoptotic events and pre-mitotic cells. We provide optimized protocols for specific applications and step-by-step guidelines for adapting them to a variety of biological systems.

TIS7 induces transcriptional cascade of methylosome components required for muscle differentiation.

BACKGROUND: TPA Induced Sequence 7 acts as a transcriptional co-regulator controlling the expression of genes involved in differentiation of various cell types, including skeletal myoblasts. We and others have shown that TIS7 regulates adult myogenesis through MyoD, one of the essential myogenic regulatory factors. RESULTS: Here, we present data identifying ICln as the specific, novel protein downstream of TIS7 controlling myogenesis. We show that TIS7/ICln epigenetically regulate myoD expression controlling protein methyl transferase activity. In particular, ICln regulates MyoD expression via its interaction with PRMT5 by an epigenetic modification that utilizes symmetrical di-methylation of histone H3 on arginine 8. We provide multiple evidences that TIS7 directly binds DNA, which is a functional feature necessary for its role in transcriptional regulation. CONCLUSION: We present here a molecular insight into TIS7-specific control of MyoD gene expression and thereby skeletal muscle differentiation.

Intracellular kinetics of the androgen receptor shown by multimodal Image Correlation Spectroscopy (mICS).

The androgen receptor (AR) pathway plays a central role in prostate cancer (PCa) growth and progression and is a validated therapeutic target. In response to ligand binding AR translocates to the nucleus, though the molecular mechanism is not well understood. We therefore developed multimodal Image Correlation Spectroscopy (mICS) to measure anisotropic molecular motion across a live cell. We applied mICS to AR translocation dynamics to reveal its multimodal motion. By integrating fluorescence imaging methods we observed evidence for diffusion, confined movement, and binding of AR within both the cytoplasm and nucleus of PCa cells. Our findings suggest that in presence of cytoplasmic diffusion, the probability of AR crossing the nuclear membrane is an important factor in determining the AR distribution between cytoplasm and the nucleus, independent of functional microtubule transport. These findings may have implications for the future design of novel therapeutics targeting the AR pathway in PCa.