Preclinical testing of the glycogen synthase kinase-3β inhibitor tideglusib for rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma. RMS often arise from myogenic precursors and displays a poorly differentiated skeletal muscle phenotype most closely resembling regenerating muscle. GSK3β is a ubiquitously expressed serine-threonine kinase capable of repressing the terminal myogenic differentiation program in cardiac and skeletal muscle. Recent unbiased chemical screening efforts have prioritized GSK3β inhibitors as inducers of myodifferentiation in RMS, suggesting efficacy as single agents in suppressing growth and promoting self-renewal in zebrafish transgenic embryonal RMS (eRMS) models in vivo. In this study, we tested the irreversible GSK3β-inhibitor, tideglusib for in vivo efficacy in patient-derived xenograft models of both alveolar rhabdomyosarcoma (aRMS) and eRMS. Tideglusib had effective on-target pharmacodynamic efficacy, but as a single agent had no effect on tumor progression or myodifferentiation. These results suggest that as monotherapy, GSK3β inhibitors may not be a viable treatment for aRMS or eRMS

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

BACKGROUND: Cancer patients with advanced disease routinely exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates molecular sequencing data with functional assay data to develop patient-specific combination cancer treatments. METHODS: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the primary murine tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient's epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient's primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. RESULTS: Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). CONCLUSIONS: These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research

Movement Disorders and Neurochemical Changes in Zebrafish Larvae After Bath Exposure to Fluoxetine (PROZAC)

This study examines the effects of the selective serotonin reuptake inhibitor (SSRI), fluoxetine (PROZAC), on the ontogeny of spontaneous swimming activity (SSA) in developing zebrafish. The development of zebrafish motor behavior consists of four sequential locomotor patterns that develop over 1-5 days post fertilization (dpf), with the final pattern, SSA, established at 4-5 dpf. In stage specific experiments, larvae were exposed to 4.6 μM fluoxetine for 24 h periods beginning at 24 h post fertilization (hpf) and extending through 5 dpf. From 1-3 dpf, there was no effect on SSA or earlier stages of motor development, i.e., spontaneous coiling, evoked coiling and burst swimming. Fluoxetine exposure at 3 dpf for 24 h resulted in a transient decrease in SSA through 7 dpf with a complete recovery by 8 dpf. Larvae exposed to 4.6 μM fluoxetine for 24 h on 4 or 5 dpf showed a significant decrease in SSA by day 6 with no recovery through 14 dpf. Although SSA was significantly affected 24 h after fluoxetine exposure, there was little or no effect on pectoral fin movement. These results demonstrate both a stage specific and a long term effect of 4.6 μM fluoxetine exposure in 4 and 5 dpf larvae. Reverse transcriptase polymerase chain reaction (RT-PCR) was performed to determine the relative levels of a serotonin transporter protein (SERT) transcript and the serotonin 1A (5-HT1A) receptor transcript in developing embryos/larvae over 1-6 dpf. Both transcripts were present at 24 hpf with the relative concentration of SERT transcript showing no change over the developmental time range. The relative concentration of the 5-HT1A receptor transcript, however, showed a two-tiered pattern of concentration. RT-PCR was also used to detect potential changes in the SERT and 5-HT1A receptor transcripts in 6 dpf larvae after a 24 h exposure to 4.6 μM fluoxetine on 5 dpf. Three separate regions of the CNS were individually analyzed, two defined brain regions and spinal cord. The two brain regions showed no effect on transcript levels subsequent to fluoxetine exposure, however, the spinal cord showed a significant decrease in both transcripts. These results suggest a correlation between decreased concentration of SERT and 5-HT1A receptor transcripts in spinal cord and decreased SSA subsequent to fluoxetine exposure