Browsing by Author "Svalina, Matthew N."
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Item Preclinical rationale for entinostat in embryonal rhabdomyosarcoma(2019) Bharathy, Narendra; Berlow, Noah E.; Wang, Eric; Abraham, Jinu; Settelmeyer, Teagan P.; Hooper, Jody E.; Svalina, Matthew N.; Bajwa, Zia; Goros, Martin W.; Hernandez, Brian S.; Wolff, Johannes E.; Pal, Ranadip (TTU); Davies, Angela M.; Ashok, Arya; Bushby, Darnell; Mancini, Maria; Noakes, Christopher; Goodwin, Neal C.; Ordentlich, Peter; Keck, James; Hawkins, Douglas S.; Rudzinski, Erin R.; Mansoor, Atiya; Perkins, Theodore J.; Vakoc, Christopher R.; Michalek, Joel E.; Keller, CharlesBackground: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in the pediatric cancer population. Survival among metastatic RMS patients has remained dismal yet unimproved for years. We previously identified the class I-specific histone deacetylase inhibitor, entinostat (ENT), as a pharmacological agent that transcriptionally suppresses the PAX3:FOXO1 tumor-initiating fusion gene found in alveolar rhabdomyosarcoma (aRMS), and we further investigated the mechanism by which ENT suppresses PAX3:FOXO1 oncogene and demonstrated the preclinical efficacy of ENT in RMS orthotopic allograft and patient-derived xenograft (PDX) models. In this study, we investigated whether ENT also has antitumor activity in fusion-negative eRMS orthotopic allografts and PDX models either as a single agent or in combination with vincristine (VCR). Methods: We tested the efficacy of ENT and VCR as single agents and in combination in orthotopic allograft and PDX mouse models of eRMS. We then performed CRISPR screening to identify which HDAC among the class I HDACs is responsible for tumor growth inhibition in eRMS. To analyze whether ENT treatment as a single agent or in combination with VCR induces myogenic differentiation, we performed hematoxylin and eosin (H&E) staining in tumors. Results: ENT in combination with the chemotherapy VCR has synergistic antitumor activity in a subset of fusion-negative eRMS in orthotopic "allografts," although PDX mouse models were too hypersensitive to the VCR dose used to detect synergy. Mechanistic studies involving CRISPR suggest that HDAC3 inhibition is the primary mechanism of cell-autonomous cytoreduction in eRMS. Following cytoreduction in vivo, residual tumor cells in the allograft models treated with chemotherapy undergo a dramatic, entinostat-induced (70-100%) conversion to non-proliferative rhabdomyoblasts. Conclusion: Our results suggest that the targeting class I HDACs may provide a therapeutic benefit for selected patients with eRMS. ENT's preclinical in vivo efficacy makes ENT a rational drug candidate in a phase II clinical trial for eRMS.Item Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma(2019) Berlow, Noah E. (TTU); Rikhi, Rishi; Geltzeiler, Mathew; Abraham, Jinu; Svalina, Matthew N.; Davis, Lara E.; Wise, Erin; Mancini, Maria; Noujaim, Jonathan; Mansoor, Atiya; Quist, Michael J.; Matlock, Kevin L. (TTU); Goros, Martin W.; Hernandez, Brian S.; Doung, Yee C.; Thway, Khin; Tsukahara, Tomohide; Nishio, Jun; Huang, Elaine T.; Airhart, Susan; Bult, Carol J.; Gandour-Edwards, Regina; Maki, Robert G.; Jones, Robin L.; Michalek, Joel E.; Milovancev, Milan; Ghosh, Souparno (TTU); Pal, Ranadip (TTU); Keller, CharlesBackground: 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.