Abstract Treatment failure is the key determinant of poor outcome in lymphoma therapy. Unveiling the underlying molecular mechanisms is critical to overcome drug insensitivity, may identify novel targets and direct the development of conceptual treatment alternatives. We utilize transgenic mouse lymphoma models as valuable tools for the molecular dissection of treatment responsiveness. Notably, we previously demonstrated the predictive cross-species power of our murine lymphoma model for patients diagnosed with diffuse large B-cell lymphoma (DLBCL) (Reimann-M et al., Cancer Cell, 2010; Jing-H et al., Genes Dev., 2011). Here, we employ two different approaches: reverse genomics, allowing us to test the dependency of certain effector mechanisms such as apoptosis or senescence (Dörr-JR et al., Nature, 2013) on distinct genetics, and forward omics, a multitude of omics-based investigations, namely (epi-)genomics, transcriptomics, proteomics, and metabolomics to decipher mechanisms of patient-reminiscent treatment resistance in the well-established Eµ-myc-driven lymphoma mouse model. Technically, we transplanted primary Eµ-myc transgenic mouse B-cell lymphomas with or without defined genetic lesions into immunocompetent mice, and expose the recipients to cyclophosphamide (CTX) chemotherapy upon tumor manifestation. Whole-exome sequencing, copy number alteration analysis, array-based transcriptomics and kinomics, mass spectrometry-based proteomics and metabolomics as well as functional assays (e.g. apoptosis, cellular senescence) were applied, and the data subjected to bioinformatics processing to unveil molecular mechanisms of treatment resistance. After treatment of lymphoma-bearing mice, lasting remissions (reflecting cure) were observed in about half of the cohort (comparable to DLBCL patients after induction therapy). Repetitive treatments of relapsing mice resulted in progressively shortened remission times and finally full-blown resistance, thereby recapitulating clinical courses of patients with drug-insensitive aggressive lymphomas. Multipe omics technologies were applied to the large sample panel to compare curable vs. relapse-prone and resistant lymphomas, all with or without an additional short-term exposure to CTX to acutely challenge drug-specific response programs. Candidate findings will be discussed at the conference. In the reverse genomics approaches, findings related to distinct mutations in key lymphoma drivers, their metabolic implications for treatment outcome, and their specific role in therapy-induced senescence and senescence-related vulnerabilities will be presented at the meeting. Dörr, J.R., Y. Yu, M. Milanovic, G. Beuster, C. Zasada, S. Lee, and C.A. Schmitt. 2013. Synthetic lethal metabolic targeting of cellular senescence in cancer therapy. Nature 501: 421-425. Jing, H., J. Kase, J.R. Dörr, M. Milanovic, D. Lenze, C.A. Schmitt, and S. Lee. 2011. Opposing roles of NF-κB in anti-cancer treatment outcome unveiled by cross-species investigations. Genes Dev. 25: 2137-2146. Reimann, M., S. Lee, C. Loddenkemper, J.R. Dörr, V. Tabor, T. Jenuwein, and C.A. Schmitt. 2010. Tumor stroma-derived TGF-β limits Myc-driven lymphomagenesis via Suv39h1-dependent senescence. Cancer Cell 17: 262-272. Citation Format: Clemens A. Schmitt. Exploiting metabolic alterations in therapy-induced senescence and drug resistance in a transgenic mouse lymphoma model by reverse and forward omics. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr IA21.
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