Abstract IA21: Exploiting metabolic alterations in therapy-induced senescence and drug resistance in a transgenic mouse lymphoma model by reverse and forward omics

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...

Source: Molecular Cancer Research - January 15, 2016 Category: Cancer & Oncology Authors: Schmitt, C. A. Tags: Autophagy and Metabolic Stress in Cancer: Oral Presentations - Invited Abstracts Source Type: research