Current methods of preclinical testing of potential therapeutics have been, for the most part, underwhelming in terms of their ability to yield a clinical impact. This is particularly true for glioblastoma (GBM) where prognosis has increased only by 2-3 months over the last 75 years with a 5-year survival of less than 4%. Many promising preclinical studies have failed to live up to expectations when tested clinically. This problem is likely due to: a) limitations of the preclinical model system and b) lack of reliable biomarkers for proper patient selection. To address these issues, investigators are increasingly utilizing patient-derived models of cancer (PDMC) coupled with comprehensive molecular profiling. However, differences in model composition, growth conditions, and other microenvironmental factors limit reliability of these models and hamper interpretation. We believe that a careful investigation of tumor microenvironmental (TME) stressors on 3 patientderived models (xenolines) of GBM, namely xenografts (PDX), spheroid cultures (neurospheres), and human biomatrix embedded 3D microtumors, will provide insight into critical aspects of tumor biology that are influenced by model and TME. These models pre and post TME perturbagen will also be comprehensively profiled at the genomic, transcriptomic, and kinomic (global kinase activity assessment through a peptide substrate microarray) level to generate a similarity distance metric. We hypothesize that application of TME stressors to the PDMC?s will improve both molecular and biological fidelity of the respective models to that of the original tumor or parent xenoline that can be visualized and in silico tested using an advanced computational data modeling system (GeneTerrain). Our preliminary data generated from prior NIH funded projects indicate that our existing xenolines recapitulate all four molecular subtypes of GBM identified in The Cancer Genome Atlas while reproducing the key hallmarks of GBM when implanted orthotopically in immunocompromised mice. Importantly, we can grow disaggregated xenoline tumors in a novel three-dimensional (3D) culture system incorporating many cells of the tumor microenvironment to produce 3D microtumors suitable for higher throughput drug testing. Moreover, we have preliminary evidence that TME manipulation of BTICs or 3D microtumors (e.g., hypoxia or nutrient deprivation) promotes a more aggressive tumor phenotype in vitro and in vivo that is accompanied by changes in kinomic signatures. Therefore, we will: 1) Generate 3 PDMC models from existing xenolines as well as de novo GBM patient tumors with comprehensive omic testing to calculate similarity distance metrics among the models with corresponding biological assessments including growth, chemoradiation sensitivity, and stemness markers;? 2) Perform TME perturbagen testing of the derivative PDMCs (neurospheres and 3D microtumors) and determine impact on tumor biology and similarity distance metric;? 3) Develop and validate GeneTerrain models of the various PDMCs with respect to TME and therapeutic sensitivity (radiation and temozolomide).

Public Health Relevance

Patient-derived models of cancer (PDMC) are considered the gold-standard model of human cancer, yet a knowledge gap exists regarding how a patient?s tumor explant is altered by environmental and growth conditions of various PDMC approaches. We will biologically and molecularly compare three derivative PDMC models of glioma under different microenvironmental stresses with accompanying computational modeling.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZCA1)
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Salnikow, Konstantin
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University of Alabama Birmingham
Schools of Medicine
United States
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