Tissue-Engineered Models of Glioblastoma for Evaluating Treatment Responses and it is a Research Scholar Grant, which are given to early-stage investigators (https://www.cancer.org/research/we-fund-cancer-research/apply-research-grant/grant-types/research-scholar-grants.html). It’s 3 years and $792,000 (including direct costs)
Thus, we are engineering artificial tumor tissues that incorporate key aspects of the brain ECM and a patient’s own tumor cells. The proposed approach, in which patient-derived tumor cells are cultured in brain-mimetic biomaterials, is less costly, more time efficient and better controlled than animal studies — yet, unlike other cell culture methods, yields results with comparable clinical relevance. Using a patient’s own cells to create patient-tailored test beds for treatment screening will allow these test beds to capture the unique characteristics of each patient’s disease. While the majority of approaches to personalized cancer treatment rely solely on a patient’s genetic characteristics, this proposal aims to integrate this genetic information with patient-specific functional assessments to better predict treatment response.
Ultimately, we anticipate these patient-specific tumor models will be able to directly inform clinical actions to improve patient outcomes. This proposal describes the next steps towards accomplishing this long-term goal. First, we propose to evaluate the ability of these tissue-engineered tumor models to predict responses to a variety of treatments across a heterogeneous patient population. Second, we aim to improve the ability of tissue-engineered tumors to capture the heterogeneous cell population that composes an individual GBM tumor. Together, we expect the proposed studies will improve robustness of tissue-engineered models of GBM tumors by characterizing their ability to faithfully capture heterogeneity both across patients and within individual patient tumors.