2026-09-22T09:58:20Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/115508 2023-07-11 col_2142_5131 col_2142_5163 com_2142_5130 com_2142_5162 com_2142_234

Imoukhuede, Princess I Amos, Jennifer Jensen, Paul Dobrucki, Wawrzyniec Chen, Jie 2022-05 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01 The student, Colin Castleberry, accepted the attached license on 2022-03-16 at 14:11. The student, Colin Castleberry, submitted this Dissertation for approval on 2022-03-16 at 14:12. This Dissertation was approved for publication on 2022-03-24 at 15:12. DSpace SAF Submission Ingestion Package generated from Vireo submission #17505 on 2022-11-11 at 11:55:45 Characterizing the anti-angiogenic resistance potential of cross-family PDGF:VEGFR2 interactions in glioblastoma Castleberry, Colin 2022-03-24 RTK VEGF PDGF cross-family signaling cell signaling cancer angiogenesis computational modeling mass action kinetics global sensitivity analysis structural alignment meta-analysis glioblastoma growth factors Glioblastoma is the most common and lethal primary brain tumor in adults. Anti-angiogenic treatment has shown positive results in improving GBM patient survival. Bevacizumab, a drug that sequesters the angiogenic growth factor, VEGF-A, has been approved by the FDA for use in GBM patients and moderately improves patient survival; however, these GBM bevacizumab responders eventually acquire bevacizumab resistance. New approaches must be pursued to understand anti-VEGF resistance in GBM. The involvement of other signaling axes potentially explains anti-VEGF failings. PDGF:VEGFR2 interactions were recently discovered and prior computational modeling predicts that PDGF:VEGFR2 interactions could constitute a large proportion of VEGFR2-ligand complexes in certain physiological and breast cancer conditions. Under PDGF:VEGFR2 cross-family signaling, upregulated PDGFs would directly activate VEGFRs and lead to anti-VEGF therapy resistance. We aimed to use computational tools to assess how strongly PDGFs can affect VEGFR occupancy in GBM, and to assess the potential of PDGF:VEGFR2 interactions as resistance mechanisms for anti-VEGF treatment in GBM. However, the GBM ligand and receptor parameter space has not been established such that a GBM condition can be computationally modelled, and an analysis platform has not yet been developed to assess the ability of cross-family PDGF ligands to control VEGFR-occupancy in relation to canonical VEGF-family ligands in pathology. These challenges have been addressed in two ways: (1) I created and analyze a toolbox of computational models to compare PDGF:VEGFR2 interactions with canonical VEGF:VEGFR interactions across several mechanistic differences and assumptions in angiogenic signaling, and (2) I performed an in-depth meta-analysis of GBM growth factors, including: VEGF-A, Ang-2, PDGF-BB, FGF-2, EGF, PlGF, and IGF in order to better characterize the GBM growth factor landscape, and to consolidate concentration data for the ligands aiding tumor growth and angiogenesis. Thesis eng https://hdl.handle.net/2142/115508 Copyright by Colin Castleberry 2022. All Rights Reserved. Ph.D. Dissertation Bioengineering University of Illinois at Urbana-Champaign Bioengineering