====== Glioblastoma Radioresistance ======

The mechanisms to endow GBM cells with [[radioresistance]] are complex and unclear.

[[Glioblastoma Radiotherapy]] is a common and effective therapeutic option for [[glioblastoma treatment]]. Unfortunately, some [[Glioblastoma]]s are relatively radioresistant and patients have worse outcomes after [[radiation]] [[treatment]]. The mechanisms underlying intrinsic [[radioresistance]] in Glioblastoma have been rigorously investigated, but the complex interaction of the cellular molecules and signaling pathways involved in radioresistance remains incompletely defined. A clinically effective radiosensitizer that overcomes radioresistance has yet to be identified
((Ali MY, Oliva CR, Noman ASM, Allen BG, Goswami PC, Zakharia Y, Monga V, Spitz DR, Buatti JM, Griguer CE. Radioresistance in Glioblastoma and the Development of Radiosensitizers. Cancers (Basel). 2020 Sep 3;12(9):2511. doi: 10.3390/cancers12092511. PMID: 32899427; PMCID: PMC7564557.))
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Data indicate that invasive tumor cells constitute a phenotypically distinct and highly radioresistant Glioblastoma subpopulation with a prognostic impact that may be vulnerable to [[targeted therapy]] and carbon ions
((Tang Z, Dokic I, Knoll M, Ciamarone F, Schwager C, Klein C, Cebulla G, Hoffmann DC, Schlegel J, Seidel P, Rutenberg C, Brons S, Herold-Mende C, Wick W, Debus J, Lemke D, Abdollahi A. Radioresistance and Transcriptional Reprograming of Invasive Glioblastoma Cells. Int J Radiat Oncol Biol Phys. 2022 Feb 1;112(2):499-513. doi: 10.1016/j.ijrobp.2021.09.017. Epub 2021 Sep 14. PMID: 34534627.)).
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Results demonstrate that enhanced fatty acid metabolism promotes aggressive growth of Glioblastoma with CD47-mediated immune evasion. The FAO-CD47 axis may be targeted to improve Glioblastoma control by eliminating the radioresistant phagocytosis-proofing tumor cells in Glioblastoma radioimmunotherapy
((Jiang N, Xie B, Xiao W, Fan M, Xu S, Duan Y, Hamsafar Y, Evans AC, Huang J, Zhou W, Lin X, Ye N, Wanggou S, Chen W, Jing D, Fragoso RC, Dugger BN, Wilson PF, Coleman MA, Xia S, Li X, Sun LQ, Monjazeb AM, Wang A, Murphy WJ, Kung HJ, Lam KS, Chen HW, Li JJ. Fatty acid oxidation fuels glioblastoma radioresistance with CD47-mediated immune evasion. Nat Commun. 2022 Mar 21;13(1):1511. doi: 10.1038/s41467-022-29137-3. PMID: 35314680; PMCID: PMC8938495.)).
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Key molecular [[regulator]]s of acquired [[radiation]] [[resistance]] in [[recurrent glioblastoma]] (Glioblastoma) is largely unknown with a dearth of accurate pre-clinical models. To address this, Stackhouse et al. generated 8 Glioblastoma patient-derived [[xenograft]] (PDX) models of acquired radiation therapy-selected (RTS) resistance compared with same-patient, treatment naïve (RTU) PDX. These unique models mimic the longitudinal evolution of patient recurrent [[tumor]]s following serial [[radiation therapy]]. Indeed, while [[whole exome sequencing]] confirmed retention of major genomic alterations in the RTS lines, they did detect a chromosome 12q14 amplification that is associated with clinical Glioblastoma recurrence in two RTS models. A novel bioinformatics [[pipeline]] was applied to analyze phenotypic, transcriptomic, and kinomic alterations, which identified long non-coding RNAs (lncRNAs) and targetable, PDX-specific kinases. We observed differential transcriptional enrichment of DNA damage repair (DDR) pathways in our RTS models which correlated with several lncRNAs. Global kinomic profiling separated RTU and RTS models, but pairwise analyses indicated that there are multiple molecular routes to acquired radiation resistance. RTS model-specific kinases were identified and targeted with clinically relevant small molecule inhibitors (SMIs). This unique cohort of in vivo radiation therapy-selected patient-derived models will enable future preclinical therapeutic testing to help overcome the treatment resistance seen in Glioblastoma patients
((Stackhouse CT, Anderson JC, Yue Z, Nguyen T, Eustace NJ, Langford CP, Wang J, Rowland Iv JR, Xing C, Mikhail FM, Cui X, Alrefai H, Bash RE, Lee KJ, Yang ES, Hjelmeland AB, Miller CR, Chen JY, Gillespie GY, Willey CD. An in vivo model of glioblastoma radiation resistance identifies long non-coding RNAs and targetable kinases. JCI Insight. 2022 Jul 19:e148717. doi: 10.1172/jci.insight.148717. Epub ahead of print. PMID: 35852875.)).