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Abstract 1051: Dianhydrogalactitol (VAL-083) reduces glioblastoma tumor growth upon bevacizumab-induced hypoxia,<i>in vivo</i>

2019· article· en· W2955315917 on OpenAlexaff
Anna Golebiewska, Anaïs Oudin, Anne Steinø, Simone P. Niclou, Jeffrey Bacha, Dennis Brown

Bibliographic record

VenueTumor Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsDelmar (Canada)
Fundersnot available
KeywordsBevacizumabGlioblastomaIn vivoHypoxia (environmental)Cancer researchChemistryMedicineInternal medicineBiologyChemotherapyOxygen

Abstract

fetched live from OpenAlex

Background: Standard-of-care for glioblastoma (GBM) includes surgery, radiation and temozolomide (TMZ). Nearly all tumors recur and 5-year survival is less than 3%. Unmethylated promoter status for O6-methylguanine-DNA-methyltransferase (MGMT) is a validated biomarker for TMZ-resistance. Second-line treatment with bevacizumab has not only failed to improve survival, but has also been shown to induce intratumor hypoxia, which is implicated in increased chemoresistance. VAL-083 is a bi-functional DNA-targeting agent that readily crosses the blood-brain barrier and accumulates in brain tumor tissue. VAL-083 induces DNA double-strand breaks at N7-guanine and cancer cell-death in GBM cancer stem cells (CSCs) and non-CSCs, independent of MGMT. We have previously shown that bevacizumab treatment upregulates expression of glucose transporters GLUT-1/GLUT-3 on GBM cells. We hypothesized that, based on its unique monosaccharide backbone structure, VAL-083 may benefit from bevacizumab-induced GLUT transporter upregulation leading to enhanced VAL-083 uptake and anti-tumor activity.Methods: To investigate the in vivo anti-tumor effect of VAL-083+bevacizumab, we used a orthotopic patient-derived xenograft GBM model. All mice carried MGMT-unmethylated, temozolomide-resistant recurrent T16 GBM tumors as detected by MRI 35 days post-implantation. Mice were grouped into control, bevacizumab, VAL-083, and VAL-083+bevacizmab. Tumor progression was measured by MRI on days 49 and 56, and tumor growth rate was calculated for the entire study (day 35 vs. 56) and for the last 7 days (day 49 vs. 56).Results: Tumors were significantly smaller in VAL-083-treated mice both compared to control (-83%, p<0.001) and compared to bevacizumab-treated (-75%, p<0.001) mice. Additionally, analysis of tumor growth in-time showed significantly reduced tumor growth rate for VAL-083+bevacizumab compared to VAL-083 alone (p<0.01).Conclusions: These results show strong in vivo anti-tumor efficacy of VAL-083 against MGMT-unmethylated, TMZ-resistant recurrent GBM. This effect was further augmented in combination with bevacizumab, providing rationale of clinical investigation of VAL-083 in combination with bevacizumab in the treatment of GBM.Citation Format: Anna Golebiewska, Anais Oudin, Anne Steino, Simone P. Niclou, Jeffrey Bacha, Dennis M. Brown. Dianhydrogalactitol (VAL-083) reduces glioblastoma tumor growth upon bevacizumab-induced hypoxia, in vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1051.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.240
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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