Abstract 2483: Molecular mechanisms of dianhydrogalactitol (VAL-083) in overcoming chemoresistance in glioblastoma
Bibliographic record
Abstract
Abstract Standard treatments for glioblastoma (GBM) include surgery, radiation and chemotherapy with temozolomide (TMZ). Nearly all tumors recur and 5-year survival is less than 3%, largely due to chemoresistance. Evidence shows that cancer cells utilize DNA damage repair pathways to overcome cytotoxic effects of chemotherapy. GBM tumors expressing O6-methylguanine-DNA-methyltransferase (MGMT) display intrinsic chemoresistance to TMZ and nitrosoureas, while a deficient DNA mismatch repair system (MMR) confers chemoresistance to TMZ and platinum agents. Alterations in p53, particularly gain-of-function mutations, are correlated with increased MGMT-expression and poor prognoses in GBM. Second line anti-angiogenic treatment with bevacizumab has not improved overall survival and has been shown to induce intratumor hypoxia and increased chemoresistance. VAL-083 is a bi-functional alkylating agent that readily crosses the blood-brain barrier, accumulates in brain tumor tissue and has demonstrated activity against GBM in prior NCI-sponsored clinical trials. VAL-083 induces interstrand cross-links at guanine-N7 causing DNA double-strand breaks and cancer cell death. VAL-083 is equiactive against GBM cancer stem cells (CSCs) and non-CSCs independent of MGMT and p53 status, in vitro. We recently showed that VAL-083 leads to irreversible S/G2-phase cell cycle arrest, proposing synergy with S-phase specific chemotherapeutics, including topoisomerase and PARP inhibitors. VAL-083 further showed persistent activation of the homologous recombination (HR) DNA repair pathway and its potency was increased when HR was impaired, demonstrating that VAL-083-induced lesions are repaired via HR suggesting increased VAL-083 potency in HR-impaired tumors. Further, hypoxic cancer cells are known to downregulate their HR pathway, proposing increased VAL-083 potency in hypoxic tumors. Bevacizumab treatment increases hypoxia in tumor cells, presumably impairing HR, proposing VAL-083 as a treatment option in HR-deficient or hypoxic cancers following, or as part of a combination treatment with, bevacizumab. Here, VAL-083 cytotoxicity and DNA damage response was evaluated by crystal violet assays, western blot and flow cytometry. VAL-083’s ability to overcome MMR-related chemoresistance was investigated using lentiviral MLH1 and MSH2 vectors in HCT116 and LoVo cancer cells. We report synergy between VAL-083 and etoposide or camptothecin in A549 and PC3 cancer cell lines. We also investigated the potency of VAL-083 in GBM under hypoxia either in vitro or in vivo as part of a combination treatment with bevacizumab. Our results demonstrate a distinct anti-cancer mechanism for VAL-083, resulting in the ability to overcome resistance to TMZ and nitrosoureas, increased activity in cancers with impaired HR and synergy with etoposide or camptothecin. Citation Format: Beibei Zhai, Anna Gobielewska, Anne Steino, Jeffrey A. Bacha, Dennis M. Brown, Simone Niclou, Mads Daugaard. Molecular mechanisms of dianhydrogalactitol (VAL-083) in overcoming chemoresistance in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2483. doi:10.1158/1538-7445.AM2017-2483
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".