Next‐generation bromodomain inhibitors of the <scp>SWI</scp>/<scp>SNF</scp> complex enhance <scp>DNA</scp> damage and cell death in glioblastoma
Bibliographic record
Abstract
Glioblastoma (GBM) is an aggressive brain cancer with a poor prognosis. While surgical resection is the primary treatment, adjuvant temozolomide (TMZ) chemotherapy and radiotherapy only provide slight improvement in disease course and outcome. Unfortunately, most treated patients experience recurrence of highly aggressive, therapy-resistant tumours and eventually succumb to the disease. To increase chemosensitivity and overcome therapy resistance, we have modified the chemical structure of the PFI-3 bromodomain inhibitor of the BRG1 and BRM catalytic subunits of the SWI/SNF chromatin remodelling complex. Our modifications resulted in compounds that sensitized GBM to the DNA alkylating agent TMZ and the radiomimetic bleomycin. We screened these chemical analogues using a cell death ELISA with GBM cell lines and a cellular thermal shift assay using epitope tagged BRG1 or BRM bromodomains expressed in GBM cells. An active analogue, IV-129, was then identified and further modified, resulting in new generation of bromodomain inhibitors with distinct properties. IV-255 and IV-275 had higher bioactivity than IV-129, with IV-255 selectively binding to the bromodomain of BRG1 and not BRM, while IV-275 bound well to both BRG1 and BRM bromodomains. In contrast, IV-191 did not bind to either bromodomain or alter GBM chemosensitivity. Importantly, both IV-255 and IV-275 markedly increased the extent of DNA damage induced by TMZ and bleomycin as determined by nuclear γH2AX staining. Our results demonstrate that these next-generation inhibitors selectively bind to the bromodomains of catalytic subunits of the SWI/SNF complex and sensitize GBM to the anticancer effects of TMZ and bleomycin. This approach holds promise for improving the treatment of GBM.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".