A genome-wide CRISPR/Cas9 screen in acute myeloid leukemia cells identifies regulators of TAK-243 sensitivity
Bibliographic record
Abstract
TAK-243 is a first-in-class inhibitor of ubiquitin-like modifier activating enzyme 1 that catalyzes ubiquitin activation, the first step in the ubiquitylation cascade. Based on its preclinical efficacy and tolerability, TAK-243 has been advanced to phase I clinical trials in advanced malignancies. Nonetheless, the determinants of TAK-243 sensitivity remain largely unknown. Here, we conducted a genome-wide CRISPR/Cas9 knockout screen in acute myeloid leukemia (AML) cells in the presence of TAK-243 to identify genes essential for TAK-243 action. We identified BEN domain-containing protein 3 (BEND3), a transcriptional repressor and a regulator of chromatin organization, as the top gene whose knockout confers resistance to TAK-243 in vitro and in vivo. Knockout of BEND3 dampened TAK-243 effects on ubiquitylation, proteotoxic stress, and DNA damage response. BEND3 knockout upregulated the ATP-binding cassette efflux transporter breast cancer resistance protein (BCRP; ABCG2) and reduced the intracellular levelsof TAK-243. TAK-243 sensitivity correlated with BCRP expression in cancer cell lines of different origins. Moreover, chemical inhibition and genetic knockdown of BCRP sensitized intrinsically resistant high-BCRP cells to TAK-243. Thus, our data demonstrate that BEND3 regulates the expression of BCRP for which TAK-243 is a substrate. Moreover, BCRP expression could serve as a predictor of TAK-243 sensitivity.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".