TRSC-04 DE NOVO GTP SYNTHESIS IS A METABOLIC VULNERABILITY FOR THE INTERCEPTION OF BRAIN METASTASES
Bibliographic record
Abstract
Abstract Patients with brain metastases (BM) face a 90% mortality rate within one year of diagnosis and the current standard of care is mainly palliative. Targeting BM-initiating cells (BMIC) is a feasible strategy to treat BM, but druggable targets are still very limited. Here, we applied Connectivity Map analysis to lung-, breast-, and melanoma- pre-metastatic BMIC gene expression signatures and identified inosine monophosphate dehydrogenase (IMPDH), the rate-limiting enzyme in the de novo GTP synthesis pathway, as a target for BM. We showed that pharmacological and genetic perturbation of IMPDH attenuates BMIC proliferation in vitro and the formation of BM in vivo. Furthermore, we used medicinal chemistry to develop novel brain penetrant IMPDH-inhibitors with enhanced in vivo efficacy. Metabolomic analyses and CRISPR knockout studies confirmed that de novo GTP synthesis is a potent metabolic vulnerability in BM. Overall, our work employed a phenotype-guided therapeutic strategy to uncover IMPDH as a relevant target for attenuating BM outgrowth, which may provide an alternative treatment strategy for patients who are otherwise limited to palliation.
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 | 0.002 |
| 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) | 0.000 | 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".