Canagliflozin synergises with serine restriction mediating anti-leukaemic effects in T-cell acute lymphoblastic leukaemia
Bibliographic record
Abstract
T-cell acute lymphoblastic leukaemia (T-ALL) is a haematological malignancy commonly driven by NOTCH1 activating mutations. A concomitant feature associated with NOTCH1 mutations is heightened oxidative metabolism enabling the exponential proliferation of T-ALL blasts. As such, targeting mitochondrial metabolism in T-ALL is an attractive therapeutic avenue. Related to this, canagliflozin (cana), is an FDA-approved sodium glucose co-transporter 2 inhibitor with known off-target effects on complex I and glutamate dehydrogenase, but its potential anti-leukaemic effects remain unexplored. Here, we show that cana possesses potent anti-leukaemic effects underpinned by proliferative defects, cell cycle disruption and apoptosis. These anti-leukaemic effects driven by cana, are attributed to a perturbed tricarboxylic acid (TCA) cycle and mitochondrial metabolism, and elevated mitochondrial ROS. Proteomic analysis revealed that cana treatment resulted in a compensatory increase in the expression of ATF4 targets, including upregulation of serine biosynthesis pathway and one-carbon metabolism enzymes. As such, restriction of serine and glycine synergized with cana treatment, further enhancing its anti-leukaemic effects. Collectively, our study reveals a cana-driven metabolic vulnerability that can be further exploited via dietary manipulation to treat T-ALL. • Canagliflozin impairs human T-ALL proliferation, and impacts viability, extending to a broad range of genetic subtypes. • Canagliflozin reprogrammes the proteomic landscape in T-ALL leading to compensatory increases in downstream ATF4 targets, including proteins associated with amino acid transport, serine, glycine and one carbon metabolism. • Restriction of serine/glycine synergistically complemented canagliflozin treatment by heightening T-ALL apoptosis, highlighting the possibility of a dietary intervention alongside canagliflozin treatment
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".