The diabetes medication Canagliflozin reduces cancer cell proliferation by inhibiting mitochondrial complex-I supported respiration
Bibliographic record
Abstract
OBJECTIVE: The sodium-glucose transporter 2 (SGLT2) inhibitors Canagliflozin and Dapagliflozin are recently approved medications for type 2 diabetes. Recent studies indicate that SGLT2 inhibitors may inhibit the growth of some cancer cells but the mechanism(s) remain unclear. METHODS: Cellular proliferation and clonogenic survival were used to assess the sensitivity of prostate and lung cancer cell growth to the SGLT2 inhibitors. Oxygen consumption, extracellular acidification rate, cellular ATP, glucose uptake, lipogenesis, and phosphorylation of AMP-activated protein kinase (AMPK), acetyl-CoA carboxylase, and the p70S6 kinase were assessed. Overexpression of a protein that maintains complex-I supported mitochondrial respiration (NDI1) was used to establish the importance of this pathway for mediating the anti-proliferative effects of Canagliflozin. RESULTS: Clinically achievable concentrations of Canagliflozin, but not Dapagliflozin, inhibit cellular proliferation and clonogenic survival of prostate and lung cancer cells alone and in combination with ionizing radiation and the chemotherapy Docetaxel. Canagliflozin reduced glucose uptake, mitochondrial complex-I supported respiration, ATP, and lipogenesis while increasing the activating phosphorylation of AMPK. The overexpression of NDI1 blocked the anti-proliferative effects of Canagliflozin indicating reductions in mitochondrial respiration are critical for anti-proliferative actions. CONCLUSION: These data indicate that like the biguanide metformin, Canagliflozin not only lowers blood glucose but also inhibits complex-I supported respiration and cellular proliferation in prostate and lung cancer cells. These observations support the initiation of studies evaluating the clinical efficacy of Canagliflozin on limiting tumorigenesis in pre-clinical animal models as well epidemiological studies on cancer incidence relative to other glucose lowering therapies in clinical populations.
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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) | 0.001 | 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".