Intracellular Hyper-Acidification Potentiated by Hydrogen Sulfide Mediates Invasive and Therapy Resistant Cancer Cell Death
Bibliographic record
Abstract
Slow and continuous release of H2S by GYY4137 has previously been demonstrated to kill cancer cells by increasing glycolysis and impairing anion exchanger and sodium/proton exchanger activity. This action is specific for cancer cells. The resulting lactate overproduction and defective pH homeostasis brings about intracellular acidification-induced cancer cell death. The present study investigated the potency of H2S released by GYY4137 against invasive and radio- as well as chemo-resistant cancers, known to be glycolytically active. We characterized and utilized cancer cell line pairs of various organ origins, based on their aggressive behaviors, and assessed their response to GYY4137. We compared glycolytic activity, via lactate production, and intracellular pH of each cancer cell line pair after exposure to H2S. Invasive and therapy resistant cancers, collectively termed aggressive cancers, are receptive to H2S-mediated cytotoxicity, albeit at a higher concentration of GYY4137 donor. While lactate production was enhanced, intracellular pH of aggressive cancers was only modestly decreased. Inherently, the magnitude of intracellular pH decrease is a key determinant for cancer cell sensitivity to H2S. We demonstrated the utility of coupling GYY4137 with either simvastatin, known to inhibit monocarboxylate transporter 4 (MCT4), or metformin, to further boost glycolysis, in bringing about cell death for aggressive cancers. Simvastatin inhibits lactate extrusion and thence contains excess lactate induced by GYY4137 within intracellular compartment. In contrast, the combined exposure to both GYY4137 and metformin overwhelms cancer cells with lactate over-production exceeding its expulsion rate. Together, GYY4137 and simvastatin or metformin synergize to induce intracellular hyper-acidification-mediated cancer cell death.
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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".