Hydrogen sulfide-releasing naproxen suppresses colon cancer cell growth and inhibits NF-κB signaling
Bibliographic record
Abstract
Ravinder Kodela,1 Niharika Nath,2 Mitali Chattopadhyay,1 Diandra E Nesbitt,1 Carlos A Velázquez-Martínez,3 Khosrow Kashfi11Department of Physiology, Pharmacology and Neuroscience, Sophie Davis School of Biomedical Education, City University of New York Medical School, 2Department of Life Sciences, New York Institute of Technology, New York, NY, USA; 3Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada Abstract: Colorectal cancer (CRC) is the second leading cause of death due to cancer and the third most common cancer in men and women in the USA. Nuclear factor kappa B (NF-κB) is known to be activated in CRC and is strongly implicated in its development and progression. Therefore, activated NF-κB constitutes a bona fide target for drug development in this type of malignancy. Many epidemiological and interventional studies have established nonsteroidal anti-inflammatory drugs (NSAIDs) as a viable chemopreventive strategy against CRC. Our previous studies have shown that several novel hydrogen sulfide-releasing NSAIDs are promising anticancer agents and are safer derivatives of NSAIDs. In this study, we examined the growth inhibitory effect of a novel H2S-releasing naproxen (HS-NAP), which has a repertoire as a cardiovascular-safe NSAID, for its effects on cell proliferation, cell cycle phase transitions, and apoptosis using HT-29 human colon cancer cells. We also investigated its effect as a chemopreventive agent in a xenograft mouse model. HS-NAP suppressed the growth of HT-29 cells by induction of G0/G1 arrest and apoptosis and downregulated NF-κB. Tumor xenografts in mice were significantly reduced in volume. The decrease in tumor mass was associated with a reduction of cell proliferation, induction of apoptosis, and decreases in NF-κB levels in vivo. Therefore, HS-NAP demonstrates strong anticancer potential in CRC. Keywords: nonsteroidal anti-inflammatory drugs, cell cycle, apoptosis, xenograft, NF-κB, thioredoxin reductase, chemoprevention
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".