Bradykinin-related compounds as new drugs for cancer and inflammation
Bibliographic record
Abstract
Bradykinin (BK) (Arg-Pro-Pro-Gly-Phe-Ser-Pro-Phe-Arg) is an important growth factor for small-cell lung cancer (SCLC) and prostate cancer (PC). These cancers have cells of neuroendocrine origin and express receptors for a variety of neuropeptides. BK receptors are expressed on almost all lung cancer cell lines and on many PC cells. Our very potent BK antagonist B9430 (D-Arg-Arg-Pro-Hyp-Gly-lgl-Ser-D-Igl-Oic-Arg) (Hyp, trans-4-hydroxy-L-proline; Ig1, alpha-2-indanylglycine; Oic, octahydroindole-2-carboxylic acid) is a candidate anti-inflammatory drug but does not inhibit growth of SCLC or PC. When B9430 is dimerized by N-terminal cross-linking with a suberimide linker, the product B9870 is a potent growth inhibitor for SCLC both in vitro and in vivo in athymic nude mice. Daily i.p. injection at 5 mg x kg(-1) day(-1) beginning on day 8 after SCLC SHP-77 cell implantation gave 65% inhibition of tumor growth. B9870 stimulates apoptosis in SCLC by a novel "biased agonist" action. We have also developed new small mimetic antagonists. BKM-570 (F5C-OC2Y-Atmp) (F5C, pentafluorocinnamic acid; OC2Y, O-2,6-dichlorobenzyl tyrosine; Atmp, 4-amino-2,2,6,6-tetramethylpiperidine) is very potent for inhibition of SHP-77 growth in nude mice. When injected daily i.p. at 5 mg x kg(-1), M-570 gave 90% suppression of tumor growth. M-570 is more potent than the well-known anticancer drug cisPlatin (60% inhibition) or the recently developed SU5416 (40% inhibition) in this model. M-570 also showed activity against various other cancer cell lines in vitro (SCLC, non-SCLC, lung, prostate, colon, cervix) and inhibited growth of prostate cell line PC3 in nude mice. M-570 and related compounds evidently act in vivo through pathways other than BK receptors. These compounds have clinical potential for treatment of human lung and prostate cancers.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".