Anti - GNRH Receptor Monoclonal Antibodies are Long Acting Analogs of GNRH
Bibliographic record
Abstract
Monoclonal antibodies were generated against a synthetic peptide corresponding to N1-29 sequence located in the extracellular domain of human GnRH (gonadotropin-releasing hormone) receptor.Among the fourteen established monoclonal antibodies GHR103 and GHR106 were shown to have the highest affinity (Kd≈2 x10 -9 M) to the synthetic peptide as well as to the native GnRH receptor in cancer cell extract.Through immunoglobulin gene analysis, both GHR103 and GHR106 were shown to have identical DNA sequences in both heavy and light chains of IgG1 subclass.GHR106 was shown to be highly specific to N1-29 peptides derived from GnRH receptor of human and monkey, but not to that from mouse.Immunohistochemical studies were performed with as many as 30 different cancer cell lines and were found to positively stain more than 80% of cases, irrespective of their tissue origins.Consistent results were obtained with other assays such as Western Blot, indirect immunofluorescence and RT-PCR.Similar to GnRH decapeptide antagonist, Antide, GHR106 was shown to induce apoptosis and inhibit cell proliferation to culturing cancer cells by TUNEL and MTT assays, respectively.Furthermore, GHR106 was shown to induce lysis of cancer cells in culture through complement-dependent cytotoxicity reactions (CDC) which are absent with GnRH peptide analogs.Humanized forms of GHR106 (hGHR106) were generated and found to be bioequivalent to murine GHR106 (mGHR106) as well as to GnRH antagonist, Antide in terms of their respective binding affinity and biological properties.Widespread expressions of GnRH receptor among various human cancer, hGHR106 can be bioequivalent alternative to GnRH decapeptide analogs and can serve as the antibody-based anti-cancer drugs of much longer half-life as compared to that of GnRH decapeptide analogs (days vs. hrs.).Furthermore, humanized GHR106 can be long-acting substitute to GnRH decapeptide analog for numerous gynecological indications in fertility regulations and women health.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".