Anti-GnRH Receptor Monoclonal Antibody, GHR106 is First-inClass GnRH Antagonist
Bibliographic record
Abstract
During the last decade, a monoclonal antibody, GHR106 was generated and characterized extensively biologically and immunologically. This antibody targets specific human pan cancer marker and is being evaluated for potential therapeutic applications in cancer immunotherapy and fertility regulations. GHR106 was generated against N1-29 oligopeptide located in the extracellular domains of human GnRH receptor found either in the anterior pituitary or in most of cancer cells. In vitro culture of cancer cells revealed that this antibody can induce apoptosis of cancer cells following 24-48 hours incubations. Anti-tumor activities of GHR106 were evaluated by typical nude mouse experiments in which the effective volume reduction of implanted tumor was observed. Humanized forms of GHR106 were made available in CAR (chimeric antigen receptor) T-cell constructs. GHR106 was shown separately to induce cytotoxic killings of cancer cells in vitro by releasing cytokines following incubations of tumor cells with CAR-T cell constructs. In addition, GHR106 also acts as GnRH antagonist by a specific targeting to pituitary GnRH receptor for reversible suppressions of reproductive hormones. These were demonstrated in “Proof of Concept” rabbit experiments. A single subcutaneous injection with 1-3mg/kg of GHR106 to rabbits of either sex could result in 60 to 90% reductions of gonadotropins, estrogen and/or testosterone over a period of one to two weeks. Based on these preclinical assessments, it can be concluded that GHR106 is restricted in tissue expressions and suitable for cancer immunotherapy. It can also act as long-acting GnRH antagonist to target specifically on GnRH receptor in anterior pituitary for numerous gynecological diseases including ovulation inhibition in IVF/ART, endometriosis-premenstrual syndrome, precocious puberty, uterine fibroids and/or polycystic ovarian syndrome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".