Progesterone-3 [HRP]

We evaluated if an additional GnRH injection 7 days before pre-synchronization with simultaneous PGF(2 alpha) and GnRH (PG+G) would improve responses to presynchronization, synchronization, and pregnancy per AI (P/AI). We hypothesized that administering GnRH 7 days before PG+G would increase ovulation and corpus luteum (CL) presence at the PG+G, improve response to OvSynch treatments and P/AI. Holstein cows were blocked by parity and randomly assigned to either a PG+G (Control, n = 205); or to GnRH followed 7 days later by PG+G (ExtG, n = 201). At enrollment, Control was left untreated, whereas ExtG received GnRH. Seven days after enrollment, Control and ExtG received PG+G followed by OvSynch 7 days later (GnRH, 7 days PGF(2 alpha), 56 h GnRH, 16 h timed AI). Ovarian dynamics were assessed using ultrasonography in a subset of cows (n = 53 for Control; and n = 50 for ExtG) at each treatment, except the 2(nd) GnRH of OvSynch. Pregnancy diagnosed at 32- and 67-days post AI. Ovulation at enrollment tended (P = 0.06) to be higher for ExtG, but ovulation was not different at PG+G (P = 0.41) and first GnRH of the OvSynch (P = 0.25). There was a tendency (P = 0.08) for ExtG to have larger CL than Control at PGF(2 alpha) of the OvSynch. There were no differences in CL and follicle sizes in any other treatment point assessed. There were no differences (P = 0.12) in luteolysis between treatments after PG+G. Overall P/AI was similar between treatments on Day 32 (Control = 33.0% vs. ExtG = 34.6%, P = 0.75) and 67 (Control = 31.8% vs. ExtG = 32.5%, P = 0.29) post AI. There was a tendency for an interaction between treatment and parity (P = 0.09) for P/AI at day 67 post-AI. In multiparous cows, ExtG tended to have greater P/AI than Control, whereas, in primiparous cows Control tended to have greater P/AI than ExtG at day 67 post-AI. In conclusion, the effects of GnRH 7 days before PG+G presynchronization lead to positive and negative tendencies, respectively, in multiparous and primiparous cows for P/AI at day 67 post-AI and needs further investigation.

Objectives This review examines how response rates to progestin treatment of low-grade endometrial cancer can be improved. In addition to providing a brief overview of the pathogenesis of low-grade endometrial cancer, we discuss limitations in the current classification of endometrial cancer and how stratification may be refined using molecular markers to reproducibly identify 'low-risk' cancers which may represent the best candidates for progestin therapy. We also discuss constraints in current approaches to progestin treatment of low-grade endometrial cancer and perform a systematic review of predictive biomarkers. Methods PubMed, ClinicalTrials.gov, and Cochrane Library were searched for studies reporting pre-treatment biomarkers associated with outcome in women with low-grade endometrial cancer or endometrial hyperplasia with an intact uterus who received progestin treatment. Studies of fewer than 50 women were excluded. The study protocol was registered in PROSPERO (ID 152374). A descriptive synthesis of pre-treatment predictive biomarkers reported in the included studies was conducted. Results Of 1908 records reviewed, 19 studies were included. Clinical features such as age or body mass index cannot predict progestin response. Lesions defined as 'low-risk' by FIGO criteria (stage 1A, grade 1) can respond well; however, the reproducibility and prognostic ability of the current histopathological classification system is suboptimal. Molecular markers can be reproducibly assessed, have been validated as prognostic biomarkers, and may inform patient selection for progestin treatment. DNA polymerase epsilon (POLE)-ultramutated tumors and a subset of p53 wild-type or DNA mismatch repair (MMR)-deficient tumors with 'low-risk' features (eg, progesterone and estrogen receptor-positive) may have improved response rates, though this needs to be validated. Discussion Molecular markers can identify cases which may be candidates for progestin treatment. More work is needed to validate these biomarkers and potentially identify new ones. Predictive biomarkers are anticipated to inform future research into progestin treatment of low-grade endometrial cancer and ultimately improve patient outcomes.