Onset and resolution of ovarian toxicity with nirogacestat treatment in females with desmoid tumors: Updated safety analyses from the DeFi phase 3 study.

INTRODUCTION: Nirogacestat is a targeted gamma secretase inhibitor approved in the United States for adults with progressing desmoid tumors. In the phase 3 DeFi study (NCT03785964) of nirogacestat, ovarian toxicity (OT) was identified as a safety signal among females of reproductive potential (FORP). This analysis further describes the incidence, presentation, and resolution of OT. METHODS: Patients were randomized to twice-daily oral nirogacestat (150 mg) or placebo, taken in continuous 28-day cycles. Investigator-identified OT in FORP was based on abnormal reproductive hormone values or perimenopausal symptoms (or both). Adverse event follow-up was conducted to assess OT resolution. Post hoc analyses included return of menstruation and return of follicle-stimulating hormone (FSH) to within normal limits (WNL) (≤20.4 mIU/mL). RESULTS: Of 92 randomized females, 73 in the safety population were FORP (n = 36 nirogacestat, n = 37 placebo). OT was identified in 75% (27 of 36) receiving nirogacestat and 0% (0 of 37) receiving placebo. As of October 24, 2022, investigators reported OT resolution in 78% (21 of 27) of patients, with median OT duration of 19.1 weeks. Off-treatment resolution was reported in all 11 patients (100%) who stopped nirogacestat treatment; of these, all nine with available menstruation information experienced return of menstruation and eight had FSH WNL at last reported assessment. Resolution was reported in 10 of 14 (71%) while on nirogacestat; of these, all 10 experienced return of menstruation and seven had FSH WNL. Two patients were lost to follow-up. CONCLUSION: Most FORP treated with nirogacestat experienced OT, with the majority resolving, including all who stopped treatment, suggesting that OT is transient.

A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as "overexpression" and "shorter survival" is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify genes whose expression levels were associated with shorter survival. Next, genes associated with shorter survival were entered into pathway analysis to identify pathways that were altered in a shorter survival cohort. We identified pathways involving upregulation of GRB2. Overexpression of GRB2 was linked to shorter survival in the TCGA dataset, a finding validated by histological examination of biopsy samples taken from the patients for diagnostic purposes. Thus, GRB2 is a novel biomarker that predicts shorter survival of patients with aggressive prostate cancer (GS ≧8).

An enhanced approach for the use of satellite-derived leaf area index values in dry deposition modeling in the Athabasca oil sands region.

In the Athabasca oil sands region (AOSR) of Northern Alberta, the dry deposition of sulphur and nitrogen compounds represents a major fraction of total (wet plus dry) deposition due to oil sands emissions. The leaf area index (LAI) is a critical parameter that affects the dry deposition of these gaseous and particulate compounds to the surrounding boreal forest canopy. For this study, LAI values based on Moderate Resolution Imaging Spectroradiometer satellite imagery were obtained and compared to ground-based measurements, and two limitations with the satellite data were identified. The satellite LAI data firstly represents one-sided LAI values that do not account for the enhanced LAI associated with needle leaf geometry, and secondly, underestimates LAI in winter-time northern latitude regions. An approach for adjusting satellite LAI values for different boreal forest cover types, as a function of time of year, was developed to produce more representative LAI values that can be used by air quality sulphur and nitrogen deposition models. The application of the approach increases the AOSR average LAI for January from 0.19 to 1.40, which represents an increase of 637%. Based on the application of the CALMET/CALPUFF model system, this increases the predicted regional average dry deposition of sulphur and nitrogen compounds for January by factors of 1.40 to 1.30, respectively. The corresponding AOSR average LAI for July increased from 2.8 to 4.0, which represents an increase of 43%. This increases the predicted regional average dry deposition of sulphur and nitrogen compounds for July by factors of 1.28 to 1.22, respectively. These findings reinforce the importance of the LAI metric for predicting the dry deposition of sulphur and nitrogen compounds. While satellite data can provide enhanced spatial and temporal resolution, adjustments are identified to overcome associated limitations. This work is considered to have application for other deposition model studies where dry deposition represents a significant fraction of total deposition.