Gene cascade analysis in human granulosa tumor cells (KGN) following exposure to high levels of free fatty acids and insulin.

Maternal metabolic disorders such as obesity and diabetes are detrimental factors that compromise fertility and the success rates of medically assisted procreation procedures. During metabolic stress, adipose tissue is more likely to release free fatty acids (FFA) in the serum resulting in an increase of FFA levels not only in blood, but also in follicular fluid (FF). In humans, high concentrations of palmitic acid and stearic acid reduced granulosa cell survival and were associated with poor cumulus-oocyte complex (COC) morphology. Obesity and high levels of circulating FFA were also causatively linked to hampered insulin sensitivity in cells and compensatory hyperinsulinemia. To provide a global picture of the principal upstream signaling pathways and genomic mechanisms involved in this metabolic context, human granulosa-like tumor cells (KGN) were treated with a combination of palmitic acid, oleic acid, and stearic acid at the higher physiological concentrations found in the follicular fluid of women with a higher body mass index (BMI) (≥ 30.0 kg/m2). We also tested a high concentration of insulin alone and in combination with high concentrations of fatty acids. Transcription analysis by RNA-seq with a cut off for fold change of 1.5 and p-value 0.05 resulted in thousands of differentially expressed genes for each treatment. Using analysis software such as Ingenuity Pathway Analysis (IPA), we were able to establish that high concentrations of FFA affected the expression of genes mainly related to glucose and insulin homoeostasis, fatty acid metabolism, as well as steroidogenesis and granulosa cell differentiation processes. The combination of insulin and high concentrations of FFA affected signaling pathways related to apoptosis, inflammation, and oxidative stress. Taken together, our results provided new information on the mechanisms that might be involved in human granulosa cells exposed to high concentrations of FFA and insulin in the contexts of metabolism disorders.

Patients who failed to conceive following an in vitro fertilization cycle can be clustered into different failure causes using gene expression hierarchical analysis†.

The patient's response to an IVF stimulation protocol is highly variable and thus difficult to predict. When a cycle fails, there are often no apparent or obvious reasons to explain the failure. Having clues on what went wrong during stimulation could serve as a basis to improve and personalize the next protocol. This exploratory study aimed to investigate if it is possible to distinguish different failure causes or different follicular responses in a population of nonpregnant IVF patients. Using qRT-PCR, we analyzed a panel of genes indicative of different failure causes in patients who did not achieve pregnancy following an IVF cycle. For each patient, a pool of follicular cells from all aspirated follicles was used as a sample which gives a global picture of the patient's ovary and not a specific picture of each follicle. We performed hierarchical clustering analysis to split the patients according to the gene expression pattern. Hierarchical analysis showed that the population of nonpregnant IVF patients could be divided into three clusters. Gene expression was significantly different, and each cluster displayed a particular gene expression pattern. Follicular cells from patients in clusters 1, 2 and 3 displayed respectively a pattern of gene expression related to large incompetent follicles with a higher apoptosis (over matured), to follicles not ready to ovulate (under mature) and to an excess of inflammation with no visible symptoms. This study reinforces the idea that women often have different response to the same protocol and would benefit from more personalized treatments.

Gene expression analysis of follicular cells revealed inflammation as a potential IVF failure cause.

PURPOSE: Hormonal stimulation prior to IVF influences the ovarian environment and therefore impacts oocytes and subsequent embryo quality. Not every patient has the same response to the same treatment and many fail for unknown reasons. Knowing why a cycle has failed and how the follicles were affected would allow clinicians to adapt the treatment accordingly and improve success rate. This study examines the hypothesis that transcriptomic analysis of follicular cells from failed IVF cycles reveals potential reasons for failure and provides new information on the physiological mechanisms related to IVF failure. METHODS: Follicular cells (granulosa cells) were obtained from IVF patients of four Canadian fertility clinics. Using microarray analysis, patients that did not become pregnant following the IVF cycle were compared to those that did. Functional analysis was performed using ingenuity pathway analysis and qRT-PCR was used to validate the microarray results in a larger cohort of patients. RESULTS: The microarray showed 165 differentially expressed genes (DEGs) in the negative group compared to the pregnancy group. DEGs include many pro-inflammatory cytokines and other factors related to inflammation, suggesting that this process might be altered when IVF fails. Overexpression of several factors, some of which act upstream from vascular endothelial growth factor (VEGF), also indicates increased permeability and vasodilation. Some DEGs were related to abnormal differentiation and increased apoptosis. CONCLUSIONS: Our results suggest that failure to conceive following IVF cycles could be associated with an imbalance between pro-inflammatory and anti-inflammatory mediators. The findings of this study identify potential failure causes and pathways for further investigation. Stimulatory protocols personalized according to patient response could improve the chances of later success.

Comparative analysis of granulosa cell gene expression in association with oocyte competence in FSH-stimulated Holstein cows.

Ovarian stimulation with exogenous FSH followed by FSH withdrawal or 'coasting' is an effective means of increasing the number of oocytes obtainable for the in vitro production of cattle embryos. However, the quality of the oocytes thus obtained varies considerably from one cow to the next. The aim of the present study was to gain a better understanding of the follicular conditions associated with low oocyte developmental competence. Granulosa cells from 94 Holstein cows in a commercial embryo production facility were collected following ovarian stimulation and coasting. Microarray analysis showed 120 genes expressed with a differential of at least 1.5 when comparing donors of mostly competent with donors of mostly incompetent oocytes. Using ingenuity pathway analysis, we revealed the main biological functions and potential upstream regulators that distinguish donors of mostly incompetent oocytes. These are involved in cell proliferation, apoptosis, lipid metabolism, retinol availability and insulin signalling. In summary, we demonstrated that differences in follicle maturity at collection could explain differences in oocyte competence associated with individual animals. We also revealed deficiencies in lipid metabolism and retinol signalling in granulosa cells from donors of mostly incompetent oocytes.