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BioMed Research International
Volume 2014 (2014), Article ID 964614, 10 pages
Female Aging Alters Expression of Human Cumulus Cells Genes that Are Essential for Oocyte Quality
1UFR de Médecine, Université Montpellier 1, 34295 Montpellier, France
2CHU Montpellier, Institut pour la Médecine Régénérative et Biothérapies, Hôpital Saint-Eloi, INSERM U1040, 34295 Montpellier, France
3ART-PGD Department, CHU Montpellier, Hôpital Arnaud de Villeneuve, 34295 Montpellier, France
4Institute of Molecular Genetics of Montpellier, 34293 Montpellier, France
Received 2 July 2014; Revised 15 July 2014; Accepted 17 July 2014; Published 3 September 2014
Academic Editor: Calvin Yu-Chian Chen
Copyright © 2014 Tamadir Al-Edani et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Impact of female aging is an important issue in human reproduction. There was a need for an extensive analysis of age impact on transcriptome profile of cumulus cells (CCs) to link oocyte quality and developmental potential with patient’s age. CCs from patients of three age groups were analyzed individually using microarrays. RT-qPCR validation was performed on independent CC cohorts. We focused here on pathways affected by aging in CCs that may explain the decline of oocyte quality with age. In CCs collected from patients >37 years, angiogenic genes including ANGPTL4, LEPR, TGFBR3, and FGF2 were significantly overexpressed compared to patients of the two younger groups. In contrast genes implicated in TGF-β signaling pathway such as AMH, TGFB1, inhibin, and activin receptor were underexpressed. CCs from patients whose ages are between 31 and 36 years showed an overexpression of genes related to insulin signaling pathway such as IGFBP3, PIK3R1, and IGFBP5. A bioinformatic analysis was performed to identify the microRNAs that are potential regulators of the differentially expressed genes of the study. It revealed that the pathways impacted by age were potential targets of specific miRNAs previously identified in our CCs small RNAs sequencing.
In developing countries, the first baby is conceived with a delay that keeps increasing. With aging there is natural decline in female fertility, which raises crucial issues for the society. The fertility decline is slow and steady in 30 to 35 years old women. However, this decline accelerates past 35 years due to the decrease in oocyte quality and ovarian reserve [1, 2]. Therefore female age is crucial and oocyte aging is a common cause of assisted reproduction technology failures . MII oocyte stores large quantities of mRNA and proteins and contains a high number of mitochondria [4, 5]. Oocytes from women with an advanced reproductive age may have an increase of oxidative stress with consequences on mitochondrial DNA (mtDNA) integrity, resulting in mitochondrial dysfunction [6, 7]. Interestingly transcriptome profiles showed a substantial difference between younger and older human oocytes . Moreover the increase of aneuploidy due to aging is well documented. Indeed, the link between female age and oocyte aneuploidy prevalence was extensively studied . However both intrinsic (oocyte) and/or extrinsic (follicular) factors may be involved in the oocyte quality decline. The ovarian follicular microenvironment, mediated through cumulus cells (CCs), is crucial for the development of competent oocytes . The CCs are in physical contact with the oocyte; together they form the cumulus-oocyte complex (COC) and undergo a cross-talk . The oocyte controls the differentiation and expansion of CCs, which in turn are responsible for the metabolism of the glucose and pyruvate used for energy production in the oocyte . An aged follicular microenvironment could impact oocytes and leave a characteristic transcriptional footprint in the surrounding CCs. Indeed, the use of human CC gene expression has proved powerful as a noninvasive approach to predict oocyte quality and developmental potential [13–16]. The analysis of gene expression in human CCs in relation to female age is based on the same rationale [17–19]. However, with the exception of one proteomic analysis , no high throughput study based on gene expression profile in relation to female age was performed on cumulus cells. Our hypothesis here is based on the assumption that female age may have a wide impact on gene expression and may specifically affect pathways that are critical for oocyte quality and development. The purposes of this study were (i) to thoroughly evaluate impact of maternal age on gene expression profiles using individual CCs isolated from the periovulatory follicles of three age categories of patients, (ii) to characterize the pathways that were significantly affected by female aging, and (iii) to identify their miRNAs regulators.
2. Materials and Methods
2.1. Sample Characterization and Collection
The Review Board of the Institute of Research in Biotherapy approved this project. All patients provided their written informed consent for the use of CC samples for research.
CC samples were collected from patients who participated to the multicentric trial previously described  and from Montpellier ART centre. Patients were stimulated with a combination of GnRH antagonist protocol with recombinant FSH or with HP-hMG before undergoing intracytoplasmic sperm injection (ICSI) procedure for male infertility. Cumulus oocyte complexes (COCs) were recovered under ultrasound echo-guidance 36 h after human Chorionic Gonadotrophin (5,000 UI, hCG) administration. CCs were separated mechanically from the corresponding oocyte as previously described . For microarray 28 individual CC samples obtained from 16 patients were classified into three age groups: <30 years (), 31–34 years (), and >37 years (). The qRT-PCR analyses were performed on 15 independent CCs from the above groups and 4 CCs from a 35-36 additional group.
2.2. RNA Extraction and Microarray Processing
CCs were frozen at −80°C in RLT buffer before RNA extraction. Then the RNeasy Micro kit (ref: 74004; Qiagen) was used to extract total RNA from each CC sample, according to the manufacturers’ recommended protocols. The quantity and purity of the total RNAs were determined by using a NanoDrop ND-1000 spectrophotometer (NanoDrop ND-Thermo Fisher Scientific, Wilmington, DE, USA) and their integrity determined by using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, http://www.agilent.com). All RNA samples were stored at −80°C. Microarray experiments were performed on the microarray platform of Institute of Research in Biotherapy at the Montpellier University Hospital. The Affymetrix 3′ IVT express protocol (reference 901229) was used as previously described .
2.3. Microarray Data Analysis
After image processing with the Affymetrix GeneChip Operating 1.4 software, the CEL files were analyzed using the Affymetrix Expression Console Software v1.3.1 and normalized with the MAS5.0 algorithm by scaling each array to a target value of 100 using the global scaling method. This algorithm also determines whether a gene is expressed with a defined “detection call.” This “call” can either be “present” (when the perfect match probes are significantly more hybridized than the mismatch probes, ), “marginal” (0.04 < ), or “absent” (). Gene annotation was performed using NetAffx (http://www.affymetrix.com; March 2009). A first selection using the detection call (present in at least seven samples) and variation coefficient (≥40%) of CC samples identified 9,802 transcripts. Then, to compare the three groups of CCs according to maternal age, a Significance Analysis of Microarrays-Multiclass (SAM-M) (http://statweb.stanford.edu/~tibs/SAM/) was used. SAM-M handed the significantly expressed genes with a q-value <5% in the three age categories. CLUSTER and TREEVIEW software packages were used for the hierarchical clustering analysis. SPSS 12.0 (SPSS, Chicago, IL) software was used for box-and-whisker plots representation of expression levels of specific genes. The miRNA target predictions were performed with GeneGo MetaCore analysis software (St. Joseph, MI). Ingenuity Pathway Analysis software and DAVID (http://david.abcc.ncifcrf.gov/) were used for functional annotation.
2.4. Quantitative RT-PCR
Reverse transcription (RT) was performed as recommended by the manufacturer (Invitrogen) with 150 ng of RNA in a 20 μL reaction volume that included Superscript II (ref. 18064-014, Invitrogen), oligo-dT primer, dNTP mixture, MgCl2, and RNase inhibitor. Quantitative PCR was performed using the SYBR Green I Master kit (Roche Diagnostics, Mannheim, Germany) with 2 μL of 1/20 dilution of the RT reaction product and 0.5 mM primer (SIGMA Genosys) in a total volume of 10 μL. The amplification was run in a LightCycler 480 apparatus as follows: after the denaturation step for 10 min at 95°C, cycling conditions were 10 s at 95°C, 30 s at 65°C and 1 s at 72°C for 45 cycles. Gene expression levels were normalized to the housekeeping gene Glyceraldehyde 3-Phosphate Dehydrogenase (GAPDH) using the following formula where . The primer sequences are shown in (see Table SI in Supplementary Material available online at http://dx.doi.org/10.1155/2014/964614).
2.5. Statistical Analysis
Statistical analysis was performed with the GraphPad InStat 3 software. For qRT-PCR, the Kruskal-Wallis nonparametric test was used. The differences among the groups were considered significant when the P value is <0.05.
3.1. Gene Expression Profiles of CCs according to Female Age
In order to gain insight into the molecular basis of age impact on COCs, we analyzed the transcriptomes of CCs from women with different age categories. A first selection based on the detection call and variation coefficient of all the CC samples from aged and young patients delineated 9,802 transcripts. Then, using SAM-M and after having discarded 35 genes that we previously showed to be affected by the COS protocols , we identified a total of 2,186 transcripts (corresponding to 1,874 genes) with a q-value <5% that significantly distinguished the three CC groups according to female age (Supplementary Table SII). The analysis of the transcriptome data revealed a characteristic molecular signature for each one of the three age categories (Figure 1). The expression patterns of the genes that best represent these categories are illustrated in the box-plots (Figure 1(a)). In group, overexpression was observed for inflammatory response genes such as B4GALT1, SERPINA1, C1S, IL18R1, FN1, and OSMR. The group revealed overexpression of genes involved in insulin signaling pathway, the most representative being IGFBP3, IGFBP5 and PIK3R1. Finally the CColder group was significantly enriched with genes that are important for angiogenesis such as ANGPTL4, LEPR, TGFBR3, VEGFC, FGF2 and NR2F2. In addition, a list of 20 genes with the highest contrast and lowest q-value according to SAM-M, were chosen for each category to perform the hierarchical clustering (Supplementary Table SIII). Interestingly, CColder samples distantly located from the and samples (Figure 1(b)).
3.2. Validation of Gene Expression by Quantitative RT-PCR
Nine differentially expressed genes were selected for validation on the basis of relevant functional annotations. Hence, three genes involved in the inflammatory process (B4GALT1, SERPINA1, and C1S), three genes of the insulin signaling (IGFBP3, IGFBP5, and PIK3R1) and three genes of the angiogenesis process (ANGPTL4, LEPR, and TGFBR3) were chosen for qRT-PCR validation. Analysis of the qRT-PCR data on independent cohorts of CCs indicated that all the selected genes were differentially expressed in the three age categories and in agreement with the microarray findings (Figure 2). Using qRT-PCR we aimed to test the expression level of the above genes in individual CCs from 35 and 36 old patients. These CCs clearly displayed an expression pattern similar to the age category (Figure SI) suggesting that the switch for these genes occurs after the age of 36.
3.3. Deregulation in Genes that Are Essential for the Oocyte Quality and Competence
Many biological pathways were reported to be crucial for their impact on the oocyte development. They include transforming growth factor β (TGF-β) signaling, steroidogenesis and metabolic pathways. Interestingly the key members of these pathways displayed significant changes in their gene expression (Table SII). As shown in Figure 3(a), many genes of the TGF-β signaling pathway were underexpressed in CColder compared with and , including AMH (Anti-Mullerien Hormone), TGFB1, inhibin (INHA) and activin receptor (ACVR2B). In contrast overexpression was observed in CColder for several genes that are involved in steroidogenesis and fatty acid metabolism (HSD17B1, HSD17B6, NSDHL, SRA1, CYP19A1, PPARA), glucose metabolism (ALG13, GLT8D3) and glucose transporters (SLC2A3, SLC2A1, SLC2A13, SLC2A8). It is noteworthy that several genes that play an essential role in the cumulus-oocyte dialog (INHA, CD200 and IL6ST) were downregulated in CColder (Figure 3(b)). Moreover, CColder may be distinguished from the two younger age categories by a downregulation of genes that are essential for genome integrity, in particular MSRB3, UCHL5IP, POLH, OBFC2B, and CHAF1A that are essential for antioxidative and DNA repair functions.
3.4. Potential miRNA Regulators of the Differentially Expressed Genes of the Study
Using the GenGo Metacore software, we first aimed to identify which miRNAs regulate the genes that were overexpressed in each of the three age categories, , and CColder (Figure 4(a)). We identified altogether 286 miRNAs that are putative regulators of the differentially expressed genes identified in this study, among which 176 are common putative regulators of the genes overexpressed in the three age categories, 71 for the genes whose expression was higher in and . Only one miRNA was shared by and CColder categories specifically; similarly genes overexpressed in and CColder had one specific miRNA in common. Interestingly this analysis also discriminates the CColder from and , which may be considered as a super-group with common features. Some miRNAs were specific for one of the three age categories. Thirty-three miRNAs were identified as putative regulators of the genes overexpressed in CColder, one for the and 3 for the categories (for the comprehensive lists, see Supplementary Table SIV). Among all the miRNAs retrieved by GenGo, 87% were identified by sequencing in CCs . The fact that only the differentially expressed genes were submitted to GenGO may account for the missing 13%. There is another discrepancy between the list of the potential regulators and the miRNAs actually present in the CCs as identified in our previous work . It is illustrated in Figure 4(a) for the two categories that stand out in the present study, namely the - super-group (71) on the one hand and the CColder (33) on the other hand. Among these potential miRNA regulators, only 6 are actually expressed in CCs: MIR425, MIR744, MIR146b, Let-7d for the - super group and MIR202, Let-7e for the CColder. This discrepancy might reflect a tissue specific expression of miRNAs. Interestingly MIR202 is a potential regulator of the hyaluronan synthase-encoding gene HAS2 that is related to aging and angiogenesis  and MIR744 is a TGFB1 validated regulator . The largest set of miRNAs retrieved by GenGo was common to the three age categories (176). This set was crossed with those effectively expressed in CCs , resulting in a list of 22 miRNAs. We were interested in those that regulate significant gene members of the pathways and processes impacted by female age and that were also experimentally validated. The results of this analysis are shown in Figure 4(b). None fulfills these criteria for the validated genes of the inflammatory process overexpressed in the . In , IGFBP3, and IGFBP5 of the insulin-signaling pathway are targets of MIR210 and MIR140, respectively. Finally in CColder, genes implicated in angiogenesis LEPR and TGFBR3 are MIR21 targets whereas FGF2 is targeted by MIR424. For more details see Table SV.
Acquisition of oocyte competence is a gradual and complex process, which depends on the follicular microenvironment. Within this microenvironment, the bidirectional communication between the CCs and the oocyte plays a crucial role. Therefore gene expression in CCs mirrors the oocyte physiology. In order to gain insight into the mechanisms that underlie oocyte quality decline with age, we first investigated the transcriptome profiles in CCs from women of three age categories. Our objective was to identify molecular signatures characteristic of each age category and investigate their biological relevance to oocyte quality. DNA microarray analysis revealed a significantly distinct molecular signature of 1,874 genes among the three age groups, suggesting a wide impact of female age on the CC gene-expression profile. It is noteworthy that the inflammatory genes emerged in the group such as IL18R1, IL1R1, IL1R2, SERPINA1, and B4GALT1. Inflammatory reaction is known to induce ovulation through infiltration of leukocytes into the area surrounding the follicle . Cytokines are important in the regulation of ovarian function and oocyte quality . On the other hand interleukins IL18 and IL1β were reported to be present in floating granulosa cells of human preovulatory follicles . group may be characterized by an overexpression of gene members of the “insulin-signaling pathway”, such as IGFBP3 and IGFBP5 whereas INSR was overexpressed in both the and CColder groups. Several studies have shown that insulin and IGF system play an important role in folliculogenesis [27–29] and in oocyte maturation . IGF-binding proteins (IGFBPs) that modulate interactions of IGFs with IGF and insulin receptors  have also an antiangiogenic activity [32–34]. Therefore, overexpression of IGFBPs in may be to modulate angiogenesis and maintain a balance. Last, the CColder group is precisely characterized by an upregulation of genes associated with angiogenesis (ANGPTL4, LEPR, TGFBR3, VEGFC, FGF2 and NR2F2). Angiogenesis plays a critical role in the late stages of folliculogenesis by providing nutrients and oxygen to the growing follicles. However, it may be associated with pathology and induced by microenvironmental factors like hypoxia. In this context, the follicular cells synthesize several angiogenic factors [26, 35, 36], among which the vascular endothelial growth factor C (VEGFC) and angiopoietin-like 4 (ANGPTL4), which are induced in response to hypoxic stimuli [37–39]. So, the overexpression of angiogenic factors and hypoxia-inducible protein 2 (HIG2) in the CColder group could be caused by insufficiency of oxygen. Similarly VEGF that is shown to increase in follicular fluid with age could be enhanced by hypoxia in old follicles [40, 41]. Most interestingly oocytes from hypoxic follicles have disorganized meiotic spindles . These observations added to the reported increase of aneuploidy with female aging  may be revisited in light of our results. Hypoxia might be one of the consequences of aging, which in turn would affect chromosome segregation. Adaptive changes to oxygen availability are critical for cell survival and tissue homeostasis. Therefore, augmentation of angiogenesis in the CColder group may be a compensatory process to modulate the deleterious impact of hypoxia. Similarly the upregulation of genes that encode metabolic enzymes (HSD17B, CYP19A1, ALG13, and GLT8D3) and glucose transporters (SLC2A3, SLC2A1, SLC2A13, SLC2A8) in the CColder group could reflect a compensatory mechanism to increase energy production. These results are consistent with the observations reported recently [17, 19]. Indeed, the energy supplied by the CCs is known to be required for oocyte quality [44, 45]. Some members of the TGF-β superfamily, which are crucial to processes that govern follicle development and oocyte maturation , were underexpressed in the CColder group such as AMH (Anti-Mullerien Hormone), TGFB1, inhibin (INHA),and activin receptor (ACVR2B). Interestingly AMH is produced by early primary follicles and its mRNA level is known to decrease with age. Therefore, it represents an early marker of ovarian follicle growth and a reliable marker of ovarian reserve and oocyte quality [47–49].
Another important question we addressed concerns the regulation of the genes that stand out in our study. We focused on the bioinformatic analysis of miRNAs. MiRNAs are noncoding small RNAs (18–25 nucleotides), which regulate cellular genes through RNA degradation or translational inhibition [50, 51]. Not only miRNAs have been shown to regulate the aging process in different tissues and cells , but their importance is also well recognized in the control of human cumulus-oocyte crosstalk and ovarian function and aging [21, 53, 54]. Interestingly, TGF-β signaling is one of the most significant pathways targeted by miRNAs contained in the follicular fluid . Moreover gene members of this pathway are direct targets of MIR21 that is the most abundant miRNA in CCs . The role of MIR21 is essential in ovarian function toprevent apoptosis in mouse periovulatory granulosa cells both in vivo and in vitro . Moreover, it promotes the follicular cell survival during ovulation and is upregulated during luteinization . Interestingly, a recent work reports a correlation between MIR21 abundance and women age; a significant decrease was observed in follicular fluid of older women . In the current study, two angiogenic genes (LEPR and TGFBR3) were upregulated in CColder where MIR21 is the least abundant . Finally, the process that is central to this study is angiogenesis that may be induced in response to hypoxia, a major issue in aging follicles. Interestingly, miRNAs play a critical role in the cellular response to hypoxia . MIR210 whose overexpressionin hypoxic conditions induces angiogenesis [59, 60] directly targets IGFBP3, an inhibitor of angiogenesis [32, 61]. Furthermore, MIR424 that is downregulated in response to hypoxia in primary human trophoblasts  targets FGF2, an angiogenesis inducer [63, 64]. Taken together these data suggest that in aging follicles angiogenesis may be induced in response to hypoxia by the underexpression of IGFBP3 and overexpression of FGF2.
The present study reports for the first time an extensive analysis of gene expression in cumulus cells in relation to female age. Specific molecular signatures were characterized for the three age categories. Our findings point to aging as a major player in processes and pathways that are of key biological importance for oocyte growth and genome integrity. Moreover the upregulation of angiogenic genes in CColder is very informative on the way the follicle attempts to buffer the deleterious impact of aging associated hypoxia. In addition to the transcriptomes, the comprehensive characterization of the miRNA regulators of the genes impacted by female age represents a valuable resource for future investigations on the biology of aging oocyte.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Tamadir Al-Edani and Said Assou contributed equally to this work.
This work was supported by Ferring Pharmaceuticals A/S. The authors thank the direction of the Montpellier 1 University and University Hospital of Montpellier for their support. They thank all members of ART team for their assistance during this study.
- M. J. Faddy, R. G. Gosden, A. Gougeon, S. J. Richardson, and J. F. Nelson, “Accelerated disappearance of ovarian follicles in mid-life: implications for forecasting menopause,” Human Reproduction, vol. 7, no. 10, pp. 1342–1346, 1992.
- C. Alviggi, P. Humaidan, C. M. Howles, D. Tredway, and S. G. Hillier, “Biological versus chronological ovarian age: implications for assisted reproductive technology,” Reproductive Biology and Endocrinology, vol. 7, article 101, 2009.
- A. J. Wilcox, C. R. Weinberg, and D. D. Baird, “Post-ovulatory ageing of the human oocyte and embryo failure,” Human Reproduction, vol. 13, no. 2, pp. 394–397, 1998.
- R. P. S. Jansen, “Germline passage of mitochondria: quantitative considerations and possible embryological sequelae,” Human Reproduction, vol. 15, supplement 2, pp. 112–128, 2000.
- T. A. L. Brevini Gandolfi and F. Gandolfi, “The maternal legacy to the embryo: cytoplasmic components and their effects on early development,” Theriogenology, vol. 55, no. 6, pp. 1255–1276, 2001.
- A. Agarwal, S. Gupta, and R. K. Sharma, “Role of oxidative stress in female reproduction,” Reproductive Biology and Endocrinology, vol. 3, article 28, 2005.
- U. Eichenlaub-Ritter, M. Wieczorek, S. Lüke, and T. Seidel, “Age related changes in mitochondrial function and new approaches to study redox regulation in mammalian oocytes in response to age or maturation conditions,” Mitochondrion, vol. 11, no. 5, pp. 783–796, 2011.
- M. L. Grøndahl, C. Y. Andersen, J. Bogstad, F. C. Nielsen, H. Meinertz, and R. Borup, “Gene expression profiles of single human mature oocytes in relation to age,” Human Reproduction, vol. 25, no. 4, pp. 957–968, 2010.
- E. Fragouli, D. Wells, and J. D. A. Delhanty, “Chromosome abnormalities in the human oocyte,” Cytogenetic and Genome Research, vol. 133, no. 2–4, pp. 107–118, 2011.
- R. B. Gilchrist, M. Lane, and J. G. Thompson, “Oocyte-secreted factors: regulators of cumulus cell function and oocyte quality,” Human Reproduction Update, vol. 14, no. 2, pp. 159–177, 2008.
- D. F. Albertini, C. M. H. Combelles, E. Benecchi, and M. J. Carabatsos, “Cellular basis for paracrine regulation of ovarian follicle development,” Reproduction, vol. 121, no. 5, pp. 647–653, 2001.
- D. L. Russell and R. L. Robker, “Molecular mechanisms of ovulation: co-ordination through the cumulus complex,” Human Reproduction Update, vol. 13, no. 3, pp. 289–312, 2007.
- S. Assou, D. Haouzi, J. de Vos, and S. Hamamah, “Human cumulus cells as biomarkers for embryo and pregnancy outcomes,” Molecular Human Reproduction, vol. 16, no. 8, Article ID gaq032, pp. 531–538, 2010.
- S. Assou, D. Haouzi, K. Mahmoud et al., “A non-invasive test for assessing embryo potential by gene expression profiles of human cumulus cells: a proof of concept study,” Molecular Human Reproduction, vol. 14, no. 12, pp. 711–719, 2008.
- M. Hamel, I. Dufort, C. Robert et al., “Identification of differentially expressed markers in human follicular cells associated with competent oocytes,” Human Reproduction, vol. 23, no. 5, pp. 1118–1127, 2008.
- S. Assou, I. Boumela, D. Haouzi et al., “Dynamic changes in gene expression during human early embryo development: from fundamental aspects to clinical applications,” Human Reproduction Update, vol. 17, no. 2, Article ID dmq036, pp. 272–290, 2011.
- S. McReynolds, M. Dzieciatkowska, B. R. McCallie et al., “Impact of maternal aging on the molecular signature of human cumulus cells,” Fertility and Sterility, vol. 98, no. 6, pp. 1574.e5–1580.e5, 2012.
- M.-S. Lee, C.-H. Liu, T.-H. Lee et al., “Association of creatin kinase B and peroxiredoxin 2 expression with age and embryo quality in cumulus cells,” Journal of Assisted Reproduction and Genetics, vol. 27, no. 11, pp. 629–639, 2010.
- L. Pacella, D. L. Zander-Fox, D. T. Armstrong, and M. Lane, “Women with reduced ovarian reserve or advanced maternal age have an altered follicular environment,” Fertility and Sterility, vol. 98, no. 4, pp. 986.e2–994.e2, 2012.
- S. Assou, D. Haouzi, H. Dechaud, A. Gala, A. Ferrieres, and S. Hamamah, “Comparative gene expression profiling in human cumulus cells according to ovarian gonadotropin treatments,” BioMed Research International, vol. 2013, Article ID 354582, 13 pages, 2013.
- S. Assou, T. Al-Edani, D. Haouzi et al., “MicroRNAs: new candidates for the regulation of the human cumulus-oocyte complex,” Human Reproduction, vol. 28, no. 11, pp. 3038–3049, 2013.
- C. C. Sprenger, S. R. Plymate, and M. J. Reed, “Aging-related alterations in the extracellular matrix modulate the microenvironment and influence tumor progression,” International Journal of Cancer, vol. 127, no. 12, pp. 2739–2748, 2010.
- J. Martin, R. H. Jenkins, R. Bennagi et al., “Post-transcriptional regulation of transforming growth factor beta-1 by microRNA-744,” PLoS ONE, vol. 6, no. 10, Article ID e25044, 2011.
- J. Goto, N. Suganuma, K. Takata et al., “Morphological analyses of interleukin-8 effects on rat ovarian follicles at ovulation and luteinization in vivo,” Cytokine, vol. 20, no. 4, pp. 168–173, 2002.
- S. Vujisić, S. Ž. Lepej, I. Emedi, R. Bauman, A. Remenar, and M. K. Tiljak, “Ovarian follicular concentration of IL-12, IL-15, IL-18 and p40 subunit of IL-12 and IL-23,” Human Reproduction, vol. 21, no. 10, pp. 2650–2655, 2006.
- S. Kõks, A. Velthut, A. Sarapik et al., “The differential transcriptome and ontology profiles of floating and cumulus granulosa cells in stimulated human antral follicles,” Molecular Human Reproduction, vol. 16, no. 4, Article ID gap103, pp. 229–240, 2009.
- H. Louhio, O. Hovatta, J. Sjöberg, and T. Tuuri, “The effects of insulin, and insulin-like growth factors I and II on human ovarian follicles in long-term culture,” Molecular Human Reproduction, vol. 6, no. 8, pp. 694–698, 2000.
- J. Zhao, M. A. Taverne, G. C. van der Weijden, M. M. Bevers, and R. van den Hurk, “Insulin-like growth factor-I (IGF-I) stimulates the development of cultured rat pre-antral follicles,” Molecular Reproduction and Development, vol. 58, no. 3, pp. 287–296, 2001.
- J. Kwintkiewicz and L. C. Giudice, “The interplay of insulin-like growth factors, gonadotropins, and endocrine disruptors in ovarian follicular development and function,” Seminars in Reproductive Medicine, vol. 27, no. 1, pp. 43–51, 2009.
- P. L. Lorenzo, M. J. Illera, J. C. Illera, and M. Illera, “Enhancement of cumulus expansion and nuclear maturation during bovine oocyte maturation in vitro by the addition of epidermal growth factor and insulin-like growth factor I,” Journal of Reproduction and Fertility, vol. 101, no. 3, pp. 697–701, 1994.
- S. M. Firth and R. C. Baxter, “Cellular actions of the insulin-like growth factor binding proteins,” Endocrine Reviews, vol. 23, no. 6, pp. 824–854, 2002.
- S.-H. Oh, W.-Y. Kim, O.-H. Lee et al., “Insulin-like growth factor binding protein-3 suppresses vascular endothelial growth factor expression and tumor angiogenesis in head and neck squamous cell carcinoma,” Cancer Science, vol. 103, no. 7, pp. 1259–1266, 2012.
- M. J. Moreno, M. Ball, M. Rukhlova et al., “IGFBP-4 anti-angiogenic and anti-tumorigenic effects are associated with anti-cathepsin B activity,” Neoplasia, vol. 15, no. 5, pp. 554–567, 2013.
- C. Zhang, L. Lu, Y. Li et al., “IGF binding protein-6 expression in vascular endothelial cells is induced by hypoxia and plays a negative role in tumor angiogenesis,” International Journal of Cancer, vol. 130, no. 9, pp. 2003–2012, 2012.
- H. M. Fraser, “Regulation of the ovarian follicular vasculature,” Reproductive Biology and Endocrinology, vol. 4, article 18, 2006.
- C. W. Pugh and P. J. Ratcliffe, “Regulation of angiogenesis by hypoxia: role of the HIF system,” Nature Medicine, vol. 9, no. 6, pp. 677–684, 2003.
- M. Neeman, R. Abramovitch, Y. S. Schiffenbauer, and C. Tempel, “Regulation of angiogenesis by hypoxic stress: from solid tumours to the ovarian follicle,” International Journal of Experimental Pathology, vol. 78, no. 2, pp. 57–70, 1997.
- P. González-Muniesa, C. de Oliveira, F. P. de Heredia, M. P. Thompson, and P. Trayhurn, “Fatty acids and hypoxia stimulate the expression and secretion of the adipokine ANGPTL4 (angiopoietin-like protein 4/ fasting-induced adipose factor) by human adipocytes,” Journal of Nutrigenetics and Nutrigenomics, vol. 4, no. 3, pp. 146–153, 2011.
- S.-H. Kim, Y.-Y. Park, S.-W. Kim, J.-S. Lee, D. Wang, and R. N. DuBois, “ANGPTL4 induction by prostaglandin E 2 under hypoxic conditions promotes colorectal cancer progression,” Cancer Research, vol. 71, no. 22, pp. 7010–7020, 2011.
- C. I. Friedman, D. R. Danforth, C. Herbosa-Encarnacion, L. Arbogast, B. M. Alak, and D. B. Seifer, “Follicular fluid vascular endothelial growth factor concentrations are elevated in women of advanced reproductive age undergoing ovulation induction,” Fertility and Sterility, vol. 68, no. 4, pp. 607–612, 1997.
- E. Y. Fujii and M. Nakayama, “The measurements of RAGE, VEGF, and AGEs in the plasma and follicular fluid of reproductive women: the influence of aging,” Fertility and Sterility, vol. 94, no. 2, pp. 694–700, 2010.
- J. van Blerkom, M. Antczak, and R. Schrader, “The developmental potential of the human oocyte is related to the dissolved oxygen content of follicular fluid: association with vascular endothelial growth factor levels and perifollicular blood flow characteristics,” Human Reproduction, vol. 12, no. 5, pp. 1047–1055, 1997.
- E. Fragouli, V. Bianchi, P. Patrizio et al., “Transcriptomic profiling of human oocytes: association of meiotic aneuploidy and altered oocyte gene expression,” Molecular Human Reproduction, vol. 16, no. 8, pp. 570–582, 2010.
- Q. Li, D.-Q. Miao, P. Zhou et al., “Glucose metabolism in mouse cumulus cells prevents oocyte aging by maintaining both energy supply and the intracellular redox potential,” Biology of Reproduction, vol. 84, no. 6, pp. 1111–1118, 2011.
- D. Brisard, A. Desmarchais, J. L. Touze et al., “Alteration of energy metabolism gene expression in cumulus cells affects oocyte maturation via MOS-mitogen-activated protein kinase pathway in dairy cows with an unfavorable “Fertil-” haplotype of one female fertility quantitative trait locus,” Theriogenology, vol. 81, no. 4, pp. 599–612, 2014.
- P. G. Knight and C. Glister, “Local roles of TGF-β superfamily members in the control of ovarian follicle development,” Animal Reproduction Science, vol. 78, no. 3-4, pp. 165–183, 2003.
- Z. Merhi, E. Buyuk, D. S. Berger et al., “Leptin suppresses anti-Mullerian hormone gene expression through the JAK2/STAT3 pathway in luteinized granulosa cells of women undergoing IVF,” Human Reproduction, vol. 28, no. 6, pp. 1661–1669, 2013.
- A. L. L. Durlinger, M. J. G. Gruijters, P. Kramer et al., “Anti-Müllerian hormone inhibits initiation of primordial follicle growth in the mouse ovary,” Endocrinology, vol. 143, no. 3, pp. 1076–1084, 2002.
- P. Lehmann, M. P. Velez, J. Saumet et al., “Anti-mullerian hormone (AMH): a reliable biomarker of oocyte quality in IVF,” Journal of Assisted Reproduction and Genetics, vol. 31, no. 4, pp. 493–498, 2014.
- D. P. Bartel, “MicroRNAs: target recognition and regulatory functions,” Cell, vol. 136, no. 2, pp. 215–233, 2009.
- E. Huntzinger and E. Izaurralde, “Gene silencing by microRNAs: contributions of translational repression and mRNA decay,” Nature Reviews Genetics, vol. 12, no. 2, pp. 99–110, 2011.
- D. Xu and H. Tahara, “The role of exosomes and microRNAs in senescence and aging,” Advanced Drug Delivery Reviews, vol. 65, no. 3, pp. 368–375, 2013.
- A. Diez-Fraile, T. Lammens, K. Tilleman et al., “Age-associated differential microRNA levels in human follicular fluid reveal pathways potentially determining fertility and success of in vitro fertilization,” Human Fertility, vol. 17, no. 2, pp. 90–98, 2014.
- X. Yang, Y. Zhou, S. Peng et al., “Differentially expressed plasma microRNAs in premature ovarian failure patients and the potential regulatory function of mir-23a in granulosa cell apoptosis,” Reproduction, vol. 144, no. 2, pp. 235–244, 2012.
- J. C. da Silveira, D. N. R. Veeramachaneni, Q. A. Winger, E. M. Carnevale, and G. J. Bouma, “Cell-secreted vesicles in equine ovarian follicular fluid contain mirnas and proteins: a possible new form of cell communication within the ovarian follicle,” Biology of Reproduction, vol. 86, no. 3, article 71, 2012.
- M. Z. Carletti, S. D. Fiedler, and L. K. Christenson, “MicroRNA 21 blocks apoptosis in mouse periovulatory granulosa cells,” Biology of Reproduction, vol. 83, no. 2, pp. 286–295, 2010.
- F. X. Donadeu, S. N. Schauer, and S. D. Sontakke, “Involvement of miRNAs in ovarian follicular and luteal development,” Journal of Endocrinology, vol. 215, no. 3, pp. 323–334, 2012.
- Y. C. Chan, J. Banerjee, S. Y. Choi, and C. K. Sen, “miR-210: the master hypoxamir,” Microcirculation, vol. 19, no. 3, pp. 215–223, 2012.
- L. Zeng, X. He, Y. Wang et al., “MicroRNA-210 overexpression induces angiogenesis and neurogenesis in the normal adult mouse brain,” Gene Therapy, vol. 21, no. 1, pp. 37–43, 2014.
- J. Y. Li, T. Y. Yong, M. Z. Michael, and J. M. Gleadle, “MicroRNAs: are they the missing link between hypoxia and pre-eclampsia?” Hypertens Pregnancy, vol. 33, no. 1, pp. 102–114, 2014.
- T. Bertero, S. Grosso, K. Robbe-Sermesant et al., ““Seed-milarity” confers to hsa-miR-210 and hsa-miR-147b similar functional activity,” PLoS ONE, vol. 7, no. 9, Article ID e44919, 2012.
- J. F. Mouillet, R. B. Donker, T. Mishima, T. Cronqvist, T. Chu, and Y. Sadovsky, “The unique expression and function of miR-424 in human placental trophoblasts,” Biology of Reproduction, vol. 89, no. 2, p. 25, 2013.
- T. Ren, Y. Qing, N. Dai, et al., “Apurinic/apyrimidinic endonuclease 1 induced upregulation of fibroblast growth factor 2 and its receptor 3 induces angiogenesis in human osteosarcoma cells,” Cancer Science, vol. 105, no. 2, pp. 186–194, 2014.
- J. Kim, Y. Kang, Y. Kojima et al., “An endothelial apelin-FGF link mediated by miR-424 and miR-503 is disrupted in pulmonary arterial hypertension,” Nature Medicine, vol. 19, no. 1, pp. 74–82, 2013.