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BackgroundEndometrium acquires structural and functional competence for embryo implantation only during the receptive phase of menstrual cycle in fertile women. Sizeable data are available to indicate that this ability is acquired by modulation in the expression of several genes/gene products. However, there exists little consensus on the identity, number of expressed/not-detected genes and their pattern of expression (up or down regulation).MethodsLiterature search was carried out to retrieve the data on endometrial expression of genes/proteins in various conditions. Data were compiled to generate a comprehensive database, Human Gene Expression Endometrial Receptivity database (HGEx-ERdb). The database was used to identify the Receptivity Associated Genes (RAGs) which display the similar pattern of expression across different investigations. Transcript levels of select RAGs encoding cell adhesion proteins were compared between two human endometrial epithelial cell lines; RL95-2 and HEC-1-A by quantitative real time polymerase chain reaction (q-RT-PCR). Further select RAGs were investigated for their expression in pre-receptive (n = 4) and receptive phase (n = 4) human endometrial tissues by immunohistochemical studies. JAr spheroid attachment assays were carried out to assess the functional significance of two RAGs.ResultsHGEx-ERdb (http://resource.ibab.ac.in/HGEx-ERdb/) helped identification of 179 RAGs, of which 151 genes were consistently expressed and upregulated and 28 consistently not-detected and downregulated in receptive phase as compared to pre-receptive phase. q-RT-PCR confirmed significantly higher (p<0.005) expression of Thrombospondin1 (THBS1), CD36 and Mucin 16 transcripts, in RL95-2 as compared to HEC-1-A. Further, the pretreatment with antibodies against CD36 and COMP led to a reduction in the percentage of JAr spheroids attached to RL95-2. Immunohistochemical studies demonstrated significantly higher (p<0.05) expression of endometrial THBS1, Cartilage Oligomeric Matrix Protein (COMP) and CD36 in the receptive phase as compared to pre-receptive phase human endometrial tissues.ConclusionHGEx-ERdb is a catalogue of 19,285 genes, reported for their expression in human endometrium. Further 179 genes were identified as the RAGs. Expression analysis of some RAGs validated the utility of approach employed in creation of HGEx-ERdb. Studies aimed towards defining the specific functions of RAGs and their potential networks may yield relevant information about the major ‘nodes’ which regulate endometrial receptivity.

Cancer-Associated Fibroblasts (CAFs) are crucial in genesis and progression of tumors; however, cervical CAFs (C-CAFs) are not well characterized. Estradiol (E2) has been implicated as a cofactor in human papillomavirus (HPV)-mediated cervical cancer (CxCa), both in animal models and in women using oral contraceptives; however, the exact role of the hormone is unclear. Human C-CAFs have recently been shown to express estrogen receptor alpha (ER-α). We investigated gene expression patterns in ex vivo cultured early and late stage C-CAFs in the context of E2. CAFs were isolated from four patients with early and two patients with late stage CxCa. ER-α expression in CxCa tissues was localized to stromal fibroblast-like cells and confirmed in ex vivo cultured C-CAFs. Two ER antagonists (ICI 182,780 and Methyl Piperidino Pyrazole) were used to unravel ER signaling in CAFs. Microarray technology was used for expression profiling and validated by quantitative reverse transcription PCR. The transcriptomes of C-CAFs across stages indicated their activated state. C-CAFs had gene expression patterns associated with both pro-tumorigenic and pro-inflammatory signaling. Late-stage C-CAFs compared to those of early stage appeared to be more actively metabolizing and cycling but expressed fewer genes related to immune function. We report differential expression profiles between C-CAFs: early vs. late stage and in the presence of ER antagonists. Both ER antagonists seemed to modulate C-CAF function by down regulating genes associated with cell cycle and metabolism, affecting angiogenesis and cancer progression. This study characterized C-CAFs from early and late stage disease, and experiments with ER inhibitors emphasized the probable importance of canonical ER-α signaling. Interfering with paracrine signaling through fibroblast ER-α is worth exploiting as a targeted therapy in CxCa management.

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BackgroundIn the recent years, there has been a rise in gene expression profiling reports. Unfortunately, it has not been possible to make maximum use of available gene expression data. Many databases and programs can be used to derive the possible expression patterns of mammalian genes, based on existing data. However, these available resources have limitations. For example, it is not possible to obtain a list of genes that are expressed in certain conditions. To overcome such limitations, we have taken up a new strategy to predict gene expression patterns using available information, for one tissue at a time.ResultsThe first step of this approach involved manual collection of maximum data derived from large-scale (genome-wide) gene expression studies, pertaining to mammalian testis. These data have been compiled into a Mammalian Gene Expression Testis-database (MGEx-Tdb). This process resulted in a richer collection of gene expression data compared to other databases/resources, for multiple testicular conditions. The gene-lists collected this way in turn were exploited to derive a 'consensus' expression status for each gene, across studies. The expression information obtained from the newly developed database mostly agreed with results from multiple small-scale studies on selected genes. A comparative analysis showed that MGEx-Tdb can retrieve the gene expression information more efficiently than other commonly used databases. It has the ability to provide a clear expression status (transcribed or dormant) for most genes, in the testis tissue, under several specific physiological/experimental conditions and/or cell-types.ConclusionsManual compilation of gene expression data, which can be a painstaking process, followed by a consensus expression status determination for specific locations and conditions, can be a reliable way of making use of the existing data to predict gene expression patterns. MGEx-Tdb provides expression information for 14 different combinations of specific locations and conditions in humans (25,158 genes), 79 in mice (22,919 genes) and 23 in rats (14,108 genes). It is also the first system that can predict expression of genes with a 'reliability-score', which is calculated based on the extent of agreements and contradictions across gene-sets/studies. This new platform is publicly available at the following web address: http://resource.ibab.ac.in/MGEx-Tdb/