Identification of mRNAs related to endometrium function regulated by lncRNA CD36-005 in rat endometrial stromal cells

Whispers of the polycystic ovary syndrome theater: Directing role of long noncoding RNAs

Polycystic Ovary Syndrome (PCOS) is a multifaceted endocrine disorder that implicates a spectrum of clinical manifestations, including hormonal imbalance, metabolic dysfunction, and even compromised ovarian granulosa cell (GC) activity. The underlying molecular mechanisms of PCOS remain elusive, presenting a significant barrier to effective diagnosis and treatment. This review delves into the emerging role of long non-coding RNAs (lncRNAs) in the pathophysiology of PCOS, articulating their intricate interactions with mRNAs, microRNAs, and other epigenetic regulators that collectively influence the hormonal and metabolic milieu of PCOS. We examine the dynamic regulatory networks orchestrated by lncRNAs that impact GC function, steroidogenesis, insulin resistance, and inflammatory pathways. By integrating findings from recent studies, we illuminate the potential of lncRNAs as biomarkers for PCOS and highlight their contribution to the disorder, offering a detailed perspective on the lncRNA-mediated modulation of gene expression and pathogenic pathways. Understanding targeted lncRNA interactions with PCOS proposes novel avenues for therapeutic intervention to ameliorate the reproductive and metabolic disturbances characteristic of the syndrome.

Unveiling the Role of Artificial Intelligence (AI) in Polycystic Ovary Syndrome (PCOS) Diagnosis: A Comprehensive Review

Polycystic Ovary Syndrome (PCOS) is one of the most widespread endocrine and metabolic disorders affecting women of reproductive age. Major symptoms include hyperandrogenism, polycystic ovary, irregular menstruation cycle, excessive hair growth, etc., which sometimes may lead to more severe complications like infertility, pregnancy complications and other co-morbidities such as diabetes, hypertension, sleep apnea, etc. Early detection and effective management of PCOS are essential to enhance patients' quality of life and reduce the chances of associated health complications. Artificial intelligence (AI) techniques have recently emerged as a popular methodology in the healthcare industry for diagnosing and managing complex diseases such as PCOS. AI utilizes machine learning algorithms to analyze ultrasound images and anthropometric and biochemical test result data to diagnose PCOS quickly and accurately. AI can assist in integrating different data sources, such as patient histories, lab findings, and medical records, to present a clear and complete picture of an individual's health. This information can help the physician make more informed and efficient diagnostic decisions. This review article provides a comprehensive analysis of the evolving role of AI in various aspects of the management of PCOS, with a major focus on AI-based diagnosis tools.

Expression profile analysis of LncRNAs and mRNAs in pre-receptive endometrium of women with polycystic ovary syndrome undergoing in vitro fertilization-embryo transfer

BACKGROUND

To compare the expression levels of long non-coding RNA (lncRNA) and messenger RNA (mRNA) in pre-receptive endometrium between patients with Polycystic Ovary Syndrome (PCOS)and normal ovulation undergoing in vitro fertilization-embryo transfer (IVF-ET).

METHODS

Endometrial tissues were collected with endometrial vacuum curette in pre-receptive phase (3 days after oocytes retrieval) from PCOS and control groups. LncRNAs and mRNAs of endometrium were identified via RNA sequencing and alignments. A subset of 9 differentially expressed lncRNAs and 11 mRNAs were validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)in 22 PCOS patients and 18 ovulation patients. The function of mRNAs with differential expression patterns were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).

RESULTS

We found out 687 up-regulated and 680 down-regulated mRNAs, as well as 345 up-regulated and 63 down-regulated lncRNAs in the PCOS patients in contrast to normal ovulation patients. qRT-PCR was used to detect the expression of 11 mRNAs, and validated that the expression of these 6 mRNAs CXCR4, RABL6, OPN3, SYBU, IDH1, NOP10 were significantly elevated among PCOS patients, and the expression of ZEB1 was significantly decreased. qRT-PCR was performed to detect the expression of 9 lncRNAs, and validated that the expression of these 7 lncRNAs IDH1-AS1, PCAT14, FTX, DANCR, PRKCQ-AS1, SNHG8, TPT1-AS1 were significantly enhanced among PCOS patients. Bioinformatics analysis showed that differentially expressed genes (DEGs) involved KEGG pathway were tyrosine metabolism, PI3K-Akt pathway, metabolic pathway, Jak-STAT pathway, pyruvate metabolism, protein processing in endoplasmic reticulum, oxidative phosphorylation and proteasome. The up-regulation of GO classification was involved in ATP metabolic process, oxidative phosphorylation, RNA catabolic process, and down-regulation of GO classification was response to corticosteroid, steroid hormone, and T cell activation.

CONCLUSION

Our results determined the characteristics and expression profile of endometrial lncRNAs and mRNAs in PCOS patients in pre-receptive phase, which is the day 3 after oocytes retrival. The possible pathways and related genes of endometrial receptivity disorders were found, and those lncRNAs may be developed as a predictive biomarker of endometrium in pre-receptive phase.

Proto-Oncogene FAM50A Can Regulate the Immune Microenvironment and Development of Hepatocellular Carcinoma In Vitro and In Vivo

Hepatocellular carcinoma (HCC) is a vital global health problem. The characteristics are high morbidity, high mortality, difficulty in early diagnosis and insensitivity to chemotherapy. The main therapeutic schemes for treating HCC mainly include Tyrosine kinase inhibitors represented by sorafenib and lenvatinib. In recent years, immunotherapy for HCC has also achieved certain results. However, a great number of patients failed to benefit from systemic therapies. FAM50A belongs to the FAM50 family and can be used as a DNA-binding protein or transcription factor. It may take part in the splicing of RNA precursors. In studies of cancer, FAM50A has been demonstrated to participate in the progression of myeloid breast cancer and chronic lymphocytic leukemia. However, the effect of FAM50A on HCC is still unknown. In this study, we have demonstrated the cancer-promoting effects and diagnostic value of FAM50A in HCC using multiple databases and surgical samples. We identified the role of FAM50A in the tumor immune microenvironment (TIME) and immunotherapy efficacy in HCC. We also proved the effects of FAM50A on the malignancy of HCC in vitro and in vivo. In conclusion, we confirmed that FAM50A is an important proto-oncogene in HCC. FAM50A acts as a diagnostic marker, immunomodulator and therapeutic target for HCC.

3D bio-printed endometrial construct restores the full-thickness morphology and fertility of injured uterine endometrium

Severe damage to the uterine endometrium, which results in scar formation and endometrial dysfunction, eventually leads to infertility or pregnancy-related complications. No effective therapeutic treatment is currently available for such injuries owing to the structural complexity, internal environment, and function of the uterus. Three-dimensional (3D) bio-printing to engineer biomimetic structural constructs provides a unique opportunity for tissue regeneration. Herein, using 3D extrusion-based bioprinting (EBB), we constructed a bilayer endometrial construct (EC) based on a sodium alginate-hyaluronic acid (Alg-HA) hydrogel for functional regeneration of the endometrium. The upper layer of the 3D bio-printed EC is a monolayer of endometrial epithelial cells (EECs), while the lower layer has a grid-like microstructure loaded with endometrial stromal cells (ESCs). In a partial full-thickness uterine excision rat model, our bilayer EC not only restored the morphology and structure of the endometrial wall (including organized luminal/ glandular epithelium, stroma, vasculature and the smooth muscle layer), but also significantly improved the reproductive outcome in the surgical area after implantation (75%, 12/16, p < 0.01). Therefore, repair of the uterine endometrium using the developed 3D bio-printed bilayer EC may represent an effective regenerative treatment for severe endometrial injury. STATEMENT OF SIGNIFICANCE: Achieving structural and functional recovery of the endometrium following severe injury is still a challenge. Here, we designed a 3D bio-printed endometrial construct (EC) to mimic the native bilayer structure and cellular components of the endometrium. The bio-printed EC consists of a dense upper layer with endometrial epithelial cells and a lower layer with endometrial stromal cells. In particular, the 3D bio-printed EC significantly improved the reproductive outcome in the surgical area (75%, 12/16) compared to that of the cell-loaded non-printed group (12.5%, 2/16). This study demonstrates that a biomimetic bilayer construct can facilitate endometrial repair and regeneration. Therefore, an endometrial cells-loaded 3D-bioprinted EC is a promising therapeutic option for patients suffering from severe endometrial damage.

Combined proteomics and transcriptomics identifies serpin family C member 1 associated protein as a biomarker of endometriosis

OBJECTIVE

To explore potential biomarkers indicating endometriosis (EM).

MATERIALS AND METHODS

A proteomics method and combined quantitative transcriptomics were adopted to highlight markers in the EM. Venn analysis was used to integrate the ribonucleic acid sequencing (RNA-seq) and protein profiles. Promising candidate markers were tested by enzyme-related immunosorbent assay.

RESULTS

A sum of 979 mRNAs and 39 proteins were tested to be significantly differentially expression in the standard cluster compared with the EM cluster. Venn analysis showed a filtered signature of only two down-regulated molecules in the EM group, i.e. fetuin B (FETUB) and serpin family C member 1 (SERPINC1); the latter showed a big variance between the control category and the EM set in the authentication test.

CONCLUSION

SERPINC1 may be a useful possible biomarker for the analysis of EM.

microRNAs and long non-coding RNAs as biomarkers for polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is known as the most common metabolic/endocrine disorder among women of reproductive age. Its complicated causality assessment and diagnostic emphasized the role of non‐coding regulatory RNAs as molecular biomarkers in studying, diagnosing and even as therapeutics of PCOS. This review discusses a comparative summary of research into microRNAs (miRNAs) and long non‐coding RNAs (lncRNAs) that are molecularly or statistically related to PCOS. We categorize the literature in terms of centering on either miRNAs or lncRNAs and discuss the combinatory studies and promising ideas as well. Additionally, we compare the pros and cons of the prominent research methodologies used for each of the abovementioned research themes and discuss how errors can be stopped from propagation by selecting correct methodologies for future research. Finally, it can be concluded that research into miRNAs and lncRNAs has the potential for identifying functional networks of regulation with multiple mRNAs (and hence, functional proteins). This new understanding may eventually afford clinicians to control the molecular course of the pathogenesis better. With further research, RNA (with statistical significance and present in the blood) may be used as biomarkers for the disease, and more possibilities for RNA therapy agents can be identified.

Long noncoding RNAs as a piece of polycystic ovary syndrome puzzle

Polycystic ovary syndrome (PCOS) is an endocrine disorder and affects 5-10% of reproductive-age women. Chronic anovulation, polycystic ovaries, and hyperandrogenism are the important features of this syndrome. Furthermore, hyperinsulinemia and central obesity are frequent in PCOS women. In recent years, noncoding RNAs detection provided new ideas to explain the etiology of female reproductive disorders. Long noncoding RNAs (lncRNAs) as a subset of noncoding RNAs are associated with the pathogenesis of manifold reproductive-related disorders. Various investigations emphasized the potential involvement of lncRNAs in PCOS development. Therefore, in this paper, we will summarize the function of numerous lncRNAs in the apoptosis and proliferation of granulosa cells (GCs), insulin resistance (IR), and steroidogenesis in PCOS.

Long non-coding RNAs: novel players in the pathogenesis of polycystic ovary syndrome

Long non-coding RNAs (lncRNAs) are a class of transcripts (>200 nucleotides) lacking protein-coding capacity. Based on the complex three-dimensional structure, lncRNAs are involved in many biological processes and can regulate the expression of target genes at chromatin modification, transcriptional and post-transcriptional levels. LncRNAs have been studied in multiple diseases but little is known about their role(s) in polycystic ovary syndrome (PCOS), the most common endocrinological disorder in reproductive-aged women around the world. In this review, we characterized and explored the potential mechanisms of lncRNAs in the pathogenesis of PCOS. We found that lncRNAs play a molecular role in PCOS mainly by functioning as the competitive endogenous RNA (ceRNA) and are significantly correlated with some clinical phenotypes. We summarized in detail regarding aberrant lncRNAs in different specimens of women with PCOS [i.e., granulosa cells (GCs), cumulus cells (CCs), follicular fluid (FF), peripheral blood] and various PCOS rodent models [i.e., dehydroepiandrosterone (DHEA) and letrozole induced models]. In clinical practice, detection of lncRNAs in serum might enable early diagnosis. Furthermore, new lncRNA-based classifications might be emerging as potent predictors of a particular phenotype in PCOS. Overall, we proposed new insights for the application of precision medicine approaches to the management of PCOS.

Analysis and Screening of Reproductive Long Non-coding RNAs Through Genome-Wide Analyses of Goat Endometrium During the Pre-attachment Phase

Reproduction in goat is highly impeded by implantation failure. Of concern, the underlying mechanism leading to embryo implantation remains unclear. In this study, deep sequencing was employed through strand-specific Ribo-Zero RNA-Seq to characterize transcriptome changes in the endometrium during the maternal recognition of pregnancy. A total of 996 differential transcripts (115 lncRNAs and 881 mRNAs) existing between the pregnant and non-pregnant endometrium were revealed through bioinformatics analysis. The screening was performed on lncRNAs (XR_001918173.1, LNC_002760, and LNC_000599) and LNC_009053, to determine their potential role in regulating the synthesis of retinol and endometrium remolding through the proteasome pathway, respectively. The hypothesis of whether certain lncRNAs, namely, LNC_007223, LNC_005256, and LNC_010092 could play important roles in embryo implantation was tested. These novel findings are of paramount relevance to further elucidate the molecular mechanisms of embryo implantation and uncover new targets to improve goat reproduction.

Specific trophoblast transcripts transferred by extracellular vesicles affect gene expression in endometrial epithelial cells and may have a role in embryo-maternal crosstalk

Background

Successful establishment of pregnancy hinges on appropriate communication between the embryo and the uterus prior to implantation, but the nature of this communication remains poorly understood. Here, we tested the hypothesis that the endometrium is receptive to embryo-derived signals in the form of RNA.

Methods

We have utilized a non-contact co culture system to simulate the conditions of pre implantation environment of the uterus. We bioorthogonally tagged embryonic RNA and tracked the transferred transcripts to endometrium. Transferred transcripts were separated from endometrial transcripts and sequenced. Changes in endometrial transcripts were quantified using quantitative PCR.

Results

We show that three specific transcripts are transferred to endometrial cells. We subsequently demonstrate a role of extracellular vesicles (EVs) in this process, as EVs obtained from cultured trophoblast spheroids incubated with endometrial cells induced down-regulation of all the three identified transcripts in endometrial cells.

Finally, we show that EVs/nanoparticles captured from conditioned culture media of viable embryos as opposed to degenerating embryos induce ZNF81 down-regulation in endometrial cells, hinting at the functional importance of this intercellular communication.

Conclusion

Ultimately, our findings demonstrate the existence of an RNA-based communication which may be of critical importance for the establishment of pregnancy.

Endometriosis-related ceRNA network to identify predictive biomarkers of endometrial receptivity

AIM

As RNA, which plays a role in the regulation of endometrial receptivity, can be modulated via ceRNA mechanisms, we constructed a ceRNA network to explore potential RNA/ceRNA biomarkers indicating endometrial receptivity associated with endometriosis.

MATERIALS & METHODS

RNA sequencing was performed on eutopic endometrium from eight patients with and without endometriosis. Bioinformatics algorithms were used to predict ceRNA network and pathway analysis.

RESULTS

We identified an endometriosis-associated ceRNA network involving 45 pathways and four ceRNAs as potential predictive biomarkers for endometrial receptivity. Patients with endometriosis presented lower levels of progesterone receptor type B expression.

CONCLUSION

Differentially expressed RNAs and lower progesterone receptors type B levels in endometriosis might be related to the impairment of endometrial receptivity.