Purpose This study aimed to explore the expression profiles of circRNA in granulosa cells of women of reproductive age with polycystic ovary syndrome (PCOS). Methods Total RNA was isolated from granulosa cells of 15 women with PCOS and 15 body mass index- and age-matched healthy women (control). RNA sequencing was conducted on ribosomal-depleted RNA for circRNA expression profiling. The differential expression of circRNA between women with PCOS and controls was compared and visualized using hierarchical clustering heat maps and Volcano plots. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed to determine the role of the differential expression of circRNAs. The expression rates of circRNAs were confirmed using quantitative real-time PCR (qRT-PCR) using divergent primers. Results A total of 4258 and 7395 candidate circRNAs were predicted in PCOS and controls, respectively, based on the RNA-sequencing data. Differences were noted in the expression patterns of circRNA between the two groups. Analysis of the expression profiles revealed that four circRNAs were upregulated, whereas 23 were downregulated in the women with PCOS. GO analysis suggested that the 27 differentially expressed circRNAs were mainly distributed in biological process pathways, particularly in pathways involving inflammation, proliferation, and the vascular endothelial growth factor-related signaling pathway. Six circRNAs were identified in PCOS-affected women using divergent primers. qRT-PCR confirmed that hsa_circ_0001577 was significantly upregulated and hsa_circ_0020093 was downregulated in the women with PCOS. Conclusions Several circRNAs were differentially expressed in women of reproductive age with PCOS, suggesting the involvement of these circRNAs in the development of PCOS and the potential clinical implications of their use as PCOS biomarkers. Electronic supplementary material The online version of this article (10.1007/s00404-019-05129-5) contains supplementary material, which is available to authorized users.
STUDY QUESTION Does acupuncture improve insulin sensitivity more effectively than metformin or sham acupuncture in women with polycystic ovary syndrome (PCOS) and insulin resistance (IR)? SUMMARY ANSWER Among women with PCOS and IR, acupuncture was not more effective than metformin or sham acupuncture in improving insulin sensitivity. WHAT IS KNOWN ALREADY Uncontrolled trials have shown that acupuncture improved insulin sensitivity with fewer side effects compared with metformin in women with PCOS and IR. However, data from randomized trials between acupuncture and metformin or sham acupuncture are lacking. STUDY DESIGN, SIZE, DURATION This was a three-armed randomized controlled trial enrolling a total of 342 women with PCOS and IR from three hospitals between November 2015 and February 2018, with a 3-month follow-up until October 2018. PARTICIPANTS/MATERIALS, SETTING, METHODS Women aged from 18 to 40 years with PCOS and homeostasis model assessment of insulin resistance (HOMA-IR) ≥2.14 were randomly assigned (n = 114 per group) to receive true acupuncture plus placebo (true acupuncture), metformin plus sham acupuncture (metformin, 0.5 g three times daily) or sham acupuncture plus placebo (sham acupuncture) for 4 months, with an additional 3-month follow-up. True or sham acupuncture was given three times per week, and 0.5 g metformin or placebo was given three times daily. The primary outcome was change in HOMA-IR from baseline to 4 months after baseline visit. Secondary outcomes included changes in the glucose AUC during an oral glucose tolerance test, BMI and side effects at 4 months after baseline visit. MAIN RESULTS AND THE ROLE OF CHANCE After 4 months of treatment, the changes of HOMA-IR were –0.5 (decreased 14.7%) in the true acupuncture group, –1.0 (decreased 25.0%) in the metformin group and –0.3 (decreased 8.6%) in the sham acupuncture group, when compared with baseline. True acupuncture is not as effective as metformin in improving HOMA-IR at 4 months after baseline visit (difference, 0.6; 95% CI, 0.1–1.1). No significant difference was found in change in HOMA-IR between true and sham acupuncture groups at 4 months after baseline visit (difference, –0.2; 95% CI, –0.7 to 0.3). During the 4 months of treatment, gastrointestinal side effects were more frequent in the metformin group, including diarrhea, nausea, loss of appetite, fatigue, vomiting and stomach discomfort (31.6%, 13.2%, 11.4%, 8.8%, 14.0% and 8.8%, respectively). Bruising was more common in the true acupuncture group (14.9%). LIMITATIONS, REASONS FOR CAUTION This study might have underestimated the sample size in the true acupuncture group with 4 months of treatment to enable detection of statistically significant changes in HOMA-IR with fixed acupuncture (i.e. a non-personalized protocol). Participants who withdrew because of pregnancy did not have further blood tests and this can introduce bias. WIDER IMPLICATIONS OF THE FINDINGS True acupuncture did not improve insulin sensitivity as effectively as metformin in women with PCOS and IR, but it is better than metformin in improving glucose metabolism (which might reduce the risk of type 2 diabetes) and has less side effects. Metformin had a higher incidence of gastrointestinal adverse effects than acupuncture groups, and thus acupuncture might be a non-pharmacological treatment with low risk for women with PCOS. Further studies are needed to evaluate the effect of acupuncture combined with metformin on insulin sensitivity in these women. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by grants 2017A020213004 and 2014A020221060 from the Science and Technology Planning Project of Guangdong Province. The authors have no conflicts of interest. TRIAL REGISTRATION NUMBER Clinicaltrials.gov number: NCT02491333. TRIAL REGISTRATION DATE 8 July 2015. DATE OF FIRST PATIENT’S ENROLLMENT 11 November 2015.
Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3-and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3-and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.
Background: Traditional Chinese medicine (TCM) usually involves syndrome differentiation and treatment. Acupuncture, one form of TCM, requires the selection of appropriate acupoints and needling techniques, but many clinical trials on acupuncture have used fixed acupuncture protocols without accounting for individual patient differences. We have designed a multicenter randomized controlled trial (RCT) to evaluate whether personalized or fixed acupuncture increases the likelihood of live births in infertile women with polycystic ovary syndrome (PCOS) compared with letrozole or placebo letrozole. We hypothesize that letrozole is more effective than personalized acupuncture, which in turn is more effective than fixed acupuncture, and that placebo letrozole is the least effective intervention. Moreover, we hypothesize that personalized acupuncture is more likely to reduce the miscarriage rate and the risk of pregnancy complications compared with letrozole. Methods/design: The study is designed as an assessor-blinded RCT. A total of 1100 infertile women with PCOS will be recruited from 28 hospitals and randomly allocated to 4 groups: personalized acupuncture, fixed acupuncture, letrozole, or placebo letrozole. They will receive treatment for 16 weeks, and the primary outcome is live birth. Secondary outcomes include ovulation rate, conception rate, pregnancy rate, pregnancy loss rate, changes in hormonal and metabolic parameters, and changes in quality of life scores. Adverse events will be recorded throughout the trial. All statistical analyses will be performed using IBM SPSS Statistics version 21.0 software (IBM Corp., Armonk, NY, USA), and a P value < 0.05 will be considered statistically significant.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.