Alternative splicing events have been increasingly reported for anomalous perturbations in various cancers, including papillary thyroid cancer (PTC).

Increased glycolysis has been reported as a major metabolic hallmark in many cancers, and is closely related to malignant behavior of tumors. However, the potential mechanism of glycolysis in hepatocellular carcinoma (HCC) and its prognostic value are not well understood. To address this, we investigated glycolysis-related gene expression data of patients with HCC from TCGA and ICGC. Patients were categorized into three different glycolysis-associated subgroups: Glycolysis-M, Glycolysis-H, and Glycolysis-L. We found that Glycolysis-H combined with Glycolysis-M (Glycolysis-H+M) subgroup was associated with poor overall survival and distinct cancer stem cell characteristics and immune infiltrate patterns. Additionally, multiomics-based analyses were conducted to evaluate genomic patterns of glycolysis subgroups, including their gene mutations, copy number variations, and RNA-sequencing data. Finally, a glycolysis-associated multiomics prognostic model (GMPM) consisting of 19 glycolysis-associated genes was developed. The capability of GMPM in categorizing patients with HCC into high- and low-risk groups was validated with independent HCC datasets. Finally, GMPM was confirmed as an independent risk factor for the prognosis of patients with HCC. We believe that our findings provide new insights into the mechanism of glycolysis and highlight the potential clinical value of GMPM in predicting the prognosis of patients with HCC.

To explore the effects of miR-141-3p on intestinal epithelial cells in necrotizing enterocolitis and the underlying mechanism.

Postoperative cognitive dysfunction (POCD) is frequently observed in elderly patients following anesthesia, but its pathophysiological mechanisms have not been fully elucidated. Sevoflurane was reported to repress autophagy in aged rat neurons; however, the role of mitophagy, which is crucial for the control of mitochondrial quality and neuronal health, in sevoflurane-induced POCD in aged rats remains undetermined. Therefore, this study investigated whether mitophagy impairment is involved in sevoflurane-induced cognitive dysfunction. We found sevoflurane treatment inhibited mitochondrial respiration and mitophagic flux, changes in mitochondria morphology, impaired lysosomal acidification, and increased Tomm20 and deceased LAMP1 accumulation were observed in H4 cell and aged rat models. Rapamycin counteracted ROS induced by sevoflurane, restored mitophagy and improved mitochondrial function. Furthermore, rapamycin ameliorated the cognitive deficits observed in aged rats given sevoflurane anesthesia as determined by the Morris water maze test; this improvement was associated with an increased number of dendritic spines and pyramidal neurons. Overexpression of PARK2, but not mutant PARK2 lacking enzyme activity, in H4 cells decreased ROS and Tomm20 accumulation and reversed mitophagy dysfunction after sevoflurane treatment. These findings suggest that mitophagy dysfunction could be a mechanism underlying sevoflurane-induced POCD and that activating mitophagy may provide a new strategy to rescue cognitive deficits.

This study aimed to investigate the effects of micro ribonucleic acid (miR)-338-3p on the migration, invasion and proliferation of lung adenocarcinoma (LUAD) cells.

Cholangiocarcinoma (CCA) is a fatal disease with dismal survival rates. Long non-coding RNA (lncRNA) expression profiling as potential prognostic biomarkers play critical roles in tumor initiation, development, and poor prognosis. Identifying specific lncRNA to predict the prognosis of CCA patients in the early stages is very important for improving a patient's survival. In the current study, we aimed to establish a novel risk-stratification lncRNA signature panel in CCA. The initial lncRNA discovery was identified in The Cancer Genome Atlas database (TCGA cohort). The Cox regression analysis was used to establish the lncRNA prognostic model and the receiver operating characteristic (ROC) curve analysis was performed to assess the specificity and sensitivity of the model. This was followed by independent validation of the lncRNA signature in the CCA patients from the First Affiliated Hospital of Wenzhou Medical University (WMU cohort). Furthermore, by using the Gene Ontology function and Kyoto Encyclopedia Gene and Genome pathway enrichment analysis, we explored the potential function of prognosis lncRNA. Finally, five lncRNA (HULC; AL359715.5; AC006504.8; AC090114.2; AP00943.4) were screened to establish the predictive model that significantly associated with poor overall survival(HR:4.879;95%CI,1.587-14.996;p=0.006). This five-lncRNA signature model showed excellent accuracy in the TCGA cohort (AUC=0.938), and also robustly predicted survival in the validation WMU cohort(AUC=0.816). Functional enrichment analysis suggested prognostic lncRNA was primarily associated with CCA-related biological processes. Our data established a novel lncRNA signature model for CCA risk-stratification and robust identification of CCA patients with poor molecular genotypes. Moreover, it revealed new molecular mechanisms of CCA.

Skeletal muscle is capable of repairing itself after injury to maintain the stability of its own tissue, but this ability declines with aging. Circular RNAs (circRNAs) are involved in cell aging. However, there is little research into their role and underlying mechanisms, especially in skeletal muscle stem cells (SkMSCs). In this study, we assessed circRNA FUT10 expression in aged and adult SkMSCs. We observed that circRNA FUT10 was upregulated in aged SkMSCs compared with that in adult SkMSCs. Furthermore, we identified putative miR-365-3p binding sites on circRNA FUT10, suggesting that this circRNA sponges miR-365a-3p. We also found that HOXA9 is a downstream target of miR-365a-3p and confirmed that miR-365a-3p can bind to circRNA FUT10 and the 3'-untranslated region of HOXA9 mRNA. This finding indicated that miR-365a-3p might serve as a "bridge" between circRNA FUT10 and HOXA9. Finally, we found that the circRNA FUT10/miR365a-3p/HOXA9 axis is involved in SkMSC aging. Collectively, our results show that the circRNA FUT10/miR365a-3p/HOXA9 axis is a promising therapeutic target and are expected to facilitate the development of therapeutic strategies to improve the prognosis of degenerative muscle disease.

Circular RNAs (circRNAs) have recently been shown to exert effects on multiple pathological processes by acting as miRNA sponges. However, the roles of circRNAs in ovarian senescence are largely unknown. The objective of this study was to identify the circRNAs involved in ovarian aging and predict their potential biological functions. We first performed RNA-sequencing to generate ovarian circRNA expression profiles from young (n = 3) and aging (n = 3) groups. In total, 48,220 circRNAs were identified, of which 194 circRNAs were significantly up-regulated and 207 circRNAs were down-regulated during aging (fold change > 2, P < 0.05). Bioinformatics analysis demonstrated that the metabolic process, regulated secretory pathway, oxidation-reduction process, steroid hormone biosynthesis, and insulin secretion pathways, which may be associated with ovarian aging, were significantly enriched (P < 0.05). The biological characteristics of ovary-derived circRNA, such as back-splicing, RNase R resistance, stability, and alternative splicing, were further validated. Bioinformatics predicted that most of the circRNAs harboured miRNA binding sites, of which circDDX10-miR-1301-3p/miR-4660-SIRT3 axis may be involved in the regulation of ovarian function. Our study indicates that circRNAs are aberrantly expressed in the aging ovary and may play potential roles in the development of ovarian senescence.

Chemotherapy-induced ovarian aging not only increases the risk for early menopause-related complications but also results in infertility in young female cancer survivors. Oogonial stem cells have the ability to generate new oocytes and thus provide new opportunities for treating ovarian aging and female infertility. Resveratrol (3,5,4'-trihydroxy-trans-stilbene) is a natural phenol derived from plants, that has been shown to have positive effects on longevity and redox flow in lipid metabolism and a preventive function against certain tumors. To evaluate whether resveratrol could promote the repair of oogonial stem cells damage in a busulfan/cyclophosphamide (Bu/Cy)-induced accelerated ovarian aging model, female mice were administered 30 and 100 mg/kg/d resveratrol through a gavage for 2 weeks. We demonstrated that resveratrol (30 mg/kg/d) relieved oogonial stem cells loss and showed an attenuating effect on Bu/Cy-induced oxidative apoptosis in mouse ovaries, which may be attributed to the attenuation of oxidative levels in ovaries. Additionally, we also showed that Res exerted a dose-dependent effect on oogonial stem cells and attenuated H2O2-induced cytotoxicity and oxidative stress injury by activating Nrf2 in vitro. Therefore, resveratrol could be of a potential therapeutic drug used to prevent chemotherapy-induced ovarian aging.

Alternative splicing (AS) is crucial a mechanism by which the complexity of mammalian and viral proteom increased overwhelmingly. There lacks systematic and comprehensive analysis of the prognostic significance of AS profiling landscape for uteri corpus endometrial carcinoma (UCEC). In this study, univariate and multivariate Cox regression analyses were conducted to identify candidate survival-associated AS events curated from SpliceSeq for the construction of prognostic index (PI) models. A correlation network between splicing factor-related AS events and significant survival-associated AS events were constructed using Cytoscape 3.5. As consequence, 28281 AS events from 8137 genes were detected from 506 UCEC patients, including 2630 survival-associated AS events. Kaplan Meier survival analysis revealed that six of the seven PI models (AD, AP, AT, ME, RI and ALL) exhibited good performance in stratifying the prognosis of low risk and high risk group (P<0.05). Among the six PI models, PI-AT performed best with an area under curves (AUC) value of 0.758 from time-dependent receiver operating characteristic. Correlation network implicated potential regulatory mechanism of AS events in UCEC. PI models based on survival-associated AS events for UCEC in this study showed preferable prognosis-predicting ability and may be promising prognostic indicators for UCEC patients.Summary: This is the first study to systematically investigate the prognostic value of AS in UCEC. Findings in the presents study supported the clinical potential of AS for UCEC and shed light on the potential AS-associated molecular basis of UCEC.

The purposes of this study are to investigate whether the Characterizing Alzheimer's disease Risk Events (CARE) index can accurately predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) on an individual subject basis, and to investigate whether this model can be generalized to an independent cohort. Using an event-based probabilistic model approach to integrate widely available biomarkers from behavioral data and brain structural and functional imaging, we calculated the CARE index. We then applied the CARE index to identify which MCI individuals from the ADNI dataset progressed to AD during a three-year follow-up period. Subsequently, the CARE index was generalized to the prediction of MCI individuals from an independent Nanjing Aging and Dementia Study (NADS) dataset during the same time period. The CARE index achieved high prediction performance with 80.4% accuracy, 75% sensitivity, 82% specificity, and 0.809 area under the receiver operating characteristic (ROC) curve (AUC) on MCI subjects from the ADNI dataset over three years, and a highly validated prediction performance with 87.5% accuracy, 81% sensitivity, 90% specificity, and 0.861 AUC on MCI subjects from the NADS dataset. In conclusion, the CARE index is highly accurate, sufficiently robust, and generalized for predicting which MCI individuals will develop AD over a three-year period. This suggests that the CARE index can be usefully applied to select individuals with MCI for clinical trials and to identify which individuals will convert from MCI to AD for administration of early disease-modifying treatment.

With the rising number of COVID-19 cases, global health resources are strained by the pandemic. No proven effective therapies or vaccines for this virus are currently available. In order to maximize the use of limited medical resources, distinguishing between mild and severe patients as early as possible has become pivotal.

Inadequate endometrial receptivity contributes to recurrent implantation failure (RIF) during IVF-embryo transfer. Though multiple circRNAs have been confirmed differentially expression in RIF, the potential function of novel circRNAs needed to be detected.

Long noncoding RNAs (lncRNAs) promote invasion and migration by glioblastoma (GBM) cells. In this study, quantitative real-time polymerase chain reaction was used to detect expression levels of the lncRNA HOTAIRM1 in GBM tissue samples and cells. The function of HOTAIRM1 was examined using wound healing assays, transwell assays, and in vivo experiments after GBM cells were transfected with either sh-ctrl or sh-HOTAIRM1. Luciferase reporter assays and RIP assays were performed to determine the interactions between HOTAIRM1 and miR-153-5p and between miR-153-5p and SNAI2. We also used luciferase reporter assays and ChIP assays to assess the transcriptional regulation of HOTAIRM1 by SNAI2 and CDH1. HOTAIRM1 was significantly overexpressed in GBM tissues and cells. HOTAIRM1 knockdown significantly weakened the migration and invasion by GBM cells. HOTAIRM1 was found to sponge miR-153-5p, and SNAI2 is a direct target of miR-153-5p. In addition, SNAI2 was shown to force HOTAIRM1 expression through directly promoting transcription and suppressing the negative regulation of CDH1 on transcription. Our results indicate a positive feedback loop between HOTAIRM1 and SNAI2, and suggest that the lncRNA HOTAIRM1 is a potential biomarker and therapeutic target in GBM.

Vulvovaginal atrophy (VVA) is a common menopause-related symptom affecting more than 50% of midlife and older women and cancer patients whose ovarian function are lost or damaged. Regardless of estrogen deficiency, whether other factors such as the gut microbiota play role in VVA have not been thoroughly investigated. To this end, we performed ovariectomy on 12-weeks' old mice and follow-up at 4 weeks after ovariectomy, and observed atrophied vagina and an altered gut microbiota in ovariectomized mice.. We further performed fecal microbiota transplantation with feces from another cohort of ovary-intact fecund female mice to the ovariectomized ones, and found that the vaginal epithelial atrophy was significantly alleviated as well as the gut microbiota was pointedly changed. All these results suggest that ovarian activity has some influence on the gut microbiota, and the latter from the ovary-intact female mice can somehow make the vagina of mice deficient in ovarian function healthier maybe by up-expressing ESR1 in vaginal cells and enhancing regeneration in vagina. This kind of association between gut microbiota and vaginal health need further exploration such that it may provide an alternative treatment by modulating gut microbiota in patients suffering from VVA but may be reluctant to hormone therapy.

Predicting the prognosis of hepatocellular carcinoma (HCC) is a major medical challenge and of guiding significance for treatment. This study explored the actual relevance of RNA expression in predicting HCC prognosis. Cox's multiple regression was used to establish a risk score staging classification and to predict the HCC patients' prognosis on the basis of data in the Cancer Genome Atlas (TCGA). We screened seven gene biomarkers related to the prognosis of HCC from the perspective of oxidative stress, including Alpha-Enolase 1(ENO1), N-myc downstream-regulated gene 1 (NDRG1), nucleophosmin (NPM1), metallothionein-3, H2A histone family member X, Thioredoxin reductase 1 (TXNRD1) and interleukin 33 (IL-33). Among them we measured the expression of ENO1, NGDP1, NPM1, TXNRD1 and IL-33 to investigate the reliability of the multi-index prediction. The first four markers' expressions increased successively in the paracellular tissues, the hepatocellular carcinoma samples (from patients with better prognosis) and the hepatocellular carcinoma samples (from patients with poor prognosis), while IL-33 showed the opposite trend. The seven genes increased the sensitivity and specificity of the predictive model, resulting in a significant increase in overall confidence. Compared with the patients with higher-risk scores, the survival rates with lower-risk scores are significantly increased. Risk score is more accurate in predicting the prognosis HCC patients than other clinical factors. In conclusion, we use the Cox regression model to identify seven oxidative stress-related genes, investigate the reliability of the multi-index prediction, and develop a risk staging model for predicting the prognosis of HCC patients and guiding precise treatment strategy.

Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study.

The pathogenic mechanisms of prostate cancer (PCa) remain to be defined. In this study, we utilized the Robust Rank Aggregation (RRA) method to integrate 10 eligible PCa microarray datasets from the GEO and identified a set of significant differentially expressed genes (DEGs) between tumor samples and normal, matched specimens. To explore potential associations between gene sets and PCa clinical features and to identify hub genes, we utilized WGCNA to construct gene co-expression networks incorporating the DEGs screened with the use of RRA. From the key module, we selected LMNB1, TK1, ZWINT, and RACGAP1 for validation. We found that these genes were up-regulated in PCa samples, and higher expression levels were associated with higher Gleason scores and tumor grades. Moreover, ROC and K-M plots indicated these genes had good diagnostic and prognostic value for PCa. On the other hand, methylation analyses suggested that the abnormal up-regulation of these four genes likely resulted from hypomethylation, while GSEA and GSVA for single hub gene revealed they all had a close association with proliferation of PCa cells. These findings provide new insight into PCa pathogenesis, and identify LMNB1, TK1, RACGAP1 and ZWINT as candidate biomarkers for diagnosis and prognosis of PCa.

Dysregulation of α(1,6)-fucosyltransferase (FUT8) plays significant roles in development of a variety of malignant tumor types. We collected as many relevant articles and microarray datasets as possible to assess the prognostic value of FUT8 expression in malignant tumors. For this purpose, we systematically searched PubMed, Embase, Web of Science, Springer, Chinese National Knowledge Infrastructure (CNKI), and Wan Fang, and eventually identified 7 articles and 35 microarray datasets (involving 6124 patients and 10 tumor types) for inclusion in meta-analysis. In each tumor type, FUT8 expression showed significant (p< 0.05) correlation with one or more clinicopathological parameters; these included patient gender, molecular subgroup, histological grade, TNM stage, estrogen receptor, progesterone receptor, and recurrence status. In regard to survival prognosis, FUT8 expression level was associated with overall survival in non-small cell lung cancer (NSCLC), breast cancer, diffuse large B cell lymphoma, gastric cancer, and glioma. FUT8 expression was also correlated with disease-free survival in NSCLC, breast cancer, and colorectal cancer, and with relapse-free survival in pancreatic ductal adenocarcinoma. For most tumor types, survival prognosis of patients with high FUT8 expression was related primarily to clinical features such as gender, tumor stage, age, and pathological category. Our systematic review and meta-analysis confirmed the association of FUT8 with clinicopathological features and patient survival rates for numerous malignant tumor types. Verification of prognostic value of FUT8 in these tumor types will require a large-scale study using standardized methods of detection and analysis.

The aim of this study was to determine the effect of HDAC6 inhibition using the selective inhibitor Tubastatin A (TubA) on the regulation of tert-butyl hydroperoxide (TBHP)-treated chondrocytes and a mouse OA model. Using conventional molecular biology methods, our results showed that the level of HDAC6 increases both in the cartilage of osteoarthritis (OA) mice and TBHP-treated chondrocytes in vitro. TubA treatment effectively inhibits the expression of HDAC6, attenuates oxidative stress, reduces the level of apoptotic proteins to maintain chondrocyte survival, and suppresses the extracellular matrix (ECM) degradation. In addition, our results also revealed that HDAC6 inhibition by TubA activates autophagy in chondrocytes, whereas the protective effects of TubA were abolished by autophagy inhibitor intervention. Subsequently, the positive effects of HDAC6 inhibition by TubA were also found in a mouse OA model. Therefore, our study provide evidence that HDAC6 inhibition prevents OA development, and HDAC6 could be applied as a potential therapeutic target for OA management.