Construction and analysis of a competing endogenous RNA network to reveal potential prognostic biomarkers for Oral Floor Squamous Cell Carcinoma.

BackgroundPatients diagnosed with Oral Floor Squamous Cell Carcinoma (OFSCC) face considerable challenges in physiology and psychology. This study explored prognostic signatures to predict prognosis in OFSCC through a detailed transcriptomic analysis.MethodWe built an interactive competing endogenous RNA (ceRNA) network that included lncRNAs, miRNAs and mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to predict the gene functions and regulatory pathways of mRNAs. Least absolute shrinkage and selection operator algorithm (LASSO) analysis and Cox regression analysis were used to screen prognosis factors. The Kaplan-Meier method was used to analyze the survival rate of prognosis factors. Risk score was used to assess the reliability of the prediction model.ResultsA specific ceRNA network consisting of 56 mRNAs, 16 miRNAs and 31 lncRNAs was established. Three key genes (HOXC13, TGFBR3, KLHL40) and 4 clinical factors (age, gender, TNM, and clinical stage) were identified and effectively predicted the for survival time. The expression of a gene signature was validated in two external validation cohorts. The signature (areas under the curve of 3 and 5 years were 0.977 and 0.982, respectively) showed high prognostic accuracy in the complete TCGA cohort.ConclusionsOur study successfully developed an extensive ceRNA network for OFSCC and further identified a 3-mRNA and 4-clinical-factor signature, which may serve as a biomarker

Table_1_Non-linear associations of cardiometabolic index with insulin resistance, impaired fasting glucose, and type 2 diabetes among US adults: a cross-sectional study.docx

BackgroundCardiometabolic index (CMI) is a novel indicator for predicting the risk of obesity-related diseases. We aimed to determine the relationships of CMI with insulin resistance (IR), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM) using NHANES data from 1999 to 2020.MethodsAfter CMI values were estimated, weighted univariate and multivariate logistic regression analyses were used to ascertain whether CMI was an independent risk indicator for IR, IFG, and T2DM. Furthermore, stratified analyses and interaction analyses were carried out to investigate the heterogeneity of correlations across various subgroups. Subsequently, restricted cubic splines (RCS) were used to examine nonlinear relationships.Results21,304 US adults were enrolled in our study, of whom 5,326 (22.38%) had IR, 4,706 (20.17%) had IFG, and 3,724 (13.02%) had T2DM. In the studied population, a higher CMI index value was significantly associated with an elevated likelihood of IR, IFG, and T2DM. In the RCS regression model, the relationship between CMI and IR, IFG, and T2DM was identified as nonlinear. A nonlinear inverted U-shaped relationship was found between CMI and IFG, and an inverse L-shaped association was observed between CMI and IR, CMI and T2DM. The cut-off values of CMI were 1.35, 1.48, and 1.30 for IR, IFG, and T2DM, respectively.ConclusionOur results indicate that CMI was positively correlated with an increase in IR, IFG, and T2DM in the studied population. CMI may be a simple and effective surrogate indicator of IR, IFG, and T2DM.</p

Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library

High‐grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5‐year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced‐stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high‐quality ovary‐specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan‐human spectral library (DPHL), this spectral library provides 10% more ovary‐specific and 3% more ovary‐enriched proteins. This library was then applied to analyze data‐independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six‐protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log‐rank test, P = 0.002). The classifier was validated with 57 patients from an independent clinical center (P = 0.014). Thus, we have developed an ovary‐specific spectral library for targeted proteome analysis, and propose a six‐protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT‐IDS treatment

Chrysophanol Alleviates Metabolic Syndrome by Activating the SIRT6/AMPK Signaling Pathway in Brown Adipocytes

Chrysophanol, a primary active ingredient of Cassia mimosoides Linn or Rhei radix et rhizoma, has various pharmacological properties, including anticancer, antidiabetic, and anti-inflammatory, as well as blood lipid regulation. However, whether chrysophanol can mitigate obesity, and its underlying mechanisms remains unclear. This study investigated whether chrysophanol effects energy metabolism in high-fat diet- (HFD-) induced obese mice and fat-specific Sirtuin 6- (SIRT6-) knockout (FKO) mice, targeting the SIRT6/AMPK signaling pathway in brown and white fat tissue. Our results showed that chrysophanol can effectively inhibit lipid accumulation in vitro and reduce mice’s body weight, improve insulin sensitivity and reduced fat content of mice, and induce energy consumption in HFD-induced obese mice by activating the SIRT6/AMPK pathway. However, a treatment with OSS-128167, an SIRT6 inhibitor, or si-SIRT6, SIRT6 target specific small interfering RNA, in vitro blocked chrysophanol inhibition of lipid accumulation. Similar results were obtained when blocking the AMPK pathway. Moreover, in the HFD-induced obese model with SIRT6 FKO mice, histological analysis and genetic test results showed that chrysophanol treatment did not reduce lipid droplets and upregulated the uncoupling protein 1 (UCP1) expression. Rather, it upregulated the expression of thermogenic genes and activated white fat breakdown by inducing phosphorylation of adenosine 5′-monophosphate- (AMP-) activated protein kinase (AMPK), both in vitro and in vivo. OSS-128167 or si-SIRT6 blocked chrysophanol’s upregulation of peroxisome proliferator-activated receptor-γ coactivator-1α (Pgc-1α) and Ucp1 expression. In conclusion, this study demonstrated that chrysophanol can activate brown fat through the SIRT6/AMPK pathway and increase energy consumption, insulin sensitivity, and heat production, thereby alleviating obesity and metabolic disorders