scholarly journals Identification and Analysis of Potential Autophagy-Related Biomarkers in Endometriosis by WGCNA

2021 ◽  
Vol 8 ◽  
Author(s):  
Jing Wang ◽  
Shanshan Cong ◽  
Han Wu ◽  
Yanan He ◽  
Xiaoli Liu ◽  
...  

Background: Endometriosis is a serious gynecological disorder characterized by debilitating pain, infertility and the establishment of innervated endometriosis lesions outside the uterus. Early detection and accurate diagnosis are pivotal in endometriosis. The work screened autophagy-related genes (ATGs) as potential biomarkers to reveal new molecular subgroups for the early diagnosis of endometriosis.Materials and Methods: The gene lists of ATGs from five databases were integrated. Then, weighted gene co-expression network analysis (WGCNA) was used to map the genes to the gene profile of endometriosis samples in GSE51981 to obtain functional modules. GO and KEGG analyses were performed on the ATGs from the key modules. Differentially expressed ATGs were identified by the limma R package and further validated in the external datasets of GSE7305 and GSE135485. The DESeq2 R package was utilized to establish multifactorial network. Subsequently, one-way analysis of variance (ANOVA) was performed to identify new molecular subgroups. Real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting were used to confirm the differential expression of hub ATGs, and the receiver operating characteristic (ROC) curve analysis and Spearman correlation analysis were applied to assess the diagnostic value of hub ATGs in 40 clinical samples and human primary endometrial stromal cells (ESCs).Results: We screened 4 key modules and 12 hub ATGs and found the key genes to be strongly correlated with endometriosis. The pathways of ATGs were mainly enriched in autophagy, apoptosis, ubiquitin-protein ligase binding, and MAPK signaling pathway. The expression levels of EZH2 (Enhancer of Zeste homolog 2) and RND3 (also known as RhoE) had statistically significant changes with higher values in the endometriosis group compared with the controls, both in the tissue samples and primary ESCs. Besides, they also showed higher specificity and sensitivity by the receiver operating characteristic analysis and Spearman correlation analysis for the diagnosis of endometriosis. The TF-mRNA-miRNA-lncRNA multifactorial network was successfully constructed. Four new molecular subgroups were identified, and we preliminarily showed the ability of IQCG to independently differentiate subgroups.Conclusion: EZH2 and RND3 could be candidate biomarkers for endometriosis, which would contribute to the early diagnosis and intervention in endometriosis.

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S277-S277
Author(s):  
Katherine C Jankousky ◽  
Peter Hyson ◽  
Jin Huang ◽  
Daniel B Chastain ◽  
Carlos Franco-Paredes ◽  
...  

Abstract Background Accurate, rapid, inexpensive biomarkers are needed to differentiate COVID-19 from bacterial pneumonia, allowing effective treatment and antibiotic stewardship. We hypothesized that the ratio of ferritin to procalcitonin (F/P) reflects greater viral activity and host response with COVID-19 pneumonia, while bacterial pneumonia would be associated with less cytolysis (lower ferritin) and more inflammation (higher procalcitonin), thus a lower F/P ratio. Methods We conducted a retrospective study of adult patients admitted to a single University hospital in the US through May 2020, during the COVID-19 pandemic. We compared F/P ratio of patients diagnosed with COVID-19 or bacterial pneumonia, excluding patients with COVID-19 and bacterial co-infections. In a logistic regression, we controlled for age, sex, body mass index (BMI), diabetes (DM), and hypertension (HTN). We used a receiver operating characteristic analysis to calculate the sensitivity and specificity of F/P values for the diagnosis of COVID-19 versus bacterial pneumonia. Results Of 218 patients with COVID-19 and 17 with bacterial pneumonia, COVID-19 patients were younger (56 vs 66 years, p=0.04), male (66% vs 24%, p=0.009), had higher BMI (31 vs 27 kg/m2, p=0.03), and similar rates of HTN (59% vs 45%, p=0.3) and DM (32% vs 18%, p=0.2). The median F/P ratio was significantly higher in patients with COVID-19 (3195 vs 860, p=0.0003, Figure 1). An F/P ratio cut-off of ≥ 1250 generated a sensitivity of 78% and a specificity of 59% to correctly classify a COVID-19 case (Figure 2). When adjusted for age, gender, BMI, DM, and HTN, a ratio ≥ of 1250 was associated with significantly greater odds of COVID-19 versus bacterial pneumonia (OR: 4.9, CI: 1.5, 16.1, p=0.009). Figure 1. Ferritin to Procalcitonin Ratios of patients with COVID-19 and patients with Bacterial Pneumonia (controls). Figure 2. Receiver Operating Characteristic Analysis of Ferritin to Procalcitonin Ratio Cut-off Values Predicting COVID-19 Diagnosis. Conclusion We observed an elevated F/P ratio in patients with COVID-19 compared to those with bacterial pneumonia. A F/P ratio ≥ 1250 provides a clinically relevant increase in pre-test probability of COVID-19. Prospective studies evaluating the discriminatory characteristics of F/P ratio in larger cohorts is warranted. Disclosures All Authors: No reported disclosures


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jing Zhao ◽  
Bernd Hamm ◽  
Winfried Brenner ◽  
Marcus R. Makowski

Abstract Purpose This study aimed to calculate an applicable relative ratio threshold value instead of the absolute threshold value for simultaneous 68Ga prostate-specific membrane antigen/positron emission tomography ([68Ga]Ga-PSMA-11 PET) in patients with prostate cancer (PCa). Materials and methods Our study evaluated thirty-two patients and 170 focal prostate lesions. Lesions are classified into groups according to Prostate Imaging Reporting and Data System (PI-RADS). Standardized uptake values maximum (SUVmax), corresponding lesion-to-background ratios (LBRs) of SUVmax, and LBR distributions of each group were measured based on regions of interest (ROI). We examined LBR with receiver operating characteristic analysis to determine threshold values for differentiation between multiparametric magnetic resonance imaging (mpMRI)-positive and mpMRI-negative lesions. Results We analyzed a total of 170 focal prostate lesions. Lesions number of PI-RADS 2 to 5 was 70, 16, 46, and 38. LBR of SUVmax of each PI-RADS scores was 1.5 (0.9, 2.4), 2.5 (1.6, 3.4), 3.7 (2.6, 4.8), and 6.7 (3.5, 12.7). Based on an optimal threshold ratio of 2.5 to be exceeded, lesions could be classified into MRI-positive lesion on [68Ga]Ga-PSMA PET with a sensitivity of 85.2%, a specificity of 72.0%, with the corresponding area under the receiver operating characteristic curve (AUC) of 0.83, p < 0.001. This value matches the imaging findings better. Conclusion The ratio threshold value of SUVmax, LBR, has improved clinical and research applicability compared with the absolute value of SUVmax. A higher threshold value than the background’s uptake can dovetail the imaging findings on MRI better. It reduces the bias from using absolute background uptake value as the threshold value.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bianca M. Leca ◽  
Maria Mytilinaiou ◽  
Marina Tsoli ◽  
Andreea Epure ◽  
Simon J. B. Aylwin ◽  
...  

AbstractProlactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.


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