Expression Levels Of Biomarkers Research Articles

Abstract 822: A retrospective study on the disparities of hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults and the third leading cause of cancer-related deaths worldwide. Studies report that the incidence of, and mortality from HCC vary significantly by age, sex, and race/ethnicity; however, disparities in the expression level of tumor biomarkers, liver functions, lipid profiles, and comorbidities have not been thoroughly investigated among subpopulations of patient with HCC. Methods: A retrospective study was conducted to review 247 serial HCC cases enrolled in the University of Mississippi Medical Center during June 2000 to May 2023. The entire HCC population was stratified into subpopulations by race, gender, age and BMI. Then comparisons were performed between two corresponding subpopulations in the expression level of HCC-related biomarkers including Alpha-FP, liver functions including albumin, ALT, AST, and ALP, plasma lipid profiles including cholesterol, and comorbidity conditions including cirrhosis in benign liver tissues, smoking, alcohol using, and illness with viral hepatitis. Two-tailed Student’s T-test was used to calculate the difference in mean values, and Chi-Square Test was used to compare the difference in rates or percentages. The significant p value was set at p<0.05. Results: In total 247 HCC cases, males were 178 (72.1%) and females were 69 (27.9%) with a male to female ratio of 2.6:1; black patients were 108 (43.7%), white patients were 127 (51.4%), and others were 4.9%. The mean age was 59.6 years and mean BMI was 27.04. AFP was the only one of detected tumor biomarkers showing disparities: it was significantly higher in patients of male (p=0.026), younger age (p<0.0001), lower BMI (p=0.039), smokers (p=0.0325) and illness with viral hepatitis (p=0.0007). Disparities in liver functions included: 1) AST was significantly higher in Black HCC patients (p=0.027); 2) no statistical difference of liver functions in gender; 3) younger HCC patients had significantly lower level of Albumin (p=0.006), and higher levels of ALT (p=0.014) and AST (p=0.0032); 4) HCC patients with lower BMI also had lower level of Albumin (p=0.015), and higher levels of AST (p=0.0480 and ALP (p=0.0057). There was no statistical difference of plasma lipid profiles between subpopulations, Black HCC patients except that Black HCC patients had significantly higher levels of cholesterol (p=0.0006) and HDL (p=0.048). In comorbidity, Black HCC patients had higher rates of alcohol using and existence of cirrhosis; and male HCC patients had higher rates of smoking, alcohol usage and viral hepatitis. Conclusions: HCC patients are greatly disparate in the expression level of tumor biomarkers, liver functions, plasma lipid profiles and comorbidity conditions between subpopulations stratified by race, gender, age and BMI. These results could provide useful information for clinical management and prognosis of patients with HCC. Citation Format: Xinchun Zhou, Barrett Aldridge, Nazar Rahmanov, Zhirong Liu, Jinghe Mao, Neha Varshney. A retrospective study on the disparities of hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 822.

Surface functionalization of calcium magnesium phosphate cements with alginate sodium for enhanced bone regeneration via TRPM7/PI3K/Akt signaling pathway

Although calcium‑magnesium phosphate cements (CMPCs) have been widely applied to treating critical-size bone defects, their repair efficiency is unsatisfactory owing to their weak surface bioactivity and uncontrolled ion release. In this study, we lyophilized alginate sodium (AS) as a coating onto HAp/K-struvite (H@KSv) to develop AS/HAp/K-struvite (AH@KSv), which promotes bone regeneration. The compressive strength and hydrophilicity of AH@KSv significantly improved, leading to enhanced cell adhesion in vitro. Importantly, the SA coating enables continuous ions release of Mg2+ and Ca2+, finally leading to enhanced osteogenesis in vitro/vivo and different patterns of new bone ingrowth in vivo. Furthermore, these composites increased the expression levels of biomarkers of the TRPM7/PI3K/Akt signaling pathway via an equilibrium effect of Mg2+ to Ca2+. In conclusion, our study provides novel insights into the mechanisms of Mg-based biomaterials for bone regeneration.

Quantitative Proteomic Analysis Identifying and Evaluating TRAF6 and IL-8 as Potential Diagnostic Biomarkers in Neonatal Patients with Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a common gastrointestinal complication in premature infants, resulting in high morbidity and mortality, and its early detection is crucial for accurate treatment and outcome prediction. Extensive research has demonstrated a clear correlation between NEC and extremely low birth weight, degree of preterm, formula feeding, infection, hypoxic/ischemic damage, and intestinal dysbiosis. The development of noninvasive biomarkers of NEC from stool, urine, and serum has attracted a great deal of interest because to these clinical connections and the quest for a deeper knowledge of disease pathophysiology. Therefore, this study aims to identify protein expression patterns in NEC and discover innovative diagnostic biomarkers. In this study, we recruited five patients diagnosed with NEC and paired necrotic segments of intestinal tissue with adjacent normal segments of intestine to form experimental and control groups. Quantitative proteomics tandem mass tagging (TMT) labeling technique was used to detect and quantify the proteins, and the expression levels of the candidate biomarkers in the intestinal tissues were further determined by quantitative polymerase chain reaction (RT-qPCR), Western blot analysis, Immunofluorescence methods and enzyme-linked immunosorbent assay (ELISA). A total of 6880 proteins were identified and quantified in patients with NEC. A significant disparity in protein expression was observed between necrotic and normal segments of intestinal tissue in NEC patients. A total of 55 proteins were found to be upregulated, and 40 proteins were found to be downregulated in NEC patients when using a p-value of < 0.05, and an absolute fold change of > 1.2 for analysis. GO function enrichment analysis showed the positive regulation of significant biological processes such as mitochondrial organization, vasoconstriction, rRNA catabolism, fluid shear stress response, and glycerol ether biosynthesis processes. Enrichment analysis also revealed essential functions such as ligand-gated ion channel activity, potassium channel activity, ligand-gated cation channel activity, ligand-gated ion channel activity, and ligand-gated channel activity, including molecular functions such as ligand-gated ion channel activity and mitotic events in this comparative group. Significant changes were found in endomembrane protein complex, membrane fraction, mitochondrial membrane fraction, membrane components, membrane intrinsic components, and other localized proteins. Additional validation of intestinal tissue and serum revealed a substantial increase in TRAF6 (tumor necrosis factor receptor-associated factor 6) and IL-8(Interleukin-8, CXCL8). The quantitative proteomic TMT method can effectively detect proteins with differential expression in the intestinal tissues of NEC patients. Proteins TRAF6 and CXCL8/IL-8 are significantly upregulated in the intestinal tissues and serum samples of patients and may serve as valuable predictor factors for NEC's early diagnosis.

Dynamic contrast-enhanced magnetic resonance imaging in cervical cancer: correlation between quantitative parameters and molecular markers hypoxia-inducible factors-1-alpha, vascular endothelial growth factor, and Ki-67

To investigate whether dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has the potential to non-invasively detect microenvironmental condition by quantitatively measuring blood perfusion, vessel wall permeability, and vascularity, and to elucidate the possible correlations between DCE-MRI quantitative parameters and the expression level of hypoxia, vascularity, and cell proliferation related molecular biomarkers. In this prospective single center clinical study, 58 patients diagnosed with cervical cancer underwent DCE-MRI before anticancer treatment were enrolled. Ktrans, Kep, Ve, and Vp were generated from Extended Toft's model. Then patients conducted colposcopy biopsy within 1 week after DCE-MRI. Pretreatment expression levels of HIF-1α, VEGF and Ki-67 were assessed and scored by immunohistochemistry on colposcopy obtained tumor specimens. In HIF-1α low-expression group, Ktrans (p=0.031) and Kep (p=0.012) values were significantly higher than the high-expression group. In VEGF high-expression group, Ktrans (p=0.044) and Ve values (p=0.021) were significantly higher than the low-expression group. In Ki-67 high-expression group, Ktrans (p=0.026) and Kep (p=0.033) were significantly higher than the low-expression group. Multiple linear regression analyses and Pearson correlation revealed that Ktrans independently negatively correlated with HIF-1α expression, Ve independently positively correlated with VEGF, and Kep independently positively correlated with Ki-67. The area under the ROC curves of Ktrans for HIF-1α, Ve for VEGF, and Kep for Ki-67 were 0.728, 0.743, 0.730, respectively. Our results suggest that DCE-MRI quantitative parameters could be potentially used as imaging markers for non-invasively detecting microenvironmental hypoxia, vascularity and proliferation in cervical cancer patients.

Deubiquitinase BRCC3 promotes the migration, invasion and EMT progression of colon adenocarcinoma by stabilizing MET expression.

Breast cancer type 1 susceptibility protein/breast cancer type 2 susceptibility protein-containing complex subunit 3 (BRCC3), a deubiquitinase (DUBs), is overexpressed in various cancers. However, the underlying biological roles of BRCC3 in adenocarcinoma colon (COAD) have yet to be decrypted. In this work, we explored the potential biological function of BRCC3 in the natural process of COAD cells. The expression levels of BRCC3 in COAD tissues and cell lines were investigated via quantitative real time polymerase chain reaction and western blotting analyses. Meanwhile, short hairpin RNAs targeting BRCC3 (sh-BRCC3) or mesenchymal-epithelial transition factor (MET) (sh-MET) were used to investigate the biological function, including proliferation, apoptosis, migration, invasion, and epithelial-mesenchymal transition (EMT) progression in COAD cells. Furthermore, the expression levels of EMT-related biomarkers were detected with western blotting analysis. Furthermore, we also performed Co-IP assay to identify the correlation between BRCC3 and MET. BRCC3 expression was increased in COAD tissues and cell lines. ShRNA-mediated downmodulation of BRCC3 in COAD cell lines induced EMT progression. BRCC3 knockdown resulted in decreased migration as well as invasion and increased apoptosis of SW480 and Lovo cells. Besides, MET was regulated by BRCC3 and involved in the migration, invasion, and EMT in SW480 and Lovo cells. Finally, we uncovered that the overexpressed MET reversed the effects of BRCC3 knockdown in COAD cell development. BRCC3 acted as a critical factor in the development of COAD by deubiquitinating and stabilizing MET, which might provide an emerging biomarker for the therapeutic and diagnosis strategy of COAD.

Evaluation of IL-1β and CRP mRNA expression levels by RT-PCR in postorthodontic treatment patients with temporomandibular joint disorders: a cross-sectional Study.

Temporomandibular joint disorder (TMD), which affects the masticatory muscles, temporomandibular joint, and surrounding tissues, can manifest as inflammation. This study aims to explore the expression levels of the inflammatory biomarkers, interleukin (IL)-1β and C-reactive protein (CRP), in TMD patients who have undergone orthodontic treatment. Buccal swabs from 105 postorthodontic treatment patients were analyzed using real-time polymerase chain reaction to assess the expression levels of IL-1β and CRP in each group after messenger ribonucleic acid extraction. Patients were also examined using the Diagnostic Criteria for TMD (DC/TMD) to determine if they met the criteria for a TMD diagnosis. The TMD group was subdivided into three categories based on the DC/TMD. The study included 37 patients who did not develop TMD (group 0) and 68 participants who developed TMD after orthodontic treatment, including 17 with pain-related TMDs (group 1), 29 with intra-articular TMDs (Group 2), and 22 with combined pain-related and intra-articular TMDs (group 3). CRP expression was higher than IL-1β in groups 1 and 2, and IL-1β expression was higher than CRP in group 3. The Kruskal-Wallis test showed that IL-1β and CRP expression levels in groups 1, 2, and 3 were not statistically different. Sex and adult age had considerable effects on the occurrence of TMD in patients after orthodontic treatment. Higher IL-1β expression was found in postorthodontic treatment patients with more complex TMD. This study strengthens the evidence of inflammation through IL-1β and CRP expression in individuals with TMD, especially after orthodontic treatment.

Extracellular-Vesicle Catch-and-Release Isolation System Using a Net-Charge Invertible Curvature-Sensing Peptide.

Extracellular vesicles (EVs) carry various informative components, including signaling proteins, transcriptional regulators, lipids, and nucleic acids. These components are utilized for cell-cell communication between donor and recipient cells. EVs have shown great promise as pharmaceutical-targeting vesicles and have attracted the attention of researchers in the fields of biological and medical science because of their importance as diagnostic and prognostic markers. However, the isolation and purification of EVs from cell-cultured media remain challenging. Ultracentrifugation is the most widely used method, but it requires specialized and expensive equipment. In the present study, we proposed a novel methodology to isolate EVs using a simple and convenient method, i.e., an EV catch-and-release isolation system (EV-CaRiS) using a net-charge invertible curvature-sensing peptide (NIC). Curvature-sensing peptides recognize vesicles by binding to lipid-packing defects on highly curved membranes regardless of the expression levels of biomarkers. NIC was newly designed to reversibly capture and release EVs in a pH-dependent manner. NIC allowed us to achieve reproducible EV isolation from three human cell lines on resin using a batch method and single-particle imaging of EVs containing the ubiquitous exosome markers CD63 and CD81 by total internal reflection fluorescence microscopy (TIRFM). EV-CaRiS was demonstrated as a simple and convenient methodology for EV isolation, and NIC is promising for applications in the single-particle analysis of EVs.

Analysis and identification of oxidative stress-ferroptosis related biomarkers in ischemic stroke

Studies have shown that a series of molecular events caused by oxidative stress is associated with ferroptosis and oxidation after ischemic stroke (IS). Differential analysis was performed to identify differentially expressed mRNA (DEmRNAs) between IS and control groups. Critical module genes were identified using weighted gene co-expression network analysis (WGCNA). DEmRNAs, critical module genes, oxidative stress-related genes (ORGs), and ferroptosis-related genes (FRGs) were crossed to screen for intersection mRNAs. Candidate mRNAs were screened based on the protein–protein interaction (PPI) network and the MCODE plug-in. Biomarkers were identified based on two types of machine learning algorithms, and the intersection was obtained. Functional items and related pathways of the biomarkers were identified using gene set enrichment analysis (GSEA). Finally, single-sample GSEA (ssGSEA) and Wilcoxon tests were used to identify differential immune cells. An miRNA-mRNA-TF network was created. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the expression levels of biomarkers in the IS and control groups. There were 8287 DE mRNAs between the IS and control groups. The genes in the turquoise module were selected as critical module genes for IS. Thirty intersecting mRNAs were screened for overlaps. Seventeen candidate mRNAs were also identified. Four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) were identified using two types of machine-learning algorithms. GSEA results indicated that the biomarkers were associated with steroid biosynthesis. Nine types of immune cells (activated B cells and neutrophils) were markedly different between the IS and control groups. We identified 3747 miRNA-mRNA-TF regulatory pairs in the miRNA-mRNA-TF regulatory network, including hsa-miR-4469-CDKN1A-BACH2 and hsa-miR-188-3p-GPX4-ATF2. CDKN1A, PRDX1, and PRDX6 were upregulated in IS samples compared with control samples. This study suggests that four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) are significantly associated with IS. This study provides a new reference for the diagnosis and treatment of IS.

Identification and Analysis of Gene Biomarkers for Ovarian Cancer.

Objective: To identify potential diagnostic markers for ovarian cancer (OC) and explore the contribution of immune cells infiltration to the pathogenesis of OC. Methods: As the study cohort, two gene expression datasets of human OC (GSE27651 and GSE26712, taken as the metadata) taken from the Gene Expression Omnibus (GEO) database were combined, comprising 228 OC and 16 control samples. Analysis was performed to identify the differentially expressed genes between the OC and control samples, while support vector machine analysis using the recursive feature elimination algorithm and least absolute shrinkage and selection operator regression were performed to identify candidate biomarkers that could discriminate OC. In addition, immunohistochemistry staining was performed to verify the diagnostic value and protein expression levels of the candidate biomarkers. The GSE146553 dataset (OC n = 40, control n = 3) was used to further validate the diagnostic values of those biomarkers. Further, the proportions of various immune cells infiltration in the OC and control samples were evaluated using the CIBERSORT algorithm. Results: CLEC4M, PFKP, and SCRIB were identified as potential diagnostic markers for OC in both the metadata (area under the receiver operating characteristic curve [AUC] = 0.996, AUC = 1.000, AUC = 1.000) and GSE146553 dataset (AUC = 0.983, AUC = 0.975, AUC = 0.892). Regarding immune cell infiltration, there was an increase in the infiltration of follicular helper dendritic cells, and a decrease in the infiltration of M2 macrophages and neutrophils, as well as activated natural killer (NK) cells and T cells in OC. CLEC4M showed a significantly positive correlation with neutrophils (r = 0.57, p < 0.001) and resting NK cells (r = 0.42, p = 0.0047), but a negative correlation with activated dendritic cells (r = -0.33, p = 0.032). PFKP displayed a significantly positive correlation with activated NK cells (r = 0.36, p = 0.016) and follicular helper T cells (r = 0.32, p = 0.035), but a negative correlation with the naive B cells (r = -0.3, p = 0.049) and resting NK cells (r = -0.41, p = 0.007). SCRIB demonstrated a significantly positive correlation with plasma cells (r = 0.39, p = 0.01), memory B cells (r = 0.34, p = 0.025), and follicular helper T cells (r = 0.31, p = 0.04), but a negative correlation with neutrophils (r = -0.46, p = 0.002) and naive B cells (r = -0.48, p = 0.0012). Conclusion: CLEC4M, PFKP, and SCRIB were identified and verified as potential diagnostic biomarkers for OC. This work and identification of the three biomarkers may provide guidance for future studies into the mechanism and treatment of OC.

Myocardial sodium-glucose cotransporter 2 expression and cardiac remodelling in patients with severe aortic stenosis: The BIO-AS study.

Cardiac remodelling plays a major role in the prognosis of patients with aortic stenosis (AS) and could impact the benefits of aortic valve replacement. Our study aimed to evaluate the expression of sodium-glucose cotransporter 2 (SGLT2) gene and protein in patients with severe AS stratified in high gradient (HG) and low flow-low gradient (LF-LG) AS and its association with cardiac functional impairments. Gene expression and protein levels of main biomarkers of cardiac fibrosis (galectin-3, sST2, serpin-4, procollagen type I amino-terminal peptide, procollagen type I carboxy-terminal propeptide, collagen, transforming growth factor [TGF]-β), inflammation (growth differentiation factor-15, interleukin-6, nuclear factor-κB [NF-κB]), oxidative stress (superoxide dismutase 1 [SOD1] and 2 [SOD2]), and cardiac metabolism (sodium-hydrogen exchanger, peroxisome proliferator-activated receptor [PPAR]-α, PPAR-γ, glucose transporter 1 [GLUT1] and 4 [GLUT4]) were evaluated in blood samples and heart biopsies of 45 patients with AS. Our study showed SGLT2 gene and protein hyper-expression in patients with LF-LG AS, compared to controls and HG AS (p < 0.05). These differences remained significant even after adjusting for age, gender, body mass index, history of diabetes mellitus, arterial hypertension, and coronary artery disease. SGLT2 gene expression was positively correlated with: (i) TGF-β (r = 0.72, p < 0.001) and collagen (r = 0.73, p < 0.001) as markers of fibrosis; (ii) NF-κB (r = 0.36, p < 0.01) and myocardial interleukin-6 (r = 0.68, p < 0.001) as markers of inflammation: (iii) SOD2 (r = -0.38, p < 0.006) as a marker of oxidative stress; (iv) GLUT4 (r = 0.33, p < 0.02) and PPAR-α (r = 0.36, p < 0.01) as markers of cardiac metabolism. In patients with LF-LG AS, SGLT2 gene and protein were hyper-expressed in cardiomyocytes and associated with myocardial fibrosis, inflammation, and oxidative stress.

Unveiling proteomic diversity: A quantitative study of antibody drug conjugate and chemotherapy targets in gastroesophageal cancer.

261 Background: Gastroesophageal cancer (GEC), is a significant global health concern with a 5-year relative survival of 7% for metastatic GEC. Standard treatments often include surgery, chemotherapy, and radiation therapy, but their effectiveness can be limited. Chemotherapy is frequently utilized in the treatment of GEC, although no biomarkers for chemotherapy are used in the selection of the chemo agent. There are several well-known biomarkers of resistance and sensitivity for various chemo agents. We used targeted proteomics to quantify protein expression levels of several protein biomarkers associated with chemotherapy efficiency in 125 GEC patients. These include resistance markers for platinum agents (ERCC1), and tubulin inhibitors (TUBB3). It also includes sensitivity markers for irinotecan/topotecan (Topo1), and doxorubicin/etoposide (Topo2A). We also assessed the protein levels of several antibodies-drug conjugate markers (EGFR, Her2, Trop2, FR-alpha, Mesothelin, Axl, CLDN18.2, and Nectin-4). Methods: FFPE tumor tissues from 125 clinical GC patients were microdissected and solubilized for mass spectrometry-based targeted proteomic analysis in our CLIA-certified laboratory. 72 proteins were quantified from 2-3 sections of FFPE tissue. Results: 5-Fluorouracil (5-FU), taxanes, and platinum agents (such as carboplatin) are among the chemotherapy agents that are frequently used to treat GEC. TYMP, a sensitivity marker for 5-FU, was expressed in 32% of GEC cases. ERCC1, a resistance marker for platinum drugs, was expressed at 34%. Additionally, 48% of GEC exhibited TUBB3, a resistance marker for paclitaxel and docetaxel. Topoisomerase 1 (Topo1) is the target for irinotecan or topotecan, and is also the target for some ADCs (e.g. trastuzumab deruxtecan, sacituzumab govitecan etc.). Topo1 was expressed in 92% of GEC with a 10x range (415 - 4195 amol/μg). Another topoisomerase, Topo2A, targetable by etoposide, epirubicin, and doxorubicin, was expressed in 59% of GEC with 19x range (402-7804 amol/μg). ADC targets, such as EGFR (82% detected with 184x range of distribution), Her3 (18%, 4x), AXL (18%,7x), MET (27%, 19x), and Trop2 (50%, 57x) showed a wide range of protein expression. With a 56x range (318 - 17786 amol/μg), Her2 was found in 46% of GEC, of which 12% of GEC had overexpression of Her2 (&gt;740 amol/μg), suggesting that the majority of GEC has low levels of Her2 (318-690 amol/μg), which is potentially targetable by newer anti-Her2 agents. Conclusions: Every cancer is different, and the ability to quantitate simultaneously 72 protein biomarkers from 2-3 FFPE sections provides a wealth of actionable information that, when combined with other multi-omics biomarker data, will help guide clinical treatment or patient stratification for clinical trials.

Bioinformatics and Machine Learning Methods Identified MGST1 and QPCT as Novel Biomarkers for Severe Acute Pancreatitis.

Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to identify biomarkers and investigate molecular mechanisms of SAP. The GSE194331 dataset from GEO database was analyzed using bioinformatics. Differentially expressed genes (DEGs) associated with SAP were identified, and a protein-protein interaction network (PPI) was constructed. Machine learning algorithms were used to determine potential biomarkers. Gene set enrichment analysis (GSEA) explored molecular mechanisms. Immune cell infiltration were analyzed, and correlation between biomarker expression and immune cell infiltration was calculated. A competing endogenous RNA network (ceRNA) was constructed, and biomarker expression levels were quantified in clinical samples using RT-PCR. 1101 DEGs were found, with two modules most relevant to SAP. Potential biomarkers in peripheral blood samples were identified as glutathione S-transferase 1 (MGST1) and glutamyl peptidyltransferase (QPCT). GSEA revealed their association with immunoglobulin regulation, with QPCT potentially linked to pancreatic cancer development. Correlation between biomarkers and immune cell infiltration was demonstrated. A ceRNA network consisting of 39 nodes and 41 edges was constructed. Elevated expression levels of MGST1 and QPCT were verified in clinical samples. In conclusion, peripheral blood MGST1 and QPCT show promise as SAP biomarkers for diagnosis, providing targets for therapeutic intervention and contributing to SAP understanding.

Effect of running exercise training on inflammatory mediators and cytokines expression in testicular tissue; effect of exercise intensity

The aim of this study is to investigate the impact of running exercise training protocols (ETPs) with varying intensities on inflammatory responses, with a specific focus on the interactions between inflammatory mediators, cytokines, and Leydig cell steroidogenic activity, as well as testosterone secretion. To this end, 24 Wistar rats were subdivided into sedentary control, low (LICT), moderate (MICT), and high (HICT) intensity continuous running ETP groups. After 8 weeks, the expression levels of Toll-like receptor-4 (TLR-4), nuclear factor-kappa-B (NF-KB), interleukin-6 (IL-6), interleukin-10 (IL-10), Tumor necrosis factor alpha (TNF-α), cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), and the testicular nitric oxide (NO) content were assessed and compared between groups. Moreover, the mean distributions of Leydig cells/mm2 of interstitial connective tissue, their steroidogenic activity, and serum level of testosterone were assessed. The LICT did not show any significant (p > 0.05) change in the expression levels of all aforementioned biomarkers. In contrast, both the MICT and HICT groups demonstrated a significant (p < 0.05) increase in the expression levels of TLR-4, NFK-B, IL-6, TNF-α, iNOS, and COX-2 at both the mRNA and protein levels. The testicular NO has increased in HICT and MICT groups. Despite a decrease in the distribution of Leydig cells in both the MICT and HICT groups, the HICT group exhibited a significant (p < 0.05) reduction in Leydig cell steroidogenic activity and serum testosterone levels. In conclusion, our findings revealed that ETPs can influence Leydig cell steroidogenic activity and testosterone secretion, contingent on their intensity. These effects are attributed to alterations in the expression levels of pro-inflammatory mediators and cytokines.

Construction and evaluation of endometriosis diagnostic prediction model and immune infiltration based on efferocytosis-related genes.

Background: Endometriosis (EM) is a long-lasting inflammatory disease that is difficult to treat and prevent. Existing research indicates the significance of immune infiltration in the progression of EM. Efferocytosis has an important immunomodulatory function. However, research on the identification and clinical significance of efferocytosis-related genes (EFRGs) in EM is sparse. Methods: The EFRDEGs (differentially expressed efferocytosis-related genes) linked to datasets associated with endometriosis were thoroughly examined utilizing the Gene Expression Omnibus (GEO) and GeneCards databases. The construction of the protein-protein interaction (PPI) and transcription factor (TF) regulatory network of EFRDEGs ensued. Subsequently, machine learning techniques including Univariate logistic regression, LASSO, and SVM classification were applied to filter and pinpoint diagnostic biomarkers. To establish and assess the diagnostic model, ROC analysis, multivariate regression analysis, nomogram, and calibration curve were employed. The CIBERSORT algorithm and single-cell RNA sequencing (scRNA-seq) were employed to explore immune cell infiltration, while the Comparative Toxicogenomics Database (CTD) was utilized for the identification of potential therapeutic drugs for endometriosis. Finally, immunohistochemistry (IHC) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were utilized to quantify the expression levels of biomarkers in clinical samples of endometriosis. Results: Our findings revealed 13 EFRDEGs associated with EM, and the LASSO and SVM regression model identified six hub genes (ARG2, GAS6, C3, PROS1, CLU, and FGL2). Among these, ARG2, GAS6, and C3 were confirmed as diagnostic biomarkers through multivariate logistic regression analysis. The ROC curve analysis of GSE37837 (AUC = 0.627) and GSE6374 (AUC = 0.635), along with calibration and DCA curve assessments, demonstrated that the nomogram built on these three biomarkers exhibited a commendable predictive capacity for the disease. Notably, the ratio of nine immune cell types exhibited significant differences between eutopic and ectopic endometrial samples, with scRNA-seq highlighting M0 Macrophages, Fibroblasts, and CD8 Tex cells as the cell populations undergoing the most substantial changes in the three biomarkers. Additionally, our study predicted seven potential medications for EM. Finally, the expression levels of the three biomarkers in clinical samples were validated through RT-qPCR and IHC, consistently aligning with the results obtained from the public database. Conclusion: we identified three biomarkers and constructed a diagnostic model for EM in this study, these findings provide valuable insights for subsequent mechanistic research and clinical applications in the field of endometriosis.

Astragaloside IV Mediates the PI3K/Akt/mTOR Pathway to Alleviate Injury and Modulate the Composition of Intestinal Flora in ApoE-/- Atherosclerosis Model Rats.

Atherosclerosis (AS) is a chronic inflammatory vascular disease with a complex pathogenesis. Astragaloside IV (AST IV), the primary active component of Astragalus, possesses anti-inflammatory, antioxidant, and immunomodulatory properties. This research aims to investigate the outcome of AST IV on AS and its potential molecular mechanism. A high-fat diet (21% fat, 50% carbohydrate, 20% protein, 0.15% cholesterol, and 34% sucrose) was utilized to feed Apolipoprotein E deficient (ApoE-/-) SD rats for 8 weeks, followed by continuous intragastric administration of AST IV for 8 weeks. Biochemical detection was conducted for serum lipid levels and changes in vasoactive substances. After Masson staining, aortic root oil red O staining, and Hematoxylin Eosin (HE) staining, the efficacy of AST IV was verified using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The mRNA expression levels of inflammatory factors and endothelial dysfunction-related biomarkers in rat aortic root tissues were appraised. The changes in the composition of intestinal flora in rats after AST IV treatment were appraised using Image J (Multi-point Tool). Western blot was used to evaluate phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway-related protein levels in rat aortic root tissues. AST IV administration alleviated the pathological symptoms of AS rats. AST IV administration reduced serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), endothelin-1 (ET-1) and angiotensin (Ang)-II (Ang-II) levels, and augmented serum high-density lipoprotein cholesterol (HDL-C) and nitric oxide (NO) levels. At the same time, AST IV administration inhibited the levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-1β, vascular cell adhesion molecule-1 (VCAM-1), matrix metalloproteinase-2 (MMP-2), macrophage inflammatory protein-1 (MCP-1), and intercellular adhesion molecule-1 (ICAM-1) in the aortic root tissue of AS rats. In addition, the intestinal flora changed significantly after AST IV administration. The number of Bifidobacterium, Lactobacillus, and Bacteroides augmented significantly, and Enterobacter, Enterococcus, Fusobacterium, and Clostridium significantly decreased. Mechanistically, AST IV administration inhibited the phosphorylation of PI3K, Akt, and mTOR in AS rats. When combined with Dactolisib (BEZ235) (a PI3K/Akt/mTOR pathway inhibitor), AST IV could further inhibit phosphorylation and reduce inflammation. AST IV has a potential anti-AS effect, which can improve the pathological changes of the aorta in ApoE-/- rats fed with a high-fat diet, reduce the level of inflammatory factors, and modulate the composition of intestinal flora via the PI3K/Akt/mTOR pathway.

Machine learning based on magnetic resonance imaging and clinical parameters helps predict mesenchymal-epithelial transition factor expression in oral tongue squamous cell carcinoma: a pilot study

ObjectivesThis study aimed to develop machine learning models to predict phosphorylated mesenchymal-epithelial transition factor (p-MET) expression in oral tongue squamous cell carcinoma (OTSCC) using magnetic resonance imaging (MRI)-derived texture features and clinical features. MethodsThirty-four patients with OTSCC were retrospectively collected. Texture features were derived from preoperative MR images, including T2WI, apparent diffusion coefficient mapping, and contrast-enhanced (ce)-T1WI. Dimension reduction was performed consecutively with reproducibility analysis and an information gain algorithm. Five machine learning methods—AdaBoost, logistic regression (LR), naïve Bayes (NB), random forest (RF), and support vector machine (SVM)—were adopted to create models predicting p-MET expression. Their performance was assessed with fivefold cross-validation. ResultsIn total, 22 and 12 cases showed low and high p-MET expression, respectively. After dimension reduction, 3 texture features (ADC-Minimum, ce-T1WI-Imc2, and ce-T1WI-DependenceVariance) and 2 clinical features (depth of invasion [DOI] and T-stage) were selected with good reproducibility and best correlation with p-MET expression levels. The RF model yielded the best overall performance, correctly classifying p-MET expression status in 87.5% of OTSCCs with an area under the receiver operating characteristic curve of 0.875. ConclusionDifferences in p-MET expression in OTSCCs can be noninvasively reflected in MRI-based texture features and clinical parameters. Machine learning can potentially predict biomarker expression levels, such as MET, in patients with OTSCC.

Berberine exerts antidepressant effects in vivo and in vitro through the PI3K/AKT/CREB/BDNF signaling pathway

BackgroundDepression, a global neuropsychiatric disorder, brings a serious burden to patients and society as its incidence continues to rise. Berberine is one of the main compounds of a variety of Chinese herbal medicines and has been shown to have multiple pharmacological effects. However, whether berberine can exert antidepressant effects in vivo and in vitro and its related mechanisms remain to be explored. MethodsThe chronic restraint stress (CRS) method and corticosterone (CORT) were applied to simulate depression-like behavior in vivo and neuronal apoptosis in vitro, respectively. The antidepressant effects of berberine were evaluated by behavioral tests and changes in the content of monoamine neurotransmitters. Inflammatory cytokines were detected and immunofluorescence staining was used to observe the expression levels of apoptosis-related proteins. RT-qPCR and Western blot were used to examine the mRNA and protein expression (or phosphorylation) levels of biomarkers of the PI3K/AKT/CREB/BDNF signaling pathways. ResultsBehavioral tests and levels of neurotransmitters proved that berberine could effectively ameliorate depression-like symptoms in CRS mice. Meanwhile, the results of ELISA and immunofluorescence staining showed that berberine could alleviate inflammatory status and reduce cell apoptosis in vivo and in vitro. Moreover, the changes of the PI3K/AKT/CREB/BDNF signaling pathway induced by CRS or CORT in mouse hippocampus or HT-22 cells were significantly reversed by berberine. ConclusionOur current study suggested that berberine could exert antidepressant effects in vitro and in vivo, which may be associated with the PI3K/AKT/CREB/BDNF signaling pathway.

Identification and subtype analysis of biomarkers associated with the solute carrier family in acute myocardial infarction.

The dysregulation of some solute carrier (SLC) proteins has been linked to a variety of diseases, including diabetes and chronic kidney disease. However, SLC-related genes (SLCs) has not been extensively studied in acute myocardial infarction (AMI). The GSE66360 and GSE60993 datasets, and SLCs geneset were enrolled in this study. Differentially expressed SLCs (DE-SLCs) were screened by overlapping DEGs between the AMI and control groups and SLCs. Next, functional enrichment analysis was carried out to research the function of DE-SLCs. Consistent clustering of samples from the GSE66360 dataset was accomplished based on DE-SLCs selected. Next, the gene set enrichment analysis (GSEA) was performed on the DEGs-cluster (cluster 1 vs cluster 2). Three machine learning models were performed to obtain key genes. Subsequently, biomarkers were obtained through receiver operating characteristic (ROC) curves and expression analysis. Then, the immune infiltration analysis was performed. Afterwards, single-gene GSEA was carried out, and the biomarker-drug network was established. Finally, quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of biomarkers. In this study, 13 DE-SLCs were filtered by overlapping 366 SLCs and 448 DEGs. The functional enrichment results indicated that the genes were implicated with amino acid transport and TNF signaling pathway. After the consistency clustering analysis, the samples were classified into cluster 1 and cluster 2 subtypes. The functional enrichment results showed that DEGs-cluster were implicated with chemokine signaling pathway and so on. Further, SLC11A1 and SLC2A3 were identified as SLC-related biomarkers, which had the strongest negative relationship with resting memory CD4 T cells and the strongest positive association with activated mast cells. In addition, the single-gene GSEA results showed that cytosolic ribosome was enriched by the biomarkers. Five drugs targeting SLC2A3 were predicted as well. Lastly, the experimental results showed that the biomarkers expression trends were consistent with public database. In this study, 2 SLC-related biomarkers (SLC11A1 and SLC2A3) were screened and drug predictions were carried out to explore the prediction and treatment of AMI.

Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients

BackgroundMicrovascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction.MethodsWe conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57).ResultsUrinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell–cell adhesion, and cell–cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts.ConclusionsThe four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.

Identification and validation of novel biomarkers for cold-dampness syndrome of rheumatoid arthritis based on integration of multiple bioinformatics methods

This study aims to identify the novel biomarkers of cold-dampness syndrome(RA-Cold) of rheumatoid arthritis(RA) by gene set enrichment analysis(GSEA), weighted gene correlation network analysis(WGCNA), and clinical validation. Firstly, transcriptome sequencing was carried out for the whole blood samples from RA-Cold patients, RA patients with other traditional Chinese medicine(TCM) syndromes, and healthy volunteers. The differentially expressed gene(DEG) sets of RA-Cold were screened by comparison with the RA patients with other TCM syndromes and healthy volunteers. Then, GSEA and WGCNA were carried out to screen the key DEGs as candidate biomarkers for RA-Cold. Experimentally, the expression levels of the candidate biomarkers were determined by RT-qPCR for an independent clinical cohort(not less than 10 cases/group), and the clinical efficacy of the candidates was assessed using the receiver operating characteristic(ROC) curve. The results showed that 3 601 DEGs associated with RA-Cold were obtained, including 106 up-regulated genes and 3 495 down-regulated genes. The DEGs of RA-Cold were mainly enriched in the pathways associated with inflammation-immunity regulation, hormone regulation, substance and energy metabolism, cell function regulation, and synovial pannus formation. GSEA and WGCNA showed that recombinant proteasome 26S subunit, ATPase 2(PSMC2), which ranked in the top 50% in terms of coefficient of variation, representativeness of pathway, and biological modules, was a candidate biomarker of RA-Cold. Furthermore, the validation results based on the clinical independent sample set showed that the F1 value, specificity, accuracy, and precision of PSMC2 for RA-Cold were 70.3%, 61.9%, 64.5%, and 81.3%, respectively, and the area under the curve(AUC) value was 0.96. In summary, this study employed the &quot;GSEA-WGCNA-validation&quot; integrated strategy to identify novel biomarkers of RA-Cold, which helped to improve the TCM clinical diagnosis and treatment of core syndromes in RA and provided an experimental basis for TCM syndrome differentiation.