Potential Biomarkers Research Articles

#49 Uremic toxins and inflammation: Metabolic pathways affected in stage 5 kidney disease

Abstract Background and Aims Chronic kidney disease (CKD) is a global health threat, affecting around 12% of the population. The uremic phenotype associated with CKD is considered a predictor for the high cardiovascular and overall mortality in these patients and inflammation is regarded as an essential contributor to it. We seek to discover new inflammation-related metabolites in the CKD population through the use of semitargeted metabolomics, in order to gain insight into the pathways involved and identify potential biomarkers. Method The study employed an observational prospective design to investigate metabolite impact on inflammation in 50 non-dialysis-dependent stage 5 CKD patients. Blood samples were collected before the start of the first haemodialysis session. A semitargeted metabolomic approach was followed, utilising liquid chromatography and high-resolution mass spectrometry with an in-house library of polar compounds. Univariate (Mann-Whitney test) and multivariate (logistic regression with LASSO regularization) analyses identified metabolomic variables associated with inflammation. Results Univariate analysis revealed that adenosine-5′-phosphosulfate (APS) (p-value (p) 0.0211), dimethyglycine (p 0.0015), pyruvate (p 0.0066), lactate (p 0.0156) and 2-ketobutyric acid (p 0.0458) were significantly increased with inflammation, with differences over 1,5-fold changes (inflammation = yes vs inflammation = no). Cholic acid (p 0.01655), homogentisic acid (p 0.0007), 2-phenylpropionic acid (p 0.0351) and 3-indoxylsulfate (p 0.0087) show similar patterns but in the opposite direction, as observed in the volcano plot in Fig. 1. Multivariate analysis revealed significant associations between metabolites and inflammation in CKD stage 5 patients. Specifically, odds ratios for N-Butyrylglycine (OR: 1.87), dimethylglycine (OR: 1.81), 2-Oxoisopentanoic acid (OR: 1.70), and pyruvate (OR: 1.71) were related to a higher probability of experiencing inflammation. Conversely, homogentisic acid (OR: 072), 2-Phenylpropionic acid (OR: 0.77), and 2-Methylglutaric acid (OR: 0.78) exhibited an OR<1, suggestive of decreased probability. This is graphically represented in Fig. 2. Conclusion In our semi-targeted metabolomics study on stage 5 CKD patients, we pinpointed various metabolites linked to inflammation. Notably, dimethylglycine, a uremic toxin, may contribute to vascular damage, while pyruvate's abnormal metabolism is a known feature in heart failure and chronic kidney disease. N-butyrilglycine and 2-oxoisopentanoic acid were also associated with inflammation, potentially tied to mitochondrial fatty acid beta oxidation and incomplete breakdown of branched-chain amino acids. APS, impacting bone development and intestinal permeability, showed a positive correlation with inflammation. Conversely, homogentisic acid and phenylpropionic acid were negatively correlated. While homogentisic acid's anti-inflammatory role isn't clear, phenylpropionic acid exhibits protective effects against hepatotoxicity by reducing immune response. 2-methylglutaric acid and cholic acid were inversely correlated with inflammation, suggesting a protective effect related to fatty acid metabolism and bile acid regulation. These identified metabolites enhance our understanding of CKD-associated inflammation and present strong candidates for future biomarker validation with potential for clinical translation.

Immunotherapy Applications for Thymine Dimers and WT1 Antigen in Renal Cancers: A Comparative Statistical Analysis.

Renal cell carcinoma (RCC) remains incurable in advanced stages. Biomarkers have proven to be quite useful in cancer therapeutics. Herein, we provide a comparative/integrative statistical analysis of seminal immunohistochemistry (IHC) findings for Wilms' Tumor 1 antigen (WT1) and thymine dimers (TDs), emerging as atypical, yet promising, potential biomarkers for RCCs. We assessed WT1/TD reactivity in adult RCC tumor cells, tumor microenvironment (TME), and tumor-adjacent healthy renal tissue (HRT). WT1 positivity was scarce and strictly nuclear in tumor cells, whereas TD-reactive tumor tissues were prevalent. We report statistically significant positive correlations between the density of reactive RCC cellularity and the intensity of nuclear staining for both biomarkers (WT1 - rho = 0.341, p-value = 0.036; TDs - rho = 0.379, p-value = 0.002). RCC stromal TME TD-positivity was much more frequent than WT1 reactivity, apparently proportional to that of the proper RCC cellularity and facilitated by extensive RCC inflammatory infiltration. TDs exhibited nuclear reactivity for most TME cell lines, while RCC TME WT1 expression was rare and inconsistent. In HRTs, TDs were entirely restricted to renal tubular cells, the likely cellular progenitor of most conventional RCC subtypes. In lieu of proper validation, these early findings have significant implications regarding the origins/biology of RCCs and may inform RCC therapeutics, both accounting for the high frequency of immunotherapy-permissive frameshift indels in RCCs, but also hinting at novel predictive clinical tools for WT1-targeted immunotherapy. Overall, the current study represents a meek yet hopefully significant step towards understanding the molecular biology and potential therapeutic targets of RCCs.

Neutrophil extracellular trap-induced ferroptosis promotes abdominal aortic aneurysm formation via SLC25A11-mediated depletion of mitochondrial glutathione

BackgroundNeutrophil extracellular traps (NETs) induce oxidative stress, which may initiate ferroptosis, an iron-dependent programmed cell death, during abdominal aortic aneurysm (AAA) formation. Mitochondria regulate the progression of ferroptosis, which is characterized by the depletion of mitochondrial glutathione (mitoGSH) levels. However, the mechanisms are poorly understood. This study examined the role of mitoGSH in regulating NET-induced ferroptosis of smooth muscle cells (SMCs) during AAA formation. MethodsConcentrations of NET markers were tested in plasma samples. Western blotting and immunofluorescent staining were performed to detect the expression and localization of NET and ferroptosis markers in tissue samples. The role of NETs and SMC ferroptosis during AAA formation was investigated using peptidyl arginine deiminase 4 gene (Padi4) knockout or treatment with a PAD4 inhibitor, ferroptosis inhibitor or activator in an angiotensin II-induced AAA mouse model. The regulatory effect of SLC25A11, a mitochondrial glutathione transporter, on mitoGSH and NET-induced ferroptosis of SMCs was investigated using in vitro and in vivo experiments. Transmission electron microscopy was used to detect mitochondrial damage. Blue native polyacrylamide gel electrophoresis was used to analyze the dimeric and monomeric forms of the protein. ResultsSignificantly elevated levels of NETosis and ferroptosis markers in aortic tissue samples were observed during AAA formation. Specifically, NETs promoted AAA formation by inducing ferroptosis of SMCs. Subsequently, SLC25A11 was identified as a potential biomarker for evaluating the clinical prognosis of patients with AAA. Furthermore, NETs decreased the stability and dimerization of SLC25A11, leading to the depletion of mitoGSH. This depletion induced the ferroptosis of SMCs and promoted AAA formation. ConclusionDuring AAA formation, NETs regulate the stability of the mitochondrial carrier protein SLC25A11, leading to the depletion of mitoGSH and subsequent activation of NET-induced ferroptosis of SMCs. Preventing mitoGSH depletion and ferroptosis in SMCs is a potential strategy for treating AAA.

#1493 Upregulated miR-205 as a biomarker of diet-induced obesity-related glomerulopathy

Abstract Background and Aims Obesity is a modifiable risk factor for the development and progression of chronic kidney disease (CKD). Pathways through which obesity might cause renal disease are not completely understood, as not all obese subjects develop CKD. In terms of deepening the knowledge of the preliminary steps of obesity-related renal damage, our group has developed a diet-induced obese murine model with obesity related glomerulopathy (ORG). The objective of this study was to investigate ORG at a cellular, structural and transcriptomic level as a way to discover the triggering pathogenic phenomena of ORG and evaluate potential biomarkers. Method Thirty Wistar rats were randomized into two groups: control rats (n = 15), which were fed with standard diet (SD) and study rats (n = 15), which were fed with high-fat diet (HFD). After 10 weeks, weight, parameters of kidney function, renal histological features, transcriptomic changes, miRNA and mRNA isolation were compared. Results HFD gained significantly more weight (55.8%) than SD(29.2%), p = 0.001. Albuminuria was also significantly higher in HFD (10,384.04) compared with SD (5,845.45), p = 0.001. HFD rats showed typical lesions of early-stages of ORG, with a predominance of mesangial matrix increase (MMI) and podocyte hypertrophy (PH). All histologic lesions correlated with genes differentially expressed (DE) in kidneys of HFD group and, both MMI and PH, also correlated with specific miRNAs DE in the urine of HFD group. The functional analysis showed 4 miRNAs DE in the kidneys of HFD group that negatively regulates PTEN gene, which promotes podocyte endocytosis of lipids in ORG. The electronic microscope confirmed the spaces of lipid vacuoles in the podocytes of HFD rats. Between those 4 miRNAs DE, miR-205 was also found to be upregulated in the urine of HFD group. Conclusion Wistar rats fed with HFD for 10 weeks developed early-stages of ORG, with a specific targetome of miRNAs and gene expression. The upregulation of miR-205 in kidney and its isolation in urine is associated with lipid endocytosis of podocytes, which takes place in the early-stages of ORG and could become a plausible biomarker of early-stages of ORG and open new avenues for future therapeutics research.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Specific feature recognition on group specific networks (SFR-GSN): a biomarker identification model for cancer stages

Background and ObjectiveAccurate identification of cancer stages is challenging due to the complexity and heterogeneity of the disease. Current clinical diagnosis methods primarily rely on phenotypic observations, which may not capture early molecular-level changes accurately.MethodsIn this study, a novel biomarker recognition method was proposed tailored for cancer stages by considering the change of gene expression relationships. Utilizing the sample-specific information and protein-protein interaction networks, the group specific networks were constructed to address the limited specificity of potential biomarkers. Then, a specific feature recognition method was proposed based on these group specific networks, which employed the random forest algorithm for initial screening followed by a recursive feature elimination process to identify the optimal biomarker subset. During exploring optimal results, a strategy termed the Cost-Benefit Ratio, was devised to facilitate the identification of stage-specific biomarkers.ResultsComparative experiments were conducted on lung adenocarcinoma and breast cancer datasets to validate the method’s efficacy and generalizability. The results showed that the identified biomarkers were highly stage-specific, and the F1 scores for predicting cancer stages were significantly improved. For the lung adenocarcinoma dataset, the F1 score reached 97.68%, and for the breast cancer dataset, it achieved 96.87%. These results significantly surpassed those of three conventional methods in terms of F1 scores. Moreover, from the perspective of biological functions, the biomarkers were proved playing an important role in cancer stage-evolution.ConclusionThe proposed method demonstrated its effectiveness in identifying stage-related biomarkers. By using these biomarkers as features, accurate prediction of cancer stages was achieved. Furthermore, the method exhibited potential for biomarker identification in subtype analyses, offering novel perspectives for cancer prognosis.

Altered Genome-Wide DNA Methylation in the Duodenum of Common Variable Immunodeficiency Patients

PurposeA large proportion of Common variable immunodeficiency (CVID) patients has duodenal inflammation with increased intraepithelial lymphocytes (IEL) of unknown aetiology. The histologic similarities to celiac disease, lead to confusion regarding treatment (gluten-free diet) of these patients. We aimed to elucidate the role of epigenetic DNA methylation in the aetiology of duodenal inflammation in CVID and differentiate it from true celiac disease.MethodsDNA was isolated from snap-frozen pieces of duodenal biopsies and analysed for differences in genome-wide epigenetic DNA methylation between CVID patients with increased IEL (CVID_IEL; n = 5) without IEL (CVID_N; n = 3), celiac disease (n = 3) and healthy controls (n = 3).ResultsThe DNA methylation data of 5-methylcytosine in CpG sites separated CVID and celiac diseases from healthy controls. Differential methylation in promoters of genes were identified as potential novel mediators in CVID and celiac disease. There was limited overlap of methylation associated genes between CVID_IEL and Celiac disease. High frequency of differentially methylated CpG sites was detected in over 100 genes nearby transcription start site (TSS) in both CVID_IEL and celiac disease, compared to healthy controls. Differential methylation of genes involved in regulation of TNF/cytokine production were enriched in CVID_IEL, compared to healthy controls.ConclusionThis is the first study to reveal a role of epigenetic DNA methylation in the etiology of duodenal inflammation of CVID patients, distinguishing CVID_IEL from celiac disease. We identified potential biomarkers and therapeutic targets within gene promotors and in high-frequency differentially methylated CpG regions proximal to TSS in both CVID_IEL and celiac disease.

Glutathione conjugation of sesquimustard: in vitro investigation of potential biomarkers.

Sesquimustard (Q) is a powerful blistering agent that contains additional sulfur atoms. Sulfur mustard causes covalent bonding by alkylating nucleophilic groups of biologically important macromolecules such as lipids, proteins, DNA, or RNA. Most cells maintain relatively high amounts of a unique tripeptide called glutathione (GSH) (γ-glutamyl-cysteinyl glycine), which possesses a free thiol group, to prevent unwanted reactions caused by reactive chemical entities. Moreover, these thiol groups on cysteines (Cys) are the main target for alkylation. Although Q is the most potent vesicant among sulfur mustards, research studies identifying biomarkers of Q are very limited. Therefore, here in this study, we aimed to identify the GSH and Cys conjugates of Q using mass spectrometric methods and to observe the formation of these conjugates in HaCat cell culture following exposure to different doses. We identified four different conjugates of Q, which are bis-glutathionyl ethylthioethylthioethyl conjugate (GSH-ETETE-GSH), hydroxyethylthioethylthioethyl glutathione conjugate (HETETE-GSH), bis-cysteinyl ethylthioethylthioethyl conjugate (Cys-ETETE-Cys), and hydroxyethylthioethylthioethyl cysteine conjugate (HETETE-Cys). The identity of the conjugates was elucidated using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). We also investigated changes in conjugate formation with exposure concentration and time elapsed after exposure in the cell culture. After exposure, GSH conjugates decreased until 1st hour, while Cys conjugates increased until 6th hour. We also observed that conjugate formation depended on the concentration of Q. This is the first study to elucidate the conjugates of Q dependent on GSH conjugation. As biomarkers are essential tools for evaluating exposure to Q, this study contributes to the limited number of studies identifying biomarkers for Q.

#1393 Urinary soluble CD163 correlates with glomerular inflammation in proliferative lupus nephritis

Abstract Background and Aims Clinical distinction between histologic activity and chronicity in lupus nephritis remains challenging. We sought to evaluate the utility of urinary soluble protein CD613 (usCD163) as a potential biomarker to reflect histologic activity in lupus nephritis (LN). Method Forty-three patients with LN with concurrent determination of usCD163 at the moment of kidney biopsy were included in the study. A first morning void prior to the kidney biopsy was collected and usCD163 was measured by a commercial ELISA assay (EUROIMMUN, Lubeck, DE). Urine CD163 values were normalized to urine creatinine and expressed as ng per mmol of urine creatinine. Results The study cohort had a mean age at the moment of kidney biopsy of 35.3 ± 12.3 years, 81.4% being females. The mean eGFR and 24-h proteinuria were 77.1 ± 33.7 ml/min/1.73 m2 and 3.28 ± 3.23 g/day, respectively. In terms of histological findings, the majority of patients had proliferative LN (class III—34.9%, class IV—34.9%, class IV+V—9.3%), while the median activity and chronicity index were 7 (IQR: 3-11) and 3 (IQR: 1-5), respectively. The median usCD163 normalized to urine creatinine was 616.4 ng/mmol (IQR: 117.6-2363.7). usCD163 significantly correlated with 24-h proteinuria (r = 0.46, p = 0.002), albumin/creatinine ratio (r = 0.61, p < 0.001) and C3 level (r = −0.32, p = 0.03), but not with hematuria (r = 0.26, p = 0.09) or eGFR (r = −0.27, p = 0.07). Regarding the histological parameters, usCD163 significantly correlated with the activity index (AI) and the individual active lesions (with the exception of fibrinoid necrosis), but not with chronicity index or any chronic lesion (Fig. 1). In addition, the level of usCD163 was higher in patients with proliferative LN compared to those with class II or isolated class V LN (Fig. 2). When evaluating the capacity of different variables to discriminate patients with a high AI (≥9), usCD163 outperformed classical clinical or immunological variables, with an area under the curve of 0.71 (95% CI, 0.55-0.86; p = 0.01). At a cutoff of 313 ng/mmol (Youden Index = 0.42), usCD163 had a sensitivity of 88.2% and specificity of 46% to identify patients with a high AI. Patients with an elevated level of usCD163 (≥313 ng/mmol) had higher 24-h proteinuria (4.41 ± 3.4 vs. 1.36 ± 1.74 g/day, p < 0.001), higher AI [10 (IQR: 6-12) vs. 3.5 (IQR: 0-6), p < 0.001] and more frequently class IV LN (48.1% vs. 12.5%, p = 0.02), compared to those with low levels of usCD163. In addition, 4 patients underwent repeat kidney biopsy post-induction therapy. In these patients, serial monitoring showed a normalization of usCD163 levels that paralleled a decrease in both proteinuria and AI. Conclusion Urinary soluble CD163 is a promising non-invasive biomarker for glomerular inflammation and could be used to evaluate histologic activity in patients with LN.

Breast cancer clinical outcomes and tumor immune microenvironment: cross-dialogue of multiple epigenetic modification profiles.

The discovery of RNA methylation alterations associated with cancer holds promise for their utilization as potential biomarkers in cancer diagnosis, prognosis, and prediction. RNA methylation has been found to impact the immunological microenvironment of tumors, but the specific role of methylation-related genes (MRGs), particularly in breast cancer (BC), the most common cancer among women globally, within the tumor microenvironment remains unknown. In this study, we obtained data from TCGA and GEO databases to investigate the expression patterns of MRGs in both genomic and transcriptional domains in BC. By analyzing the data, we identified two distinct genetic groupings that were correlated with clinicopathological characteristics, prognosis, degree of TME cell infiltration, and other abnormalities in MRGs among patients. Subsequently, an MRG model was developed to predict overall survival (OS) and its accuracy was evaluated in BC patients. Additionally, a highly precise nomogram was created to enhance the practical usability of the MRG model. In low-risk groups, we observed lower TBM values and higher TIDE scores. We further explored how MRGs influence a patient's prognosis, clinically significant characteristics, response to therapy, and the TME. These risk signatures have the potential to improve treatment strategies for BC patients and could be applied in future clinical settings. Moreover, they may also be utilized to determine prognosis and biological features in these patients.

Lipidomics study of Liujunzi decoction in hyperlipidemia rats with spleen deficiency based on UPLC-Q-TOF/MS

Hyperlipidemia refers to the abnormal levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL-C) and high-density lipoprotein (HDL-C) in peripheral blood circulation. It is a predominant risk factor underlying cardiovascular and cerebrovascular diseases, including coronary heart disease and atherosclerosis. Furthermore, it is also one of the most prevalent chronic diseases globally. Liujunzi Decoction is the basic prescription for the treatment of spleen and stomach diseases. It can tonify the spleen and qi, remove dampness, and reduce turbidity. Moreover, it is also clinically used for the treatment of spleen deficiency hyperlipidemia. However, its metabolites and therapeutic effect on spleen deficiency hyperlipidemia have not been comprehensively determined in vitro and in vivo. This study established a rat model of spleen deficiency hyperlipidemia by inducing starvation and satiety disorders, exhaustion swimming, and intragastric administration of the fat emulsion. To identify related metabolite changes and serum lipid composition, UPLC-Q-TOF-MS, PCA, and OPLS-DA lipidological methods were performed. The results demonstrated significant changes in rat's signs during the modeling process, which were consistent with the criteria for the syndrome differentiation of spleen deficiency in traditional Chinese medicine. Furthermore, this study identified 100 potential biomarkers in rat serum, of which 52 were associated with lipid synthesis, such as LPC, PC, PI, PE, PA, Cer, SM, etc. The pathways involved were glycerol phospholipid, sphingomyelin, and glycerol ester metabolisms. After the Liujunzi decoction intervention, 56 potential biomarkers were observed in the high-dose group, alleviating the metabolic spectrum imbalance by reducing metabolite levels. In addition, metabolic pathway disturbances were markedly improved. This study provides references for future studies on Liujunzi decoction and furnishes essential data for assessing the relationships between chemical constituents and pharmacological activities of Liujunzi decoction.

Evaluation of tauroursodeoxycholic acid in liver cells' cultures by MEKC: Initial hints to comprehend its role in diabetes mellitus of obese individuals.

Genetic factors, diet, lifestyle, and other factors lead to various complications in the body, such as obesity and other chronic diseases. The inflammatory state caused by excessive accumulation of body fat affects the pathways related to the control of glycemic homeostasis, leading to a high demand for insulin, to subsequent failure of stressed β cells, and development of type 2 diabetes mellitus (T2DM). The study of new endocrine signalers, such as bile acids (BAs), becomes necessary as it allows the development of alternatives for T2DM treatment. In this work, a methodology was developed to quantify tauroursodeoxycholic BA (TUDCA) in liver cells of the HepG2 strain treated in hyperlipidic medium. This BA helps to improve insulin clearance by increasing the expression of the insulin-degrading enzyme, restoring sensitivity to this hormone, and making it viable for treating T2DM. Herein, a targeted metabolomic method for TUDCA determination in extracellular medium of hepatocyte matrices by micellar electrokinetic chromatography-UV was optimized, validated, and applied. The optimized background electrolyte was composed of 40mmol/L sodium cholate and 30mmol/L sodium tetraborate at pH 9.0. The following figures of merit were evaluated: linearity, limit of quantification, limit of detection, accuracy, and precision. Data obtained with the validated electrophoretic method showed a self-stimulation of TUDCA production in media supplemented only with BA. On the other hand, TUDCA concentration was reduced in the hyperlipidic medium. This suggests that, in these media, the effect of TUDCA is reduced, such as self-stimulated production and consequent regulation of glycemic homeostasis. Therefore, the results reinforce the need for investigating TUDCA as a potential T2DM biomarker as well as its use to treat several comorbidities, such as obesity and diabetes mellitus.

Identification of established and novel extracellular matrix components in glioblastoma as targets for angiogenesis and prognosis.

Glioblastomas (GBM) are aggressive tumors known for their heterogeneity, rapid proliferation, treatment resistance, and extensive vasculature. Angiogenesis, the formation of new vessels, involves endothelial cell (EC) migration and proliferation. Various extracellular matrix (ECM) molecules regulate EC survival, migration, and proliferation. Culturing human brain EC (HBMEC) on GBM-derived ECM revealed a decrease in EC numbers compared to controls. Through in silico analysis, we explored ECM gene expression differences between GBM and brain normal glia cells and the impact of GBM microenvironment on EC ECM transcripts. ECM molecules such as collagen alpha chains (COL4A1, COL4A2, p < 0.0001); laminin alpha (LAMA4), beta (LAMB2), and gamma (LAMC1) chains (p < 0.0005); neurocan (NCAN), brevican (BCAN) and versican (VCAN) (p < 0.0005); hyaluronan synthase (HAS) 2 and metalloprotease (MMP) 2 (p < 0.005); MMP inhibitors (TIMP1-4, p < 0.0005), transforming growth factor beta-1 (TGFB1) and integrin alpha (ITGA3/5) (p < 0.05) and beta (ITGB1, p < 0.0005) chains showed increased expression in GBM. Additionally, GBM-influenced EC exhibited elevated expression of COL5A3, COL6A1, COL22A1 and COL27A1 (p < 0.01); LAMA1, LAMB1 (p < 0.001); fibulins (FBLN1/2, p < 0.01); MMP9, HAS1, ITGA3, TGFB1, and wingless-related integration site 9B (WNT9B) (p < 0.01) compared to normal EC. Some of these molecules: COL5A1/3, COL6A1, COL22/27A1, FBLN1/2, ITGA3/5, ITGB1 and LAMA1/B1 (p < 0.01); NCAN, HAS1, MMP2/9, TIMP1/2 and TGFB1 (p < 0.05) correlated with GBM patient survival. In conclusion, this study identified both established and novel ECM molecules regulating GBM angiogenesis, suggesting NCAN and COL27A1 are new potential prognostic biomarkers for GBM.

Causal roles and clinical utility of cardiovascular proteins in colorectal cancer risk: a multi-modal study integrating mendelian randomization, expression profiling, and survival analysis.

This comprehensive investigation delved into the intricate causal interplay existing between cardiovascular-related plasma proteins and the susceptibility to colorectal cancer, leveraging the robust framework of Mendelian randomization, and employed expression profiling and survival analysis to unravel the latent clinical worth embedded within pertinent gene expressions. Protein quantitative trait loci (pQTLs) of 85 cardiovascular proteins were employed as instrumental variables to investigate the causal relationship between proteins and CRC risk using a Mendelian randomization approach. Causal inferences were graded as strong, intermediate or weak based on statistical checks. Drug-target MR examined VEGF receptors for their potential as therapeutic targets for colorectal cancer. Differential expression analysis, diagnostic ROC curves, and survival analyses were performed for identified proteins using RNA-seq data from The Cancer Genome Atlas (TCGA) colorectal cancer cohort. Using cis-pQTLs, LOX-1, VEGF-A and OPG were associated with increased CRC risk (strong evidence), while PTX3, TNF-R2 and MMP-7 were protective (strong evidence). Pan-pQTL analysis found MMP-10 increased risk (intermediate evidence) and ADM increased risk (weak evidence). Drug-target MR found VEGF R1 may be promising therapeutic targets. Differential expression analysis revealed seven genes encoding the identified proteins were dysregulated in tumors. ROC analysis showed five gene expression had high diagnostic accuracy. KM analysis showed four genes had prognostic value. This large-scale MR study implicates several cardiovascular proteins in CRC susceptibility and progression. Findings highlight roles for VEGF signaling and extracellular matrix regulation. Results nominate specific proteins as potential diagnostic biomarkers or therapeutic targets warranting further investigation.

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis

BackgroundOsteoporosis (OP), the “silent epidemic” of our century, poses a significant challenge to public health, predominantly affecting postmenopausal women and the elderly. It evolves from mild symptoms to pronounced severity, stabilizing eventually. Unique among OP’s characteristics is the altered metabolic profile of affected cells, particularly in pyrimidine metabolism (PyM), a crucial pathway for nucleotide turnover and pyrimidine decomposition. While metabolic adaptation is acknowledged as a therapeutic target in various diseases, the specific role of PyM genes (PyMGs) in OP’s molecular response remains to be clarified.MethodsIn pursuit of elucidating and authenticating PyMGs relevant to OP, we embarked on a comprehensive bioinformatics exploration. This entailed the integration of Weighted Gene Co-expression Network Analysis (WGCNA) with a curated list of 37 candidate PyMGs, followed by the examination of their biological functions and pathways via Gene Set Variation Analysis (GSVA). The Least Absolute Shrinkage and Selection Operator (LASSO) technique was harnessed to identify crucial hub genes. We evaluated the diagnostic prowess of five PyMGs in OP detection and explored their correlation with OP’s clinical traits, further validating their expression profiles through independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).ResultsOur analytical rigor unveiled five PyMGs—IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N—with significant ties to OP. A deeper dive into their biological functions highlighted their roles in estrogen response modulation, cytosolic calcium ion concentration regulation, and GABAergic synaptic transmission. Remarkably, these PyMGs emerged as potent diagnostic biomarkers for OP, distinguishing affected individuals with substantial accuracy.ConclusionsThis investigation brings to light five PyMGs intricately associated with OP, heralding new avenues for biomarker discovery and providing insights into its pathophysiological underpinnings. These findings not only deepen our comprehension of OP’s complexity but also herald the advent of more refined diagnostic and therapeutic modalities.

The lesion core extent modulates the impact of early perfusion mismatch imaging on outcome variability after thrombectomy in stroke.

Despite profitable group effects on functional outcomes after mechanical thrombectomy (MT) in large vessel occlusion (LVO), many patients with successful reperfusion show a non-favorable long-term outcome, highlighting the necessity to identify potential biomarkers predicting outcome variability. In this regard, the role of perfusion mismatch imaging for outcome variability in the early time window within 6 h after symptom onset is a matter of debate. We attempted to investigate under which conditions early perfusion mismatch imaging accounts for variability in functional outcomes after mechanical thrombectomy. In a retrospective single-center study, we examined 190 consecutive patients with LVO who were admitted to the Medical Center Lübeck within 6 h after symptom onset, all of whom underwent MT. Perfusion mismatch was quantified by applying the Alberta Stroke Program Early CT score (ASPECTS) on CT-measured cerebral blood flow (CBF-ASPECTS) and subtracting it from an ASPECTS application on cerebral blood volume (CBV-ASPECTS), i.e., ASPECTS mismatch. Using multivariate ordinal regression models, associations between ASPECTS mismatch and modified Rankin Scale (mRS) after 90 days were assessed. Furthermore, the interaction between ASPECTS mismatch and the core lesion volume was calculated to evaluate conditional associations. ASPECTS mismatch did not correlate with functional outcomes when corrected for multiple influencing covariables. However, interactions between ASPECTS mismatch and CBV-ASPECTS [OR: 1.12 (1.06-1.18), p-value < 0.001], as well as NCCT-ASPECTS [OR: 1.15 (1.06-1.25), p-value < 0.001], did show a significant association with functional outcomes. Model comparisons revealed that, profoundly, in patients with large core lesion volumes (CBV-ASPECTS < 6 or NCCT-ASPECTS < 6), perfusion mismatch showed a negative correlation with the mRS. Perfusion mismatch imaging within the first 6 h of symptom onset provides valuable insights into the outcome variability of LVO stroke patients receiving thrombectomy but only in patients with large ischemic core lesions.

Investigating the Z-scan technique for quantifying circulating cell-free DNA (ccfDNA) extracted from blood plasma as a potential biomarker for various cancers

The Z-scan technique is a nonlinear optical method that has found applications in characterizing various materials, particularly those exhibiting nonlinear optical response (NLOR). This study applies the continuous wave (CW) Z-scan technique to examine the NLOR in terms of the nonlinear optical phase shifts (ΔΦ0 ) exhibited by the ccfDNA extracted from blood plasma samples collected from a group constituting 30 cancer-diagnosed patients and another group constituting 30 non-diagnosed individuals. The cancer group exhibited significantly higher ΔΦ0 versus incident power slopes compared to the non-cancer group (0.34 versus 0.12) providing a clear distinction between the two groups. The receiver operating characteristic (ROC) curve analysis of the results indicates a clear separation between cancer and non-cancer groups, along with a 94% accuracy rate of the data. The Z-scan results are corroborated by spectrophotometric analysis, revealing a consistent trend in the concentration values of ccfDNA samples extracted from both cancerous and non-cancerous samples, measuring 3.24 and 1.41 respectively. Additionally, more sensitive fluorometric analyses of the respective samples demonstrate significantly higher concentrations of ccfDNA in the cancer group, further affirming the correlation with the Z-scan results. The study suggests that the Z-scan technique holds promise as an effective method for cancer detection, potentially contributing to improved oncology diagnosis and prognosis in the future.

Methylation-regulated tumor suppressor gene PDE7B promotes HCC invasion and metastasis through the PI3K/AKT signaling pathway.

Hepatocellular carcinoma (HCC) has a high mortality rate, and the mechanisms underlying tumor development and progression remain unclear. However, inactivated tumor suppressor genes might play key roles. DNA methylation is a critical regulatory mechanism for inactivating tumor suppressor genes in HCC. Therefore, this study investigated methylation-related tumor suppressors in HCC to identify potential biomarkers and therapeutic targets. We assessed genome-wide DNA methylation in HCC using whole genome bisulfite sequencing (WGBS) and RNA sequencing, respectively, and identified the differential expression of methylation-related genes, and finally screened phosphodiesterase 7B (PDE7B) for the study. The correlation between PDE7B expression and clinical features was then assessed. We then analyzed the changes of PDE7B expression in HCC cells before and after DNA methyltransferase inhibitor treatment by MassArray nucleic acid mass spectrometry. Furthermore, HCC cell lines overexpressing PDE7B were constructed to investigate its effect on HCC cell function. Finally, GO and KEGG were applied for the enrichment analysis of PDE7B-related pathways, and their effects on the expression of pathway proteins and EMT-related factors in HCC cells were preliminarily explored. HCC exhibited a genome-wide hypomethylation pattern. We screened 713 hypomethylated and 362 hypermethylated mCG regions in HCC and adjacent normal tissues. GO analysis showed that the main molecular functions of hypermethylation and hypomethylation were "DNA-binding transcriptional activator activity" and "structural component of ribosomes", respectively, whereas KEGG analysis showed that they were enriched in "bile secretion" and "Ras-associated protein-1 (Rap1) signaling pathway", respectively. PDE7B expression was significantly down-regulated in HCC tissues, and this low expression was negatively correlated with recurrence and prognosis of HCC. In addition, DNA methylation regulates PDE7B expression in HCC. On the contrary, overexpression of PDE7B inhibited tumor proliferation and metastasis in vitro. In addition, PDE7B-related genes were mainly enriched in the PI3K/ATK signaling pathway, and PDE7B overexpression inhibited the progression of PI3K/ATK signaling pathway-related proteins and EMT. PDE7B expression in HCC may be regulated by promoter methylation. PDE7B can regulate the EMT process in HCC cells through the PI3K/AKT pathway, which in turn affects HCC metastasis and invasion.

Inflammatory cytokines and their potential role in kidney stone disease: a Mendelian randomization study.

Previous studies have reported a complex relationship between inflammatory cytokines and kidney stone disease (KSD). The purpose of this paper is to investigate the potential causal impact of inflammatory cytokines on KSD by Mendelian randomization (MR) analysis. In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between inflammatory cytokines and kidney stone disease. Utilizing GWAS summary data of inflammatory cytokines and KSD, we performed the first two-sample MR analysis. Genetic variants in GWASs related to inflammatory cytokines were employed as instrumental variables (IVs). The data on cytokines were derived from 14,824 participants and analyzed by utilizing the Olink Target-96 Inflammation Panel. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Reverse MR analysis, Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. 91 cytokines were enrolled in the MR analysis after strict quality control of IV. The IVW analysis revealed 2 cytokines as risk factors for KSD: Cystatin D (OR 1.06, 95% CI 1.01-1.11), Fibroblast growth factor 5 (OR 1.06, 95% CI 1.00-1.12), suggesting they are positively associated with the occurrence of kidney stones. We also found 3 protective associations between cytokines and KSD: Artemin (OR 0.86, 95% CI 0.78-0.96), T-cell surface glycoprotein CD6 isoform (OR 0.92, 95% CI 0.88-0.98), STAM-binding protein (OR 0.83, 95% CI 0.69-0.99). There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our MR Egger's intercept test, Cochrane Q-test, and MR-PRESSO, which were all > 0.05. Our study explored a variety of inflammatory cytokines related to KSD through MR analysis, which validated several previous findings and provided some new potential biomarkers for KSD. However, the findings require further investigation to validate their exact functions in the pathogenesis and evolution of KSD.

CYP17A1 Network Analysis in Ovarian Serous Cystadenocarcinoma for Retrieval of Polycystic ovaries Targets

Background/Aims: CYP17A1 is great metabolic switch for androgen overproduction which is hallmark of polycystic ovary syndrome (PCOS)initiation and progression. There is an urgent need to determine CYP17A1 mediated set of metabolic therapeutic targets for PCOS to control androgen synthesis with wide range of molecular options. Methodology: We apply rational in silico approach for determination of PCOS comprehensive set of drug targets. First, we retrieve CYP17A1 network dataset from STRING database (https://string-db.org/) by querying CYP17A1 name that gives us updated 30 nodes containing network with unique options of enrichment analysis and module extraction. The enrichment analysis determines CYP17A1 network involvement in steroidogenesis process with carcinogenesis and drug metabolism. We select ovarian serous cystadenocarcinoma dataset from cBioPortal server (https://www.cbioportal.org/) for CYP17A1 network differential analysis. Results: In this study, several steroid synthesis pathway members showed overexpression including SRD5A1, AKR1C3, CYP11B1, CYP11B2, CYP7A1, AKR1C1, AKR1D1, CYP7B1, CYP21A2, POR and HSD17B8 and are ideal biomarkers that provide cell cycle energy requirements for ovarian carcinoma. Few anti-androgenic members such as HSD17B2, STS, SULT2B1 and CYB5A showed down regulation that predicts the impact of hyper androgenemia on carcinogenesis. Drug metabolism components also showed up regulation which can be potential biomarkers for drug resistance in chemotherapies. Conclusion: Our work suggests androgen and its synthesis pathway paramount in tumorigenesis and is an excellent therapeutic target in ovarian carcinoma. In future, validation of CYP17A1 network as a signature in both ovarian serous cystadenocarcinoma and PCOS dataset may lead to novel shared therapeutic combinations and tremendous syndrome-syndrome molecular linkage for personalized medicine.