The issues and challenges with cancer biomarkers.

A biomarker is a measurable indicator used to distinguish precisely/objectively either normal biological state/pathological condition/response to a specific therapeutic intervention. The use of novel molecular biomarkers within evidence-based medicine may improve the diagnosis/treatment of disease, improve health outcomes, and reduce the disease's socio-economic impact. Presently cancer biomarkers are the backbone of therapy, with greater efficacy and better survival rates. Cancer biomarkers are extensively used to treat cancer and monitor the disease's progress, drug response, relapses, and drug resistance. The highest percent of all biomarkers explored are in the domain of cancer. Extensive research using various methods/tissues is carried out for identifying biomarkers for early detection, which has been mostly unsuccessful. The quantitative/qualitative detection of various biomarkers in different tissues should ideally be done in accordance with qualification rules laid down by the Early Detection Research Network (EDRN), Program for the Assessment of Clinical Cancer Tests (PACCT), and National Academy of Clinical Biochemistry. Many biomarkers are presently under investigation, but lacunae lie in the biomarker's sensitivity and specificity. An ideal biomarker should be quantifiable, reliable, of considerable high/low expression, correlate with the outcome progression, cost-effective, and consistent across gender and ethnic groups. Further, we also highlight that these biomarkers' application remains questionable in childhood malignancies due to the lack of reference values in the pediatric population. The development of a cancer biomarker stands very challenging due to its complexity and sensitivity/resistance to the therapy. In past decades, the cross-talks between molecular pathways have been targeted to study the nature of cancer. To generate sensitive and specific biomarkers representing the pathogenesis of specific cancer, predicting the treatment responses and outcomes would necessitate inclusion of multiple biomarkers.

A Scoping Review Investigating the "Gene-Dosage Theory" of Mitochondrial DNA in the Healthy Skeletal Muscle.

This review provides an overview of the evidence regarding mtDNA and valid biomarkers for assessing mitochondrial adaptions. Mitochondria are small organelles that exist in almost all cells throughout the human body. As the only organelle, mitochondria contain their own DNA, mitochondrial DNA (mtDNA). mtDNA-encoded polypeptides are subunits of the enzyme complexes in the electron transport chain (ETC) that are responsible for production of ATP to the cells. mtDNA is frequently used as a biomarker for mitochondrial content, since changes in mitochondrial volume are thought to induce similar changes in mtDNA. However, some exercise studies have challenged this "gene-dosage theory", and have indicated that changes in mitochondrial content can adapt without changes in mtDNA. Thus, the aim of this scoping review was to summarize the studies that used mtDNA as a biomarker for mitochondrial adaptions and address the question as to whether changes in mitochondrial content, induce changes in mtDNA in response to aerobic exercise in the healthy skeletal muscle. The literature was searched in PubMed and Embase. Eligibility criteria included: interventional study design, aerobic exercise, mtDNA measurements reported pre- and postintervention for the healthy skeletal muscle and English language. Overall, 1585 studies were identified. Nine studies were included for analysis. Eight out of the nine studies showed proof of increased oxidative capacity, six found improvements in mitochondrial volume, content and/or improved mitochondrial enzyme activity and seven studies did not find evidence of change in mtDNA copy number. In conclusion, the findings imply that mitochondrial adaptions, as a response to aerobic exercise, can occur without a change in mtDNA copy number.

Changes in the salivary metabolome in patients with chronic erosive gastritis.

INTRODUCTION: Chronic erosive gastritis (CEG) is closely related to gastric cancer, which requires early diagnosis and intervention. The invasiveness and discomfort of electronic gastroscope have limited its application in the large-scale screening of CEG. Therefore, a simple and noninvasive screening method is needed in the clinic. OBJECTIVES: The aim of this study is to screen potential biomarkers that can identify diseases from the saliva samples of CEG patients using metabolomics. METHODS: Saliva samples from 64 CEG patients and 30 healthy volunteers were collected, and metabolomic analysis was performed using UHPLC-Q-TOF/MS in the positive and negative ion modes. Statistical analysis was performed using both univariate (Student's t-test) and multivariate (orthogonal partial least squares discriminant analysis) tests. Receiver operating characteristic (ROC) analysis was conducted to determine significant predictors in the saliva of CEG patients. RESULTS: By comparing the saliva samples from CEG patients and healthy volunteers, 45 differentially expressed metabolites were identified, of which 37 were up-regulated and 8 were down-regulated. These differential metabolites were related to amino acid, lipid, phenylalanine metabolism, protein digestion and absorption, and mTOR signaling pathway. In the ROC analysis, the AUC values of 7 metabolites were greater than 0.8, among which the AUC values of 1,2-dioleoyl-sn-glycoro-3-phosphodylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phospholine (SOPC) were greater than 0.9. CONCLUSIONS: In summary, a total of 45 metabolites were identified in the saliva of CEG patients. Among them, 1,2-dioleoyl-sn-glycoro-3-phosphorylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phosphorine (SOPC) might have potential clinical application value.

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

BACKGROUND: Extracellular vesicles (EV) are extensively studied in human body fluids as potential biomarkers for numerous diseases. Major impediments of EV-based biomarker discovery include the specificity and reproducibility of EV sample preparation as well as intensive manual labor. We present an automated liquid handling workstation for the density-based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers. RESULTS: Automated versus manual density-based separation of trackable recombinant extracellular vesicles (rEV) spiked in PBS significantly reduces variability in rEV recovery as quantified by fluorescent nanoparticle tracking analysis and ELISA. To validate automated density-based EV separation from complex body fluids, including blood plasma and urine, we assess reproducibility, recovery, and specificity by mass spectrometry-based proteomics and transmission electron microscopy. Method reproducibility is the highest in the automated procedure independent of the matrix used. While retaining (in urine) or enhancing (in plasma) EV recovery compared to manual liquid handling, automation significantly reduces the presence of body fluid specific abundant proteins in EV preparations, including apolipoproteins in plasma and Tamm-Horsfall protein in urine. CONCLUSIONS: In conclusion, automated liquid handling ensures cost-effective EV separation from human body fluids with high reproducibility, specificity, and reduced hands-on time with the potential to enable larger-scale biomarker studies.

Integrated bulk and single-cell RNA-sequencing reveals SPOCK2 as a novel biomarker gene in the development of congenital pulmonary airway malformation.

BACKGROUND: Congenital pulmonary airway malformation (CPAM) is the most frequent pulmonary developmental malformation and the pathophysiology remains poorly understood. This study aimed to identify the characteristic gene expression patterns and the marker genes essential to CPAM. METHODS: Tissues from the cystic area displaying CPAM and the area of normal appearance were obtained during surgery. Bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) were performed for integrating analysis. Iterative weighted gene correlation network analysis (iWGCNA) was used to identify specifically expressed genes to CPAM. RESULTS: In total, 2074 genes were significantly differentially expressed between the CPAM and control areas. Of these differentially expressed genes (DEGs), 1675 genes were up-regulated and 399 genes were down-regulated. Gene ontology analysis revealed these DEGs were specifically enriched in ciliated epithelium and involved in immune response. We also identified several CPAM-related modules by iWGCNA, among them, P15_I4_M3 module was the most influential module for distinguishing CPAMs from controls. By combining the analysis of the expression dataset from RNA-seq and scRNA-seq, SPOCK2, STX11, and ZNF331 were highlighted in CPAM. CONCLUSIONS: Through our analysis of expression datasets from both scRNA-seq and bulk RNA-seq of tissues obtained from patients with CPAM, we identified the characteristic gene expression patterns associated with the condition. Our findings suggest that SPOCK2 could be a potential biomarker gene for the diagnosis and therapeutic target in the development of CPAM, whereas STX11 and ZNF331 might serve as prognostic markers for this condition. Further investigations with larger samples and function studies are necessary to confirm the involvement of these genes in CPAM.

The necroptosis related gene LGALS3 can be used as a biomarker for the adverse progression from chronic HBV infection to HCC.

The number of patients with hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) infection remains large, despite the remarkable effectiveness of antiviral drugs and vaccines for HBV in preventing and treating HBV infection. Necroptosis is closely related to the occurrence of inflammation, clearance of viral infection, and tumor progression. Presently, little is known about the changes in necroptosis-related genes in the progression from chronic HBV infection (CHI) to HBV-related hepatic fibrosis (HBV-HF) and HBV-related hepatocellular carcinoma (HBV-HCC). In this study, Cox regression analysis was performed using GSE14520 chip data and a necroptosis-related genes survival prognosis score (NRGPS) was established for HBV-HCC patients. NRGPS was constructed using three model genes (G6PD, PINK1 and LGALS3), and verified by data sequencing in the TCGA database. The HBV-HCC cell model was established by transfection of pAAV/HBV1.2C2, constructed by homologous recombination, into HUH7 and HEPG2 cells. The expression levels of G6PD, PINK1, and LGALS3 were detected using RT-qPCR. We further analyzed the expression of the model genes in GSE83148, GSE84044, and GSE14520 and found that LGALS3 was consistently highly expressed in CHI, high fibrosis score and high NRGPS. In addition, immune microenvironment analysis showed that LGALS3 was not only associated with the infiltration of regulatory T cells in the immune microenvironment but also with expression of CCL20 and CCR6. The expression levels of model genes, FOXP3 and CCR6, were analyzed using RT-qPCR in peripheral blood mononuclear cells of 31 hepatitis B surface antibody positive patients, 30 CHI, 21 HBV-HF, and 20 HBV-HCC. In further cell-model experiments, we analyzed the expression of CCL20 by RT-qPCR and the changes in cell proliferation and migration by CCK8 and transwell assays, respectively, in HBV-HCC cell models after LGALS3 knockdown. The findings of this study suggest that LGALS3 could be a biomarker for adverse progression following chronic HBV infection and may also be involved in the regulation of the immune microenvironment, making it a potential therapeutic target.

Epigenetic reprogramming of Runx3 reinforces CD8 + T-cell function and improves the clinical response to immunotherapy.

BACKGROUND: Checkpoint blockade immunotherapy, represented by PD-1 or PD-L1 antibody treatment, has been of tremendous success in clinical practice. However, the low clinical response rate and lack of biomarkers for prediction of the immune response limit the clinical application of anti-PD-1 immunotherapy. Our recent work showed that a combination of low-dose decitabine and PD-1-ab significantly improved the complete response (CR) rate of cHL patients from 32 to 71%, which indicates that there is a significant correlation between epigenetic regulation and the clinical response to immunotherapy. METHODS: We recruited two groups of Hodgkin lymphoma patients who were treated with anti-PD-1 and DAC+anti-PD-1. CD8+ T cells were isolated from the patients' peripheral blood, DNA methylation was analyzed by EPIC, the expression profile was analyzed by RNA-seq, and multigroup analysis was performed with IPA and GSEA functional annotations. We explored the effect of DAC on the function of CD8+ T cells in the blood, spleen, tumor and lymph nodes using a mouse model. Furthermore, we explored the function of Tils in the tumor microenvironment. Then, we constructed Runx3-knockout mice to confirm the T-cell-specific function of Runx3 in CD8+ T cells and analyzed various subtypes of T cells and cytokines using mass cytometry (CyTOF). RESULTS: Multiomics analysis identified that DNA methylation reprogramming of Runx3 was a crucial mediator of CD8+ T-cell function. Multiomics data showed that reversal of methylation of the Runx3 promoter promoted the infiltration of CD8+ TILs and mitigated the exhaustion of CD8+ T cells. Furthermore, experiments on tissue-specific Runx3-knockout mice showed that Runx3 deficiency reduced CD8+ T infiltration and the differentiation of effector T and memory T cells. Furthermore, Runx3 deficiency significantly decreased CCR3 and CCR5 levels. Immunotherapy experiments in Runx3 conditional knockout mice showed that DAC could not reverse the resistance of anti-PD-1 in the absence of Runx3. Moreover, both our clinical data and data from TISIDB showed that Runx3 could be a potential biomarker for immunotherapy to predict the clinical response rate. CONCLUSION: We demonstrate that the DNA methylation of Runx3 plays a critical role in CD8+ T-cell infiltration and differentiation during decitabine-primed PD-1-ab immunotherapy, which provides a supporting mechanism for the essential role of epiregulation in immunotherapy.

The N-Glycosylation of Total Plasma Proteins and IgG in Atrial Fibrillation.

Atrial fibrillation is a disease with a complex pathophysiology, whose occurrence and persistence are caused not only by aberrant electrical signaling in the heart, but by the development of a susceptible heart substrate. These changes, such as the accumulation of adipose tissue and interstitial fibrosis, are characterized by the presence of inflammation. N-glycans have shown great promise as biomarkers in different diseases, specifically those involving inflammatory changes. To assess the changes in the N-glycosylation of the plasma proteins and IgG in atrial fibrillation, we analyzed the N-glycosylation of 172 patients with atrial fibrillation, before and six months after a pulmonary vein isolation procedure, with 54 cardiovascularly healthy controls. An analysis was performed using ultra-high-performance liquid chromatography. We found one oligomannose N-glycan structure from the plasma N-glycome and six IgG N-glycans, mainly revolving around the presence of bisecting N-acetylglucosamine, that were significantly different between the case and control groups. In addition, four plasma N-glycans, mostly oligomannose structures and a derived trait that was related to them, were found to be different in the patients who experienced an atrial fibrillation recurrence during the six-month follow-up. IgG N-glycosylation was extensively associated with the CHA2DS2-VASc score, confirming its previously reported associations with the conditions that make up the score. This is the first study looking at the N-glycosylation patterns in atrial fibrillation and warrants further investigation into the prospect of glycans as biomarkers for atrial fibrillation.

Plasma Cytokeratin-18 Fragment Level Reflects the Metabolic Phenotype in Obesity.

There is growing interest in the non-invasive identification and monitoring of the outcome of liver damage in obese patients. Plasma cytokeratin-18 (CK-18) fragment levels correlate with the magnitude of hepatocyte apoptosis and have recently been proposed to independently predict the presence of non-alcoholic steatohepatitis (NASH). The aim of the study was to analyze the associations of CK-18 with obesity and related complications: insulin resistance, impaired lipid metabolism and the secretion of hepatokines, adipokines and pro-inflammatory cytokines. The study involved 151 overweight and obese patients (BMI 25-40), without diabetes, dyslipidemia or apparent liver disease. Liver function was assessed based on alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and the fatty liver index (FLI). CK-18 M30 plasma levels, FGF-21, FGF-19 and cytokines were determined by ELISA. CK-18 values >150 U/l were accompanied by high ALT, GGT and FLI, insulin resistance, postprandial hypertriglyceridemia, elevated FGF-21 and MCP-1 and decreased adiponectin. ALT activity was the strongest independent factor influencing high CK-18 plasma levels, even after an adjustment for age, sex and BMI [ß coefficient (95%CI): 0.40 (0.19-0.61)]. In conclusion, the applied CK-18 cut-off point at 150 U/l allows to distinguish between two metabolic phenotypes in obesity.

Biofluid Biomarkers in the Prognosis of Amyotrophic Lateral Sclerosis: Recent Developments and Therapeutic Applications.

Amyotrophic lateral sclerosis is a neurodegenerative disease characterized by the degeneration of motor neurons for which effective therapies are lacking. One of the most explored areas of research in ALS is the discovery and validation of biomarkers that can be applied to clinical practice and incorporated into the development of innovative therapies. The study of biomarkers requires an adequate theoretical and operational framework, highlighting the "fit-for-purpose" concept and distinguishing different types of biomarkers based on common terminology. In this review, we aim to discuss the current status of fluid-based prognostic and predictive biomarkers in ALS, with particular emphasis on those that are the most promising ones for clinical trial design and routine clinical practice. Neurofilaments in cerebrospinal fluid and blood are the main prognostic and pharmacodynamic biomarkers. Furthermore, several candidates exist covering various pathological aspects of the disease, such as immune, metabolic and muscle damage markers. Urine has been studied less often and should be explored for its possible advantages. New advances in the knowledge of cryptic exons introduce the possibility of discovering new biomarkers. Collaborative efforts, prospective studies and standardized procedures are needed to validate candidate biomarkers. A combined biomarkers panel can provide a more detailed disease status.

The Potential of Fibroblast Activation Protein-Targeted Imaging as a Biomarker of Cardiac Remodeling and Injury.

PURPOSE OF REVIEW: Cardiovascular disease features adverse fibrotic processes within the myocardium, leading to contractile dysfunction. Activated cardiac fibroblasts play a pivotal role in the remodeling and progression of heart failure, but conventional diagnostics struggle to identify early changes in cardiac fibroblast dynamics. Emerging imaging methods visualize fibroblast activation protein (FAP) as a marker of activated fibroblasts, enabling non-invasive quantitative measurement of early cardiac remodeling. RECENT FINDINGS: Retrospective analysis of oncology patient cohorts has identified cardiac uptake of FAP radioligands in response to various cardiovascular conditions. Small scale studies in dedicated cardiac populations have revealed FAP upregulation in injured myocardium, wherein the area of upregulation predicts subsequent ventricle dysfunction. Recent studies have demonstrated that silencing of FAP-expressing fibroblasts can reverse cardiac fibrosis in disease models. The parallel growth of FAP-targeted imaging and therapy provides the opportunity for imaging-based monitoring and refinement of treatments targeting cardiac fibroblast activation.

Automatic Detection of Two Synovial Fluid Periprosthetic Joint Infection Biomarkers on an Integrated Microfluidic System.

Post-arthroplasty periprosthetic joint infection (PJI) is a serious ailment that can be difficult to diagnose. Herein, we developed a novel integrated microfluidic system (IMS) capable of detecting two common PJI biomarkers, alpha defensin human neutrophil peptide 1 (HNP-1) and C-reactive protein (CRP), from synovial fluid (SF). A magnetic bead-based one-aptamer-one-antibody assay was carried out automatically within 45 min on a single chip for simultaneous detection of both biomarkers at concentration ranges of 0.01-50 (HNP-1) and 1-100 (CRP) mg/L. It is the first report for utilizing these two biomarkers as targets to establish the new one-aptamer-one-antibody assay to detect PJI on-chip, and the aptamers demonstrated high specificity to their SF targets. As 20 clinical samples were correctly diagnosed with our IMS (verified by a common gold standard kit), it could serve as a promising tool for PJI diagnostics.

Artemisia annua L. (Sweet wormwood) leaf extract attenuates high-fat diet-induced testicular dysfunctions and improves spermatogenesis in obese rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Artemisia annua L., known as "sweet wormwood," is widely used in Egyptian folk medicine. Egyptians implement the aerial parts in the treatment of respiratory, digestive and sexual dysfunctions. However, the mechanism by which Artemisia annua improves testicular function is still being discovered. AIM OF THE STUDY: This study aimed to evaluate the modulatory effects of the crude leaf extract of Artemisia annua (AAE) on a high-fat diet induced testicular dysfunction in rats and compare it with the antilipolytic drug Orlistat. MATERIAL AND METHODS: Forty adult rats were randomly classified and assigned to four groups. The first group typically consumed a balanced diet and served as a negative control (GP1). A high-fat diet-induced obesity was applied to the other three groups for 12 weeks. A positive control remained on HFD for another 8 weeks, which is GP2. Other groups were administered for 8 consecutive weeks either with Orlistat (50 mg/kg body weight) or AAE (100 mg/kg body weight), which have been defined as GP3 and GP4, respectively. Testosterone (TST), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) were determined in the sera of all groups. In addition, the oxidant/antioxidant biomarkers such as protein carbonyl, malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT) activities, lactate dehydrogenase (LDH) and creatine kinase isoenzyme-B (CK-MB) were determined. An immunohistochemical stain with the apoptotic marker caspase-3 and the proliferating cell nuclear antigen (PCNA) were also investigated. RESULTS: In the testes of the obese group, the results showed hormonal imbalance, an increase in oxidative stress biomarkers and apoptosis. In the group treated with orlistat (GP3), noticeably more perturbations were noted. The obese rats that had been treated with AAE (GP4) showed a significantly reduced level of oxidative stress, hormonal balance restoration and reduced apoptosis. CONCLUSIONS: The crude leaf extract of A. annua is a potential herbal therapeutic for the treatment of obesity-related testicular dysfunction and the restoration of hormonal imbalance in obese rats.

The relationship between clinical phenotype and kallikrein-kinin bioregulation in different forms of arthritis.

OBJECTIVE: Patients with rheumatoid arthritis (RA) have shown increased levels of neutrophils generating kallikrein-kinin peptides in blood which are potent mediators of inflammation. This study investigated the association between the bioregulation of kinin-mediated inflammation with the clinical, quality of life, and imaging characteristics (e.g. ultrasonography) of different arthritides. METHODS: Patients with osteoarthritis (OA, n = 29), gout (n = 10) and RA (n = 8) were recruited and screened for clinical symptoms, quality of life, and ultrasonographical assessment of arthritis. Blood neutrophils were assessed for the expression of bradykinin receptors (B1R and B2R), kininogens and kallikreins by immunocytochemistry with visualization by bright field microscopy. Levels of plasma biomarkers were measured by ELISA and cytometric bead array. RESULTS: Quality of life (SF-36 domains and summary scores; including pain; and, HAQ) was similar across OA, gout and RA patients; with the exception of worse physical functioning scores between OA and gout patients. Synovial hypertrophy (on ultrasound) differed between groups (p = 0.001), and the dichotomised Power Doppler (PD) score of greater than or equal to 2 (PD-GE2) was marginally significant (p = 0.09). Plasma IL-8 were highest in patients with gout followed by RA and OA (both, P < 0.05). Patients with RA had higher plasma levels of sTNFR1, IL-1ß, IL-12p70, TNF and IL-6, compared to OA and gout patients (all, P < 0.05). Patients with OA had higher expression of K1B and KLK1 on blood neutrophils followed by RA and gout patients (both, P < 0.05). Bodily pain correlated with B1R expression on blood neutrophils (r = 0.334, p = 0.05), and inversely with plasma levels of CRP (r = -0.55), sTNFR1 (r = -0.352) and IL-6 (r = -0.422), all P < 0.05. Expression of B1R on blood neutrophils also correlated with Knee PD (r = 0.403) and PD-GE2 (r = 0.480), both P < 0.05. CONCLUSIONS: Pain levels and quality of life were similar between patients with OA, RA and gout with knee arthritis. Plasma inflammatory biomarkers and B1R expression on blood neutrophils correlated with pain. Targeting B1R to modulate the kinin-kallikrein system may pose as a new therapeutic target in the treatment of arthritis.

Extracellular vesicles from human plasma for biomarkers discovery: Impact of anticoagulants and isolation techniques.

Extracellular vesicles (EVs) isolated from plasma are increasingly recognized as promising circulating biomarkers for disease discovery and progression, as well as for therapeutic drug delivery. The scientific community underlined the necessity of standard operative procedures for the isolation and storage of the EVs to ensure robust results. The understanding of the impact of the pre-analytical variables is still limited and some considerations about plasma anticoagulants and isolation methods are necessary. Therefore, we performed a comparison study between EVs isolated by ultracentrifugation and by affinity substrate separation from plasma EDTA and sodium citrate. The EVs were characterized by Nano Tracking Analysis, Western Blot, cytofluorimetric analysis of surface markers, and lipidomic analysis. While anticoagulants did not significantly alter any of the analyzed parameters, the isolation methods influenced EVs size, purity, surface markers expression and lipidomic profile. Compared to ultracentrifugation, affinity substrate separation yielded bigger particles highly enriched in tetraspanins (CD9, CD63, CD81), fatty acids and glycerolipids, with a predominant LDL- and vLDL-like contamination. Herein, we highlighted that the isolation method should be carefully evaluated prior to study design and the need of standardized operative procedures for EVs isolation and application to biomarkers discovery.

Association between triglyceride glucose-related markers and the risk of metabolic-associated fatty liver disease: a cross-sectional study in healthy Chinese participants.

OBJECTIVES: This study aimed to evaluate the performance of the triglyceride glucose (TyG) index and its related markers in predicting metabolic-associated fatty liver disease (MAFLD) in healthy Chinese participants. DESIGN: This was a cross-sectional study. SETTING: The study was conducted at Health Management Department of the Affiliated Hospital of Xuzhou Medical University. PARTICIPANTS: A total of 20 922 asymptomatic Chinese participants (56% men) were enrolled. OUTCOME MEASURES: Hepatic ultrasonography was performed to diagnose MAFLD based on the latest diagnostic criteria. The TyG, TyG-body mass (TyG-BMI) and TyG-waist circumference indices were calculated and analysed. RESULTS: Compared with the lowest quartile of the TyG-BMI, the adjusted ORs and 95% CIs for MAFLD were 20.76 (14.54 to 29.65), 92.33 (64.61 to 131.95) and 380.87 (263.25 to 551.05) in the second, third and fourth quartiles, respectively. According to the subgroup analysis, the TyG-BMI in the female and the lean groups (BMI<23 kg/m2) showed the strongest predictive value, with optimal cut-off values for MAFLD of 162.05 and 156.31, respectively. The areas under the receiver operating characteristic curves in female and lean groups were 0.933 (95% CI 0.927 to 0.938) and 0.928 (95% CI 0.914 to 0.943), respectively, with 90.7% sensitivity and 81.2% specificity in female participants with MAFLD and 87.2% sensitivity and 87.1% specificity in lean participants with MAFLD. The TyG-BMI index demonstrated superior predictive ability for MAFLD compared with other markers. CONCLUSIONS: The TyG-BMI is an effective, simple and promising tool for predicting MAFLD, especially in lean and female participants.

Lymphocyte-C-reactive protein ratio with calf circumference could better predict survival of patients with non-metastatic cancer.

Systemic inflammatory responses caused by tumor cells play an important role in the occurrence and development of tumors. The aim of this study was to identify biomarkers that most accurately predict prognoses in patients with non-metastatic cancer and to evaluate their clinical significance when combined with muscle markers. This study retrospectively evaluated 2,797 cancer patients diagnosed with cancer at TNM stages I, II, and III. Lymphocyte-C-reactive protein ratio (LCR) in conjunction with calf circumference (CC) were used (or chosed) after evaluating the predictive value of 13 inflammatory marker combinations and five anthropometric indicators for patient outcomes using the C-index. The Kaplan-Meier method and Cox's proportional hazards regression modeling were used to analyze the individual and combined effects of these two potential biomarkers on overall survival. This study enrolled 1,604 men (57.3%) and 1,193 women (42.7%) with a mean age of 58.75 years. Among the 13 inflammatory nutritional indicators, the LCR was the most accurate predictor of prognoses in patients with non-metastatic cancer. After multifactorial adjustment, we found that low LCR had an adverse effect on overall survival (hazard ratio [HR]: 2.50; 95% confidence interval [CI]: 2.17, 2.88; P < 0.001). Low LCR combined with low CC was also shown to be an independent risk factor for poor overall survival (HR: 2.26; 95% CI: 1.80, 2.83; P < 0.001). Compared with LCR or CC alone, the combination of the two had greater prognostic value for patients with non-metastatic cancer. The LCR can be implemented as a useful biomarker to predict prognoses in patients with non-metastatic cancer. CC is the best anthropometric indicator of muscle loss in patients with non-metastatic cancer. The combination of LCR and CC can better predict the prognosis of patients with non-metastatic cancer, and can provide important information for clinicians to formulate diagnosis and treatment plans.

Identification of NETs-related biomarkers and molecular clusters in systemic lupus erythematosus.

Neutrophil extracellular traps (NETs) is an important process involved in the pathogenesis of systemic lupus erythematosus (SLE), but the potential mechanisms of NETs contributing to SLE at the genetic level have not been clearly investigated. This investigation aimed to explore the molecular characteristics of NETs-related genes (NRGs) in SLE based on bioinformatics analysis, and identify associated reliable biomarkers and molecular clusters. Dataset GSE45291 was acquired from the Gene Expression Omnibus repository and used as a training set for subsequent analysis. A total of 1006 differentially expressed genes (DEGs) were obtained, most of which were associated with multiple viral infections. The interaction of DEGs with NRGs revealed 8 differentially expressed NRGs (DE-NRGs). The correlation and protein-protein interaction analyses of these DE-NRGs were performed. Among them, HMGB1, ITGB2, and CREB5 were selected as hub genes by random forest, support vector machine, and least absolute shrinkage and selection operator algorithms. The significant diagnostic value for SLE was confirmed in the training set and three validation sets (GSE81622, GSE61635, and GSE122459). Additionally, three NETs-related sub-clusters were identified based on the hub genes' expression profiles analyzed by unsupervised consensus cluster assessment. Functional enrichment was performed among the three NETs subgroups, and the data revealed that cluster 1 highly expressed DEGs were prevalent in innate immune response pathways while that of cluster 3 were enriched in adaptive immune response pathways. Moreover, immune infiltration analysis also revealed that innate immune cells were markedly infiltrated in cluster 1 while the adaptive immune cells were upregulated in cluster 3. As per our knowledge, this investigation is the first to explore the molecular characteristics of NRGs in SLE, identify three potential biomarkers (HMGB1, ITGB2, and CREB5), and three distinct clusters based on these hub biomarkers.

Gut microbiota predicts the diagnosis of celiac disease in Saudi children.

BACKGROUND: Celiac disease (CeD) is a multisystem immune-mediated multifactorial condition strongly associated with the intestinal microbiota. AIM: To evaluate the predictive power of the gut microbiota in the diagnosis of CeD and to search for important taxa that may help to distinguish CeD patients from controls. METHODS: Microbial DNA from bacteria, viruses, and fungi, was isolated from mucosal and fecal samples of 40 children with CeD and 39 controls. All samples were sequenced using the HiSeq platform, the data were analyzed, and abundance and diversities were assessed. For this analysis, the predictive power of the microbiota was evaluated by calculating the area under the curve (AUC) using data for the entire microbiome. The Kruskal-Wallis test was used to evaluate the significance of the difference between AUCs. The Boruta logarithm, a wrapper built around the random forest classification algorithm, was used to identify important bacterial biomarkers for CeD. RESULTS: In fecal samples, AUCs for bacterial, viral, and fungal microbiota were 52%, 58%, and 67.7% respectively, suggesting weak performance in predicting CeD. However, the combination of fecal bacteria and viruses showed a higher AUC of 81.8 %, indicating stronger predictive power in the diagnosis of CeD. In mucosal samples, AUCs for bacterial, viral, and fungal microbiota were 81.2%, 58.6%, and 35%, respectively, indicating that mucosal bacteria alone had the highest predictive power. Two bacteria, Bacteroides intestinalis and Burkholderiales bacterium 1-1-47, in fecal samples and one virus, Human_endogenous _retrovirus_K, in mucosal samples are predicted to be "important" biomarkers, differentiating celiac from nonceliac disease groups. Bacteroides intestinalis is known to degrade complex arabinoxylans and xylan which have a protective role in the intestinal mucosa. Similarly, several Burkholderiales species have been reported to produce peptidases that hydrolyze gluten peptides, with the potential to reduce the gluten content of food. Finally, a role for Human_endogenous _retrovirus_K in immune-mediated disease such as CeD has been reported. CONCLUSION: The excellent predictive power of the combination of the fecal bacterial and viral microbiota with mucosal bacteria alone indicates a potential role in the diagnosis of difficult cases of CeD. Bacteroides intestinalis and Burkholderiales bacterium 1-1-47, which were found to be deficient in CeD, have a potential protective role in the development of prophylactic modalities. Further studies on the role of the microbiota in general and Human_endogenous _retrovirus_K in particular are needed.

Patient-derived head and neck cancer organoids allow treatment stratification and serve as a tool for biomarker validation and identification.

BACKGROUND: Organoids are in vitro three-dimensional structures that can be grown from patient tissue. Head and neck cancer (HNC) is a collective term used for multiple tumor types including squamous cell carcinomas and salivary gland adenocarcinomas. METHODS: Organoids were established from HNC patient tumor tissue and characterized using immunohistochemistry and DNA sequencing. Organoids were exposed to chemo- and radiotherapy and a panel of targeted agents. Organoid response was correlated with patient clinical response. CRISPR-Cas9-based gene editing of organoids was applied for biomarker validation. FINDINGS: A HNC biobank consisting of 110 models, including 65 tumor models, was generated. Organoids retained DNA alterations found in HNC. Comparison of organoid and patient response to radiotherapy (primary [n = 6] and adjuvant [n = 15]) indicated potential for guiding treatment options in the adjuvant setting. In organoids, the radio-sensitizing potential of cisplatin and carboplatin could be validated. However, cetuximab conveyed radioprotection in most models. HNC-targeted treatments were tested on 31 models, indicating possible novel treatment options with the potential for treatment stratification in the future. Activating PIK3CA mutations did not predict alpelisib response in organoids. Protein arginine methyltransferase 5 (PRMT5) inhibitors were identified as a potential treatment option for cyclin-dependent kinase inhibitor 2A (CDKN2A) null HNC. CONCLUSIONS: Organoids hold potential as a diagnostic tool in personalized medicine for HNC. In vitro organoid response to radiotherapy (RT) showed a trend that mimics clinical response, indicating the predictive potential of patient-derived organoids. Moreover, organoids could be used for biomarker discovery and validation. FUNDING: This work was funded by Oncode PoC 2018-P0003.