Pentraxin 3: A Main Driver of Inflammation and Immune System Dysfunction in the Tumor Microenvironment of Glioblastoma

Brain tumors are a heterogeneous group of brain neoplasms that are highly prevalent in individuals of all ages worldwide. Within this pathological framework, the most prevalent and aggressive type of primary brain tumor is glioblastoma (GB), a subtype of glioma that falls within the IV-grade astrocytoma group. The death rate for patients with GB remains high, occurring within a few months after diagnosis, even with the gold-standard therapies now available, such as surgery, radiation, or a pharmaceutical approach with Temozolomide. For this reason, it is crucial to continue looking for cutting-edge therapeutic options to raise patients' survival chances. Pentraxin 3 (PTX3) is a multifunctional protein that has a variety of regulatory roles in inflammatory processes related to extracellular matrix (ECM). An increase in PTX3 blood levels is considered a trustworthy factor associated with the beginning of inflammation. Moreover, scientific evidence suggested that PTX3 is a sensitive and earlier inflammation-related marker compared to the short pentraxin C-reactive protein (CRP). In several tumoral subtypes, via regulating complement-dependent and macrophage-associated tumor-promoting inflammation, it has been demonstrated that PTX3 may function as a promoter of cancer metastasis, invasion, and stemness. Our review aims to deeply evaluate the function of PTX3 in the pathological context of GB, considering its pivotal biological activities and its possible role as a molecular target for future therapies.

Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status

Current diagnostic algorithms are insufficient for the optimal clinical and therapeutic management of cutaneous spitzoid tumors, particularly atypical spitzoid tumors (AST). Therefore, it is crucial to identify new markers that allow for reliable and reproducible diagnostic assessment and can also be used as a predictive tool to anticipate the individual malignant potential of each patient, leading to tailored individual therapy. Using Reduced Representation Bisulfite Sequencing (RRBS), we studied genome-wide methylation profiles of a series of Spitz nevi (SN), spitzoid melanoma (SM), and AST. We established a diagnostic algorithm based on the methylation status of seven cg sites located in TETK4P2 (Tektin 4 Pseudogene 2), MYO1D (Myosin ID), and PMF1-BGLAP (PMF1-BGLAP Readthrough), which allows the distinction between SN and SM but is also capable of subclassifying AST according to their similarity to the methylation levels of Spitz nevi or spitzoid melanoma. Thus, our epigenetic algorithm can predict the risk level of AST and predict its potential clinical outcomes.

Overview of Antibiotic-Induced Nephrotoxicity

Drug-induced nephrotoxicity accounts for up to 60% of cases of acute kidney injury (AKI) in hospitalized patients and is associated with increased morbidity and mortality in both adults and children. Antibiotics are one of the most common causes of drug-induced nephrotoxicity. Mechanisms of antibiotic-induced nephrotoxicity include glomerular injury, tubular injury or dysfunction, distal tubular obstruction from casts, and acute interstitial nephritis (AIN) mediated by a type IV (delayed-type) hypersensitivity response. Clinical manifestations of antibiotic-induced nephrotoxicity include acute tubular necrosis (ATN), AIN, and Fanconi syndrome. Given the potential nephrotoxic effects of antibiotics on critically ill patients, the use of novel biomarkers can provide information to optimize dosing and duration of treatment and can help prevent nephrotoxicity when traditional markers, such as creatinine, are unreliable. Use of novel kidney specific biomarkers, such as cystatin C and urinary kidney injury molecule-1 (KIM-1), may result in earlier detection of AKI, dose adjustment, or discontinuation of antibiotic and development of nonnephrotoxic antibiotics.

Redox Status and Telomere-Telomerase System Biomarkers in Patients with Acute Myocardial Infarction Using a Principal Component Analysis: Is There a Link?

In the present study, we examined redox status parameters in arterial and venous blood samples, its potential to predict the prognosis of acute myocardial infarction (AMI) patients assessed through its impact on the comprehensive grading SYNTAX score, and its clinical accuracy. Potential connections between common blood biomarkers, biomarkers of redox status, leukocyte telomere length, and telomerase enzyme activity in the acute myocardial infarction burden were assessed using principal component analysis (PCA). This study included 92 patients with acute myocardial infarction. Significantly higher levels of advanced oxidation protein products (AOPP), superoxide anion (O2•-), ischemia-modified albumin (IMA), and significantly lower levels of total oxidant status (TOS) and total protein sulfhydryl (SH-) groups were found in arterial blood than in the peripheral venous blood samples, while biomarkers of the telomere-telomerase system did not show statistical significance in the two compared sample types (p = 0.834 and p = 0.419). To better understand the effect of the examined biomarkers in the AMI patients on SYNTAX score, those biomarkers were grouped using PCA, which merged them into the four the most contributing factors. The "cholesterol-protein factor" and "oxidative-telomere factor" were independent predictors of higher SYNTAX score (OR = 0.338, p = 0.008 and OR = 0.427, p = 0.035, respectively), while the ability to discriminate STEMI from non-STEMI patients had only the "oxidative-telomere factor" (AUC = 0.860, p = 0.008). The results show that traditional cardiovascular risk factors, i.e., high total cholesterol together with high total serum proteins and haemoglobin, are associated with severe disease progression in much the same way as a combination of redox biomarkers (pro-oxidant-antioxidant balance, total antioxidant status, IMA) and telomere length.

Single-Cell RNA Sequencing and Microarray Analysis Reveal the Role of Lipid-Metabolism-Related Genes and Cellular Immune Infiltration in Pre-Eclampsia and Identify Novel Biomarkers for Pre-Eclampsia

Pre-eclampsia (PE) is a gestational hypertensive disorder that is characterized by hypertension and proteinuria, typically occurring after 20 weeks of gestation. Despite its global impact on pregnant women, the precise pathogenic mechanisms of PE remain unclear. Dysregulated lipid metabolism and immune cell infiltration contribute to PE development. Our study aimed to identify lipid-metabolism-related genes (LMRG-PEs) and investigate their association with immune infiltration. We utilized the "Seurat" R package for data quality control, cell clustering, and marker gene identification. The "SingleR" package enabled the matching of marker genes to specific cell types. Pseudotemporal ordering analysis was conducted using the "Monocle" package. Weighted correlation network analysis (WGCNA), gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) approaches were employed to explore lipid-metabolism-related genes, while potential targeted drugs were predicted using the drug-gene interaction database (DGIdb). Hub gene expression was validated through RT-qPCR. By analyzing single-cell RNA sequencing data, we identified and classified 20 cell clusters into 5 distinct types. Differential gene expression analysis revealed 186 DEGs. WGCNA identified 9 critical modules and 265 genes significantly associated with PE diagnosis, emphasizing the importance of the core genes PLA2G7 and PTGS2. RT-qPCR confirmed the significantly decreased expression of PLA2G7 and PTGS2 in PE patient tissues. These findings offer valuable insights into the molecular mechanisms of PE, particularly those involving lipid metabolism and immune infiltration. The identified hub genes have potential as therapeutic targets and biomarkers for future research and clinical applications.

Focus on Therapeutic Options for Surgically Resectable Pancreatic Adenocarcinoma Based on Novel Biomarkers

Pancreatic ductal adenocarcinoma remains associated with a poor prognosis, even when diagnosed at an early stage. Consequently, it is imperative to carefully consider the available therapeutic options and tailor them based on clinically relevant biomarkers. In our comprehensive review, we specifically concentrated on the identification of novel predictive and prognostic markers that have the potential to be integrated into multiparametric scoring systems. These scoring systems aim to accurately predict the efficacy of neoadjuvant chemotherapy in surgically resectable pancreatic cancer cases. By identifying robust predictive markers, we can enhance our ability to select patients who are most likely to benefit from neoadjuvant chemotherapy. Furthermore, the identification of prognostic markers can provide valuable insights into the overall disease trajectory and inform treatment decisions. The development of multiparametric scoring systems that incorporate these markers holds great promise for optimizing the selection of patients for neoadjuvant chemotherapy, leading to improved outcomes in resectable pancreatic neoplasia. Continued research efforts are needed to validate and refine these markers and scoring systems, ultimately advancing the field of personalized medicine in pancreatic adenocarcinoma management.

Detection of Novel Biomarkers in Pediatric Autoimmune Hepatitis by Proteomic Profiling

Autoimmune hepatitis (AIH) is characterized by immune-mediated hepatocyte injury resulting in the destruction of liver cells, causing inflammation, liver failure, and fibrosis. Pediatric (AIH) is an autoimmune inflammatory disease that usually requires immunosuppression for an extended period. Frequent relapses after treatment discontinuation demonstrate that current therapies do not control intrahepatic immune processes. This study describes targeted proteomic profiling data in patients with AIH and controls. A total of 92 inflammatory and 92 cardiometabolic plasma markers were assessed for (i) pediatric AIH versus controls, (ii) AIH type 1 versus type 2, (iii) AIH and AIH-autoimmune sclerosing cholangitis overlapping syndrome and (iv) correlations with circulating vitamin D levels in AIH. A total of 16 proteins showed a nominally significant differential abundance in pediatric patients with AIH compared to controls. No clustering of AIH subphenotypes based on all protein data was observed, and no significant correlation of vitamin D levels was observed for the identified proteins. The proteins that showed variable expression include CA1, CA3, GAS6, FCGR2A, 4E-BP1 and CCL19, which may serve as potential biomarkers for patients with AIH. CX3CL1, CXCL10, CCL23, CSF1 and CCL19 showed homology to one another and may be coexpressed in AIH. CXCL10 seems to be the central intermediary link for the listed proteins. These proteins were involved in relevant mechanistic pathways for liver diseases and immune processes in AIH pathogenesis. This is the first report on the proteomic profile of pediatric AIH. The identified markers could potentially lead to new diagnostic and therapeutic tools. Nevertheless, considering the complex pathogenesis of AIH, more extensive studies are warranted to replicate and validate the present study's findings.

Biophysical Changes of Leukocyte Activation (and NETosis) in the Cellular Host Response to Sepsis

Sepsis, the leading cause of mortality in hospitals, currently lacks effective early diagnostics. A new cellular host response test, the IntelliSep test, may provide an indicator of the immune dysregulation characterizing sepsis. The objective of this study was to examine the correlation between the measurements performed using this test and biological markers and processes associated with sepsis. Phorbol myristate acetate (PMA), an agonist of neutrophils known to induce neutrophil extracellular trap (NET) formation, was added to whole blood of healthy volunteers at concentrations of 0, 200, and 400 nM and then evaluated using the IntelliSep test. Separately, plasma from a cohort of subjects was segregated into Control and Diseased populations and tested for levels of NET components (citrullinated histone (cit-H3) DNA and neutrophil elastase (NE) DNA) using customized ELISA assays and correlated with ISI scores from the same patient samples. Significant increases in IntelliSep Index (ISI) scores were observed with increasing concentrations of PMA in healthy blood (0 and 200: p < 10-10; 0 and 400: p < 10-10). Linear correlation was observed between the ISI and quantities of NE DNA and Cit-H3 DNA in patient samples. Together these experiments demonstrate that the IntelliSep test is associated with the biological processes of leukocyte activation and NETosis and may indicate changes consistent with sepsis.

The clinical use of urinary mitochondrial DNA in adult surgical critical care patients with acute kidney injury

Acute kidney injury (AKI) affects 47% of adult surgical critical care patients (ASCCPs). AKI is induced through a common oxidative stress pathway resulting in mitochondrial and tubular cell injury with increased urinary mitochondrial DNA (UmtDNA) excretion. UmtDNA is an emerging and readily sampled novel biomarker for varied surgical critical care cohorts. This review aimed to determine the clinical use of UmtDNA genes (ND1 and COX3) in AKI in ASCCPs. PubMed, MEDLINE and Web of Science databases were searched. Eligibility criteria were based on the patient/problem, intervention, comparison and outcome framework. Methodological quality of studies was assessed with the Newcastle-Ottawa Quality Assessment Scale. WebPlot Digitizer version 4.4 was used to extract UmtDNA data from graphs and UmtDNA ratios were statistically analysed with PRISM version 9.1.0 (GraphPad Software). Six human studies (n = 391) with three translational murine models (n = 112) satisfied inclusion criteria. One sample t test suggested significantly high UmtDNA-ND1 ratios in progressive/severe AKI (or delayed renal transplant graft function) to no AKI (or immediate renal transplant graft function) and increased UmtDNA-COX3 ratios approached significance. Sensitivities and specificities for UmtDNA ranged from 68% to 85% and 52% to 83.6%, respectively, comparable with new biomarkers, neutrophil gelatinase-associated lipocalin and kidney injury molecule-1. Weak correlation was observed with serum creatinine. These findings were complemented in translational murine AKI experiments with significantly elevated ND1 and COX3. From bench to clinical practice, UmtDNA appears to be a promising novel biomarker of progressive/severe AKI (or delayed graft function). Large prospective, multi-centre studies reporting standardised UmtDNA findings should clarify use of UmtDNA in ASCCP-AKI management.

Chronic Kidney Disease of Unknown Etiology in a Tertiary Care Teaching Hospital

Background Several primary studies have looked at the burden of chronic kidney disease among diabetic patients, but their results have shown significant variance in India. In order to determine the combined prevalence of chronic kidney disease and associated risk factors among patients with diabetes, this study used a combination of methods. Methods Over the course of two years, a cross-sectional observational study was undertaken in the Tertiary Care Teaching Hospital's Department of General Medicine including all chronic kidney disease patients of 18 years of age and above of either gender. People not suffering from the disease were chosen as controls. Kidney Injury Molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin-ELISA (NGAL-ELISA) sample analysis by the kit method was done. The study was carried out in accordance with Schedule Y, ICH GCP principles, and the Helsinki Declaration after receiving approval from the institutional ethics committee. Results In our study, the urinary mean KIM-1 was 49.75±4.35 μg/g Cr in the Chronic Kidney Disease of Unknown etiology (CKDu) group and 1.43±0.15 μg/g Cr in the controls group. The mean NGAL levels of the CKDu Group and the controls group were 8.94±1.31 μg/g and 0.41±0.05 μg/g, respectively. In CKDu and the controls group, the mean eGFR (ml/min/1.73m²) was 69.83±7.91 and 108±3.7, respectively. The mean serum creatinine (mg/dL) was reported 3.79 in the CKDu group and 1.0 in the controls group. Conclusion Despite the urban centers previously being thought of as a non-endemic location, for the first time in the city, 60 CKDu patients are reported in this study. This is the first study to use the urinary biomarkers KIM-1 and NGAL to find suspected cases of CKDu and early kidney damage in local communities in the urban centers.

An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma

The pathogenesis and vital factors of early and progressive stages of stomach adenocarcinoma (STAD) have not been fully elucidated. In order to discover novel and potential targets to guide effective treatment strategies, a comprehensive bioinformatics study was performed, and the representative results were then validated by quantitative polymerase chain reaction (qPCR) and immunohistochemical (IMC) staining in clinical samples. A total of 4,627, 4,715, and 3,465 differentially expressed genes (DEGs) from overall-, early-, and progressive-stage STAD were identified, respectively. Prognostic models of 5-year OS were established for overall-, early-, and progressive-stage STAD, and ROC curves demonstrated AUC values for each model were 0.73, 0.87, and 0.92, respectively. Function analysis revealed that mRNAs of early-stage STAD were enriched in chemical stimulus-related pathways, whereas remarkable enrichment of mRNAs in progressive-stage STAD mainly lay in immune-related pathways. Both qPCR and IHC data confirmed the up-regulation of IGFBP1 in the early-stage and CHAF1A in progressive-stage STAD compared with their matched normal tissues, indicating that these two representative targets could be used to predict the prognostic status of the patients in these two distinct STAD stages, respectively. In addition, seven mRNAs (F2, GRID2, TF, APOB, KIF18B, INCENP, and GCG) could be potential novel biomarkers for STAD at different stages from this study. These results contributed to identifying STAD patients at high-risk, thus guiding targeted treatment with efficacy in these patients.

Inflammation in coronary artery disease-clinical implications of novel HDL-cholesterol-related inflammatory parameters as predictors

Coronary artery disease (CAD) is the leading cause of death worldwide. Inflammation and atherosclerotic plaques are the primary pathological mechanisms of CAD. Upon stimulation by deposited lipids and damaged endothelium, innate and adaptive immune cells are activated and recruited to initiate plaque development. Therefore, inflammatory cells and mediators are used to identify inflammatory risk in CAD patients. HDL-cholesterol (HDL-C) is demonstrated to have anti-inflammatory roles in atherosclerosis by interfering with plasma membrane lipid rafts of immune cells. Based on this, novel inflammatory parameters such as monocyte to HDL-C ratio are explored to improve the risk estimation of CAD prognosis. Moreover, with the advance in treatment strategies targeting the inflammatory process in atherosclerosis, identifying CAD patients with increased inflammatory risk by novel inflammatory parameters is of great importance in guiding CAD management. Therefore, this review aims to summarize the current information regarding inflammatory activation and HDL-C in atherosclerosis with a particular focus on the clinical implication of the novel HDL-C-related inflammatory parameters in CAD.

Novel biomarkers of acute kidney injury in chronic liver disease: Where do we stand after a decade of research?

Acute kidney injury (AKI) is a frequently encountered complication in decompensated chronic liver disease (CLD) with an estimated prevalence of 20%-50% among hospitalized patients. AKI often heralds the onset of a downhill course in the natural history of CLD. Serum creatinine has several limitations as a stand-alone marker of AKI in patients with decompensated CLD. The concept of hepatorenal syndrome, the prototype of AKI in decompensated CLD, has evolved tremendously over recent years. There is emerging evidence of an additional "structural" component in the pathophysiology of hepatorenal syndrome-AKI, which was previously identified as a purely "functional" form of renal impairment. Lacunae in the existent biochemical arsenal for diagnosis and prognosis of AKI have fueled enthusiastic research in the field of novel biomarkers of kidney injury in patients with cirrhosis. The advent of these biomarkers provides a crucial window of opportunity to improve the diagnosis and clinical outcomes of this vulnerable cohort of patients. This review summarizes the dynamic concept of renal dysfunction in CLD and the available literature on the role of novel biomarkers of AKI in assessing renal function, identifying AKI subtypes, and predicting prognosis. There is special emphasis on the renal tubular injury marker, neutrophil gelatinase-associated lipocalin, the most exhaustively studied biomarker of AKI in the CLD population.

Predictors of Complicated Appendicitis with Evolution to Appendicular Peritonitis in Pediatric Patients

Background and Objecitves: Appendicitis is one of the most frequent surgical emergencies in pediatric surgery. Complicated appendicitis can evolve with appendicular peritonitis characterized by the diffusion of the pathological process to the peritoneal cavity, thus producing generalized or localized inflammation of the peritoneum. The capacity to anticipate the possibility of perforation in acute appendicitis can direct prompt management and lower morbidity. There is no specific symptom that could be used to anticipate complicated appendicitis, and diagnostic clues include a longer period of symptoms, diffuse peritoneal signs, high fever, elevated leukocytosis and CRP, hyponatremia, and high ESR. Imagistic methods, particularly US and CT, are useful but not sufficient. There are no traditional inflammation biomarkers able to predict the evolution of uncomplicated to complicated appendicitis alone, but the predictive capacity of novel biomarkers is being investigated. Materials and Methods: The present study represents a retrospective evaluation of children hospitalized between January 2021 and July 2022 in the Grigore Alexandrescu Clinical Emergency Hospital for Children with a diagnosis of acute appendicitis settled based on clinical characteristics, traditional and novel biomarkers, and ultrasonographic features. The children were subsequently grouped into two groups based on the existence of appendicular peritonitis on intraoperative inspection of the abdominal cavity. The aim of this report is to establish the predictors that may aid physicians in timely identifying pediatric patients diagnosed with acute appendicitis at risk for developing complicated appendicitis with evolution to appendicular peritonitis. Results: The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte radio (PLR) are representative severity markers in infections. This report analyzes the benefit of these markers for distinguishing uncomplicated appendicitis from complicated appendicitis in pediatric patients. Conclusions: Our study suggests that a value of neutrophil-to-lymphocyte ratio greater than 8.39 is a reliable parameter to predict the evolution to appendicular peritonitis.

PgRNA kinetics predict HBsAg reduction in pregnant chronic hepatitis B carriers after treatment cessation

Background

Pregenomic RNA (pgRNA) and hepatitis B core-related antigen (HBcrAg) play significant roles in predicting discontinuing treatment outcomes. However, their role in pregnancy has rarely been reported. We aimed to evaluate the performance of pgRNA and HBcrAg kinetics in predicting HBeAg seroconversion and HBsAg reduction postpartum in HBeAg-positive pregnant women.

Methods

Pregnant HBeAg-positive patients receiving antiviral prophylaxis and ceasing treatment postpartum were included. PgRNA and HBcrAg levels were measured before treatment, at 32 weeks of gestation, and at treatment withdrawal postpartum. Other virological and biochemical parameters were regularly examined until 96 weeks postpartum.

Results

Of 76 pregnant chronic hepatitis B (CHB) carriers with a median treatment duration of 18.1 weeks, HBeAg seroconversion and HBsAg reduction >0.3 log₁₀ IU/mL at 96 weeks postpartum occurred in 8 (10.5%) and 13 (17.1%) patients, respectively. HBsAg correlated most strongly with pgRNA, while HBeAg correlated most strongly with HBcrAg. Multivariable regression analysis revealed that postpartum pgRNA decline and peak ALT levels were independent predictors of HBsAg reduction. The area under the curve of the regression model was 0.79 and reached as high as 0.76 through bootstrapping validation. The calibration plot showed that the nomogram had a performance similar to that of the ideal model. A decision tree was established to facilitate application of the nomogram. In addition, HBcrAg kinetics, as an independent predictor, performed poorly in predicting HBeAg seroconversion.

Conclusions

Postpartum pgRNA decline together with peak ALT levels may identify patients with a higher probability of HBsAg reduction after treatment cessation postpartum among pregnant CHB carriers receiving antiviral prophylaxis.

Clinical significance of novel biomarkers to predict the natural course of hepatitis B infection

Background and aim

Chronic hepatitis B (CHB) can be divided into immune tolerance (IT), immune clearance (IC), hepatitis B e antigen (HBeAg)-negative inactive/quiescent carrier (ENQ), and HBeAg-negative hepatitis (ENH) phases. The conventional biomarkers used to distinguish these phases have limitations. We examined the clinical significance of hepatitis B virus (HBV) RNA and hepatitis B core-related antigen (HBcrAg) as novel biomarkers.

Methods

One hundred eighty-nine patients without treatment currently were categorized by CHB phase (IT = 46, IC = 45, ENQ = 49, ENH = 49). The associations of HBV RNA and HBcrAg with HBV DNA and alanine transaminase (ALT) were analyzed. The decision tree model was used to distinguish the four phases in the natural course of CHB.

Results

The concentrations of HBV RNA and HBcrAg were highest in the IT and IC phases (P < 0.01). Serum HBV RNA was similar to HBcrAg in treatment-naïve patients. HBV RNA and HBcrAg correlated with HBV DNA in the HBeAg⁺ and HBeAg^- status (HBV RNA: e⁺ r = 0.51, e^- r = 0.62; HBcrAg: e⁺ r = 0.51, e^- r = 0.71), but their association with HBV DNA differed among phases. The accuracy, sensitivity, and specificity of HBcrAg with ALT in distinguishing the CHB phases were 95.65%, 95.83%, and 95.55%, respectively.

Conclusion

Serum HBV RNA and HBcrAg may be useful to monitor CHB progression.

Novel Anti Double-Stranded Nucleic Acids Full-Length Recombinant Camelid Heavy-Chain Antibody for the Detection of miRNA

The discovery that certain diseases have specific miRNA signatures which correspond to disease progression opens a new biomarker category. The detection of these small non-coding RNAs is performed routinely using body fluids or tissues with real-time PCR, next-generation sequencing, or amplification-based miRNA assays. Antibody-based detection systems allow an easy onset handling compared to PCR or sequencing and can be considered as alternative methods to support miRNA diagnostic in the future. In this study, we describe the generation of a camelid heavy-chain-only antibody specifically recognizing miRNAs to establish an antibody-based detection method. The generation of nucleic acid-specific binders is a challenge. We selected camelid binders via phage display, expressed them as VHH as well as full-length antibodies, and characterized the binding to several miRNAs from a signature specific for dilated cardiomyopathy. The described workflow can be used to create miRNA-specific binders and establish antibody-based detection methods to provide an additional way to analyze disease-specific miRNA signatures.

Prognostic Value of SPOCD1 in Esophageal Squamous Cell Carcinoma: A Comprehensive Study Based on Bioinformatics and Validation

In the study, we aimed to explore and analyze the potential function of SPOC Domain Containing 1 (SPOCD1) in esophageal squamous cell carcinoma (ESCC). We performed a comprehensive analysis of gene expression of SPOCD1 and its corresponding clinicopathological features in ESCC. In particular, the correlation between SPOCD1 and ESCC was evaluated using a wide range of analysis tools and databases, including TCGA, GTEx, GenePattern, CellMiner, GDSC, and STRING datasets. Different bioinformatics analyses, including differential expression analysis, mutation analysis, drug sensitivity analysis, function analysis, pathway analysis, co-expression network analysis, immune cell infiltration analysis, and survival analysis, were carried out to comprehensively explore the potential molecular mechanisms and functional effects of SPOCD1 on the initiation and progression of ESCC. The expression of SPOCD1 was upregulated in ESCC tissues compared to those in normal tissues. In the high SPOCD1 expression group, we found apparent mutations in TP53, TTN, and MUC16 genes, which were 92, 36, and 18%, respectively. GO and KEGG enrichment analysis of SPOCD1 and its co-expressed genes demonstrated that it may serve as an ESCC oncogene by regulating the genes expression in the essential functions and pathways of tumorigenesis, such as glycosaminoglycan binding, Cytokine-cytokine receptor interaction, and Ras signaling pathway. Besides, the immune cell infiltration results revealed that SPOCD1 expression was positively correlated with Macrophages M0 and Mast cells activated cells, and negatively correlated with plasma cells and T cells follicular helper cell infiltration. Finally, ESCC patients with high expression of SPOCD1 indicated poor overall survival. qRT-PCR demonstrated that the SPOCD1 expression in ESCC tissues was significantly higher than adjacent tissues (p < 0.001). Our study indicated that SPOCD1 was increased in ESCC tissues. The current data support the oncogenic role of SPOCD1 in the occurrence and development of ESCC. Most importantly, SPOCD1 might be an independent prognostic factor for ESCC patients.

Validation of Novel Molecular Imaging Targets Identified by Functional Genomic mRNA Profiling to Detect Dysplasia in Barrett's Esophagus

Barrett’s esophagus (BE) is the precursor of esophageal adenocarcinoma (EAC). Dysplastic BE (DBE) has a higher progression risk to EAC compared to non-dysplastic BE (NDBE). However, the miss rates for the endoscopic detection of DBE remain high. Fluorescence molecular endoscopy (FME) can detect DBE and mucosal EAC by highlighting the tumor-specific expression of proteins. This study aimed to identify target proteins suitable for FME. Publicly available RNA expression profiles of EAC and NDBE were corrected by functional genomic mRNA (FGmRNA) profiling. Following a class comparison between FGmRNA profiles of EAC and NDBE, predicted, significantly upregulated genes in EAC were prioritized by a literature search. Protein expression of prioritized genes was validated by immunohistochemistry (IHC) on DBE and NDBE tissues. Near-infrared fluorescent tracers targeting the proteins were developed and evaluated ex vivo on fresh human specimens. In total, 1976 overexpressed genes were identified in EAC (n = 64) compared to NDBE (n = 66) at RNA level. Prioritization and IHC validation revealed SPARC, SULF1, PKCι, and DDR1 (all p < 0.0001) as the most attractive imaging protein targets for DBE detection. Newly developed tracers SULF1-800CW and SPARC-800CW both showed higher fluorescence intensity in DBE tissue compared to paired non-dysplastic tissue. This study identified SPARC, SULF1, PKCι, and DDR1 as promising targets for FME to differentiate DBE from NDBE tissue, for which SULF1-800CW and SPARC-800CW were successfully ex vivo evaluated. Clinical studies should further validate these findings.

Promising novel biomarkers and candidate small-molecule drugs for lung adenocarcinoma: Evidence from bioinformatics analysis of high-throughput data

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer associated with an unstable prognosis. Thus, there is an urgent demand for the identification of novel diagnostic and prognostic biomarkers as well as targeted drugs for LUAD. The present study aimed to identify potential new biomarkers associated with the pathogenesis and prognosis of LUAD. Three microarray datasets (GSE10072, GSE31210, and GSE40791) from the Gene Expression Omnibus database were integrated to identify the differentially expressed genes (DEGs) in normal and LUAD samples using the limma package. Bioinformatics tools were used to perform functional and signaling pathway enrichment analyses for the DEGs. The expression and prognostic values of the hub genes were further evaluated by Gene Expression Profiling Interactive Analysis and real-time quantitative polymerase chain reaction. Furthermore, we mined the “Connectivity Map” (CMap) to explore candidate small molecules that can reverse the tumoral of LUAD based on the DEGs. A total of 505 DEGs were identified, which included 337 downregulated and 168 upregulated genes. The PPI network was established with 1,860 interactions and 373 nodes. The most significant pathway and functional enrichment associated with the genes were cell adhesion and extracellular matrix-receptor interaction, respectively. Seven DEGs with high connectivity degrees (ZWINT, RRM2, NDC80, KIF4A, CEP55, CENPU, and CENPF) that were significantly associated with worse survival were chosen as hub genes. Lastly, top 20 most important small molecules which reverses the LUAD gene expressions were identified. The findings contribute to revealing the molecular mechanisms of the initiation and progression of LUAD and provide new insights for integrating multiple biomarkers in clinical practice.

WT1-AS/IGF2BP2 Axis Is a Potential Diagnostic and Prognostic Biomarker for Lung Adenocarcinoma According to ceRNA Network Comprehensive Analysis Combined with Experiments

Lung adenocarcinoma (LUAD) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. Here, we comprehensively analyze the characteristics of. an RNA sequencing data set of LUAD samples. In total, 395 long non-coding RNAs (lncRNAs), 89 microRNAs (miRNAs), and 872 mRNAs associated with c-Myc were identified, which were differentially expressed between tumor and normal tissues. The most relevant pathway was found to be WT1-AS–miR-200a-3p–IGF2BP2 according to the rules of competitive endogenous RNA (ceRNA) regulation. WT1-AS and IGF2BP2 expression were positively correlated and increased in LUAD samples, while miR-200a-3p had relatively low expression. The high expression of WT1-AS and IGF2BP2 was associated with poor prognosis in LUAD patients, while low expression of miR-200a-3p predicted reduced survival (p < 0.05). The analysis of the multi-gene regulation model indicated that the WT1-AS (downregulation)–miR-200a-3p (upregulation)–IGF2BP2 (downregulation) pattern significantly improved the survival of LUAD patients. Finally, reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting were detected in LUAD cells, and the results are consistent with the bioinformatics analysis. In summary, the WT1-AS/IGF2BP2 axis is a potential prognostic biomarker in LUAD and is expected to become an effective target for diagnosis and treatment.

Cost Analysis of Screening for IgA Nephropathy Using Novel Biomarkers

OBJECTIVES

IgA nephropathy (IgAN) is the most common primary chronic glomerulonephritis and a major cause of end-stage kidney disease worldwide. Novel biomarkers, including the aberrantly glycosylated IgA1 and glycan-specific antibodies, could be useful in the diagnosis of IgAN. The aim of this study was to assess the cost analysis of IgAN screening using novel biomarkers in addition to the conventional screening compared with conventional screening alone.

METHODS

To estimate the medical expense of each strategy related to renal disease for 40 years, we developed an analytical decision model. The decision tree started at "40 years of age with first-time hematuria." It simulated 2 clinical strategies: IgAN screening using the novel biomarkers (group N) and conventional screening (group C). The analysis results were presented as medical expenses from a societal perspective. Discounting was not conducted.

RESULTS

The expected medical expense per person for 40 years was ¥31.2 million (~$291 000) in group N and ¥33.4 million (~$312 000) in group C; hence, expense in group N was lower by ¥2.2 million (~$21 000). In group N, the expected value of IgAN increased by 5.67% points (N 48.44%, C 42.77%) and that of dialysis introduction decreased by 0.85% points (N 19.06%, C 19.91%). In the sensitivity analysis, expenses could be reduced in almost all cases except when renal biopsy using conventional screening was performed at the rate of 73% or higher.

CONCLUSION

Screening for IgAN using novel biomarkers would reduce renal disease-related expenses.

Cardiorenal Syndrome: New Pathways and Novel Biomarkers

Cardiorenal syndrome (CRS) is a multi-organ disease characterized by the complex interaction between heart and kidney during acute or chronic injury. The pathogenesis of CRS involves metabolic, hemodynamic, neurohormonal, and inflammatory mechanisms, and atherosclerotic degeneration. In the process of better understanding the bi-directional pathophysiological aspects of CRS, the need to find precise and easy-to-use markers has also evolved. Based on the new pathophysiological standpoints and an overall vision of the CRS, the literature on renal, cardiac, metabolic, oxidative, and vascular circulating biomarkers was evaluated. Though the effectiveness of different extensively applied biomarkers remains controversial, evidence for several indicators, particularly when combined, has increased in recent years. From new aspects of classic biomarkers to microRNAs, this review aimed at a 360-degree analysis of the pathways that balance the kidney and the heart physiologies. In this delicate system, different markers and their combination can shed light on the diagnosis, risk, and prognosis of CRS.

Proteome profiling of formalin-fixed, paraffin-embedded lung adenocarcinoma tissues using a tandem mass tag-based quantitative proteomics approach

Over the past few decades, increasing efforts have been made to improve the understanding of, and treatment options for, lung adenocarcinoma (LUAD). However, considering the heterogeneity of LUAD, precise proteomics-based characterization at the molecular level is an urgent clinical requirement for effective treatment. Formalin-fixed, paraffin-embedded (FFPE) tissue is a good option as the working tool for proteomics studies. The present study aimed to obtain a global protein profile using LUAD FFPE tissue samples. Using a quantitative proteomics approach, the study revealed that 360 proteins were significantly more highly expressed in LUAD than in adjacent nontumor lung tissues. Also, 19 differentially expressed membrane proteins were found to be primarily responsible for immune processes. Epidermal growth factor (EGF)-like domain and laminin EGF domain showed markedly different expression levels between cancer tissues and tumor-adjacent normal tissues. Furthermore, Gene Ontology functional enrichment analysis showed that significantly upregulated proteins were associated with the endoplasmic reticulum lumen, protein disulfide isomerase activity, vitamin binding, cell cycle G₁/S phase transition, to name but a few. Also, numerous kinases and post-translational modification enzymes were significantly upregulated across all eight LUAD samples compared with paracarcinoma tissues. Proteomics analysis revealed that AAA domain containing 3A (ATAD3a), a member of the ATPase family, was highly expressed in LUAD tissues, which was supported by immunohistochemical analysis. Furthermore, the study confirmed that ATAD3a enhanced the cisplatin sensitivity of LUAD cells. Collectively, the findings of the present study provide new potential candidate targets in patients with LUAD, and may aid auxiliary LUAD diagnosis and surveillance in a noninvasive manner.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the metabolic disorder that appears during pregnancy. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non-GDM samples were analyzed. Functional enrichment analysis were performed using ToppGene. Then we constructed the protein–protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA–hub gene network and TF–hub gene regulatory network. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up-regulated and 430 down-regulated genes. Functional enrichment analysis showed these DEGs were mainly enriched in reproduction, cell adhesion, cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3 and PRKCA were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. This investigation identified hub genes, signal pathways and therapeutic agents, which might help us, enhance our understanding of the mechanisms of GDM and find some novel therapeutic agents for GDM.

Endothelial Dysfunction, Inflammation and Coronary Artery Disease: Potential Biomarkers and Promising Therapeutical Approaches

Coronary artery disease (CAD) and its complications are the leading cause of death worldwide. Inflammatory activation and dysfunction of the endothelium are key events in the development and pathophysiology of atherosclerosis and are associated with an elevated risk of cardiovascular events. There is great interest to further understand the pathophysiologic mechanisms underlying endothelial dysfunction and atherosclerosis progression, and to identify novel biomarkers and therapeutic strategies to prevent endothelial dysfunction, atherosclerosis and to reduce the risk of developing CAD and its complications. The use of liquid biopsies and new molecular biology techniques have allowed the identification of a growing list of molecular and cellular markers of endothelial dysfunction, which have provided insight on the molecular basis of atherosclerosis and are potential biomarkers and therapeutic targets for the prevention and or treatment of atherosclerosis and CAD. This review describes recent information on normal vascular endothelium function, as well as traditional and novel potential biomarkers of endothelial dysfunction and inflammation, and pharmacological and non-pharmacological therapeutic strategies aimed to protect the endothelium or reverse endothelial damage, as a preventive treatment for CAD and related complications.

Advanced Approaches to Breast Cancer Classification and Diagnosis

The International Agency for Research on Cancer (IARC) has recently reported a 66% increase in the global number of cancer deaths since 1960. In the US alone, about one in eight women is expected to develop invasive breast cancer(s) (breast cancer) at some point in their lifetime. Traditionally, a BC diagnosis includes mammography, ultrasound, and some high-end molecular bioimaging. Unfortunately, these techniques detect BC at a later stage. So early and advanced molecular diagnostic tools are still in demand. In the past decade, various histological and immuno-molecular studies have demonstrated that BC is highly heterogeneous in nature. Its growth pattern, cytological features, and expression of key biomarkers in BC cells including hormonal receptor markers can be utilized to develop advanced diagnostic and therapeutic tools. A cancer cell's progression to malignancy exhibits various vital biomarkers, many of which are still underrepresented in BC diagnosis and treatment. Advances in genetics have also enabled the development of multigene assays to detect genetic heterogeneity in BC. However, thus far, the FDA has approved only four such biomarkers-cancer antigens (CA); CA 15-3, CA 27-29, Human epidermal growth factor receptor 2 (HER2), and circulating tumor cells (CTC) in assessing BC in body fluids. An adequately structured portable-biosensor with its non-invasive and inexpensive point-of-care analysis can quickly detect such biomarkers without significantly compromising its specificity and selectivity. Such advanced techniques are likely to discriminate between BC and a healthy patient by accurately measuring the cell shape, structure, depth, intracellular and extracellular environment, and lipid membrane compositions. Presently, BC treatments include surgery and systemic chemo- and targeted radiation therapy. A biopsied sample is then subjected to various multigene assays to predict the heterogeneity and recurrence score, thus guiding a specific treatment by providing complete information on the BC subtype involved. Thus far, we have seven prognostic multigene signature tests for BC providing a risk profile that can avoid unnecessary treatments in low-risk patients. Many comparative studies on multigene analysis projected the importance of integrating clinicopathological information with genomic-imprint analysis. Current cohort studies such as MINDACT, TAILORx, Trans-aTTOM, and many more, are likely to provide positive impact on long-term patient outcome. This review offers consolidated information on currently available BC diagnosis and treatment options. It further describes advanced biomarkers for the development of state-of-the-art early screening and diagnostic technologies.

Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis

Background: Melanoma is a pernicious skin cancer with high aggressiveness. This study aimed to identify potential novel biomarkers associated with the prognosis and pathogenesis of cutaneous melanoma and to explore new targeted drugs for melanoma. Methods: Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined to analyze the differentially expressed genes (DEGs). To better understand the DEGs in the melanoma pathogenesis, we performed gene enrichment analyses and established a protein-protein interaction network (PPI). The survival analyses for key genes were conducted based on the GEPIA platform. Finally, we mined the CMap database to explore potential small-molecule drugs to target the obtained DEGs. Results: In short, we identified 500 DEGs between cutaneous melanoma samples and normal samples. The PPI network was established with 349 nodes and 1251 edges. Signaling pathway analysis showed that these genes play a vital role in ECM-receptor interactions, the PPAR signaling pathway and pathways in cancer. Eight DEGs with a relatively high degree of connectivity (CDC45, CENPF, DTL, FANCI, GINS2, HJURP, TPX2 and TRIP13) were selected as hub-genes that remarkably correlated to a poor survival rate. Based on 500 DEGs, 20 small-molecule drugs that potentially target genes with abnormal expression in cutaneous melanoma were obtained from the CMap database. Among these compounds, we found that menadione has the greatest therapeutic value for melanoma. Conclusions: In conclusion, we identified the 8 candidate biomarkers and potential key signaling pathways in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs have provided several directive significances for the synthesis medicine for melanoma.

Update of early phase clinical trials in cancer immunotherapy

Immunotherapy has revolutionized the landscape of cancer treatment and become a standard pillar of the treatment. The two main drivers, immune checkpoint inhibitors and chimeric antigen receptor T cells, contributed to this unprecedented success. However, despite the striking clinical improvements, most patients still suffer from disease progression because of the evolution of primary or acquired resistance. This mini-review summarizes new treatment options including novel targets and interesting combinational approaches to increase our understanding of the mechanisms of the action of and resistance to immunotherapy, to expand our knowledge of advances in biomarker and therapeutics development, and to help to find the most appropriate option or a way of overcoming the resistance for cancer patients. [BMB Reports 2021; 54(1): 70-88].

Relationship of Circulating Endothelial Cells With Obesity and Cardiometabolic Risk Factors in Children and Adolescents

Background Circulating endothelial cells (CECs) reflect early changes in endothelial health; however, the degree to which CEC number and activation is related to adiposity and cardiovascular risk factors in youth is not well described. Methods and Results Youth in this study (N=271; aged 8-20 years) were classified into normal weight (body mass index [BMI] percentage <85th; n=114), obesity (BMI percentage ≥95th to <120% of the 95th; n=63), and severe obesity (BMI percentage ≥120% of the 95th; n=94) catagories. CEC enumeration was determined using immunohistochemical examination of buffy coat smears and activated CEC (percentage of vascular cell adhesion molecule-1 expression) was assessed using immunofluorescent staining. Cardiovascular risk factors included measures of body composition, blood pressure, glucose, insulin, lipid profile, C-reactive protein, leptin, adiponectin, oxidized low-density lipoprotein cholesterol, carotid artery intima-media thickness, and pulse wave velocity. Linear regression models examined associations between CEC number and activation with BMI and cardiovascular risk factors. CEC number did not differ among BMI classes (P>0.05). Youth with severe obesity had a higher degree of CEC activation compared with normal weight youth (8.3%; 95% CI, 1.1-15.6 [P=0.024]). Higher CEC number was associated with greater body fat percentage (0.02 per percentage; 95% CI, 0.00-0.03 [P=0.020]) and systolic blood pressure percentile (0.01 per percentage; 95% CI, 0.00-0.01 [P=0.035]). Higher degree of CEC activation was associated with greater visceral adipose tissue (5.7% per kg; 95% CI, 0.4-10.9 [P=0.034]) and non-high-density lipoprotein cholesterol (0.11% per mg/dL; 95% CI, 0.01-0.21 [P=0.039]). Conclusions Methods of CEC quantification are associated with adiposity and cardiometabolic risk factors and may potentially reflect accelerated atherosclerosis as early as childhood.

The Utility of Novel Renal Biomarkers in Assessment of Chronic Kidney Disease of Unknown Etiology (CKDu): A Review

Chronic Kidney Disease (CKD) is a globally prevalent non-communicable disease with significant mortality and morbidity. It is typically associated with diabetes and hypertension; however, over the last two decades, an emergence of CKD of unknown etiology (CKDu) has claimed thousands of lives in several tropical agricultural communities. CKDu is associated with gradual loss of renal function without initial symptoms until reaching complete kidney failure and eventually death. The most impacted are young adult males of lower socio-economic strata. Since the disease progression can be successfully attenuated through early detection, the development of superior screening and management measures is of utmost importance. In contrast to the conventional biomarkers, novel biomarkers with improved sensitivity and specificity are being discussed as promising tools for early diagnosis of the disease. This review summarizes emerging novel biomarkers used in assessing CKD and discusses the current utility and diagnostic potential of such biomarkers for CKDu screening in clinical settings of different communities impacted by CKDu. Our goal is to provide a framework for practitioners in CKDu impacted regions to consider the use of these novel biomarkers through this synthesis. The increased use of these biomarkers will not only help to validate their diagnostic power further and establish potential prognostic value but may also provide critical insights into sites and mechanisms of renal damage.

Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.

Methods

It identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein–protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.

Results

A total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA LIFR and lncRNA AC124312.3 were significantly correlated with the overall survival of patients with TNBC in the TCGA databases (P < 0.05). Finally, the LIFR protein was validated, and immunohistochemical results showed the upregulated expression of LIFR in TNBC tissues.

Conclusion

Thus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene LIFR may be a new promising potential therapeutic target for patients with TNBC.

Bioinformatics analysis of high-throughput data to validate potential novel biomarkers and small molecule drugs for glioblastoma multiforme

Objective

There have been no recent improvements in the glioblastoma multiforme (GBM) outcome, with median survival remaining 15 months. Consequently, the need to identify novel biomarkers for GBM diagnosis and prognosis, and to develop targeted therapies is high. This study aimed to establish biomarkers for GBM pathogenesis and prognosis.

Methods

In total, 220 overlapping differentially expressed genes (DEGs) were obtained by integrating four microarray datasets from the Gene Expression Omnibus database (GSE4290, GSE12657, GSE15824, and GSE68848). Then a 140-node protein–protein interaction network with 343 interactions was constructed.

Results

The immune response and cell adhesion molecules were the most significantly enriched functions and pathways, respectively, among DEGs. The designated hub genes ITGB5 and RGS4, which have a high degree of connectivity, were closely correlated with patient prognosis, and GEPIA database mining further confirmed their differential expression in GBM versus normal tissue. We also determined the 20 most appropriate small molecules that could potentially reverse GBM gene expression, Prestwick-1080 was the most promising and had the highest negative scores.

Conclusions

This study identified ITGB5 and RGS4 as potential biomarkers for GBM diagnosis and prognosis. Insights into molecular mechanisms governing GBM occurrence and progression will help identify alternative biomarkers for clinical practice.

Circular RNAs in gastric cancer: Biomarkers for early diagnosis

Circular RNAs (circRNAs) are highly conserved and stable closed-loop non-coding RNAs. They are involved in numerous biological functions, including regulating gene transcription or protein translation by interacting with proteins and regulating expression of microRNAs. The aberrant expression of circRNAs has been reported in many cancers, including gastric cancer. By regulating gene expression, circRNAs are able to affect the proliferation, invasion and metastasis of gastric cancer. The current review focused on the characteristics and biological functions of circRNAs, the carcinogenic potential and the possible implications of circRNAs on the diagnosis and treatment of gastric cancer. In conclusion, circRNAs may serve as potential biomarkers for diagnosis, as well as therapeutic targets.

Emerging Noninvasive Biomarkers, and Medical Management Strategies for Alcoholic Hepatitis: Present Understanding and Scope

Alcohol use disorder is associated with a wide array of hepatic pathologies ranging from steatosis to alcoholic-related cirrhosis (AC), alcoholic hepatitis (AH), or hepatocellular carcinoma (HCC). Biomarkers are categorized into two main categories: biomarkers associated with alcohol consumption and biomarkers of alcoholic liver disease (ALD). No ideal biomarker has been identified to quantify the degree of hepatocyte death or severity of AH, even though numerous biomarkers have been associated with AH. This review provides information of some of the novel and latest biomarkers that are being investigated and have shown a substantial association with the degree and severity of liver injury and inflammation. Importantly, they can be measured noninvasively. In this manuscript, we consolidate the present understanding and prospects of these biomarkers; and their application in assessing the severity and progression of the alcoholic liver disease (ALD). We also review current and upcoming management options for AH.

Identification of novel biomarkers and candidate small molecule drugs in non-small-cell lung cancer by integrated microarray analysis

Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC.

Methods: The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein–protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database.

Results: A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression.

Conclusions: Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

Acute Kidney Injury Induced by Bothrops Venom: Insights into the Pathogenic Mechanisms

Acute kidney injury (AKI) following snakebite is common in developing countries and Bothrops genus is the main group of snakes in Latin America. To evaluate the pathogenic mechanisms associated with Bothrops venom nephrotoxicity, we assessed urinary and blood samples of patients after hospital admission resulting from Bothrops snakebite in a prospective cohort study in Northeast Brazil. Urinary and blood samples were evaluated during hospital stay in 63 consenting patients, divided into AKI and No-AKI groups according to the KDIGO criteria. The AKI group showed higher levels of urinary MCP-1 (Urinary monocyte chemotactic protein-1) (median 547.5 vs. 274.1 pg/mgCr; p = 0.02) and urinary NGAL (Neutrophil gelatinase-associated lipocalin) (median 21.28 vs. 12.73 ng/mgCr; p = 0.03). Risk factors for AKI included lower serum sodium and hemoglobin levels, proteinuria and aPTT (Activated Partial Thromboplastin Time) on admission and disclosed lower serum sodium (p = 0.01, OR = 0.73, 95% CI: 0.57–0.94) and aPTT (p = 0.031, OR = 26.27, 95% CI: 1.34–512.11) levels as independent factors associated with AKI. Proteinuria showed a positive correlation with uMCP-1 (r = 0.70, p < 0.0001) and uNGAL (r = 0.47, p = 0.001). FE_Na (Fractional Excretion of sodium) correlated with uMCP-1 (r = 0.47, P = 0.001) and uNGAL (r = 0.56, p < 0.0001). sCr (serum Creatinine) showed a better performance to predict AKI (AUC = 0.85) in comparison with new biomarkers. FE_K showed fair accuracy in predicting AKI (AUC = 0.92). Coagulation abnormality was strongly associated with Bothrops venom-related AKI. Urinary NGAL and MCP-1 were good biomarkers in predicting AKI; however, sCr remained the best biomarker. FE_K (Fractional Excretion of potassium) emerged as another diagnostic tool to predict early AKI. Positive correlations between uNGAL and uMCP-1 with proteinuria and FE_Na may signal glomerular and tubular injury. Defects in urinary concentrations highlighted asymptomatic abnormalities, which deserve further study.

The promising novel biomarkers and candidate small molecule drugs in kidney renal clear cell carcinoma: Evidence from bioinformatics analysis of high-throughput data

Background

Kidney renal clear cell carcinoma (KIRC) is the most common subtype of renal tumor. However, the molecular mechanisms of KIRC pathogenesis remain little known. The purpose of our study was to identify potential key genes related to the occurrence and prognosis of KIRC, which could serve as novel diagnostic and prognostic biomarkers for KIRC.

Methods

Three gene expression profiles from gene expression omnibus database were integrated to identify differential expressed genes (DEGs) using limma package. Enrichment analysis and PPI construction for these DEGs were performed by bioinformatics tools. We used Gene Expression Profiling Interactive Analysis (GEPIA) database to further analyze the expression and prognostic values of hub genes.

The GEPIA database was used to further validate the bioinformatics results. The Connectivity Map was used to identify candidate small molecules that could reverse the gene expression of KIRC.

Results

A total of 503 DEGs were obtained. The PPI network with 417 nodes and 1912 interactions was constructed. Go and KEGG pathway analysis revealed that these DEGs were most significantly enriched in excretion and valine, leucine, and isoleucine degradation, respectively. Six DEGs with high degree of connectivity (ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA) were selected as hub genes, which significantly associated with worse survival of patients. Finally, we identified the top 20 most significant small molecules and pipemidic acid was the most promising small molecule to reverse the KIRC gene expression.

Conclusions

This study first uncovered six key genes in KIRC which contributed to improving our understanding of the molecular mechanisms of KIRC pathogenesis. ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA could serve as the promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.

Programmed cell death ligand-1 (PD-L1) as a biomarker for non-small cell lung cancer (NSCLC) treatment-are we barking up the wrong tree?

Immunotherapy with monoclonal antibodies targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) has become a standard of care treatment for patients with advanced or metastatic non-small cell lung cancer (NSCLC) in first and later treatment lines with durable responses seen in approximately 10-20% of patients treated. However, the optimal selection of eligible patients who will benefit most, is far from being clear and the best biomarker has not yet been established. PD-L1 expression as a predictive biomarker for immunotherapy in NSCLC patients has shown some value for predicting response to immune checkpoint inhibitors in some studies, but not in others, and its use has been complicated by a number of factors which has prompted many researchers to establish better predictive biomarkers for immunotherapy of NSCLC. Most recently, two phase III first-line NSCLC studies have provided evidence that tumour mutational burden (TMB) correlates with the clinical response to the combination of nivolumab and ipilimumab (CheckMate-227; NCT02477826), whereas atezolizumab response was correlated with T effector gene signature expression (IMPower 150; NCT02366143). Both studies demonstrated a significant primary endpoint [progression-free survival (PFS)] benefit in the TMB group and in the group of patients expressing a T effector cell signature, respectively. However, PFS benefit in both studies was seen regardless of the PD-L1 status of all patients suggesting that TMB and T effector cell signatures may be more robust to predict clinical response following treatment with checkpoint inhibitors. The role of putative novel predictive biomarkers evaluated in the CheckMate-227 and the IMPower 150 trials may, if confirmed in future prospective studies, offer a new perspective for predicting immunotherapy treatment outcomes of NSCLC patients in the near future.

Strategies to improve monitoring disease progression, assessing cardiovascular risk, and defining prognostic biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is a major global public health problem with significant gaps in research, care, and policy. In order to mitigate the risks and adverse effects of CKD, the International Society of Nephrology has created a cohesive set of activities to improve the global outcomes of people living with CKD. Improving monitoring of renal disease progression can be done by screening and monitoring albuminuria and estimated glomerular filtration rate in primary care. Consensus on how many times and how often albuminuria and estimated glomerular filtration rate are measured should be defined. Meaningful changes in both renal biomarkers should be determined in order to ascertain what is clinically relevant. Increasing social awareness of CKD and partnering with the technological community may be ways to engage patients. Furthermore, improving the prediction of cardiovascular events in patients with CKD can be achieved by including the renal risk markers albuminuria and estimated glomerular filtration rate in cardiovascular risk algorithms and by encouraging uptake of assessing cardiovascular risk by general practitioners and nephrologists. Finally, examining ways to further validate and implement novel biomarkers for CKD will help mitigate the global problem of CKD. The more frequent use of renal biopsy will facilitate further knowledge into the underlying etiologies of CKD and help put new biomarkers into biological context. Real-world assessments of these biomarkers in existing cohorts is important, as well as obtaining regulatory approval to use these biomarkers in clinical practice. Collaborations among academia, physician and patient groups, industry, payer organizations, and regulatory authorities will help improve the global outcomes of people living with CKD.

Dietary Effect on the Proteome of the Common Octopus (Octopus vulgaris) Paralarvae

Nowadays, the common octopus (Octopus vulgaris) culture is hampered by massive mortalities occurring during early life-cycle stages (paralarvae). Despite the causes of the high paralarvae mortality are not yet well-defined and understood, the nutritional stress caused by inadequate diets is pointed out as one of the main factors. In this study, the effects of diet on paralarvae is analyzed through a proteomic approach, to search for novel biomarkers of nutritional stress. A total of 43 proteins showing differential expression in the different conditions studied have been identified. The analysis highlights proteins related with the carbohydrate metabolism: glyceraldehyde-3-phosphate-dedydrogenase (GAPDH), triosephosphate isomerase; other ways of energetic metabolism: NADP⁺-specific isocitrate dehydrogenase, arginine kinase; detoxification: glutathione-S-transferase (GST); stress: heat shock proteins (HSP70); structural constituent of eye lens: S-crystallin 3; and cytoskeleton: actin, actin-beta/gamma1, beta actin. These results allow defining characteristic proteomes of paralarvae depending on the diet; as well as the use of several of these proteins as novel biomarkers to evaluate their welfare linked to nutritional stress. Notably, the changes of proteins like S-crystallin 3, arginine kinase and NAD⁺ specific isocitrate dehydrogenase, may be related to fed vs. starving paralarvae, particularly in the first 4 days of development.

Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes

Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification. In this review, we first focus on the classical panel of albuminuria and estimated glomerular filtration rate as the primary clinical predictors of renal disease and then move our attention to novel biomarkers, primarily concentrating on assay-based multiple/panel biomarkers, proteomics biomarkers and metabolomics biomarkers. We focus on multiple biomarker panels since the molecular processes of renal disease progression in type 2 diabetes are heterogeneous, rendering it unlikely that a single biomarker significantly adds to clinical risk prediction. A limited number of prospective studies of multiple biomarkers address the predictive performance of novel biomarker panels in addition to the classical panel in type 2 diabetes. However, the prospective studies conducted so far have small sample sizes, are insufficiently powered and lack external validation. Adequately sized validation studies of multiple biomarker panels are thus required. There is also a paucity of studies that assess the effect of treatments on novel biomarker panels and determine whether initial treatment-induced changes in novel biomarkers predict changes in long-term renal outcomes. Such studies can not only improve our healthcare but also our understanding of the mechanisms of actions of existing and novel drugs and may yield biomarkers that can be used to monitor drug response. We conclude that this will be an area to focus research on in the future.

Facilitating the Validation of Novel Protein Biomarkers for Dementia: An Optimal Workflow for the Development of Sandwich Immunoassays

Different neurodegenerative disorders, such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), lead to dementia syndromes. Dementia will pose a huge impact on society and thus it is essential to develop novel tools that are able to detect the earliest, most sensitive, discriminative, and dynamic biomarkers for each of the disorders. To date, the most common assays used in large-scale protein biomarker analysis are enzyme-linked immunosorbent assays (ELISA), such as the sandwich immunoassays, which are sensitive, practical, and easily implemented. However, due to the novelty of many candidate biomarkers identified during proteomics screening, such assays or the antibodies that specifically recognize the desired marker are often not available. The development and optimization of a new ELISA should be carried out with considerable caution since a poor planning can be costly, ineffective, time consuming, and it may lead to a misinterpretation of the findings. Previous guidelines described either the overall biomarker development in more general terms (i.e., the process from biomarker discovery to validation) or the specific steps of performing an ELISA procedure. However, a workflow describing and guiding the main issues in the development of a novel ELISA is missing. Here, we describe a specific and detailed workflow to develop and validate new ELISA for a successful and reliable validation of novel dementia biomarkers. The proposed workflow highlights the main issues in the development of an ELISA and covers several critical aspects, including production, screening, and selection of specific antibodies until optimal fine-tuning of the assay. Although these recommendations are designed to analyze novel biomarkers for dementia in cerebrospinal fluid, they are generally applicable for the development of immunoassays for biomarkers in other human body fluids or tissues. This workflow is designed to maximize the quality of the developed ELISA using a time- and cost-efficient strategy. This will facilitate the validation of the dementia biomarker candidates ultimately allowing accurate diagnostic conclusions.

NGAL and ST2 levels in ambulatory patients with chronic heart failure. Clinical and echocardiographic correlates

AIM

Neutrophil gelatinase-associated lipocalin (NGAL) and ST2 receptor, a member of the interleukin-1 receptor family, are novel biomarkers with a potential role in the diagnosis and risk stratification of patients with chronic heart failure (CHF). There is however scarce data on their relation with clinical characteristics and cardiac function in patients with CHF.

METHODS

Consecutive ambulatory patients with CHF were studied. All patients underwent clinical and echocardiographic assessment, and blood samples were collected for the estimation of ST2 and NGAL serum levels during the same assessment.

RESULTS

A total of 76 patients (79% male, mean age: 63 ± 14 years), with CHF and left ventricular ejection fraction of 28 ± 7% were included. Median NGAL was 0.16 (0.09-0.275) mg/L and median ST2 was 0.0125 (0.0071-0.0176) mg/L. No association between NGAL and ST2 was observed. Multivariate analysis revealed tissue Doppler-derived right ventricular systolic velocity as an independent predictor of ST2, and the duration of HF and serum creatinine levels as independent predictors of NGAL.

CONCLUSIONS

NGAL levels depend on the renal function and the duration of HF, while ST2 levels are affected by the right but not the left ventricular function and show no association with clinical indices of HF.

Beyond cardiac troponin: recent advances in the development of alternative biomarkers for cardiovascular disease

Biomarkers complement clinical assessment, electrocardiogram and cardiac imaging in the diagnosis, risk stratification, triage and management of patients with suspected acute cardiovascular diseases. While there is broad consensus that cardiac troponin is the preferred biomarker in clinical practice for the detection of cardiomyocyte damage, the role of alternative biomarkers is less clear. In fact, despite high quality basic and clinical research by hundreds of groups worldwide, only a single new alternative cardiovascular biomarker (natriuretic peptides) has managed to achieve widespread clinical acceptance and inclusion in contemporary clinical practice guidelines in the last decade. This review aims to discuss the remaining unmet needs (and hence opportunities for new biomarkers) in two major clinical areas: early diagnosis of acute myocardial infarction; and early diagnosis and management of acute heart failure, and to evaluate in detail selected alternative biomarkers and recent insights gained from measuring novel biomarkers in large randomized treatment studies in patients with stable coronary artery disease, a setting in which alternative biomarkers may play a more prominent role in the future.

Diet quality is associated with leisure-time physical activity in individuals at cardiometabolic risk

OBJECTIVES

We investigated whether diet quality was associated with leisure-time physical activity (LTPA) and television viewing and the associations of these variables with traditional cardiovascular risk factors and novel biomarkers in individuals at cardiometabolic risk.

METHODS

A total of 193 prediabetic adults (63.7% women, mean age 54.1 years), screened for a diabetes prevention program in Brazil, participated in this cross-sectional study. Clinical data and blood samples were collected for several determinations. Twenty-four-hour recalls were used to calculate the Healthy Eating Index (HEI) adapted to Brazilian dietary habits and the International Physical Activity Questionnaire to assess physical activity level. Analysis of covariance with adjustments for age and body mass index (BMI) was employed to test associations across categories of LTPA and television viewing.

RESULTS

Stratifying according to LTPA categories, the most active subset (≥150 minutes/week) showed better HEI scores after adjustments (64.6 ± 11.0, 65.1 ± 10.3, and 68.6 ± 10.8, p = 0.02) and significant higher values of dark green and orange vegetables but not of whole grains (p = 0.06). Active individuals had lower BMI, waist circumference, inflammatory markers, and better insulin sensitivity (p < 0.05). Individuals at the highest category of television viewing had higher age-adjusted BMI (32.0 ± 6.2, 30.7 ± 6.0, and 28.8 ± 4.7 hours/week; p = 0.01) than the others. Time watching television was inversely associated with homeostasis model assessment (HOMA-IR) and C-reactive protein (CRP; p < 0.01) after adjustments but not with lipids and HEI score. Comparisons of individuals with healthy habits (better diet and higher physical activity [PA]), with those with unhealthy habits revealing better anthropometric and cardiometabolic profiles in the former group.

CONCLUSION

Diet quality assessed by the HEI adapted for Brazilian eating habits attained significance in differentiating more active from inactive at-risk individuals during leisure time. Time watching television, as a surrogate of sedentary behavior, is not useful to detect unhealthy diet quality. LTPA is indicative of better cardiometabolic profile reflected by lipid and inflammatory markers and index of insulin resistance.