Diagnostic Biomarkers Research Articles

Case report: Novel genotype of ALG2-CDG and confirmation of the heptasaccharide glycan (NeuAc-Gal-GlcNAc-Man2-GlcNAc2) as a specific diagnostic biomarker

Case report: Novel genotype of ALG2-CDG and confirmation of the heptasaccharide glycan (NeuAc-Gal-GlcNAc-Man2-GlcNAc2) as a specific diagnostic biomarker

Comprehensive bioinformatics analytics and in vivo validation reveal SLC31A1 as an emerging diagnostic biomarker for acute myocardial infarction.

Globally, Acute Myocardial Infarction (AMI) is a common cause of heart failure (HF), which has been a leading cause of mortality resulting from non-communicable diseases. On the other hand, increasing evidence suggests that the role of energy production within the mitochondria strongly links to the development and progression of heart diseases, while Cuproptosis, a newly identified cell death mechanism, has not yet been comprehensively analyzed from the aspect of cardiovascular medicine. 8 transcriptome profiles curated from the GEO database were integrated, from which a diagnostic model based on the Stacking algorithm was established. The efficacy of the model was evaluated in a multifaced manner (i.e., by Precision-Recall curve, Receiver Operative Characteristic curve, etc.). We also sequenced our animal models at the bulk RNA level and conducted qPCR and immunohistochemical staining, with which we further validated the expression of the key contributor gene to the model. Finally, we explored the immune implications of the key contributor gene. A merged machine learning model containing 4 Cuproptosis-related genes (i.e., PDHB, CDKN2A, GLS, and SLC31A1) for robust AMI diagnosis was developed, in which SLC31A1 served as the key contributor. Through in vivo modeling, we validated the aberrant overexpression of SLC31A1 in AMI. Besides, further transcriptome analysis revealed that its high expression was correlated with significant potential immunological implications in the infiltration of many immune cell types, especially monocyte. We constructed an AMI diagnostic model based on Cuproptosis-related genes and validated the key contributor gene in animal modeling. We also analyzed the effects on the immune system for its overexpression in AMI.

Exosome-transported circ_0061407 and circ_0008103 play a tumour-repressive role and show diagnostic value in non-small-cell lung cancer

BackgroundCircular RNAs (circRNAs), one of the major contents of exosomes, have been shown to participate in the occurrence and progression of cancers. The role and the diagnostic potential of exosome-transported circRNAs in non-small-cell lung cancer (NSCLC) remain largely unknown.MethodsThe NSCLC-associated exosomal circ_0061407 and circ_0008103 were screened by circRNA microarray. The role of circ_0061407 and circ_0008103 in NSCLC was examined in vitro and in vivo. The encapsulation of the two circRNAs into exosomes and the transport to recipient cells were observed by confocal microscopy. The effects of exosome-transported circ_0061407 and circ_0008103 on recipient cells were investigated using a co-culture device. Bioinformatics analyses were performed to predict the mechanisms by which circ_0061407 and circ_0008103 affected NSCLC. The quantitative polymerase chain reaction was used to quantify the exosome-containing circ_0061407 and circ_0008103 in the serum samples of healthy, pneumonia, benign lung tumours, and NSCLC. The diagnostic efficacy was evaluated using receiver operating characteristic curves.ResultsThe levels of circ_0061407 and circ_0008103 within exosomes were down-regulated in the serum of patients with NSCLC. The up-regulation of circ_0061407 and circ_0008103 inhibited the proliferation, migration/invasion, cloning formation of NSCLC cells in vitro and inhibited lung tumour growth in vivo. Circ_0061407 and circ_0008103 were observed to be packaged in exosomes and transported to recipient cells, where they inhibited the proliferation, migration/invasion, and cloning formation abilities of the recipient cells. Moreover, circ_0061407 and circ_0008103 might be involved in the progression of NSCLC by interacting with microRNAs and proteins. Additionally, lower serum exosomal circ_0061407 and circ_0008103 levels were associated with advanced pathological staging and distant metastasis.ConclusionsThis study identified two novel exosome-transported circRNAs (circ_0061407 and circ_0008103) associated with NSCLC. These findings may provide additional insights into the development of NSCLC and potential diagnostic biomarkers for NSCLC.

Downregulation of miR-29a as a possible diagnostic biomarker for schizophrenia

BackgroundMicroRNAs (miRNAs) are epigenetic factors regulating many genes involved in brain development. Dysregulation of miRNA could result in dysregulation of genes which may contribute to diseases affecting the brain and behavior (e.g., schizophrenia). miR-29 family is a miRNA family contributing to brain maturation. miR-29 knockout in animal studies is reported to correlate with psychiatric disorders very similar to those seen in schizophrenia. In this study, we aimed to evaluate the miR-29a level in patients with schizophrenia and its potential value in the diagnosis of schizophrenia.Materials and methodsThe serum sample of 42 patients with schizophrenia and 40 healthy subjects were obtained from the Azeri Recent onset/Acute phase psychosis Survey (ARAS) Cohort study. After preparations, the expression level of miR-29a was investigated by real-time PCR. The SPSS and GraphPad prism software were used to analyze the relation between miR-29a level and clinical parameters and its potential as a biomarker for the diagnosis of schizophrenia.ResultsOur study showed a significantly lower miR-29a level in patients compared to healthy controls (p = 0.0012). Furthermore, miR-29a level was significantly lower in some types of schizophrenia (p = 0.024). miR-29a level was not related to sex, age, or heredity (p > 0.05). miR-29a also showed 80% specificity and 71.43% sensitivity in the diagnosis of schizophrenia.ConclusionDownregulation of miR-29a in schizophrenia is significantly related to the development of this illness. It might have the potential as a biomarker for schizophrenia.

Potential clinical value of fibrinogen-like protein 1 as a serum biomarker for the identification of diabetic cardiomyopathy

Diabetic individuals with diabetic cardiomyopathy (DbCM) present with abnormal myocardial structure and function. DbCM cannot be accurately diagnosed due to the lack of suitable diagnostic biomarkers. In this study, 171 eligible participants were divided into a healthy control (HC), type 2 diabetes mellitus (T2DM) patients without DbCM (T2DM), or DbCM group. Serum fibrinogen-like protein 1 (FGL-1) and other biochemical parameters were determined for all participants. Serum FGL-1 levels were significantly higher in patients with DbCM compared with those in the T2DM group and HCs. Serum FGL-1 levels were negatively correlated with left ventricular fractional shortening and left ventricular ejection fraction (LVEF) and positively correlated with left ventricular mass index in patients with DbCM after adjusting for age, sex and body mass index. Interaction of serum FGL-1 and triglyceride levels on LVEF was noted in patients with DbCM. A composite marker including serum FGL-1 and triglycerides could differentiate patients with DbCM from those with T2DM and HCs with an area under the curve of 0.773 and 0.789, respectively. Composite marker levels were negatively correlated with N-terminal B-type natriuretic peptide levels in patients with DbCM. Circulating FGL-1 may therefore be a valuable index reflecting cardiac functions in DbCM and to diagnose DbCM.

A study of the association between single nucleotide polymorphisms of the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene and the risk of ankylosing spondylitis in Egyptians

BackgroundAnkylosing spondylitis (AS) is often regarded as the prototypical manifestation of spondylo-arthropathies that prevalently involves the axial skeleton with the potential attribution of ERAP2 polymorphisms to AS predisposition. The purpose of this study was to determine the genetic association between ERAP2 gene rs2910686, and rs2248374 single nucleotide polymorphisms (SNPs) and the risk of ankylosing spondylitis in the Egyptian population.Methods and resultsA cross-sectional work involved 200 individuals: 100 AS individuals diagnosed based on modified New York criteria in 1984 with 100 healthy controls matched in age and gender. The study included a comprehensive evaluation of historical data, clinical examinations, and evaluation of the activity of the disease using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). A comprehensive laboratory and radiological evaluation were conducted, accompanied by an assessment and genotyping of the ERAP2 gene variants rs2248374 and rs2910686. This genotyping was performed utilizing a real-time allelic discrimination methodology.Highly statistically substantial variations existed among the AS patients and the healthy control group regarding rs2910686 and rs2248374 alleles. There was a statistically significant difference between rs2910686 and rs2248374 regarding BASDAI, BASFI, mSASSS, ASQoL, V.A.S, E.S.R, and BASMI in the active AS group.ConclusionsERAP2 gene SNPs have been identified as valuable diagnostic biomarkers for AS patients in the Egyptian population being a sensitive and non-invasive approach for AS diagnosis especially rs2910686. Highly statistically significant variations existed among the AS patients and the healthy control group regarding rs2910686 alleles and genotypes.Further research is recommended to explore the potential therapeutic implications of these SNPs.

Functional metabolomics characterizes the contribution of farnesoid X receptor in pyrrolizidine alkaloid-induced hepatic sinusoidal obstruction syndrome.

Consumption of herbal products containing pyrrolizidine alkaloids (PAs) is one of the major causes for hepatic sinusoidal obstruction syndrome (HSOS), a deadly liver disease. However, the crucial metabolic variation and biomarkers which can reflect these changes remain amphibious and thus to result in a lack of effective prevention, diagnosis and treatments against this disease. The aim of the study was to determine the impact of HSOS caused by PA exposure, and to translate metabolomics-derived biomarkers to the mechanism. In present study, cholic acid species (namely, cholic acid, taurine conjugated-cholic acid, and glycine conjugated-cholic acid) were identified as the candidate biomarkers (area under the ROC curve 0.968 [95% CI 0.908-0.994], sensitivity 83.87%, specificity 96.55%) for PA-HSOS using two independent cohorts of patients with PA-HSOS. The increased primary bile acid biosynthesis and decreased liver expression of farnesoid X receptor (FXR, which is known to inhibit bile acid biosynthesis in hepatocytes) were highlighted in PA-HSOS patients. Furtherly, a murine PA-HSOS model induced by senecionine (50mg/kg, p.o.), a hepatotoxic PA, showed increased biosynthesis of cholic acid species via inhibition of hepatic FXR-SHP singling and treatment with the FXR agonist obeticholic acid restored the cholic acid species to the normal levels and protected mice from senecionine-induced HSOS. This work elucidates that increased levels of cholic acid species can serve as diagnostic biomarkers in PA-HSOS and targeting FXR may represent a therapeutic strategy for treating PA-HSOS in clinics.

Targeted metabolomics combined with machine learning to identify and validate new biomarkers for early SLE diagnosis and disease activity.

The early diagnosis of systemic lupus erythematosus (SLE) and the assessment of disease activity progression remain a great challenge. Targeted metabolomics has great potential to identify new biomarkers of SLE. Serum from 44 healthy participants and 89 SLE patients were analyzed using HM400 high-throughput targeted metabolomics. Machine learning (ML) with seven learning models and trained the model several times iteratively selected the two best prediction model in a competitive way, which were independent validated by enzyme-linked immunosorbent (ELISA) with 90 SLE patients. In this study, 146 differential metabolites, most of them organic acids, amino acids, and bile acids, were detected between patients with initial SLE and healthy participants, and 8 potential biomarkers were found by intersection of ML and statistics (area under the curve [AUC] > 0.95) showing a significant positive correlation with clinical indicators. In addition, we identified and validated 2 potential biomarkers for SLE classification (P < 0.05, AUC > 0.775; N-Methyl-L-glutamic acid, L-2-aminobutyric acid) showing a significant correlation with the SLE Disease Activity Index. These differential metabolites were mainly involved in metabolic pathways, amino acid biosynthesis, 2-oxocarboxylic acid metabolism and other pathways. This study indicated that the tricarboxylic acid cycle might be associated with SLE drug therapy. We identified 8 diagnostic models biomarkers and 2 biomarkers that could be used to identify initial SLE and distinguish different activity degree, which will promote the development of new tools for the diagnosis and evaluation of SLE.

Elevated cathepsin S serum levels in new-onset type 1 diabetes and autoantibody-positive siblings.

Accumulating data suggest a role for the lysosomal protease cathepsin S (CTSS) in type 1 diabetes. Circulating CTSS is increased in type 1 diabetes; however, whether CTSS has protective or deleterious effects is unclear. The study's objectives were to examine the biomarker potential of CTSS in new-onset type 1 diabetes, and to investigate the expression and secretion of CTSS in human islets and β cells. The CTSS level was analyzed in serum from children with new-onset type 1 diabetes and autoantibody-positive and -negative siblings by ELISA. The expression and secretion of CTSS were evaluated in isolated human islets and EndoC-βH5 cells by real-time qPCR, immunoblotting, and ELISA. The CTSS serum level was elevated in children with new-onset type 1 diabetes and positively associated with autoantibody status in healthy siblings. Human islets and EndoC-βH5 cells demonstrated induction and secretion of CTSS after exposure to pro-inflammatory cytokines, a model system of islet inflammation. Analysis of publicly available single-cell RNA sequencing data on human islets showed that elevated CTSS expression was exclusive for the β cells in donors with type 1 diabetes as compared to non-diabetic donors. These findings suggest a potential of CTSS as a diagnostic biomarker in type 1 diabetes.

The role of exosome derived miRNAs in inter-cell crosstalk among insulin-related organs in type 2 diabetes mellitus.

Exosomes are small extracellular vesicles secreted by almost all cell types, and carry diverse cargo including RNA, and other substances. Recent studies have focused exosomal microRNAs (miRNAs) on various human diseases, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (METS) which accompany the occurrence of insulin resistance. The regulation of insulin signaling has connected with some miRNA expression which play a significant regulatory character in insulin targeted cells or organs, such as fat, muscle, and liver. The miRNAs carried by exosomes, through the circulation in the body fluids, mediate all kinds of physiological and pathological process involved in the human body. Studies have found that exosome derived miRNAs are abnormally expressed and cross-talked with insulin targeted cells or organs to affect insulin pathways. Further investigations of the mechanisms of exosomal miRNAs in T2DM will be valuable for the diagnostic biomarkers and therapeutic targets of T2DM. This review will summarize the molecular mechanism of action of the miRNAs carried by exosomes which are secreted from insulin signaling related cells, and elucidate the pathogenesis of insulin resistance to provide a new strategy for the potential diagnostic biomarkers and therapeutic targets for the type 2 diabetes.

Extracellular vesicles in non-small cell lung cancer stemness and clinical applications

Non-small cell lung carcinoma (NSCLC) accounts for 85% of lung cancers, the leading cause of cancer associated deaths in the US and worldwide. Within NSCLC tumors, there is a subpopulation of cancer cells termed cancer stem cells (CSCs) which exhibit stem-like properties that drive NSCLC progression, metastasis, relapse, and therapeutic resistance. Extracellular vesicles (EVs) are membrane-bound nanoparticles secreted by cells that carry vital messages for short- and long-range intercellular communication. Numerous studies have implicated NSCLC CSC-derived EVs in the factors associated with NSCLC lethality. In this review, we have discussed mechanisms of EV-directed cross-talk between CSCs and cells of the tumor microenvironment that promote stemness, tumor progression and metastasis in NSCLC. The mechanistic studies discussed herein have provided insights for developing novel NSCLC diagnostic and prognostic biomarkers and strategies to therapeutically target the NSCLC CSC niche.

Identification and validation of the surface proteins FIBG, PDGF-β, and TGF-β on serum extracellular vesicles for non-invasive detection of colorectal cancer: experimental study.

The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multicenter study comprising 404 individuals. In the application phase, we evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. Through 4D-DIA proteomic analysis, we identified 7 potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of 3 EVs surface proteins, FIBG, PDGF-β and TGF-β, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an AUC of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-β, and TGF-β as novel diagnostic biomarkers for CRC. And the development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Serum and urine lipidomic profiles identify biomarkers diagnostic for seropositive and seronegative rheumatoid arthritis

ObjectiveSeronegative rheumatoid arthritis (RA) is defined as RA without circulating autoantibodies such as rheumatoid factor and anti-citrullinated protein antibodies; thus, early diagnosis of seronegative RA can be challenging. Here, we aimed to identify diagnostic biomarkers for seronegative RA by performing lipidomic analyses of sera and urine samples from patients with RA.MethodsWe performed untargeted lipidomic analysis of sera and urine samples from 111 RA patients, 45 osteoarthritis (OA) patients, and 25 healthy controls (HC). These samples were divided into a discovery cohort (n = 97) and a validation cohort (n = 84). Serum samples from 20 patients with systemic lupus erythematosus (SLE) were also used for validation.ResultsThe serum lipidome profile of RA was distinguishable from that of OA and HC. We identified a panel of ten serum lipids and three urine lipids in the discovery cohort that showed the most significant differences. These were deemed potential lipid biomarker candidates for RA. The serum lipid panel was tested using a validation cohort; the results revealed an accuracy of 79%, a sensitivity of 71%, and a specificity of 86%. Both seropositive and seronegative RA patients were differentiated from patients with OA, SLE, and HC. Three urinary lipids showing differential expression between RA from HC were identified with an accuracy of 84%, but they failed to differentiate RA from OA. There were five lipid pathways that differed between seronegative and seropositive RA.ConclusionHere, we identified a panel of ten serum lipids as potential biomarkers that can differentiate RA from OA and SLE, regardless of seropositivity. In addition, three urinary lipids had diagnostic utility for differentiating RA from HC.

Clinical Use of Molecular Biomarkers in Canine and Feline Oncology: Current and Future

Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for testing dogs and cats in a clinical setting, discussing their utility in each biomarker class. We also look at some emerging molecular biomarkers that are promising for clinical use. Finally, we discuss the hurdles that need to be overcome in going ‘bench to bedside’, i.e., the translation from discovery of genomic alterations to adoption by veterinary clinicians. As we understand more of the genomics underlying canine and feline tumours, molecular biomarkers will undoubtedly become a mainstay in delivering precision veterinary care to dogs and cats with cancer.

Abstract PO1-19-05: COGNITION/-GUIDE – Implementation of Precision Oncology in Early High-Risk Breast Cancer

Abstract Background: The concept of precision oncology is nowadays increasingly implemented into clinical practice but is predominantly restricted to the metastatic setting limiting the benefits to prolongation of progression-free-survival (PFS). Implementation of precision oncology at an earlier disease stage with less tumor burden, heterogeneity and a higher capacity of tumor lesions to inform on the molecular tumor landscape holds the promise to impact cure rates. Methods: The prospective COGNITION/-GUIDE precision oncology platform encompasses the COGNITION diagnostic multi-omics biomarker screening platform (NCT05906407) linked to the multi-arm phase II COGNITION-GUIDE umbrella trial (NCT05332561). Based on a two-step consenting procedure, patients with early breast cancer (eBC) and poor response towards standard-of-care (SOC) neoadjuvant chemotherapy (NACT) are first enrolled into the COGNITION diagnostic platform. Residual bulk tumors are subjected to whole-genome- (WGS)/whole exome- (WES) and RNA-sequencing to enable streamlined detection of a rigorous biomarker-framework for subsequent genomics-guided arm allocation. Pilot analyses revealed that 78% (81/104) of high-risk tumors (TNBC or HER2+ BC with non-pCR or HR+/HER2- BC with non-pCR and CPS-EG score ≥ 3, or ypN+ and CPS-EG score ≥ 2) can be successfully sequenced and discussed within an interdisciplinary molecular tumor board. In 67% (70/104) eligible biomarker-profiles could be identified for potential biomarker-guided therapeutic intervention. In a second step, having completed all standard-of-care neoadjuvant and post-neoadjuvant treatments (except endocrine therapy, which can be administered simultaneously to the experimental therapy), patients can be enrolled into one of 6 biomarker-based arms in the COGNITION-GUIDE phase II trial (atezolizumab, inavolisib, ipatasertib, olaparib, sacituzumab govitecan or trastuzumab/pertuzumab). Primary end point is invasive disease-free survival (IDFS) at 4 years after surgery in the whole study population. Secondary endpoints are overall survival (OS), IDFS in each treatment arm, distant disease-free survival (DDFS) and patient-reported outcomes (PROs). Enrollment in COGNITION-GUIDE started in Q2/2023 and 240 patients will be enrolled in 5 German sites until Q2/2027. A comprehensive biomarker discovery program is integrated on longitudinal tumor tissue and liquid biopsies for exploratory analyses. Further clinical work and accrual will be reported at the meeting. Conclusion: The theranostic COGNITION/-GUIDE platform moves the concept of precision oncology to a potentially curative but still high-risk stage of eBC following SOC NACT. Hence, this novel application in the field of precision oncology harbours the prospect to increase cure rates. Citation Format: Verena Thewes, Luise Strassl, Marc Zapatka, Mario Hlevnjak, Constantin Pixberg, Christian Maurer, Katharina Smetanay, Carlo Fremd, Laura Michel, Sabine Heublein, Celina V. Wagner, Jan-Philip Suppelna, Lars Buschhorn, Albrecht Stenzinger, Renate Haidinger, Eva Schumacher-Wulf, Sibylle Loibl, Pauline Wimberger, Jens-Uwe Blohmer, Peter A. Fasching, Wolfgang Janni, Richard F. Schlenk, Peter Lichter, Andreas Schneeweiss. COGNITION/-GUIDE – Implementation of Precision Oncology in Early High-Risk Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-19-05.

Pleural mesothelioma from fluoro-edenite exposure: PACAP and PAC1 receptor. A preliminary report.

Pleural mesothelioma is a devastating malignancy primarily associated with asbestos exposure. However, emerging evidence suggests that exposure to fluoro-edenite fibers, a naturally occurring mineral fiber, can also lead to the development of pleural mesothelioma. In this study, based on the hypothesis that pituitary adenylate cyclase-activating polypeptide (PACAP) and PACAP-preferring receptor (PAC1R) expressions could be dysregulated in pleural mesothelioma samples and that they could potentially act as diagnostic or prognostic biomarkers, we aimed to investigate the immunohistochemical expression of PACAP and PAC1R in pleural biopsies from patients with pleural mesothelioma exposed to fluoro-edenite fibers. A total of 12 patients were included in this study, and their biopsies were processed for immunohistochemical analysis to evaluate the expression of PACAP and its receptor. The study revealed a correlation between the overexpression of PACAP and PAC1R and shorter overall survival in patients with malignant mesothelioma. These findings suggest that PACAP and PAC1R expression levels could serve as potential prognostic biomarkers for malignant mesothelioma. Furthermore, the immunohistochemical analysis of PACAP and PAC1R may provide valuable information for clinicians to guide therapeutic decisions and identify patients with poorer prognosis.

Disulfidptosis in head and neck squamous carcinoma: Integrative bioinformatic and in-vitro analysis.

Head and neck squamous carcinoma (HNSC) is a prevalent global malignancy with limited treatment options, which necessitates the development of novel therapeutic strategies. Disulfidptosis, a recently discovered and unique cell death pathway, may offer promise as a treatment target in HNSC. We identified disulfidptosis-related genes (DRGs) using multiple algorithms and developed a prognostic model based on a disulfidptosis-related gene index (DRGI). The model's predictive accuracy was assessed by ROC-AUC, and patients were stratified by risk scores. We investigated the tumor immune microenvironment, immune responses, tumorigenesis pathways, and chemotherapy sensitivity (IC50). We also constructed a diagnostic model using 20 machine-learning algorithms and validated PCBP2 expression through RT-qPCR and western blot. We developed a 12-DRG DRGI prognostic model, classifying patients into high- and low-risk groups, with the high-risk group experiencing poorer clinical outcomes. Notable differences in tumor immune microenvironment and chemosensitivity were observed, with reduced immune activity and suboptimal treatment responses in the high-risk group. Advanced machine learning and in-vitro experiments supported DRGI's potential as a reliable HNSC diagnostic biomarker. We established a novel DRGI-based prognostic and diagnostic model for HNSC, exploring its tumor immune microenvironment implications, and offering valuable insights for future research and clinical trials.

Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD).

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.

Association between neuropsychological assessment and amyloid status in a clinical setting.

Large research cohorts show robust associations between neuropsychological tests and Alzheimer's disease (AD) biomarkers, but studies in clinical settings are limited. The increasing availability of AD biomarkers to the practicing clinician makes it important to understand the relationship between comprehensive clinical neuropsychological assessment and biomarker status. This study examined concordance between practicing clinical neuropsychologists' diagnostic impressions and AD biomarker status in patients seen at an outpatient medical center, with a secondary aim of defining the characteristics of discordant cases. Participants (N = 79) seen for clinical neuropsychological assessment who subsequently underwent lumbar puncture or amyloid positron emission tomography imaging were identified via retrospective chart review. Concordance between clinical neuropsychological diagnosis (non-AD, indeterminate, possible/probable AD) and AD biomarker status (negative, indeterminate, positive) was determined. Individual test score data were used to examine between-group differences based on amyloid status. AD biomarker positive and negative patients did not differ on individual neuropsychological tests after correcting for multiple comparisons, though the small number of AD biomarker indeterminate individuals performed better than biomarker positive patients. However, there was 76.7% concordance between neuropsychologists' diagnostic impressions and AD biomarker status (88% sensitivity and 55% specificity of neuropsychological assessment in detecting AD biomarker status). AD biomarker negative patients diagnosed as possible/probable AD (discordant) versus non-AD (concordant) had significantly lower Neuropsychological Assessment Battery Story Delayed Recall, higher Wechsler Adult Intelligence Scale-Fourth Edition Coding, and higher Trail-Making A (i.e., an amnestic memory profile). Comprehensive neuropsychological assessment showed modest concordance with AD biomarker status in patients seen in an outpatient medical center for routine clinical care. Low specificity for the clinical diagnosis of AD could be explained by the multiplicity of etiologies that cause memory impairment (i.e., TAR DNA-binding protein 43, suspected non-AD pathology). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Circulating MiR-1185¸ MiR-3183, and MiR-584 Levels in Plasma as Diagnostic Non-invasive Biomarkers for Early Detection of Breast Cancer

Introduction: MicroRNAs (miRNAs) are non-coding RNA molecules with short sequences that function as main post-transcriptional gene regulators of different biological pathways via negative regulation of gene expression, thereby leading to either mRNA degradation or translational blockade. Dysregulated expression of these miRNAs has been related etiologically to many human diseases, including breast cancer. Various cellular processes of breast cancer progression, including cell proliferation, apoptosis, metastasis, recurrence and chemodrug resistance, are modulated by oncogenic miRNA (oncomiR). Objective: The objective of this investigation was to study the expression level and potential diagnostic/ prognostic roles of circulating microRNAs (miR-3183, miR-1185, and miR-584) as novel breast cancer biomarkers. Method: The current study was conducted on 99 breast cancer (BC) female patients, aged between 20-63 years old, as the case group and 50 age-matched healthy females as control (HC). After microRNA extraction from the serum samples, real-time PCR was carried out for relative expression quantification of miR-1185, miR-3183a, and miR-584. The ROC curve analysis was performed to investigate the diagnostic value of miRNAs. Result: It was demonstrated that miRNA-1185, miRNA-584, and miRNA-3183 were significantly up-regulated (p-values &lt;0.0001) in female BC cases compared to the control group. Besides, based on the ROC analysis for BC versus HC, it was revealed that the AUC for miRNA-584 was 0.844 (95% confidence interval (CI) and could be proposed as a diagnostic biomarker for breast cancer screening and follow-up. Conclusion: MiRNAs expression profiling using blood-based samples demonstrated their upregulation in the serum and plasma and revealed the concept that circulating miRNAs have high potential as novel noninvasive biomarkers for cancer diagnosis and screening.