Transcriptomic analysis identifies the shared diagnostic biomarkers and immune relationship between Atherosclerosis and abdominal aortic aneurysm based on fatty acid metabolism gene set

Background

Epidemiological research has demonstrated that there is a connection between lipid metabolism disorder and an increased risk of developing arteriosclerosis (AS) and abdominal aortic aneurysm (AAA). However, the precise relationship between lipid metabolism, AS, and AAA is still not fully understood. The objective of this study was to examine the pathways and potential fatty acid metabolism-related genes (FRGs) that are shared between AS and AAA.

Methods

AS- and AAA-associated datasets were retrieved from the Gene Expression Omnibus (GEO) database, and the limma package was utilized to identify differentially expressed FRGs (DFRGs) common to both AS and AAA patients. Functional enrichment analysis was conducted on the (DFRGs), and a protein-protein interaction (PPI) network was established. The selection of signature genes was performed through the utilization of least absolute shrinkage and selection operator (LASSO) regression and random forest (RF). Subsequently, a nomogram was developed using the results of the screening process, and the crucial genes were validated in two separate external datasets (GSE28829 and GSE17901) as well as clinical samples. In the end, single-sample gene set enrichment analysis (ssGSEA) was utilized to assess the immune cell patterns in both AS and AAA. Additionally, the correlation between key crosstalk genes and immune cell was evaluated.

Results

In comparison to control group, both AS and AAA patients exhibited a decrease in fatty acid metabolism score. We found 40 DFRGs overlapping in AS and AAA, with lipid and amino acid metabolism critical in their pathogenesis. PCBD1, ACADL, MGLL, BCKDHB, and IDH3G were identified as signature genes connecting AS and AAA. Their expression levels were confirmed in validation datasets and clinical samples. The analysis of immune infiltration showed that neutrophils, NK CD56dim cells, and Tem cells are important in AS and AAA development. Correlation analysis suggested that these signature genes may be involved in immune cell infiltration.

Conclusion

The fatty acid metabolism pathway appears to be linked to the development of both AS and AAA. Furthermore, PCBD1, ACADL, MGLL, BCKDHB, and IDH3G have the potential to serve as diagnostic markers for patients with AS complicated by AAA.

The Combination of circEPSTI1 and MIF Offers Diagnostic Value for Endometrial Cancer

Background

Circular RNAs (circRNAs) exhibit unique patterns of expression and high levels of stability in patient plasma samples such that they represent ideal non-invasive biomarkers that can be leveraged to detect a wide array of diseases including endometrial cancer (EC). This study was designed to identify circRNAs with potential diagnostic utility in serum samples from EC patients while also evaluating the utility of macrophage migration inhibitory factor (MIF) as a biomarker when screening for this form of cancer in the clinic.

Methods

Levels of circEPSTI1 and MIF were assessed in the plasma of EC patients and healthy subjects (n=186 each) through qPCR and ELISAs. The diagnostic utility of these biomarkers was assessed with receiver operating characteristic curve (ROC) analyses.

Results

Relative to healthy subjects, EC patient serum contained significantly elevated circEPSTI1 and MIF. An association was noted between circEPSTI1 expression in stages, histologic grade, and residual tumor. ROC curves confirmed that serum circEPSTI1 levels distinguished between controls and patients with EC with an Area of 0.835 and serum MIF levels distinguished between controls and patients with EC with an Area of 0.6646. When instead diagnosing patients based on the combination of MIF and circEPSTI1, the Area further rose to 0.8604.

Conclusion

Assessing the combination of circEPSTI1 and MIF may be a viable approach to reliably diagnosing EC.

Large-Scale Proteome Profiling Identifies Biomarkers Associated with Suspected Neurosyphilis Diagnosis

Neurosyphilis (NS) is a central nervous system (CNS) infection caused by Treponema pallidum (T. pallidum). NS can occur at any stage of syphilis and manifests as a broad spectrum of clinical symptoms. Often referred to as "the great imitator," NS can be easily overlooked or misdiagnosed due to the absence of standard diagnostic tests, potentially leading to severe and irreversible organ dysfunction. In this study, proteomic and machine learning model techniques are used to characterize 223 cerebrospinal fluid (CSF) samples to identify diagnostic markers of NS and provide insights into the underlying mechanisms of the associated inflammatory responses. Three biomarkers (SEMA7A, SERPINA3, and ITIH4) are validated as contributors to NS diagnosis through multicenter verification of an additional 115 CSF samples. We anticipate that the identified biomarkers will become effective tools for assisting in diagnosis of NS. Our insights into NS pathogenesis in brain tissue may inform therapeutic strategies and drug discoveries for NS patients.

A state-of-the-art overview of candidate diagnostic biomarkers for Attention-deficit/hyperactivity disorder (ADHD)

INTRODUCTION

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental conditions and is highly heterogeneous in terms of symptom profile, associated cognitive deficits, comorbidities, and outcomes. Heterogeneity may also affect the ability to recognize and diagnose this condition. The diagnosis of ADHD is primarily clinical but there are increasing research efforts aiming at identifying biomarkers that can aid the diagnosis.

AREAS COVERED

We first discuss the definition of biomarkers and the necessary research steps from discovery to implementation. We then provide a broad overview of research studies on candidate diagnostic biomarkers in ADHD encompassing genetic/epigenetic, biochemical, neuroimaging, neurophysiological and neuropsychological techniques. Finally, we critically appraise current limitations in the field and suggest possible ways forward.

EXPERT OPINION

Despite the large number of studies and variety of techniques used, no promising biomarkers have been identified so far. Clinical and biological heterogeneity as well as methodological limitations, including small sample size, lack of standardization, confounding factors, and poor replicability, have hampered progress in the field. Going forward, increased international collaborative efforts are warranted to support larger and more robustly designed studies, develop multimodal datasets to combine biomarkers and improve diagnostic accuracy, and ensure reproducibility and meaningful clinical translation.

Surface protein profiling and subtyping of extracellular vesicles in body fluids reveals non-CSF biomarkers of Alzheimer's disease

Noninvasive and effortless diagnosis of Alzheimer's disease (AD) remains challenging. Here we report the multiplexed profiling of extracellular vesicle (EV) surface proteins at the single EV level in five types of easily accessible body fluids using a proximity barcoding assay (PBA). A total of 183 surface proteins were detected on the EVs from body fluids collected from APP/PS1 transgenic mice and patients with AD. The AD-associated differentially expressed EV proteins could discriminate between the control and AD/AD model samples with high accuracy. Based on machine learning predictive models, urinary EV proteins exhibited the highest diagnostic potential compared to those on other biofluid EVs, both in mice and humans. Single EV analysis further revealed AD-associated EV subpopulations in the tested body fluids, and a urinary EV subpopulation with the signature proteins PLAU, ITGAX and ANXA1 could diagnose patients with AD in blinded datasets with 88% accuracy. Our results suggest that EVs and their subpopulations from noninvasive body fluids, particularly urine, are potential diagnostic biomarkers for AD.

Untargeted metabolomics reveals potential plasma biomarkers for diagnosis of primary aldosteronism using liquid chromatography-mass spectrometry

Metabolite profiling has the potential to comprehensively bridge phenotypes and complex heterogeneous physiological and pathological states. We performed a metabolomics study using parallel liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis to screen for biomarkers of primary aldosteronism (PA) from a cohort of 111 PA patients and 218 primary hypertension (PH) patients. Hydrophilic interaction chromatography and reversed-phase liquid chromatography separations were employed to obtain a global plasma metabolome of endogenous metabolites. The satisfactory classification between PA and PH patients was obtained using the MVDA model. A total of 35 differential metabolites were screened out and identified. A diagnostic biomarker panel was established using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model and receiver operating characteristic analysis. Joint analysis with clinical indicators, including plasma supine aldosterone level, plasma orthostatic aldosterone level, body mass index, and blood potassium, revealed that the combination of metabolite biomarker panel and plasma supine aldosterone has the best clinical diagnostic efficacy.

TOX, TWIST1, STAT4, and SATB1 protein expressions in early-stage mycosis fungoides

BACKGROUND

Diagnosis of early mycosis fungoides (eMF) is challenging and often delayed as many of its clinical and histopathologic features may mimic various benign inflammatory dermatoses (BIDs). The products of the thymocyte selection-associated high mobility group box (TOX), twist family BHLH transcription factor 1 (TWIST1), signal transducer and activator of transcription 4 (STAT4), and special AT-rich sequence-binding protein 1 (SATB1) genes function as transcription factors and are involved in the pathogenesis of MF.

OBJECTIVES

We aim to determine the diagnostic value of TOX, TWIST1, STAT4, and SATB1 protein expressions in eMF.

METHODS

This non-randomized, controlled, prospective analytic study was conducted by performing immunohistochemistry staining with TOX, TWIST1, STAT4, and SATB1 polyclonal antibodies in lesional skin biopsies of eMF and BID patients. Nuclear staining of lymphocytes was compared between eMF and BIDs, and the capacity of these antibodies to predict eMF was determined.

RESULTS

Immunostainings with anti-TWIST1 showed an increase in protein expression (p = 0.003) and showed a decrease with anti-SATB1 antibodies in eMF compared to BIDs (p = 0.005) while anti-TOX and anti-STAT4 antibodies did not exhibit significant differences (p = 0.384; p = 0.150). Receiver operating characteristic analysis showed that immunohistochemical evaluations of TWIST1 and SATB1 protein expressions can differentiate eMF (area under the curve [AUC]: 0.728, 95% confidence interval [CI]: 0.605-0.851, p = 0.002; AUC: 0.686, 95% CI: 0.565-0.807, p = 0.013).

CONCLUSIONS

TWIST1 and SATB1 are potential diagnostic markers for the histologic diagnosis of eMF.

Comprehensive Analysis Reveals Deoxyribonuclease 1 as a Potential Prognostic and Diagnostic Biomarker in Human Cancers

BACKGROUND

Deoxyribonuclease 1 (DNASE1) is an important gene associated with several cancers, including liver, bladder, and gastric cancer. It has been linked to autoimmune illnesses, including systemic lupus erythematosus, which may lead to cancer formation. However, the role of DNASE1 in cancer has not been studied.

MATERIALS AND METHODS

We performed a pan-cancer analysis using bioinformatics tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) databases, Kaplan-Meier plotter, and cBioPortal, to investigate the expression of DNASE1 across various cancers as well as its association with immune infiltration and genetic alterations. Public datasets were used to validate DNASE1 expression in kidney renal clear cell carcinoma (KIRC) and kidney papillary renal cell carcinoma (KIRP) samples.

RESULTS

DNASE1 was found to be highly expressed in many cancers, such as bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), and was lowly expressed in other cancers, including KIRC, KIRP, and thyroid carcinoma (THCA). Additionally, TIMER results showed an association of DNASE1 with immune cell infiltration in KIRC and KIRP. Survival analysis indicated that high DNASE1 expression was associated with poor prognosis in KIRC. We also discovered that altered DNASE1 expression was related to poor prognosis in The Cancer Genome Atlas (TCGA) tumors.

CONCLUSION

DNASE1 could potentially be used as a prognostic and diagnostic biomarker for KIRC and as a diagnostic biomarker for KIRP.

Machine learning-based endoplasmic reticulum-related diagnostic biomarker and immune microenvironment landscape for osteoarthritis

BACKGROUND

Osteoarthritis (OA) is the most common degenerative joint disease worldwide. Further improving the current limited understanding of osteoarthritis has positive clinical value.

METHODS

OA samples were collected from GEO database and endoplasmic reticulum related genes (ERRGs) were identified. The WGCNA network was further built to identify the crucial gene module. Based on the expression profiles of characteristic ERRGs, LASSO algorithm was used to select key factors according to the minimum λ value. Random forest (RF) algorithm was used to calculate the importance of ERRGs. Subsequently, overlapping genes based on LASSO and RF algorithms were identified as ERRGs-related diagnostic biomarkers. In addition, OA specimens were also collected and performed qRT-PCR quantitative analysis of selected ERRGs.

RESULTS

We identified four ERRGs associated with OA risk assessment through machine learning methods, and verified the abnormal expressions of these screened markers in OA patients through in vitro experiments. The influence of selected markers on OA immune infiltration was also evaluated.

CONCLUSIONS

Our results provide new evidence for the role of ER stress in the OA progression, as well as new markers and potential intervention targets for OA.

Plasma MERTK is a promising biomarker for the diagnosis and prognosis of HBV-related acute-on-chronic liver failure

BACKGROUND

Hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) has a high short-term mortality. This study aimed to determine the diagnostic and prognostic role of MER tyrosine kinase (MERTK) in HBV-ACLF patients.

METHODS

Transcriptomics analysis evaluated MERTK expression and function during disease progression. The diagnostic and prognostic significance of MERTK for HBV-ACLF patients were verified by ELISA, the area under the receiver operating characteristic curve (AUROC) analysis, and immunohistochemistry (IHC) of liver tissues.

RESULTS

MERTK mRNA was highly expressed in the HBV-ACLF compared to the liver cirrhosis (LC), chronic hepatitis B (CHB) and normal controls (NC) groups. Elevated MERTK mRNA predicted poor prognosis for HBV-ACLF at 28/90 days (AUROCs=0.814/0.731). Functional analysis showed MERTK was significantly associated with TLR and inflammatory signaling, and several key biological processes. External validation with 285 plasma subjects confirmed the high diagnostic accuracy of plasma MERTK for HBV-ACLF (AUROC=0.859) and potential prognostic value for 28/90-day mortality rates (AUROC=0.673 and 0.644, respectively). Risk stratification analysis indicated higher mortality risk for patients with plasma MERTK level above the cut-off value. Moreover, IHC staining showed increasing MERTK expression from NC, CHB and LC to HBV-ACLF patients.

CONCLUSIONS

MERTK shows promise as a candidate biomarker for early diagnosis and prognosis of HBV-ACLF.

Soluble Urokinase Plasminogen Activator Receptor (SuPAR) Analysis for Diagnosis of Periprosthetic Joint Infection

Soluble urokinase plasminogen activator receptors (suPARs) are a biomarker for inflammatory diseases. This study aims to investigate its diagnostic properties regarding periprosthetic joint infections (PJI). This retrospective cohort study included adult patients who underwent joint puncture for suspected PJI. The presence of PJI was determined according to the criteria of the European Bone and Joint Infection Society (EBJIS). Laboratory study analyses included the determination of white blood cells (WBC) in whole blood, C-reactive protein (CRP) in blood plasma, and suPAR in both blood plasma and synovial fluid. Appropriate diagnostic cut-off values were identified utilizing Youden's J, and their diagnostic performance was determined by calculating the positive (PPV) and negative predictive value (NPV) for each marker. Sixty-seven cases were included in the final analysis. Forty-three samples (64%) were identified as periprosthetic joint infection (PJI) and twenty-four specimen (36%) were PJI negative cases. The PPV and NPV were 0.80 and 0.70 for synovial suPAR, 0.86 and 0.55 for CRP, 0.84 and 0.31 for WBC and 1.00 and 0.31 for plasma suPAR. Synovial suPAR showed a solid diagnostic performance in this study and has the potential to be an alternative or complementary biomarker for PJI. Further investigations in larger patient collectives are indicated.

Machine learning-based B cell-related diagnostic biomarker signature and molecular subtypes characteristic of ulcerative colitis

As an inflammatory bowel disease, ulcerative colitis (UC) does not respond well to current treatments. It is of positive clinical significance to further study the pathogenesis of UC and find new therapeutic targets. B lymphocytes play an important role in the pathogenesis of UC. The effect of anti-CD20 therapy on UC also provides new evidence for the involvement of B cells in UC process additionally, suggesting the important role and potential therapeutic value of B cells in UC. In this study, we screened the most critical immune cell-related gene modules associated with UC and found that activated B cells were closely related to the gene modules. Subsequently, key activated B cell-associated gene (BRG) signatures were obtained based on WGCNA and differential expression analysis, and three overlapping BRG-associated genes were obtained by RF and LASSO algorithms as BRG-related diagnostic biomarkers for UC. Nomogram model was further performed to evaluate the diagnostic ability of BRG-related diagnostic biomarkers, subsequently followed by UC molecular subsets identification and immunoinfiltration analysis. We also further verified the expressions of the three screened BRGs in vitro by using an LPS-induced NCM460 cell line model. Our results provide new evidence and potential intervention targets for the role of B cells in UC from a new perspective.

Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation

BACKGROUND

The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways.

METHODS

We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein-protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF.

RESULTS

We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF.

CONCLUSIONS

We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.

The Gut Microbiome and Acute Leukemia: Implications for Early Diagnostic and New Therapies

Acute leukemia (AL), one of the hematological malignancies, shows high heterogeneity. Tremendous progresses are achieved in treating AL with novel targeted drugs and allogeneic hematopoietic stem cell transplantation, there are numerous issues including pathogenesis, early diagnosis, and therapeutic efficacy of AL to be solved. In recent years, an increasing number of studies regarding microbiome have shed more lights on the role of gut microbiota in promoting AL progression. Mechanisms related to the role of gut microbiota in enhancing AL genesis are summarized in the present work, especially on critical pathways like leaky gut, bacterial dysbiosis, microorganism-related molecular patterns, and bacterial metabolites, resulting in AL development. Additionally, the potential of gut microbiota as the biomarker for early AL diagnosis is discussed. It also outlooks therapies targeting gut microbiota for preventing AL development.

Identifying Minimal Hepatic Encephalopathy: A New Perspective from Magnetic Resonance Imaging

Type C hepatic encephalopathy (HE) is a condition characterized by brain dysfunction caused by liver insufficiency and/or portal-systemic blood shunting, which manifests as a broad spectrum of neurological or psychiatric abnormalities, ranging from minimal HE (MHE), detectable only by neuropsychological or neurophysiological assessment, to coma. Though MHE is the subclinical phase of HE, it is highly prevalent in cirrhotic patients and strongly associated with poor quality of life, high risk of overt HE, and mortality. It is, therefore, critical to identify MHE at the earliest and timely intervene, thereby minimizing the subsequent complications and costs. However, proper and sensitive diagnosis of MHE is hampered by its unnoticeable symptoms and the absence of standard diagnostic criteria. A variety of neuropsychological or neurophysiological tests have been performed to diagnose MHE. However, these tests are nonspecific and susceptible to multiple factors (eg, aging, education), thereby limiting their application in clinical practice. Thus, developing an objective, effective, and noninvasive method is imperative to help detect MHE. Magnetic resonance imaging (MRI), a noninvasive technique which can produce many objective biomarkers by different imaging sequences (eg, Magnetic resonance spectroscopy, DWI, rs-MRI, and arterial spin labeling), has recently shown the ability to screen MHE from NHE (non-HE) patients accurately. As advanced MRI techniques continue to emerge, more minor changes in the brain could be captured, providing new means for early diagnosis and quantitative assessment of MHE. In addition, the advancement of artificial intelligence in medical imaging also presents the potential to mine more effective diagnostic biomarkers and further improves the predictive efficiency of MHE. Taken together, advanced MRI techniques may provide a new perspective for us to identify MHE in the future. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Urine metabolomics phenotyping and urinary biomarker exploratory in mild cognitive impairment and Alzheimer's disease

Introduction

Alzheimer's disease is a prevalent disease with a heavy global burden and is suggested to be a metabolic disease in the brain in recent years. The metabolome is considered to be the most promising phenotype which reflects changes in genetic, transcript, and protein profiles as well as environmental effects. Aiming to obtain a comprehensive understanding and convenient diagnosis of MCI and AD from another perspective, researchers are working on AD metabolomics. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.

Methods

We first enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples and conducted an LC-MS/MS analysis. In parallel, clinical data were collected and clinical examinations were performed. After statistical and bioinformatics analyzes, significant risk factors and differential urinary metabolites were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.

Results

Fifty-seven AD patients, 43 MCI patients and 62 CN subjects were enrolled. A total of 2,140 metabolites were identified among which 125 significantly differed between the AD and CN groups, including 46 upregulated ones and 79 downregulated ones. In parallel, there were 93 significant differential metabolites between the MCI and CN groups, including 23 upregulated ones and 70 downregulated ones. AD diagnostic panel (30 metabolites+ age + APOE) achieved an AUC of 0.9575 in the test set while MCI diagnostic panel (45 metabolites+ age + APOE) achieved an AUC of 0.7333 in the test set. Atropine, S-Methyl-L-cysteine-S-oxide, D-Mannose 6-phosphate (M6P), Spiculisporic Acid, N-Acetyl-L-methionine, 13,14-dihydro-15-keto-tetranor Prostaglandin D2, Pyridoxal 5'-Phosphate (PLP) and 17(S)-HpDHA were considered valuable for both AD and MCI diagnosis and defined as hub metabolites. Besides, diagnostic metabolites were weakly correlated with cognitive functions.

Discussion

In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN. Atropine, M6P and PLP were evidence-based hub metabolites in AD.

The Gut Microbiome and Autoimmune Hepatitis: Implications for Early Diagnostic Biomarkers and Novel Therapies

Autoimmune hepatitis (AIH) is a serious chronic liver disease that may last for decades and eventually develop into cirrhosis and liver failure. In recent years, people have paid more attention to the microbiome-gut-liver axis, which provides guidance for all to explore the role of microbiome in the occurrence and development of liver diseases. In this review, the possible mechanism of intestinal microbes promoting the occurrence of AIH, mainly expounding the key ways such as bacterial ecological imbalance, intestinal leakage, and molecular simulation between microbes and autoantigens is summarized. In addition, this paper also discusses that intestinal microbiome has great potential as a biomarker for early diagnosis of AIH, and intestinal microbiome is also a candidate target for prevention and treatment of AIH. Finally, the study summarizes and prospects the targeted therapy of intestinal microorganisms to prevent the occurrence and development of AIH.

Thyroid hormones as biomarkers of lung cancer: a retrospective study

BACKGROUND

Thyroid hormones are key regulators of several physiological processes, including differentiation, embryonic development, proliferation, and metabolism. Several prospective studies have shown a relationship between hyperthyroidism and cancer incidence; however, since the association between thyroid hormone levels and lung cancer remains controversial, this study aimed to determine the correlation between the same.

METHODS

We retrospectively analyzed 289 patients, who were diagnosed with lung cancer at the Huzhou Central Hospital between January 2016 and January 2021, and 238 healthy subjects. The baseline clinical data of two groups were collected. The concentrations of thyroid hormones, tumor CEA, CYF, SCC, and NSE in both the lung cancer patient and healthy volunteer groups were analyzed. Student's t-test or Mann-Whitney test was used to compare continuous variables. A chi-square test was adopted to estimate the relationship between serum thyroid hormones level and clinical characteristics of lung cancer cases. ROC curve analyses were used to determine the characteristics of thyroid hormones for recognizing lung cancer.

RESULTS

The results showed that serum thyroid stimulating hormone (TSH), total thyroxine, total triiodothyronine, and free triiodothyronine (FT3) levels were significantly decreased, while free thyroxine (FT4) levels were increased in patients with lung cancer. In addition, FT3 was identified as a potential diagnostic biomarker of stage I-IV lung cancer with the area under the curve values of 0.807. What's more, FT3 and FT4 were used in combination with CEA and were identified as potential diagnostic biomarkers of stage 0 lung cancer (Tis) with the area under the curve values of 0.774.

CONCLUSIONS

Our study highlights the possibility of using thyroid hormones as innovative diagnostic markers for lung cancer.

Quantitative electroencephalography as a potential biomarker in migraine

OBJECTIVE

The aim of this study was to investigate the utility of quantitative electroencephalography (QEEG) as a diagnostic tool for migraine and as an indicator of treatment response by comparing QEEG characteristics between migraine patients and controls, and monitoring changes in these characteristics alongside clinical symptoms in response to treatment BACKGROUND: We hypothesized that patients with migraine exhibit distinctive characteristics in QEEG measurements, which could be used as potential diagnostic biomarkers and as a tool for monitoring treatment response.

METHODS

A total of 720 patients were included in the study, comprising 619 patients with migraine and 101 subjects as a control group. QEEG measurements were analyzed for absolute power across specific frequency bands: delta wave (0.5-4 Hz), theta wave (4-8 Hz), alpha wave (8-12 Hz), beta wave (12-25 Hz), and high beta wave (25-30 Hz). The absolute power was normalized against a normative dataset from NeuroGuide, with electrodes being highlighted for significance if they exceeded 1.96. Clinical symptoms were also monitored for correlation with QEEG changes.

RESULTS

Our analysis showed that patients with migraine exhibited significantly higher absolute power across all frequencies, most markedly within the high beta frequency range. When considering electrodes with z-scores exceeding the threshold of 1.96 in the high beta range, a significant association with migraine diagnosis was observed (per 1 electrode increase, OR 1.06; 95% CI 1.01-1.11; p = .012). Moreover, pre- and posttreatment changes in QEEG measurements corresponded with changes in clinical symptoms.

CONCLUSION

Patients with migraine have distinctive QEEG measurements, particularly regarding absolute power and the number of electrodes that surpassed the z-score threshold in high beta wave activity. These findings suggest the potential of QEEG as a diagnostic biomarker and as a tool for monitoring treatment response in migraine patients, warranting further large-scale studies for confirmation and expansion.

Bacterial extracellular vesicles: an emerging avenue to tackle diseases

A growing body of research, especially in recent years, has shown that bacterial extracellular vesicles (bEVs) are one of the key underlying mechanisms behind the pathogenesis of various diseases like pulmonary fibrosis, sepsis, systemic bone loss, and Alzheimer's disease. Given these new insights, bEVs are proposed as an emerging vehicle that can be used as a diagnostic tool or to tackle diseases when used as a therapeutic target. To further boost the understanding of bEVs in health and disease we thoroughly discuss the contribution of bEVs in disease pathogenesis and the underlying mechanisms. In addition, we speculate on their potential as novel diagnostic biomarkers and how bEV-related mechanisms can be exploited as therapeutic targets.

The significance of long non-coding RNAs in the pathogenesis, diagnosis and treatment of inflammatory bowel disease

Inflammatory bowel diseases (IBD) are a group of chronic relapsing gastrointestinal inflammatory diseases with significant global incidence. Although the pathomechanism of IBD has been extensively investigated, several aspects of its pathogenesis remain unclear. Long non-coding RNAs (lncRNAs) are transcripts with more than 200 nucleotides in length that have potential protein-coding functions. LncRNAs play important roles in biological processes such as epigenetic modification, transcriptional regulation and post-transcriptional regulation. In this review, we summarize recent advances in research on IBD-related lncRNAs from the perspective of the overall intestinal microenvironment, as well as their potential roles as immune regulators, diagnostic biomarkers and therapeutic targets or agents for IBD.

Exosomal Long Non-Coding Ribonucleic Acid Ribonuclease Component of Mitochondrial Ribonucleic Acid Processing Endoribonuclease Is Defined as a Potential Non-Invasive Diagnostic Biomarker for Bladder Cancer and Facilitates Tumorigenesis via the miR-206/G6PD Axis

Bladder cancer (BLCA) is one of the cancers that is highly sensitive to specific non-invasive tumor biomarkers that facilitate early diagnosis. Exosome-derived long non-coding RNAs (lncRNAs) hold promise as diagnostic biomarkers for BLCA. In this study, we employed RNA-sequencing to compare the expression patterns of lncRNAs in urine exosomes from three BLCA patients and three healthy individuals. RMRP displayed the most significant differential expression. Elevated RMRP expression levels were observed in urinary and plasma exosomes from BLCA patients compared with those from healthy individuals. RMRP exhibited significant associations with certain BLCA patient clinicopathological features, including tumor stage, poor prognosis, and tumor grade. Combined diagnosis using RMRP in urine and plasma exosomes demonstrated a superior diagnostic performance with receiver operating characteristic curve analysis. RMRP was found to be related to BLCA tumor progression and the cell migration and invasion processes via the miR-206/G6PD axis both in vitro and in vivo. Mechanistically, RMRP serves as an miR-206 sponge, as suggested by dual-luciferase reporter assays and RNA immunoprecipitation. Our study suggests that the combined diagnosis of RMRP in urinary and plasma exosomes can serve as an excellent non-invasive diagnostic biomarker for BLCA patients. Additionally, targeting the RMRP/miR-206/G6PD axis holds promise as a therapeutic strategy for BLCA.

Serum sphingolipids aid in diagnosing adult HIV-negative patients with pulmonary cryptococcosis: a clinical cohort study

Background

Pulmonary cryptococcosis (PC) contributes to the ongoing global disease burden in human immunodeficiency virus (HIV)-negative populations. Since some PC patients are misdiagnosed under existing diagnostic guidelines, new diagnostic markers are needed to improve diagnostic accuracy and therapeutic efficacy and reduce disease risk.

Methods

Our previously established sphingolipidomic approach was employed to explore the use of serum sphingolipids (SPLs) in diagnosing HIV-negative patients with PC. A clinical cohort of PC, pulmonary aspergillosis (PA), and tuberculosis (TB) patients and healthy controls was assessed to identify SPL biomarkers.

Results

A total of 47 PC, 27 PA, and 18 TB patients and 40 controls were enrolled. PC and TB patients had similar clinical features, laboratory test results and radiological features, excluding plural effusion. The serum ceramide [Cer (d18:1/18:0)] level showed a significant increase in PC patients compared to controls and PA and TB patients (P<0.05). Cer (d18:1/18:0) was identified as a specific diagnostic biomarker for PC. The optimal cut-off value of greater than 18.00 nM showed a diagnostic sensitivity of 76.60% and a specificity of 95.00% and better distinguished PC patients from PA and TB patients. Furthermore, the serum Cer (d18:1/18:0) level gradually decreased after 3 and 6 months of treatment, suggesting the prediction potential for therapeutic efficacy of this biomarker. In addition, Cer (d18:1/18:0) analysis presented a higher sensitivity than the cryptococcal antigen (CrAg) assay.

Conclusions

This is the first study to report the use of the SPL Cer (d18:1/18:0) as a serum biomarker for diagnosing Cryptococcus spp. infection in HIV-negative patients.

Identification of Potential Genes and Critical Pathways in Postoperative Recurrence of Crohn's Disease by Machine Learning And WGCNA Network Analysis

Background

Crohn's disease (CD) is a chronic idiopathic inflammatory bowel disease affecting the entire gastrointestinal tract from the mouth to the anus. These patients often experience a period of symptomatic relapse and remission. A 20 - 30% symptomatic recurrence rate is reported in the first year after surgery, with a 10% increase each subsequent year. Thus, surgery is done only to relieve symptoms and not for the complete cure of the disease. The determinants and the genetic factors of this disease recurrence are also not well-defined. Therefore, enhanced diagnostic efficiency and prognostic outcome are critical for confronting CD recurrence.

Methods

We analysed ileal mucosa samples collected from neo-terminal ileum six months after surgery (M6=121 samples) from Crohn's disease dataset (GSE186582). The primary aim of this study is to identify the potential genes and critical pathways in post-operative recurrence of Crohn's disease. We combined the differential gene expression analysis with Recursive feature elimination (RFE), a machine learning approach to get five critical genes for the postoperative recurrence of Crohn's disease. The features (genes) selected by different methods were validated using five binary classifiers for recurrence and remission samples: Logistic Regression (LR), Decision tree classifier (DT), Support Vector Machine (SVM), Random Forest classifier (RF), and K-nearest neighbor (KNN) with 10-fold cross-validation. We also performed weighted gene co-expression network analysis (WGCNA) to select specific modules and feature genes associated with Crohn's disease postoperative recurrence, smoking, and biological sex. Combined with other biological interpretations, including Gene Ontology (GO) analysis, pathway enrichment, and protein-protein interaction (PPI) network analysis, our current study sheds light on the in-depth research of CD diagnosis and prognosis in postoperative recurrence.

Results

PLOD2, ZNF165, BOK, CX3CR1, and ARMCX4, are the important genes identified from the machine learning approach. These genes are reported to be involved in the viral protein interaction with cytokine and cytokine receptors, lysine degradation, and apoptosis. They are also linked with various cellular and molecular functions such as Peptidyl-lysine hydroxylation, Central nervous system maturation, G protein-coupled chemoattractant receptor activity, BCL-2 homology (BH) domain binding, Gliogenesis and negative regulation of mitochondrial depolarization. WGCNA identified a gene co-expression module that was primarily involved in mitochondrial translational elongation, mitochondrial translational termination, mitochondrial translation, mitochondrial respiratory chain complex, mRNA splicing via spliceosome pathways, etc.; Both the analysis result emphasizes that the mitochondrial depolarization pathway is linked with CD recurrence leading to oxidative stress in promoting inflammation in CD patients.

Conclusion

These key genes serve as the novel diagnostic biomarker for the postoperative recurrence of Crohn's disease. Thus, among other treatment options present until now, these biomarkers would provide success in both diagnosis and prognosis, aiming for a long-lasting remission to prevent further complications in CD.

Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis

IMPORTANCE

Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis.

Integrated bulk and scRNA sequence identified anoikis-related diagnostic biomarkers and potential association with immune infiltration in type A aortic dissection

Type-A aortic dissection (TAAD) is common life-threatening cardiovascular diseases with high-morbidity and mortality but the concrete etiology of disease remains unclear, which might disturb or delay the early diagnosis for TAAD. Anoikis is a special form of programmed cell-death (PCD) induced by detachment of anchorage-dependent cells from the extracellular matrix (ECM) or neighboring cells, and has been widely applied to identify anoikis-related biomarkers for the prediction and prognosis in oncological fields. However, the specific roles of anoikis-related genes (ARGs) in TAAD remain unclear. In this study, we first identified and validated eight diagnostic ARGs for TAAD based on multiple RNA-sequence datasets, including CHEK2, HIF1A, HK2, HMGA1, SERPINA1, PTPN1, SLC2A1 and VEGFA. The comprehensive functional annotation was evaluated by the integrated functional enrichments analysis. We identified the activation of inflammatory-related pathways, metabolic reprogramming and angiogenesis, and the inhibition of cardiovascular development pathways in TAAD. Immune cell infiltration (ICI) analysis further demonstrated that innate immune-cells were more dominant than adaptive immune-cells in TAAD tissues, especially in macrophages, monocytes, activated-DC, NKT cells and CD56+dim NK cells. The cellular landscape was further validated by single-cell RNA sequence technology with significant associations with anoikis in TAAD patients. Four vital ARGs (HIF1A, HMGA1, SERPINA1 and VEGFA) were ultimately identified along with the changes of differentiation trajectory, and major expressions were conformably concentrated on Macro1-3, Mono1-2 and Mono4 subtypes. These findings provide a promising diagnostic biomarker for the accurately diagnosing the disease and would be helpful to further explore the potential pathogenesis with anoikis process for TAAD.

Peripheral blood microR-146a and microR-29c expression in children with Mycoplasma pneumoniae pneumonia and its clinical value

BACKGROUND

We investigated changes in microR-29c and microR-146a expression in the serum of children with Mycoplasma pneumoniae pneumonia, analysed their relationship with inflammatory factors and disease severity, and evaluated their diagnostic significance.

METHODS

Fifty-six children with Mycoplasma pneumoniae pneumonia were enrolled as the Mycoplasma pneumoniae pneumonia group; 37 healthy children were enrolled as the control group. The microR-29c or microR-146a serum expression levels were determined using real-time quantitative reverse transcription polymerase chain reaction. Interleukin-17, tumour necrosis factor-alpha, and interleukin-1 beta levels were detected using enzyme-linked immunosorbent assay. The correlation between serum microR-29c or microR-146a expression and inflammatory factors was analysed using the Pearson's method. Receiver operating characteristic curves were used to evaluate the diagnostic value of serum microR-29c, microR-146a, and their combined detection in Mycoplasma pneumoniae pneumonia.

RESULTS

Compared with that in healthy children, the microR-29c and microR-146a serum levels were significantly downregulated in children with Mycoplasma pneumoniae pneumonia; the decrease was more obvious in children with severe cases than that in those with mild cases. In addition, microR-29c and microR-146a were negatively correlated with increased expression of interleukin-17, tumour necrosis factor-alpha, and interleukin-1 beta. Receiver operating characteristic curves showed that a combination of microR-29c and microR-146a was highly suitable for diagnosing Mycoplasma pneumoniae pneumonia.

CONCLUSION

Serum microR-29c and microR-146a were underexpressed in children with Mycoplasma pneumoniae pneumonia, and diagnostic accuracy was significantly improved with combined microR-29c and microR-146a detection. Therefore, both microR-29c and microR-146a levels can be used as biomarkers for the diagnosis of Mycoplasma pneumoniae pneumonia.

A Positive Feedback Loop of E2F4-Mediated Activation of MNX1 Regulates Tumour Progression in Colorectal Cancer

Purpose: Colorectal cancer (CRC) is the 3rd most prevalent malignant tumour globally. Although significant strides have been made in diagnosis and treatment, its prognosis at the moment remains unpromising. Therefore, there is an urgent and desperate need to identify novel biomarkers of CRC and evaluate its mechanism of tumourigenesis and development. Methods: JASPAR and RNAinter databases are used to analyze target genes associated with colorectal cancer. Western blotting, q-PCR and immunohistochemistry et, al. were used to detect the level of MNX1 in patients with colorectal cancer, and Chip-PCR was used to detect the targeted binding ability of E2F4 and MNX1. The cells and animal models overexpressed MNX1 and E2F4 were constructed by shRNA transfection. Results: Herein, MNX1 was highly expressed and linked to favourable overall survival curves in colorectal cancer. The functional assay revealed that MNX1 overexpression could promote proliferation, migration, and invasion of CRC cells. Based on the prediction of the JASPAR and RNAinter databases, the transcription factor, E2F4, was bound to the MNX1 promoter region. The Chromatin Immunoprecipitation (ChIP) assay verified the interactions between MNX1 and E2F4 in CRC. Additionally, we found that sh-E2F4 markedly downregulated the MNX1 levels and reduced CRC progression in vivo and in vitro, which reversed MNX1 overexpression. Conclusion: Therefore, our research discovered that E2F4-mediated abnormal MNX1 expression promotes CRC progression and could become a novel diagnostic or therapeutic target of CRC.

Identifying Aging-Related Biomarkers and Immune Infiltration Features in Diabetic Nephropathy Using Integrative Bioinformatics Approaches and Machine-Learning Strategies

BACKGROUND

Aging plays an essential role in the development of diabetic nephropathy (DN). This study aimed to identify and verify potential aging-related genes associated with DN using bioinformatics analysis.

METHODS

To begin with, we combined the datasets from GEO microarrays (GSE104954 and GSE30528) to find the genes that were differentially expressed (DEGs) across samples from DN and healthy patient populations. By overlapping DEGs, weighted co-expression network analysis (WGCNA), and 1357 aging-related genes (ARGs), differentially expressed ARGs (DEARGs) were discovered. We next performed functional analysis to determine DEARGs' possible roles. Moreover, protein-protein interactions were examined using STRING. The hub DEARGs were identified using the CytoHubba, MCODE, and LASSO algorithms. We next used two validation datasets and Receiver Operating Characteristic (ROC) curves to determine the diagnostic significance of the hub DEARGs. RT-qPCR, meanwhile, was used to confirm the hub DEARGs' expression levels in vitro. In addition, we investigated the relationships between immune cells and hub DEARGs. Next, Gene Set Enrichment Analysis (GSEA) was used to identify each biomarker's biological role. The hub DEARGs' subcellular location and cell subpopulations were both identified and predicted using the HPA and COMPARTMENTS databases, respectively. Finally, drug-protein interactions were predicted and validated using STITCH and AutoDock Vina.

RESULTS

A total of 57 DEARGs were identified, and functional analysis reveals that they play a major role in inflammatory processes and immunomodulation in DN. In particular, aging and the AGE-RAGE signaling pathway in diabetic complications are significantly enriched. Four hub DEARGs (CCR2, VCAM1, CSF1R, and ITGAM) were further screened using the interaction network, CytoHubba, MCODE, and LASSO algorithms. The results above were further supported by validation sets, ROC curves, and RT-qPCR. According to an evaluation of immune infiltration, DN had significantly more resting mast cells and delta gamma T cells but fewer regulatory T cells and active mast cells. Four DEARGs have statistical correlations with them as well. Further investigation revealed that four DEARGs were implicated in immune cell abnormalities and regulated a wide range of immunological and inflammatory responses. Furthermore, the drug-protein interactions included four possible therapeutic medicines that target four DEARGs, and molecular docking could make this association practical.

CONCLUSIONS

This study identified four DEARGs (CCR2, VCAM1, CSF1R, and ITGAM) associated with DN, which might play a key role in the development of DN and could be potential biomarkers in DN.

Circulating hsa_circ_0072309, acting via the miR-100/ACKR3 pathway, maybe a potential biomarker for the diagnosis, prognosis, and treatment of brain metastasis from non-small-cell lung cancer

BACKGROUND

One of the main causes of lung cancer-related death is brain metastasis (BM). Finding early indicators of BM derived from lung cancer is crucial. Therefore, this study was designed to determine if serum hsa_circ_0072309 may be employed as a potential biomarker for BM induced by non-small-cell lung cancer (NSCLC) and to understand its possible underlying mechanism.

METHODS

Primary lung cancer and healthy neighboring tissues were obtained from all patients, while BM tissues were taken from BM+ patients. Serum specimens were collected from all patients and healthy volunteers. Hsa_circ_001653, miR-100, and ACKR3 RNA expressions were analyzed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and atypical chemokine receptor 3 (ACKR3) protein expression by western blotting (WB), immunohistochemistry (IHC), and enzyme-linked immunosorbent assay (ELISA). In order to examine the effect of serum hsa_circ_0072309 and its relevant mechanism on BM development, an NSCLC-associated BM model in mice was established.

RESULTS

According to the results, miR-100 expression was down-regulated in primary lung cancer tissues compared to healthy lung tissues in all NSCLC patients, and circ_0072309 and ACKR3 expression were up-regulated. In BM tissues compared with primary lung tumors of BM+ patients, in serum samples from all patients compared to healthy volunteers, and in lung tumors of BM+ patients compared to those from BM- patients. Patients' serum exhibits the same level of hsa_circ_0072309/miR-100/ACKR3 expression as in BM samples. Advanced tumor-node-metastasis (TNM) stage, higher BM, shorter post-operative overall survival (OS), and progression-free survival (PFS) are all substantially associated with increased serum circ_0072309 levels in BM+ patients. In animal models, serum owning hsa_circ_0072309 from BM+ patients facilitates BM formation by regulating the miR-100/ACKR3 pathway.

CONCLUSIONS

The current preliminary research reveals serum hsa_circ_0072309 as a possible biomarker and target for early diagnosis, prognosis, and therapy of NSCLC-derived BM and suggests a substantial role for the hsa_circ_0072309/miR-100/ACKR3 axis in the formation of BM from NSCLC.

Phosphatase and Tensin Homolog (PTEN) Expression as a Surrogate Biomarker Correlated With the Depth of Invasion in Cutaneous Malignant Melanoma

Objective The aim of this study is to evaluate the expression of the phosphatase and tensin homolog (PTEN), which is a tumor suppressor gene that is implicated in the pathogenesis of cutaneous malignant melanoma, in normal skin and melanoma tissue samples. The study also aimed to correlate PTEN expression levels with various clinicopathological parameters of melanoma lesions, thus highlighting the utility of PTEN expression as a prognostic biomarker for melanoma. Study design Immunohistochemistry (IHC) staining was performed on tissue microarray samples representing normal skin and melanoma biopsies of different clinicopathological parameters. Tissue photomicrographs were evaluated with Aperio ImageScope, which has a positive-pixel-counting algorithm built in. Subsequently, a histochemical score (H-score) was derived from the percentage of positive cells (%-staining) and their staining intensity. The H-scores were averaged in groups of tissue samples representing the different melanomas' tumor (T), node (N), and distant metastasis (M), also known as TNM parameters, as set forth by the American Joint Committee on Cancer (AJCC) classification. The mean H-scores were statistically compared using a two-tailed unpaired t-test. Results The PTEN protein expression was measured by IHC and found to be correlated with tumor thickness (T), which is a reliable indicator for survival rates. Specifically, PTEN was significantly downregulated in tumors with a thickness over 2 mm (T3+T4) compared to tumors with a thickness at or below 2 mm (T1+T2). Conclusions The PTEN protein expression, as measured by immunohistochemistry, helped differentiate between tumors with a thickness over 2 mm and tumors with a thickness at or below 2 mm, suggesting PTEN as a potential surrogate marker for the melanoma's invasion depth along with possible prognostic implications. Longitudinal studies evaluating risk stratification based on the expression of PTEN are needed to establish the utility of this promising biomarker in the clinic as an adjunct for pathological examination.

Extracellular Vesicles-A Source of RNA Biomarkers for the Detection of Breast Cancer in Liquid Biopsies

Over the past decade, extracellular vesicles (EVs) have emerged as a promising source of cancer-derived RNAs for liquid biopsies. However, blood contains a pool of heterogeneous EVs released by a variety of cell types, making the identification of cancer RNA biomarkers challenging. Here, we performed deep sequencing of plasma EV RNA cargo in 32 patients with locally advanced breast cancer (BC) at diagnosis and 7 days after breast surgery and in 30 cancer-free healthy controls (HCs). To identify BC-derived RNA biomarkers, we searched for RNAs that had higher levels in BC EVs at the time of diagnosis compared with HCs and decreased after surgery. Data analysis showed that the fractions of miRNAs, snRNAs, snoRNAs, and tRFs were increased, but the fraction of lncRNAs was decreased in BC EVs as compared to HCs. BC-derived biomarker candidates were identified across various RNA biotypes. Considered individually, they had very high specificity but moderate sensitivity for the detection of BC, whereas a biomarker model composed of eight RNAs: SNORD3H, SNORD1C, SNORA74D, miR-224-5p, piR-32949, lnc-IFT-122-2, lnc-C9orf50-4, and lnc-FAM122C-3 was able to distinguish BC from HC EVs with an AUC of 0.902 (95% CI = 0.872-0.931, p = 3.4 × 10-9) in leave-one-out cross-validation. Furthermore, a number of RNA biomarkers were correlated with the ER and HER2 expression and additional biomarker models were created to predict hormone receptor and HER2 status. Overall, this study demonstrated that the RNA composition of plasma EVs is altered in BC patients and that they contain cancer-derived RNA biomarkers that can be used for BC detection and monitoring using liquid biopsies.

Thrombin Time is a Diagnostic Biomarker of Sudden Sensorineural Hearing Loss and Predicts the Prognosis

OBJECTIVES

The aim of this study is to determine whether thrombin time (TT) could be used as diagnostic biomarkers and predict the prognosis for sudden sensorineural hearing loss (SSNHL).

METHODS

Sixty-one patients diagnosed with SSNHL and 65 people who underwent physical examination were recruited. Data on the patient's background, clinical course, and laboratory findings were collected. SSNHL patients were divided into the effective and ineffective groups according to the hearing recovery from the treatment and were assessed by binary logistic regression. Receiver-operating characteristic (ROC) analysis was carried out for the best discriminating cutoff value of the biomarker with the corresponding sensitivity and specificity was calculated.

RESULTS

The SSNHL group exhibited prolonged TT (19.11 ± 1.12 seconds) compared to the control group (17.58 ± 2.18 seconds, P < .001). Binary logistic regression analysis found a significant positive association between TT and SSNHL and was observed with an odds ratio (OR) 1.769 [95% confidence interval (CI) 1.344-2.330, P < .001] in the unadjusted model. Even after adjustment using the variables included in the multivariate models, TT was significantly predictive of SSNHL. A TT cutoff value of 17.65 seconds provides optimal separation between patients with SSNHL and controls in the ROC analysis [Area Under the Curve (AUC) 0.773, 95% CI 0.689-0.856; sensitivity, 0.918; and specificity, 0.569]. TT in the effective group of SSNHL patients was shorter (18.76 ± 1.06 seconds) than that in the ineffective group (19.43 ± 1.09 seconds, P = .018). The cutoff value of TT as progress predictors was 19.85 seconds. The TT < 19.85 seconds showed an effective rate 59.09% (26/44) higher than 17.65% (3/17) of TT ≥ 19.85 seconds.

CONCLUSIONS

TT is a potential biomarker of SSNHL and is independently associated with the prognosis of patients with SSNHL.

Bioinformatics, RNA sequencing, and targeted bisulfite sequencing analyses identify the role of PROM2 as a diagnostic and prognostic biomarker

OBJECTIVES

Prominin 2 (PROM2) gene has been reported as a molecular biomarker of human cancers; however, its role is still controversial. This study was therefore arranged to seek the role of PROM2 in different cancers with Bioinformatics and in vitro analyses.

METHODS

A combination of bioinformatics and molecular experiments.

RESULTS

Through the utilization of Bioinformatics analysis, it was observed that in 19 out of the 24 human cancers studied, there was a significant increase in the expression of PROM2 compared to the respective control samples. Additionally, the overexpression of PROM2 was linked specifically to a decrease in overall survival (OS) among breast cancer (BRCA), lung adenocarcinoma (LUAD), and uterine corpus endometrial carcinoma (UCEC) patients. Furthermore, advanced molecular investigations were conducted, encompassing RNA sequencing (RNA-seq) as well as targeted bisulfite sequencing (bisulfite-seq) assessments of PROM2. These analyses were performed across an array of lung cancer cell lines (A549, ABC-1, EBC-1, and LK-2) and a normal control lung cell line (MRC-9). Results of these analysis revealed overexpression and reduced methylation of PROM2 within lung cancer cell lines, relative to the corresponding control cell line. This suggests that PROM2 assumes a substantial function in the advancement and course of BRCA, LUAD, and UCEC cancers. Subsequent pathway analysis revealed that genes enriched by PROM2 are actively engaged in four pivotal pathways. Additionally, intriguing associations were observed between PROM2 expression, tumor purity, infiltration of CD8+ T immune cells, and genetic modifications. Moreover, we also predicted a few MicroRNAs (miRNAs), transcription factors (TFs), and potential drugs that could help to understand and better manage these cancers via designing appropriate therapies targeting PROM2.

CONCLUSION

Via this study, we effectively revealed PROM2 overexpression as a potential diagnostic and prognostic biomarker of survival in BRCA, LUAD, and UCEC.

Increased let-7d-5p in non-alcoholic fatty liver promotes insulin resistance and is a potential blood biomarker for diagnosis

BACKGROUND AND AIMS

The molecular mechanisms driving non-alcoholic fatty liver disease (NAFLD) are poorly understood; however, microRNAs might play a key role in these processes. We hypothesize that let-7d-5p could contribute to the pathophysiology of NAFLD and serve as a potential diagnostic biomarker.

METHODS

We evaluated let-7d-5p levels and its targets in liver biopsies from a cross-sectional study including patients with NAFLD and healthy donors, and from a mouse model of NAFLD. Moreover, the induction of let-7d-5p expression by fatty acids was evaluated in vitro. Further, we overexpressed let-7d-5p in vitro to corroborate the results observed in vivo. Circulating let-7d-5p and its potential as a NAFLD biomarker was determined in isolated extracellular vesicles from human plasma by RT-qPCR.

RESULTS

Our results demonstrate that hepatic let-7d-5p was significantly up-regulated in patients with steatosis, and this increase correlated with obesity and a decreased expression of AKT serine/threonine kinase (AKT), insulin-like growth factor 1 (IGF1), IGF-I receptor (IGF1R) and insulin receptor (INSR). These alterations were corroborated in a NAFLD mouse model. In vitro, fatty acids increased let-7d-5p expression, and its overexpression decreased AKT, IGF-IR and IR protein expression. Furthermore, let-7d-5p hindered AKT phosphorylation in vitro after insulin stimulation. Finally, circulating let-7d-5p significantly decreased in steatosis patients and receiver operating characteristic (ROC) analyses confirmed its utility as a diagnostic biomarker.

CONCLUSIONS

Our results highlight the emerging role of let-7d-5p as a potential therapeutic target for NAFLD since its overexpression impairs hepatic insulin signalling, and also, as a novel non-invasive biomarker for NAFLD diagnosis.

Comparison of Extracellular Vesicle Isolation Methods for miRNA Sequencing

MicroRNAs (miRNAs) encapsulated in extracellular vesicles (EVs) are potential diagnostic and prognostic biomarkers. However, discrepancies in miRNA patterns and their validation are still frequent due to differences in sample origin, EV isolation, and miRNA sequencing methods. The aim of the present study is to find a reliable EV isolation method for miRNA sequencing, adequate for clinical application. To this aim, two comparative studies were performed in parallel with the same human plasma sample: (i) isolation and characterization of EVs obtained using three procedures: size exclusion chromatography (SEC), iodixanol gradient (GRAD), and its combination (SEC+GRAD) and (ii) evaluation of the yield of miRNA sequences obtained using NextSeq 500 (Illumina) and three miRNA library preparation protocols: NEBNext, NEXTFlex, and SMARTer smRNA-seq. The conclusion of comparison (i) is that recovery of the largest amount of EVs and reproducibility were attained with SEC, but GRAD and SEC+GRAD yielded purer EV preparations. The conclusion of (ii) is that the NEBNext library showed the highest reproducibility in the number of miRNAs recovered and the highest diversity of miRNAs. These results render the combination of GRAD EV isolation and NEBNext library preparation for miRNA retrieval as adequate for clinical applications using plasma samples.

The Potential of Bile Acids as Biomarkers for Metabolic Disorders

Bile acids (BAs) are well known to facilitate the absorption of dietary fat and fat-soluble molecules. These unique steroids also function by binding to the ubiquitous cell membranes and nuclear receptors. As chemical signals in gut-liver axis, the presence of metabolic disorders such as nonalcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), and even tumors have been reported to be closely related to abnormal levels of BAs in the blood and fecal metabolites of patients. Thus, the gut microbiota interacting with BAs and altering BA metabolism are critical in the pathogenesis of numerous chronic diseases. This review intends to summarize the mechanistic links between metabolic disorders and BAs in gut-liver axis, and such stage-specific BA perturbation patterns may provide clues for developing new auxiliary diagnostic means.

Promising Novel Biomarkers for Hepatocellular Carcinoma: Diagnostic and Prognostic Insights

The systemic therapy landscape for hepatocellular carcinoma is rapidly evolving, as the recent approvals of checkpoint inhibitor-based regimens such as atezolizumab-bevacizumab and durvalumab-tremelimumab in advanced disease have led to an expanding therapeutic armamentarium. The development of biomarkers, however, has not kept up with the approvals of new agents. Nevertheless, biomarker research for hepatocellular carcinoma has recently been growing at a rapid pace. The most active areas of research are biomarkers for early detection and screening, accurate prognostication, and detection of minimal residual disease following curative intent therapies, and, perhaps most importantly, predictive markers to guide selection and sequencing of the individual agents, including tyrosine kinase inhibitors and immunotherapy. In this review, we briefly summarize the recent developments in systemic therapeutics for hepatocellular carcinoma, introduce the key completed and ongoing prospective and retrospective studies evaluating diagnostic, prognostic, and predictive biomarkers with high clinical relevance, highlight several potentially important areas of future research, and share our insights for each biomarker.

Identification of S100A8 as a common diagnostic biomarkers and exploring potential pathogenesis for osteoarthritis and metabolic syndrome

Background

Osteoarthritis (OA) is the most frequent musculoskeletal disease and the major contributor to disability worldwide. Metabolic syndrome (MetS) has been recognized as being associated with the pathogenesis of osteoarthritis. However, the exact mechanisms and links between the two are not clear.

Methods

We downloaded clinical information data and gene expression profiles for OA and MetS from the database of Gene Expression Omnibus (GEO), and immune related gene (IRG) from the database of Immunology Database and Analysis Portal (IMMPORT). After screening OA-DEG and MetS-DEG, we identified the common immune hub gene by screening the overlapping genes between OA-DEG, MetS-DEG and IRG. Then we conducted single-gene analysis of S100A8, assessed the correlation of S100A8 with immune cell infiltration, and verified the diagnostic value of S100A8 in OA and MetS database respectively.

Results

323 OA-DEGs,101 MetS-DEGs and an immune-related hub gene, S100A8, were identified. In single gene analysis of S100A8 in OA samples, GSEA suggested that immune-related biological processes were more significantly enriched. The results of immune cell infiltration analysis showed that the enrichment fraction of M2 macrophages was significantly higher in the high S100A8-expressing group, and the level of S100A8 expression was positively correlated with M2 macrophage infiltration. The results of the dataset validation showed that S100A8 expression levels were significantly upregulated in the OA group and performed well in the diagnosis of OA. In single gene analysis of S100A8 in MetS samples, immune cell infiltration analysis showed that monocyte infiltration was higher in the S100A8 high expression samples and that there was a positive correlation between the two. Dataset validation showed that S100A8 is of high value for the diagnosis of MetS. In the validation of the dataset for the four metabolism-related diseases (obesity, diabetes, hypertension and hyperlipidaemia), S100A8 was expressed at higher levels in the disease group and also had a higher diagnostic value for the four metabolism-related diseases.

Conclusion

S100A8 is a common hub gene and diagnostic biomarker for OA and MetS, and the immune regulation involved in S100A8 may play a central role in the pathogenesis of OA and MetS.

Biomarkers of ocular allergy and dry eye disease

The most common disorders of the ocular surface are dry eye disease (DED) and ocular allergy (OA). These conditions are frequently coexisting with or without a clinical overlap and can cause a severe impact on the patient's quality of life. Therefore, it can sometimes be hard to distinguish between DED and OA because similar changes and manifestations may be present. Atopic patients can also develop DED, which can aggravate their manifestations. Moreover, patients with DED can develop ocular allergies, so these two pathological entities of the ocular surface can be considered as mutual conditions that share the same background. Nowadays, by using different techniques to collect tissue from ocular surfaces, the changes in molecular homeostasis can be detected and this can lead to a precise diagnosis. The article provides an up-to-date review of the various ocular surface biomarkers that have been identified in DED, OA, or both conditions. Abbreviations: DED = dry eye disease, OA = ocular allergy, SS = Sjogren syndrome, TBUT = tear break up time, TFO = tear film osmolarity, AKC = Atopic keratoconjunctivitis, ANXA1 = Annexin 1, ANXA11 = Annexin 11, CALT = Conjunctival associated lymphoid tissue, CCL2/MIP-1 = Chemokine (C-C motif) ligand2/Monocyte chemoattractant protein 1, CCL3/MIP-1α = Chemokine (C-C motif) ligand 3/Macrophage inflammatory protein 1 alpha, CCL4/MIP-1β = Chemokine (C-C motif) ligand 4/Macrophage inflammatory protein 1 beta, CCL5/RANTES = Chemokine (C-C motif) ligand 5 /Regulated on Activation, Normal T cell Expressed and Secreted, CCR2 = Chemokine (C-C motif) receptor 2, CCR5 = Chemokine (C-C motif) receptor 5, CD3+ = Cluster of differentiation 3 positive, CD4+ = Cluster of differentiation 4 positive, CD8+ = Cluster of differentiation 8 positive, CGRP = Calcitonin-gene-related peptide, CX3CL1 C-X3 = C motif -chemokine ligand 1 /Fractalkine, CXCL8 = Chemokine (C-X-C motif) ligand 8, CXCL9 = Chemokine (C-X-C motif) ligand 9, CXCL10 = Chemokine (C-X-C motif) ligand 10, CXCL11 = Chemokine (C-X-C motif) ligand 11, CXCL12 = Chemokine (C-X-C motif) ligand 12, CXCR4 = Chemokine (C-X-C motif) receptor 4, EGF = Epidermal growth factor, HLA-DR = Human leukocyte antigen-D-related, ICAM-1 = Intercellular adhesion molecule 1, IFN-γ = Interferon-gamma, IgG = Immunoglobulin G, IgE = Immunoglobulin E, IL-1 = Interleukin-1, IL-1α = Interleukin-1 alpha, IL-1β = Interleukin-1 beta, CGRP = Calcitonin-Gene-Related Peptide, IL-3 = Interleukin-3, IL-4 = Interleukin-4, IL-6 = Interleukin-6, IL-8 = Interleukin-8, IL-10 = Interleukin-10, IL-17 = Interleukin-17, IL-17A = Interleukin-17A, LPRR3 = Lacrimal proline-rich protein 3, LPRR4 = Lacrimal proline-rich protein 4, MUC5AC = Mucin 5 subtype AC, oligomeric mucus/gel-forming, MUC16 = Mucin 16, OCT = Optical coherence tomography, OGVHD = Ocular graft versus host disease, PAX6 = Paired-box protein 6, VKC = Vernal keratoconjunctivitis, TGF-β = Transforming growth factor β, S100 = proteins Calcium activated signaling proteins, Th1 = T helper 1 cell, Th17 = T helper 17 cell, MGD = Meibomian gland dysfunction, TFOS = Tear film and ocular surface society, SS-KCS = Keratoconjunctivitis Sicca, MMP-9 = Matrix metalloproteinase 9, MMP-1 = Matrix metalloproteinase 1, ZAG = Zinc alpha glycoprotein, CBA = Cytometric bead array, MALDI TOF-MS = matrix assisted laser desorption ionization-time of flight, SELDI TOF-MS = surface-enhanced laser desorption ionization-time of flight, IVCM = in vivo confocal microscopy, AS-OCT = anterior segment optical coherence tomography, iTRAQ = Isobaric tags for relative and absolute quantitation, LC-MS = Liquid chromatography-mass spectrometry, LCN-1 = lipocalin 1, PIP = prolactin induced protein, NGF = Nerve growth factor, PRR4 = proline rich protein 4, VIP = Vasoactive intestinal peptide, ELISA = enzyme linked immunoassay, TNF-α = tumor necrosis factor alpha, PAC = perennial allergic conjunctivitis, SAC = seasonal allergic conjunctivitis, IC = impression cytology, RT-PCR = reverse transcription polymerase chain reaction, PCR = polymerase chain reaction, APCs = antigen-presenting cells, NK cells = natural killer cells, HEL = hexanoyl-lysine, 4-HNE = 4-hydroxy-2-nonenal, MDA = malondialdehyde.

Recent advances in proteomic-based diagnostics of cystic fibrosis

INTRODUCTION

Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF.

AREAS COVERED

We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers.

EXPERT OPINION

Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.

Identifying immune cell infiltration and diagnostic biomarkers in heart failure and osteoarthritis by bioinformatics analysis

Heart failure (HF) and osteoarthritis (OA) are medical conditions that can significantly impact daily activities. Evidence has shown that HF and OA may share some pathogenic mechanisms. However, the underlying genomic mechanisms remain unclear. This study aimed to explore the underlying molecular mechanism and identify diagnostic biomarkers for HF and OA. With the cutoff criteria of fold change (FC) > 1.3 and P < .05, 920, 1500, 2195, and 2164 differentially expressed genes (DEGs) were identified in GSE57338, GSE116250, GSE114007, and GSE169077, respectively. After making the intersection of DEGs, we obtained 90 upregulated DEGs and 51 downregulated DEGs in HF datasets and 115 upregulated DEGs and 75 downregulated DEGs in OA datasets. Afterward, we conducted genome ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, protein-protein interaction (PPI) networks, and hub genes screening based on DEGs. Then, 4 common DEGs (fibroblast activation protein alpha [FAP], secreted frizzled-related protein 4 (SFRP4), Thy-1 cell surface antigen (THY1), matrix remodeling associated 5 [MXRA5]) between HF and OA were screened and validated in GSE5406 and GSE113825 datasets, based on which we established the support vector machine (SVM) models. The combined area under the receiver operating characteristic curve (AUC) of THY1, FAP, SFRP4, and MXRA5 in the HF training and test sets reached 0.949 and 0.928. While in the OA training set and test set, the combined AUC of THY1, FAP, SFRP4, and MXRA5 reached 1 and 1, respectively. The analysis of immune cells in HF revealed high levels of dendritic cell (DC), B cells, natural killer T cell (NKT), Type 1 regulatory T cell (Tr1), cytotoxic T cell (Tc), exhausted T cell (Tex), and mucosal-associated invariant T cell (MAIT), while displaying lower levels of monocytes, macrophages, NK, CD4 + T, gamma delta T (γδ T), T helper type 1 (Th1), T helper type 2 (Th2), and effector memory T cell (Tem). Moreover, the 4 common DEGs were positively correlated with DCs and B cells and negatively correlated with γδ T. In OA patients, the abundance of monocyte, macrophage, CD4 + naïve, and natural T regulatory cell (nTreg) was higher, while the infiltration of CD8 + T, γδ T, CD8 + naïve, and MAIT was lower. The expression of THY1 and FAP was significantly correlated with macrophage, CD8 + T, nTreg, and CD8 + naïve. SFRP4 was correlated with monocyte, CD8 + T, γδ T, CD4 + naïve, nTreg, CD8 + naïve and MAIT. MXRA5 was correlated with macrophage, CD8 + T, nTreg and CD8 + naïve. FAP, THY1, MXRA5, and SFRP4 may be diagnostic biomarkers for both HF and OA, and their correlation with immune cell infiltrations suggests shared immune pathogenesis.

Extremely rare chronic neutrophilic leukemia characterized by unrelieved abdominal distention and swollen painful limbs: new clinical insight

The pathogenesis of hematological tumors has not been fully elucidated. The academic community believes that genetic mutation abnormalities play a crucial role in the occurrence and development of hematological malignancies. Chronic neutrophilic leukemia (CNL) is a rare hematological tumor in the world. It is characterized by a Philadelphia chromosome BCR-ABL1-negative myeloproliferative tumor. It can be accompanied by mutations in various genes. Colony-stimulating factor 3 receptor (CSF3R) is a classic mutation in CNL and is included in the diagnostic criteria for CNL. This article described a 46-year-old male patient who came to the hospital with non-specific clinical manifestations such as unrelieved abdominal distension and edema of both lower extremities as the primary symptoms. The middle-aged male patient was provided with a peripheral a routine blood test. The biochemical tests revealed abnormalities. A bone marrow biopsy was performed to complete various tests such as bone marrow morphology, immunology, molecular biology, cytogenetics, and imaging. He was diagnosed with a rare chronic neutrophilic leukemia. After the diagnosis, the patient took ruxolitinib orally targeted therapy as prescribed by the doctor. Doctors regularly reviewed the peripheral blood examination and bone marrow status. The current condition is well controlled. CNL is extremely rare. The disease usually has non-specific clinical features and manifestations as the primary symptoms. These symptoms can easily be missed or lead to misdiagnosed ailments by clinicians. It is necessary to increase the awareness and vigilance of CNL.

Exploration into Plasma Hsa_circ_0052184 as a New Biomarker of Colorectal Cancer Prognosis

Background

Circular RNAs (circRNAs) are strong modulators of tumor pathology. Herein, our goal was to examine the plasma hsa_circ_0052184 content among colorectal cancer (CRC) patients, and assess its association with patient clinicopathological profile and diagnostic values.

Methods

Overall, we collected 228 presurgical CRC and 146 normal plasma samples from The First People's Hospital of Wenling. Circulating hsa_circ_0052184 levels were assessed via qRT-PCR, and the diagnostic prediction was conducted with the receiver operating characteristic (ROC) curve.

Results

Relative to healthy controls, CRC patients exhibited markedly enhanced circulating hsa_circ_0052184 levels, which were closely correlated with advanced stage of disease and worse outcome. Based on our uni- (UA) and multivariate assessments (MA), elevated hsa_circ_0052184 levels were a stand-alone predictor of poor prognosis. The ROC curve depicted an area under the curve (AUC) for CRC diagnosis to be 0.9072.

Conclusion

Circulating hsa_circ_0052184 is a potential bioindicator of CRC outcome.

Construction of a neural network diagnostic model for renal fibrosis and investigation of immune infiltration characteristics

Background

Recently, the incidence rate of renal fibrosis has been increasing worldwide, greatly increasing the burden on society. However, the diagnostic and therapeutic tools available for the disease are insufficient, necessitating the screening of potential biomarkers to predict renal fibrosis.

Methods

Using the Gene Expression Omnibus (GEO) database, we obtained two gene array datasets (GSE76882 and GSE22459) from patients with renal fibrosis and healthy individuals. We identified differentially expressed genes (DEGs) between renal fibrosis and normal tissues and analyzed possible diagnostic biomarkers using machine learning. The diagnostic effect of the candidate markers was evaluated using receiver operating characteristic (ROC) curves and verified their expression using Reverse transcription quantitative polymerase chain reaction (RT-qPCR). The CIBERSORT algorithm was used to determine the proportions of 22 types of immune cells in patients with renal fibrosis, and the correlation between biomarker expression and the proportion of immune cells was studied. Finally, we developed an artificial neural network model of renal fibrosis.

Results

Four candidate genes namely DOCK2, SLC1A3, SOX9 and TARP were identified as biomarkers of renal fibrosis, with the area under the ROC curve (AUC) values higher than 0.75. Next, we verified the expression of these genes by RT-qPCR. Subsequently, we revealed the potential disorder of immune cells in the renal fibrosis group through CIBERSORT analysis and found that immune cells were highly correlated with the expression of candidate markers.

Conclusion

DOCK2, SLC1A3, SOX9, and TARP were identified as potential diagnostic genes for renal fibrosis, and the most relevant immune cells were identified. Our findings provide potential biomarkers for the diagnosis of renal fibrosis.

The Versatility of Plectin in Cancer: A Pan-Cancer Analysis on Potential Diagnostic and Prognostic Impacts of Plectin Isoforms

Plectin, encoded by PLEC, is a cytoskeletal and scaffold protein with a number of unique isoforms that act on various cellular functions such as cell adhesion, signal transduction, cancer cell invasion, and migration. While plectin has been shown to display high expression and mislocalization in tumor cells, our knowledge of the biological significance of plectin and its isoforms in tumorigenesis remain limited. In this study, we first performed pathway enrichment analysis to identify cancer hallmark proteins associated with plectin. Then, a pan-cancer analysis was performed using RNA-seq data collected from the Cancer Genome Atlas (TCGA) to detect the mRNA expression levels of PLEC and its transcript isoforms, and the prognostic as well as diagnostic significance of the transcript isoforms was evaluated considering cancer stages. We show here that several tissue specific PLEC isoforms are dysregulated in different cancer types and stages but not the expression of PLEC. Among them, PLEC 1d and PLEC 1f are potential biomarker candidates and call for further translational and personalized medicine research. This study makes a contribution as a stride to unravel the molecular mechanisms underpinning plectin isoforms in cancer development and progression by revealing the potent plectin isoforms in different stages of cancer as potential early cancer detection biomarkers. Importantly, uncovering how plectin isoforms guide malignancy and particular cancer types by comprehensive functional studies might open new avenues toward novel cancer therapeutics.

Serum microRNA Levels as a Biomarker for Diagnosing Non-Alcoholic Fatty Liver Disease in Chinese Colorectal Polyp Patients

Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases and its prevalence is increasing worldwide. It is reported that NAFLD is associated with colorectal polyps. Since identifying NAFLD in its early stages could prevent possible disease progression to cirrhosis and decrease the risk of HCC by early intervention, patients with colorectal polyp may thus be considered a target group for screening NAFLD. This study aimed to investigate the potential of serum microRNAs (miRNAs) in identifying NAFLD for colorectal polyp patients. Serum samples were collected from 141 colorectal polyp patients, of which 38 had NAFLD. The serum level of eight miRNAs was determined by quantitative PCR and delta Ct values of different miRNA pairs which were compared between NAFLD and control groups. A miRNA panel was formulated from candidate miRNA pairs by multiple linear regression model and ROC analysis was performed to evaluate its diagnostic potential for NAFLD. Compared to the control group, the NAFLD group showed significantly lower delta Ct values of miR-18a/miR-16 (6.141 vs. 7.374, p = 0.009), miR-25-3p/miR-16 (2.311 vs. 2.978, p = 0.003), miR-18a/miR-21-5p (4.367 vs. 5.081, p = 0.021) and miR-18a/miR-92a-3p (8.807 vs. 9.582, p = 0.020). A serum miRNA panel composed of these four miRNA pairs significantly identified NAFLD in colorectal polyp patients with an AUC value of 0.6584 (p = 0.004). The performance of the miRNA panel was further improved to an AUC value of 0.8337 (p < 0.0001) when polyp patients with other concurrent metabolic disorders were removed from the analysis. The serum miRNA panel is a potential diagnostic biomarker for screening NAFLD in colorectal polyp patients. This serum miRNA test could be performed for colorectal polyp patients for early diagnosis and for prevention of the disease from progressing into more advanced stages.

Real-time quaking-induced conversion assay using a small-scale substrate production workflow for the diagnosis of Creutzfeldt-Jakob disease

The lack of a dedicated surveillance program for prion disease, particularly in low- and middle-income countries (LMICs), has hindered the global effort to address this public health threat. Although cerebrospinal fluid (CSF) Real-time quaking-induced conversion (RT-QuIC) is considered the most reliable test for sporadic Creutzfeldt-Jakob disease (sCJD), its availability in LMICs is limited due to its cost and technical difficulty in generating the recombinant prion protein substrate (recPrP). This study aimed to evaluate the performance of RT-QuIC with recPrP produced in-house through a small-scale method - i.e. the application of reusable pre-packed chromatography columns and subsequent dialysis. Here, CSF specimens from patients suspected of having prion disease were consecutively collected and stored between October 2015 and January 2023. Electronic medical record data were reviewed to clinically classified participants as probable sCJD or non-sCJD. CSF RT-QuIC was performed using in-house recPrP. Its specificity and sensitivity for diagnosing probable sCJD were reported, along with details of other clinical data and investigations. We found that among 39 eligible participants, with a median (interquartile range) age of 64 (56-70) years and 16 (41%) female, 13 had probable sCJD and the remaining 26 unequivocally suffered from non-prion disorders. Magnetic resonance imaging and electroencephalogram were suggestive of sCJD in 100% (13/13) and 46.2% (6/13) of sCJD participants, respectively. RT-QuIC was positive in 12/13 sCJD participants (sensitivity 0.92, 95% confidence interval (CI) 0.67-0.99) and negative in all non-sCJD participants (specificity 1.00, 95%CI 0.87-1.00). CSF tau/p-tau ratio showed sensitivity and specificity of 0.62-1.0 and 0.85-1.0, respectively. In summary, RT-QuIC using recPrP generated through a small-scale workflow demonstrated great performance in detecting sCJD. Given its performance results along with its low cost, this technique could feasibly be implemented in LMICs and potentially be the first step towards establishing local prion disease surveillance programs.

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Rheumatoid arthritis (RA) causes irreversible joint damage, but the pathogenesis is unknown. Therefore, it is crucial to identify diagnostic biomarkers of RA metabolism-related genes (MRGs). This study obtained transcriptome data from healthy individuals (HC) and RA patients from the GEO database. Weighted gene correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and random forest (RF) algorithms were adopted to identify the diagnostic feature biomarker for RA. In addition, biomarkers were verified by qRT-PCR and Western blot analysis. We established a mouse model of collagen-induced arthritis (CIA), which was confirmed by HE staining and bone structure micro-CT analysis, and then further verified the biomarkers by immunofluorescence. In vitro NMR analysis was used to analyze and identify possible metabolites. The correlation of diagnostic feature biomarkers and immune cells was performed using the Spearman-rank correlation algorithm. In this study, a total of 434 DE-MRGs were identified. GO and KEGG enrichment analysis indicated that the DE-MRGs were significantly enriched in small molecules, catabolic process, purine metabolism, carbon metabolism, and inositol phosphate metabolism. AKR1C3, MCEE, POLE4, and PFKM were identified through WGCNA, LASSO, and RF algorithms. The nomogram result should have a significant diagnostic capacity of four biomarkers in RA. Immune infiltration landscape analysis revealed a significant difference in immune cells between HC and RA groups. Our findings suggest that AKR1C3, MCEE, POLE4, and PFKM were identified as potential diagnostic feature biomarkers associated with RA's immune cell infiltrations, providing a new perspective for future research and clinical management of RA.

A comprehensive review of novel biomarkers in the diagnosis of intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is a disease specific to pregnancy, featuring maternal itching and elevated serum bile acid levels. It leads to a series of adverse pregnancy outcomes as well as increased fetal mortality. Routine biochemical markers fail to fulfill the tremendous clinical requirements, thereby novel effective biomarkers are urgently desired. In our review, the potential novel biomarkers for ICP diagnosis are classified into four categories and elaborated in detail. The concrete diagnostic performances (sensitivity, specificity and area under the curve) of these biomarkers are demonstrated in tables. Moreover, the relationships between some biomarkers and ICP pathogenesis are briefly expounded. Nevertheless, only a few novel biomarkers are ideal, and their clinical applicability requires more evidence from larger multicenter trials.