Potential Diagnostic Biomarkers Research Articles

Identification and Validation of Oxidative Stress-Related Biomarkers for Bronchopulmonary Dysplasia.

The objective of this study was to identify and characterize oxidative stress (OS)-related biomarkers in bronchopulmonary dysplasia (BPD) through a combination of bioinformatics analyses and wet experiments. The study utilized the Gene Expression Omnibus database to obtain the mRNA expression profile dataset GSE32472. Differential expression analysis and functional enrichment analysis were employed to investigate the role of OS-related genes in BPD. Gene Ontology Function Enrichment Analysis and Gene Set Enrichment Analysis were conducted to understand the mechanisms behind the signature. Protein-protein interaction analysis to identify hub genes in BPD, and predictions were made for microRNAs (miRNAs), transcription factors (TFs), and potential medications targeting these genes. CIBERSORT was utilized to investigate the correlation between hub genes and the infiltration of immune cells. Hub genes were ultimately determined and confirmed using expression analysis, correlation analysis, receiver operating characteristic (ROC) analysis, and quantitative real-time PCR (qRT-PCR). A novel OS-related gene signature (ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3) was constructed for the prediction of BPD. We identified 18 miRNAs, 14 TFs, and 30 potential medications targeting these genes. ROC analysis further validated that these genes could diagnose BPD with high specificity and sensitivity. The qRT-PCR revealed that IL1R1 and ARG1 were highly expressed in the lung tissue of the model group, while the expressions of RETN, SOCS3, IL1R2, and MMP9 were decreased. This study demonstrated that ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3 may serve as potential diagnostic biomarkers in BPD. Furthermore, a significant association between IL1R1 and the pathogenesis of BPD is observed.

The plasma miRNAome in ADNI: Signatures to aid the detection of at-risk individuals.

MicroRNAs are short non-coding RNAs that control proteostasis at the systems level and are emerging as potential prognostic and diagnostic biomarkers for Alzheimer's disease (AD). We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD. Our data demonstrate that plasma microRNA signatures can be used to not only diagnose MCI, but also, critically, predict the conversion from MCI to AD. Moreover, combined with neuropsychological testing, plasma microRNAome evaluation helps predict MCI to AD conversion. These findings are of considerable public interest because they provide a path toward reducing indiscriminate utilization of costly and invasive testing by defining the at-risk segment of the aging population. We provide the first analysis of the plasma microRNAome for the ADNI study. The levels of several microRNAs can be used as biomarkers for the prediction of conversion from MCI to AD. Adding the evaluation of plasma microRNA levels to neuropsychological testing in a clinical setting increases the accuracy of MCI to AD conversion prediction.

An abnormal metabolism-related gene, ALG3, is a potential diagnostic and prognostic biomarker for lung adenocarcinoma.

To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network. Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples. In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD. The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.

Somatic mutations in 3929 HPV positive cervical cells associated with infection outcome and HPV type

Invasive cervical cancers (ICC), caused by HPV infections, have a heterogeneous molecular landscape. We investigate the detection, timing, and HPV type specificity of somatic mutations in 3929 HPV-positive exfoliated cervical cell samples from individuals undergoing cervical screening in the U.S. using deep targeted sequencing in ICC cases, precancers, and HPV-positive controls. We discover a subset of hotspot mutations rare in controls (2.6%) but significantly more prevalent in precancers, particularly glandular precancer lesions (10.2%), and cancers (25.7%), supporting their involvement in ICC carcinogenesis. Hotspot mutations differ by HPV type, and HPV18/45-positive ICC are more likely to have multiple hotspot mutations compared to HPV16-positive ICC. The proportion of cells containing hotspot mutations is higher (i.e., higher variant allele fraction) in ICC and mutations are detectable up to 6 years prior to cancer diagnosis. Our findings demonstrate the feasibility of using exfoliated cervical cells for detection of somatic mutations as potential diagnostic biomarkers.

The Prominence of the Broad-Spectrum Protease inhibitor gene A2ML1 as a potential biomarker in cervical cancer diagnostics using Immunotherapeutic and Multi-Omics approaches

One of the venereal tumors that threaten human life is cervical cancer. A2ML1 is detected in advanced-stage cancer patients and is found to be strongly associated with cervical cancer. A2ML1 was shown to be substantially expressed in cervical cancer in this study, which used data from the TCGA database. Those with high A2ML1 expression had a lower chance of survival than patients with low A2ML1 expression. Both univariate and multivariate Cox regression analyses were utilized to investigate the relationship between clinical variables and overall survival rates. An investigation into the link between A2ML1 and immune infiltration was subsequently conducted. Utilizing the immune cell database, research was conducted to investigate the dispersion of 24 immune cells and their correlation to A2ML1 expression. In addition to this, the favorable correlation between immune cells and A2ML1 was validated using all three immune cell methodologies. The Genomics of Drug Sensitivity in Cancer database was used to confirm the idea that there is a link between A2ML1 expression and the efficacy of chemotherapy or immunotherapy. The findings demonstrated that A2ML1 is a potential biomarker for cervical cancer diagnostics. This biomarker may be used to chaperone immunotherapy, as well as to explain the elucidates of cervical cancer caused by the immunological microenvironment.

Mapping the intricacies of GLI1 in hedgehog signaling: A combined bioinformatics and clinical analysis in Head & Neck cancer in Western India

BackgroundActivation of various cancer stem cell pathways are thought to be responsible for treatment failure and loco-regional recurrence in Head and Neck cancer. Hedgehog signaling, a major cancer stem signaling pathway plays a major role in relapse of disease. GLI1, a transcription activator, plays an important role in canonical/non-canonical activation of Hedgehog signaling. MethodsData for H&N cancer patients were collected from The Cancer Genome Atlas- H&N Cancer (TCGA-HNSC). GLI1 co-expressed genes in TCGA-HNSC were then identified using cBioPortal and subjected to KEGG pathway analysis by DAVID tool. Network Analyzer and GeneMania plugins from CytoScape were used to identify hub genes and predict a probable pathway from the identified hub genes respectively. To confirm the hypothesis, real-time gene expression was carried out in 75 patients of head and neck cancer. ResultsSignificantly higher GLI1 expression was observed in tumor tissues of H&N cancer and it also showed worst overall survival. Using cBioPortal tool, 2345 genes were identified that were significantly co-expressed with GLI1. From which, 15 hub genes were identified through the Network Analyzer plugin in CytoScape. A probable pathway prediction based on hub genes showed the interconnected molecular mechanism and its role in non-canonical activation of Hedgehog pathway by altering the GLI1 activity. The expressions of SHH, GLI1 and AKT1 were significant with each other and were found to be significantly associated with Age, Lymph-Node status and Keratin. ConclusionThe study emphasizes the critical role of the Hh pathway's activation modes in H&N cancer, particularly highlighting the non-canonical activation through GLI1 and AKT1. The identification of SHH, GLI1 and AKT1 as potential diagnostic biomarkers and their association with clinic-pathological parameters underscores their relevance in prognostication and treatment planning. Hh pathway activation through GLI1 and its cross-talk with various pathways opens up the possibility of newer treatment strategies and developing a panel of therapeutic targets in H&N cancer patients.

Potential diagnostic and prognostic biomarkers of pediatric Burkitt lymphoma identified through miRNA expression profiling.

Pediatric Burkitt lymphoma (pBL) is the most common non-Hodgkin lymphoma in children. These patients require prompt diagnosis and initiation of therapy due to rapid tumor growth. The roles of tumor tissue and circulating microRNAs (miRNAs) in the diagnosis or prognostication have not been fully elucidated in pBLs. Differentially expressed (DE) miRNAs were identified with microRNA sequencing (miRNA-Seq) in tumor tissues and plasma of diagnostic pBLs. The diagnostic potential of total miRNA concentrations and overexpressed miRNAs were evaluated through receiver operating characteristic (ROC) analyses. Log-rank test was employed to evaluate survival differences associated with DE miRNAs. Selected miRNA expressions were cross-validated with quantitative reverse transcription PCR (qRT-PCR). Total circulating cell-free miRNAs were higher in pBL cases compared to controls. Cancer-associated pathways were enriched among miRNAs differentially expressed in pBL tumor tissues. Several upregulated miRNAs in pBL tumors demonstrated high diagnostic potential. Similarly, ROC analysis of overexpressed plasma miRNAs revealed circulating cell-free or exosomal miRNAs that can distinguish pBLs from control cases. Indeed, integrative analysis of overexpressed circulating exosomal miRNAs showed an enhanced diagnostic potential for certain triple combinations. Kaplan-Meier analyses of DE miRNAs in tumor tissues identified miRNAs predicting overall survival. Differentially expressed miRNAs in tumor tissue and plasma of pBL have the potential to improve diagnosis and prognosis. Differentially expressed miRNAs in treatment-naive pediatric Burkitt lymphoma cases have diagnostic or prognostic biomarker potential. This is the first study that applied miRNA-Seq on treatment-naive pediatric Burkitt lymphoma cases for identification of differentially expressed miRNAs both in tumor tissue and plasma samples with diagnostic potential. Through systematic analysis of differentially expressed miRNAs, tumor tissue miRNAs associated with the overall survival of pBLs have been discovered. The clinically significant, differentially expressed miRNAs identified in pediatric Burkitt lymphoma cases can potentially improve the current tissue-based or non-invasive clinical practice in terms of diagnosis or prognostication.

Proteomic profiling of cerebrospinal fluid reveals TKT as a potential biomarker for medulloblastoma

Cerebrospinal fluid (CSF) plays an important role in brain tumors, including medulloblastoma (MBL). Recent advancements in mass spectrometry systems and ‘Omics’ data analysis methods enable unbiased, high proteome depth research. We conducted proteomic profiling of the total CSF in MBL patients with the purpose of finding a potential diagnostic biomarker for MBL. We quantified 1112 proteins per CSF sample. Feature selection identified four elevated soluble proteins (SPTBN1, HSP90AA1, TKT, and NME1-NME2) in MBL CSF. Validation with ELISA confirmed that TKT was significantly elevated in MBL. Additionally, TKT-positive extracellular vesicles were significantly enriched in MBL CSF and correlated with the burden of leptomeningeal seeding. Our results provide insights into the proteomics data of the total CSF of MBL patients. Furthermore, we identified the significance of TKT within the total CSF and its presence within circulating EVs in the CSF. We suggest that TKT may serve as a biomarker for MBL.

Neurofilament light chain as a diagnostic and prognostic biomarker in Guillain-Barré syndrome.

Elevated neurofilament light chain (NfL) levels are associated with worse prognosis in Guillain-Barré syndrome (GBS). Our objectives were to determine the utility of serum NfL (sNfL), cerebrospinal fluid (CSF)/serum NfL ratio and NfL index as prognostic and diagnostic biomarkers for GBS. We measured NfL in serum and/or CSF obtained from 96 GBS patients between 1989 and 2014 in western Sweden. The sNfL Z-scores, NfL ratios and NfL indices were calculated. Outcome was determined with the GBS disability scale (GBSDS) at 3 and 12months. NfL parameters in GBS were compared with healthy controls (HC), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS). The sNfL Z-score was higher for GBSDS > 2 at 3months (median [IQR], 3.5ng/L [3.2-4.0], vs 2.6 [1.7-3.4], p = 0.008) and at 12months (3.6ng/L [3.5-3.8] vs 2.6 [1.8-3.5], p = 0.049). NfL ratio and index were not associated with outcome. The area under the curve (AUC) for sNfL Z-score was 0.76 (95% CI 0.58-0.93, p < 0.0001) for GBSDS > 2 at 3months. NfL ratio and index were lower in GBS than HC, MS, and ALS. The AUC for the NfL ratio was 0.66 (95% CI 0.55-0.78, p = 0.0018) and for the NfL index 0.86 (95% CI 0.78-0.93, p < 0.0001). Our results confirm sNfL as prognostic biomarker for GBS and the precision was improved using the age-adjusted sNfL Z score. NfL index and Qalb are potential diagnostic biomarkers for GBS.

Molecular biomarkers involved in the progression of gallbladder inflammatory lesions to invasive cancer: A proteomic approach.

The progression of gallbladder inflammatory lesions to invasive cancer remains poorly understood, necessitating research on biomarkers involved in this transition. This study aims to identify and validate proteins associated with this progression, offering insights into potential diagnostic biomarkers for gallbladder cancer (GBC). Label-free liquid chromatography assisted tandem mass spectrometry (LC-MS/MS) proteomics was performed on samples from 10 cases each of GBC and inflammatory lesions, with technical duplicates.Validation was conducted through the enzyme-linked immunosorbent assay (ELISA) using 80 samples (40 GBC and 40 inflammatory lesions). Bioinformatics tools analyzed protein-protein interaction (PPI) networks and pathways. Statistical correlations with clinicopathological variables were assessed. Prognostic evaluation utilized Kaplan-Meier survival analysis and Cox regression analyses. mRNA expressions were studied using real time-polymerase chain reaction (RT-PCR). Out of 5,714 proteins analyzed, 621 were differentially expressed. Three upregulated (the S100 calcium-binding protein P [S100P], polymeric immunoglobulin receptor [PIGR], and complement C1q-binding protein [C1QBP]) and two downregulated (transgelin [TAGLN] and calponin 1 [CNN1]) proteins showed significant expression. Pathway analysis implicated involvement of proteoglycans in cancer and glycosaminoglycan metabolism. Significant correlations were observed between protein concentrations and clinicopathological variables.Prognostic factors such as tumor size, lymph node metastasis, and preoperative bilirubin levels were associated with overall survival. Protein-based assays demonstrated higher resolution compared to mRNA analysis, suggesting their utility in GBC risk stratification. S100P, PIGR, C1QBP, TAGLN, and CNN1 emerge as potential protein-based biomarkers involved in the progression from gallbladder inflammatory lesions to invasive cancer. These findings hold promise for improved diagnostic and prognostic strategies in GBC management.

Sensitive phenotyping of serum extracellular vesicles on a SERS-microfluidic platform for early-stage clinical diagnosis of ovarian carcinoma

Ovarian carcinoma (OvCa) poses a severe threat to women's health due to its high mortality rate and lack of efficient early diagnosis approach. There is evidence to suggest that nanosized small extracellular vesicles (sEVs) which carrying cell-specific components from OvCa can serve as potential diagnostic biomarkers. Herein, we reported a Surface-enhanced Raman Scattering (SERS)-multichannel microchip for sEVs (S-MMEV) assay to investigate the phenotype changes of sEVs. The microchip composed of seven microchannels, which enabled the parallel detection of multiple biomarkers to improve the detection accuracy. Using SERS probes conjugated with antibodies recognizing different biomarkers including ubiquitous EV biomarkers (i.e., tetraspanins; CD9, CD81) and putative OvCa tumor biomarkers (i.e. EpCAM, CD24, CA125, EGFR), we successfully analyzed the phenotypic changes of sEVs and accurately differentiated OvCa patients from healthy controls, even at early stage (I-II), with high sensitivity, high specificity and an area under the curve value of 0.9467. Additionally, the proposed approach exhibited higher sensitivity than conventional methods, demonstrating the efficiency of precise detection from cell culture and clinical samples. Collectively, the developed EV phenotyping approach S-MMEV could serve as a potential tool to achieve the early clinical diagnosis of OvCa for further precise diagnosis and personal treatment monitoring.

The relationship between salivary cytokines and oral cancer and their diagnostic capability for oral cancer: a systematic review and network meta-analysis

BackgroundOral cancer (OC) is a common malignancy in clinical practice. Saliva testing is a convenient and noninvasive early diagnostic technique for OC. Several salivary cytokines have been identified as potential biomarkers for OC, including IL-8, IL-6, TNF-α, IL-1β, and IL-10. Nonetheless, the optimal cytokine for OC diagnosis remains inconclusive and highly contentious.MethodsPubMed, Embase, Web of Science, and Cochrane Library databases were comprehensively retrieved to collect all case–control studies on OC. A meta-analysis was performed to compare the levels of salivary IL-8, IL-6, IL-10, TNF-α, and IL-1β in OC patients and healthy controls. Network meta-analysis (NMA) was carried out to probe into the accuracy of these salivary cytokines in diagnosing OC.ResultsThis analysis included 40 studies, encompassing 1280 individuals with OC and 1254 healthy controls. Significantly higher levels of salivary IL-8, IL-6, TNF-α, IL-1β, and IL-10 were observed in patients with OC in comparison to healthy controls. The results of NMA showed that TNF-α had the highest diagnostic accuracy for OC, with a sensitivity of 79% and a specificity of 92%, followed by IL-6 (sensitivity: 75%, specificity: 86%) and IL-8 (sensitivity: 80%, specificity: 80%).ConclusionThis study suggests that IL-8, IL-6, IL-10, TNF-α, and IL-1β may be potential diagnostic biomarkers for OC. Among them, TNF-α, IL-6, and IL-8 are highly accurate in the diagnosis of OC. Nevertheless, further studies that eliminate other confounding factors are warranted, and more standardized procedures and large-scale studies are needed to support the clinical use of saliva testing.

Integrated transcriptomic analysis and machine learning for characterizing diagnostic biomarkers and immune cell infiltration in fetal growth restriction.

Fetal growth restriction (FGR) occurs in 10% of pregnancies worldwide. Placenta dysfunction, as one of the most common causes of FGR, is associated with various poor perinatal outcomes. The main objectives of this study were to screen potential diagnostic biomarkers for FGR and to evaluate the function of immune cell infiltration in the process of FGR. Firstly, differential expression genes (DEGs) were identified in two Gene Expression Omnibus (GEO) datasets, and gene set enrichment analysis was performed. Diagnosis-related key genes were identified by using three machine learning algorithms (least absolute shrinkage and selection operator, random forest, and support vector machine model), and the nomogram was then developed. The receiver operating characteristic curve, calibration curve, and decision curve analysis curve were used to verify the validity of the diagnostic model. Using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), the characteristics of immune cell infiltration in placental tissue of FGR were evaluated and the candidate key immune cells of FGR were screened. In addition, this study also validated the diagnostic efficacy of TREM1 in the real world and explored associations between TREM1 and various clinical features. By overlapping the genes selected by three machine learning algorithms, four key genes were identified from 290 DEGs, and the diagnostic model based on the key genes showed good predictive performance (AUC = 0.971). The analysis of immune cell infiltration indicated that a variety of immune cells may be involved in the development of FGR, and nine candidate key immune cells of FGR were screened. Results from real-world data further validated TREM1 as an effective diagnostic biomarker (AUC = 0.894) and TREM1 expression was associated with increased uterine artery PI (UtA-PI) (p-value = 0.029). Four candidate hub genes (SCD, SPINK1, TREM1, and HIST1H2BB) were identified, and the nomogram was constructed for FGR diagnosis. TREM1 was not only associated with a variety of key immune cells but also correlated with increased UtA-PI. The results of this study could provide some new clues for future research on the prediction and treatment of FGR.

Anti-sulfatide antibodies in neurological disorders: should we test?

Neurological autoimmune peripheral and central nervous system disorders can be associated with anti-sulfatide antibodies. These antibodies are considered potential diagnostic biomarkers, although their additional diagnostic value in neurological fields has been increasingly questioned. Given the little evidence of anti-sulfatide antibodies' frequency and diagnostic value in neurology, we aimed to fill this knowledge gap by investigating 10years of data. This retrospective study analyzed the results of the anti-ganglioside dot kits (GA Generic Assays GmbH) from 1318 serum samples and 462 cerebrospinal fluid (CSF) samples for the frequency, sensitivity, and specificity of anti-sulfatide antibodies in neurological disorders. Although anti-sulfatide antibodies are rarely present in neurological autoimmune disorders (serum IgM 2.5%, IgG 4.6%), they are also present in non-autoimmune diseases (serum IgM 1.2%, IgG 2.5%) and lack sensitivity and specificity towards being a diagnostic marker. Furthermore, anti-sulfatide antibodies are rarely found in CSF (e.g., no positive results for IgM), and including so-called borderline results ((+)) increases sensitivity and the false-positive rate in serum and CSF. While anti-sulfatide antibodies appear more frequently in neurological autoimmune diseases, they are rare overall and provide very limited diagnostic value in determining specific neurological diseases and-more importantly-if a neurological disease has a potential autoimmune etiology.

Identification of potential diagnostic biomarkers and therapeutic targets in patients with hypoxia pulmonary hypertension

BackgroundPulmonary hypertension is a serious disease. Emerging studies have shown that M2 macrophages play an essential role in pulmonary hypertension; however, their mechanism of action is uncertain. MethodsFour GEO datasets were downloaded. The differentially expressed genes (DEGs) were obtained using the limma package. Simultaneously, the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm and weighted gene co-expression network analysis (WGCNA) were used to get the information about M2 macrophage–related modules. Potential key genes were obtained by intersecting DEGs with M2 macrophage–related module genes (M2MRGs), and finally the area under the curve (AUC) was calculated. Rats were exposed to hypoxia condition (10 % O2) for 4 weeks to induce PH. Subsequently, potential key genes with AUC>0.7 were analyzed by quantitative real-time polymerase chain reaction and Western blot using normoxia and hypoxia rat lungs. We knocked down EPHA3 in Raw264.7 cells and detected the protein expression of M2 macrophage markers including arginase 1 (ARG1) and interleukin 10 (IL-10), phospho-protein kinase B (P-Akt), and protein kinase B (Akt) to explore the downstream pathways of EPHA3. ResultsSeven potential hub genes were detected by intersecting M2MRGs and DEGs. Six genes with AUC values above 0.7 were used for further exploration. The expression of EPHA3 mRNA and protein was significantly more upregulated in rats with hypoxia than in rats with normoxia. The expression levels of IL10, ARG1, and P-Akt/Akt decreased after knocking down EPHA3. ConclusionsThis study suggested that the activation of the P-Akt/Akt signaling pathway promoted by EPHA3 played an essential role in the progression of pulmonary hypertension.

Exploration of potential biomarkers for prurigo nodularis based on plasma-metabolome analysis.

Prurigo nodularis (PN) is a chronic and debilitating skin disease with severe itching that negatively impacts patients' quality of life and mental state. However, the treatment options for PN remain limited. Global metabolomics analysis can offer effective information on energy metabolism, pathogenesis and potential diagnostic biomarkers. No study on metabolomic analysis of PN has been reported. To further understand the mechanisms of PN and analyse the plasma metabolite profiles in patients with PN. Targeted-metabolome analysis of 306 metabolites in plasma from 18 patients with PN and 19 healthy controls was performed using Liquid Chromatography-tandem Mass Spectrometer analysis. We identified 31 differential metabolites. Most acylcarnitines, long-chain fatty acids, alpha-aminobutyric acid, hydroxybutyric acid and lactic acid among these metabolites were up-regulated in patients with PN; in contrast, glucaric acid, suberic acid, bile acid derivatives and most amino acids were down-regulated. Positive correlations exist between glucaric acid and itching severity and acylcarnitines and insomnia. Suberic acid and the Investigator's Global Assessment (IGA) scores correlate negatively. Metabolite variation reflects the dysregulation of energy metabolism and chronic systematic inflammation in PN. Several metabolites, such as glucaric acid, suberic acid and acylcarnitines, merit further study as potential biomarkers of disease severity in PN.

CircZMYM2 plays a pivotal role in osteosarcoma by regulating the translation of NACA and ARPC1B

Osteosarcoma (OS) is a primary malignant bone tumor in children and young adults because of its intertumoral heterogeneity and absence of molecular targets. This study aimed to elucidate the role of circular RNA in the pathogenesis of OS. Using bioinformatics analysis and OS clinical samples, we found that hsa_circ_0029634 formed during the splicing process of Zinc finger MYM-type containing 2 (circZMYM2) was highly expressed in OS tissues. Nuclear cap-binding protein subunit 2 regulated circZMYM2 bio-generation by binding to flanking sequences of ZMYM2 transcripts. In addition, knockdown circZMYM2 inhibited cell growth and metastasis in OS cell lines in vitro and inhibited tumor growth in vivo. Mechanistically, circZMYM2 competitively bound to FXR1 to regulate the translation of NACA and ARPC1B. CircZMYM2 may be a crucial regulator of OS tumorigenesis and a potential diagnostic and therapeutic biomarker for OS patients.

Construction of Prognostic ceRNA Network Landscape in Brea st Cancer to Explore Impacting Genes on Drug Response by Integrati ve Bioinformatics Analysis

Background: Breast cancer accounts for 30% of all new female cancers yearly. Bioinformatics serves us to find new biomarkers and facilitate future experimental research. Exploring a distinct network of competing endogenous RNA (ceRNA) that includes potential prognostic, diagnostic, and therapeutic biomarkers is captivating. Methods: Differentially expressed lncRNAs, mRNAs, and miRNAs were collected using Gene Expression Omnibus datasets. DEGs were validated based on TCGA. Functional analysis and pathway activity were also done. Drug sensitivity analyses were done, and IC50 vs. gene expression plots were depicted. Results: A total of 696 mRNAs, 48 lncRNAs, and, 43 miRNAs were identified to have significant differential expression in cancerous breast tissue than normal breast tissue samples. Functional analysis showed significant pathway enrichments in cancer. We found that 13 individual genes, lncRNAs, and miRNAs, CDC6, ERBB2, EZR, HELLS, MAPK13, MCM2, MMP1, SLC7A5, TINCR, TRIP13, hsa-miR-376a, hsa-miR-21, hsa-miR-454 were significantly predictive of poor overall survival and AKAP12, CXCL12, FGF2, IRS2, LINC00342, LINC01140, MEG3, MIR250HG, NAV3, NDRG2, NEAT1, TGFBR3 and, hsa-miR-29c were associated with favorable overall survival. We reached a set of five genes (EGR1, NFIB, TGFBR3, SMARCA4, and MCM2) that exhibit altered expression patterns in breast cancer, resulting in increased susceptibility of cancer cells to certain drug treatments. Conclusion: We successfully made a unique ce-network, providing new clues to understand the regulatory functions of non-coding RNAs (miRNAs and lncRNAs) in the pathogenesis and prognosis of breast cancer and will facilitate further experimental studies to develop new biomarkers in the diagnosis, prognosis and, therapy of breast cancer.

Inter-organ cross-talk in human cancer cachexia revealed by spatial metabolomics

BackgroundCancer cachexia (CCx) presents a multifaceted challenge characterized by negative protein and energy balance and systemic inflammatory response activation. While previous CCx studies predominantly focused on mouse models or human body fluids, there's an unmet need to elucidate the molecular inter-organ cross-talk underlying the pathophysiology of human CCx. MethodsSpatial metabolomics were conducted on liver, skeletal muscle, subcutaneous and visceral adipose tissue, and serum from cachectic and control cancer patients. Organ-wise comparisons were performed using component, pathway enrichment and correlation network analyses. Inter-organ correlations in CCx altered pathways were assessed using Circos. Machine learning on tissues and serum established classifiers as potential diagnostic biomarkers for CCx. ResultsDistinct metabolic pathway alteration was detected in CCx, with adipose tissues and liver displaying the most significant (P ≤ 0.05) metabolic disturbances. CCx patients exhibited increased metabolic activity in visceral and subcutaneous adipose tissues and liver, contrasting with decreased activity in muscle and serum compared to control patients. Carbohydrate, lipid, amino acid, and vitamin metabolism emerged as highly interacting pathways across different organ systems in CCx. Muscle tissue showed decreased (P ≤ 0.001) energy charge in CCx patients, while liver and adipose tissues displayed increased energy charge (P ≤ 0.001). We stratified CCx patients by severity and metabolic changes, finding that visceral adipose tissue is most affected, especially in cases of severe cachexia. Morphometric analysis showed smaller (P ≤ 0.05) adipocyte size in visceral adipose tissue, indicating catabolic processes. We developed tissue-based classifiers for cancer cachexia specific to individual organs, facilitating the transfer of patient serum as minimally invasive diagnostic markers of CCx in the constitution of the organs. ConclusionsThese findings support the concept of CCx as a multi-organ syndrome with diverse metabolic alterations, providing insights into the pathophysiology and organ cross-talk of human CCx. This study pioneers spatial metabolomics for CCx, demonstrating the feasibility of distinguishing cachexia status at the organ level using serum.

Machine learning and single-cell analysis identify the mitophagy-associated gene TOMM22 as a potential diagnostic biomarker for intervertebral disc degeneration

BackgroundMitophagy selectively eliminates potentially cytotoxic and damaged mitochondria and effectively prevents excessive cytotoxicity from damaged mitochondria, thereby attenuating inflammatory and oxidative responses. However, the potential role of mitophagy in intervertebral disc degeneration remains to be elucidated. MethodsThe GSVA method, two machine learning methods (SVM-RFE algorithm and random forest), the CIBERSORT and MCPcounter methods, as well as the consensus clustering method and the WGCNA algorithm were used to analyze the involvement of mitophagy in intervertebral disc degeneration, the diagnostic value of mitophagy-associated genes in intervertebral disc degeneration, and the infiltration of immune cells, and identify the gene modules that were closely related to mitophagy. Single-cell analysis was used to detect mitophagy scores and TOMM22 expression, and pseudo-temporal analysis was used to explore the function of TOMM22 in nucleus pulposus cells. In addition, TOMM22 expression was compared between human normal and degenerated intervertebral disc tissue samples by immunohistochemistry and PCR. ResultsThis study identified that the mitophagy pathway score was elevated in intervertebral disc degeneration compared with the normal condition. A strong link was present between mitophagy genes and immune cells, which may be used to typify intervertebral disc degeneration. The single-cell level showed that mitophagy-associated gene TOMM22 was highly expressed in medullary cells of the disease group. Further investigations indicated the upregulation of TOMM22 expression in late-stage nucleus pulposus cells and its role in cellular communication. In addition, human intervertebral disc tissue samples established that TOMM22 levels were higher in disc degeneration samples than in normal samples. ConclusionsOur findings revealed that mitophagy may be used in the diagnosis of intervertebral disc degeneration and its typing, and TOMM22 is a molecule in this regard and may act as a potential diagnostic marker in intervertebral disc degeneration.