Potential Diagnostic Biomarkers Research Articles

Gut Microbiota Signatures in Colorectal Cancer as a Potential Diagnostic Biomarker in the Future: A Systematic Review

Gut Microbiota Signatures in Colorectal Cancer as a Potential Diagnostic Biomarker in the Future: A Systematic Review

Identification and validation of potential genes for the diagnosis of sepsis by bioinformatics and 2-sample Mendelian randomization study.

This integrated study combines bioinformatics, machine learning, and Mendelian randomization (MR) to discover and validate molecular biomarkers for sepsis diagnosis. Methods include differential expression analysis, weighted gene co-expression network analysis (WGCNA) for identifying sepsis-related modules and hub genes, and functional enrichment analyses to explore the roles of hub genes. Machine learning algorithms identify 3 diagnostic genes - CD177, LDHA, and MCEMP1 - consistently highly expressed in sepsis patients. The nomogram model effectively predicts sepsis risk, supported by receiver operator characteristic (ROC) curves. Correlations between diagnostic genes and immune cell infiltration are observed. MR analysis reveals a positive causal relationship between MCEMP1 and sepsis risk. In conclusion, this study presents potential sepsis diagnostic biomarkers, highlighting the genetic association of MCEMP1 with sepsis for insights into early diagnosis.

Collaborative CRISPR-Cas System-Enabled Detection of Circulating Circular RNA for Reliable Monitoring of Acute Myocardial Infarction.

Acute myocardial infarction (AMI) is one of the major causes of death worldwide, posing significant global health challenges. Circular RNA (circRNA) has recently emerged as a potential diagnostic biomarker for AMI, providing valuable information for timely medical care. In this work, a new electrochemical method for circRNA detection by engineering a collaborative CRISPR-Cas system is developed. This system integrates the unique circRNA-targeting ability with cascade trans-cleavage activities of Cas effectors, using an isothermal primer exchange reaction as the bridge. Using cZNF292, a circulating circRNA biomarker for AMI is identified by this group; as a model, the collaborative CRISPR-Cas system-based method exhibits excellent accuracy and sensitivity with a low detection limit of 2.13 × 10-15 m. Moreover, the method demonstrates a good diagnostic performance for AMI when analyzing whole blood samples. Therefore, the method may provide new insight into the detection of circRNA biomarkers and is expected to have great potential in AMI diagnosis in the future.

The diagnostic value of serum exosomal SNORD116 and SNORA21 for NSCLC patients.

Non-small cell lung cancer (NSCLC) is a widespread and serious global malignancy. This study aimed to examine the clinical relevance of serum exosomal SNORD116 and SNORA21 as novel diagnostic biomarkers for NSCLC. Serum exosomes from 226 healthy controls and 305 NSCLC patients were isolated by ultracentrifugation. Characterization of exosomes was conducted by qNano, transmission electron microscopy (TEM) and Western immunoblotting. RT-PCR revealed snoRNAs that were differentially expressed. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance. In NSCLC patients, the levels of serum exosomal SNORD116 and SNORA21 were significantly reduced compared to those in healthy controls (P < 0.0001 for both). ROC curves showed AUC values of 0.738 and 0.761. By combining SNORD116 and SNORA21 with traditional blood biomarkers CYFRA21-1 and carcinoembryonic antigen (CEA), the AUC increased to 0.917. Moreover, these two exosomal snoRNAs distinguished between patients with metastatic NSCLC (n = 132) and those with non-metastatic NSCLC (n = 173) significantly (P < 0.0001 for both). The ROC curves gave AUC values of 0.743 and 0.694, respectively. The combined analysis raised the AUC to 0.751. The diagnostic power of these two exosomal snoRNAs combined with CYFRA21-1 and CEA increased to 0.784. This study demonstrated that serum exosomal SNORD116 and SNORA21 can be used as potential promising non-invasive diagnostic biomarkers for NSCLC.

CXCL9, IL2RB, and SPP1, potential diagnostic biomarkers in the co-morbidity pattern of atherosclerosis and non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) is a hepatocyte inflammation based on hepatocellular steatosis, yet there is no effective drug treatment. Atherosclerosis (AS) is caused by lipid deposition in the endothelium, which can lead to various cardiovascular diseases. NASH and AS share common risk factors, and NASH can also elevate the risk of AS, causing a higher morbidity and mortality rate for atherosclerotic heart disease. Therefore, timely detection and diagnosis of NASH and AS are particularly important. In this study, differential gene expression analysis and weighted gene co-expression network analysis were performed on the AS (GSE100927) and NASH (GSE89632) datasets to obtain common crosstalk genes, respectively. Then, candidate Hub genes were screened using four topological algorithms and externally validated in the GSE43292 and GSE63067 datasets to obtain Hub genes. Furthermore, immune infiltration analysis and gene set variation analysis were performed on the Hub genes to explore the underlying mechanisms. The DGIbd database was used to screen candidate drugs for AS and NASH. Finally, a NASH model was constructed using free fatty acid-induced human L02 cells, an AS model was constructed using lipopolysaccharide-induced HUVECs, and a co-morbidity model was constructed using L02 cells and HUVECs to verify Hub gene expression. The result showed that a total of 113 genes common to both AS and NASH were identified as crosstalk genes, and enrichment analysis indicated that these genes were mainly involved in the regulation of immune and metabolism-related pathways. 28 candidate Hub genes were screened according to four topological algorithms, and CXCL9, IL2RB, and SPP1 were identified as Hub genes after in vitro experiments and external dataset validation. The ROC curves and SVM modeling demonstrated the good diagnostic efficacy of these three Hub genes. In addition, the Hub genes are strongly associated with immune cell infiltration, especially macrophages and γ–δ T cell infiltration. Finally, five potential therapeutic drugs were identified. has-miR-185 and hsa-miR-335 were closely related to AS and NASH. This study demonstrates that CXCL9, IL2RB, and SPP1 may serve as potential biomarkers for the diagnosis of the co-morbidity patterns of AS and NASH and as potential targets for drug therapy.

Comprehensive Analysis Reveals Epithelial Growth Factor Receptor as a Potential Diagnostic Biomarker in Glioblastoma Multiforme

Comprehensive Analysis Reveals Epithelial Growth Factor Receptor as a Potential Diagnostic Biomarker in Glioblastoma Multiforme

Utility of gingival crevicular fluid components for periodontal diagnosis.

Periodontal diseases are highly prevalent chronic diseases, and severe periodontitis creates functional and esthetic problems and decreases self-esteem for a large percentage of the older population worldwide. In many cases of periodontitis, there is no distinct tell-tale pain that motivates a patient to seek treatment, rather the signs become clinically detectable late, and typically when the disease has progressed to a problematic level for the life of the dentition. Early periodontal screening and diagnostics tools will provide early recognition of periodontal diseases and facilitate timely management of the disease to reduce tooth loss. To this goal, gingival crevicular fluid is easily sampled, can be repeatedly and non-invasively collected, and can be tested for potential biomarkers. Moreover, the site specificity of periodontal diseases enhances the usefulness of gingival crevicular fluid sampled from specific sites as a biofluid for diagnosis and longitudinal monitoring of periodontal diseases. The present review aimed to provide up-to-date information on potential diagnostic biomarkers with utility that can be assayed from gingival crevicular fluid samples, focusing on what is new and useful and providing only general historic background textually and in a tabulated format.

Proteomic insights into extracellular vesicles in ALS for therapeutic potential of Ropinirole and biomarker discovery

BackgroundExtracellular vesicles (EVs) hold the potential for elucidating the pathogenesis of amyotrophic lateral sclerosis (ALS) and serve as biomarkers. Notably, the comparative and longitudinal alterations in the protein profiles of EVs in serum (sEVs) and cerebrospinal fluid (CSF; cEVs) of sporadic ALS (SALS) patients remain uncharted. Ropinirole hydrochloride (ROPI; dopamine D2 receptor [D2R] agonist), a new anti-ALS drug candidate identified through induced pluripotent stem cell (iPSC)-based drug discovery, has been suggested to inhibit ALS disease progression in the Ropinirole Hydrochloride Remedy for Amyotrophic Lateral Sclerosis (ROPALS) trial, but its mechanism of action is not well understood. Therefore, we tried to reveal longitudinal changes with disease progression and the effects of ROPI on protein profiles of EVs.MethodsWe collected serum and CSF at fixed intervals from ten controls and from 20 SALS patients participating in the ROPALS trial. Comprehensive proteomic analysis of EVs, extracted from these samples, was conducted using liquid chromatography/mass spectrometer (LC/MS). Furthermore, we generated iPSC-derived astrocytes (iPasts) and performed RNA sequencing on astrocytes with or without ROPI treatment.ResultsThe findings revealed notable disparities yet high congruity in sEVs and cEVs protein profiles concerning disease status, time and ROPI administration. In SALS, both sEVs and cEVs presented elevated levels of inflammation-related proteins but reduced levels associated with unfolded protein response (UPR). These results mirrored the longitudinal changes after disease onset and correlated with the revised ALS Functional Rating Scale (ALSFRS-R) at sampling time, suggesting a link to the onset and progression of SALS. ROPI appeared to counteract these changes, attenuating inflammation-related protein levels and boosting those tied to UPR in SALS, proposing an anti-ALS impact on EV protein profiles. Reverse translational research using iPasts indicated that these changes may partly reflect the DRD2-dependent neuroinflammatory inhibitory effects of ROPI. We have also identified biomarkers that predict diagnosis and disease progression by machine learning-driven biomarker search.ConclusionsDespite the limited sample size, this study pioneers in reporting time-series proteomic alterations in serum and CSF EVs from SALS patients, offering comprehensive insights into SALS pathogenesis, ROPI-induced changes, and potential prognostic and diagnostic biomarkers.

The relationship between follicle-stimulating hormone and metabolic dysfunction-associated fatty liver disease in men

ObjectivesThe present study aimed to investigate the relationship between male hormones and metabolic dysfunction-associated fatty liver disease (MAFLD) in males.MethodsData from the Fangchenggang Area Male Health and Examination Survey (FAMHES) were used to analyze the male hormone levels between MAFLD patients and controls. Univariate and multivariate logistic regression analyses were performed to identify risk factors for MAFLD. Receiver operating characteristic curve analysis was used to assess the diagnostic performance of male hormones for MAFLD.ResultA total of 1578 individuals were included, with 482 individuals (30.54%) of MAFLD, including 293 (18.57%) with mild disease and 189 (11.98%) with moderate-to-severe disease. The MAFLD patients were significantly older than those without MAFLD. The LH, FSH, and SHBG levels in the MAFLD patients were significantly greater than those in the control group. Age, FSH, LH, SHBG, and estradiol were all risk factors for MAFLD. Age, FSH, and LH were risk factors for moderate-to-severe MAFLD. FSH was an independent risk factor for MAFLD and moderate-to-severe MAFLD. FSH showed an excellent diagnostic value, with an AUC of 0.992 alone and 0.996 after adjusting age.ConclusionsOur findings indicate that FSH may be a potential diagnostic and predictive biomarker for MAFLD.

Extraction and characterization of exosomes from the exhaled breath condensate and sputum of lung cancer patients and vulnerable tobacco consumers—potential noninvasive diagnostic biomarker source

Noninvasive sample sources of exosomes, such as exhaled breath and sputum, which are in close proximity to the tumor microenvironment and may contain biomarkers indicative of lung cancer, are far more permissive than invasive sample sources for biomarker screening. Standardized exosome extraction and characterization approaches for low-volume noninvasive samples are critically needed. We isolated and characterized exhaled breath condensate (EBC) and sputum exosomes from healthy nonsmokers (n = 30), tobacco smokers (n = 30), and lung cancer patients (n = 40) and correlated the findings with invasive sample sources. EBC samples were collected by using commercially available R-Tubes. To collect sputum samples the participants were directed to take deep breaths, hold their breath, and cough in a collection container. Dynamic light scattering, nanoparticle tracking analysis, and transmission electron microscopy were used to evaluate the exosome morphology. Protein isolation, western blotting, exosome quantification via EXOCET, and Fourier transform infrared spectroscopy were performed for molecular characterization. Exosomes were successfully isolated from EBC and sputum samples, and their yields were adequate and sufficiently pure for subsequent downstream processing and characterization. The exosomes were confirmed based on their size, shape, and surface marker expression. Remarkably, cancer exosomes were the largest in size not only in the plasma subgroups, but also in the EBC (p < 0.05) and sputum (p = 0.0036) subgroups, according to our findings. A significant difference in exosome concentrations were observed between the control sub-groups (p < 0.05). Our research confirmed that exosomes can be extracted from noninvasive sources, such as EBC and sputum, to investigate lung cancer diagnostic biomarkers for research, clinical, and early detection in smokers.

Ribonuclease 4 functions as an intestinal antimicrobial protein to maintain gut microbiota and metabolite homeostasis

Antimicrobial proteins contribute to host-microbiota interactions and are associated with inflammatory bowel disease (IBD), but our understanding on antimicrobial protein diversity and functions remains incomplete. Ribonuclease 4 (Rnase4) is a potential antimicrobial protein with no known function in the intestines. Here we find that RNASE4 is expressed in intestinal epithelial cells (IEC) including Paneth and goblet cells, and is detectable in human and mouse stool. Results from Rnase4-deficient mice and recombinant protein suggest that Rnase4 kills Parasutterella to modulate intestinal microbiome, thereby enhancing indoleamine-2,3-dioxygenase 1 (IDO1) expression and subsequently kynurenic and xanthurenic acid production in IECs to reduce colitis susceptibility. Furthermore, deceased RNASE4 levels are observed in the intestinal tissues and stool from patients with IBD, correlating with increased stool Parasutterella. Our results thus implicate Rnase4 as an intestinal antimicrobial protein regulating gut microbiota and metabolite homeostasis, and as a potential diagnostic biomarker and therapeutic target for IBD.

Identifying Diagnostic Markers and Constructing Predictive Models for Oxidative Stress in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic disease characterized by inflammation and neurodegeneration of the central nervous system. Despite the significant role of oxidative stress in the pathogenesis of MS, its precise molecular mechanisms remain unclear. This study utilized microarray datasets from the GEO database to analyze differentially expressed oxidative-stress-related genes (DE-OSRGs), identifying 101 DE-OSRGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that these genes are primarily involved in oxidative stress and immune responses. Through protein–protein interaction (PPI) network, LASSO regression, and logistic regression analyses, four genes (MMP9, NFKBIA, NFKB1, and SRC) were identified as being closely related to MS. A diagnostic prediction model based on logistic regression demonstrated good predictive power, as shown by the nomogram curve index and DAC results. An immune-cell infiltration analysis using CIBERSORT revealed significant correlations between these genes and immune cell subpopulations. Abnormal oxidative stress and upregulated expression of key genes were observed in the blood and brain tissues of EAE mice. A molecular docking analysis suggested strong binding potentials between the proteins of these genes and several drug molecules, including isoquercitrin, decitabine, benztropine, and curcumin. In conclusion, this study identifies and validates potential diagnostic biomarkers for MS, establishes an effective prediction model, and provides new insights for the early diagnosis and personalized treatment of MS.

CircCFL1 Promotes TNBC Stemness and Immunoescape via Deacetylation-Mediated c-Myc Deubiquitylation to Facilitate Mutant TP53 Transcription.

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. TP53, which has a mutation rate of ≈70%-80% in TNBC patients, plays oncogenic roles when mutated. However, whether circRNAs can exert their effects on TNBC through regulating mutant TP53 has not been well evaluated. In this study, circCFL1, which is highly expressed in TNBC cells and tissues and has prognostic potential is identified. Functionally, circCFL1 promoted the proliferation, metastasis and stemness of TNBC cells. Mechanistically, circCFL1 acted as a scaffold to enhance the interaction between HDAC1 and c-Myc, further promoting the stability of c-Myc via deacetylation-mediated inhibition of K48-linked ubiquitylation. Stably expressed c-Myc further enhanced the expression of mutp53 in TNBC cells with TP53 mutations by directly binding to the promoter of TP53, which promoted the stemness of TNBC cells via activation of the p-AKT/WIP/YAP/TAZ pathway. Moreover, circCFL1 can facilitate the immune escape of TNBC cells by promoting the expression of PD-L1 and suppressing the antitumor immunity of CD8+ T cells. In conclusion, the results revealed that circCFL1 plays an oncogenic role by promoting the HDAC1/c-Myc/mutp53 axis, which can serve as a potential diagnostic biomarker and therapeutic target for TNBC patients with TP53 mutations.

Current potential diagnostic biomarkers of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) currently lacks the useful diagnostic biomarkers. The current diagnosis of ALS is mainly depended on the clinical manifestations, which contributes to the diagnostic delay and be difficult to make the accurate diagnosis at the early stage of ALS, and hinders the clinical early therapeutics. The more and more pathogenesis of ALS are found at the last 30 years, including excitotoxicity, the oxidative stress, the mitochondrial dysfunction, neuroinflammation, the altered energy metabolism, the RNA misprocessing and the most recent neuroimaging findings. The findings of these pathogenesis bring the new clues for searching the diagnostic biomarkers of ALS. At present, a large number of relevant studies about the diagnostic biomarkers are underway. The ALS pathogenesis related to the diagnostic biomarkers might lessen the diagnostic reliance on the clinical manifestations. Among them, the cortical altered signatures of ALS patients derived from both structural and functional magnetic resonance imaging and the emerging proteomic biomarkers of neuronal loss and glial activation in the cerebrospinal fluid as well as the potential biomarkers in blood, serum, urine, and saliva are leading a new phase of biomarkers. Here, we reviewed these current potential diagnostic biomarkers of ALS.

LCP1 correlates with immune infiltration: a prognostic marker for triple-negative breast cancer

ObjectiveTriple-Negative Breast Cancer (TNBC) is known for its aggressiveness and treatment challenges due to the absence of ER, PR, and HER2 receptors. Our work emphasizes the prognostic value of LCP1 (Lymphocyte cytosolic protein 1), which plays a crucial role in cell processes and immune cell activity, to predict outcomes and guide treatments in TNBC.MethodsWe explored LCP1 as a potential biomarker in TNBC and investigated the mRNA and protein expression levels of LCP1. We investigated different databases, including GTEX, TCGA, GEO, cBioPortal and Kaplan-Meier Plotter. Immunohistochemistry on TNBC and benign tumor samples was performed to examine LCP1's relationship with patient clinical characteristics and macrophage markers. We also assessed survival rates, immune cell infiltration, and drug sensitivity related to LCP1 using various bioinformatics tools.ResultsThe results indicated that LCP1 expression was higher in TNBC tissues compared to adjacent normal tissues. However, high expression of LCP1 was significantly associated with favorable survival outcomes in patients with TNBC. Enrichment analysis revealed that genes co-expressed with LCP1 were significantly enriched in various immune processes. LCP1 showed a positive correlation with the infiltration of resting dendritic cells, M1 macrophages, and memory CD4 T cells, and a negative correlation with M2 macrophages. Further analysis suggested a link between high levels of LCP1 and increased survival outcomes in cancer patients receiving immunotherapy.ConclusionLCP1 may serve as a potential diagnostic and prognostic biomarker for TNBC, which was closely associated with immune cell infiltration, particularly M1 and M2 macrophages. Our findings may provide valuable insights into immunotherapeutic strategies for TNBC patients.

Preclinical evaluation of [18F]FP-CIT, the radiotracer targeting dopamine transporter for diagnosing Parkinson’s disease: pharmacokinetic and efficacy analysis

BackgroundN-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (FP-CIT), the representative cocaine derivative used in dopamine transporter imaging, is a promising biomarker, as it reflects the severity of Parkinson’s disease (PD). 123I- and 18F-labeled FP-CIT has been used for PD diagnosis. However, preclinical studies evaluating [18F]FP-CIT as a potential diagnostic biomarker are scarce. Among translational research advancements from bench to bedside, translating preclinical findings into clinical practice is one-directional. The aim of this study is to employ a circular approach, beginning back from the preclinical stage, progressing to the supplementation of [18F]FP-CIT, and subsequently returning to clinical application. We investigated the pharmacokinetic properties of [18F]FP-CIT and its efficacy for PD diagnosis using murine models.ResultsBiodistribution, metabolite and excretion analyses were performed in mice and PD models were induced in rats using 6-hydroxydopamine (6-OHDA). The targeting efficiency of [18F]FP-CIT for the dopamine receptor was assessed through animal PET/CT imaging. Subsequently, correlation analysis was conducted between animal PET/CT imaging results and immunohistochemistry (IHC) targeting tyrosine hydroxylase. Rapid circulation was confirmed after [18F]FP-CIT injection. [18F]FP-CIT reached the highest uptake of 23.50 ± 12.46%ID/g in the striatum 1 min after injection, and it was rapidly excreted within 60 min. The major metabolic organs of [18F]FP-CIT were confirmed to be the intestines, liver, and kidneys. Its uptake in the intestine was approximately 5% ID/g. The uptake in the liver gradually increased, with excretion beginning after reaching a maximum after 60 min. The kidneys exhibited rapid elimination after 10 min. In the excretion study, rapid elimination was verified, with 21.46 ± 9.53% of the compound excreted within a 6 h period. Additionally, the efficacy of [18F]FP-CIT PET was demonstrated in the PD model, with a high correlation with IHC for both the absolute value (R = 0.803, p = 0.0017) and the ratio value (R = 0.973, p = 0.0011).ConclusionsThis study fills the gap regarding insufficient preclinical studies on [18F]FP-CIT, including its ADME, metabolites, and efficiency. The pharmacological results, including accurate diagnosis, rapid circulation, and [18F]FP-CIT excretion, provide complementary evidence that [18F]FP-CIT can be used safely and efficiently to diagnose PD in clinics, although it is already used in clinics.

Potential role of mitochondrial uncoupling protein 2 as a biomarker in patients with sepsis and septic shock: A prospective observational study

Background and Aims: Early diagnosis of sepsis is crucial. The primary objective of this study was to explore the role of uncoupling protein 2 (UCP2) in diagnosing sepsis and septic shock. Methods: This prospective observational study was conducted over 19 months. All adult patients aged more than 18 years with a diagnosis of sepsis or septic shock based on quick sequential organ failure assessment (qSOFA) score were enroled. Blood was drawn for procalcitonin (PCT) and UCP2 on days 0, 3, 7 and 28. Blood samples from 50 healthy volunteers were used as controls. An electrochemiluminescence test was done for PCT. A quantitative enzyme-linked immune sorbent assay was used for UCP2. The Chi-square test was used for qualitative variables and the independent t-test for quantitative variables. The receiver operator characteristic curve was used to evaluate the diagnostic efficacy of UCP2. Results: A total of 128 subjects were included in the study. Out of these, 78 patients (qSOFA score ≥2) were subcategorised into the infection group, sepsis or septic shock group based on the PCT levels. The UCP2 levels in the infection, sepsis or septic shock group were significantly higher than in the control group (P &gt; 0.001). The UCP2 levels correlated with PCT on admission, day 3 and day 7. Conclusion: The UCP2 levels were significantly higher in sepsis and septic shock groups compared to controls and hence could be a potential diagnostic biomarker of sepsis.

Potential diagnostic, prognostic, and predictive biomarkers of gastric cancer.

Gastric cancer (GC), a malignant epithelial tumor, is the fourth leading cause of cancer-related death worldwide. Therapeutic strategies for GC, despite the biggest challenges, can significantly improve survival rates through early detection and effective screening methods. To provide brief information on the necessity of multiple specific diagnostic, prognostic, and predictive markers for GC. This review was conducted using a variety of search engines, including PubMed Central, Scopus, Web of Science, Google Scholar, and others. Some potential biomarkers that provide essential information include circulating tumor cells (CTCs), DNA methylation, claudin 18.2, fibroblast growth factor receptor 2 (FGFR2), long noncoding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and serum pepsinogens. Multiple tumor markers are essential for screening, tumor identification, staging, prognostic assessment, and monitoring recurrence after therapy due to the absence of a single tumor indicator for diagnosing, prognosticating, and predicting GC.

The Potential MicroRNA Diagnostic Biomarkers in Oral Squamous Cell Carcinoma of the Tongue

Oral squamous cell carcinoma (OSCC) of the tongue is a common type of head and neck malignancy with a poor prognosis, underscoring the urgency for early detection. MicroRNAs (miRNAs) have remarkable stability and are easily measurable. Thus, miRNAs may be a promising biomarker candidate among biomarkers in cancer diagnosis. Biomarkers have the potential to facilitate personalized medicine approaches by guiding treatment decisions and optimizing therapy regimens for individual patients. Utilizing data from The Cancer Genome Atlas, we identified 13 differentially expressed upregulated miRNAs in OSCC of the tongue. Differentially expressed miRNAs were analyzed by enrichment analysis to reveal underlying biological processes, pathways, or functions. Furthermore, we identified miRNAs associated with the progression of OSCC of the tongue, utilizing receiver operating characteristic analysis to evaluate their potential as diagnostic biomarkers. A total of 13 upregulated miRNAs were identified as differentially expressed in OSCC of the tongue. Five of these miRNAs had high diagnostic power. In particular, miR-196b has the potential to serve as one of the most effective diagnostic biomarkers. Then, functional enrichment analysis for the target gene of miR-196b was performed, and a protein–protein interaction network was constructed. This study assessed an effective approach for identifying miRNAs as early diagnostic markers for OSCC of the tongue.

Upregulation of the long noncoding RNA GJA9-MYCBP and PVT1 is a potential diagnostic biomarker for acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the most common type of blood cancer in children. Aberrant expression of long noncoding RNAs (lncRNAs) may set stages for ALL development. LncRNAs are emerging as a novel diagnostic and prognostic biomarker for ALL. Herein, we aimed to evaluate the expression of lncRNA GJA9-MYCBP and PVT1 in blood samples of ALL and healthy individuals. As a case-control study, 40 pairs of ALL and healthy individual samples were used. The expression of MYC and each candidate lncRNA was measured using quantitative real-time PCR. Any possible association between the expression of putative noncoding RNAs and clinicopathological characteristics was also evaluated. LncRNA GJA9-MYCBP and PVT1 were significantly upregulated in ALL samples compared with healthy ones. Similarly, mRNA levels of MYC were increased in ALL samples than control ones. Receiver operating characteristic curve analysis indicated a satisfactory diagnostic efficacy (p-value <.0001), suggesting that lncRNA GJA9-MYCBP and PVT1 may serve as a diagnostic biomarker for ALL. Linear regression analysis unveiled positive correlations between the expression level of MYC and lncRNA GJA9-MYCBP and PVT1 in ALL patients (p-values <.01). In this study, we provided approval for the clinical diagnostic significance of lncRNA GJA9-MYCBP and PVT1that their upregulations may be a diagnostic biomarker for ALL.