scholarly journals A Novel Serum tsRNA for Diagnosis and Prediction of Nephritis in SLE

2021 ◽  
Vol 12 ◽  
Author(s):  
Ping Yang ◽  
Xiaoshan Zhang ◽  
Shanshan Chen ◽  
Yue Tao ◽  
Mingzhe Ning ◽  
...  
Keyword(s):  
Lupus Erythematosus ◽  
Noncoding Rna ◽  
Area Under The Curve ◽  
Taqman Probe ◽  
Small Rna Sequencing ◽  
Roc Curve Analysis ◽  
Diagnostic Efficacy ◽  
Small Noncoding Rna ◽  
Reverse Transcription Pcr ◽  
Noninvasive Biomarkers

ObjectiveDysregulation of transfer RNA (tRNA)-derived small noncoding RNA (tsRNA) signatures in human serum has been found in various diseases. Here, we determine whether the signatures of tsRNAs in serum can serve as biomarkers for diagnosis or prognosis of systemic lupus erythematosus (SLE).MethodsInitially, small RNA sequencing was employed for the screening serum tsRNAs obtained from SLE patients, followed by validation with TaqMan probe-based quantitative reverse transcription-PCR (RT-PCR) assay. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy. The biological functions of tsRNAs were identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) assay.ResultsWe first analyzed tsRNA signatures in SLE serum and identified that tRF-His-GTG-1 was significantly upregulated in SLE serum. The combination of tRF-His-GTG-1 and anti-dsDNA could serve as biomarkers for diagnosing SLE with a high area under the curve (AUC) of 0.95 (95% CI = 0.92–0.99), sensitivity (83.72%), and specificity (94.19%). Importantly, the noninvasive serum tRF-His-GTG-1 could also be used to distinguish SLE with LN or SLE without LN with AUC of 0.81 (95% CI, 0.73–0.88) and performance (sensitivity 66.27%, specificity 96.15%). Moreover, the serum tsRNA is mainly secreted via exosome and can directly target signaling molecules that play crucial roles in regulating the immune system.ConclusionIn this study, it has been demonstrated for the first time that serum tsRNAs can be employed as noninvasive biomarkers for the efficient diagnosis and prediction of nephritis in SLE.

scholarly journals Doppler ultrasound for diagnosis of soft tissue sarcoma: efficacy of ultrasound-based screening score

2015 ◽  
Vol 49 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Satoshi Nagano ◽  
Yuhei Yahiro ◽  
Masahiro Yokouchi ◽  
Takao Setoguchi ◽  
Yasuhiro Ishidou ◽  
...  
Keyword(s):  
Doppler Ultrasound ◽  
Ultrasound Imaging ◽  
Operating Characteristic ◽  
Soft Part ◽  
Imaging Modality ◽  
Screening Method ◽  
Area Under The Curve ◽  
Roc Curve Analysis ◽  
Diagnostic Efficacy ◽  
The Mean

Abstract Background. The utility of ultrasound imaging in the screening of soft-part tumours (SPTs) has been reported. We classified SPTs according to their blood flow pattern on Doppler ultrasound and re-evaluated the efficacy of this imaging modality as a screening method. Additionally, we combined Doppler ultrasound with several values to improve the diagnostic efficacy and to establish a new diagnostic tool. Patients and methods. This study included 189 cases of pathologically confirmed SPTs (122 cases of benign disease including SPTs and tumour-like lesions and 67 cases of malignant SPTs). Ultrasound imaging included evaluation of vascularity by colour Doppler. We established a scoring system to more effectively differentiate malignant from benign SPTs (ultrasound-based sarcoma screening [USS] score). Results. The mean scores in the benign and malignant groups were 1.47 ± 0.93 and 3.42 ± 1.30, respectively. Patients with malignant masses showed significantly higher USS scores than did those with benign masses (p < 1 × 10-10). The area under the curve was 0.88 by receiver operating characteristic (ROC) analysis. Based on the cut-off value (3 points) calculated by ROC curve analysis, the sensitivity and specificity for a diagnosis of malignant SPT was 85.1% and 86.9%, respectively. Conclusions. Assessment of vascularity by Doppler ultrasound alone is insufficient for differentiation between benign and malignant SPTs. Preoperative diagnosis of most SPTs is possible by combining our USS score with characteristic clinical and magnetic resonance imaging findings.

Circulating Small Noncoding RNA Biomarkers of Response to Triple Disease-modifying Antirheumatic Drug Therapy in White Women With Early Rheumatoid Arthritis

2020 ◽  
Vol 47 (12) ◽  
pp. 1746-1751
Author(s):  
Andrew D. Foers ◽  
Alexandra L. Garnham ◽  
Gordon K. Smyth ◽  
Susanna M. Proudman ◽  
Lesley Cheng ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Early Rheumatoid Arthritis ◽  
Noncoding Rna ◽  
Differential Expression Analysis ◽  
Antirheumatic Drug ◽  
Small Rna Sequencing ◽  
Dmard Therapy ◽  
Small Noncoding Rna ◽  
Disease Modifying ◽  
Disease Modifying Antirheumatic Drug

ObjectiveTo identify small noncoding RNA (sncRNA) serum biomarkers that predict response to triple disease-modifying antirheumatic drug (DMARD) therapy in patients with early rheumatoid arthritis (RA).MethodsEarly RA patients entered into a treat-to-target management algorithm, with triple DMARD therapy (methotrexate, sulfasalazine, hydroxychloroquine). Patients were assessed following 6 months of therapy and classified as European League Against Rheumatism responders or nonresponders. RNA was isolated from 42 archived serum samples, collected prior to commencement of triple DMARD therapy. Small RNA sequencing was performed and the reads mapped to annotations in a database of human sncRNA. Differential expression analysis was performed, comparing responders (n = 24) and nonresponders (n = 18).ResultsPretreatment levels of 4 sncRNA were significantly increased in nonresponders: chr1. tRNA131-GlyCCC (4.1-fold, adjusted P = 0.01), chr2.tRNA13-AlaCGC (2.2-fold, adjusted P = 0.02), U2-L166 (6.6-fold, adjusted P = 0.02), and piR-35982 (2.4-fold, adjusted P = 0.03). 5S-L612 was the only sncRNA significantly increased in responders (3.3-fold; adjusted P = 0.01). Reads for chr1. tRNA131-GlyCCC and chr2.tRNA13-AlaCGC mapped to the 5′ end of each tRNA gene and were truncated at the anticodon loop, consistent with these sncRNA having roles as 5′ translation interfering tRNA halves (tiRNA).ConclusionPretreatment levels of specific serum sncRNA might facilitate identification of patients more likely to respond to triple DMARD therapy.

Next-generation sequencing (NGS) of serum microRNA in hepatocellular carcinoma (HCC) patients treated with sorafenib and an mTOR inhibitor.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. LBA204-LBA204 ◽  
Author(s):  
Robin Kate Kelley ◽  
Aaron N. Chang ◽  
Esperanza Anguiano ◽  
Jimmy Hwang ◽  
Hubert J. Stoppler ◽  
...  
Keyword(s):  
Noncoding Rna ◽  
Predictive Biomarkers ◽  
P Value ◽  
Serum Samples ◽  
Illumina Hiseq ◽  
Small Noncoding Rna ◽  
Multiple Test ◽  
Serum Microrna ◽  
Noninvasive Biomarkers ◽  
Malignant Liver

LBA204 Background: Noninvasive biomarkers are urgently needed in HCC. MicroRNA (miRNA) are small, noncoding RNA that regulate mRNA expression and are detectable in tumor tissue and extracellular compartments. miRNA signatures in blood specimens show association with HCC diagnosis but have not been explored as pharmacodynamic or predictive biomarkers. We present a pilot study to identify differentially expressed miRNA using NGS on serum from HCC patients at baseline and on targeted therapy, compared to controls. Methods: Serum samples were obtained from HCC patients enrolled on a clinical trial of sorafenib plus temsirolimus. Control sera were obtained from patients with non-malignant liver diseases (NMLD) and healthy volunteers (HV). Total RNA was extracted using RNAzol followed by library construction for each sample. Small RNA were separated by gel purification and sequenced by Illumina HiSeq 2500 at 5M+ reads per sample. Raw sequencing reads were mapped using Novoalign and quantified. Counts were normalized using an exogenous spike-in miRNA. Comparisons between HCC vs. control and baseline vs. on treatment cohorts were performed by linear regression (one-way ANOVA) and multiple-test corrected using Benjamini-Hochberg statistics. Candidate signature miRNA were derived using fold change, p-value, and abundance cutoffs. Results: Cohorts: HCC baseline (n=23) and paired on treatment (n=20), NMLD (n=12), and HV (n=10). HCC cohort: HBV+/dual 40%, HCV+ 32%. NMLD cohort: HCV+ 83%. Median RNA yield/200 µL was 410 ng (range: 69-1066) for HCC, 406 ng (range: 224-1100) for NMLD. The mapping rate ranged from 10-70%. Elevated AFP was associated with up-regulated miRNA identified in TCGA HCC cases, including miR-10a/b. No significant differences were observed for HBV+ vs. HCV+. Multiple oncomiRs appeared downregulated on treatment including Let-7 and miR-17/92 family members. Some miRNA isoforms were differentially regulated in each cohort. Conclusions: Serum miRNA in HCC patients demonstrate changes on treatment and can be characterized by NGS. Certain miRNA implicated in HCC appeared related to clinical covariates and warrant further study as novel biomarkers.

scholarly journals Circulating MicroRNA-4739 May Be a Potential Biomarker of Critical Limb Ischemia in Patients with Diabetes

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Ju-yi Li ◽  
Biao Cheng ◽  
Xiu-fang Wang ◽  
Zhong-jing Wang ◽  
Hong-mei Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critical Limb Ischemia ◽  
Area Under The Curve ◽  
Limb Ischemia ◽  
Circulating Microrna ◽  
Roc Curve Analysis ◽  
Altered Expression ◽  
Potential Biomarker ◽  
Patients With Diabetes ◽  
Noninvasive Biomarkers

Critical limb ischemia (CLI) is the most severe manifestation of peripheral artery disease, which is common but rarely diagnosed. Noninvasive biomarkers are urgently required to assist in the diagnosis of CLI. Accumulating evidence indicates that miRNAs play an important role in the development of various diseases. In this study, microarray profiling revealed 11 miRNAs with significantly altered expression in four T2DM patients with CLI compared with that in four sex- and age-matched T2DM patients without CLI. In independent cohorts, qRT-PCR validation confirmed the increased miRNA-4739 level in patients with CLI versus patients without CLI. miRNA-4739 levels increased with FPG and HbA1c (all P < 0.05). After adjusting for the risk factors, miRNA-4739 levels were found to be associated with an increased odds ratio (OR) of T2DM with CLI (OR =12.818, 95% confidence intervals (CI) 1.148 to 143.143, P = 0.038). ROC curve analysis revealed that the area under the curve (AUC) of miR-4739+confounding risk factors was 0.94 (95% CI 0.891 to 0.998, P < 0.001), which was higher than that of confounding risk factors (AUC 0.94 vs. 0.91, 95% CI -0.122 to 0.060, P > 0.05) and of miR-4739 (AUC 0.94 vs. 0.69, 95% CI -0.399 to -0.101, P < 0.001), respectively. We conclude that elevated plasma miRNA-4739 levels are independently associated with CLI in T2DM patients. miRNA-4739 is implicated as a novel diagnostic marker and a potential therapeutic target for CLI in diabetes.

Long non-coding RNA (lncRNA) DSCAM-AS1 is upregulated in breast cancer

2021 ◽  
pp. 1-6
Author(s):  
Mahsa Tarighi ◽  
Mohammad Khalaj-Kondori ◽  
Asghar Hosseinzadeh ◽  
Maryam Abtin
Keyword(s):  
Breast Cancer ◽  
Roc Curve ◽  
Noncoding Rna ◽  
Area Under The Curve ◽  
Clinicopathological Characteristics ◽  
Curve Analysis ◽  
Cancer Development ◽  
Roc Curve Analysis ◽  
Neoplastic Tissue ◽  
Tissue Samples

BACKGROUND: Accumulating evidence highlights that long noncoding RNA (lncRNA) DSCAM-AS1 play a key regulatory role in different stages of cancer development and progression. This study aimed to investigate whether the expression of DSCAM-AS1 is deregulated in breast cancer. MATERIALS AND METHODS: The relative expression of DSCAM-AS1 was measured in fifty breast cancerous and matched adjacent non-neoplastic tissue samples using quantitative real-time polymerase chain reaction (qPCR) technique. The association between DSCAM-AS1 expression and patients’ clinicopathological features was evaluated. Sensitivity and specificity of the DSCAM-AS1 expression for diagnosing breast cancer was obtained by the receiver operating characteristic (ROC) curve analysis. RESULTS: Our results showed that the expression of DSCAM-AS1 was significantly up-regulated in breast cancerous tissues compared with the matched adjacent non-neoplastic tissues (P < 0.05). Furthermore, we observed a significant association between the DSCAM-AS1 expression and lymph node metastasis (P = 0.011) but no other clinicopathological characteristics (P > 0.05). ROC curve analysis resulted in an area under the curve (AUC) of 0.67 and showed that the DSCAM-AS1 expression level may discriminate cancerous and non-cancerous tissues with 68% sensitivity and 76% specificity. CONCLUSION: This study provides further evidence that the expression of DSCAM-AS1 is deregulated in breast cancer and highlights its potential in breast cancer development.

scholarly journals Specific PIWI-interacting small noncoding RNA expression patterns in pulmonary tuberculosis patients

Epigenomics ◽  
2019 ◽  
Vol 11 (16) ◽  
pp. 1779-1794 ◽  
Author(s):  
Xing Zhang ◽  
Zi Liang ◽  
Yunshan Zhang ◽  
Min Zhu ◽  
Yueping Zhu ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Peripheral Blood ◽  
Noncoding Rna ◽  
Target Genes ◽  
Human Peripheral Blood ◽  
Expression Patterns ◽  
Small Rna Sequencing ◽  
Germline Development ◽  
Small Noncoding Rna ◽  
Pirna Pathway

Aim: PIWI-interacting RNAs (piRNAs) play crucial roles in germline development and carcinogenesis. The expression patterns of piRNAs in pulmonary tuberculosis (PTB) are still unclear. Materials & methods: Small RNA sequencing was applied to investigate peripheral blood piRNA expression patterns in PTB patients and healthy individuals. Results: A total of 428 upregulated and 349 downregulated piRNAs were identified from PTB patients. Target genes of dysregulated piRNAs were mainly involved in transcription and protein binding. Dysregulated piRNAs were enriched in many pathways related with immunity. Many target genes were regulated by the same piRNAs. Nucleotide bias of these piRNAs showed that piRNAs in peripheral blood may be formed from the primary biogenesis pathway. Conclusion: Findings demonstrated that the PIWI-piRNA pathway is active in human peripheral blood, where it may represent a new player in the PTB pathogenesis.

scholarly journals Noncoding RNAs Serve as Diagnosis and Prognosis Biomarkers for Hepatocellular Carcinoma

2019 ◽  
Vol 65 (7) ◽  
pp. 905-915 ◽  
Author(s):  
Chang Tan ◽  
Jingyi Cao ◽  
Lu Chen ◽  
Xiaochen Xi ◽  
Siqi Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Clinical Performance ◽  
Survival Rates ◽  
Noncoding Rnas ◽  
Area Under The Curve ◽  
Small Rna Sequencing ◽  
Diagnosis And Prognosis ◽  
Noninvasive Biomarkers

Abstract BACKGROUND Reliable noninvasive biomarkers for hepatocellular carcinoma (HCC) diagnosis and prognosis are urgently needed. We explored the potential of not only microRNAs (miRNAs) but other types of noncoding RNAs (ncRNAs) as HCC biomarkers. METHODS Peripheral blood samples were collected from 77 individuals; among them, 57 plasma cell-free RNA transcriptomes and 20 exosomal RNA transcriptomes were profiled. Significantly upregulated ncRNAs and published potential HCC biomarkers were validated with reverse transcription (RT)-qPCR in an independent validation cohort (60–150 samples). We particularly investigated the diagnosis and prognosis performance and biological function for 1 ncRNA biomarker, RN7SL1, and its S fragment. RESULTS We identified certain circulating ncRNAs escaping from RNase degradation, possibly through binding with RNA-binding proteins: 899 ncRNAs were highly upregulated in HCC patients. Among them, 337 genes were fragmented long noncoding RNAs, 252 genes were small nucleolar RNAs, and 134 genes were piwi-interacting RNAs. Forty-eight candidates were selected and validated with RT-qPCR, of which, 16 ncRNAs were verified to be significantly upregulated in HCC, including RN7SL1, SNHG1, ZFAS1, and LINC01359. Particularly, the abundance of RN7SL1 S fragment discriminated HCC samples from negative controls (area under the curve, 0.87; 95% CI, 0.817–0.920). HCC patients with higher concentrations of RN7SL1 S fragment had lower survival rates. Furthermore, RN7SL1 S fragment alone promoted cancer cell proliferation and clonogenic growth. CONCLUSIONS Our results show that various ncRNA species, not only miRNAs, identified in the small RNA sequencing of plasma are also able to serve as noninvasive biomarkers. Particularly, we identified a domain of srpRNA RN7SL1 with reliable clinical performance for HCC diagnosis and prognosis.

scholarly journals COT-04 Circulating biomarker for glioblastoma and primary central nervous system lymphoma -Next Generation Sequencing of small noncoding RNA-

2020 ◽  
Vol 2 (Supplement_3) ◽  
pp. ii21-ii21
Author(s):  
Shumpei Onishi ◽  
Fumiyuki Yamasaki ◽  
Motoki Takano ◽  
Ushio Yonezawa ◽  
Kazuhiko Sugiyama ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Noncoding Rna ◽  
Central Nervous System Lymphoma ◽  
Serum Samples ◽  
Small Noncoding Rna ◽  
Non Invasive ◽  
Diagnostic Models ◽  
Healthy Control ◽  
Generation Sequencing

Abstract Objective: Glioblastoma (GBM) and Primary Central Nervous System Lymphoma (PCNSL) are common intracranial malignant tumors. They sometimes present similar radiological findings and diagnoses could be difficult without surgical biopsy. For improving the current management, development of non-invasive biomarkers are desired. In this study, we explored the differently expressed circulating small noncoding RNA (sncRNA) in serum for specific diagnostic tool of GBM and PCNSL. Material & Methods: Serum samples were obtained from three groups: 1) GBM patients (N=26), 2) PCNSL patients (N=14) 3) healthy control (N=114). The total small RNAs were extracted from serum. The whole expression profiles of serum sncRNAs were measured using Next-Generation Sequencing System. We analyzed serum levels of sncRNAs (15–55 nt) in each serum samples. The difference of sncRNAs expression profile among three groups were compared. Data analysis was performed by logistic regression analysis followed by leave-one-out cross-validation (LOOCV). The accuracy of diagnostic models of sncRNAs combination were evaluated by receiver operating characteristic (ROC) analysis. Results: We created the combination models using three sncRNA in each models based on the logistic regression analysis. The model 1 (based on sncRNA-X1, X2 and X3) enabled to differentiate GBM patients form healthy control with a sensitivity of 92.3% and a specificity of 99.2% (AUC: 0.993). The model 2 (based on sncRNA-Y1, Y2 and Y3) enabled to differentiate PCNSL patients form healthy control with a sensitivity of 100% and a specificity of 93.9% (AUC: 0.984). The model 3 (based on sncRNA-Z1, Z2 and Z3) enabled to differentiate GBM patients form PCNSL patients with a sensitivity of 92.3% and a specificity of 78.6% (AUC: 0.920). Conclusion: We found three diagnostic models of serum sncRNAs as non-invasive biomarkers potentially useful for detection of GBM and PCNSL from healthy control, and for differentiation GBM from PCNSL.

scholarly journals Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bohan Liu ◽  
Pan Liu ◽  
Lutao Dai ◽  
Yanlin Yang ◽  
Peng Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Area Under The Curve ◽  
Independent Set ◽  
Reference Method ◽  
Ct Images ◽  
Loss Of Life ◽  
Case Identification ◽  
Reverse Transcription Pcr ◽  
Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

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