Elucidating the Role of Serum tRF-31-U5YKFN8DYDZDD as a Novel Diagnostic Biomarker in Gastric Cancer (GC)

BackgroundGastric cancer (GC) is one of the malignant tumors with the highest morbidity and mortality in the world. Early diagnosis combined with surgical treatment can significantly improve the prognosis of patients. Therefore, it is urgent to seek higher sensitivity and specificity biomarkers in GC. tRNA-derived small RNAs are a new non-coding small RNA that widely exists in tumor cells and body fluids. In this study, we explore the expression and biological significance of tRNA-derived small RNAs in GC.Materials and MethodsFirst of all, we screened the differentially expressed tRNA-derived small RNAs in tumor tissues by high-throughput sequencing. Agarose gel electrophoresis (AGE), Sanger sequencing, and Nuclear and Cytoplasmic RNA Separation Assay were used to screen tRF-31-U5YKFN8DYDZDD as a potential tumor biomarker for the diagnosis of GC. Then, we detected the different expressions of tRF-31-U5YKFN8DYDZDD in 24 pairs of GC and paracancerous tissues, the serum of 111 GC patients at first diagnosis, 89 normal subjects, 48 superficial gastritis patients, and 28 postoperative GC patients by quantitative real-time PCR (qRT-PCR). Finally, we used the receiver operating characteristic (ROC) curve to analyze its diagnostic efficacy.ResultsThe expression of tRF-31-U5YKFN8DYDZDD has good stability and easy detection. tRF-31-U5YKFN8DYDZDD was highly expressed in tumor tissue, serum, and cell lines of GC, and the expression was significantly related to TNM stage, depth of tumor invasion, lymph node metastasis, and vascular invasion. The expression of serum tRF-31-U5YKFN8DYDZDD in the GC patients decreased after the operation (P = 0.0003). Combined with ROC curve analysis, tRF-31-U5YKFN8DYDZDD has better detection efficiency than conventional markers.ConclusionsThe expressions of tRF-31-U5YKFN8DYDZDD in the tumor and paracancerous tissues, the serum of GC patients and healthy people, and the serum of GC patients before and after operation were different. tRF-31-U5YKFN8DYDZDD is not only a diagnostic biomarker of GC but also a predictor of poor prognosis.

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A Novel Ferroptosis-Related Long Non-coding RNA Prognostic Risk Model for Gastric Cancer

10.21203/rs.3.rs-718468/v1 ◽

2021 ◽

Author(s):

Shenglan Huang ◽

Dan Li ◽

Lingling Zhuang ◽

Liying Sun ◽

Jianbing Wu

Keyword(s):

Gastric Cancer ◽

Risk Score ◽

Roc Curve ◽

Cox Regression ◽

Risk Group ◽

Clinical Stage ◽

Curve Analysis ◽

Clinicopathological Features ◽

Roc Curve Analysis ◽

Kaplan Meier

Abstract Background：Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is a novel and distinct type of non-apoptotic cell death that is closely associated with metabolism, redox biology, and tumor prognosis. Recently, ferroptosis-related long non-coding RNAs (lncRNAs) have received increasing attention in predicting cancer prognosis. Thus, we aimed to construct an ferroptosis-related lncRNAs signature for predicting the prognosis of patients with gastric cancer.Methods：We built an ferroptosis-related lncRNA risk signature by using Cox regression based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. Cox regression was performed to explore whether the signature could be used as an independent factor. A nomogram was built involving the risk score and clinicopathological features. Furthermore, we explored the biological functions and immune states in two groups.Results：Eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in gastric cancer. Kaplan–Meier curve analysis revealed that patients in the high-risk group had worse survival than those in the low-risk group. The survival outcome was also appropriate for subgroup analysis, including age, sex, grade, and clinical stage. Multivariate Cox regression analysis and receiver operating characteristic (ROC) curve analysis demonstrated that the risk score was an independent prognostic factor and superior to traditional clinicopathological features in predicting GC prognosis. Next, we established a nomogram according to clinical parameters (age, sex, grade, and clinical stage) and risk score. All the verified results, including ROC curve analysis, calibration curve, and decision curve analysis, demonstrated that the nomogram could accurately predict the survival of patients with gastric cancer. Gene set enrichment analysis revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation.Conclusion: We established a novel ferroptosis-related prognostic risk signature including eight lncRNAs and constructed a nomogram to predict the prognosis of gastric cancer patients, which may improve prognostic predictive accuracy and guide individualized treatment for patients with GC.

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Serum hsa_tsr016141 as a Kind of tRNA-Derived Fragments Is a Novel Biomarker in Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.679366 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xinliang Gu ◽

Shuo Ma ◽

Bo Liang ◽

Shaoqing Ju

Keyword(s):

Gastric Cancer ◽

Sensitivity And Specificity ◽

Small Rnas ◽

Malignant Tumors ◽

Tumor Grade ◽

Expression Level ◽

Dynamic Monitoring ◽

Molecular Characteristics ◽

Diagnostic Efficiency ◽

Healthy Donors

BackgroundGastric cancer (GC) is one of the most common malignant tumors globally and the third leading cause of cancer-related death. Currently, the sensitivity and specificity of diagnostic markers for GC are low, so it is urgent to find new biomarkers with higher sensitivity and specificity. tRNA-derived small RNAs are a kind of small non-coding RNAs derived from tRNAs. It is abundant in cancer cells and body fluids. Our goal is to find the differentially expressed tRNA-derived small RNAs in GC to explore their potential as a GC biomarker.MethodsQuantitative real-time PCR was used to detect the expression level of hsa_tsr016141. The molecular characteristics of hsa_tsr016141 were verified by agarose gel electrophoresis, Sanger sequencing, Actinomycin D Assay, and Nuclear and Cytoplasmic RNA Separation Assay. The diagnostic efficiency of hsa_tsr016141 was analyzed through receiver operating characteristic.ResultsThe expression level of hsa_tsr016141 in GC tissues and serum was significantly increased. The serum expression level showed a gradient change between GC patients, gastritis patients, and healthy donors and was positively correlated with the degree of lymph node metastasis and tumor grade. ROC analysis showed that the serum expression level of hsa_tsr016141 could significantly distinguish GC patients from healthy donors or gastritis patients. Besides, the expression level of hsa_tsr016141 in GC patients decreased significantly after the operation (P<0.0001).ConclusionsSerum hsa_tsr016141 has good stability and specificity and can be used for dynamic monitoring of GC patients, suggesting that serum hsa_tsr016141 can be a novel biomarker for GC diagnosis and postoperative monitoring.

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Construction on of a Ferroptosis-Related lncRNA-Based Model to Improve the Prognostic Evaluation of Gastric Cancer Patients Based on Bioinformatics

Frontiers in Genetics ◽

10.3389/fgene.2021.739470 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiahui Pan ◽

Xinyue Zhang ◽

Xuedong Fang ◽

Zhuoyuan Xin

Keyword(s):

Gastric Cancer ◽

Cancer Patients ◽

Roc Curve ◽

Cox Regression ◽

Risk Group ◽

Survival Curve ◽

Curve Analysis ◽

Roc Curve Analysis ◽

Cox Regression Analysis ◽

Gastric Cancer Patients

BackgroundGastric cancer is one of the most serious gastrointestinal malignancies with bad prognosis. Ferroptosis is an iron-dependent form of programmed cell death, which may affect the prognosis of gastric cancer patients. Long non-coding RNAs (lncRNAs) can affect the prognosis of cancer through regulating the ferroptosis process, which could be potential overall survival (OS) prediction factors for gastric cancer.MethodsFerroptosis-related lncRNA expression profiles and the clinicopathological and OS information were collected from The Cancer Genome Atlas (TCGA) and the FerrDb database. The differentially expressed ferroptosis-related lncRNAs were screened with the DESeq2 method. Through co-expression analysis and functional annotation, we then identified the associations between ferroptosis-related lncRNAs and the OS rates for gastric cancer patients. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 17 ferroptosis-related lncRNAs. We also evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA).ResultsA ferroptosis-related “lncRNA–mRNA” co-expression network was constructed. Functional annotation revealed that the FOXO and HIF-1 signaling pathways were dysregulated, which might control the prognosis of gastric cancer patients. Then, a ferroptosis-related gastric cancer prognostic signature model including 17 lncRNAs was constructed. Based on the RiskScore calculated using this model, the patients were divided into a High-Risk group and a low-risk group. The K-M survival curve analysis revealed that the higher the RiskScore, the worse is the obtained prognosis. The ROC curve analysis showed that the area under the ROC curve (AUC) of our model is 0.751, which was better than those of other published models. The multivariate Cox regression analysis results showed that the lncRNA signature is an independent risk factor for the OS rates. Finally, using nomogram and DCA, we also observed a preferable clinical practicality potential for prognosis prediction of gastric cancer patients.ConclusionOur prognostic signature model based on 17 ferroptosis-related lncRNAs may improve the overall survival prediction in gastric cancer.

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Identification of MCM4 as a Prognostic Marker of Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2021/7479326 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Huandi Zhou ◽

Le Jiang ◽

Guohui Wang ◽

Linlin Su ◽

Liubing Hou ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Real Time ◽

Roc Curve ◽

Real Time Pcr ◽

Malignant Tumors ◽

Nodal Metastasis ◽

Cellular Heterogeneity ◽

Survival Prediction ◽

Roc Curve Analysis ◽

Potential Biomarker

Object. Hepatocellular carcinoma is one of the most common malignant tumors worldwide owing to its complicated molecular and cellular heterogeneity and its high incidence rate every year. It is an urgent need to search for new efficient molecular markers of HCC to reduce mortality and improve HCC prognosis. In this article, MCM4, a member of a family of proteins closely related to DNA replication and cell proliferation, was selected as a potential biomarker of HCC prognosis. Methods. MCM4 expression difference in HCC were analyzed from TCGA and GEO data and verified by real-time PCR and western blot. ROC curve was used to analyze the diagnostic value of MCM4 and AFP. Additionally, the relationship between MCM4 and stage or nodal metastasis status or grade or age in TCGA cohort with HCC was observed from the UALCAN website. The univariate and multivariate Cox and functional analyses were done to explore the prognostic value of MCM4 in TCGA cohort. Results. It was found that MCM4 was significantly highly expressed in HCC tissues from TCGA, GEO, and experimental data. Furthermore, ROC curve analysis showed that MCM4 was superior to be a diagnostic biomarker than AFP from TCGA ( AU C MCM 4 = 0.9461 , AU C AFP = 0.7056 ) and GEO (GSE19665: AU C MCM 4 = 0.8800 , AU C AFP = 0.5100 ; GSE64041 AU C MCM 4 = 0.8038 , AU C AFP = 0.6304 ). AUC of MCM4 from real-time PCR result in 60 pairs of HCC and adjacent tissues was 0.7172, demonstrating the prediction value of MCM4. Besides, different expression tendencies of MCM4 among different stages or nodal metastasis status or grade or age were observed from the UALCAN website. In addition, multiROC analysis showed the advantage of MCM4 as a survival prediction at 1, 3, and 5 years with the higher AUC at 0.69 of 1 year, 0.65 of 3 years, and 0.61 of 5 years. It was shown that MCM4 was independently associated with OS in univariate and multivariate Cox analysis. And GSEA displayed that MCM4 was highly enriched in KEGG_CELL_CYCLE signaling pathway following higher correlation positively with CDC6, PLK1, CRC1, and BUB1B in HCC. Conclusion. MCM4 might be a potential biomarker in guiding the prognostic status of HCC patients.

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Circulating serum exosomal miR-92a-3p as a novel biomarker for early diagnosis of gastric cancer

Future Oncology ◽

10.2217/fon-2020-0792 ◽

2021 ◽

Vol 17 (8) ◽

pp. 907-919

Author(s):

Xu Lu ◽

Jianxin Lu ◽

Siqi Wang ◽

Yu Zhang ◽

Ye Ding ◽

...

Keyword(s):

Gastric Cancer ◽

Early Diagnosis ◽

Malignant Tumors ◽

Area Under The Curve ◽

Tumor Biomarker ◽

Diagnostic Efficiency ◽

Node Metastasis ◽

Tumor Node Metastasis Stage ◽

Combined Detection ◽

Serum Exosomes

Gastric cancer (GC) is one of the common malignant tumors with high mortality. The abundance of miRNAs in serum exosomes has proved to have a high application value as a new noninvasive diagnostic method. The purpose of this study was to investigate whether serum exosomal miR-92a-3p could be used as a new biomarker for early diagnosis of GC and evaluate its clinical application value by detecting the expression of serum exosomal miR-92a-3p in 131 patients with primary GC and 122 healthy controls by real-time quantitative (qRT)-PCR. The results showed that the expression level of serum exosomal miR-92a-3p in GC patients was significantly lower than that in normal controls (p < 0.0001). In addition, the level was closely correlated with lymph node metastasis and tumor node metastasis stage of GC patients. The area under the curve for serum exosomal miR-92a-3p was 0.829, significantly higher than for other indicators. Furthermore, combined detection of serum exosomal miR-92a-3p, CEA and CA19-9 was more sensitive than any of the three alone or any pair. These results showed that serum exosomal miR-92a-3p could be used as a novel new tumor biomarker to improve diagnostic efficiency in GC.

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Increased miR-25 expression in serum of gastric cancer patients is correlated with CA19-9 and acts as a potential diagnostic biomarker

Open Medicine ◽

10.1515/med-2017-0040 ◽

2017 ◽

Vol 12 (1) ◽

pp. 266-270

Author(s):

Qin Le ◽

Niu Jianhua ◽

Xi Yu ◽

He Jiageng ◽

Keyword(s):

Gastric Cancer ◽

Sensitivity And Specificity ◽

Roc Curve ◽

Diagnostic Sensitivity ◽

Enzyme Linked Immunosorbent Assay ◽

Healthy Controls ◽

Diagnostic Biomarker ◽

Relative Expression ◽

Potential Biomarker ◽

Diagnostic Sensitivity And Specificity

AbstractObjectiveTo evaluate miR-25 expression in serum of gastric cancer (GC) patients and whether it can be a potential biomarker for GC diagnosis.MethodsForty one pathology confirmed GC patients and 41 healthy controls were included in this study. 10 mL peripheral venous blood were collected from GC patients and healthy controls. miR-25 relative expression and CA19-9 level in serum of GC patients and healthy controls were measured by real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) and enzyme linked immunosorbent assay (ELISA), respectively. The diagnostic sensitivity, specificity and receiver operating characteristic (ROC) curve of serum miR-25 and CA19-9 were calculated by STATA11.0 software.ResultsThe relative expression of miR-25 was 0.47±0.53 and 0.05±0.36 in serum of GC patients and healthy controls respectively with significant statistical difference (P<0.05). The serum level of CA19-9 for GC patients and healthy controls were 11.91±6.17 U/mL and 7.40±3.97 U/mL, indicating GC patients were much higher than those of healthy controls (P<0.05). The diagnostic sensitivity and specificity were 78.05% and 60.98% with the cut-off value of 0.32 for serum miR-25. Under this cut-off value, the area under the ROC curve was 0.75. For serum CA19-9, the diagnostic sensitivity and specificity were 70.73% and 56.10% with the cut-off value of 9.22 U/mL. Under this cut-off value, the area under the ROC curve was 0.73 with the 95% confidence interval of 0.62-0.84. Positive correlation was found between serum miR-25 relative expression and CA19-9 concentration of GC patients (r=0.75, P<0.05).ConclusionAccording to our present study, serum miR-25 was elevated in GC patients which may serve as a diagnostic biomarker for GC.

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Utility of Alpha-Fetoprotein-L3 and Golgi Protein 73 for Diagnosis of Hepatocellular Carcinoma

10.51429/ejmm29402 ◽

2020 ◽

Vol EJMM29 (4) ◽

pp. 9-15

Author(s):

Rania A. El-Kady ◽

Mohammed M. El-Naggar ◽

ehab A. Abd El-Shakour ◽

Monir H. Bahgat

Keyword(s):

Hepatocellular Carcinoma ◽

Roc Curve ◽

Malignant Tumors ◽

Curve Analysis ◽

Alpha Fetoprotein ◽

Enzyme Linked Immunosorbent Assay ◽

Roc Curve Analysis ◽

Median Serum ◽

Significant Difference ◽

Golgi Protein

Background: Hepatocellular carcinoma (HCC) is amongst the most common malignant tumors that carries a poor prognosis. Clinically, alpha-fetoprotein (AFP) is the most extensively used serum biomarker for diagnosing HCC. Objectives: The current study was conducted to explore the diagnostic value of serum levels of alpha-fetoprotein-L3 (AFP-L3) and Golgi protein 73 (GP73) regarding HCC, and to determine the diagnostic accuracy of these biomarkers when used individually as well as in combination with AFP. Methodology: Blood samples were collected from 50 patients with HCV-related cirrhosis (25 subjects with HCC and 25 without HCC) recruited from the outpatient clinics of the Specialized Internal Medicine Hospital, Mansoura University, Egypt. Serum concentrations of AFP-L3 and GP73 were evaluated using enzyme-linked immunosorbent assay (ELISA). Diagnostic performance of AFP-L3 and GP73 was determined by receiver operating characteristic (ROC) curve analysis. Results: Overall, the median serum level of AFP-L3 was higher in the HCC group compared to the cirrhotic group (p=0.05). Moreover, a statistically-significant difference was observed between the median serum value of GP73 in HCC patients compared to those with cirrhosis (p < 0.001). The ROC curve analysis showed that the area under the ROC curve (AUROC) values for AFP, AFP-L3 and GP73 were 0.88, 0.67 and 0.83, respectively. Of the 3 biomarkers, GP73 demonstrated the highest sensitivity (88%). The AUROC for AFP and AFP-L3 combination was 0.85, whereas that for AFP and GP73 was 0.90. Conclusion: Our findings indicate that GP73 is more sensitive than AFP and AFP-L3 in diagnosing HCC. Furthermore, the combined determination of GP73 and AFP could improve the diagnostic ability of HCC.

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Evaluating the presence of deregulated tumoral onco-microRNAs in serum-derived exosomes of gastric cancer patients as noninvasive diagnostic biomarkers

Bioimpacts ◽

10.34172/bi.2021.22178 ◽

2021 ◽

Author(s):

Houman Kahroba ◽

Nasser Samadi ◽

Mostafa Mostafazadeh ◽

Mohamad Saied Hejazi ◽

Mohammad Reza Sadeghi ◽

...

Keyword(s):

Gastric Cancer ◽

Mirna Expression ◽

Roc Curve ◽

Mirna Expression Profile ◽

Curve Analysis ◽

Diagnostic Purpose ◽

Roc Curve Analysis ◽

Diagnostic Biomarkers ◽

Diagnostic Potential ◽

Serum Exosomes

Introduction: Exosomal microRNAs (miRNAs) are emerging diagnostic biomarkers for different types of cancers. We aim to detect gastric cancer (GC)-specific miRNAs in serum exosomes with diagnostic potential. Methods: A pair of 43 tumor and tumor-adjacent tissue biopsies obtained from GC patients, also 5 mL peripheral blood (following 12h fasting) were collected from the same patients and healthy controls (HCs). QIAGEN miRCURY LNA miRNA Focus PCR Panel applied to screen differentially expressed onco-miRNAs. The candidate miRNAs with the highest fold changes proceeded for validation by qRT-PCR in individuals. Results: We identified that exosomal miR-10a-5p, miR-19b-3p, miR-215-5p, and miR-18a-5p were significantly upregulated in GC patient’s exosomes in contrast to HCs exosomes, Roc curve analysis indicated area under the ROC curve (AUC) of 0.801, 0.721, 0.780 and 0.736 respectively. The Roc curve analysis for the combined signature of four exosomal miRNAs indicated AUC of 0.813. Also, Spearman's correlation coefficients indicated that the miRNA expression is highly correlated between tumor and exosome. Conclusion: Herein, we specifically identified four miRNAs in serum exosomes of GC patients for a diagnostic purpose which are directly associated with tumoral miRNA expression profile.

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Prognostic Impact of Preoperative Naples Prognostic Score in Gastric Cancer Patients Undergoing Surgery

Frontiers in Surgery ◽

10.3389/fsurg.2021.617744 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jianping Xiong ◽

Haitao Hu ◽

Wenzhe Kang ◽

Hao Liu ◽

Fuhai Ma ◽

...

Keyword(s):

Gastric Cancer ◽

Prognostic Factor ◽

Roc Curve ◽

Prognostic Value ◽

Total Cholesterol Level ◽

Prognostic Score ◽

Curve Analysis ◽

Independent Prognostic Factor ◽

Prognostic Impact ◽

Roc Curve Analysis

Background: The Naples prognostic score (NPS) is established according to nutritional or inflammatory state, which has been identified as a new prognostic score for various malignant tumors. However, its prognosis prediction effect on gastric cancer (GC) patients is still unknown so far. The present work aimed to examine the NPS function in the prediction of GC prognosis.Methods: In this study, patients undergoing surgery with no preoperative therapy were retrospectively examined from June 2011 to August 2019. Typically, the total cholesterol level, serum albumin content, neutrophil-to-lymphocyte ratio and lymphocyte-to-monocyte ratio were determined to calculate the NPS. Besides, the prognostic value of NPS was evaluated by survival analyses. Time-dependent receiver operating characteristic (t-ROC) curve analysis was also carried out to compare the prognostic value of the scoring systems.Results: Altogether 1,283 cases were enrolled into the present work. NPS was markedly related to age, gender, tumor size, body mass index, vascular invasion, perineural invasion, and pTNM stage. Upon multivariate analysis, NPS was identified as an independent prognostic factor for the prediction of overall survival (OS) (P < 0.001). In subgroup analyses stratified by adjuvant chemotherapy or surgery alone, NPS was still the independent prognostic factor for OS in both groups (both P < 0.001). Furthermore, NPS exhibited higher accuracy in the prediction of OS than additional prognostic factors, as revealed by the results of t-ROC curve analysis.Conclusions: NPS is a simple and useful scoring system that can be used to independently predict the survival of GC cases undergoing surgery.

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Circulating Exosomal miR-17-92 Cluster Serves as a Novel Non-Invasive Diagnostic Marker for Gastric Cancer Patients

10.21203/rs.3.rs-826985/v1 ◽

2021 ◽

Author(s):

Fei Liu ◽

Ye Han ◽

Dongbao Li ◽

Jun Zhou ◽

Jingjing Xu ◽

...

Keyword(s):

Gastric Cancer ◽

Malignant Tumors ◽

Quantitative Polymerase Chain Reaction ◽

Characteristic Curve ◽

Diagnostic Value ◽

Diagnostic Efficiency ◽

Roc Curve Analysis ◽

Non Invasive ◽

Clinical Diagnostic ◽

Potential Biomarker

Abstract Gastric cancer (GC) is one of the most common malignant tumors with a leading cause of cancer-related mortality worldwide. Exosomal miRNAs are considered as promising non-invasive biomarkers for the diagnosis of malignant tumors. In this study, we aimed to investigate the expression of exosomal miR-17-92 cluster and develop a potential biomarker for the diagnosis of GC. Exosomal RNAs were extracted and the expression profile of miR-17-92 cluster was detected using quantitative polymerase chain reaction (qRT-PCR). The ROC (receiver-operating characteristic) curve and AUC (area under the ROC curve) analysis were used to explore the diagnostic utility of miRNAs. Statistical was used to analyze the expression of serum exosomal miR-17-92 cluster with the clinical pathological parameters of GC patients. The results showed that the expressions of four members of the exosomal miR-17-92 cluster in the serum samples of GC patients were significantly upregulated compared with those of healthy controls. The AUC for serum exosomal miR-17, miR-18, miR-19a and miR-92 was 0.750 (95%CI=0.626-0.874, sensitivity=84.7%, specificity=70.0%), 0.736 (95%CI=0.590-0.881, sensitivity=88.9%, specificity=65.0%), 0.700 (95%CI=0.562-0.838, sensitivity=62.5%, specificity=80.0%), 0.689 (95%CI=0.567-0.811, sensitivity=45.8%, specificity=90.0%), respectively. The AUC for the newly combined panel consisting of miR-17, miR-18, miR-19a and miR-92 was 0.808 (95%CI=0.680-0.937), with sensitivity of 90.3% and specificity of 70.0%, which showed much higher clinical diagnostic value for GC than any of the four alone or any pair. Besides, the AUC for the newly developed panel consisting of the two traditional tumor biomarkers including CEA (carcinoembryonic antigen) and CA19-9 (carbohydrate antigen 19-9) and the four miR-17-92 cluster members was 0.881 (95%CI, 0.765-0.998) with sensitivity of 91.7% and specificity of 90.0%, which showed the greatest powerful clinical diagnostic value for GC. Moreover, the elevated exosomal miR-17-92 expressions were closely correlated with tumor size, tumor depth, lymph node metastasis, distant metastasis and TNM stage of GC patients. In conclusion, our findings revealed that circulating exosomal miR-17-92 cluster may be used as a novel potential non-invasive biomarker to improve the diagnostic efficiency in GC.

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