MiRNA sequencing of serum exosomes from hepatocellular carcinoma and liver cirrhosis patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE104251 | GEO | 2018/10/01
REPOSITORIES: GEO
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Project description:Background: The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC). We sought to develop a non-invasive diagnostic approach using circulating cell-free DNA (cfDNA) for the early detection of HCC. Methods: Applying the 5hmC-Seal technique, we obtained genome-wide 5-hydroxymethylcytosines (5hmC) in cfDNA samples from 2,554 Chinese subjects: 1,204 HCC patients, 392 patients with chronic hepatitis B virus infection (CHB) or liver cirrhosis (LC), and 958 healthy individuals and patients with benign liver lesions. A diagnostic model for early HCC was developed through case-control analyses using the elastic net regularization for feature selection. Results: The 5hmC-Seal data from HCC patients showed a genome-wide distribution enriched with liver-derived enhancer marks. We developed a 32-gene diagnostic model that accurately distinguished early HCC (stage 0/A) based on the Barcelona Clinic Liver Cancer (BCLC) staging system from non-HCC (validation set: AUC = 88.4%; 95% CI, 85.8-91.1%), showing superior performance over α-fetoprotein (AFP). Besides detecting patients with early stage or small tumors (e.g., ≤ 2.0 cm) from non-HCC, the 5hmC model showed high capacity for distinguishing early HCC from high risk subjects with CHB or LC history (validation set: AUC = 84.6%; 95% CI, 80.6-88.7%), also significantly outperforming AFP. Furthermore, the 5hmC diagnostic model appeared to be independent from potential confounders (e.g., smoking/alcohol intake history). Conclusions: We have developed and validated a non-invasive approach with clinical application potential for the early detection of HCC that are still surgically resectable in high risk individuals.
2019-08-07 | GSE112679 | GEO
Project description:Background & Aims: MicroRNAs have been shown to offer great potential in the diagnosis of cancer. We aimed to identify microRNAs in peripheral blood mononuclear cells (PBMCs) for diagnosing pancreatic cancer (PC). Methods: PBMCs microRNA expression was investigated in three independent cohorts including 352 participants (healthy, benign pancreatic/peripancreatic diseases (BPD), and PC). First, we used sequencing technology to identify differentially expressed microRNAs in 60 PBMCs samples for diagnosing PC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using an independent cohort. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: We found that PBMCs miR-27a-3p could efficiently discriminate PC from BPD (AUC=0.840; 95% CI, 0.787 to 0.885; sensitivity=82.2%, specificity=76.7%). A panel composed of PBMCs miR-27a-3p and serum CA19-9 provided a high diagnostic accuracy in differentiating PC from BPD in the clinical setting (AUC=0.886; 95% CI, 0.837 to 0.923; sensitivity=85.3%, specificity=81.6%). The satisfactory diagnostic performance of the panel persisted regardless of disease status (AUCs for tumour-node-metastasis stages?,?, and ? were 0.881, 0.884, and 0.893, respectively). Conclusion: PBMCs miR-27a-3p could be a potential marker for PC screening. A panel composed of PBMCs miR-27a-3p and serum CA19-9 has considerable clinical value in diagnosing early-stage PC. Therefore, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy. Examination of different MicroRNA profiles in 3 types of PBMCs samples
2012-05-03 | E-GEOD-37710 | biostudies-arrayexpress
Project description:Background & Aims: MicroRNAs have been shown to offer great potential in the diagnosis of cancer. We aimed to identify microRNAs in peripheral blood mononuclear cells (PBMCs) for diagnosing pancreatic cancer (PC). Methods: PBMCs microRNA expression was investigated in three independent cohorts including 352 participants (healthy, benign pancreatic/peripancreatic diseases (BPD), and PC). First, we used sequencing technology to identify differentially expressed microRNAs in 60 PBMCs samples for diagnosing PC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using an independent cohort. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: We found that PBMCs miR-27a-3p could efficiently discriminate PC from BPD (AUC=0.840; 95% CI, 0.787 to 0.885; sensitivity=82.2%, specificity=76.7%). A panel composed of PBMCs miR-27a-3p and serum CA19-9 provided a high diagnostic accuracy in differentiating PC from BPD in the clinical setting (AUC=0.886; 95% CI, 0.837 to 0.923; sensitivity=85.3%, specificity=81.6%). The satisfactory diagnostic performance of the panel persisted regardless of disease status (AUCs for tumour-node-metastasis stagesⅠ,Ⅱ, and Ⅲ were 0.881, 0.884, and 0.893, respectively). Conclusion: PBMCs miR-27a-3p could be a potential marker for PC screening. A panel composed of PBMCs miR-27a-3p and serum CA19-9 has considerable clinical value in diagnosing early-stage PC. Therefore, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.
2012-05-04 | GSE37710 | GEO
Project description:Background: The identification of new high sensitivity and specificity markers for HCC are essential. We aimed to identify serum microRNAs for diagnosing hepatitis B virus (HBV) â??related HCC. Methods: Serum microRNA expression was investigated with four cohorts including 667 participants (261 HCC patients ,233 cirrhosi patients and 173 healthy controls), recruited between August 2010 and June 2013. First, An initial screening of miRNA expression by Illumina sequencing was performed using serum samples pooled from HCC patients and controls,respectively. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n=357) and then validated using a cohort(n=241). The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: , We identified 8 miRNAs(hsa-miR-206, hsa-miR-141-3p, hsa-miR-433-3p, hsa-miR-1228-5p, hsa-miR-199a-5p, hsa-miR-122-5p, hsa-miR-192-5p and hsa-miR-26a-5p.) formed a miRNA panel that provided a high diagnostic accuracy of HCC (AUC=0.887 and 0.879 for training and validation data set, respectively). The microRNA panel can also differentiate HCC from healthy (AUC =0.894) and cirrhosis (AUC = 0.892), respectively. Conclusions:We found a serum microRNAs panel that has considerable clinical value in diagnosing HCC. 9 serum samples pooled from 3 healthy control donors and 3 HCC patients, 3 cirrhosi patients treated at The First Affiliated Hospital of Soochow University were subjected to Illumina HiSeq 2000 deep sequencing to identify the miRNAs that were significantly differentially expressed.
2015-12-20 | E-GEOD-59418 | biostudies-arrayexpress
Project description:Background: The identification of new high sensitivity and specificity markers for HCC are essential. We aimed to identify serum microRNAs for diagnosing hepatitis B virus (HBV) –related HCC. Methods: Serum microRNA expression was investigated with four cohorts including 667 participants (261 HCC patients ,233 cirrhosi patients and 173 healthy controls), recruited between August 2010 and June 2013. First, An initial screening of miRNA expression by Illumina sequencing was performed using serum samples pooled from HCC patients and controls,respectively. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n=357) and then validated using a cohort(n=241). The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: , We identified 8 miRNAs(hsa-miR-206, hsa-miR-141-3p, hsa-miR-433-3p, hsa-miR-1228-5p, hsa-miR-199a-5p, hsa-miR-122-5p, hsa-miR-192-5p and hsa-miR-26a-5p.) formed a miRNA panel that provided a high diagnostic accuracy of HCC (AUC=0.887 and 0.879 for training and validation data set, respectively). The microRNA panel can also differentiate HCC from healthy (AUC =0.894) and cirrhosis (AUC = 0.892), respectively. Conclusions:We found a serum microRNAs panel that has considerable clinical value in diagnosing HCC.
2015-12-20 | GSE59418 | GEO
Project description:Background: In patients with left heart failure, microRNAs (miRNAs) have been shown to be of diagnostic and prognostic value. The present study aims to identify miRNAs in patients with univentricular heart (UVH) disease that may be predictive of overt heart failure. Methods: A large panel of human miRNA arrays were used to determine miRNA expression profiles in the blood of 48 UVH patients and 32 age and gender-matched healthy controls. For further selection, the most abundantly expressed miRNA arrays were related to clinical measures of heart failure and selected miRNAs validated by Reverse transcription quantitative polymerase chain reaction (RT-qPCR). These validated miRNAs were used for the prediction of overt heart failure and all-cause mortality. Results: According to microarray analysis, 50 miRNAs were found to be significantly abundant in UVH patients of which miR-150-5p was best related to heart failure parameters. According to ROC analysis, NT-proBNP levels (AUC 0.940, 95% CI 0.873-1.000; p=0.001), miR-150-5p expression levels (AUC 0.905, 95% CI 0.779-1.000; p=0.001) and a higher NYHA class ≥ III (AUC 0.893, 95% CI 0.713-1.000; p=0.002) were the 3 most significant predictors of overt heart failure. Using a combined biomarker model, AUC increased to 0.980 indicating an additive value of miR-150-5p. Moreover, in the multivariate analysis, a higher NYHA class ≥ III (p=0.005) and miR-150-5p (p=0.006) turned out to be independent predictors of overt heart failure. Conclusion: In patients with UVH, miR-150-5p has additive value to natriuretic peptides for the prediction of overt heart failure and thus may be used as additional biomarker for risk assessment in these patients.
2019-10-17 | GSE136547 | GEO
Project description:Liver transplantation is the only lifesaving therapy for patients with irreversible liver failure, and 30% of the recipients experience acute rejection in the first 12 months following transplantation. Acute rejection is diagnosed by core needle biopsy and noninvasive methods for predicting acute rejection could improve clinical care. MicroRNAs (miRNAs) are emerging as biomarkers of clinically significant events. We investigated whether circulating extracellular miRNA profiles in sera matched to liver allograft biopsies predict human liver allograft status. Small RNA sequencing and TaqMan low-density array analysis of RNA from biopsy matched sera identified that liver specific miR-122, and miRs -885, -210, -194, 193b, -192, -148a, -34a and -22 distinguish patients with acute rejection biopsies from those with biopsies without rejection features (false discovery rate of <0.15). We measured absolute levels of these informative 9 miRNAs using quantitative real-time PCR assays. Receiver-operating-characteristic (ROC) curve analysis of circulating levels of miRNA levels validated that all 9 miRNAs discriminate patients with acute rejection in their biopsies from those without rejection in their biopsies (P <0.01 to P<0.0001). A parsimonious diagnostic signature of miR-122 and miR-194 was diagnostic of acute rejection with a sensitivity of 79% (95% confidence interval [CI], 49% to 95%) and a specificity of 88% (95% CI, 64% to 99%) (area under the curve, 0.91; 95% CI, 0.81 to 1.00; P<0.001 by ROC curve analysis). Our findings suggest that a molecular signature of miR-122 and miR-194 in serum offers a noninvasive means of diagnosing acute rejection including mild forms in human liver allografts.
2019-06-30 | GSE69579 | GEO
Project description:The aim of the presented study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC), and to investigate miRNA profiles in regard to clinicopathological characteristics of the tumors. Results: qPCR validation revealed regulation of 14 miRNAs in EEC tissues (miR-9, miR-141,miR-205,miR-203,miR-183,miR-200a*,miR-200b*,miR-200a,miR-200c,miR-429,miR-200b,miR-410,miR-92a,miR-1305) and 9 in plasma samples (miR-449a,miR-1290,miR-1228,miR-203,miR-200a,miR-141,miR-92a, miR-9, miR-301b). Expression of certain miRNAs showed association with FIGO stage, grade and relapse. Two miRNA signatures, miR-205/miR-410 and miR-410/miR-429/miR-92a, classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC 0.972, 95% CI 0.919-0.995 and 0.991, 95% CI 0.948-1.000, resepctively). miRNA signature composed of miR-205 and miR-200a predicted relapse with AUC of 0.854 (95% CI 0.691-0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR-1228/miR-200c/miR-429, HR 2.98) and progression-free survival (miR-1228/miR-429, HR 4.149). Plasma miRNA signatures classified EEC plasma samples with high accuracy. Conclusions: We conclude that miRNA signatures hold great promise for becoming non-invasive biomarkers for early EEC detection and prognosis.
2012-06-01 | GSE35794 | GEO
Project description:In cancer management, early and accurate diagnosis of hepatocellular carcinoma (HCC) is important for enhancing survival rate of patients. Currently, serum alpha-fetoprotein (AFP) is the only one biomarker for detection of HCC. However, serum AFP is not satisfactory for diagnosis of HCC due to its low accuracy (about 60-70%). In this study, we collected 109 serum samples (discovery set) from healthy control (HC) and patients with chronic hepatitis B (CHB), liver cirrhosis (LC) and HCC, and analyzed them with custom lncRNA microarray. Profiling analysis shows 181 differentially expressed lncRNAs between HCs and patients with CHB, LC and HCC. Then a 48-lncRNA diagnostic signature was identified with 100% predictive accuracy for all subjects in the discovery set. This diagnostic signature was verified with a cross-validation analysis in the discovery set. To further corroborate the signature, we gathered another 66 serum samples (validation set) and also analyzed them with microarray. The result indicates that the same signature has similar diagnostic accuracy for HC (100%), CHB (73%), LC (88%) and HCC (95%), implying a reproducible diagnostic biomarker for HCC. Receiver operating characteristic (ROC) analysis exhibits that this signature has significantly higher diagnostic accuracy for HCC and non-cancerous subjects (area under curve [AUC]: 0.994) than AFP (AUC: 0.773) in the discovery set and this was also verified in the validation set (0.964 vs 0.792). More importantly, the signature detected small HCC (<3cm) with 100% (13/13) accuracy while AFP with only 61.5% (8/13). Altogether, this study demonstrates that the serum 48-lncRNA signature is not only a powerful and sensitive biomarker for diagnosis of HCC but also a potential biomarker for LC. ***************************************************************** Submitter declares these data are subject to patent number ZL 2016 1 0397094. *****************************************************************
2022-10-15 | GSE78160 | GEO
Project description:The aim of the presented study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC), and to investigate miRNA profiles in regard to clinicopathological characteristics of the tumors. Results: qPCR validation revealed regulation of 14 miRNAs in EEC tissues (miR-9, miR-141,miR-205,miR-203,miR-183,miR-200a*,miR-200b*,miR-200a,miR-200c,miR-429,miR-200b,miR-410,miR-92a,miR-1305) and 9 in plasma samples (miR-449a,miR-1290,miR-1228,miR-203,miR-200a,miR-141,miR-92a, miR-9, miR-301b). Expression of certain miRNAs showed association with FIGO stage, grade and relapse. Two miRNA signatures, miR-205/miR-410 and miR-410/miR-429/miR-92a, classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC 0.972, 95% CI 0.919-0.995 and 0.991, 95% CI 0.948-1.000, resepctively). miRNA signature composed of miR-205 and miR-200a predicted relapse with AUC of 0.854 (95% CI 0.691-0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR-1228/miR-200c/miR-429, HR 2.98) and progression-free survival (miR-1228/miR-429, HR 4.149). Plasma miRNA signatures classified EEC plasma samples with high accuracy. Conclusions: We conclude that miRNA signatures hold great promise for becoming non-invasive biomarkers for early EEC detection and prognosis. Tissue samples were collected from 122 women (77 EEC and 45 controls). Expression profiling of 866 human miRNAs and 89 human viral miRNAs was performed in 24 samples and was followed by qPCR validation in 104 patients. Of 24 samples analyzed by microarrays, 22 (18 EEC, 4 normal controls) were available for final analysis. Expression of 14 miRNAs was analysed in 48 plasma samples by qPCR.
2012-05-31 | E-GEOD-35794 | biostudies-arrayexpress