Blood Circulating miRNA Pairs as a Robust Signature for Early Detection of Esophageal Cancer.
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ABSTRACT:
SUBMITTER: Song Y
PROVIDER: S-EPMC8343071 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundIdentifying reliable biomarkers could effectively predict esophagus carcinoma (EC) patients with poor prognosis. In this work, we constructed an immune-related gene pairs (IRGP) signature to evaluate the prognosis of EC.ResultsThe IRGP signature was trained by the TCGA cohort and validated by three GEO datasets, respectively. Cox regression model together with LASSO was applied to construct the overall survival (OS) associated IRGP. 21 IRGPs consisting of 38 immune-related genes were included in our signature, according to which patients were stratified into high- and low-risk groups. The results of Kaplan-Meier survival analyses indicated that high-risk EC patients had worse OS than low-risk group in the training set, meta-validation set and all independent validation datasets. After adjustment in multivariate Cox analyses, our signature continued to be an independent prognostic factor of EC and the signature-based nomogram could effectively predict the prognosis of EC sufferers. Besides, Gene Ontology analysis revealed this signature is related to immunity. 'CIBERSORT' analysis revealed the infiltration levels of plasma cells and activated CD4 memory T cells in two risk groups were significantly different. Ultimately, we validated the expression levels of six selected genes from IRGP index in KYSE-150 and KYSE-450.ConclusionsThis IRGP signature could be applied to select EC patients with high mortality risk, thereby improving prospects for the treatment of EC.
| S-EPMC10332031 | biostudies-literature
Project description:The early detection of lung cancer continues to be a major clinical challenge. Using whole-transcriptome next-generation sequencing to analyze lung tumor and the matched noncancerous tissues, we previously identified 54 lung cancer-associated microRNAs (miRNAs). The objective of this study was to investigate whether the miRNAs could be used as plasma biomarkers for lung cancer. We determined expressions of the lung tumor-miRNAs in plasma of a development cohort of 180 subjects by using reverse transcription PCR to develop biomarkers. The development cohort included 92 lung cancer patients and 88 cancer-free smokers. We validated the biomarkers in a validation cohort of 64 individuals comprising 34 lung cancer patients and 30 cancer-free smokers. Of the 54 miRNAs, 30 displayed a significant different expression level in plasma of the lung cancer patients vs. cancer-free controls (all P < 0.05). A plasma miRNA signature (miRs-126, 145, 210, and 205-5p) with the best prediction was developed, producing 91.5% sensitivity and 96.2% specificity for lung cancer detection. Diagnostic performance of the plasma miRNA signature had no association with stage and histological type of lung tumor, and patients' age, sex, and ethnicity (all p > 0.05). The plasma miRNA signature was reproducibly confirmed in the validation cohort. The plasma miRNA signature may provide a blood-based assay for diagnosing lung cancer at the early stage, and thereby reduce the associated mortality and cost.
| S-EPMC5762367 | biostudies-literature
Project description:Bladder cancer is the 9th leading cause of cancer death worldwide. The major problem in bladder cancer is primarily the high recurrence rate after drug treatment and resection. Although conventional screening methods, such as cystoscopy, urinary cytology and ultrasound sonography, have become widely used in clinical settings, the diagnostic performance of these modalities is unsatisfactory due to low accuracy or high invasiveness. Because circulating micro RNA (miRNA) profiles have recently been reported as an attractive tool for liquid biopsy in cancer screening, here, we performed global miRNA profiling of 392 serum samples of bladder cancer patients with 100 non-cancer samples and 480 samples of other types of cancer as controls. We randomly classified the bladder cancer and control samples into 2 cohorts, a training set (N = 486) and a validation set (N = 486). By comparing both controls, we identified specific miRNA, such as miR-6087, for diagnosing bladder cancer in the training and validation sets. Furthermore, we found that a combination of 7 miRNA (7-miRNA panel: miR-6087, miR-6724-5p, miR-3960, miR-1343-5p, miR-1185-1-3p, miR-6831-5p and miR-4695-5p) could discriminate bladder cancer from non-cancer and other types of tumors with the highest accuracy (AUC: .97; sensitivity: 95%; specificity: 87%). The diagnostic accuracy was high, regardless of the stage and grade of bladder cancer. Our data demonstrated that the 7-miRNA panel could be a biomarker for the specific and early detection of bladder cancer.
| S-EPMC6317958 | biostudies-literature
Project description:A serum miRNA combination could be a powerful classifier for the detection of patients with bladder cancer.
2018-11-06 | GSE113486 | GEO
Project description:Esophageal cancer is one of the deadliest cancers worldwide. It typically has a poor overall prognosis because of diagnosis in advanced stages. Sensitive biomarkers for the early detection of esophageal cancer are urgently needed to reduce the high mortality of this disease. Circulating microRNAs (miRNAs) are emerging as a novel non-invasive biomarker for cancer diagnosis due to its high stability and specificity. In this study, we profiled circulating miRNAs in serum of patients with esophageal adenocarcinoma (EAC) using the Solexa sequencing analysis. The analysis demonstrated marked differences of more than 195 circulating miRNAs including 96 of upregulated and 99 of downregulated miRNA in EAC patients compared with healthy subjects. Quantitative reverse transcription PCR verified that the concentrations of circulating miR-25-3p and miR-151a-3p were significantly elevated, while the concentrations of miR-100-5p and miR-375 were significantly decreased in EAC patients compared with healthy controls. These data indicate the profile of these 4 miRNAs may potentially serve as a serum biomarker to identify patients with EAC, and circulating miRNA profiling may be clinically useful for early detection or treatment response in EAC patients.
| S-EPMC5126285 | biostudies-literature
Project description:ObjectivesPancreatic ductal adenocarcinoma (PDAC) presents the lowest survival rate of all cancers because only 6% of patients reach five-year survival. Alterations in the expression of several microRNAs (miRNAs) occur in the tumor of PDAC and in preneoplastic lesions as the called intraductal papillary mucinous neoplasm (IPMN). Here, we aimed at identifying which miRNAs are significantly altered in liquid biopsies from patients with PDAC and IPMN to find new noninvasive biomarkers for early detection of PDAC.MethodsWe analyzed by real-time quantitative reverse transcription-PCR (qRT-PCR) the expression of 17 circulating miRNAs, previously found to be significantly overexpressed in tissue pancreatic neoplasms, in a set of 182 plasma samples (94 PDAC, 19 IPMN, 18 chronic pancreatitis, and 51 disease-free controls). Then, we analyzed CA19.9 levels in the same plasma set, and we assessed the diagnostic values of differentially expressed miRNAs, CA19.9, and all possible combinations.ResultsOf note, 16, 14, and 9 miRNAs were significantly increased in PDAC, IPMN, and chronic pancreatitis, respectively, compared with control plasmas. miR-21-5p, miR-33a-3p, miR-320a, and miR-93-5p showed the highest discriminating capacity for pancreatic neoplasia (PDAC or IPMN) with an area under the receiver operating characteristic curve (AUC) of 0.86, 0.85, 0.85, and 0.80, respectively. 2-miRNA combinations improved these performances reaching AUC = 0.90 for "miR-33a-3p+miR-320a." Addition of CA19.9 increased the diagnostic potential of miRNA signatures even further achieving an AUC of 0.95 (93% sensitivity and 85% specificity) for the combination of "miR-33a-3p+miR-320a+CA19.9."ConclusionsNovel signatures combining miRNAs and CA19.9 could be used as noninvasive biomarkers for early detection of PDAC.
| S-EPMC6602779 | biostudies-literature
Project description:We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not sufficient to be used in the clinics. Given the heterogeneity of lung tumors developed from multifactorial molecular aberrations, we determine whether integrating the different classes of molecular biomarkers can improve diagnosis of lung cancer. By using droplet digital PCR, we analyze expression of the seven genes in plasma of a development cohort of 64 lung cancer patients and 33 cancer-free individuals. The panels of three miRNAs (miRs-21, 210, and 486-5p), two lncRNAs (SNHG1 and RMRP), and two FUTs (FUT8 and POFUT1) have a sensitivity of 81-86% and a specificity of 84-87% for diagnosis of lung cancer. From the seven genes, an integromic plasma signature comprising miR-210, SNHG1, and FUT8 is developed that produces higher sensitivity (95.45%) and specificity (96.97%) compared with the individual biomarker panels (all p<0.05). The diagnostic value of the signature was confirmed in a validation cohort of 40 lung cancer patients and 29 controls, independent of stage and histological type of lung tumor, and patients' age, sex, and smoking status (all p>0.05). The integration of the different categories of biomarkers might improve diagnosis of lung cancer.
| S-EPMC5973873 | biostudies-other
Project description:BackgroundPreeclampsia (PE) is a multisystemic maternal syndrome with substantial maternal and fetal morbidity and mortality. Currently, there is no clinically viable non-invasive biomarker assay for early detection, thus limiting the effective prevention and therapeutic strategies for PE.MethodsWe conducted a discovery-training-validation three-phase retrospective and prospective study with cross-platform and multicenter cohorts. The initial biomarkers were discovered and verified in tissue specimens by small RNA sequencing and qRT-PCR. A miRNA signature (miR2PE-score) was developed using Firth's bias-reduced logistic regression analysis and subsequently validated in two independent multinational retrospective cohorts and two prospective plasma cohorts.ResultsWe initially identified five PE-associated differentially expressed miRNAs from miRNA sequencing data and subsequently validated two miRNAs (miR-196b-5p and miR-584-5p) as robust biomarkers by association analysis with clinical characteristics and qRT-PCR in tissue specimens in the discovery phase. Using Firth's bias-reduced logistic regression analysis, we developed the miR2PE-score for the early detection of PE. The miR2PE-score showed a high diagnostic performance with an area under the receiver operating characteristic curve (AUROC) of 0.920, 0.848, 0.864, and 0.812 in training, internal, and two external validation cross-platform and multicenter cohorts, respectively. Finally, we demonstrated the non-invasive diagnostic performance of the miR2PE-score in two prospective plasma cohorts with AUROC of 0.933 and 0.787. Furthermore, the miR2PE-score revealed superior performance in non-invasive diagnosis compared with previously published miRNA biomarkers.ConclusionsWe developed and validated a novel and robust blood-based miRNA signature, which may serve as a promising clinically applicable non-invasive tool for the early detection of PE.
| S-EPMC9469544 | biostudies-literature
Project description:Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.
| S-EPMC10003255 | biostudies-literature
Project description:INTRODUCTION: MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls. METHODS: We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718). RESULTS: Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202. CONCLUSIONS: MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.
| S-EPMC3252341 | biostudies-literature