four-miRNA Signature Research Articles

Identification of a four-miRNA signature predicts the prognosis of papillary thyroid cancer.

In recently diagnosed patients with thyroid cancer, papillary thyroid cancer (PTC), as the most common histological subtype, accounts for 90% of all cases. Although PTC is known as a relatively adolescent malignant disease, there still is a high possibility of recurrence in PTC patients with a poor prognosis. Therefore, new biomarkers are necessary to guide more effective stratification of PTC patients and personalize therapy to avoid overtreatment or inadequate treatment. Accumulating evidence demonstrates that microRNAs (miRNAs) have broad application prospects as diagnostic biomarkers in cancer. To explore novel markers consisting of miRNA-associated signatures for PTC prognostication. We obtained and analyzed the data of 497 PTC patients from The Cancer Genome Atlas. The patients were randomly assigned to either a training or testing cohort. We discovered 237 differentially expressed miRNAs in tumorous thyroid tissues compared with normal tissues, which contained 172 up-regulated and 65 down-regulated miRNAs. The evaluation of differently expressed miRNAs was conducted using our risk score model. We then successfully generated a four-miRNA potential prognostic signature [risk score = (-0.001 × hsa-miR-181a-2-3p) + (0.003 × hsa-miR-138-5p) + (-0.018 × hsa-miR-424-3p) + (0.284 × hsa-miR-612)], which reliably distinguished patients from high and low risk with a significant difference in the overall survival (P < 0.01) and was effective in predicting the five-year disease survival rate with the area under the receiver operating characteristic curve of 0.937 and 0.812 in the training and testing cohorts, respectively. Additionally, there was a trend indicated that high-risk patients had shorter relapse-free survival, although statistical significance was not reached (P = 0.082) in our sequencing cohort. Our results indicated a four-miRNA signature that has a robust predictive effect on the prognosis of PTC. Accordingly, we would recommend more radical therapy and closer follow-ups for high-risk groups.

A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and patients at advanced stage showed poor survival rate. Despite microRNAs (miRNAs) are used as potential biomarkers in many cancers, miRNA biomarkers for predicting the tumor stage of ccRCC are still limitedly identified. Therefore, we proposed a new integrated machine learning (ML) strategy to identify a novel miRNA signature related to tumor stage and prognosis of ccRCC patients using miRNA expression profiles. A multivariate Cox regression model with three hybrid penalties including Least absolute shrinkage and selection operator (Lasso), Adaptive lasso and Elastic net algorithms was used to screen relevant prognostic related miRNAs. The best subset regression (BSR) model was used to identify optimal prognostic model. Five ML algorithms were used to develop stage classification models. The biological significance of the miRNA signature was analyzed by utilizing DIANA-mirPath.ResultsA four-miRNA signature associated with survival was identified and the expression of this signature was strongly correlated with high risk patients. The high risk patients had unfavorable overall survival compared with the low risk group (HR = 4.523, P-value = 2.86e−08). Univariate and multivariate analyses confirmed independent and translational value of this predictive model. A combined ML algorithm identified six miRNA signatures for cancer staging prediction. After using the data balancing algorithm SMOTE, the Support Vector Machine (SVM) algorithm achieved the best classification performance (accuracy = 0.923, sensitivity = 0.927, specificity = 0.919, MCC = 0.843) when compared with other classifiers. Furthermore, enrichment analysis indicated that the identified miRNA signature involved in cancer-associated pathways.ConclusionsA novel miRNA classification model using the identified prognostic and tumor stage associated miRNA signature will be useful for risk and stage stratification for clinical practice, and the identified miRNA signature can provide promising insight to understand the progression mechanism of ccRCC.

Serum microRNA expression profiling revealing potential diagnostic biomarkers for lung adenocarcinoma.

BackgroundRecent studies have demonstrated that microRNAs (miRNAs) in the blood circulation can serve as promising diagnostic markers for cancers. This four-stage study aimed at finding serum miRNAs as potential biomarkers for lung adenocarcinoma (LA) diagnosis.MethodsThe study was carried out between 2016 and 2017. The Exiqon miRNA qPCR panel (3 LA vs. 1 normal control [NC] pooled serum samples) was used for initial screening to acquire miRNA profiles. Thirty-five dysregulated miRNAs were further evaluated in the training (24 LA vs. 24 NCs) and testing stages (110 LA vs. 110 NCs) using quantitative real-time polymerase chain reaction assays.ResultsFour serum miRNAs (miR-133a-3p, miR-584-5p, miR-10b-5p, and miR-221-3p) were significantly overexpressed in LA patients compared with NCs. The diagnostic value of the four-miRNA panel was validated by an external cohort (36 LA vs. 36 NCs). The areas under the receiver operating characteristic curve of the four-miRNA panel in the training, testing, and external validation stages were 0.734, 0.803, and 0.894 respectively. Meanwhile, the expression level of miR-221-3p was much higher in LA tumor samples than that in the adjacent normal tissues (19 LA vs. 19 NCs). The expression level of miR-10b-5p was also elevated in the serum-derived exosomes samples (18 LA vs. 18 NCs). The expression of miR-133a-3p, miR-584-5p, and miR-10b-5p was significantly elevated in LA patients with epidermal growth factor receptor mutation compared with NCs.ConclusionThe study established a four-miRNA signature in serum that could improve the diagnostic capability of LA.

Four-microRNA signature for detection of type 2 diabetes.

BACKGROUNDSensitive, novel, and accurate biomarkers for the detection of physiological changes in type 2 diabetes (T2DM) at an early stage are urgently needed.AIMTo build a multi-parameter diagnostic model for the early detection of T2DM.METHODSMiR-148b, miR-223, miR-130a, and miR-19a levels were detected by real-time polymerase chain reaction in serum of healthy controls, individuals with impaired glucose regulation, and T2DM patients. The diagnostic value of miR-148b, miR-223, miR-130a, and miR-19a, alone or in combination, was analyzed.RESULTSThe area under the curve (AUC) of miR-223, which had the best diagnostic value for discriminating the impaired glucose regulation and T2DM groups, was 0.84, and the sensitivity and specificity were 73.37% and 81.37%, respectively. The AUC of the four-miRNA signature was 0.90, and the sensitivity and specificity were 78.82% and 88.23%, respectively. In the validation set, the AUC was 0.88, and the sensitivity and specificity were 78.36% and 87.63%, respectively.CONCLUSIONIn summary, we have built a multi-parameter diagnostic model consisting of miR-148b, miR-223, miR-130a, and miR-19a for the detection of T2DM. It may be a potential tool for the early detection of T2DM.

Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer.

BackgroundmiRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.MethodsR software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.ResultsA combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis.ConclusionsThis study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.

Identification of Novel Circulating miRNA Biomarkers for the Diagnosis of Esophageal Squamous Cell Carcinoma and Squamous Dysplasia.

Circulating miRNAs have been identified as diagnostic biomarkers for esophageal squamous cell carcinoma (ESCC), but their efficacy in discovering early-stage ESCC is still unsatisfying. Esophageal squamous dysplasia (ESD) is the precursor lesion of ESCC. Notably, little is known about the role(s) of circulating miRNAs in identifying ESD. In this study, we, therefore, aimed to identify serum miRNAs as novel diagnostic markers for detecting ESD and ESCC. The genome-wide miRNA expression was profiled in 104 (52 ESCC and 52 controls) serum samples using microarray. Seven candidate miRNAs from the microarray assay were evaluated for their diagnostic performance in another cohort of 266 participants (96 ESCC, 92 ESD, and 78 healthy controls). The serum levels of miR-16-5p, miR-197-5p, miR-451a, and miR-92a-3p were associated with ESCC; the biomarker based on the panel of these four miRNAs could efficiently distinguish patients with ESCC from the controls [AUC = 0.856; 95% confidence interval (CI), 0.794-0.905; P < 0.001]. The serum levels of miR-16-5p, miR-320c, miR-638, and miR-92a-3p were significantly higher in patients with ESD than in controls, and this four-miRNA signature could efficiently differentiate patients with ESD from the controls (AUC = 0.842; 95% CI, 0.778-0.893; P < 0.001). In addition, compared with serum carcinoembryonic antigen and carbohydrate antigen 199, miRNA-based panels had a better diagnostic performance in distinguishing patients with ESCC and ESD from healthy controls. Our study identified two novel panels of circulating miRNAs with high efficiency in detecting ESCC and ESD, suggesting that circulating miRNAs, in particular the combination of them, might serve as noninvasive biomarkers for the early detection of ESCC. This study suggests the feasibility of using circular miRNA-based blood tests to aid in the detection of ESD and ESCC.

Circulating miRNAs as non-invasive biomarkers to predict aggressive prostate cancer after radical prostatectomy

BackgroundProstate cancer is an extremely heterogeneous disease. Despite being clinically similar, some tumours are more likely to recur after surgery compared to others. Distinguishing those that need adjuvant or salvage radiotherapy will improve patient outcomes. The goal of this study was to identify circulating microRNA that could independently predict prostate cancer patient risk stratification after radical prostatectomy.MethodsSeventy-eight prostate cancer patients were recruited at the Odette Cancer Centre in Sunnybrook Health Sciences Centre. All patients had previously undergone radical prostatectomy. Blood samples were collected simultaneously for PSA testing and miRNA analysis using NanoString nCounter technology. Of the 78 samples, 75 had acceptable miRNA quantity and quality. Patients were stratified into high- and low-risk categories based on Gleason score, pathological T stage, surgical margin status, and diagnostic PSA: patients with Gleason ≥ 8; pT3a and positive margin; pT3b and any margin; or diagnostic PSA > 20 µg/mL were classified as high-risk (n = 44) and all other patients were classified as low-risk (n = 31).ResultsUsing our patient dataset, we identified a four-miRNA signature (miR-17, miR-20a, miR-20b, miR-106a) that can distinguish high- and low-risk patients, in addition to their pathological tumour stage. High expression of these miRNAs is associated with shorter time to biochemical recurrence in the TCGA dataset. These miRNAs confer an aggressive phenotype upon overexpression in vitro.ConclusionsThis proof-of-principle report highlights the potential of circulating miRNAs to independently predict risk stratification of prostate cancer patients after radical prostatectomy.

Prognostic Value of a Four-miRNA Signature in Patients With Lymph Node Positive Locoregional Esophageal Squamous Cell Carcinoma Undergoing Complete Surgical Resection.

This study was intended to identify prognostic biomarkers for lymph node (LN)-positive locoregional esophageal squamous cell carcinoma (ESCC) patients. Surgery is a major treatment for LN-positive locoregional ESCC patients in China. However, patient outcomes are poor and heterogeneous. ESCC-associated miRNAs were identified by microarray and validated by quantitative real-time polymerase chain reaction analyses in ESCC and normal esophageal epithelial samples. A multi-miRNA based classifier was established using a least absolute shrinkage and selection operator model in a training set of 145 LN-positive locoregional ESCCs, and further assessed in internal testing and independent validation sets of 145 and 243 patients, respectively. Twenty ESCC-associated miRNAs were identified and validated. A 4-miRNA based classifier (miR-135b-5p, miR-139-5p, miR-29c-5p, and miR-338-3p) was generated to classify LN-positive locoregional ESCC patients into high and low-risk groups. Patients with high-risk scores in the training set had a lower 5-year overall survival rate [8.7%, 95% confidence interval (CI): 0-20.3] than those with low-risk scores (50.3%, 95% CI: 40.0-60.7; P < 0.0001). The prognostic accuracy of the classifier was validated in the internal testing (P < 0.0001) and independent validation sets (P = 0.00073). Multivariate survival analyses showed that the 4-miRNA based classifier was an independent prognostic factor, and the combination of the 4-miRNA based classifier and clinicopathological prognostic factors significantly improved the prognostic accuracy of clinicopathological prognostic factors alone. Our 4-miRNA based classifier is a reliable prognostic prediction tool for overall survival in LN-positive locoregional ESCC patients and might offer a novel probability of ESCC treatment individualization.

A four-miRNA signature as a novel biomarker for predicting survival in endometrial cancer

BackgroundThe microRNAs (miRNAs) have been validated as prognostic markers in many cancers. The aim of this study was to identify new miRNA prognostic biomarkers in endometrial cancer (EC) and to develop an expression-based miRNA signature to provide survival risk prediction for EC patients. MethodsFrom TCGA database, the miRNA datasets of EC and clinical information were downloaded in April 2018. Using univariate and multivariate Cox regression analyses identify prognostic factors. Using area under the curve (AUC) of receiver operating characteristic (ROC) curve assess the sensitivity and specificity of prognostic model. Results530 patients were randomly divided into training set and testing set. Among 561 differentially expressed miRNAs, 4 miRNAs (miR-4758, miR-876, miR-142, miR-190b) were demonstrated to be predictive biomarkers of overall survival (OS) for EC patients in training set. Based on the risk score of 4-miRNA model, patients in the training set were divided into high-risk and low-risk groups with significantly different OS. This 4-miRNA model was validated in testing and entire set. The AUC for the ROC curves in the entire set was 0.704. Meanwhile, multivariate Cox regression combined with other traditional clinical parameters indicated that the 4-miRNA model can be used as an independent OS prognostic factor. Functional enrichment analysis revealed that these miRNAs are involved in biological processes and pathways that are closely related to cancer. ConclusionA robust 4-miRNA signature as an independent prognostic factor for OS in EC patients was established.

Four-miRNA Signature to Identify Asbestos-Related Lung Malignancies.

Altered miRNA expression is an early event upon exposure to occupational/environmental carcinogens; thus, identification of a novel asbestos-related profile of miRNAs able to distinguish asbestos-induced cancer from cancer with different etiology can be useful for diagnosis. We therefore performed a study to identify miRNAs associated with asbestos-induced malignancies. Four groups of patients were included in the study, including patients with asbestos-related (NSCLCAsb) and asbestos-unrelated non-small cell lung cancer (NSCLC) or with malignant pleural mesothelioma (MPM), and disease-free subjects (CTRL). The selected miRNAs were evaluated in asbestos-exposed population. Four serum miRNAs, that is miR-126, miR-205, miR-222, and miR-520g, were found to be implicated in asbestos-related malignant diseases. Notably, increased expression of miR-126 and miR-222 were found in asbestos-exposed subjects, and both miRNAs are involved in major pathways linked to cancer development. Epigenetic changes and cancer-stroma cross-talk could induce repression of miR-126 to facilitate tumor formation, angiogenesis, and invasion. This study indicates that miRNAs are potentially involved in asbestos-related malignancies, and their expression outlines mechanism(s) whereby miRNAs may be involved in an asbestos-induced pathogenesis. The discovery of a miRNA panel for asbestos-related malignancies would impact on occupational compensation and may be utilized for screening asbestos-exposed populations.

Identification and validation of a four-miRNA (miRNA-21-5p, miRNA-9-5p, miR-149-5p, and miRNA-30b-5p) prognosis signature in clear cell renal cell carcinoma.

PurposeClear cell renal cell carcinoma (ccRCC) is one of the most common cancers with high mortality worldwide. However, biomarkers for predicting prognosis in ccRCC are limited. In this study, we attempted to identify potential prognostic biomarkers of ccRCC.MethodsClinical information and the preprocessed ccRCC mature miRNA expression profiles in The Cancer Genome Atlas database were downloaded from UCSC Xena. The miRNAs differentially expressed between ccRCCs and matched normal tissues were analyzed using the “limma” package. A miRNA-based signature was constructed using the multivariate Cox regression model with prognosis index (PI) formula. Patients with ccRCC were divided into low-risk and high-risk subgroups according to median PI. The survival times were compared between the two groups using Kaplan–Meier analysis with log-rank test. The training set was used to construct a miRNA-based signature for predicting prognosis. The test set was used to verify the signature. Target gene prediction and functional enrichment analysis of the four miRNAs were performed using miRNet.ResultsWe identified four miRNAs, miRNA-21-5p, miRNA-9-5p, miR-149-5p, and miRNA-30b-5p, as independent prognostic indicators. Next, we used these four miRNAs to construct a four-miRNA PI for each patient. Results revealed that patients in the high-risk group (n=119) had significantly shorter survival time than those in the low-risk group (n=118) (high-risk/low-risk group log-rank P=0.000). This four-miRNA signature is an independent prognostic factor compared with routine clinicopathological features in the test set. These miRNAs targeted 1,634 genes, and a miRNA-target gene network was constructed using miRNet. The target genes of these four miRNAs were involved in various pathways related to cancer.ConclusionOur observations suggest that the four-miRNA signature correlated with the survival of patients with ccRCC and can be used as a prognostic biomarker of ccRCC.

Serum-based microRNA signature predicts relapse and therapeutic outcome of adjuvant chemotherapy in colorectal cancer patients.

BackgroundApproximately 60% of patients with colorectal cancer (CRC) undergo either local recurrence or distant metastases after surgery. Current prognostic biomarkers are insufficient to predict recurrence of CRC and provide little forecast information about what patients are likely to receive benefit from the adjuvant chemotherapy. As microRNAs (miRNAs) constantly exist in human serum and being used to predict the prognosis of a various cancers, this study was designed to identify miRNA-based circulating biomarkers to predict clinical outcomes of CRC.MethodsA serum-focused miRNA expression was used to investigate if miRNA expression profiles could predict the clinical outcomes of patients with CRC. We created miRNA signature profiles associated in the training set (n = 40), and further validated its prediction in two independent testing cohorts.ResultsUsing Cox regression and risk-score analysis, we identified a four-miRNA signature (miR-652-3p, miR-342-3p, miR-501-3p and miR-328-3p) for the prediction of tumor relapse and the overall survival(OS) of patients with CRC in the training set (n = 40). This miRNA signature was further validated in a testing set (n = 226) and another independent cohort (n = 56). A high-risk signature score was significantly associated with CRC tumor recurrence and poor treatment outcome. Multivariable Cox regression models indicated that the risk score, based on the four-miRNA signature, was an independent prognostic classifier for patients with CRC.ConclusionsThe serum miRNA signature may serve as a minimally invasive predictor for tumor relapse and treatment outcome in patients with CRC and provide a useful reference for treatment selection.

Serum-Based MicroRNA Signature Predicts Relapse and Therapeutic Outcome of Adjuvant Chemotherapy in Colorectal Cancer Patients

Background: Approximately 60% of patients with colorectal cancer (CRC) undergo either local recurrence or distant metastases after surgery. Current prognostic biomarkers are insufficient to predict recurrence of CRC and provide little forecast information about what patients are likely to receive benefit from the adjuvant chemotherapy. As microRNAs (miRNAs) constantly exist in human serum and being used to predict the prognosis of a various cancers, this study was designed to identify miRNA-based circulating biomarkers to predict clinical outcomes of CRC. Methods: A serum-focused miRNA expression was used to investigate if miRNA expression profiles could predict the clinical outcomes of patients with CRC. We created miRNA signature profiles associated in the training set (n = 40), and further validated its prediction in two independent testing cohorts. Results: Using Cox regression and risk-score analysis, we identified a four-miRNA signature (miR-652, miR-342, miR-501, and miR-328) for the prediction of tumor relapse and the overall survival(OS) of patients with CRC in the training set (n = 40). This miRNA signature was further validated in a testing set (n = 226) and another independent cohort (n = 56). A high-risk signature score was significantly associated with CRC tumor recurrence and poor treatment outcome. Multivariable Cox regression models indicated that the risk score, based on the four-miRNA signature, was an independent prognostic classifier for patients with CRC. Conclusions: The serum miRNA signature may serve as a minimally invasive predictor for tumor relapse and treatment outcome in patients with CRC and provide a useful reference for treatment selection. Funding Statement: This work was supported by the National Natural Science Foundation of China (81372593, 81201965, 81772565), Beijing Natural Science Foundation (7132052), and the National High Technology Research and Development Program of China (863 Program) (No.2012AA02A506, 2014AA020801). Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: This research was approved by the ethics committee of the Health Science Center of Peking University and the Oncology Center at Peking University and Zhejiang University. Written informed consent was obtained from all participants before enrollment to the study.

Dysregulation of the MiR-449b target TGFBI alters the TGF\u03b2 pathway to induce cisplatin resistance in nasopharyngeal carcinoma

Despite the improvement in locoregional control of nasopharyngeal carcinoma (NPC), distant metastasis (DM), and chemoresistance persist as major causes of mortality. This study identified a novel role for miR-449b, an overexpressed gene in a validated four-miRNA signature for NPC DM, leading to chemoresistance via the direct targeting of transforming growth factor beta-induced (TGFBI). In vitro shRNA-mediated downregulation of TGFBI induced phosphorylation of PTEN and AKT, increasing cisplatin resistance. Conversely, the overexpression of TGFBI sensitized the NPC cells to cisplatin. In NPC patients treated with concurrent chemoradiotherapy (CRT), the overall survival (OS) was significantly inversely correlated with miR-449b, and directly correlated with both TGFBI mRNA and protein expression, as assessed by RNA sequencing and immunohistochemistry (IHC). Mechanistically, co-immunoprecipitation demonstrated that TGFBI competes with pro-TGFβ1 for integrin receptor binding. Decreased TGFBI led to increased pro-TGFβ1 activation and TGFβ1 canonical/noncanonical pathway-induced cisplatin resistance. Thus, overexpression of miR-449b decreases TGFBI, thereby altering the balance between TGFBI and pro-TGFβ1, revealing a novel mechanism of chemoresistance in NPC.

MP58-12 A FOUR MIRNAS SIGNATURE AS A POTENTIAL BIOMARKER FOR PREDICTING SURVIVAL USING BIOINFORMATICS ANALYSIS IN BLADDER CANCER

You have accessJournal of UrologyBladder Cancer: Basic Research & Pathophysiology II1 Apr 2018MP58-12 A FOUR MIRNAS SIGNATURE AS A POTENTIAL BIOMARKER FOR PREDICTING SURVIVAL USING BIOINFORMATICS ANALYSIS IN BLADDER CANCER He Xiao, Ping Chen, Deqiang Xu, Michael E DiSanto, Xinhua Zhang, and Xinhua Zhang He XiaoHe Xiao More articles by this author , Ping ChenPing Chen More articles by this author , Deqiang XuDeqiang Xu More articles by this author , Michael E DiSantoMichael E DiSanto More articles by this author , Xinhua ZhangXinhua Zhang More articles by this author , and Xinhua ZhangXinhua Zhang More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1844AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Human bladder cancer (BCa) is a common disease, with the etiology and mechanism unknown. Accumulated evidence shows that micro RNAs (miRNAs) play vital roles and can be used as biomarkers for many types of cancers. The aim of this study is to use bioinformatics analysis to identify the key miRNAs and potential target genes, as well as studying the underlying mechanisms for BCa. METHODS The raw sequencing data and clinical information were downloaded from TCGA database. The miRNA profiles were normalized by log2 transformed. Subsequently, a prognostic miRNA signature was constructed, and the miRNA signature could calculate a risk score for each bladder cancer patient. The target genes of prognostic miRNAs were predicted using TargetScan, miRDB, PicTar, and miRanda online analysis tools. To further enhance the bioinformatics analysis reliability, the overlapping target genes were identified using Venn diagram and the Database for Annotation, Visualization and Integrated Discovery bioinformatics tool. RESULTS In the present study, a total of 407 samples were enrolled and 348 differentially expressed miRNAs were identified between bladder cancer tissues and normal tissues, including 264 up-regulated miRNAs and 84 down-regulated miRNAs. Meanwhile, the Kaplan-Meier survival method revealed that the prognostic function of four miRNAs (miRNA-217, miRNA-378c, miR-33b and miRNA-615). miR-217, miR-33b and miR-615 were positively associated to overall survival (OS), while miR-378c was reversely correlated with OS. Interestingly, univariate and multivariate Cox regression analyses showed that the four-miRNA (miRNA-217, miRNA-378c, miR-33b and miRNA-615) signature was an independent prognostic factor in bladder cancer. The functional enrichment analysis showed that the target genes of four miRNAs might be involved in various pathways related to cancer signaling pathways, including Notch signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway, cGMP-PKG signaling pathway, FoxO and signaling pathway. CONCLUSIONS This study identified, for the first time, a four-miRNA signature as a potential prognostic predictor for bladder cancer patients. Further studies are needed to validate our findings in large sample size, and function investigations are also required to explore the molecular mechanisms of these miRNAs in bladder cancer progression. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e777 Advertisement Copyright & Permissions© 2018MetricsAuthor Information He Xiao More articles by this author Ping Chen More articles by this author Deqiang Xu More articles by this author Michael E DiSanto More articles by this author Xinhua Zhang More articles by this author Xinhua Zhang More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Prognostic value of a microRNA signature as a novel biomarker in patients with lower-grade gliomas.

MicroRNAs (miRNAs) may act as prognostic biomarkers in a variety of cancers. The aim of this study was to identify and evaluate a prognostic miRNA signature in patients with lower-grade gliomas (LGGs). miRNA expression profiles and clinical data of patients with LGGs from the Chinese Glioma Genome Atlas (CGGA; the training cohort) and The Cancer Genome Atlas (TCGA; the validation cohort) were analyzed, and the least absolute shrinkage and selection operator Cox regression model was used to identify the miRNA signature, which was combined with clinical prognostic factors to develop an individualized survival prediction model. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to reveal the biological implications of the signature. We identified a four-miRNA signature that stratified patients in the training cohort into low- or high-risk groups according to overall survival time, a finding that was verified in the validation cohort. Multivariate Cox regression analysis indicated that the four-miRNA signature was an independent prognostic biomarker, and a nomogram combining this miRNA signature with clinicopathological and molecular factors showed high prognostic accuracy for individualized survival prediction in both TCGA (C-index = 0.83) and CGGA (C-index = 0.68) cohorts. Functional annotation indicated that the major biological processes of this prognostic miRNA signature were enriched in cell cycle and DNA repair-associated biological processes. Our findings indicated that our newly discovered four-miRNA signature may be an effective independent prognostic factor for the prediction of patients with LGGs.

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

PurposeThe aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD).Patients and methodsUsing expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses.ResultsBased on our cutoff criteria (P<0.05 and |log2FC| >1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan–Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group (P=0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways.ConclusionTaken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

An Integrated Approach Identifies Mediators of Local Recurrence in Head and Neck Squamous Carcinoma.

Purpose: Head and neck squamous cell carcinomas (HNSCCs) cause more than 300,000 deaths worldwide each year. Locoregional and distant recurrences represent worse prognostic events and accepted surrogate markers of patients' overall survival. No valid biomarker and salvage therapy exist to identify and treat patients at high-risk of recurrence. We aimed to verify if selected miRNAs could be used as biomarkers of recurrence in HNSCC.Experimental Design: A NanoString array was used to identify miRNAs associated with locoregional recurrence in 44 patients with HNSCC. Bioinformatic approaches validated the signature and identified potential miRNA targets. Validation experiments were performed using an independent cohort of primary HNSCC samples and a panel of HNSCC cell lines. In vivo experiments validated the in vitro results.Results: Our data identified a four-miRNA signature that classified HNSCC patients at high- or low-risk of recurrence. These miRNAs collectively impinge on the epithelial-mesenchymal transition process. In silico and wet lab approaches showed that miR-9, expressed at high levels in recurrent HNSCC, targets SASH1 and KRT13, whereas miR-1, miR-133, and miR-150, expressed at low levels in recurrent HNSCC, collectively target SP1 and TGFβ pathways. A six-gene signature comprising these targets identified patients at high risk of recurrences, as well. Combined pharmacological inhibition of SP1 and TGFβ pathways induced HNSCC cell death and, when timely administered, prevented recurrence formation in a preclinical model of HNSCC recurrence.Conclusions: By integrating different experimental approaches and competences, we identified critical mediators of recurrence formation in HNSCC that may merit to be considered for future clinical development. Clin Cancer Res; 23(14); 3769-80. ©2017 AACR.

Abstract 469: Microrna signature as a potential biomarker for predicting survival in colon cancer

Abstract Background: Colon cancer is one of the most common cancers with increasing incidence and high mortality worldwide. Prognosis and choice of treatment is largely based on the tumor stage at presentation. Thus, finding novel biomarkers for predicting survival is highly desirable. Lately, several studies have been looking at microRNAs (miRNAs) in several cancers, including colon cancer. MicroRNAs are conserved, non-coding RNA molecules that play an important role in the regulation of post-transcriptional gene expression. Material and Methods: In the present study, we have profiled miRNA in one hundred and seventy two TNM stage I-IV colon cancer patients and 10 corresponding normal colon tissue samples. Total RNA was extracted from freshly frozen tissues, and the expression of miRNA profile were assessed using Pick and Mix focus panels from Exiqon containing 84 miRNAs that have been linked to cancer. Results: The results were visualized in a heatmap (Qlucore omics Software) and more than 20 miRNAs were found to be differentially expressed in tumors compared to the normal colon. Further, twelve miRNAs were found to discriminate between relapse and no-relapse patients in TNM- stage II and III, and four of these miRNAs (miR-23a, miR-25, miR-30d and miR-31) were found to be statistically significant in binary logistic regression with relapse as outcome variable. In univariate analysis, low expression of the four-miRNA signature was associated with better 3-year disease-free survival (DFS), 88 % versus 63% in low versus high signature, respectively (P=0.001). Moreover, the signature was a predictor of poor relapse-free survival in multivariate analyses (P=0.001; HR 31; 95% CI: 3.8-248.9). Another regression analyses method (LASSO) identified a 16-miRNA signature, and the four miRNAs found earlier were among them. The 16-miRNA signature was associated with better survival (P&amp;lt;0.001). Conclusion: The present study has identified a four-miRNA signature predicting relapse in colon cancer stage II and III patients. Citation Format: Havjin Jacob, Luka Stanisavljevic, Kristian Eeg Storli, Olav Dahl, Mette Pernille Myklebust. Microrna signature as a potential biomarker for predicting survival in colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 469. doi:10.1158/1538-7445.AM2017-469

A serum microRNA signature as a prognostic factor for patients with advanced NSCLC and its association with tissue microRNA expression profiles.

The aim of the present study was to detect microRNA (miRNA) signatures in advanced non-small cell lung cancer (NSCLC), and to study the association between miRNA expression levels in serum and tissue. A cohort of patients who had previously been diagnosed with advanced NSCLC was enrolled in the present study. miRNAs associated with prognosis, which had previously been detected in early stage NSCLC samples, were measured in the serum of the patient groups using a cross-validation method. In addition, serum miRNAs associated with progression-free survival (PFS) were detected in paired fresh tissue samples, in order to analyze the correlation between serum and tissue expression levels. A risk-score analysis was used to develop a four-miRNA signature to predict PFS. miR-1, miR-30d, miR-221 and miR-486 were identified as having a significant correlation with PFS in advanced NSCLC. miR-221 and miR-486 exhibited significant positive correlations between serum and tissue expression. Furthermore, overexpression of miR-221 and reduced expression of miR-486 increased cell proliferation, migration and invasion in vitro. In conclusion, the miRNA signature identified in the present study may be considered an independent prognostic factor of PFS in advanced NSCLC. In addition, the expression levels of miR-221 and miR-486 were significantly correlated between serum and tissue. miR-221 was identified as an oncogenic risk factor, whereas miR-486 exerted protective effects against cancer cell proliferation, migration and invasion.