Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection

Song, Tianci; Liang, Yanchun; Cao, Zhijun; Du, Wei; Liu, Ying

doi:10.1155/2017/4680650

Cited by 11 publications

(7 citation statements)

References 62 publications

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“…Recent studies have demonstrated that microRNAs take crucial regulatory roles in many biological processes of human tumor including UM [19][20][21][22][23]. With the advances of sequencing techniques, growing computational studies aimed at identifying microRNAs biomarkers for the diagnosis and prognosis of cancers due to their regulation of target gene expression [24][25][26][27][28]. Furthermore, recent evidences suggested that the abnormal expression of microRNAs signifcantly correlated with the prognosis of UM patients and could be regarded as a potential target for treatment, like the previous demonstrated microRNAs: hsa-miR-374b-5p, hsa-miR-29c-3p, and hsa-miR-211-5p [29].…”

Section: Discussionmentioning

confidence: 99%

Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases

Zuo

Tang

et al. 2022

Journal of Ophthalmology

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Background. The aim of this study was to apply bioinformatic analysis to develop a robust miRNA signature and construct a nomogram model in uveal melanoma (UM) to improve prognosis prediction. Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internally verify the signature). Then, miRNAs data of GSE84976 and GSE68828 were downloaded from Gene Expression Omnibus (GEO) database for outside verification. Combining univariate analysis and LASSO methods for identifying a robust miRNA biomarker in training set and the signature was validated in testing set and outside dataset. A prognostic nomogram was constructed and combined with decision curve as well as reduction curve analyses to assess the application of clinical usefulness. Finally, we constructed a miRNA-mRNA regulator network in UM and conducted pathway enrichment analysis according to the mRNAs in the network. Results. In total, a 3-miRNA was identified and validated that can robustly predict UM patients’ survival. According to univariate and multivariate cox analyses, age at diagnosis, tumor node metastasis (TNM) classification, stage, and the 3-miRNA signature significantly correlated with the survival outcomes. These characteristics were used to establish nomogram. The nomogram worked well for predicting 1 and 3 years of overall survival time. The decision curve of nomogram revealed a good clinical usefulness of our nomogram. What’s more, a miRNA-mRNA network was constructed. Pathway enrichment showed that this network was largely involved in mRNA processing, the mRNA surveillance pathway, the spliceosome, and so on. Conclusions. We developed a 3-miRNA biomarker and constructed a prognostic nomogram, which may afford a quantitative tool for predicting the survival of UM. Our finding also provided some new potential targets for the treatment of UM.

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Section: Discussionmentioning

confidence: 99%

Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases

Zuo

Tang

et al. 2022

Journal of Ophthalmology

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“…Therefore, reproducible biomarkers are needed to predict the survival of patients with HCC at clinical settings. Based on bioinformatic studies, extensive evidence has been theoretically investigated to show that abundant target genes were regulated by miRNAs, which virtually involves in every process of malignant tumors pathway regulation, therapeutic strategy, and prognosis [26][27][28][29]. In particular, in the process of tumorigenesis and development, a large number of miRNAs play different roles as prognostic biomarkers, including lung cancer [30], breast cancer [31], colorectal cancer [32], prostate cancer [33], gastric cancer [34], and pancreatic cancer [35].…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma

Zhang¹,

Ma²,

Zhai³

et al. 2021

Int. J. Med. Sci.

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Hepatocellular carcinoma (HCC), a common type of primary liver cancer, is one of the most aggressive malignant tumors worldwide. Although overall survival (OS) rates for HCC has significantly improved in recent years, however, the exact predictive value of microRNA (miRNA) for the prognosis of HCC has not yet been recognized. Here, we aimed to identify potential prognostic miRNAs involved in HCC by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. The RNA expression profiles and corresponding clinical information of HCC were available from The Cancer Genome Atlas (TCGA) datasets. Differentially expression and standardization analysis of miRNAs, Kaplan-Meier curve and time dependent ROC curve were performed by using R tools. Differentially expressed miRNAs (DEmiRNAs) and clinical parameters involved in the OS of HCC were confirmed by Cox regression models. And functional enrichment analysis was used to establish functions of the targeted genes of DEmiRNAs. A total of 300 DEmiRNAs were significantly related with HCC, of which 40 were down-regulated and 260 were up-regulated. A total of 344 patients with DEmiRNAs, status, overall survival (OS) time were randomized into training group (172) and test group (172). Multivariate Cox regression analyses revealed that 3 miRNA (hsa-miR-139-3p, hsa-miR-760, hsa-miR-7-5p) had independent prognostic significance for the OS of HCC in both training and test group. Moreover, according to Kaplan Meier analysis, the OS of HCC patients with high-risk score was shorter in validation and entire series. The time dependent ROC curve demonstrated high accuracy of the signature for OS. Besides, target genes of three miRNAs were analyzed by functional enrichment analysis and 20 genes associated with OS were verified by using Kaplan-Meier method. Compared with normal and benign group, the relative expression level of hsa-miR-139-3p was significantly decreased, while hsa-miR-7-5p and hsa-miR-760 were distinctly increased in the plasma of HCC patients. The same results were observed in the independent cohort. Collectively, our research suggested that three-miRNA signature could serve as an independent prognostic indicator for HCC patients.

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“…These cancer-screening tests are characterized by low sensitivities or specificities (PSA and fecal occult blood tests) or require specialized trained personnel (image related tests) that make them expensive and limit their use to specific populations and/or referral centers [14]. This is the reason by which blood biomarkers have been proposed as effective indicators to distinguish between cancer and normal conditions or among different cancer groups [15].…”

Section: Discussionmentioning

confidence: 99%

A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types

Pastor-Navarro

García-Flores

Fernández-Serra

et al. 2020

IJMS

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The purpose of this study is to clinically validate a series of circulating miRNAs that distinguish between the 4 most prevalent tumor types (lung cancer (LC); breast cancer (BC); colorectal cancer (CRC); and prostate cancer (PCa)) and healthy donors (HDs). A total of 18 miRNAs and 3 housekeeping miRNA genes were evaluated by qRT-PCR on RNA extracted from serum of cancer patients, 44 LC, 45 BC, 27 CRC, and 40 PCa, and on 45 HDs. The cancer detection performance of the miRNA expression levels was evaluated by studying the area under the curve (AUC) of receiver operating characteristic (ROC) curves at univariate and multivariate levels. miR-21 was significantly overexpressed in all cancer types compared with HDs, with accuracy of 67.5% (p = 0.001) for all 4 tumor types and of 80.8% (p < 0.0001) when PCa cases were removed from the analysis. For each tumor type, a panel of miRNAs was defined that provided cancer-detection accuracies of 91%, 94%, 89%, and 77%, respectively. In conclusion, we have described a series of circulating miRNAs that define different tumor types with a very high diagnostic performance. These panels of miRNAs would constitute the basis of different approaches of cancer-detection systems for which clinical utility should be validated in prospective cohorts.

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Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection

Cited by 11 publications

References 62 publications

Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases

Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma

A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types

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