Dataset Information

Ratio-Based Method To Identify True Biomarkers by Normalizing Circulating ncRNA Sequencing and Quantitative PCR Data.

ABSTRACT: Recent studies have indicated that circulating noncoding RNAs (ncRNAs) such as miRNAs are stable biomarkers for the diagnosis and prognosis of human diseases. However, due to low concentrations of circulating ncRNAs in blood, data normalization in plasma/serum ncRNA experiments using next-generation sequencing and quantitative real time RT-qPCR is a challenge. We found that the current normalization methods based on synthetic external spiked-in controls or published endogenous miRNA controls are inappropriate as they are not stably expressed and therefore fail to reliably detect differentially expressed ncRNAs. Using the alternative of individual ncRNAs as biomarkers, we considered a ratio-based normalization method calculated taking the ratio of any two ncRNAs in the same sample and used the resulting ratios as biomarkers. We mathematically verified the method to be independent of spiked-in and internal controls, and more robust than existing reference control based normalization methods to identify differentially expressed ncRNAs as potential biomarkers for human diseases. Thus, the ratio-based method can solve the difficult normalization problem for circuiting ncRNA data to identify reliable biomarkers to meet real clinical practice.

SUBMITTER: Deng Y

PROVIDER: S-EPMC6884007 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Ratio-Based Method To Identify True Biomarkers by Normalizing Circulating ncRNA Sequencing and Quantitative PCR Data.

Deng Youping Y Zhu Yong Y Wang Hongwei H Khadka Vedbar S VS Hu Ling L Ai Junmei J Dou Yuhong Y Li Yan Y Dai Shengming S Mason Christopher E CE Wang Yunliang Y Jia Wei W Zhang Jicai J Huang Gang G Jiang Bin B

Analytical chemistry 20190430 10

Recent studies have indicated that circulating noncoding RNAs (ncRNAs) such as miRNAs are stable biomarkers for the diagnosis and prognosis of human diseases. However, due to low concentrations of circulating ncRNAs in blood, data normalization in plasma/serum ncRNA experiments using next-generation sequencing and quantitative real time RT-qPCR is a challenge. We found that the current normalization methods based on synthetic external spiked-in controls or published endogenous miRNA controls are ...[more]

PMID: 31002238

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Project description:The discovery and characterization of blood-based disease biomarkers are clinically important because blood collection is easy and involves relatively little stress for the patient. However, blood generally reflects not only targeted diseases, but also the whole body status of patients. Thus, the selection of biomarkers may be difficult. In this study, we considered miRNAs as biomarker candidates for several reasons. First, since miRNAs were discovered relatively recently, they have not yet been tested extensively. Second, since the number of miRNAs is relatively limited, selection is expected to be easy. Third, since they are known to play critical roles in a wide range of biological processes, their expression may be disease specific. We applied a newly proposed method to select combinations of miRNAs that discriminate between healthy controls and each of 14 diseases that include 5 cancers. A new feature selection method is based on principal component analysis. Namely this method does not require knowledge of whether each sample was derived from a disease patient or a healthy control. Using this method, we found that hsa-miR-425, hsa-miR-15b, hsa-miR-185, hsa-miR-92a, hsa-miR-140-3p, hsa-miR-320a, hsa-miR-486-5p, hsa-miR-16, hsa-miR-191, hsa-miR-106b, hsa-miR-19b, and hsa-miR-30d were potential biomarkers; combinations of 10 of these miRNAs allowed us to discriminate each disease included in this study from healthy controls. These 12 miRNAs are significantly up- or downregulated in most cancers and other diseases, albeit in a cancer- or disease-specific combinatory manner. Therefore, these 12 miRNAs were also previously reported to be cancer- and disease-related miRNAs. Many disease-specific KEGG pathways were also significantly enriched by target genes of up-/downregulated miRNAs within several combinations of 10 miRNAs among these 12 miRNAs. We also selected miRNAs that could discriminate one disease from another or from healthy controls. These miRNAs were found to be largely overlapped with miRNAs that discriminate each disease from healthy controls.

Dataset Information

Ratio-Based Method To Identify True Biomarkers by Normalizing Circulating ncRNA Sequencing and Quantitative PCR Data.

Publications

Ratio-Based Method To Identify True Biomarkers by Normalizing Circulating ncRNA Sequencing and Quantitative PCR Data.

Similar Datasets

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