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Analytics of Cerebrospinal Fluid MicroRNA Quantitative PCR Studies.

ABSTRACT: MicroRNAs (miRNAs) are small non-coding RNAs that regulate post-transcriptional gene expression. Recent studies have shown that human disease states correlate with measurable differences in the level of circulating miRNAs relative to healthy controls. Thus, there is great interest in developing clinical miRNA assays as diagnostic or prognostic biomarkers for diseases, and as surrogate measures for therapeutic outcomes. Our studies have focused on miRNAs in human cerebral spinal fluid (CSF) as biomarkers for central nervous system (CNS) diseases. Our objective here was to examine factors that may affect the outcome of quantitative PCR (qPCR) studies on CSF miRNAs, in order to guide planning and interpretation of future CSF miRNA TaqMan® low-density array (TLDA) studies. We obtained CSF from neurologically normal (control) donors and used TLDAs to measure miRNA expression. We examined sources of error in the TLDA outcomes due to (1) nonspecific amplification of products in total RNA, (2) variations in RNA isolations performed on different days, (3) miRNA primer probe efficiency, and (4) variations in individual TLDA cards. We also examined the utility of card-to-card TLDA corrections and use of an unchanged "reference standard" to remove batch processing effects in large-scale studies.

SUBMITTER: Lusardi TA

PROVIDER: S-EPMC6527498 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Analytics of Cerebrospinal Fluid MicroRNA Quantitative PCR Studies.

Lusardi Theresa A TA Wiedrick Jack T JT Malone Molly M Phillips Jay I JI Sandau Ursula S US Lind Babett B Quinn Joseph F JF Lapidus Jodi A JA Saugstad Julie A JA

Molecular neurobiology 20181114 7

MicroRNAs (miRNAs) are small non-coding RNAs that regulate post-transcriptional gene expression. Recent studies have shown that human disease states correlate with measurable differences in the level of circulating miRNAs relative to healthy controls. Thus, there is great interest in developing clinical miRNA assays as diagnostic or prognostic biomarkers for diseases, and as surrogate measures for therapeutic outcomes. Our studies have focused on miRNAs in human cerebral spinal fluid (CSF) as bi ...[more]

PMID: 30430409

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Project description:Purpose: Leptomeningeal metastasis (LM) is a dismal terminal stage disease of solid cancer without definitive treatment. Both the limitation of cerebrospinal fluid (CSF) sample volume and a paucity of floating cancer cells are difficulties to study the genomic profiling of LM. As the profiling of microRNAs reflect the strategy and behavior of cancer cells to survive, and CSF is carrying micro-molecules from central nervous system (CNS), we evaluated the extracellular microRNA profiles of CSF from different CNS tumor status including LM. Materials and Methods: We prospectively collected CSF from 65 patients of five groups of cancer control (CC), healthy control (HC), LM, brain metastasis (BM); and brain tumor (BT). Extracellular RNA was extracted from 2 mL of CSF after proper cell down, and preceded to small RNA microarray with Affymetrix miRNA 4.0 microarray chips. Results: The mean RNA yield of LM patients was significantly higher compared to that of other patients groups (9.28 vs. 6.30 ㎍, p = 0.003). The small RNA (< 70 nucleotides) percentage was the highest in controls than that of other groups (53% vs. 26%, p < 0.001). Among 6,599 small RNA probes, mature microRNAs showed higher expression than that of pre-microRNAs and small nucleolar RNAs. The number of probes with the Present call in all samples is 22 mature microRNAs, 18 pre-mature microRNAs, and 27 small nucleolar RNAs. Expression value of mature microRNAs regarding their direction of 5 prime (5p) and 3 prime (3p), the expression of 3p microRNA is higher than those of 5p microRNA in both LM and BM samples (p < 0.001). Both supervised and unsupervised hierarchical clustering of 263 microRNAs, which showed more than 2 fold change at a significance level of p < 0.05, can differentiate LM from other CNS tumor patient groups. Prediction analysis of microarray (PAM) identified 13 microRNAs differentiate LM group from others including hsa-miR-335-5p and hsa-miR-466. MicroRNA profiling using significance of analysis of microarrays (SAM) analysis did not differentiate HC and CC. Whereas CSF samples from patients with LM showed the most number of 108 differentially expressed (more than 2 fold change) microRNAs compared to control group and also revealed 36 differentially expressed microRNAs between LM and BM including hsa-miR-466, hsa-miR-190a-3p, hsa-miR-98-3p, hsa-miR-34b-3p and so on. Representative discriminative microRNAs from microarray data were confirmed their expression level by digital droplet PCR in available CSF samples among the microarray samples. Gene Set Enrichment Analysis was performed using both 10 highly expressed and 6 suppressed microRNAs between LM and BM after normalization and 13 microRNAs from PAM analysis. The most targeted pathway was ‘positive-/ negative-transcription from RNA polymerase II promoter followed by ‘positive regulation of transcription, DNA-templated’ by discriminative microRNAs. When pathways were denoted by microRNAs from PAM, the most enriched pathway was inflammatory response and transcription relative to immune response. Conclusion: We performed extracellular small RNA microarray successfully with small volume of CSF. Analysis of profiles of microRNA according to patients with various CNS tumor status suggested the unique profiles might responsible for leptomeningeal metastasis.

Dataset Information

Analytics of Cerebrospinal Fluid MicroRNA Quantitative PCR Studies.

Publications

Analytics of Cerebrospinal Fluid MicroRNA Quantitative PCR Studies.

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