Identification of Endogenous Control miRNAs for RT-qPCR in T-Cell Acute Lymphoblastic Leukemia

Abstract

Optimal endogenous controls enable reliable normalization of microRNA (miRNA) expression in reverse-transcription quantitative PCR (RT-qPCR). This is particularly important when miRNAs are considered as candidate diagnostic or prognostic biomarkers. Universal endogenous controls are lacking, thus candidate normalizers must be evaluated individually for each experiment. Here we present a strategy that we applied to the identification of optimal control miRNAs for RT-qPCR profiling of miRNA expression in T-cell acute lymphoblastic leukemia (T-ALL) and in normal cells of T-lineage. First, using NormFinder for an iterative analysis of miRNA stability in our miRNA-seq data, we established the number of control miRNAs to be used in RT-qPCR. Then, we identified optimal control miRNAs by a comprehensive analysis of miRNA stability in miRNA-seq data and in RT-qPCR by analysis of RT-qPCR amplification efficiency and expression across a variety of T-lineage samples and T-ALL cell line culture conditions. We then showed the utility of the combination of three miRNAs as endogenous normalizers (hsa-miR-16-5p, hsa-miR-25-3p, and hsa-let-7a-5p). These miRNAs might serve as first-line candidate endogenous controls for RT-qPCR analysis of miRNAs in different types of T-lineage samples: T-ALL patient samples, T-ALL cell lines, normal immature thymocytes, and mature T-lymphocytes. The strategy we present is universal and can be transferred to other RT-qPCR experiments.

NormiRazor: tool applying GPU-accelerated computing for determination of internal references in microRNA transcription studies

“…a Py a CUDA (4) where a Py and a CUDA are coefficients from models for Python and CUDA implementations, respectively. Standard deviation (SD) of the speed-up was calculated according to [27] as:…”

“…Otherwise, those inaccuracies could shadow true biologically relevant differences. Many normalization strategies have been already suggested, but the problem is still considered open to new proposals, especially in those areas where intensive studies have been started only recently [3,4]. One of such fields, that prompted our group to review available normalization algorithms, is research on circulating microRNAs (miRNAs) as potential biomarkers [5,6].…”

“…A new algorithm was therefore proposed that instead of analyzing only single miRNAs, also calculates stability scores for all of their 2-and 3-element combinations in geNorm (GN), NormFinder (NF or NFG when samples' groups are provided) and BestKeeper (BK). It was proven that combination-based normalizers are statistically better than single reference genes in terms of stability [4]. Moreover, it was showed that in many cases the most stable reference is formed by averaging expression of 2 or 3 miRNAs that do not necessarily score the highest when analyzed separately [24].…”

A Pseudo-Temporal Causality Approach to Identifying miRNA-mRNA Interactions During Biological Processes

“…Several studies have linked these miRNAs to different types of cancer. "hsa-miR-16-5p" appears to have a significant role in chronic lymphocytic leukemia [31] and periocular Sebaceous Gland Carcinoma [32]. "hsa-miR-182-5p" has been related with colorectal cancer [33], drug resistance in breast cancer cell lines [34], Epithelial Ovarian Cancer [35] and lung adenocarcinoma [36].…”

Comparison of a new immunoassay and PCR-based method for quantification of microRNAs in whole blood. A pilot methodical study

“…Therefore, it is not surprising that aberrant miRNA expression is involved in the pathogenesis of many diseases including cardiovascular diseases, neurodegenerative diseases, hematologic diseases, osteologic diseases and cancer. To this day, more than 2,650 different microRNAs have been described in various documents [2][3][4][5][6][7][8][9][10][11][12] .…”