Cross-comparison of high-throughput platforms for circulating mcroRNA in non small cell lung cancer - TaqMan OpenArray Advanced

This study focuses on platform comparison to assess performance variability in circulating microRNA (ct-miR) detection, agreement in assignment of a miR signature classifier (MSC) and concordance for the identification of cancer-associated miRs in plasma samples from non‐small cell lung cancer (NSCLC) patients. A plasma cohort of 10 NSCLC patients and 10 healthy donors matched for clinical features and MSC risk level was profiled for miRs expression using two sequencing- and three quantitative PCR (qPCR)-based platforms. Intra- and inter-platform variations were examined by correlation and concordance analysis. MSC risk levels were compared to those estimated using a reference method. Differentially expressed ct-miRs were identified among NSCLC patients and donors and the diagnostic value of those dysregulated in patients was assessed by receiver operating characteristic curve analysis. Downregulation of miR-150-5p was verified by qPCR. The Cancer Genome Atlas (TCGA) lung carcinoma dataset was used for validation at tissue level. Intra-platform reproducibility was consistent whereas the highest values of inter-platform correlations were among qPCR-based platforms. MSC classification concordance was >80% for four platforms. Dysregulation and discriminatory power of miR-150-5p and -210-3p were documented. Both were significantly dysregulated also on TCGA tissue-originated profiles from lung cell carcinoma in comparison to normal samples. Overall, our studies provide a large performance analysis between five different platforms for miRs quantification, indicate the solidity of MSC classifier and identify two noninvasive biomarkers for NSCLC A total of 20 human specimens were employed for this study, which included plasma from NSCLC patients (n=10) and, as control, healthy subjects (n=10), matched for age, sex, smoking status and MSC risk score RNA aliquots from these samples, including duplicates, one from a patient and two for donors, obtained from two independent RNA extractions from aliquots of the same plasma, were profiled by the following four high-throughput technological platforms: Taqman OpenArray Human miR and Taqman OpenArray Human Advanced miR Panels (Thermo Fisher Scientific); miRCURY LNA miR miRNome PCR Panels (Qiagen); QiaSeq miRNA Library (Qiagen). The fifth platform, EdgeSeq miR Whole Transcriptome Assay (HTG Molecular Diagnostics) employed, instead, crude blood plasma as starting material. All the statistical and bioinformatic analysis were performed using the R statistical program v 3.6.1. Annotation was performed according to the miRBase v21 available for each platform and downloaded from each manufacturers’ website. We studied: i) performance of miR expression profiling within platforms; ii) reproducibility of miR profiling intra-platform; iii) cross-platform comparison; iv) Cross-platform concordance in the assignement of a clinical validated miR risk score; v) differential ct-miR expression in NSCLC patients compared to control group; vi) fidelity of fold-change across platforms; vii) identification and validation of potential NSCLC biomarkers.