Background: Most eukaryotic genes produce different transcripts of multiple isoforms by inclusion or exclusion of particular exons. The isoforms of a gene often play diverse functional roles and thus, it is necessary to accurately measure isoform expressions as well as the genes'. While previous studies have demonstrated the strong agreement between mRNA-sequencing (RNA-seq) and array-based gene and/or isoform quantification platforms (Microarray gene expression and Exon-array), the more recently developed NanoString platform has not been systematically evaluated and compared, especially in large-scale studies across different cancer domains.
Results: In this paper, we present a large-scale comparative study among RNA-seq, NanoString, array-based and RT-qPCR platforms using 46 cancer cell lines across different cancer types to understand and evaluate the calibers of the platforms for measuring gene and isoform expressions in cancer studies. We first performed NanoString experiments on 59 cancer cell lines with 403 custom-designed probes for measuring the expressions of 405 isoforms in 155 genes and additional RT-qPCR experiments for a subset of the measured isoforms in 13 cell lines, and then combined the data with the matched RNA-seq, Exon-array and Microarray data of 46 of the 59 cell lines for the comparative analysis.
Conclusion: In the comparisons of the platforms for evaluating expressions at both isoform and gene levels, we found that (1) the degree of agreement across platforms on quantifying isoform expressions is lower than gene expressions; (2) NanoString and Exon-array are not consistent on isoform quantification even though both techniques are based on hybridization reactions; (3) RT-qPCR experiments are more consistent with RNA-seq quantification results on isoform-level compared to NanoString and Exon-array; (4) different RNA-seq isoform quantification algorithms showed inconsistent results, and two isoform quantification methods Net-RSTQ and eXpress are more consistent across the platforms in the comparison; (5) RNA-seq has the best overall consistent with the other platforms on gene expression quantification.