Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System

Abstract

Purpose: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with distinct molecular subtypes. The most established subtyping approach, the "Cell of Origin" (COO) algorithm, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Recently developed immunohistochemical (IHC) techniques and other established methodologies can deliver discordant results and have various technical limitations. We evaluated the NanoString nCounter gene expression system to address issues with current platforms.Experimental Design: We devised a scoring system using 145 genes from published datasets to categorize DLBCL samples. After cell line validation, clinical tissue segmentation was tested using commercially available diagnostic DLBCL samples. Finally, we profiled biopsies from patients with relapsed/refractory DLBCL enrolled in the fostamatinib phase IIb clinical trial using three independent RNA expression platforms: NanoString, Affymetrix, and qNPA.Results: Diagnostic samples showed a typical spread of subtypes with consistent gene expression profiles across matched fresh, frozen, and formalin-fixed paraffin-embedded tissues. Results from biopsy samples across platforms were remarkably consistent, in contrast to published IHC data. Interestingly, COO segmentation of longitudinal fostamatinib biopsies taken at initial diagnosis and then again at primary relapse showed 88% concordance (15/17), suggesting that COO designation remains stable over the course of disease progression.Conclusions: DLBCL segmentation of patient tumor samples is possible using a number of expression platforms. However, we found that NanoString offers the most flexibility and fewest limitations in regards to robust clinical tissue subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice.

Evaluating Robustness and Sensitivity of the NanoString Technologies nCounter Platform to Enable Multiplexed Gene Expression Analysis of Clinical Samples

“…Encouragingly, the difference in matching fresh and frozen replicates was comparable with that seen with technical replicates. The quantitative correlation was also very robust (11), demonstrating that the nCounter platform can generate high-quality data on FFPE material to enable clinically relevant mRNA gene expression studies. Numerous other publications have independently confirmed this conclusion (1-4).…”

“…The Nanostring Technologies nCounter platform is a relatively new technology and has been used within various clinical and research applications (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13). The automated nCounter platform hybridizes fluorescent barcodes directly to specific nucleic acid sequences, allowing for the nonamplified measurement of up to 800 targets within one sample (1,14).…”

“…The automated nCounter platform hybridizes fluorescent barcodes directly to specific nucleic acid sequences, allowing for the nonamplified measurement of up to 800 targets within one sample (1,14). A number of papers have shown that the Nanostring platform is comparable with other technologies (11,12,14); however, these studies have not assessed the limit of detection (LOD) and the robustness of the platform, which is essential when evaluating precious clinical trial samples.…”

Integrative mRNA-microRNA analyses reveal novel interactions related to insulin sensitivity in human adipose tissue

“…MicroRNA gene expression was measured using the nCounter Human v1 microRNA Expression Assay (NanoString Technologies, Seattle, WA) (14,31,40). RNA (100 ng) from each biopsy was hybridized with the nCounter probe set.…”

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

“…A more targeted, smaller miRNA array was then constructed, lowering the per sample cost and allowing for much larger cohorts to be analyzed in a cost-effective manner in order to validate and refine signatures and biomarkers. The gene expression platform assay system strikes a balance between the traditional exploratory nature of the microarray and more targeted, hypothesis-driven data collection to refine and test molecular signatures and biomarkers [14][15][16] . The method will be used to examine molecular and protein perturbations in in vivo and in vitro models where the described target miRNAs are experimentally over-expressed or inhibited.…”