Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes

Chanthirika Ragulan,Larissa Sena Teixeira Mendes ,Elisa Fontana,Iain Beehuat Tan,Aldo Scarpa,Andrés Cervantes,Maguy Del Rio,Gift Nyamundanda,Noelia Tarazona,Katherine Eason,Wei Tan ,Francesco Sclafani,Si-Lin Koo,David Cunningham,Pawan Poudel,Rita T Lawlor,Pierre Martineau,Yatish Patil,Ruwaida Begum,Anguraj Sadanandam

doi:10.1038/s41598-019-43492-0

Abstract

Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond.

Highlights

IntroductionFrom two different datasets that included drug response information, we observed increased responses within the stem-like subtype to irinotecan, fluorouracil and leucovorin treatment combination (FOLFIRI), and within the TA subtype to the anti-EGFR monoclonal antibody cetuximab[3,4,5] using small sample size cohorts
To address the ambiguity caused by these independent studies reaching differing conclusions, these and our findings were aggregated by our CRC Subtyping Consortium (CRCSC) into 4 consensus molecular subtypes (CMS): CMS1; CMS2; CMS3; and CMS4, plus a “mixed” subtype representing either the existence of additional subtypes or the presence of multiple subtypes in a single sample[13]
In order to develop an analytical method to classify CRC samples into subtypes, we initially developed a custom nCounter assay using a 50-gene panel (Supplementary Table S1d; 48 of which overlap with the original 786-gene signature; see Materials and Methods)

Summary

Introduction

From two different datasets that included drug response information, we observed increased responses within the stem-like subtype to irinotecan, fluorouracil and leucovorin treatment combination (FOLFIRI), and within the TA subtype to the anti-EGFR monoclonal antibody cetuximab[3,4,5] using small sample size cohorts. These treatment responses were further validated by other studies[6,7]. A summary of the classifiers utilised in this study is given in Supplementary Table S1b

Methods

Results

Conclusion