A Low-cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-relevant Subtypes
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA395057 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5838030_1.fastq.gz | Fastqsanger.gz | |||
| SRR5838030_2.fastq.gz | Fastqsanger.gz | |||
| SRR5838040_1.fastq.gz | Fastqsanger.gz | |||
| SRR5838040_2.fastq.gz | Fastqsanger.gz | |||
| SRR5838031_1.fastq.gz | Fastqsanger.gz |
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Project description:Objective: In order to personalise standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed a low-cost multiplex biomarker assay. Design: Three cohorts of primary (except one liver metastases) untreated and fresh frozen CRC samples (n=57) profiled by microarray and RNA-Seq were analyzed. A reduced 38-gene panel (CRCAssigner-38) was selected from the 786-gene CRCAssigner signature (CRCAssigner-786) using an in-house class prediction approach. A customised NanoString Technologies’ nCounter platform-based assay (NanoCRCAssigner) was developed for comparison with different classifiers (CMS subtypes), platforms (microarrays and RNA-Seq), and gene sets (CRCAssigner-38 and CRCAssigner-786). Results: NanoCRCAssigner classified samples (n=48; except those showing a mixture of subtypes) into all five CRCAssigner subtypes with overall high concordance across platforms (>87%) and with CMS subtypes (81%) irrespective of variable tumour cellularity. The association of subtypes with their known molecular (microsatellite-instable and stemness), mutational (KRAS/BRAF), and clinical characteristics (including overall survival) further demonstrated assay validity. To reduce costs, we switched from standard protocol to a low-cost protocol with a high Pearson correlation co-efficient (0.9) between protocols. Technical replicates were highly correlated (0.98).
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