Technical differences between sequencing and microarray platforms impact transcriptomic subtyping of colorectal cancer

Cancer Lett. 2020 Jan 28;469:246-255. doi: 10.1016/j.canlet.2019.10.040. Epub 2019 Oct 31.


Gene expression profiling has increasing relevance in the molecular screening of patients with colorectal cancer (CRC). We investigated potential platform-specific effects on transcriptomic subtyping according to established frameworks by comparisons of expression profiles from RNA sequencing and exon-resolution microarrays in 126 primary microsatellite stable CRCs. There was a strong platform correspondence in global gene expression levels, albeit with systematic technical bias likely attributed to few sequencing reads covering short (<2000 nucleotides) and/or lowly expressed genes (<1 FPKM), as well as over-saturation of highly expressed genes on microarrays. Classification concordances according to both the consensus molecular subtypes and CRC intrinsic subtypes (CRIS) were also strong, but with disproportionate subtype distributions between platforms caused by frequent disagreements in adherence to sample classification thresholds. Subtypes defined largely by genes expressed at low levels, including the CRIS-D subtype and the estimated level of tumor-infiltrating cytotoxic lymphocytes, had a weaker correspondence in classification metrics between platforms. In conclusion, even subtle differences between platforms suggest that clinical translation of transcriptomic CRC subtyping frameworks is dependent on assay standardization, and systematic technical biases reinforce the need for careful selection of classifier genes.

Keywords: CRC intrinsic subtypes; Classification concordance; Colorectal cancer; Consensus molecular subtypes; Microarray; RNA sequencing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor
  • Colorectal Neoplasms / classification
  • Colorectal Neoplasms / genetics*
  • Colorectal Neoplasms / pathology
  • Exons / genetics
  • Gene Expression Profiling / methods
  • Gene Expression Regulation, Neoplastic / genetics*
  • Humans
  • Microarray Analysis*
  • Mutation / genetics
  • Sequence Analysis, RNA / methods
  • Transcriptome / genetics*


  • Biomarkers, Tumor