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A modified protein marker panel to identify four consensus molecular subtypes in colorectal cancer using immunohistochemistry

Authors :
Li, Xingru
Larsson, Pär
Ljuslinder, Ingrid
Ling, Agnes
Löfgren Burström, Anna
Zingmark, Carl
Edin, Sofia
Palmqvist, Richard
Li, Xingru
Larsson, Pär
Ljuslinder, Ingrid
Ling, Agnes
Löfgren Burström, Anna
Zingmark, Carl
Edin, Sofia
Palmqvist, Richard
Publication Year :
2021

Abstract

Colorectal cancer (CRC) is a heterogeneous disease with different genetic and molecular backgrounds, leading to a diverse patient prognosis and treatment response. Four consensus molecular subtypes (CMS 1–4) have recently been proposed based on transcriptome profiling. A clinically practical immunohistochemistry (IHC) based CMS classifier consisting of the four markers FRMD6, ZEB1, HTR2B, and CDX2 was then demonstrated. However, the IHC-CMS classifier did not distinguish between CMS2 and CMS3 tumours. In this study, we have applied the proposed transcriptome based and IHC-based CMS classifiers in a CRC cohort of 65 patients and found a concordance of 77.5 %. Further, we modified the IHC-CMS classifier by analysing the differentially expressed genes between CMS2 and CMS3 tumours using RNA-sequencing data from the TCGA dataset. The result showed that WNT signalling was among the most upregulated pathways in CMS2 tumours, and the expression level of CTNNB1 (encoding β-catenin), a WNT pathway hallmark, was significantly upregulated (P = 1.15 × 10−6). We therefore introduced nuclear β-catenin staining to the IHC-CMS classifier. Using the modified classifier in our cohort, we found a 71.4 % concordance between the IHC and RNA-sequencing based CMS classifiers. Moreover, β-catenin staining could classify 16 out of the 19 CMS2/3 tumours into CMS2 or CMS3, thereby showing an 84.2 % concordance with the RNA-sequencing-based classifier. In conclusion, we evaluated CMS classifiers based on transcriptome and IHC analysis. We present a modified IHC panel that categorizes CRC tumours into the four CMS groups. To our knowledge, this is the first study using IHC to identify all four CMS groups.

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1248708544
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.prp.2021.153379