Abstract

Microsatellite instability (MSI) occurs across a number of cancers and is associated with different clinical characteristics when compared to microsatellite stable (MSS) cancers. As MSI cancers have different characteristics, routine MSI testing is now recommended for a number of cancer types including colorectal cancer (CRC). Using gene panels for sequencing of known cancer mutations is routinely performed to guide treatment decisions. By adding a number of MSI regions to a small gene panel, the efficacy of simultaneous MSI detection in a series of CRCs was tested. Tumour DNA from formalin-fixed, paraffin-embedded (FFPE) tumours was sequenced using a 23-gene panel kit (ATOM-Seq) provided by GeneFirst. The mismatch repair (MMR) status was obtained for each patient from their routine pathology reports, and compared to MSI predictions from the sequencing data. By testing 29 microsatellite regions in 335 samples the MSI status was correctly classified in 314/319 samples (98.4% concordance), with sixteen failures. By reducing the number of regions in silico, comparable performance could be reached with as few as eight MSI marker positions. This test represents a quick, and accurate means of determining MSI status in FFPE CRC samples, as part of a routine gene mutation assay, and can easily be incorporated into a research or diagnostic setting. This could replace separate mutation and MSI tests with no loss of accuracy, thus improving testing efficiency.

Details

Title
The ATOM-Seq sequence capture panel can accurately predict microsatellite instability status in formalin-fixed tumour samples, alongside routine gene mutation testing
Author
Srihar, Kanishta 1 ; Gusnanto, Arief 2 ; Richman, Susan D. 3 ; West, Nicholas P. 3 ; Galvin, Leanne 1 ; Bottomley, Daniel 3 ; Hemmings, Gemma 3 ; Glover, Amy 1 ; Natarajan, Subaashini 1 ; Miller, Rebecca 1 ; Arif, Sameira 1 ; Rossington, Hannah 4 ; Dunwell, Thomas L. 5 ; Dailey, Simon C. 5 ; Fontarum, Gracielle 5 ; George, Agnes 5 ; Wu, Winnie 5 ; Quirke, Phil 3 ; Wood, Henry M. 3 

 Leeds Institute of Medical Research at St James’s, University of Leeds, Pathology and Data Analytics, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403) 
 University of Leeds, Department of Statistics, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403) 
 Leeds Institute of Medical Research at St James’s, University of Leeds, Pathology and Data Analytics, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403); NIHR Leeds Biomedical Research Centre, Leeds, UK (GRID:grid.511501.1) (ISNI:0000 0004 8981 0543) 
 Leeds Institute of Medical Research at St James’s, University of Leeds, Pathology and Data Analytics, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403); University of Leeds, Leeds Institute of Data Analytics, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403) 
 GeneFirst Ltd., Abingdon, UK (GRID:grid.450809.0) 
Pages
21870
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3106879029
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.