Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

Philip D. Dunne (), Matthew Alderdice, Paul G. O'Reilly, Aideen C. Roddy, Amy M. B. McCorry, Susan Richman, Tim Maughan, Simon S. McDade, Patrick G. Johnston, Daniel B. Longley, Elaine Kay, Darragh G. McArt and Mark Lawler ()
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Philip D. Dunne: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Matthew Alderdice: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Paul G. O'Reilly: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Aideen C. Roddy: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Amy M. B. McCorry: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Susan Richman: Leeds Institute of Cancer and Pathology, St James Hospital
Tim Maughan: CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford
Simon S. McDade: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Patrick G. Johnston: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Daniel B. Longley: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Elaine Kay: Beaumont Hospital and Royal College of Surgeons in Ireland
Darragh G. McArt: Centre for Cancer Research and Cell Biology, Queen’s University Belfast
Mark Lawler: Centre for Cancer Research and Cell Biology, Queen’s University Belfast

Nature Communications, 2017, vol. 8, issue 1, 1-12

Abstract: Abstract Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH.

Date: 2017
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DOI: 10.1038/ncomms15657

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