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Immunohistochemistry for Myc Predicts Survival in Colorectal Cancer

Overview of attention for article published in PLOS ONE, February 2014
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Title
Immunohistochemistry for Myc Predicts Survival in Colorectal Cancer
Published in
PLOS ONE, February 2014
DOI 10.1371/journal.pone.0087456
Pubmed ID
Authors

Christopher W. Toon, Angela Chou, Adele Clarkson, Keshani DeSilva, Michelle Houang, Joseph C. Y. Chan, Loretta L. Sioson, Lucy Jankova, Anthony J. Gill

Abstract

MYC over-expression as determined by molecular means has been reported as a favorable prognostic biomarker in colorectal carcinoma (CRC). However MYC expression analysis is not available in the routine clinical setting. We investigated whether immunohistochemistry (IHC) for the myc protein using a novel commercially available rabbit monoclonal antibody [clone Y69] which is currently in widespread clinical use for lymphoma diagnosis could be used to predict outcome in resected CRC. Myc IHC was performed on a tissue microarray (TMA) comprising a retrospective cohort of 1421 CRC patients and scored blinded as to all clinical and pathological data. IHC was also performed on a subcohort of whole section CRCs to assess staining characteristics and concordance with TMA expression. MYC over-expression was found in 980 (69%) of CRCs and was associated with tumor stage and DNA mismatch repair/BRAF status. There was substantial agreement between TMA and whole section myc IHC (kappa = 0.742, p<0.01). CRCs with MYC over-expression demonstrated improved 5-year survival (93.2% vs. 57.3%), with the effect significantly modulated by the dominant effect of tumor stage, age at diagnosis and lymphovascular space invasion status on survival. We conclude that myc status as determined by IHC alone can be used to predict overall survival in patients with CRC undergoing surgical resection.

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Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Student > Bachelor 5 12%
Student > Master 4 9%
Student > Doctoral Student 2 5%
Student > Postgraduate 2 5%
Other 5 12%
Unknown 14 33%
Readers by discipline Count As %
Medicine and Dentistry 9 21%
Biochemistry, Genetics and Molecular Biology 9 21%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Social Sciences 2 5%
Agricultural and Biological Sciences 1 2%
Other 5 12%
Unknown 15 35%