Please use this identifier to cite or link to this item: https://doi.org/10.18632/oncotarget.18568
Title: A three gene immunohistochemical panel serves as an adjunct to clinical staging of patients with head and neck cancer
Authors: Ong C.-A.J. 
Shannon N.B.
Mueller S.
Lek S.M.
Qiu X.
Chong F.T.
Li K.
Koh K.K.N.
Tay G.C.A. 
Skanthakumar T.
Hwang J.S.G. 
Lim T.K.H. 
Ang M.K. 
Tan D.S.W. 
Tan N.-C. 
Tan H.K. 
Soo K.C. 
Iyer N.G. 
Keywords: biological marker
adult
aged
algorithm
Article
automation
cancer prognosis
cancer staging
cancer survival
copy number variation
female
gene expression
gene identification
genetic marker
head and neck cancer
human
human tissue
immunohistochemistry
major clinical study
male
overall survival
prediction
tissue microarray
Issue Date: 2017
Publisher: Impact Journals LLC
Citation: Ong C.-A.J., Shannon N.B., Mueller S., Lek S.M., Qiu X., Chong F.T., Li K., Koh K.K.N., Tay G.C.A., Skanthakumar T., Hwang J.S.G., Lim T.K.H., Ang M.K., Tan D.S.W., Tan N.-C., Tan H.K., Soo K.C., Iyer N.G. (2017). A three gene immunohistochemical panel serves as an adjunct to clinical staging of patients with head and neck cancer. Oncotarget 8 (45) : 79556-79566. ScholarBank@NUS Repository. https://doi.org/10.18632/oncotarget.18568
Abstract: Background: Current management of head and neck squamous cell carcinoma (HNSCC) depends on tumor staging. Despite refinements in clinical staging algorithms, outcomes remain unchanged for the last two decades. In this study, we set out to identify a small, clinically applicable molecular panel to aid prognostication of patients with HNSCC. Materials and Methods: Data from The Cancer Genome Atlas (TCGA) was used to derive copy number aberrations and expression changes to identify putative prognostic genes. To account for cross entity relevance of the biomarkers, HNSCC (n = 276), breast (n = 808) and lung cancer (n = 282) datasets were used to identify robust and reproducible markers with prognostic potential. Validation was performed using immunohistochemistry (IHC) on tissue microarrays of an independent cohort of HNSCC (n = 333). Findings: Using GISTIC algorithm together with gene expression analysis, we identified six putative prognostic genes in at least two out of three cancers analyzed, of which four were successfully optimized for automated IHC. Of these, three were successfully validated; each molecular target being significantly prognostic on univariate analysis. Patients were differentially segregated into four prognostic groups based on the number of genes dysregulated (p < 0.001). The IHC panel remained an independent predictor of survival after adjusting for known survival covariates including clinical staging criteria in a multivariate Cox regression model (p < 0.001). Interpretation: We have identified and validated a clinically applicable IHC biomarker panel that is independently associated with overall survival. This panel is readily applicable, serving as a useful adjunct to current staging systems and provides novel targets for future therapeutic strategies. © Ong et al.
Source Title: Oncotarget
URI: https://scholarbank.nus.edu.sg/handle/10635/174501
ISSN: 1949-2553
DOI: 10.18632/oncotarget.18568
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