Clinical Research Papers:
A three gene immunohistochemical panel serves as an adjunct to clinical staging of patients with head and neck cancer
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Chin-Ann J. Ong1,3,*, Nicholas B. Shannon2,*, Stefan Mueller3,7,*, Sze Min Lek2,*, Xuan Qiu1, Fui Teen Chong4, Ke Li2, Kelvin K.N. Koh2, Gerald C.A. Tay1,7, Thakshayeni Skanthakumar3, Jacqueline S.G. Hwang5, Tony Kiat Hon Lim5, Mei Kim Ang6, Daniel S.W. Tan6, Ngian-Chye Tan7, Hiang Khoon Tan7, Khee Chee Soo7 and N. Gopalakrishna Iyer2,4,7
1Department of General Surgery, Singapore General Hospital, S169856, Singapore
2Cancer and Stem Cell Biology, Duke-NUS Graduate Medical School, S169857, Singapore
3Division of Surgical Oncology, National Cancer Centre, S169610, Singapore
4Cancer Therapeutics Research Laboratory, National Cancer Centre, S169610, Singapore
5Department of Anatomical Pathology, Singapore General Hospital, S169856, Singapore
6Department of Medical Oncology, National Cancer Centre, S169610, Singapore
7Singhealth Duke-NUS Head and Neck Centre, Singhealth, S169856, Singapore
*These authors contributed equally to this work
N. Gopalakrishna Iyer, email: firstname.lastname@example.org
Keywords: head and neck squamous cell carcinoma, immunohistochemistry, genomics
Received: February 21, 2017 Accepted: June 08, 2017 Published: June 19, 2017
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.
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