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Application of the Interaction between Tissue Immunohistochemistry Staining and Clinicopathological Factors for Evaluating the Risk of Oral Cancer Progression by Hierarchical Clustering Analysis: A Case-Control Study in a Taiwanese Population.

Authors :
Wang HC
Chou MC
Wu CC
Chan LP
Moi SH
Pan MR
Liu TC
Yang CH
Source :
Diagnostics (Basel, Switzerland) [Diagnostics (Basel)] 2021 May 21; Vol. 11 (6). Date of Electronic Publication: 2021 May 21.
Publication Year :
2021

Abstract

The aim of this single-center case-control study is to investigate the feasibility and accuracy of oral cancer protein risk stratification (OCPRS) to analyze the risk of cancer progression. All patients diagnosed with oral cancer in Taiwan, between 2012 and 2014, and who underwent surgical intervention were selected for the study. The tissue was further processed for immunohistochemistry (IHC) for 21 target proteins. Analyses were performed using the results of IHC staining, clinicopathological characteristics, and survival outcomes. Novel stratifications with a hierarchical clustering approach and combinations were applied using the Cox proportional hazard regression model. Of the 163 participants recruited, 102 patients were analyzed, and OCPRS successfully identified patients with different progression-free survival (PFS) profiles in high-risk (53 subjects) versus low-risk (49 subjects) groups ( p = 0.012). OCPRS was composed of cytoplasmic PLK1, phosphoMet, and SGK2 IHC staining. After controlling for the influence of clinicopathological features, high-risk patients were 2.33 times more likely to experience cancer progression than low-risk patients ( p = 0.020). In the multivariate model, patients with extranodal extension (HR = 2.66, p = 0.045) demonstrated a significantly increased risk for disease progression. Risk stratification with OCPRS provided distinct PFS groups for patients with oral cancer after surgical intervention. OCPRS appears suitable for routine clinical use for progression and prognosis estimation.

Details

Language :
English
ISSN :
2075-4418
Volume :
11
Issue :
6
Database :
MEDLINE
Journal :
Diagnostics (Basel, Switzerland)
Publication Type :
Academic Journal
Accession number :
34063938
Full Text :
https://doi.org/10.3390/diagnostics11060925