Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma

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http://hdl.handle.net/10138/301855

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Huvila , J , Laajala , T D , Edqvist , P-H , Mardinoglu , A , Talve , L , Ponten , F , Grenman , S , Carpen , O , Aittokallio , T & Auranen , A 2018 , ' Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma ' , Gynecologic Oncology , vol. 149 , no. 1 , pp. 173-180 . https://doi.org/10.1016/j.ygyno.2018.02.016

Title: Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma
Author: Huvila, Jutta; Laajala, Teemu D.; Edqvist, Per-Henrik; Mardinoglu, Adil; Talve, Lauri; Ponten, Fredrik; Grenman, Seija; Carpen, Olli; Aittokallio, Tero; Auranen, Annika
Contributor: University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, HUSLAB
University of Helsinki, Tero Aittokallio / Principal Investigator
Date: 2018-04
Language: eng
Number of pages: 8
Belongs to series: Gynecologic Oncology
ISSN: 0090-8258
URI: http://hdl.handle.net/10138/301855
Abstract: Objective. In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. Methods. A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. Results. A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (295%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P <0.001) of dying of EEC compared to the low-risk group. Conclusions. P53 and ASRGL1 immunoprofiling stratifies EEC patients into three risk groups with significantly different outcomes. This simple and easily applicable panel could provide a useful tool in EEC risk stratification and guiding the allocation of treatment modalities. (C) 2018 Elsevier Inc. All rights reserved.
Subject: Endometrial cancer
Risk stratification
Prognostic
Modelling
ASRGL1
p53
L1CAM EXPRESSION
REGULARIZATION PATHS
COORDINATE DESCENT
CANCER
RISK
CLASSIFICATION
PROFILES
DISEASE
UTILITY
SYSTEM
3122 Cancers
3123 Gynaecology and paediatrics
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