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

• Published in: Gynecologic oncology Vol. 149; no. 1; pp. 173 - 180
• Main Authors: Huvila, Jutta, Laajala, Teemu D., Edqvist, Per-Henrik, Mardinoglu, Adil, Talve, Lauri, Pontén, Fredrik, Grénman, Seija, Carpén, Olli, Aittokallio, Tero, Auranen, Annika
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.04.2018
• Subjects: adult; aged; antineoplastic agent; asrg1 protein; ASRGL1; brachytherapy; cancer chemotherapy; cancer grading; cancer recurrence; cancer surgery; cancer survival; disease specific survival; Endometrial cancer; endometrium carcinoma; epidermal growth factor receptor 2; estrogen receptor; female; follow up; high risk patient; histopathology; human; human tissue; immunohistochemistry; immunoreactivity; Ki 67 antigen; l1cam protein; low risk patient; major clinical study; middle aged; Modelling; MutL protein homolog 1; overall survival; p53; priority journal; progesterone receptor; Prognostic; protein p53; recurrence free survival; recurrent disease; Risk stratification; tissue microarray; tumor marker; unclassified drug; Modelling; Endometrial cancer; Prognostic; ASRGL1; Risk stratification; p53
• DOI: 10.1016/j.ygyno.2018.02.016
• ISSN: 0090-8258; 1095-6859

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. 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. 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- (29.5%) 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. 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. •ASRGL1 is a promising biomarker in endometrioid endometrial cancer.•An immunopanel consisting of p53 and ASRGL1 is a useful tool in EEC risk assessment.•Different EEC subgroups can be characterized using sophisticated statistical methods.