Emma Camacho-Urkaray1, Jorge Santos-Juanes2, Francisco Borja Gutiérrez-Corres1, Beatriz García3,4, Luis M Quirós3,4, Isabel Guerra-Merino1, José Javier Aguirre1, Iván Fernández-Vega5,6,7. 1. Department of Pathology, Hospital Universitario de Araba-Txagorritxu, Vitoria-Gasteiz, Spain. 2. Department of Pathology, Hospital Universitario Central de Asturias, Oviedo, Spain. 3. Department of Functional Biology, University of Oviedo, Oviedo, Spain. 4. Instituto Universitario Fernández-Vega, Oviedo, Spain. 5. Department of Pathology, Hospital Universitario de Araba-Txagorritxu, Vitoria-Gasteiz, Spain. ivan_fernandez_vega@hotmail.com. 6. Department of Pathology, Hospital Universitario Central de Asturias, Oviedo, Spain. ivan_fernandez_vega@hotmail.com. 7. Instituto Universitario Fernández-Vega, Oviedo, Spain. ivan_fernandez_vega@hotmail.com.
Abstract
PURPOSE: Glioblastoma (GBM) ranks among the most challenging cancers to treat and there is an urgent need for clinically relevant prognostic and diagnostic biomarkers. Here, we set out to investigate the expression of eight proteins (bcl-2, cyclin D1, p16, p21, p27, p53, Sox11 and WT1) in GBM with the specific aim to establish immunohistochemistry cut-off points with clinical relevance. METHODS: Immunohistochemistry (IHC) was used to examine protein expression in 55 surgical GBM specimens using H-scores, and IHC cut-off points were established using the Cutoff Finder web platform. Protein co-expression and its correlation with histopathological features were assessed, and cases were classified according to IDH1 mutation status. Survival curves were determined using Kaplan-Meier analyses. RESULTS: Clinical and molecular parameters found to be correlated with overall survival (OS) were tumor size (r = -0.278; p = 0.048), p53 (r = -0.452; p = 0.001), p16 (r = 0.351; p = 0.012) and Sox11 (r = 0.324; p = 0.020). In addition, we found that tumor size correlated with cyclin D1 (r = -0.282; p = 0.037), p53 (r = 0.269; p = 0.041), Sox11 (r = -0.309; p = 0.022) and WT1 (r = -0.372; p = 0.003). Variables found to be significantly associated with IDH1 mutation status were OS (p < 0.01), age (p < 0.01), cyclin D1 (p = 0.046), p16 (p = 0.019) and Sox11 (p = 0.012). Variables found to be significantly associated with a poor survival were tumor size >5 cm (p < 0.001), bcl-2 score > 40 (p = 0.034), cyclin D1 score ≤ 70 (p = 0.004), p16 score ≤ 130 (p = 0.005), p53 score > 20 (p = 0.003), Sox11 score ≤ 40 (p < 0.001) and WT1 score ≤ 270 (p = 0.02). CONCLUSIONS: Correlations between protein biomarkers and main clinical GBM variables were identified. The establishment of distinct biomarker cut-off points may enable clinicians and pathologists to better weigh their prognostic value.
PURPOSE:Glioblastoma (GBM) ranks among the most challenging cancers to treat and there is an urgent need for clinically relevant prognostic and diagnostic biomarkers. Here, we set out to investigate the expression of eight proteins (bcl-2, cyclin D1, p16, p21, p27, p53, Sox11 and WT1) in GBM with the specific aim to establish immunohistochemistry cut-off points with clinical relevance. METHODS: Immunohistochemistry (IHC) was used to examine protein expression in 55 surgical GBM specimens using H-scores, and IHC cut-off points were established using the Cutoff Finder web platform. Protein co-expression and its correlation with histopathological features were assessed, and cases were classified according to IDH1 mutation status. Survival curves were determined using Kaplan-Meier analyses. RESULTS: Clinical and molecular parameters found to be correlated with overall survival (OS) were tumor size (r = -0.278; p = 0.048), p53 (r = -0.452; p = 0.001), p16 (r = 0.351; p = 0.012) and Sox11 (r = 0.324; p = 0.020). In addition, we found that tumor size correlated with cyclin D1 (r = -0.282; p = 0.037), p53 (r = 0.269; p = 0.041), Sox11 (r = -0.309; p = 0.022) and WT1 (r = -0.372; p = 0.003). Variables found to be significantly associated with IDH1 mutation status were OS (p < 0.01), age (p < 0.01), cyclin D1 (p = 0.046), p16 (p = 0.019) and Sox11 (p = 0.012). Variables found to be significantly associated with a poor survival were tumor size >5 cm (p < 0.001), bcl-2 score > 40 (p = 0.034), cyclin D1 score ≤ 70 (p = 0.004), p16 score ≤ 130 (p = 0.005), p53 score > 20 (p = 0.003), Sox11 score ≤ 40 (p < 0.001) and WT1 score ≤ 270 (p = 0.02). CONCLUSIONS: Correlations between protein biomarkers and main clinical GBM variables were identified. The establishment of distinct biomarker cut-off points may enable clinicians and pathologists to better weigh their prognostic value.
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