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000177225 1001_ $$aDelaidelli, Alberto$$b0
000177225 245__ $$aClinically Tractable Outcome Prediction of non-WNT/non-SHH Medulloblastoma Based on TPD52 Immunohistochemistry in a Multicohort Study.
000177225 260__ $$aPhiladelphia, Pa. [u.a.]$$bAACR$$c2022
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000177225 500__ $$a2022 Jan 1;28(1):116-128
000177225 520__ $$aInternational consensus and the 2021 WHO classification recognize eight molecular subgroups among non-WNT/non-SHH (Group 3/4) medulloblastoma, representing ~60% of tumors. However, very few clinical centers worldwide possess the technical capabilities to determine DNA-methylation profiles or other molecular parameters of high-risk for Group 3/4 tumors. As a result, biomarker-driven risk stratification and therapy assignment constitutes a major challenge in medulloblastoma research. Here, we identify an immunohistochemistry (IHC) marker as a clinically tractable method for improved medulloblastoma risk stratification.We bioinformatically analyzed published medulloblastoma transcriptomes and proteomes identifying as a potential biomarker TPD52, whose IHC prognostic value was validated across three Group 3/4 medulloblastoma clinical cohorts (n = 387) treated with conventional therapies.TPD52 IHC positivity represented a significant independent predictor of early relapse and death for Group 3/4 medulloblastoma (HRs between 3.67-26.7 [95% CIs between 1.00-706.23], p = 0.05, 0.017 and 0.0058). Cross-validated survival models incorporating TPD52 IHC with clinical features outperformed existing state-of-the-art risk stratification schemes, and reclassified ~50% of patients into more appropriate risk categories. Finally, TPD52 immunopositivity was a predictive indicator of poor response to chemotherapy (HR 12.66 [95% CI 3.53-45.40], p < 0.0001), suggesting important implication for therapeutic choices.The current study redefines the approach to risk stratification in Group 3/4 medulloblastoma in global practice. Since integration of TPD52 IHC in classification algorithms significantly improved outcome prediction, this test could be rapidly adopted for risk stratification on a global scale, independently of advanced but technically challenging molecular profiling techniques.
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000177225 7001_ $$aDunham, Christopher$$b1
000177225 7001_ $$aSanti, Mariarita$$b2
000177225 7001_ $$00000-0001-7722-8888$$aNegri, Gian Luca$$b3
000177225 7001_ $$aTriscott, Joanna$$b4
000177225 7001_ $$aZheludkova, Olga$$b5
000177225 7001_ $$aGolanov, Andrey$$b6
000177225 7001_ $$aRyzhova, Marina$$b7
000177225 7001_ $$0P:(DE-He78)34b3639de467b2c700920d7cbc3d2110$$aOkonechnikov, Konstantin$$b8$$udkfz
000177225 7001_ $$0P:(DE-He78)e54a1e0999c1d8c95869ef9188b794cc$$aSchrimpf, Daniel$$b9$$udkfz
000177225 7001_ $$0P:(DE-He78)d20d08adc992abdb6ccffa1686f1ba17$$aStichel, Damian$$b10$$udkfz
000177225 7001_ $$00000-0003-1239-7757$$aEllison, David W$$b11
000177225 7001_ $$0P:(DE-He78)a8a10626a848d31e70cfd96a133cc144$$avon Deimling, Andreas$$b12$$udkfz
000177225 7001_ $$0P:(DE-He78)4c28e2aade5f44d8eca9dd8e97638ec8$$aKool, Marcel$$b13$$udkfz
000177225 7001_ $$0P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9$$aPfister, Stefan$$b14$$udkfz
000177225 7001_ $$00000-0002-6557-895X$$aRamaswamy, Vijay$$b15
000177225 7001_ $$0P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93$$aKorshunov, Andrey$$b16$$udkfz
000177225 7001_ $$aTaylor, Michael D$$b17
000177225 7001_ $$aSorensen, Poul H$$b18
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