Clinical implementation of integrated molecular-morphologic risk prediction for meningioma.
Clinical implementation of integrated molecular-morphologic risk prediction for meningioma.
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DOI：
10.1111/bpa.13132
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发表时间：
2023-05
期刊：
影响因子：
--
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中科院分区：
文献类型：
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直到最近，脑膜瘤肿瘤的风险预测几乎完全基于肿瘤的形态特征。为了改进风险预测，已经建立了多种模型，将形态学和分子特征纳入综合风险预测评分。其中一种模型是综合分子形态脑膜瘤综合评分（IntS），它将分数分配给组织学分级、表观遗传甲基化家族和特定拷贝数变异。 IntS 发布后，神经病理学界对 IntS 的实际和临床实施提出了疑问，特别是关于 CNV 的调用、脑肿瘤分类器新版本 (v12.5) 的适用性以及在 IntS 计算中纳入 TERT 启动子和 CDKN2A/B 状态分析的必要性。为了调查和验证这些问题，对用于 IntS 发现和验证的发现 (n = 514)、回顾性验证 (n = 184) 和前瞻性验证 (n = 287) 队列进行了额外分析。我们的研究结果表明，任何超过 5% 的染色体臂丢失都足以调用 CNV，来自 v12.5 分类器的输入与专用脑膜瘤分类器 (v2.4) 一样好或更好，并且在为个体患者定义 IntS 时，很可能不需要对 TERT 启动子突变和/或 CDKN2A/B 纯合丢失进行额外测试。这项研究的结果有助于促进基于 IntS 的脑膜瘤患者风险预测的临床实施。在本手稿中，研究并解决了有关综合分子形态脑膜瘤综合评分（IntS）临床应用的问题。例如，在这里，我们研究了使用 v12.5 甲基化脑肿瘤分类器与专用 v2.4 脑膜瘤分类器的结果对 IntS 预测准确性的影响。
Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is the integrated molecular‐morphologic meningioma integrated score (IntS), which allocates points to the histological grade, epigenetic methylation family and specific copy‐number variations. After publication of the IntS, questions arose in the neuropathological community about the practical and clinical implementation of the IntS, specifically regarding the calling of CNVs, the applicability of the newly available version (v12.5) of the brain tumor classifier and the need for incorporation of TERT‐promoter and CDKN2A/B status analysis in the IntS calculation. To investigate and validate these questions additional analyses of the discovery (n = 514), retrospective validation (n = 184) and prospective validation (n = 287) cohorts used for IntS discovery and validation were performed. Our findings suggest that any loss over 5% of the chromosomal arm suffices for the calling of a CNV, that input from the v12.5 classifier is as good or better than the dedicated meningioma classifier (v2.4) and that there is most likely no need for additional testing for TERT‐promoter mutations and/or homozygous losses of CDKN2A/B when defining the IntS for an individual patient. The findings from this study help facilitate the clinical implementation of IntS‐based risk prediction for meningioma patients. In this manuscript, questions regarding the clinical application of the integrated molecular‐morphologic meningioma integrated score (IntS) are investigated and addressed. For example, here we investigate the influence of using results from the v12.5 methylation brain tumor classifier versus the dedicated v2.4 meningioma classifier on the predictive accuracy of the IntS.
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影响因子：
12.7
作者：
Reinhardt, Annekathrin;Stichel, Damian;Capper, David
通讯作者：
Capper, David
影响因子：
64.8
作者：
Capper D;Jones DTW;Sill M;Hovestadt V;Schrimpf D;Sturm D;Koelsche C;Sahm F;Chavez L;Reuss DE;Kratz A;Wefers AK;Huang K;Pajtler KW;Schweizer L;Stichel D;Olar A;Engel NW;Lindenberg K;Harter PN;Braczynski AK;Plate KH;Dohmen H;Garvalov BK;Coras R;Hölsken A;Hewer E;Bewerunge-Hudler M;Schick M;Fischer R;Beschorner R;Schittenhelm J;Staszewski O;Wani K;Varlet P;Pages M;Temming P;Lohmann D;Selt F;Witt H;Milde T;Witt O;Aronica E;Giangaspero F;Rushing E;Scheurlen W;Geisenberger C;Rodriguez FJ;Becker A;Preusser M;Haberler C;Bjerkvig R;Cryan J;Farrell M;Deckert M;Hench J;Frank S;Serrano J;Kannan K;Tsirigos A;Brück W;Hofer S;Brehmer S;Seiz-Rosenhagen M;Hänggi D;Hans V;Rozsnoki S;Hansford JR;Kohlhof P;Kristensen BW;Lechner M;Lopes B;Mawrin C;Ketter R;Kulozik A;Khatib Z;Heppner F;Koch A;Jouvet A;Keohane C;Mühleisen H;Mueller W;Pohl U;Prinz M;Benner A;Zapatka M;Gottardo NG;Driever PH;Kramm CM;Müller HL;Rutkowski S;von Hoff K;Frühwald MC;Gnekow A;Fleischhack G;Tippelt S;Calaminus G;Monoranu CM;Perry A;Jones C;Jacques TS;Radlwimmer B;Gessi M;Pietsch T;Schramm J;Schackert G;Westphal M;Reifenberger G;Wesseling P;Weller M;Collins VP;Blümcke I;Bendszus M;Debus J;Huang A;Jabado N;Northcott PA;Paulus W;Gajjar A;Robinson GW;Taylor MD;Jaunmuktane Z;Ryzhova M;Platten M;Unterberg A;Wick W;Karajannis MA;Mittelbronn M;Acker T;Hartmann C;Aldape K;Schüller U;Buslei R;Lichter P;Kool M;Herold-Mende C;Ellison DW;Hasselblatt M;Snuderl M;Brandner S;Korshunov A;von Deimling A;Pfister SM
通讯作者：
Pfister SM
影响因子：
15.9
作者：
Ostrom, Quinn T.;Cioffi, Gino;Barnholtz-Sloan, Jill S.
通讯作者：
Barnholtz-Sloan, Jill S.
影响因子：
15.9
作者：
Nassiri, Farshad;Mamatjan, Yasin;Zadeh, Gelareh
通讯作者：
Zadeh, Gelareh
DOI：
10.1093/jnen/60.6.628
发表时间：
2001-06-01
影响因子：
3.2
作者：
Cai, DX;Banerjee, R;Perry, A
通讯作者：
Perry, A