Browsing by Author "Aldape, Kenneth"

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    Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma
    (Springer Nature, 2024) Wang, Justin Z.; Patil, Vikas; Landry, Alexander P.; Gui, Chloe; Ajisebutu, Andrew; Liu, Jeff; Saarela, Olli; Pugh, Stephanie L.; Won, Minhee; Patel, Zeel; Yakubov, Rebeca; Kaloti, Ramneet; Wilson, Christopher; Cohen-Gadol, Aaron; Zaazoue, Mohamed A.; Tabatabai, Ghazaleh; Tatagiba, Marcos; Behling, Felix; Almiron Bonnin, Damian A.; Holland, Eric C.; Kruser, Tim J.; Barnholtz-Sloan, Jill S.; Sloan, Andrew E.; Horbinski, Craig; Chotai, Silky; Chambless, Lola B.; Gao, Andrew; Rebchuk, Alexander D.; Makarenko, Serge; Yip, Stephen; Sahm, Felix; Maas, Sybren L. N.; Tsang, Derek S.; International Consortium on Meningiomas (ICOM); Rogers, C. Leland; Aldape, Kenneth; Nassiri, Farshad; Zadeh, Gelareh; Neurological Surgery, School of Medicine
    Treatment of the tumor and dural margin with surgery and sometimes radiation are cornerstones of therapy for meningioma. Molecular classifications have provided insights into the biology of disease; however, response to treatment remains heterogeneous. In this study, we used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumors and 100 prospective meningiomas, from the RTOG-0539 phase 2 trial to define molecular biomarkers of treatment response. Using propensity score matching, we found that gross tumor resection was associated with longer progression-free survival (PFS) across all molecular groups and longer overall survival in proliferative meningiomas. Dural margin treatment (Simpson grade 1/2) prolonged PFS compared to no treatment (Simpson grade 3). Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. We subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification. This study highlights the potential for molecular profiling to refine surgical and radiotherapy decision-making.
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    Validation and next-generation update of a DNA methylation-based recurrence predictor for meningioma: A multicenter prospective study
    (Oxford University Press, 2025) Landry, Alexander P.; Wang, Justin Z.; Patil, Vikas; Gui, Chloe; Mamatjan, Yasin; Patel, Zeel; Yakubov, Rebecca; Kaloti, Ramneet; Habibi, Parnian; Wilson, Mark; Ajisebutu, Andrew; Ellenbogen, Yosef; Wei, Qingxia; Singh, Olivia; Sosa, Julio; Mansouri, Sheila; Wilson, Christopher; Cohen-Gadol, Aaron A.; Virtanen, Piiamaria; Burket, Noah; Blackwell, Matthew; Koenig, Jenna; Alfonso, Anthony; Davis, Joseph; Zaazoue, Mohamed A.; Tabatabai, Ghazaleh; Tatagiba, Marcos; Behling, Felix; Barnholtz-Sloan, Jill S.; Sloan, Andrew E.; Chotai, Silky; Chambless, Lola B.; Mansouri, Alireza; Ehret, Felix; Capper, David; Tsang, Derek S.; Aldape, Kenneth; Gao, Andrew; International Consortium on Meningiomas (ICOM); Nassiri, Farshad; Zadeh, Gelareh; Neurological Surgery, School of Medicine
    Background: We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion since its original publication. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation predictor compatible with newer methylation arrays. Methods: Genome-wide methylation profiles were generated with the Illumina EPICArray. The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. An nomogram was generated by incorporating our methylation predictor with WHO grade and the extent of resection. Results: A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and an external cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperform the 2021 WHO grade in predicting early postoperative recurrence. Dichotomizing patients into grade-specific risk subgroups was predictive of outcomes within both WHO grades 1 and 2 tumors (P < .05), whereas all WHO grade 3 tumors were considered high-risk. Multivariable Cox regression demonstrated the benefit of adjuvant radiotherapy (RT) in high-risk cases specifically, reinforcing its informative role in clinical decision-making. Finally, our next-generation predictor contains nearly 10-fold fewer features than the original model, allowing for targeted arrays. Conclusions: This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms the 2021 WHO grading in predicting time to recurrence. We make this available as a point-and-click tool that will improve prognostication, inform patient selection for RT, and allow for molecularly stratified clinical trials.