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Ajisebutu, Andrew

Mayo Clinic

Princess Margaret Cancer Centre

Citations 19

TLSB-23 RNA-SEQUENCING DERIVED RADIOSENSITIVITY INDEX (RSI) IS NOT A PREDICTOR OF LOCAL RECURRENCE AFTER POSTOPERATIVE RADIOTHERAPY IN RESECTED BRAIN METASTASES
Bhandarkar, Archis, Ajisebutu, Andrew, Tan, Elijah , Gandhi, Shreya, Bettencourt, Manuel, Breen, William, Brown, Paul D, Laack, Nadia, Lehrer, Eric, Routman, David, Patil, Vikas, Zadeh, Gelareh, Bhandarkar, Archis R. , Ajisebutu, Andrew, Bettencourt, Manuel M., Breen, William G. , Laack, Nadia N.

Neuro-Oncology Advances | August 7, 2026 | Volume: 8 | Issue: Supplement_6 | Pages: No page available

10.1093/noajnl/vdag161.141 Get It

Abstract Introduction Postoperative radiotherapy is an adjuvant therapy for brain metastases(BrMs) that improves local recurrence(LR). The radiosensitivity index(RSI) is a 10-gene index of pan-cancer molecular radiosensitivity previously validated for predicting radiotherapy response in clinical datasets. In this external validation study, we evaluate RSI as a predictor of local recurrence(LR) after radiotherapy in resected BrM. Methods Patients from University Health Network Toronto(UHN) and McGill University who had a resected BrM and subsequently underwent whole brain radiation(WBRT) or stereotactic radiosurgery(SRS). RSI was calculated using a ranked linear regression model from the weighted expression of 10 radiosensitivity genes, with higher values corresponding to radioresistance. Radiophenotype was determined using a previously validated RSI cutoff of < 0.375 to identify radiosensitive tumors. LR was defined as recurrence in the resection cavity and overall survival(OS) was measured from time of BrM diagnosis. Results 106 BrM patients were included, comprising 29 breast, 37 GI, 33 lung, and 7 melanoma primary sources. Mean age at surgery was 59.2 years, 31.1%(n = 33) were male, 67.9%(n = 72) had WBRT, 23.6%(n = 25) had a subtotal resection, and 30.2%(n = 32) had postoperative chemotherapy. Overall, 34.0%(n = 36) patients had LR. Patients with breast BrMs had median RSI 0.70(IQR:0.55-0.75, 10.3% radiosensitive) with 48.3% LR(n = 14); gastrointestinal BrMs had median RSI 0.43(IQR: 0.35-0.46, 29.7% radiosensitive) and 24.3% LR(n = 9); lung BrMs had median RSI of 0.67(IQR:0.66-0.71, 9% radiosensitive) and 33.3% LR(n = 11); melanoma BrMs had median RSI of 0.72(IQR:0.53-0.92, 0% radiosensitive) and 28.6% LR(n = 2). After adjusting for demographics, primary organ, radiotherapy, resection extent, among others, RSI did not predict LR(p = 0.56) or OS(p = 0.61). Discussion RSI did not predict either LR or OS in patients with surgically resected BrMs status post radiotherapy, further establishing the need for improved predictive scores in this population.
Modern molecular profiling recontextualizes the NRG/RTOG 0539 trial and reveals hidden high-risk and radiotherapy-resistant meningiomas
Yefet, Leeor S, Landry, Alexander , Rogers, C Leland, WANG, J, Patil, Vikas, Gui, Chloe, Ajisebutu, Andrew, Ellenbogen, Yosef , Wei, Qingxia , Singh, Olivia, Szot, Christopher, Barani, Igor J. , Straza, Michael , Shu, Hui-Kuo G, Hunter, Grant, Panet-Raymond, Valérie , Shi, Wenyin, Kavanagh, Brian D. , Gunter, Tyler, Robinson, Clifford, Pugh, Stephanie L. , Mehta, Minesh P, Chakravarti, Arnab, Nassiri, Farshad, Aldape, Kenneth, Zadeh, G Z, Gui, Chloe , Wang, Justin Z , Liu, Jeff , Gui, Chloe , Ellenbogen, Yosef , Singh, Olivia , Jordan, Richard C , Barani, Igor J , Straza, Michael W , Shu, Hui-Kuo G , Pointer, Kelli B , Hunter, Grant , Panet-Raymond, Valerie , Shi, Wenyin , Perlow, Haley K , Kavanagh, Brian D , Gunter, Tyler , Robinson, Clifford , Dicker, Adam P , Mehta, Minesh P , Chakravarti, Arnab , Aldape, Kenneth , Zadeh, Gelareh , Yefet, Leeor S. , Rogers, C. Leland, Wang, Justin Z. , Patil, Vikas , Ajisebutu, Andrew, Mansouri, Sheila , Shi, Wenyin , Perlow, Haley K. , Gunter, Tyler C., Dicker, Adam P. , Mehta, Minesh P. , Chakravarti, Arnab , Nassiri, Farshad

Neuro-Oncology | May 14, 2026 | Volume: 28 | Issue: 7 | Pages: 1727-1740

10.1093/neuonc/noag081 Get It

Abstract Background Meningiomas exhibit clinical heterogeneity. Radiotherapy (RT) remains the only adjuvant therapy, but tumor-control is variable, and biomarkers are limited. NRG/RTOG-0539 is the first prospective phase 2 trial to stratify meningioma patients for adjuvant RT based on clinical risk. Here, we apply modern molecular tools to this cohort and identify correlates of RT response. Methods Tumor tissue from 100 RTOG-0539 patients was profiled using DNA methylation arrays, RNA sequencing, and whole-exome sequencing. Recurrence scores, Molecular Groups, gene expression, and copy number alterations were compared across clinical groups and between RT responders and non-responders; non-response was defined as progression or death within 3 years. Results Modern grading criteria, including brain invasion, TERT mutation, CDKN2A/B deletion, and 1p/1q status, would reclassify 10% of tumors and alter treatment group assignment in 7%. Non-responders to RT exhibited more frequent 1p and 14q loss, and more copy number alterations. Transcriptomic and epigenetic profiling revealed immune-related signatures in responders and cell cycle–related pathways in non-responders, several of which overlapped with targets of vorinostat, a histone deacetylase inhibitor previously validated in aggressive meningioma models. The Proliferative Molecular Group was an independent predictor of post-RT recurrence in multivariable analysis, outperforming WHO grade. Conclusion Multi-omic analysis of the NRG/RTOG-0539 cohort shows that updated WHO grading criteria, incorporating molecular and cytogenetic features, improve risk stratification. However, molecular classification, particularly the Proliferative group, remains an independent and stronger predictor of RT response. These findings support integrating molecular biomarkers alongside modern grading frameworks to guide treatment and trial design in meningioma. Clinical Trial Information NCT00895622.
DNA methylation profiling in central nervous system tumours
Ellenbogen, Yosef , Essibayi, Muhammed Amir , Yefet, Leeor S, Landry, Alexander , Ajisebutu, Andrew, Gui, Chloe, Persaud, Phooja, Nassiri, Farshad, Aldape, Kenneth, Zadeh, Gelareh, Zadeh, Gelareh , Essibayi, Muhammed Amir , Ellenbogen, Yosef , Yefet, Leeor S. , Nassiri, Farshad , Zadeh, Gelareh

Journal of Neurology, Neurosurgery & Psychiatry | April 15, 2026 | Volume: No volume available | Issue: No issue available | Pages: jnnp-2025-337691

10.1136/jnnp-2025-337691 Get It

The classification and management of central nervous system (CNS) tumours have undergone substantial transformation over the past two decades, with the recognition of an expanding set of molecularly defined disease entities. Genome-wide DNA methylation profiling has emerged as an important complement to histopathology and targeted molecular testing, providing an epigenetic framework that captures tumour lineage, biological state and large-scale genomic alterations within a single assay. Accumulating evidence demonstrates that methylation-based approaches improve diagnostic precision, resolve biologically heterogeneous entities and support clinically meaningful risk stratification across a broad spectrum of CNS tumours. Methylation profiling has also increasingly been applied to outcome prediction, liquid biopsy-based analyses and the resolution of diagnostically challenging or misclassified cases. In addition, advances in multi-omic integration, computational inference from routinely acquired clinical data and evolving implementation frameworks are extending the clinical applicability of epigenetic profiling. This review synthesises the current state of DNA methylation profiling within the diagnostic and clinical framework of CNS tumours and considers how emerging technologies and practice models are shaping its ongoing integration into neuro-oncological care.
Methylation Profiling Reveals Subgroups of Intracranial Schwannoma with Distinct Biological and Clinical Features
Landry, Alex, Yefet, Leeor S. , Behling, Felix, Ajisebutu, Andrew, Chloe, Gui, Schittenhelm, Jens , Nassiri, Farshad, Tatagiba, Marcos, Zadeh, Gelareh, Landry, Alexander , Behling, Felix, Ellenbogen, Yosef , Gui, Chloe , Nassiri, Farshad

Journal of Neurological Surgery Part B: Skull Base | February 27, 2026 | Volume: 87 | Issue: No issue available | Pages: No page available

10.1055/s-0046-1818837 Get It

Methylation and Proteomic Signatures of Radiosensitivity in Chordoma
Ajisebutu, Andrew, Chloe, Gui, Zuccato, Jeff, Zadeh, Gelareh, Gui, Chloe , Zuccato, Jeffrey

Journal of Neurological Surgery Part B: Skull Base | February 27, 2026 | Volume: 87 | Issue: No issue available | Pages: No page available

10.1055/s-0046-1818754 Get It

Modern Molecular Profiling Recontextualizes the NRG/RTOG 0539 Trial and Reveals Hidden High-Risk and Radiotherapy Resistant Meningiomas
Yefet, Leo S., Landry, Alex, Wang, Justin Z, Patil, Vikas, Chloe, Gui, Ajisebutu, Andrew, Pugh, Stephanie E., Nassiri, Farshad, Aldape, Kenneth, Zadeh, Gelareh, Landry, Alexander , Liu, Jeff , Patil, Vikas , Gui, Chloe , Ellenbogen, Yosef , Pugh, Stephanie, Nassiri, Farshad

Journal of Neurological Surgery Part B: Skull Base | February 27, 2026 | Volume: 87 | Issue: No issue available | Pages: No page available

10.1055/s-0046-1818692 Get It

Establishing the Utility of Deep Learning for H&E-Based Meningioma Molecular Classification and Outcome Prediction
Landry, Alex, Nassiri, Farshad, Yefet, Leeor S. , Lalchungnunga, H., Wang, Justin Z, Chloe, Gui, Ajisebutu, Andrew, Patil, Vikas, Wei, Qingxia , Singh, Olivia, Sosa, Julio , Ma, Shihao , Wang, B. Q., Raghunathan, Aditya, Gao, Andrew, Ruppin, Eytan, Aldape, Kenneth, Zadeh, Gelareh, Gao, Andrew , Landry, Alexander , Nassiri, Farshad , Lalchungnunga, H. , Shulman, Eldad David , Ellenbogen, Yosef , Gui, Chloe , Patil, Vikas, Liu, Jeff , Singh, Olivia , Mansouri, Sheila , Raghunathan, Aditya , Ruppin, Eytan

Journal of Neurological Surgery Part B: Skull Base | February 27, 2026 | Volume: 87 | Issue: No issue available | Pages: No page available

10.1055/s-0046-1818691 Get It

Molecular classification of radiation-induced meningiomas
Ellenbogen, Yosef , Patil, Vikas, Landry, Alexander , Yefet, Leeor S. , Wang, Justin, Ajisebutu, Andrew, Chloe, Gui, Persaud, Phooja, Aldape, K., Nassiri, Farshad, Zadeh, Gelareh, Aldape, Kenneth D, Ellenbogen, Yosef , Patil, Vikas , Gui, Chloe , Liu, Jeff , Nassiri, Farshad , Zadeh, Gelareh

International Journal of Radiation Biology | February 2, 2026 | Volume: No volume available | Issue: No issue available | Pages: 1-7

10.1080/09553002.2026.2618533 Get It

A framework for using DNA methylation-based modelling for the clinical management of cranial meningioma
Landry, Alexander , Wang, Justin Z. , Patil, Vikas, Ajisebutu, Andrew, Gui, Chloe , Yefet, Leeor, Mamatjan, Yasin , Wei, Qingxia , Singh, Olivia, Mansouri, Sheila , Ehret, Felix , Capper, David , Cohen-Gadol, Aaron A, Behling, Felix , Sloan, Andrew E. , Chambless, Lola B. , Makarenko, Serge , Yip, Stephen , Tsang, Derek S. , Gao, Andrew , Aldape, Kenneth , Nassiri, Farshad , Zadeh, Gelareh , Santarius, Thomas , Selman, Warren R., Couce, Marta , Wen, Patrick Y. , Walbert, Tobias , Felicella, Michelle M. , Brodie, Chaya , Snyder, James P., Saladino, Andrea , Schichor, Christian , Tonn, Jörg‐Christian, Goldbrunner, Roland , Timmer, Marco , Schimdt, Nils Ole, Jenkinson, Michael D. , Millward, Christopher P. , Islim, Abdurrahman I. , Fl, Behling, Santacroce, Antonio , Schittenhelm, Jens , Raleigh, David R. , Butowski, Nicholas , Westphal, Manfred , Lamszus, Katrin , Mawrin, Christian , Kurz, Sylvia C. , Zada, Gabriel , Yip, Stephen, Zherebitskiy, Viktor, Hnenny, Luke, Dunn, Ian F. , Moliterno, Jennifer , McDermott, Michael , Vogelbaum, Michael A. , Aldape, Kenneth, Alkividias, Tzannis, Short, Susan , Bos, Eelke M. , Dincer, Alper , Paßlack, Peter, Ehret, Felix, Lopez, Clara, Arvaniti, Christina , Benjamin, Carolina , Jackson, Christina , Jeyaretna, Sanjeeva, Scartoni, Daniele , Amelio, Dante , Ivanidze, Jana , Kien, Duong Trung, Millareschavez, Miguel, AlThgafi, Malak, LeRhun, Emilie, Smee, Robert, Muirhead, William , Molina, Eric Suero, Julius, Vitowanu, Chen, J., Mrugała, Maciej M. , Castro, Ana Valeria , Mamatjan, Yasin , Capper, David , Tatagiba, Marcos , Barnholtz-Sloan, Jill S , Yip, Stephen , Aldape, Kenneth , Zadeh, Gelareh , Short, Susan C , Yefet, Leeor S. , Ellenbogen, Yosef , Liu, Jeff , Singh, Olivia , Tabatabai, Ghazaleh , Tatagiba, Marcos , Barnholtz‐Sloan, Jill S. , Mansouri, Alireza , Brastianos, Priscilla K. , Shih, Helen A. , Bi, Wenya Linda , Huang, Raymond Y. , Wen, Patrick Yung , Lee, Ian , Malta, Tathiane Maistro , Castro, Ana Valéria , Noushmehr, Houtan , DiMeco, Francesco , Pollo, Bianca , Kaufmann, Timothy J. , Lachance, Daniel Honore , Giannini, Caterina , Galanis, Evanthia , Raghunathan, Aditya , Hanemann, C. Oliver , Au, Karolyn , Galldiks, Norbert , Herold‐Mende, Christel C. , Sahm, Felix , Jungk, Christine , Jungwirth, Gerhard , Deimling, Andreas von , Drummond, Katharine Jann , Morokoff, Andrew P. , Renovanz, Mirjam , Fougère, Christian la , Perry, Arie , Ricklefs, Franz , Horbinski, Craig , Ng, Ho‐Keung , Snuderl, Matija , Sulman, Erik P. , Cohen‐Gadol, Aaron , Javadpour, Mohsen , Fountain, Daniel Mark , Mathiesen, Tiit Illimar , Pathmanaban, Omar Nathan , Boutros, Paul C. , Fountas, Konstantinos N. , Walsh, Kyle M. , Carvalho, Bruno , Maas, Sybren L. N. , Deng, Maximilian Y. , Mehta, Minesh P. , Odia, Yazmín , Everson, Richard G. , Balogun, James , Calabrese, Evan , Karschnia, Philipp , Teske, Nico , Fariselli, Laura , Greve, Tobias , Ivan, Michael E , Palmer, Joshua D. , Ostrom, Quinn T. , Youngblood, Mark W. , Emerson, Sam, Weller, Michael , Martínez-Pérez, Rafael , Mukherjee, Raj, Cervio, Andrés , Turner, Clinton P. , Chen, Jiawei, Karmur, Brij S. , Neth, Bryan J.

Neuro-Oncology | November 15, 2025 | Volume: 28 | Issue: 2 | Pages: 430-439

10.1093/neuonc/noaf237 Get It

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.