Yahaya A. Yabo on Muck Rack

Yahaya A. Yabo

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Articles

Glioma-intrinsic MAPK/ERK signaling promotes immunotherapy efficacy through T cell infiltration and interferon responses

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By Kwang-Soo Kim, Junyi Zhang, Víctor A. Arrieta, Crismita Dmello, Elena Grabis, Yahaya A. Yabo, Si Ran Wang, Karl Habashy, Joseph Duffy, Junfei Zhao, Andrew Gould Verified, Rishi Jain, Li Chen, Jian Hu, Irina V. Balyasnikova, Dhan Chand, Daniel F Levey, Peter Canoll, Wenting Zhao, Peter Sims, Raul Rabadan, Surya Pandey, Bin Zhang, Pouya Jamshidi, Catalina Lee-Chang, Dieter Henrik Heiland, Adam M. Sonabend
| Nature Verified
Abstract Glioblastoma (GBM) remains a formidable challenge in neuro-oncology, with immune checkpoint blockade (ICB) only showing efficacy in some patients, while the mechanisms governing therapeutic responsiveness are poorly defined. Although MAPK/ERK signaling correlates with survival following ICB, its causal role and mechanisms underlying tumor immunogenicity remain unclear.
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A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification - Nature Genetics

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By Yiheng Tang, Ferdinand Zettl, Salvatore Benfatto, Martin Sill, Yahaya A. Yabo, Matthieu Peyre, Roman Sankowski, Philipp Sievers, C. Oliver Hanemann, Christian Mawrin, Olivier Ayrault, Michael Platten, Tim Kacprowski, Markus List, Jan Baumbach, Miriam Ratliff, Jan-Philipp Mallm, Eelke M Bos, Marco Prinz, Michael Weller, Felix J. Hartmann, Matthias Preusser, Christel Herold-Mende, Sandro M. Krieg, Stefan M. Pfister, Wolfgang Wick, Andreas von Deimling, Dieter Henrik Heiland, Volker Hovestadt, Moritz Gerstung, Matthias Schlesner, Christina Blume, Domenico Calafato, Helin Kardo
| Nature Verified
Abstract Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation. Understanding the process of algorithmic interpretation is essential for safe application in clinical routine. This is paradigmatically true for the most common primary intracranial tumor in adults, meningioma.
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A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification

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By Yiheng Tang, Eric Y. Stutheit-Zhao, Ramin Rahmanzade, Christina Blume, Thomas Hielscher, Ferdinand Zettl, Salvatore Benfatto, Domenico Calafato, Martin Sill, Yahaya A. Yabo, Felix Behling, Abigail K. Suwala, Helin Kardo, Michael Ritter, Matthieu Peyre, Roman Sankowski, Konstantin Okonechnikov, Philipp Sievers, Areeba Patel, David E. Reuss, Mirco Friedrich, Damian Stichel, Daniel Schrimpf, Katja Beck, Hans-Georg Wirsching, Gerhard Jungwirth, C. Oliver Hanemann, Katrin Lamszus, Nima Etminan, Andreas W. Unterberg, Christian Mawrin, Olivier Ayrault, Peter Lichter, Guido Reifenberger, Michael Platten, Tim Kacprowski, Markus List, Josch K. Pauling, Jan Baumbach, Zvi Ram, Miriam Ratliff, Jan-Philipp Mallm, Marian C. Neidert, Eelke M Bos, Marco Prinz, Michael Weller, Felix J. Hartmann, Matthias Preusser, Ghazaleh Tabatabai, Christel Herold-Mende, Sandro M. Krieg, Stefan M. Pfister, Wolfgang Wick, Michel Kalamarides, Andreas von Deimling, Dieter Henrik Heiland, Volker Hovestadt, Moritz Gerstung, Matthias Schlesner, Felix Sahm, Jasim Kada Benotmane, Rachel Grossmann
| Flipboard
Oncologists Are Begging People To Take This One Common Cancer Risk Factor Seriously We’re not thinking or talking about this one enough. No one gets cancer on purpose. Yet, it’s hard to find someone who the disease hasn’t touched, …
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