Academic Journal

Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas

التفاصيل البيبلوغرافية
العنوان: Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas
المؤلفون: Herrgott, Grayson A, Snyder, James M, She, Ruicong, Malta, Tathiane M, Sabedot, Thais S, Lee, Ian Y, Pawloski, Jacob, Podolsky-Gondim, Guilherme G, Asmaro, Karam P, Zhang, Jiaqi, Cannella, Cara E, Nelson, Kevin K, Thomas, Bartow, de Carvalho, Ana C, Hasselbach, Laura A, Tundo, Kelly M, Newaz, Rehnuma, Transou, Andrea D, Morosini, Natalia S, Francisco, Victor, Poisson, Laila M, Chitale, Dhananjay A, Mukherjee, Abir, Mosella, Maritza S, Robin, Adam M, Walbert, Tobias, Rosenblum, Mark, Mikkelsen, Tom, Kalkanis, Steven N, Tirapelli, Daniela P. C, Weisenberger, Daniel J, Carlotti, Carlos G, Rock, Jack, Castro, Ana V, Noushmehr, Houtan
المصدر: Neurosurgery Articles
بيانات النشر: Henry Ford Health Scholarly Commons
سنة النشر: 2023
المجموعة: Henry Ford Health System Scholarly Commons
مصطلحات موضوعية: Humans, Meningioma, Prognosis, Artificial Intelligence, DNA Methylation, Liquid Biopsy, Meningeal Neoplasms
الوصف: Recurrence of meningiomas is unpredictable by current invasive methods based on surgically removed specimens. Identification of patients likely to recur using noninvasive approaches could inform treatment strategy, whether intervention or monitoring. In this study, we analyze the DNA methylation levels in blood (serum and plasma) and tissue samples from 155 meningioma patients, compared to other central nervous system tumor and non-tumor entities. We discover DNA methylation markers unique to meningiomas and use artificial intelligence to create accurate and universal models for identifying and predicting meningioma recurrence, using either blood or tissue samples. Here we show that liquid biopsy is a potential noninvasive and reliable tool for diagnosing and predicting outcomes in meningioma patients. This approach can improve personalized management strategies for these patients.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: unknown
Relation: https://scholarlycommons.henryford.com/neurosurgery_articles/507; https://scholarlycommons.henryford.com/context/neurosurgery_articles/article/1508/viewcontent/41467_2023_Article_41434.pdf
الاتاحة: https://scholarlycommons.henryford.com/neurosurgery_articles/507
https://scholarlycommons.henryford.com/context/neurosurgery_articles/article/1508/viewcontent/41467_2023_Article_41434.pdf
رقم الانضمام: edsbas.CD3E44C6
قاعدة البيانات: BASE