Literature DB >> 31343422

ENvironmental Dynamics Underlying Responsive Extreme Survivors (ENDURES) of Glioblastoma: A Multidisciplinary Team-based, Multifactorial Analytical Approach.

Sandra K Johnston1,2, Paula Whitmire1, Susan C Massey1, Priya Kumthekar3, Alyx B Porter3, Natarajan Raghunand4, Luis F Gonzalez-Cuyar5, Maciej M Mrugala3, Andrea Hawkins-Daarud1, Pamela R Jackson1, Leland S Hu6, Jann N Sarkaria7, Lei Wang8, Robert A Gatenby9, Kathleen M Egan10, Peter Canoll11, Kristin R Swanson1,12,13.   

Abstract

Although glioblastoma (GBM) is a fatal primary brain cancer with short median survival of 15 months, a small number of patients survive >5 years after diagnosis; they are known as extreme survivors (ES). Because of their rarity, very little is known about what differentiates these outliers from other patients with GBM. For the purpose of identifying unknown drivers of extreme survivorship in GBM, the ENDURES consortium (ENvironmental Dynamics Underlying Responsive Extreme Survivors of GBM) was developed. This consortium is a multicenter collaborative network of investigators focused on the integration of multiple types of clinical data and the creation of patient-specific models of tumor growth informed by radiographic and histologic parameters. Leveraging our combined resources, the goals of the ENDURES consortium are 2-fold: (1) to build a curated, searchable, multilayered repository housing clinical and outcome data on a large cohort of ES patients with GBM; and (2) to leverage the ENDURES repository for new insights into tumor behavior and novel targets for prolonging survival for all patients with GBM. In this article, the authors review the available literature and discuss what is already known about ES. The authors then describe the creation of their consortium and some preliminary results.

Entities:  

Mesh:

Year:  2019        PMID: 31343422     DOI: 10.1097/COC.0000000000000564

Source DB:  PubMed          Journal:  Am J Clin Oncol        ISSN: 0277-3732            Impact factor:   2.339


  2 in total

1.  A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type.

Authors:  Sara Ranjbar; Kyle W Singleton; Pamela R Jackson; Cassandra R Rickertsen; Scott A Whitmire; Kamala R Clark-Swanson; J Ross Mitchell; Kristin R Swanson; Leland S Hu
Journal:  J Digit Imaging       Date:  2020-04       Impact factor: 4.056

2.  Living with a central nervous system (CNS) tumor: findings on long-term survivorship from the NIH Natural History Study.

Authors:  James L Rogers; Elizabeth Vera; Alvina Acquaye; Nicole Briceno; Varna Jammula; Amanda L King; Heather Leeper; Martha M Quezado; Javier Gonzalez Alarcon; Lisa Boris; Eric Burton; Orieta Celiku; Anna Choi; Alexa Christ; Sonja Crandon; Ewa Grajkowska; Nicole Leggiero; Nicole Lollo; Marta Penas-Prado; Jennifer Reyes; Christine Siegel; Brett J Theeler; Michael Timmer; Kathleen Wall; Jing Wu; Kenneth Aldape; Mark R Gilbert; Terri S Armstrong
Journal:  Neurooncol Pract       Date:  2021-04-10
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.