Oncology Commons^™

Cancer Stem Cell Assay-Guided Chemotherapy Improves Survival Of Patients With Recurrent Glioblastoma In A Randomized Trial, Tulika Ranjan, Soma Sengupta, Michael J. Glantz, Richard M. Green, Alexander Yu, Dawit Aregawi, Rekha Chaudhary, Ricky Chen, Mario Zuccarello, Christine Lu-Emerson, Hugh D. Moulding, Neil Belman, Jon Glass, Aaron Mammoser, Mark Anderson, Jagan Valluri, Nicholas Marko, Jason Schroeder, Steven Jubelirer, Frances Chow, Pier Paolo Claudio, Anthony M. Alberico, Seth T. Lirette, Krista L. Denning, Candace M. Howard

Department of Neurosurgery Faculty Papers

Therapy-resistant cancer stem cells (CSCs) contribute to the poor clinical outcomes of patients with recurrent glioblastoma (rGBM) who fail standard of care (SOC) therapy. ChemoID is a clinically validated assay for identifying CSC-targeted cytotoxic therapies in solid tumors.

In a randomized clinical trial (NCT03632135), the ChemoID assay, a personalized approach for selecting the most effective treatment from FDA-approved chemotherapies, improves the survival of patients with rGBM (2016 WHO classification) over physician-chosen chemotherapy. In the ChemoID assay-guided group, median survival is 12.5 months (95% confidence interval [CI], 10.2-14.7) compared with 9 months (95% CI, 4.2-13.8) in the physician-choice group (p = …

Molecular-Based Recursive Partitioning Analysis Model For Glioblastoma In The Temozolomide Era: A Correlative Analysis Based On Nrg Oncology Rtog 0525., Erica Hlavin Bell, Stephanie L Pugh, Joseph P. Mcelroy, Mark R. Gilbert, Minesh Mehta, Alexander C Klimowicz, Anthony Magliocco, Markus Bredel, Pierre Robe, Anca L. Grosu, Roger Stupp, Walter Curran, Aline P. Becker, Andrea L. Salavaggione, Jill S. Barnholtz-Sloan, Kenneth Aldape, Deborah T. Blumenthal, Paul D. Brown, Jon Glass, Luis Souhami, R. Jeffrey Lee, David Brachman, John Flickinger, Minhee Won, Arnab Chakravarti

Department of Neurosurgery Faculty Papers

Importance: There is a need for a more refined, molecularly based classification model for glioblastoma (GBM) in the temozolomide era.

Objective: To refine the existing clinically based recursive partitioning analysis (RPA) model by incorporating molecular variables.

Design, Setting, and Participants: NRG Oncology RTOG 0525 specimens (n = 452) were analyzed for protein biomarkers representing key pathways in GBM by a quantitative molecular microscopy-based approach with semiquantitative immunohistochemical validation. Prognostic significance of each protein was examined by single-marker and multimarker Cox regression analyses. To reclassify the prognostic risk groups, significant protein biomarkers on single-marker analysis were incorporated into an RPA model …