Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol.

Autor: Urcuyo JC; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Curtin L; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Langworthy JM; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., De Leon G; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Anderies B; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Singleton KW; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Hawkins-Daarud A; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Jackson PR; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Bond KM; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Ranjbar S; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Lassiter-Morris Y; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Clark-Swanson KR; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Paulson LE; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Sereduk C; Department of Cancer Biology, Mayo Clinic, Phoenix, Arizona, United States of America., Mrugala MM; Department of Neurology, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Oncology, Mayo Clinic, Phoenix, Arizona, United States of America., Porter AB; Department of Neurology, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Oncology, Mayo Clinic, Phoenix, Arizona, United States of America., Baxter L; Department of Neurophysiology, Mayo Clinic, Phoenix, Arizona, United States of America., Salomao M; Department of Pathology, Mayo Clinic, Phoenix, Arizona, United States of America., Donev K; Department of Pathology, Mayo Clinic, Phoenix, Arizona, United States of America., Hudson M; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Meyer J; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Zeeshan Q; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Sattur M; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Patra DP; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Jones BA; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Rahme RJ; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Neal MT; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Patel N; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Kouloumberis P; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Turkmani AH; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Lyons M; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Krishna C; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Zimmerman RS; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Bendok BR; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America., Tran NL; Department of Cancer Biology, Mayo Clinic, Phoenix, Arizona, United States of America., Hu LS; Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America., Swanson KR; Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Cancer Biology, Mayo Clinic, Phoenix, Arizona, United States of America.; Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, United States of America.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2023 Dec 20; Vol. 18 (12), pp. e0287767. Date of Electronic Publication: 2023 Dec 20 (Print Publication: 2023).
DOI: 10.1371/journal.pone.0287767
Abstrakt: Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: KRS and LSH are co-founders of Precision Oncology Insights Inc; Imaging Biometrics (medical advisory board: LSH). The remaining authors have no relevant conflicts of interest to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2023 Urcuyo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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