TY - JOUR
T1 - Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas
T2 - From Disease Biology to Therapeutic Implications
AU - Comba, Andrea
AU - Faisal, Syed M.
AU - Varela, Maria Luisa
AU - Hollon, Todd
AU - Al-Holou, Wajd N.
AU - Umemura, Yoshie
AU - Nunez, Felipe J.
AU - Motsch, Sebastien
AU - Castro, Maria G.
AU - Lowenstein, Pedro R.
N1 - Funding Information:
This work was supported by the National Institutes of Health/ National Institute of Neurological Disorders & Stroke (NIH/ NINDS) Grants R21-NS091555, R37-NS094804, and R01-NS074387 to MC. R01-NS076991, R01-NS082311, and R01-NS096756 to PL. Rogel Cancer Center Scholar Award and Forbes Senior Research Scholar Award to MC. National institutes of Health/ National Institute of Biomedical Imaging and Bioengineering (NIH/ NIBIB) Grant R01-EB022563 to PL, and MC. University of Michigan MCube; the Department of Neurosurgery; the University of Michigan Rogel Comprehensive Cancer Center; the Pediatric Brain Tumor Foundation (BTF), Ian's Friends Foundation to PL and MC, Leah’s Happy Hearts Foundation, The Chad Tough Foundation, and the Biosciences Initiative in Brain Cancer to MC and PL. UL1 TR002240 to Michigan Institute for Clinical and Health Research (MICHR), Postdoctoral Translational Scholars Program (PTSP), Project F049768 to AC.
Publisher Copyright:
© Copyright © 2021 Comba, Faisal, Varela, Hollon, Al-Holou, Umemura, Nunez, Motsch, Castro and Lowenstein.
PY - 2021/8/5
Y1 - 2021/8/5
N2 - Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.
AB - Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.
KW - deep learning
KW - dynamic
KW - glioblastoma multiforme
KW - heterogeneity
KW - precision oncology
KW - spatial resolution
KW - tumor microenvironment
UR - http://www.scopus.com/inward/record.url?scp=85113263401&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113263401&partnerID=8YFLogxK
U2 - 10.3389/fonc.2021.703764
DO - 10.3389/fonc.2021.703764
M3 - Review article
AN - SCOPUS:85113263401
SN - 2234-943X
VL - 11
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 703764
ER -