TY - JOUR
T1 - Computational immune infiltration analysis of pediatric high-grade gliomas (pHGGs) reveals differences in immunosuppression and prognosis by tumor location
AU - Bailey, Cavan P.
AU - Wang, Ruiping
AU - Figueroa, Mary
AU - Zhang, Shaojun
AU - Wang, Linghua
AU - Chandra, Joya
N1 - Publisher Copyright:
© 2021 The Authors. Computational and Systems Oncology published by Wiley Periodicals LLC.
PY - 2021/9
Y1 - 2021/9
N2 - Immunotherapy for cancer has moved from pre-clinical hypothesis to successful clinical application in the past 15 years. However, not all cancers have shown response rates in clinical trials for these new agents. igh-grade gliomas, in particular, have proved exceedingly refractory to immunotherapy. In adult patients, there has been much investigation into these failures, and researchers have concluded that an immunosuppressive microenvironment combined with low mutational burden renders adult glioblastomas “immune cold.” Pediatric cancer patients develop gliomas at a higher rate per malignancy than adults, and their brain tumors bear even fewer mutations. These tumors can also develop in more diverse locations in the brain, beyond the cerebral hemispheres seen in adults, including in the brainstem where critical motor functions are controlled. While adult brain tumor immune infiltration has been extensively profiled from surgical resections, this is not possible for brainstem tumors that can only be sampled at autopsy. Given these limitations, there is a dearth of information on immune cells and their therapeutic and prognostic impact in pediatric high-grade gliomas (pHGGs), including hemispheric tumors in addition to brainstem. In this report, we use computational methods to examine immune infiltrate in pHGGs and discover distinct immune patterns between hemispheric and brainstem tumors. In hemispheric tumors, we find positive prognostic associations for regulatory T-cells, memory B-cells, eosinophils, and dendritic cells, but not in brainstem tumors. These differences suggest that immunotherapeutic approaches must be cognizant of pHGG tumor location and tailored for optimum efficacy.
AB - Immunotherapy for cancer has moved from pre-clinical hypothesis to successful clinical application in the past 15 years. However, not all cancers have shown response rates in clinical trials for these new agents. igh-grade gliomas, in particular, have proved exceedingly refractory to immunotherapy. In adult patients, there has been much investigation into these failures, and researchers have concluded that an immunosuppressive microenvironment combined with low mutational burden renders adult glioblastomas “immune cold.” Pediatric cancer patients develop gliomas at a higher rate per malignancy than adults, and their brain tumors bear even fewer mutations. These tumors can also develop in more diverse locations in the brain, beyond the cerebral hemispheres seen in adults, including in the brainstem where critical motor functions are controlled. While adult brain tumor immune infiltration has been extensively profiled from surgical resections, this is not possible for brainstem tumors that can only be sampled at autopsy. Given these limitations, there is a dearth of information on immune cells and their therapeutic and prognostic impact in pediatric high-grade gliomas (pHGGs), including hemispheric tumors in addition to brainstem. In this report, we use computational methods to examine immune infiltrate in pHGGs and discover distinct immune patterns between hemispheric and brainstem tumors. In hemispheric tumors, we find positive prognostic associations for regulatory T-cells, memory B-cells, eosinophils, and dendritic cells, but not in brainstem tumors. These differences suggest that immunotherapeutic approaches must be cognizant of pHGG tumor location and tailored for optimum efficacy.
KW - CIBERSORT
KW - DIPG
KW - immune infiltration
KW - immunosuppression
KW - pediatric high-grade glioma
KW - prognostic biomarker
KW - tumor location
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U2 - 10.1002/cso2.1016
DO - 10.1002/cso2.1016
M3 - Article
C2 - 34723252
AN - SCOPUS:85124598922
SN - 2689-9655
VL - 1
JO - Computational and Systems Oncology
JF - Computational and Systems Oncology
IS - 3
M1 - e1016
ER -