TY - JOUR
T1 - Immunohistochemical analysis-based proteomic subclassification of newly diagnosed glioblastomas
AU - Motomura, Kazuya
AU - Natsume, Atsushi
AU - Watanabe, Reiko
AU - Ito, Ichiro
AU - Kato, Yukinari
AU - Momota, Hiroyuki
AU - Nishikawa, Ryo
AU - Mishima, Kazuhiko
AU - Nakasu, Yoko
AU - Abe, Tatsuya
AU - Namba, Hiroki
AU - Nakazato, Yoichi
AU - Tashiro, Hiroshi
AU - Takeuchi, Ichiro
AU - Mori, Tsutomu
AU - Wakabayashi, Toshihiko
PY - 2012/10
Y1 - 2012/10
N2 - Recent gene expression and copy number profilings of glioblastoma multiforme (GBM) by The Cancer Genome Atlas (TCGA) Research Network suggest the existence of distinct subtypes of this tumor. However, these approaches might not be easily applicable in routine clinical practice. In the current study, we aimed to establish a proteomics-based subclassification of GBM by integrating their genomic and epigenomic profiles. We subclassified 79 newly diagnosed GBM based on expression patterns determined by comprehensive immunohistochemical observation in combination with their DNA copy number and DNA methylation patterns. The clinical relevance of our classification was independently validated in TCGA datasets. Consensus clustering identified the four distinct GBM subtypes: Oligodendrocyte Precursor (OPC) type, Differentiated Oligodendrocyte (DOC) type, Astrocytic Mesenchymal (AsMes) type and Mixed type. The OPC type was characterized by highly positive scores of Olig2, PDGFRA, p16, p53 and synaptophysin. In contrast, the AsMes type was strongly associated with strong expressions of nestin, CD44 and podoplanin, with a high glial fibrillary acidic protein score. The median overall survival of OPC-type patients was significantly longer than that of the AsMes-type patients (19.9 vs 12.8 months). This finding was in agreement with the Oncomine analysis of TCGA datasets, which revealed that PDGFRA and Olig2 were favorable prognostic factors and podoplanin and CD44 were associated with a poor clinical outcome. This is the first study to establish a subclassification of GBM on the basis of immunohistochemical analysis. Our study will shed light on personalized therapies that might be feasible in daily neuropathological practice.
AB - Recent gene expression and copy number profilings of glioblastoma multiforme (GBM) by The Cancer Genome Atlas (TCGA) Research Network suggest the existence of distinct subtypes of this tumor. However, these approaches might not be easily applicable in routine clinical practice. In the current study, we aimed to establish a proteomics-based subclassification of GBM by integrating their genomic and epigenomic profiles. We subclassified 79 newly diagnosed GBM based on expression patterns determined by comprehensive immunohistochemical observation in combination with their DNA copy number and DNA methylation patterns. The clinical relevance of our classification was independently validated in TCGA datasets. Consensus clustering identified the four distinct GBM subtypes: Oligodendrocyte Precursor (OPC) type, Differentiated Oligodendrocyte (DOC) type, Astrocytic Mesenchymal (AsMes) type and Mixed type. The OPC type was characterized by highly positive scores of Olig2, PDGFRA, p16, p53 and synaptophysin. In contrast, the AsMes type was strongly associated with strong expressions of nestin, CD44 and podoplanin, with a high glial fibrillary acidic protein score. The median overall survival of OPC-type patients was significantly longer than that of the AsMes-type patients (19.9 vs 12.8 months). This finding was in agreement with the Oncomine analysis of TCGA datasets, which revealed that PDGFRA and Olig2 were favorable prognostic factors and podoplanin and CD44 were associated with a poor clinical outcome. This is the first study to establish a subclassification of GBM on the basis of immunohistochemical analysis. Our study will shed light on personalized therapies that might be feasible in daily neuropathological practice.
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U2 - 10.1111/j.1349-7006.2012.02377.x
DO - 10.1111/j.1349-7006.2012.02377.x
M3 - Article
C2 - 22747609
AN - SCOPUS:84867231671
SN - 1347-9032
VL - 103
SP - 1871
EP - 1879
JO - Cancer Science
JF - Cancer Science
IS - 10
ER -