Gene expression profiles of human glioblastomas are associated with both tumor cytogenetics and histopathology

Abstract

Despite the increasing knowledge about the genetic alterations and molecular pathways involved in gliomas, few studies have investigated the association between the gene expression profiles (GEP) and both cytogenetics and histopathology of gliomas. Here, we analyzed the GEP (U133Plus2.0 chip) of 40 gliomas (35 astrocytic tumors, 3 oligodendrogliomas, and 2 mixed tumors) and their association with tumor cytogenetics and histopathology. Unsupervised and supervised analyses showed significantly different GEP in low- vs high-grade gliomas, the most discriminating genes including genes involved in the regulation of cell proliferation, apoptosis, DNA repair, and signal transduction. In turn, among glioblastoma multiforme (GBM), 3 subgroups of tumors were identified according to their GEP, which were closely associated with the cytogenetic profile of their ancestral tumor cell clones: (i) EGFR amplification, (ii) isolated trisomy 7, and (iii) more complex karyotypes. In summary, our results show a clear association between the GEP of gliomas and tumor histopathology; additionally, among grade IV astrocytoma, GEP are significantly associated with the cytogenetic profile of the ancestral tumor cell clone. Further studies in larger series of patients are necessary to confirm our observations.

Fig. 1.

Unsupervised and supervised classification of glioma samples based on their GEP. In (A) unsupervised classification of the tumors according to the 54 613 probes included in the Gene Chip Human Genome U133 Plus 2.0 array are shown; in (A) different histopathological subtypes of gliomas (n = 40) are identified by a distinct color code: pilocytic tumors are coded black; diffuse astrocytomas are identified as green; anaplastic astrocytomas, blue; glioblastoma multiforme, red; gliosarcomas, purple; oligodendrogliomas, yellow; anaplastic oligodendrogliomas, grey, and mixed oligoastrocytomas correspond to those cases depicted as orange. In (B) an MDS plot corresponding to the same 40 gliomas (identified according to their histopathologic features with the same color code as described for [A]) classified according to those 6000 genes showing the highest variability in their expression among the different tumors. In (C) is a heat map representation of the results reflecting a hierarchical cluster analysis based on the expression of those 71 genes showing the highest classification power for tumor grade/histopathology; in (C) the different histopathological subtypes of gliomas are also identified by the same color code as described for (A).

Fig. 2.

Unsupervised and supervised classification of GBM (n = 26) according to their GEP. In (A) unsupervised classification based on the 54 613 probes included in the GeneChip U133A plus 2.0 array is shown. In turn, in (B) hierarchical clustering based on those 47 genes with the highest discrimination power as identified by significance microarray analysis (SAM) shows 3 groups of tumors with distinct GEP (GEP groups: GEP 1, GEP 2, and GEP 3 are colored red, blue, and green, respectively) is displayed. In (C) a MSD plot corresponding to the same tumors classified according to their GEP and identified with the same color code as described above.

Fig. 3.

Detailed description of those genes (n = 79) showing a significant independent value for predicting the GEP of GBM (n = 26) and impact of the different GEP on overall patient survival. In (A) the size of horizontal lines reflects variation on the expression of individual genes within each group of tumors showing different GEP, according to the mean overall expression of that gene in all GBM tumors (n = 26); horizontal bars to the right of vertical lines indicate higher expression than the mean, whereas bars to the left of vertical lines reflect gene expression levels lower than the mean. In (B) overall survival curves of GBM patients grouped according to their GEP are displayed.