A fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group.

BACKGROUND: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. METHODS: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. RESULTS: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p<0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. CONCLUSION: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.

Grade-specific expression of insulin-like growth factor-binding proteins-2, -3, and -5 in astrocytomas: IGFBP-3 emerges as a strong predictor of survival in patients with newly diagnosed glioblastoma.

BACKGROUND: Insulin-like growth factor (IGF)-binding protein (IGFBP) isoforms have been implicated in the pathogenesis of human neoplasms including glioma. In view of this, we evaluated the expression of IGFBP isoforms (IGFBP-2, -3, and -5) during malignant progression of astrocytoma and their prognostic significance in glioblastoma. METHODS: The expression of IGFBP isoforms was analyzed in diffusely infiltrating astrocytomas by real-time quantitative PCR (n = 203) and immunohistochemistry (n = 256). Statistical methods were used to assess their grade-specific expression pattern and mRNA-protein intercorrelation. Survival analyses were done on a uniformly treated, prospective cohort of adult patients with newly diagnosed glioblastoma (n = 136) by using Cox regression models. RESULTS: The mean transcript levels of IGFBP-2 and -3 were significantly higher in glioblastomas (GBM) relative to anaplastic astrocytoma (AA), diffuse astrocytoma (DA), and controls whereas IGFBP-5 mRNA was higher in GBM relative to AA and controls (P < 0.05). By immunohistochemistry, the mean labeling index of all isoforms was significantly higher in GBM compared with AA, DA, and control (P < 0.05). A strong positive correlation was observed between their respective mRNA and protein expressions (P < 0.01). Multivariate analysis revealed IGFBP-3 expression (hazard ratio, 1.021; P = 0.030) and patient age (hazard ratio, 1.027; P = 0.007) to be associated with shorter survival in glioblastoma. CONCLUSIONS: This study shows the associations of IGFBP-2, -3, and -5 expression with increasing grades of malignancy in astrocytomas. IGFBP-3 is identified as a novel prognostic glioblastoma biomarker. The strong correlation between their mRNA and protein expression patterns suggests their role in the pathogenesis of these tumors. IMPACT: IGFBP isoforms have emerged as biomarkers with diagnostic and prognostic utility in astrocytomas.

Novel glioblastoma markers with diagnostic and prognostic value identified through transcriptome analysis.

PURPOSE: Current methods of classification of astrocytoma based on histopathologic methods are often subjective and less accurate. Although patients with glioblastoma have grave prognosis, significant variability in patient outcome is observed. Therefore, the aim of this study was to identify glioblastoma diagnostic and prognostic markers through microarray analysis. EXPERIMENTAL DESIGN: We carried out transcriptome analysis of 25 diffusely infiltrating astrocytoma samples [WHO grade II--diffuse astrocytoma, grade III--anaplastic astrocytoma, and grade IV--glioblastoma (GBM)] using cDNA microarrays containing 18,981 genes. Several of the markers identified were also validated by real-time reverse transcription quantitative PCR and immunohistochemical analysis on an independent set of tumor samples (n = 100). Survival analysis was carried out for two markers on another independent set of retrospective cases (n = 51). RESULTS: We identified several differentially regulated grade-specific genes. Independent validation by real-time reverse transcription quantitative PCR analysis found growth arrest and DNA-damage-inducible alpha (GADD45alpha) and follistatin-like 1 (FSTL1) to be up-regulated in most GBMs (both primary and secondary), whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 were up-regulated in the majority of primary GBM. Further, identification of the grade-specific expression of GADD45alpha and FSTL1 by immunohistochemical staining reinforced our findings. Analysis of retrospective GBM cases with known survival data revealed that cytoplasmic overexpression of GADD45alpha conferred better survival while the coexpression of FSTL1 with p53 was associated with poor survival. CONCLUSIONS: Our study reveals that GADD45alpha and FSTLI are GBM-specific whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 are primary GBM-specific diagnostic markers. Whereas GADD45alpha overexpression confers a favorable prognosis, FSTL1 overexpression is a hallmark of poor prognosis in GBM patients.

Upregulation of ASCL1 and inhibition of Notch signaling pathway characterize progressive astrocytoma.

Astrocytoma is the most common type of brain cancer constituting more than half of all brain tumors. With an aim to identify markers describing astrocytoma progression, we have carried out microarray analysis of astrocytoma samples of different grades using cDNA microarray containing 1152 cancer-specific genes. Data analysis identified several differentially regulated genes between normal brain tissue and astrocytoma as well as between grades II/III astrocytoma and glioblastoma multiforme (GBM; grade IV). We found several genes known to be involved in malignancy including Achaete-scute complex-like 1 (Drosophila) (ASCL1; Hash 1). As ASCL has been implicated in neuroendocrine, medullary thyroid and small-cell lung cancers, we chose to examine the role of ASCL1 in the astrocytoma development. Our data revealed that ASCL1 is overexpressed in progressive astrocytoma as evidenced by increased levels of ASCL1 transcripts in 85.71% (6/7) of grade II diffuse astrocytoma (DA), 90% (9/10) of grade III anaplastic astrocytoma (AA) and 87.5% (7/8) of secondary GBMs, while the majority of primary de novo GBMs expressed similar to or less than normal brain levels (66.67%; 8/12). ASCL1 upregulation in progressive astrocytoma is accompanied by inhibition of Notch signaling as seen by uninduced levels of HES1, a transcriptional target of Notch1, increased levels of HES6, a dominant-negative inhibitor of HES1-mediated repression of ASCL1, and increased levels of Notch ligand Delta1, which is capable of inhibiting Notch signaling by forming intracellular Notch ligand autonomous complexes. Our results imply that inhibition of Notch signaling may be an important early event in the development of grade II DA and subsequent progression to grade III AA and secondary GBM. Furthermore, ASCL1 appears to be a putative marker to distinguish primary GBM from secondary GBM.