Genetic Signature of Adult Gliomas and Correlation with MRI Features

Maria Grazia Bruzzone; Marica Eoli; Valeria Cuccarini; Marina Grisoli; Lorella Valletta; Gaetano Finocchiaro

In recent years the amount of information concerning the genetics and the biology of gliomas, and particularly of glioblastoma multiforme, increased steadily. Such an increase has been paralleled by the technological progress of MRI. The merging of these scientific areas, as summarized in this review, is helping the stratification of glioma patients for clinical trials and their clinical follow-up. Although available therapeutic options appear limited in number, it is likely that in the next 5 years, both as a consequence of the increased knowledge due to genomic sequencing of hundreds of glioblastoma specimens and to continuous improvements of MRI, new perspectives will be available for these patients, with a sizable impact on their prognosis.


Gliomas, the most frequent tumors occurring in the CNS, are defined and graded on the basis of histological features, and pathology is fundamental to predict prognosis and guide the correct patient management.[1] However, pathological diagnosis can be rather subjective and allows considerable interobserver variability, especially in the case of gliomas with mixed histological features.[2] In addition, gliomas of identical histology may be associated with different genetic alterations. Therefore, owing to biological heterogeneity, the histological diagnosis and expected clinical outcome do not match in a significant number of patients and the histological examination does not distinguish tumors responding or not responding to the therapy. Throwing light upon individual biological alterations, molecular analyses may detect subsets of morphologically identical tumors with different clinical behavior (diagnostic markers), describing their prognosis more effectively (prognostic markers).[3] Moreover, molecular biological studies may lead to the discovery of gene-based predictors of therapeutic response, helping to guide more rationally currently available therapies (predictive markers).[4] At present few tumor biomarkers are available for gliomas and it is sometimes unclear how to incorporate molecular genetic information into clinical practice. Differences in study design, patient and specimen characteristics, assay methods and statistical analysis make different studies poorly comparable and also make it difficult to understand the context in which the conclusion should be applied.[5]


Molecular alterations associated with cancer may confer to the tumor physical or biochemical characteristics that can be imaged: contrast enhancement, reflecting blood–brain barrier breakdown, is a key variable (even though its decrease should not be assimilated to a successful treatment).[6] MRI is commonly used in the diagnosis, characterization and clinical management of gliomas for its ability to extract structural, physical, biochemical and functional information. Since histologically similar tumors often show different distinct imaging patterns on MRI,[7] some authors have tried to correlate imaging findings with molecular markers. Despite the fact that many of the imaging features that characterize tumors currently lack biological or molecular correlates,[8–11] phenotypic diversity of gliomas at neuroimaging reflects underlying inter- and intra-tumoral gene expression differences and may be associated with overall survival (OS).[12]

Glioblastoma Multiforme & Grade III Astrocytomas

Glioblastoma multiforme (GBM) is the most common adult brain tumor, accounting for more than half of all gliomas. GBM can arise de novo (primary GBM) without clinical, radiological or histopathological evidence of a pre-existing precursor lesion or after progression from a lower grade glioma (secondary GBM).[13] In adults older than 50 years the vast majority of cases are primary GBM, while secondary GBM typically develop in younger patients.

From a molecular perspective, primary and secondary GBM can be considered as two different tumor subtypes. Loss of heterozygosity (LOH) on chromosome 10q is the most frequent genetic alteration in GBM occurring at similar frequencies in primary and secondary GBM (60–80%).[13,14] However, most primary GBM show extensive LOH or loss of the entire chromosome 10, while secondary GBM show partial or complete loss of chromosome 10q, but no loss of 10p. The most common deleted loci are located on regions 10q23–24 where PTEN maps, and on 10q25pter. PTEN mutations occur almost exclusively in primary GBM.[13]

Furthermore, loss-of-function mutations in the p53 protein are found in more than 65% of low-grade astroctytomas, anaplastic astrocytomas and secondary GBM, suggesting that this is an early event in the formation of these tumors.[15] On the other hand, primary GBM infrequently display mutations in p53 (<10%), although its pathway is deregulated at other levels.

Mutations in TP53, as well as EGF receptor (EGFR) overexpression/amplification are often mutually exclusive events.[16] Amplification of the EGFR gene (located on chromosome 7p12) occurs in 35–50% of primary GBM and rarely in secondary GBM. Overexpression of EGFR is also more common in primary (<60%) than in secondary GBM (<10%). All primary GBM with EGFR amplification show EGFR overexpression and 70–90% of those with EGFR overexpression have EGFR amplification.[13]

Mutations of the EGFR occur in approximately 50% of EGFR-amplified GBM, most frequently affecting the extracellular domain due to a deletion of exons 2–7 containing the extracellular ligand-binding domain: this deletion variant, named EGFvIII, is present in approximately 27% of GBM.[17] EGFRvIII creates a novel tertiary conformation of extracellular domain that lacks ligand binding ability: EGFRvIII is not activated by its ligand, but it is constitutively activated with continuous downstream signaling. EGFRvIII-positive tumors are also reported to be associated with a worse prognosis and shorter life expectancy.[18]

EGFRvIII and EGFR overexpression/amplification are targets of tailored treatments. Sampson, in a Phase I clinical trial of patients with malignant gliomas treated by dendritic cells loaded with the EGFRvIII peptide, found evidence of humoral and cellular immune response against the peptide and an associated median OS of 110.8 weeks in GBM patients.[19] A subsequent Phase II clinical trial of intradermal vaccination with an EGFRvIII peptide only confirmed the previous encouraging results.[19]

In two retrospective studies, responses to small tyrosine-kinase inhibitors that act as competitive antagonists of the intracellular EGFR domain, such as erlotinib (Iressa®), seem to be correlated with EGFR and PTEN status. Mellinghoff et al. analyzed pretreatment tissue from 26 patients treated with EGFR kinase inhibitors, seven of whom had had a response and 19 of whom had rapid progression during therapy. Coexpression of EGFRvIII and PTEN was significantly associated with a clinical response.[20] Haas-Kogan et al. investigated the association between expression of EGFR and downstream signaling components and the response of malignant gliomas to erlotinib in a Phase I trial of erlotinib administered either alone or in combination with temozolomide.[21] They found that GBM patients who have high levels of EGFR expression and low levels of phosphorylated PKB/Akt had better response to erlotinib than those with low levels of EGFR expression and high levels of phosphorylated PKB/Akt. No association between EGFRvIII expression and response to erlotinib was observed.[21] However, other trials failed to confirm those observations.[22]

Microarray analysis offers the option of unbiased, quantitative tumor evaluation by simultaneously analyzing the expression of thousands of genes. This approach has suggested that different gliomas have different gene-expression profiles and that there is evidence for distinct molecular subsets of morphologically identical GBM; furthermore, the expression profile might predict outcome better than histological classification.[23]

Epigenetic alterations also help in GBM subtyping. Loss of the DNA repair enzyme O6-methylguanine DNA methyltransferase (MGMT), due to promoter hypermethylation, is considered a predictive marker of treatment response in patients treated with nitrosurea or temozolomide.[24] MGMT promoter hypermethylation is significantly more frequent in secondary GBM and in tumors harboring TP53 mutations or LOH on 19q, two frequent alterations in lower grade gliomas.[25] These observations have suggested that MGMT is part of a genetic signature typical of lower grade gliomas progressing to malignancy.[26]

Several studies have attempted to correlate imaging findings with molecular markers. Most of them are mainly focused on one molecular marker, such as EGFR amplification: single markers, however, are often representative of a wider genetic signature. This should be taken into account, as other associated alterations may have an important role in shaping MRI findings. Given the increasing amount of genetic information it is likely that in the future genetic signatures (provided by linked alterations of gene sets) rather than single markers will be considered for associations with imaging and/or clinical features.

Aghi et al. (2005) examined preoperative MRI in a series of 75 patients with GBM before the administration of steroids with a computer-based method.[11] Based on the hypothesis that MRI, by showing edema and infiltrating tumor cells in the area surrounding the solid fraction of the tumor, might predict EGFR amplification status, they compared the volume of T2-bright tissue to the T1-enhancing solid tumor volume and also studied the sharpness of the borders between T1-enhancing and T2-bright volumes and adjacent tissue, reporting the first findings of radiographic differences between molecular GBM subtypes: increased T2/T1 ratio and decreased T2-border sharpness coefficients (BSCs) (fuzzier borders) were found in tumors overexpressing EGFR. The decrease of the T2/T1 ratio was significantly associated with increased T2-border sharpness, but neither of these features correlated with survival. T1-BSC and percentage of necrosis did not vary with GBM subtype.

The finding of increased T2/T1 ratio in tumors overexpressing EGFR likely reflects both the increased angiogenesis and edema caused by increased VEGF secretion and the invasion by these tumors caused by increased expression of matrix metalloproteinases and other proteases. Similarly, the finding of decreased T2-BSC in tumors overexpressing EGFR, suggesting less sharpness in the T2 border of these tumors, may reflect the increased invasiveness of these lesions.

Other evidence from our institution suggested that MRI could play a prognostic role in GBM evaluation and management, suggesting a diagnosis of secondary GBM early before surgery and genetic analysis.[26] We studied 86 MRIs of patients affected by GBM. The following MRI features were considered: tumor margins (sharp versus undefined); signal intensity on T1 and T2 images (homogeneous vs heterogeneous); pattern of enhancement (ring, nodular or mixed); presence of necrotic cysts; mass effect; and edema.

A total of 72 patients had a clinical history indicating de novo insurgence of the tumor while the remaining 14 were diagnosed as secondary GBMs. A significant difference was found between the MRI appearance of primary GBMs with unmethylated MGMT promoter (Meth) (Figure 1) and secondary Meth+ GBMs (tightly associated with LOH on 17p and/or 19q) (Figure 2). The former lesions were large, with necrotic cysts heterogeneous both in T1 and T2 sequences, and ring contrast enhancement, whereas the latter lesions were more homogeneous in T2 sequences and showed mixed-nodular contrast enhancement. Primary Meth+ GBMs show intermediate characteristics. Meth+ patients treated by chemotherapy survived significantly longer. Borders of the tumor were evaluated also on T2 images and extent of edema was scored, but significance of these values was decreased because of concurrence of steroid therapy.

As temozolomide (concurrent with radiotherapy (RT) and, subsequently, as maintenance therapy) has become standard treatment for patients with newly diagnosed GBM, Brandes et al. (2009) evaluated factors predicting the recurrence pattern after the administration of the aforementioned treatments in 95 patients, considering the MGMT methylation status and MRI.[27] After a median follow-up time of 19 months, 79 patients had recurrence and MGMT status was correlated with the site of recurrence: inside or at the margin of the RT field in 85% subjects with Meth status and 58% with Meth+ status, outside the RT field in 15% Meth and 42% Meth+ cases. Recurrences outside the RT field occurred after a longer time interval (15 vs 9 months) and patient survival was longer.

We also assessed the role of mutations and instability of mitochondrial DNA (mtDNA) in the clinical management of malignant gliomas by studying the D loop of mtDNA in 42 such tumors.[28] Alterations were found in 36% of the cases. The MRI and the clinical follow-up of these patients suggest that these mutations are not associated with increased aggressiveness. mtDNA could be amplified from postsurgical tumor cavities in patients undergoing a locoregional treatment.

Diehn et al. created radiogenomic maps using an integrated analysis of gene-expression patterns and imaging profiles from pretreatment MRI and stereotactic biopsies of 22 patients with GBM.[29] A set of binary MRI traits was scored: degree of contrast enhancement, degree of edema, necrosis, mass effect, infiltrative versus edematous T2 abnormalities, cortical involvement, subventricular zone (SVZ) involvement, contrast:necrosis (C:N) ratio, contrast:T2 ratio, and T2 heterogeneity. Seven gene-expression modules related to known biological processes were used: EGFR overexpression, hypoxia, extracellular matrix, immune cells, proliferation, glial and neuronal.

Using this information, the authors identified potential imaging biomarkers for different classes of therapeutic agents. The association between EGFR overexpression and high C:N ratio was validated in an independent group of 49 GBMs: this imaging phenotype is a surrogate of EGFR overexpression, suggesting that it may be possible to develop imaging-based predictors of treatment response.

These results also suggested that intratumoral heterogeneity of certain gene-expression programs can be spatially resolved by using imaging. The infiltrative imaging phenotype is related to a list of genes including those involved in tumor cell migration such as BCAN, TRIO, PTP4A3 and ER, has a greater tendency toward the presence of multiple tumor foci and demonstrates shorter survival. The hypoxia module, which contains genes implicated in angiogenesis and tumor hypoxia (VEGF, ADM, PLAUR, SERPINE1 and CA12), is associated with the contrast-enhancement imaging phenotype. This radiophenotype could potentially be used as an imaging biomarker for selecting patients for antiangiogenic therapy. Mass effect phenotype and the proliferation gene-expression signature (TOP2A, CDC2 and BUB1B) were also significantly correlated. Tumor size alone did not significantly correlate with the proliferation cluster. The authors concluded that the approach used in their study can be easily generalized, even though its molecular detail may not match that of conventional molecular profiling approaches.[29]

Using the enhancement patterns to divide GBM in two groups with different prognoses, Pope et al. (2008) compared gene expression of approximately 14,500 genes in 52 GBM classified as completely enhancing (CE) or incompletely enhancing (IE).[30] Approximately equal percentages of the 20 IE and 32 CE groups were treated with steroids. A total of 79 genes were differently expressed between the two groups by a factor of at least two. Eight of them, including tight junction protein-2 (acting to maintain the blood–brain barrier) and the oligodendroglioma (OD) markers OLIG2 and ASCL1 demonstrated an increased in expression in the IE group versus the CE group. A total of 71 genes, including VEGF, adrenomedullin, IL-8, decorin (associated with the hypoxia–angiogenesis–edema pathways), matrix metalloproteinase (MMP) 7, tenascin C (associated with increased invasion in gliomas, degrading the extracellular matrix and disrupting the blood–brain barrier), caveolin 1 and 2, transgelin and thrombospondin-1, were overexpressed in CE GBM when compared with IE.[30] It is noteworthy that MMP7 was elevated in CE GBM while tight junction protein-2 was increased in IE. This suggests the possibility that the balance between MMPs and tight junction proteins may be responsible for maintaining the blood–brain barrier in GBM and that a shift in this balance may promote a more aggressive phenotype associated with edema, invasiveness and contrast enhancement. Several genes associated with primary GBM (caveolin 1 and 2, IL-8, transgelin and thrombospondin-1) were higher in CE tumors whereas at least one gene associated with secondary GBM (ASCL1) was higher in IE tumors. Furthermore, none of the eight genes higher in IE tumors was overexpressed in primary GBMs and none of the 71 genes higher in the CE group were overexpressed in secondary GBMs. These data confirm that lack of enhancement in the tumor may help in distinguishing between primary and secondary GBM. This finding may have important implications on therapy because it has been suggested that angiogenic pathways are markedly different in primary and secondary GBMs and may require different antiangiogenic treatment strategies. As the gene expression of some therapeutic targets is substantially different between IE and CE GBMs, the enhancement pattern may predict a better or worse response to therapies. For example, the association between VEGF and CE may explain the higher susceptibility to anti-VEGF therapy of necrotic and enhancing tumor areas even in the same patient.

Almost all of the genes that have been found to be overexpressed in IE GBMs were associated with longer survival (e.g., LIG2, ASCL1, tight junction protein-2, astrotactin-2, Usher Syndrome 1C, inhibitor of DNA binding 4 and BCAN), whereas none of the genes enriched in CE GBMs were associated with better survival; one of them, decorin, was significantly correlated with shortened survival.

Oligodendrogliomas and oligoastrocytomas (OAs) are diffuse gliomas that can be of pure (oligodendroglial) or mixed (oligodendroglial and astrocytic) histology and are classified as WHO grade II or III. They typically occur in young- to middle-aged adults with a hasty of seizures and are frequently located within the white matter of the frontal and temporal lobes. Daumas-Duport et al. have proposed a different classification based on histology and imaging data, which distinguishes ODs and mixed gliomas of grade A (without endothelial proliferation and/or contrast enhancement), ODs and mixed gliomas of grade B (with endothelial proliferation or contrast enhancement), glioblastomas and glioneuronal malignant tumors.[31] This classification, however, is not internationally accepted and is not correlated with molecular signature. According to Daumas-Duport et al. the diagnosis may be established based on the following parameters:

  • Gliomas without enhancement: OD (or OA) grade A;
  • Gliomas with enhancement: glioblastoma or OD (or OA) grade B.

This approach is of potential interest as it openly proposes integration between histology and radiology that, together with genetics, may constitute a founding feature of future classifications in neuro-oncology.

In pure ODs, LOH on 1p and 19q are the most frequent genetic alterations, being present in more than 80% of grade II and in over 50% of grade III tumors.[32,33] Genetic alterations of OAs include LOH on chromosome 1p and/or 19q, which is observed in approximately 50% of OAs, but also loss of heterozygosity on chromosome 10q and/or 17p, which is frequently found in astrocytomas and associated with the progression to glioblastoma.[34]

Several retrospective studies suggested that patients with ODs and OAs that contain deletions on 1p and 19q have longer progression-free survival (PFS), longer OS and better response to chemotherapy or RT, regardless of tumor grade and type of chemotherapy (procarbazine, lomustine and vincristine [PCV] or temozolomide).[35,36] In particular, LOH on 1p appeared as a ‘dominant’ marker in determining the prognosis of OAs, independently from the association with LOH on 19q or 17p.[36]

Despite the clinical relevance of 1p and 19q losses, the genes targeted on these two chromosomes are still unknown.[37] Some very recent progress, however, may help pinpointing the genetics underlying these alterations. Jenkins et al. (2006) provided evidence that combined loss of 1p and 19q is mediated by the translocation (t(1,19)(q10;p10).[38] Potential candidate genes on 1p36 are T calmodulin-binding transcription activator 1 (CAMTA1) gene;[39] the retinoblastoma protein-interacting zinc-finger gene (RIZ1)[40] and chromodomain helicase DNA-binding domain 5 (Chd5).[41]

Another candidate gene, which is located on 1p31, is DIRAS3, a maternally imprinted, RAS-related tumor-suppressor gene;[42] and recently, Ngo et al. suggested stathmin as a candidate protein that is involved in the chemosensitivity of tumors with 1p deletion.[43]

Another potential candidate on 1p36 is the retinoblastoma protein-interacting zinc-finger gene, RIZ1, a member of a nuclear protein-methyltransferase superfamily involved in chromatin-mediated gene expression. RIZ1 mutations were not detected in 40 ODs, but investigations on its expression, which can be decreased by promoter methylation or haplotype insufficiency in other tumors, should be performed before ruling out its involvement in the formation of ODs or mixed gliomas.[40]

In WHO grade II and III ODs and OAs a very high frequency of MGMT promoter hypermethylation (>80%) has been found, associated with LOH of chromosomal regions on 1p and 19q.[44]

Tumors with 1p and 19q deletions have noteworthy imaging features: they are more likely to have mixed signal intensity on T1 and T2 images, ill-defined margins on T1-weighted MRI and calcifications; when they show contrast enhancement transformation to a higher histological grade is suggested.[45,46]

Ricard et al. (2007) investigated the growth kinetics of 68 low-grade gliomas (LGG) on serial MRI, evaluating the changes in mean tumor diameter.[47] Before initiation of chemotherapy, progressive continuous growth of LGG was observed, with a significantly slower slope in 1p19q-codeleted tumors as compared with 1p19q-retained tumors. The duration of the decreasing slope of the tumor volume in codeleted gliomas led to a lower rate of relapse and to a higher rate of objective response.

Merrell et al. described two cases of ODs with bony metastasis (a very rare occurrence) in patients with deletions of both chromosomes 1p and 19q.[48] Both patients did not have radiological evidence of intracranial progression. The surprising finding might be explained with the prolonged survival of OD patients associated to pronounced tumor chemosensitivity, allowing a long-standing tumor to progress to higher grade, thus contributing to the increased number of metastatic ODs reported in the literature. It is otherwise possible that tumors with this genetic subtype are more prone to metastasis, as deletions are often associated to polyploidy: this pattern is more frequent in the high-grade and/or recurrent ODs.[49]

Diffuse Astrocytomas

Well differentiated, diffuse infiltrative astrocytomas include WHO classification grade II astrocytomas and represent approximately 25% of astrocytomas.[1] According to the prevailing cell type, three mayor variants within WHO grade II diffuse astrocytomas can be distinguished: fibrillary, protoplasmatic and gemistocytic astrocytomas. Molecular data on diffuse astrocytomas are limited and their clinical value is still debated, owing to the lack of definitive evidence emerging from the literature.

Approximately 50% of diffuse astrocytomas show mutations of the TP53 gene, which is often associated with LOH on 17p.[53,54] The absence of a wild-type p53 is, therefore, the most common abnormal finding in WHO grade II astrocytomas, resulting in a nonfunctional p53 pathway. Gaiser et al. recently studied 23 diffuse astrocytomas, 11 of which had a TP53 mutation and 12 were the TP53 wild-type, by PCR amplification of genomic DNA extracted from tumor tissues and microvessel computed counting.[55] Intratumoral or peritumoral microvascular hot spots were assessed and analyzed. No association between microvessel density (MVD) and p53 immunohistochemical status was found; however, the MVD was significantly increased in p53 mutated, low-grade astrocytomas. Furthermore, the absolute vessel number was significantly higher in p53 mutated than in p53 wild-type low-grade astrocytomas. No correlation with imaging patterns was observed in this series.

Ware et al. (2007) studied 22 patients with gliomatosis cerebri and found that subjects whose tumors had contrast enhancement and those with tumors harboring +7/-10q, -10q or -13q copy number aberrations had shorter survival times: the study suggested that these risk factors are independent of each other.[56]

With the objective of investigating the utility of CXCR4, a chemokine receptor-mediating glioma cell invasiveness, as a molecular marker for peritumoral disease extent in high-grade gliomas, Stevenson et al. characterized the expression profile of CXCR4 in a large panel of tumor samples.[57] T1-post-contrast and T2-weighted MRI brain scans were used to generate voxel signal-intensity histograms that were quantitatively analyzed to determine the extent and intensity of peritumoral signal abnormality as a marker of disseminated disease in the brain. CXCR4 expression was markedly elevated in grade III and IV tumors compared with grade II gliomas. Significantly, when patients with GBM were segregated into two groups based on CXCR4 expression level, the authors observed a statistically significant increase in the intensity and extent of peritumoral MRI signal abnormalities associated with CXCR4 high-expressing gliomas.

Loss of MGMT expression as a result of promoter hypermethylation is detected more frequently in LGGs than in glioblastomas, with incidence ranging from 50 to 90%. The majority of grade II astrocytomas with MGMT promoter hypermethylation contain TP53 mutations; in particular, G:C A:T transitions.[15]

In LGGs, MGMT promoter hypermethylation seems to influence the natural history of the disease. In fact, the PFS of LGG patients with MGMT promoter hypermethylation is shorter than that of patients without MGMT hypermethylation.[58,59] Furthermore, MGMT hypermethylation is significantly more frequent in glioblastoma that progressed from LGG (i.e., secondary glioblastoma) than in glioblastoma arising de novo (77 vs 28%; p = 0.002).[26,60] These observations suggest that loss of MGMT expression due to promoter hypermethylation frequently occurs at an early stage of the disease. Treatment with temozolomide could reverse the prognostic significance of MGMT hypermethylation in LGGs. In patients treated with temozolomide and hypermethylated MGMT, PFS was longer.

Intriguingly, one recent study describing the integrated genomic analysis of 22 GBMs[61] showed for the first time somatic mutations of isocitrate dehydrogenase 1 (IDH1), which are likely to become the most reliable genetic marker for secondary GBM, confirming that these two GBM subtypes, in spite of histological similarities, are genetically and clinically distinct entities.[61–64] High frequencies of IDH1 mutations have been detected in secondary GBM (50–82%) and not in primary GBMs (3–5%), and are highly frequent in ODs, OAs (65–94%) and diffuse astrocytomas (54–88%).

Expert Commentary

Genetics and MRI have a growing role in the management of patients who are affected by gliomas. They complement histology and are becoming essential tools for making decisions on the treatment and for the definition of disease relapse: this is critical since PFS is one of the main goals of clinical trials for this disease. In terms of markers, we currently have at least four that have been validated in many ways, both clinically and preclinically: MGMT methylation, EGFR amplification, LOH of 1p and 19q, and p53 mutations. However, individual decision-making based on the status of one or more of such markers may be problematic.[5] However, the combination of MRI findings may corroborate clinical decisions, thereby providing them with a rational basis. Functional MRI techniques, such as perfusion-weighted imaging, magnetic resonance spectroscopy and even spectral analysis, may flank nuclear medicine in this context.

Five-year View

The number of markers of potential clinical impact in the treatment of gliomas is obviously growing. Their validation in clinical use, however, should be carefully evaluated in large, well-organized Phase II and III clinical trials. Patient stratification on their basis will become increasingly relevant. At the clinical level, it is also expected that MRI may play an important role in defining criteria for response to novel treatment, particularly those based on antiangiogenic factors, such as bevacizumab, and those based on the elicitation of specific immune responses (e.g., dendritic cell immunotherapy and peptide-based immunotherapy) as, at present, the criteria to define a response or a relapse in the new scenario that these treatment have created are far from unequivocal. At the preclinical level, it is also anticipated that new reagents, such as contrast media,[65,66] derived from nanotechnologies,[67] will begin to play a new role and help to enter into the new era of molecular imaging.


Key Issues

  • Genetic patterns are associated with MRI, some of them with sensitivity to therapies and/or survival.
  • Single genes can be associated with MRI.
  • Inter- and intra-tumor gene and MRI heterogeneity.
  • MRI must contain at least T1-weighted nonenhanced and contrast-enhanced, and T2-weighted images.
  • As a more sophisticated measure of tumor vascularity, it may be hypothesized that cerebral blood volume may be a better predictor of outcome than contrast enhancement.
  • Advanced MRI techniques would be useful.
  • Most studies concern glioblastoma multiforme, but the dissociation between pathology and molecular genetics is greatest in low-grade gliomas and surrogate MRI features are needed.
  • Further studies are needed to establish the role of such markers in each type of glioma; the available data support the utility of tumoral gene-image maps and imaging surrogates as diagnostic and prognostic markers that allow pretreatment evaluation of gliomas.


  1. Louis DN, Ohgaki H, Wiestler OD et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 114(2), 97–109 (2007).
  2. Kros JM. From expert opinion to evidence-based: changes in the gold standard of primary brain tumour diagnosis. J. Pathol. 213(1), 1–3 (2007).
  3. Reddy SP, Britto R, Vinnakota K et al. Novel glioblastoma markers with diagnostic and prognostic value identified through transcriptome analysis. Clin. Cancer Res. 14(10), 2978–2987 (2008).
  4. Yip S, Iafrate AJ, Louis DN. Molecular diagnostic testing in malignant gliomas: a practical update on predictive markers. J. Neuropathol. Exp. Neurol. 67(1), 1–15 (2008).
  5. Wager M, Menei P, Guilhot J et al. Prognostic molecular markers with no impact on decision-making: the paradox of gliomas based on a prospective study. Br. J. Cancer 98(11), 1830–1838 (2008).
  6. Kubota T, Yamada K, Kizu O et al. Relationship between contrast enhancement on fluid-attenuated inversion recovery MR sequences and signal intensity on T2-weighted MR images: visual evaluation of brain tumors. J. Magn. Reson. Imaging 21(6), 694–700 (2005).
  7. Emblem KE, Nedregaard B, Nome T et al. Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 247(3), 808–817 (2008).
  8. Van Meter T, Dumur C, Hafez N, Garrett C, Fillmore H, Broaddus WC. Microarray analysis of MRI-defined tissue samples in glioblastoma reveals differences in regional expression of therapeutic targets. Diagn. Mol. Pathol. 15(4), 195–205 (2006).
  9. Earnest Ft, Kelly PJ, Scheithauer BW et al. Cerebral astrocytomas: histopathologic correlation of MR and CT contrast enhancement with stereotactic biopsy. Radiology 166(3), 823–827 (1988).
  10. Carlson MR, Pope WB, Horvath S et al. Relationship between survival and edema in malignant gliomas: role of vascular endothelial growth factor and neuronal pentraxin 2. Clin. Cancer Res. 13(9), 2592–2598 (2007).
  11. Aghi M, Gaviani P, Henson JW, Batchelor TT, Louis DN, Barker FG 2nd. Magnetic resonance imaging characteristics predict epidermal growth factor receptor amplification status in glioblastoma. Clin. Cancer Res. 11(24 Pt 1), 8600–8605 (2005).
    • Describes important MRI features associated to a key genetic marker and potential therapeutic target of glioblastoma multiforme (GBM).
  12. Nelson SJ, Cha S. Imaging glioblastoma multiforme. Cancer J. 9(2), 134–145 (2003).
  13. Ohgaki H, Kleihues P. Genetic pathways to primary and secondary glioblastoma. Am J. Pathol. 170(5), 1445–1453 (2007).
    •• Exhaustive review on differences in GBM of relevant clinical impact.
  14. Ohgaki H. Genetic pathways to glioblastomas. Neuropathology 25(1), 1–7 (2005).
  15. Ohgaki H, Kleihues P. Population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. J. Neuropathol. Exp. Neurol. 64(6), 479–489 (2005).
  16. Watanabe K, Tachibana O, Sata K, Yonekawa Y, Kleihues P, Ohgaki H. Overexpression of the EGF receptor and p53 mutations are mutually exclusive in the evolution of primary and secondary glioblastomas. Brain Pathol. 6(3), 217–223; discussion 223–214 (1996).
    • Landmark paper on genetic differences in GBM.
  17. Yoshimoto K, Dang J, Zhu S et al. Development of a real-time RT-PCR assay for detecting EGFRvIII in glioblastoma samples. Clin. Cancer Res. 14(2), 488–493 (2008).
  18. Shinojima N, Tada K, Shiraishi S et al. Prognostic value of epidermal growth factor receptor in patients with glioblastoma multiforme. Cancer Res. 63(20), 6962–6970 (2003).
  19. Sampson JH, Archer GE, Mitchell DA, Heimberger AB, Bigner DD. Tumor-specific immunotherapy targeting the EGFRvIII mutation in patients with malignant glioma. Semin. Immunol. 20(5), 267–275 (2008).
  20. Mellinghoff IK, Wang MY, Vivanco I et al. Molecular determinants of the response of glioblastomas to EGFR kinase inhibitors. N. Engl. J. Med. 353(19), 2012–2024 (2005).
  21. Haas-Kogan DA, Prados MD, Tihan T et al. Epidermal growth factor receptor, protein kinase B/Akt, and glioma response to erlotinib. J. Natl Cancer Inst. 97(12), 880–887 (2005).
  22. van den Bent MJ, Brandes AA, Rampling R et al. Randomized Phase II trial of erlotinib versus temozolomide or carmustine in recurrent glioblastoma: EORTC brain tumor group study 26034. J. Clin. Oncol. 27(8), 1268–1274 (2009).
  23. Nutt CL, Mani DR, Betensky RA et al. Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63(7), 1602–1607 (2003).
  24. Hegi ME, Liu L, Herman JG et al. Correlation of O6-methylguanine methyltransferase (MGMT) promoter methylation with clinical outcomes in glioblastoma and clinical strategies to modulate MGMT activity. J. Clin. Oncol. 26(25), 4189–4199 (2008).
    • Review on O6-methylguanine methyltransferase (MGMT) – currently a major marker in GBM.
  25. Zawlik I, Vaccarella S, Kita D, Mittelbronn M, Franceschi S, Ohgaki H. Promoter methylation and polymorphisms of the MGMT gene in glioblastomas: a population-based study. Neuroepidemiology 32(1), 21–29 (2009).
  26. Eoli M, Menghi F, Bruzzone MG et al. Methylation of O6-methylguanine DNA methyltransferase and loss of heterozygosity on 19q and/or 17p are overlapping features of secondary glioblastomas with prolonged survival. Clin. Cancer Res. 13(9), 2606–2613 (2007).
    • Shows a significant correlation between MRI and MGMT methylation in primary and secondary GBM.
  27. Brandes AA, Tosoni A, Franceschi E et al. Recurrence pattern after temozolomide concomitant with and adjuvant to radiotherapy in newly diagnosed patients with glioblastoma: correlation With MGMT promoter methylation status. J. Clin. Oncol. 27(8), 1275–1279 (2009).
  28. Montanini L, Regna-Gladin C, Eoli M et al. Instability of mitochondrial DNA and MRI and clinical correlations in malignant gliomas. J. Neurooncol. 74(1), 87–89 (2005).
  29. Diehn M, Nardini C, Wang DS et al. Identification of noninvasive imaging surrogates for brain tumor gene-expression modules. Proc. Natl Acad. Sci. USA 105(13), 5213–5218 (2008).
    •• Proposes that intratumoral heterogeneity of different gene-expression programs can be spatially resolved by imaging.
  30. Pope WB, Chen JH, Dong J et al. Relationship between gene expression and enhancement in glioblastoma multiforme: exploratory DNA microarray analysis. Radiology 249(1), 268–277 (2008).
  31. Daumas-Duport C, Beuvon F, Varlet P, Fallet-Bianco C. [Gliomas: WHO and Sainte-Anne Hospital classifications]. Ann. Pathol. 20(5), 413–428 (2000).
  32. Fallon KB, Palmer CA, Roth KA et al. Prognostic value of 1p, 19q, 9p, 10q, and EGFR-FISH analyses in recurrent oligodendrogliomas. J. Neuropathol. Exp. Neurol. 63(4), 314–322 (2004).
  33. Hoang-Xuan K, He J, Huguet S et al. Molecular heterogeneity of oligodendrogliomas suggests alternative pathways in tumor progression. Neurology 57(7), 1278–1281 (2001).
  34. Blesa D, Mollejo M, Ruano Y et al. Novel genomic alterations and mechanisms associated with tumor progression in oligodendroglioma and mixed oligoastrocytoma. J. Neuropathol. Exp. Neurol. 68(3), 274–285 (2009).
  35. Mariani L, Deiana G, Vassella E et al. Loss of heterozygosity 1p36 and 19q13 is a prognostic factor for overall survival in patients with diffuse WHO grade 2 gliomas treated without chemotherapy. J. Clin. Oncol. 24(29), 4758–4763 (2006).
  36. Eoli M, Bissola L, Bruzzone MG et al. Reclassification of oligoastrocytomas by loss of heterozygosity studies. Int. J. Cancer 119(1), 84–90 (2006).
    • Demonstrates the power of genetic analysis in complementing the histological diagnosis of mixed gliomas.
  37. Felsberg J, Erkwoh A, Sabel MC et al. Oligodendroglial tumors: refinement of candidate regions on chromosome arm 1p and correlation of 1p/19q status with survival. Brain Pathol. 14(2), 121–130 (2004).
  38. Jenkins RB, Blair H, Ballman KV et al. A t(1;19)(q10;p10) mediates the combined deletions of 1p and 19q and predicts a better prognosis of patients with oligodendroglioma. Cancer Res. 66(20), 9852–9861 (2006).
  39. Barbashina V, Salazar P, Holland EC, Rosenblum MK, Ladanyi M. Allelic losses at 1p36 and 19q13 in gliomas: correlation with histologic classification, definition of a 150-kb minimal deleted region on 1p36, and evaluation of CAMTA1 as a candidate tumor suppressor gene. Clin. Cancer Res. 11(3), 1119–1128 (2005).
  40. Alonso ME, Bello MJ, Arjona D et al. Mutational study of the 1p located genes p18ink4c, Patched-2, RIZ1 and KIF1B in oligodendrogliomas. Oncol. Rep. 13(3), 539–542 (2005).
  41. Bagchi A, Papazoglu C, Wu Y et al. CHD5 is a tumor suppressor at human 1p36. Cell 128(3), 459–475 (2007).
  42. Riemenschneider MJ, Reifenberger J, Reifenberger G. Frequent biallelic inactivation and transcriptional silencing of the DIRAS3 gene at 1p31 in oligodendroglial tumors with 1p loss. Int. J. Cancer 122(11), 2503–2510 (2008).
  43. Ngo TT, Peng T, Liang XJ et al. The 1p-encoded protein stathmin and resistance of malignant gliomas to nitrosoureas. J. Natl Cancer Inst. 99(8), 639–652 (2007).
  44. Mollemann M, Wolter M, Felsberg J, Collins VP, Reifenberger G. Frequent promoter hypermethylation and low expression of the MGMT gene in oligodendroglial tumors. Int. J. Cancer 113(3), 379–385 (2005).
  45. Megyesi JF, Kachur E, Lee DH et al. Imaging correlates of molecular signatures in oligodendrogliomas. Clin. Cancer Res. 10(13), 4303–4306 (2004).
  46. Koeller KK, Rushing EJ. From the archives of the afip: oligodendroglioma and its variants: radiologic–pathologic correlation. Radiographics 25(6), 1669–1688 (2005).
  47. Ricard D, Kaloshi G, Amiel-Benouaich A et al. Dynamic history of low-grade gliomas before and after temozolomide treatment. Ann. Neurol. 61(5), 484–490 (2007).
  48. Merrell R, Nabors LB, Perry A, Palmer CA. 1p/19q chromosome deletions in metastatic oligodendroglioma. J. Neurooncol. 80(2), 203–207 (2006).
  49. Perry A, Fuller CE, Banerjee R, Brat DJ, Scheithauer BW. Ancillary FISH analysis for 1p and 19q status: preliminary observations in 287 gliomas and oligodendroglioma mimics. Front. Biosci. 8, A1–A9 (2003).
  50. Law M, Brodsky JE, Babb J et al. High cerebral blood volume in human gliomas predicts deletion of chromosome 1p: Preliminary results of molecular studies in gliomas with elevated perfusion. J. Magn. Reson. Imaging 25(6), 1113–1119 (2007).
  51. Brown R, Zlatescu M, Sijben A et al. The use of magnetic resonance imaging to noninvasively detect genetic signatures in oligodendroglioma. Clin. Cancer Res. 14(8), 2357–2362 (2008).
  52. Kapoor GS, Gocke TA, Chawla S et al. Magnetic resonance perfusion-weighted imaging defines angiogenic subtypes of oligodendroglioma according to 1p19q and EGFR status. J. Neurooncol. 92(3), 373–386 (2009).
  53. Watanabe K, Sato K, Biernat W et al. Incidence and timing of p53 mutations during astrocytoma progression in patients with multiple biopsies. Clin. Cancer Res. 3(4), 523–530 (1997).
  54. Stander M, Peraud A, Leroch B, Kreth FW. Prognostic impact of TP53 mutation status for adult patients with supratentorial World Health Organization grade II astrocytoma or oligoastrocytoma: a long-term analysis. Cancer 101(5), 1028–1035 (2004).
  55. Gaiser T, Becker MR, Meyer J, Habel A, Siegelin MD. p53-mediated inhibition of angiogenesis in diffuse low-grade astrocytomas. Neurochem. Int. 54(7), 458–463 (2009).
  56. Ware ML, Hirose Y, Scheithauer BW et al. Genetic aberrations in gliomatosis cerebri. Neurosurgery 60(1), 150–158; discussion 158 (2007).
  57. Stevenson CB, Ehtesham M, McMillan KM et al. CXCR4 expression is elevated in glioblastoma multiforme and correlates with an increase in intensity and extent of peritumoral T2-weighted magnetic resonance imaging signal abnormalities. Neurosurgery 63(3), 560–569; discussion 569–570 (2008).
  58. Komine C, Watanabe T, Katayama Y, Yoshino A, Yokoyama T, Fukushima T. Promoter hypermethylation of the DNA repair gene O6-methylguanine-DNA methyltransferase is an independent predictor of shortened progression-free survival in patients with low-grade diffuse astrocytomas. Brain Pathol. 13(2), 176–184 (2003).
  59. Nakasu S, Fukami T, Jito J, Matsuda M. Prognostic significance of loss of O6-methylguanine-DNA methyltransferase expression in supratentorial diffuse low-grade astrocytoma. Surg. Neurol. 68(6), 603–608; discussion 608–609 (2007).
  60. Nakamura M, Watanabe T, Yonekawa Y, Kleihues P, Ohgaki H. Promoter methylation of the DNA repair gene MGMT in astrocytomas is frequently associated with G:C –> A:T mutations of the TP53 tumor suppressor gene. Carcinogenesis 22(10), 1715–1719 (2001).
  61. Parsons DW, Jones S, Zhang X et al. An integrated genomic analysis of human glioblastoma multiforme. Science 321(5897), 1807–1812 (2008).
    •• Landmark study reporting an integrated analysis of the GBM cancer genome, including expression analysis.
  62. Balss J, Meyer J, Mueller W, Korshunov A, Hartmann C, von Deimling A. Analysis of the IDH1 codon 132 mutation in brain tumors. Acta Neuropathol. 116(6), 597–602 (2008).
  63. Ichimura K, Pearson DM, Kocialkowski S et al. IDH1 mutations are present in the majority of common adult gliomas but are rare in primary glioblastomas. Neuro. Oncol. 11(4), 341–347 (2009).
  64. Yan H, Parsons DW, Jin G et al. IDH1 and IDH2 mutations in gliomas. N. Engl. J. Med. 360(8), 765–773 (2009).
    • Critical paper on the frequency and functional consequences of IDH mutations in gliomas.
  65. Jasanoff A. MRI contrast agents for functional molecular imaging of brain activity. Curr. Opin. Neurobiol. 17(5), 593–600 (2007).
  66. Schaller BJ, Modo M, Buchfelder M. Molecular imaging of brain tumors: a bridge between clinical and molecular medicine? Mol. Imaging Biol. 9(2), 60–71 (2007).
  67. Liu CH, Kim YR, Ren JQ, Eichler F, Rosen BR, Liu PK. Imaging cerebral gene transcripts in live animals. J. Neurosci. 27(3), 713–722 (2007).