Cytogenetic and loss of heterozygosity studies have suggested the presence of at least one tumor suppressor gene on chromosome 10 involved in the formation of high grade gliomas. Recently, the PTEN gene, also termed MMAC1 or TEP1, on chromosomal band 10q23 has been identi®ed. Initial studies revealed mutations of PTEN in limited series of glioma cell lines and glioblastomas. In order to systematically evaluate the involvement of PTEN in gliomas, we have analysed the entire PTEN coding sequence by SSCP and direct sequencing in a series of 331 gliomas and glioneuronal tumors. PTEN mutations were detected in 20/142 glioblastomas, 1/7 giant cell glioblastomas, 1/2 gliosarcomas, 1/30 pilocytic astrocytomas and 2/22 oligodendrogliomas. No PTEN mutations were detected in 52 astrocytomas, 37 oligoastrocytomas, three subependymal giant cell astrocytomas, four pleomorphic xanthoastrocytomas, 15 ependymomas, 16 gangliogliomas and one dysembryoplastic neuroepithelial tumor. In addition, all tumors were examined for the presence of homozygous deletions of the PTEN gene; these were detected in 7 glioblastomas that did not have PTEN mutations. Therefore, PTEN mutations occur in approximately 20% of glioblastomas but are rare in lower grade gliomas. These ®ndings con®rm that PTEN is one of the chromosome 10 tumor suppressor genes involved in the development of glioblastomas.

Aims/hypothesisPancreatic islet beta cell failure causes type 2 diabetes in humans. To identify transcriptomic changes in type 2 diabetic islets, the Innovative Medicines Initiative for Diabetes: Improving beta-cell function and identification of diagnostic biomarkers for treatment monitoring in Diabetes (IMIDIA) consortium (www.imidia.org) established a comprehensive, unique multicentre biobank of human islets and pancreas tissues from organ donors and metabolically phenotyped pancreatectomised patients (PPP).MethodsAffymetrix microarrays were used to assess the islet transcriptome of islets isolated either by enzymatic digestion from 103 organ donors (OD), including 84 non-diabetic and 19 type 2 diabetic individuals, or by laser capture microdissection (LCM) from surgical specimens of 103 PPP, including 32 non-diabetic, 36 with type 2 diabetes, 15 with impaired glucose tolerance (IGT) and 20 with recent-onset diabetes (<1 year), conceivably secondary to the pancreatic disorder leading to surgery (type 3c diabetes). Bioinformatics tools were used to (1) compare the islet transcriptome of type 2 diabetic vs non-diabetic OD and PPP as well as vs IGT and type 3c diabetes within the PPP group; and (2) identify transcription factors driving gene co-expression modules correlated with insulin secretion ex vivo and glucose tolerance in vivo. Selected genes of interest were validated for their expression and function in beta cells.ResultsComparative transcriptomic analysis identified 19 genes differentially expressed (false discovery rate ≤0.05, fold change ≥1.5) in type 2 diabetic vs non-diabetic islets from OD and PPP. Nine out of these 19 dysregulated genes were not previously reported to be dysregulated in type 2 diabetic islets. Signature genes included TMEM37, which inhibited Ca2+-influx and insulin secretion in beta cells, and ARG2 and PPP1R1A, which promoted insulin secretion. Systems biology approaches identified HNF1A, PDX1 and REST as drivers of gene co-expression modules correlated with impaired insulin secretion or glucose tolerance, and 14 out of 19 differentially expressed type 2 diabetic islet signature genes were enriched in these modules. None of these signature genes was significantly dysregulated in islets of PPP with impaired glucose tolerance or type 3c diabetes.Conclusions/interpretationThese studies enabled the stringent definition of a novel transcriptomic signature of type 2 diabetic islets, regardless of islet source and isolation procedure. Lack of this signature in islets from PPP with IGT or type 3c diabetes indicates differences possibly due to peculiarities of these hyperglycaemic conditions and/or a role for duration and severity of hyperglycaemia. Alternatively, these transcriptomic changes capture, but may not precede, beta cell failure.Electronic supplementary materialThe online version of this article (10.1007/s00125-017-4500-3) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

We investigated 67 meningothelial tumors (20 benign meningiomas, 34 atypical meningiomas, and 13 anaplastic meningiomas) for losses of genetic information from chromosome arms 1p and 9p, as well as for deletion, mutation, and expression of the tumor suppressor genes CDKN2A (p16(INKa)/MTS1), p14(ARF), CDKN2B (p15(INK4b)/MTS2) (all located at 9p21) and CDKN2C (1p32). Comparative genomic hybridization and microsatellite analysis showed losses on 1p in 11 anaplastic meningiomas (85%), 23 atypical meningiomas (68%), and 5 benign meningiomas (25%). One atypical meningioma with loss of heterozygosity on 1p carried a somatic CDKN2C mutation (c.202C>T: R68X). Losses on 9p were found in five anaplastic meningiomas (38%), six atypical meningiomas (18%), and one benign meningioma (5%). Six anaplastic meningiomas (46%) and one atypical meningioma (3%) showed homozygous deletions of the CDKN2A, p14(ARF), and CDKN2B genes. Two anaplastic meningiomas carried somatic point mutations in CDKN2A (c.262G>T: E88X and c.262G>A: E88K) and p14(ARF) (c.305G>T: G102V and c.305G>A: G102E). One anaplastic meningioma, three atypical meningiomas, and one benign meningioma without a demonstrated homozygous deletion or mutation of CDKN2A, p14(ARF), or CDKN2B lacked detectable transcripts from at least one of these genes. Hypermethylation of CDKN2A, p14(ARF), and CDKN2B could be demonstrated in one of these cases. Taken together, our results indicate that CDKN2C is rarely altered in meningiomas. However, the majority of anaplastic meningiomas either show homozygous deletions of CDKN2A, p14(ARF), and CDKN2B, mutations in CDKN2A and p14(ARF), or lack of expression of one or more of these genes. Thus, inactivation of the G(1)/S-phase cell-cycle checkpoint is an important aberration in anaplastic meningiomas.

The recognition of molecular subsets among glioblastomas has raised the question whether distinct mutations in glioblastoma-associated genes may serve as prognostic markers. The present study on glioblastomas (GBM) from 97 consecutively sampled adult patients is based on a clinical, histopathological, immunohistochemical, and molecular genetic analysis. Parameters assessed were age at diagnosis, survival, cell type, proliferation, necrosis, microvascular proliferation, sarcomatous growth, lymphocytic infiltration, thromboses, calcifications, GFAP expression, MIB-1 index, loss of heterozygosity (LOH) of the chromosomal arms 1p, 10p, 10q, 17p, 19q and structural alterations in the TP53, EGFR and PTEN genes. As in previous studies, younger age was significantly associated with better survival. Among the molecular parameters, TP53 mutations and LOH10q emerged as favorable and poor prognostic factors, respectively. TP53 mutations were a favorable prognostic factor independent of whether glioblastomas were primary or secondary. LOH1p or 19q, lesions suspected to be over-represented in long term survivors with malignant glioma, were not associated with better survival. However, the combination of LOH1p and LOH19q defined GBM patients with a significantly better survival. Notably, these patients did not exhibit morphological features reminiscent of oligodendroglioma. These findings indicate that genotyping of glioblastoma may provide clinical information of prognostic importance.

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In an earlier study, we showed that heteroplasmy in the mitochondrial genome of gliomas sometimes occurs in a D-loop polycytosine tract. We extended this study by pairwise comparisons between glioma samples and adjacent brain tissue of 55 patients (50 glioblastomas, 1 astrocytoma WHO grade III, 4 astrocytomas WHO grade II). We used a combination of laser microdissection and PCR to detect and quantify variations in the polycytosine tract. New length variants undetectable in the adjacent brain tissue were observed in 5 glioblastomas (9%). In 2 of these cases, samples from a lower tumor stage (WHO grade II) could be analyzed and revealed the early occurrence of these mutations in both cases. Since the mitochondrial D-loop contains additional repeats and highly polymorphic non-coding sequences, we compared 17 glioblastomas with the corresponding blood samples of the same patients by direct sequencing of the complete D-loop. In 6 of these tumors (35%), instability was detected in 1 or 2 of 3 repeat regions; in 1 of these repeats, the instability was linked to a germline T-to-C transition. Furthermore, of 2 tumors (12%) 1 carried 1 and the other 9 additional transitions. In the latter patient, 6.7 kb of the protein coding mtDNA sequence were analyzed. Six silent transitions and 2 missense mutations (transitions) were found. All base substitutions appeared to be homoplasmic upon sequencing, and 89% occurred at known polymorphic sites in humans. Our data suggest that the same mechanisms that generate inherited mtDNA polymorphisms are strongly enhanced in gliomas and produce somatic mutations.

Using immunocytochemistry, we have compared the distribution of neurocan and phosphacan in the developing central nervous system. At embryonic day 13 (E13), phosphacan surrounds the radially oriented neuroepithelial cells of the telencephalon, whereas neurocan staining of brain parenchyma is very weak. By E16-19, strong staining of both neurocan and phosphacan is seen in the marginal zone and subplate of the neocortex, and phosphacan is present in the ventricular zone and also has a diffuse distribution in other brain areas. Phosphacan is also widely distributed in embryonic spinal cord, where it is strongly expressed throughout the gray and white matter, in the dorsal and ventral nerve roots, and in the roof plate at E13, when neurocan immunoreactivity is seen only in the mesenchyme of the future spinal canal. Neurocan first begins to appear in the spinal cord at E16-19, in the region of ventral motor neurons. In early postnatal and adult cerebellum, neurocan immunoreactivity is seen in the prospective white matter and in the granule cell, Purkinje cell, and molecular layers, whereas phosphacan immunoreactivity is associated with Bergmann glial fibers in the molecular layer and their cell bodies (the Golgi epithelial cells) below the Purkinje cells. These immunocytochemical results demonstrate that the expression of neurocan and phosphacan follow different developmental time courses not only in postnatal brain (as previously demonstrated by radioimmunoassay) but also in the embryonic central nervous system. The specific localization and different temporal expression patterns of these two proteoglycans are consistent with other evidence indicating that they have overlapping or complementary roles in axon guidance, cell interactions, and neurite outgrowth during nervous tissue histogenesis.

We have studied developmental changes in the structure and concentration of the hyaluronic acid‐binding proteoglycan, neurocan, and of phosphacan, another major chondroitin sulfate proteoglycan of nervous tissue that represents the extracellular domain of a receptor‐type protein tyrosine phosphatase. A new monoclonal antibody (designated 1F6), which recognizes an epitope in the N‐terminal portion of neurocan, has been used for the isolation of proteolytic processing fragments that occur together with link protein in a complex with hyaluronic acid. Both link protein and two of the neurocan fragments were identified by amino acid sequencing. The N‐terminal fragments of neurocan are also recognized by monoclonal antibodies (5C4, 8A4, and 3B1) to epitopes in the G1 and G2 domains of aggrecan and/or in the hyaluronic acid‐binding domain of link protein. The presence in brain of these N‐terminal fragments is consistent with the developmentally regulated appearance of the C‐terminal half of neurocan, which we described previously. We have also used a slot‐blot radioimmunoassay to determine the concentrations of neurocan and phosphacan in developing brain. The levels of both proteoglycans increased rapidly during early brain development, but whereas neurocan reached a peak at approximately postnatal day 4 and then declined to below embryonic levels in adult brain, the concentration of phosphacan remained essentially unchanged after postnatal day 12. Keratan sulfate on phosphacan‐KS (a glycoform that contains both chondroitin sulfate and keratan sulfate chains) was not detectable until just before birth, and its peak concentration (at 3 weeks postnatal) was reached ∼1 week later than that of the phosphacan core protein. Immunocytochemical studies using monoclonal antibodies to keratan sulfate (3H1 and 5D4) together with specific glycosidases (endo‐β‐galactosidase, keratanase, and keratanase II) also showed that with the exception of some very localized areas, keratan sulfate is generally not present in the embryonic rat CNS.