Pilocytic astrocytomas (PAs) were recognized as a discrete clinical entity over 70 years ago. They are relatively benign (WHO grade I) and have, as a group, a 10-year survival of over 90 %. Many ...require merely surgical removal and only very infrequently do they progress to more malignant gliomas. While most show classical morphology, they may present a spectrum of morphological patterns, and there are difficult cases that show similarities to other gliomas, some of which are malignant and require aggressive treatment. Until recently, almost nothing was known about the molecular mechanisms involved in their development. The use of high-throughput sequencing techniques interrogating the whole genome has shown that single abnormalities of the mitogen-activating protein kinase (MAPK) pathway are exclusively found in almost all cases, indicating that PA represents a one-pathway disease. The most common mechanism is a tandem duplication of a ≈2 Mb-fragment of #7q, giving rise to a fusion between two genes, resulting in a transforming fusion protein, consisting of the N-terminus of KIAA1549 and the kinase domain of BRAF. Additional infrequent fusion partners have been identified, along with other abnormalities of the MAP-K pathway, affecting tyrosine kinase growth factor receptors at the cell surface (e.g., FGFR1) as well as BRAF V600E, KRAS, and NF1 mutations among others. However, while the KIAA1549-BRAF fusion occurs in all areas, the incidence of the various other mutations identified differs in PAs that develop in different regions of the brain. Unfortunately, from a diagnostic standpoint, almost all mutations found have been reported in other brain tumor types, although some retain considerable utility. These molecular abnormalities will be reviewed, and the difficulties in their potential use in supporting a diagnosis of PA, when the histopathological findings are equivocal or in the choice of individualized therapy, will be discussed.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We ...therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number aberrations. Optimization of probe design, library generation and sequencing conditions on 150 samples resulted in a 5-workday routine workflow from the formalin-fixed paraffin-embedded sample to neuropathological report. This protocol was applied to 79 retrospective cases with established molecular aberrations for validation and 71 prospective cases for discovery of potential therapeutic targets. Concordance of NGS compared to established, single biomarker methods was 98.0 %, with discrepancies resulting from one case where a
TERT
promoter mutation was not called by NGS and three ATRX mutations not being detected by Sanger sequencing. Importantly, in samples with low tumor cell content, NGS was able to identify mutant alleles that were not detectable by traditional methods. Information derived from NGS data identified potential targets for experimental therapy in 37/47 (79 %) glioblastomas, 9/10 (90 %) pilocytic astrocytomas, and 5/14 (36 %) medulloblastomas in the prospective target discovery cohort. In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to ...well-calibrated probability estimates for these typically highly multiclass classification tasks are still lacking. To support this choice, we evaluated well-established machine learning (ML) classifiers including random forests (RFs), elastic net (ELNET), support vector machines (SVMs) and boosted trees in combination with post-processing algorithms and developed ML workflows that allow for unbiased class probability (CP) estimation. Calibrators included ridge-penalized multinomial logistic regression (MR) and Platt scaling by fitting logistic regression (LR) and Firth's penalized LR. We compared these workflows on a recently published brain tumor 450k DNA methylation cohort of 2,801 samples with 91 diagnostic categories using a 5 × 5-fold nested cross-validation scheme and demonstrated their generalizability on external data from The Cancer Genome Atlas. ELNET was the top stand-alone classifier with the best calibration profiles. The best overall two-stage workflow was MR-calibrated SVM with linear kernels closely followed by ridge-calibrated tuned RF. For calibration, MR was the most effective regardless of the primary classifier. The protocols developed as a result of these comparisons provide valuable guidance on choosing ML workflows and their tuning to generate well-calibrated CP estimates for precision diagnostics using DNA methylation data. Computation times vary depending on the ML algorithm from <15 min to 5 d using multi-core desktop PCs. Detailed scripts in the open-source R language are freely available on GitHub, targeting users with intermediate experience in bioinformatics and statistics and using R with Bioconductor extensions.
Epileptogenic tumors affecting children and young adults are a morphologically diverse collection of neuroepithelial neoplasms that, as a group, exhibit varying levels of glial and/or neuronal ...differentiation. Recent advances in molecular profiling technology, including comprehensive DNA sequencing and methylation analysis, have enabled the application of more precise and biologically relevant classification schemes to these tumors. In this report, we describe a morphologically and molecularly distinct epileptogenic neoplasm, the polymorphous low-grade neuroepithelial tumor of the young (PLNTY), which likely accounts for a sizable portion of oligodendroglioma-like tumors affecting the pediatric population. Characteristic microscopic findings most notably include infiltrative growth, the invariable presence of oligodendroglioma-like cellular components, and intense immunolabeling for cluster of differentiation 34 (CD34). Moreover, integrative molecular profiling reveals a distinct DNA methylation signature for PLNTYs, along with frequent genetic abnormalities involving either B-Raf proto-oncogene (
BRAF
) or fibroblast growth factor receptors 2 and 3 (
FGFR2
,
FGFR3
). These findings suggest that PLNTY represents a distinct biological entity within the larger spectrum of pediatric, low-grade neuroepithelial tumors.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Pediatric glioblastoma (pedGBM) is amongst the most common malignant brain tumors of childhood and carries a dismal prognosis. In contrast to adult GBM, few molecular prognostic markers for the ...pediatric counterpart have been established. We, therefore, investigated the prognostic significance of genomic and epigenetic alterations through molecular analysis of 202 pedGBM (1–18 years) with comprehensive clinical annotation. Routinely prepared formalin-fixed paraffin-embedded tumor samples were assessed for genome-wide DNA methylation profiles, with known candidate genes screened for alterations via direct sequencing or FISH. Unexpectedly, a subset of histologically diagnosed GBM (
n
= 40, 20 %) displayed methylation profiles similar to those of either low-grade gliomas or pleomorphic xanthoastrocytomas (PXA). These tumors showed a markedly better prognosis, with molecularly PXA-like tumors frequently harboring BRAF V600E mutations and 9p21 (
CDKN2A
) homozygous deletion. The remaining 162 tumors with pedGBM molecular signatures comprised four subgroups: H3.3 G34-mutant (15 %), H3.3/H3.1 K27-mutant (43 %), IDH1-mutant (6 %), and H3/IDH wild-type (wt) GBM (36 %). These subgroups were associated with specific cytogenetic aberrations,
MGMT
methylation patterns and clinical outcomes. Analysis of follow-up data identified a set of biomarkers feasible for use in risk stratification: pedGBM with any oncogene amplification and/or K27M mutation (
n
= 124) represents a particularly unfavorable group, with 3-year overall survival (OS) of 5 %, whereas tumors without these markers (
n
= 38) define a more favorable group (3-year OS ~70 %).Combined with the lower grade-like lesions, almost 40 % of pedGBM cases had distinct molecular features associated with a more favorable outcome. This refined prognostication method for pedGBM using a molecular risk algorithm may allow for improved therapeutic choices and better planning of clinical trial stratification for this otherwise devastating disease.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We ...hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (
n
= 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set (
n
= 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs) multivariable analyses for RFS showed that the baseline methylation classifier was not significant (
p
= 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence (
p
< 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In contrast to the relative morphological uniformity of histone H3 K27-mutant high-grade gliomas, H3 G34-mutant tumors present as a histopathologically heterogeneous group of neoplasms, with ...microscopic characteristics typical of either glioblastoma (GBM) or central nervous system primitive neuroectodermal tumors (CNS-PNET). In the current study, we performed an integrative clinical, histopathological and molecular analysis of 81 G34-mutant CNS tumors. Routinely prepared tumor tissues were investigated for genomic and epigenomic alterations. Despite their divergent histopathological appearance, CNS tumors with H3.3 G34 mutations displayed uniform epigenetic signatures, suggesting a single biological origin. Comparative cytogenetic analysis with other GBM subtypes disclosed a high frequency and high specificity of 3q and 4q loss across G34-mutant tumors.
PDGFRA
amplification was more common in cases with GBM than with PNET morphology (36 vs. 5 %, respectively), while
CCND2
amplifications showed the opposite trend (5 vs. 27 %). Survival analysis revealed the presence of amplified oncogene(s) and
MGMT
methylation as independent prognostic markers for poor and favorable outcomes, respectively. No difference in outcome was found between morphological variants (GBM vs. PNET). Thus, different histological variants of G34-mutant CNS tumors likely comprise a single biological entity (high-grade glioma with H3 G34 mutation, HGG_G34), which should be outlined in future diagnostic and therapeutic classifications. Screening for H3.3 G34 mutation should therefore be recommended as a routine diagnostic marker for supratentorial CNS tumors across a broad histological spectrum.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Diffuse gliomas are represented in the 2007 WHO classification as astrocytomas, oligoastrocytomas and oligodendrogliomas of grades II and III and glioblastomas WHO grade IV. Molecular data on these ...tumors have a major impact on prognosis and therapy of the patients. Consequently, the inclusion of molecular parameters in the WHO definition of brain tumors is being planned and has been forwarded as the “ISN-Haarlem” consensus. We, here, analyze markers of special interest including ATRX, IDH and 1p/19q codeletion in a series of 405 adult patients. Among the WHO 2007 classified tumors were 152 astrocytomas, 61 oligodendrogliomas, 63 oligoastrocytomas and 129 glioblastomas. Following the concepts of the “ISN-Haarlem”, we rediagnosed the series to obtain “integrated” diagnoses with 155 tumors being astrocytomas, 100 oligodendrogliomas and 150 glioblastomas. In a subset of 100 diffuse gliomas from the NOA-04 trial with long-term follow-up data available, the “integrated” diagnosis had a significantly greater prognostic power for overall and progression-free survival compared to WHO 2007. Based on the “integrated” diagnoses, loss of ATRX expression was close to being mutually exclusive to 1p/19q codeletion, with only 2 of 167 ATRX-negative tumors exhibiting 1p/19q codeletion. All but 4 of 141 patients with loss of ATRX expression and diffuse glioma carried either
IDH1
or
IDH2
mutations. Interestingly, the majority of glioblastoma patients with loss of ATRX expression but no IDH mutations exhibited an
H3F3A
mutation. Further, all patients with 1p/19 codeletion carried a mutation in
IDH1
or
IDH2
. We present an algorithm based on stepwise analysis with initial immunohistochemistry for ATRX and IDH1-R132H followed by 1p/19q analysis followed by
IDH
sequencing which reduces the number of molecular analyses and which has a far better association with patient outcome than WHO 2007.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The vast majority of peripheral nerve sheath tumors derive from the Schwann cell lineage and comprise diverse histological entities ranging from benign schwannomas and neurofibromas to high-grade ...malignant peripheral nerve sheath tumors (MPNST), each with several variants. There is increasing evidence for methylation profiling being able to delineate biologically relevant tumor groups even within the same cellular lineage. Therefore, we used DNA methylation arrays for methylome- and chromosomal profile-based characterization of 171 peripheral nerve sheath tumors. We analyzed 28 conventional high-grade MPNST, three malignant Triton tumors, six low-grade MPNST, four epithelioid MPNST, 33 neurofibromas (15 dermal, 8 intraneural, 10 plexiform), six atypical neurofibromas, 43 schwannomas (including 5 NF2 and 5 schwannomatosis associated cases), 11 cellular schwannomas, 10 melanotic schwannomas, 7 neurofibroma/schwannoma hybrid tumors, 10 nerve sheath myxomas and 10 ganglioneuromas. Schwannomas formed different epigenomic subgroups including a vestibular schwannoma subgroup. Cellular schwannomas were not distinct from conventional schwannomas. Nerve sheath myxomas and neurofibroma/schwannoma hybrid tumors were most similar to schwannomas. Dermal, intraneural and plexiform neurofibromas as well as ganglioneuromas all showed distinct methylation profiles. Atypical neurofibromas and low-grade MPNST were indistinguishable with a common methylation profile and frequent losses of
CDKN2A
. Epigenomic analysis finds two groups of conventional high-grade MPNST sharing a frequent loss of neurofibromin. The larger of the two groups shows an additional loss of trimethylation of histone H3 at lysine 27 (H3K27me3). The smaller one retains H3K27me3 and is found in spinal locations. Sporadic MPNST with retained neurofibromin expression did not form an epigenetic group and most cases could be reclassified as cellular schwannomas or soft tissue sarcomas. Widespread immunohistochemical loss of H3K27me3 was exclusively seen in MPNST of the main methylation cluster, which defines it as an additional useful marker for the differentiation of cellular schwannoma and MPNST.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
IDH
wild type (
IDH
wt) anaplastic astrocytomas WHO grade III (AA III) are associated with poor outcome. To address the possibilities of molecular subsets among astrocytoma or of diagnostic ...reclassification, we analyzed a series of 160 adult
IDH
wt tumors comprising 120 AA III and 40 diffuse astrocytomas WHO grade II (A II) for molecular hallmark alterations and established methylation and copy number profiles. Based on molecular profiles and hallmark alterations the tumors could be grouped into four major sets. 124/160 (78 %) tumors were diagnosed as the molecular equivalent of conventional glioblastoma (GBM), and 15/160 (9 %) as GBM-
H3F3A
mutated (GBM-H3). 13/160 (8 %) exhibited a distinct methylation profile that was most similar to GBM-H3-K27, however, lacked the
H3F3A
mutation. This group was enriched for tumors of infratentorial and midline localization and showed a trend towards a more favorable prognosis. All but one of the 120
IDH
wt AA III could be assigned to these three groups. 7 tumors recruited from the 40 A II, comprised a variety of molecular signatures and all but one were reclassified into distinct WHO entities of lower grades. Interestingly,
TERT
mutations were exclusively restricted to the molecular GBM (78 %) and associated with poor clinical outcome. However, the GBM-H3 group lacking
TERT
mutations appeared to fare even worse. Our data demonstrate that most of the tumors diagnosed as
IDH
wt astrocytomas can be allocated to other tumor entities on a molecular basis. The diagnosis of
IDH
wt diffuse astrocytoma or anaplastic astrocytoma should be used with caution.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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