Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups.
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ABSTRACT:
SUBMITTER: Pajtler KW
PROVIDER: S-EPMC4712639 | biostudies-literature | 2015 May
REPOSITORIES: biostudies-literature
Publications
Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups.
Pajtler Kristian W KW Witt Hendrik H Sill Martin M Jones David T W DT Hovestadt Volker V Kratochwil Fabian F Wani Khalida K Tatevossian Ruth R Punchihewa Chandanamali C Johann Pascal P Reimand Jüri J Warnatz Hans-Jörg HJ Ryzhova Marina M Mack Steve S Ramaswamy Vijay V Capper David D Schweizer Leonille L Sieber Laura L Wittmann Andrea A Huang Zhiqin Z van Sluis Peter P Volckmann Richard R Koster Jan J Versteeg Rogier R Fults Daniel D Toledano Helen H Avigad Smadar S Hoffman Lindsey M LM Donson Andrew M AM Foreman Nicholas N Hewer Ekkehard E Zitterbart Karel K Gilbert Mark M Armstrong Terri S TS Gupta Nalin N Allen Jeffrey C JC Karajannis Matthias A MA Zagzag David D Hasselblatt Martin M Kulozik Andreas E AE Witt Olaf O Collins V Peter VP von Hoff Katja K Rutkowski Stefan S Pietsch Torsten T Bader Gary G Yaspo Marie-Laure ML von Deimling Andreas A Lichter Peter P Taylor Michael D MD Gilbertson Richard R Ellison David W DW Aldape Kenneth K Korshunov Andrey A Kool Marcel M Pfister Stefan M SM
Cancer cell 20150501 5
Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, su ...[more]
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Project description:Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.
2015-05-21 | GSE65362 | GEO
Project description:Ependymal tumors across age groups have been classified solely by histopathology. It is, however, commonly accepted that this classification has limited clinical utility based on its poor reliability. We aimed at establishing a reliable and reproducible molecular classification using DNA methylation fingerprints of the tumors. Studying a cohort of 500 tumors allowed for the delineation of nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS). Two of the supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification by far and thus might serve as a basis for the upcoming update of the WHO classification of CNS tumors. DNA methylation patterns in tumors have been shown to represent a very stable molecular memory of the respective cell of origin throughout the disease course, thus making them particularly suitable for tumor classification purposes. Methylation fingerprinting of a large series of ependymal tumors of all grades revealed a highly reliable way of classifying this clinically extremely heterogeneous group of malignancies. In fact, out of nine highly reproducible molecular subgroups identified in the supratentorial, infratentorial and spinal regions, only two harbor the vast majority of clinical high-risk patients (mostly children) for whom novel therapeutic concepts are desperately needed. Since this analysis can be performed from minute amounts of DNA extracted from archived material, it is ideally suited for routine clinical application. We investigated a set of 562 ependymal tumors using the Illumina 450k methylation array.
2015-05-21 | E-GEOD-65362 | biostudies-arrayexpress
Project description:Tremendous progress has recently been made in both molecular subgrouping, and the establishment of prognostic biomarkers for embryonal brain tumors, particularly medulloblastoma. Several prognostic biomarkers that were initially identified in retrospective cohorts of medulloblastoma, including MYC and MYCN amplification, nuclear ?-catenin accumulation, and chromosome 17 aberrations have now been validated in clinical trials. Moreover, molecular subgroups based on distinct transcriptome profiles have been consistently reported from various groups on different platforms demonstrating that the concept of distinct medulloblastoma subgroups is very robust. Well-described subgroups of medulloblastomas include tumors showing wingless signaling pathway (Wnt) activation, and another characterized by sonic hedgehog pathway activity. Two or more additional subgroups were consistently reported to contain the vast majority of high-risk tumors, including most tumors with metastatic disease at diagnosis and/or large cell/anaplastic histology. Several years ago, atypical teratoid rhabdoid tumor (AT/RT) was recognized as a separate entity based on its distinct biology and particularly aggressive clinical behavior. These tumors may occur supra or infratentorially and are usually found to have genetic alterations of SMARCB1 (INI1/hSNF5), a tumor suppressor gene located on chromosome 22q. Subsequent loss of SMARCB1 protein expression comprises a relatively specific and sensitive diagnostic marker for AT/RT. For CNS primitive neuroectodermal tumors (CNS PNETs), a consistent finding has been that they are molecularly distinct from medulloblastoma. Furthermore, a distinct fraction of CNS PNETs with particularly poor prognosis only occurring in young children was delineated, which was previously labeled ependymoblastoma or embryonal tumor with abundant neuropil and true rosettes (ETANTR) and which is morphologically characterized by the presence of multilayered "ependymoblastic" rosettes. This group of tumors shows a unique cytogenetic abnormality not seen in other brain tumors: focal amplification of a micro-RNA cluster at chromosome 19q13.42, which has never been found to be amplified in other CNS PNETs, medulloblastoma or AT/RT. In summary, these consistent findings have significantly contributed to our ability to sub-classify embryonal brain tumors into clinically and biologically meaningful strata and, for some of the subgroups, have led to the identification of specific targets for future development of molecularly targeted therapies.
| S-EPMC4512653 | biostudies-literature
Project description:Advances in the understanding of the molecular biology of central nervous system (CNS) tumors prompted a new World Health Organization (WHO) classification scheme in 2021, only 5 years after the prior iteration. The 2016 version was the first to include specific molecular alterations in the diagnoses of a few tumors, but the 2021 system greatly expanded this approach, with over 40 tumor types and subtypes now being defined by their key molecular features. Many tumors have also been reconceptualized into new "supercategories," including adult-type diffuse gliomas, pediatric-type diffuse low- and high-grade gliomas, and circumscribed astrocytic gliomas. Some entirely new tumors are in this scheme, particularly pediatric tumors. Naturally, these changes will impact how CNS tumor patients are diagnosed and treated, including clinical trial enrollment. This review addresses the most clinically relevant changes in the 2021 WHO book, including diffuse and circumscribed gliomas, ependymomas, embryonal tumors, and meningiomas.
| S-EPMC9723092 | biostudies-literature
Project description:Background and Purpose Gliomas are one of the most common tumors in the central nervous system. This study aimed to explore the correlation between MRI morphological characteristics, apparent diffusion coefficient (ADC) parameters and pathological grades, as well as IDH gene phenotypes of gliomas. Methods Preoperative MRI data from 166 glioma patients with pathological confirmation were retrospectively analyzed to compare the differences of MRI characteristics and ADC parameters between the low-grade and high-grade gliomas (LGGs vs. HGGs), IDH mutant and wild-type gliomas (IDHmut vs. IDHwt). Multivariate models were constructed to predict the pathological grades and IDH gene phenotypes of gliomas and the performance was assessed by the receiver operating characteristic (ROC) analysis. Results Two multivariable logistic regression models were developed by incorporating age, ADC parameters, and MRI morphological characteristics to predict pathological grades, and IDH gene phenotypes of gliomas, respectively. The Noninvasive Grading Model classified tumor grades with areas under the ROC curve (AUROC) of 0.934 (95% CI=0.895-0.973), sensitivity of 91.2%, and specificity of 78.6%. The Noninvasive IDH Genotyping Model differentiated IDH types with an AUROC of 0.857 (95% CI=0.787-0.926), sensitivity of 88.2%, and specificity of 63.8%. Conclusion MRI features were correlated with glioma grades and IDH mutation status. Multivariable logistic regression models combined with MRI morphological characteristics and ADC parameters may provide a noninvasive and preoperative approach to predict glioma grades and IDH mutation status.
| S-EPMC9196247 | biostudies-literature
Project description:BackgroundPediatric neuro-oncology was profoundly changed in the wake of the 2016 revision of the WHO Classification of Tumors of the Central Nervous System. Practitioners were challenged to quickly adapt to a system of tumor classification redefined by molecular diagnostics.MethodsWe designed a 22-question survey studying the impact of the revised WHO classification on pediatric high-grade glioma. The survey collected basic demographics, general attitudes, issues encountered, and opinions on pediatric subtypes. Participant answers were analyzed along socioeconomic lines utilizing the human development index (HDI) of the United Nations and membership in the group of seven (G7) world economic forum.ResultsFour hundred and sixty-five participants from 53 countries were included, 187 pediatric neurooncologists (40%), 160 neuropathologists (34%), and 118 other experts (26%). When asked about pediatric high-grade glioma entities, participants from very high development countries preferred treating a patient based on genetic findings. Participants from high and medium development countries indicated using traditional histology and tumor location as mainstays for therapeutic decisions. Non-G7 countries tended to regard the introduction of molecularly characterized tumor entities as a problem for daily routine due to lack of resources.ConclusionsOur findings demonstrate an overall greater reliance and favorability to molecular diagnostics among very high development countries. A disparity in resources and access to molecular diagnostics has left some centers unable to classify pediatric high-grade glioma per the WHO classification. The forthcoming edition should strain to abate disparities in molecular diagnostic availability and work toward universal adaptation.
| S-EPMC8478775 | biostudies-literature
Project description:BackgroundHistopathological diagnosis of bone tumors is challenging for pathologists. We aim to classify bone tumors histopathologically in terms of aggressiveness using deep learning (DL) and compare performance with pathologists.MethodsA total of 427 pathological slides of bone tumors were produced and scanned as whole slide imaging (WSI). Tumor area of WSI was annotated by pathologists and cropped into 716,838 image patches of 256 × 256 pixels for training. After six DL models were trained and validated in patch level, performance was evaluated on testing dataset for binary classification (benign vs. non-benign) and ternary classification (benign vs. intermediate vs. malignant) in patch-level and slide-level prediction. The performance of four pathologists with different experiences was compared to the best-performing models. The gradient-weighted class activation mapping was used to visualize patch's important area.ResultsVGG-16 and Inception V3 performed better than other models in patch-level binary and ternary classification. For slide-level prediction, VGG-16 and Inception V3 had area under curve of 0.962 and 0.971 for binary classification and Cohen's kappa score (CKS) of 0.731 and 0.802 for ternary classification. The senior pathologist had CKS of 0.685 comparable to both models (p = 0.688 and p = 0.287) while attending and junior pathologists showed lower CKS than the best model (each p < 0.05). Visualization showed that the DL model depended on pathological features to make predictions.ConclusionDL can effectively classify bone tumors histopathologically in terms of aggressiveness with performance similar to senior pathologists. Our results are promising and would help expedite the future application of DL-assisted histopathological diagnosis for bone tumors.
| S-EPMC8526973 | biostudies-literature
Project description:BackgroundMolecular markers provide important biological and clinical information related to the classification of brain tumors, and the integration of relevant molecular parameters into brain tumor classification systems has been a widely discussed topic in neuro-oncology over the past decade. With recent advances in the development of clinically relevant molecular signatures and the 2016 World Health Organization (WHO) update, the views of the neuro-oncology community on such changes would be informative for implementing this process.MethodsA survey with 8 questions regarding molecular markers in tumor classification was sent to an email list of Society for Neuro-Oncology members and attendees of prior meetings (n=5065). There were 403 respondents. Analysis was performed using whole group response, based on self-reported subspecialty.ResultsThe survey results show overall strong support for incorporating molecular knowledge into the classification and clinical management of brain tumors. Across all 7 subspecialty groups, ≥70% of respondents agreed to this integration. Interestingly, some variability is seen among subspecialties, notably with lowest support from neuropathologists, which may reflect their roles in implementing such diagnostic technologies.ConclusionBased on a survey provided to the neuro-oncology community, we report strong support for the integration of molecular markers into the WHO classification of brain tumors, as well as for using an integrated "layered" diagnostic format. While membership from each specialty showed support, there was variation by specialty in enthusiasm regarding proposed changes. The initial results of this survey influenced the deliberations underlying the 2016 WHO classification of tumors of the central nervous system.
| S-EPMC5464323 | biostudies-literature
Project description:This study comprises DNA methylation profiles of 15 white matter samples obtained from CNS autopsies across different age groups to study age-associated epigenetic changes. The samples comprise 5 young, 5 adult and 5 old indivudials.
2024-01-01 | GSE247702 | GEO
Project description:AimThis study will explore the genetic and epigenetic alterations in astrocytomas, and identify the critical molecular signatures and signaling pathways for prognosis assessment by multiplatform comprehensive analysis.MethodWe performed integration analyses of incorporating DNA methylation, mRNA expression, microRNA expression, and long non-coding RNA (lncRNA) expression in 33 astrocytic tumor tissues and 9 non-tumor brain tissues.ResultWe observed that 11,795 DNA methylation sites, 3,627 genes, 136 microRNAs, and 3,334 lncRNAs were significantly differential between tumors and non-tumor brain tissues, and the filtered signatures through comprehensive analysis were significantly enriched in calcium signaling pathway. Furthermore, four signatures involved in calcium signaling pathway and age could contribute to predicting the patients' overall survival. Additionally, we identified differentially expressed signatures between IDH-mutated and IDH wild-type astrocytic tumors, and complement and coagulation cascades pathway was the most significant pathway in functional enrichment analysis using multiplatform data. The IDH wild-type astrocytomas were divided into two subtypes by Cluster of Cluster (CoC) analysis, one of which was enriched for astrocytomas overexpressed in chemokine signaling pathway.ConclusionThe calcium signaling pathway played a key role in astrocytoma tumorigenesis and prognosis. IDH mutation was a vital biomarker, and resulted in the change of expression level in complement and coagulation cascades pathway. The chemokine signaling pathway could characterize subtypes of IDH wild-type astrocytomas.
| S-EPMC5707104 | biostudies-literature