Methylation Class Research Articles

IGF1R Is a Potential New Therapeutic Target for HGNET-BCOR Brain Tumor Patients.

(1) Background: The high-grade neuroepithelial tumor of the central nervous system with BCOR alteration (HGNET-BCOR) is a highly malignant tumor. Preclinical models and molecular targets are urgently required for this cancer. Previous data suggest a potential role of insulin-like growth factor (IGF) signaling in HGNET-BCOR. (2) Methods: The primary HGNET-BCOR cells PhKh1 were characterized by western blot, copy number variation, and methylation analysis and by electron microscopy. The expression of IGF2 and IGF1R was assessed by qRT-PCR. The effect of chemotherapeutics and IGF1R inhibitors on PhKh1 proliferation was tested. The phosphorylation of IGF1R and downstream molecules was assessed by western blot. (3) Results: Phkh1 cells showed a DNA methylation profile compatible with the DNA methylation class “HGNET-BCOR” and morphologic features of cellular cannibalism. IGF2 and IGF1R were highly expressed by three HGNET-BCOR tumor samples and PhKh1 cells. PhKh1 cells were particularly sensitive to vincristine, vinblastine, actinomycin D (IC50 < 10 nM for all drugs), and ceritinib (IC50 = 310 nM). Ceritinib was able to abrogate the proliferation of PhKh1 cells and blocked the phosphorylation of IGF1R and AKT. (4) Conclusion: IGF1R is as an attractive target for the development of new therapy protocols for HGNET-BCOR patients, which may include ceritinib and vinblastine.

DNA Methylation Readers and Cancer: Mechanistic and Therapeutic Applications.

DNA methylation is a major epigenetic process that regulates chromatin structure which causes transcriptional activation or repression of genes in a context-dependent manner. In general, DNA methylation takes place when methyl groups are added to the appropriate bases on the genome by the action of “writer” molecules known as DNA methyltransferases. How these methylation marks are read and interpreted into different functionalities represents one of the main mechanisms through which the genes are switched “ON” or “OFF” and typically involves different types of “reader” proteins that can recognize and bind to the methylated regions. A tightly balanced regulation exists between the “writers” and “readers” in order to mediate normal cellular functions. However, alterations in normal methylation pattern is a typical hallmark of cancer which alters the way methylation marks are written, read and interpreted in different disease states. This unique characteristic of DNA methylation “readers” has identified them as attractive therapeutic targets. In this review, we describe the current state of knowledge on the different classes of DNA methylation “readers” identified thus far along with their normal biological functions, describe how they are dysregulated in cancer, and discuss the various anti-cancer therapies that are currently being developed and evaluated for targeting these proteins.

PF677 DNA HYPERMETHYLATION EMERGES AS THE STRONGEST PREDICTOR FOR POOR OUTCOME AFTER ALLOGENEIC HEMATOPOIETIC STEM CELL TRANSPLANTATION IN JUVENILE MYELOMONOCYTIC LEUKEMIA (JMML)

Background: JMML is a childhood hematopoietic malignancy characterized by hyperactive RAS signaling. For most patients early allogeneic hematopoietic stem cell transplantation (HSCT) is the therapy of choice. Risk factors for early death and relapse following HSCT are represented by age ≥ 2 yrs, low platelet count and HbF elevated for age. Most recently, genome-wide DNA methylation profiles (Lipka, Nat Comm 2017) identified distinct methylation signatures predictive for outcome. Aims: This study evaluates the clinical significance of these epigenetic changes in a large cohort of uniformly transplanted children registered to the European Working Group of MDS in Childhood (EWOG-MDS). Methods: We analyzed the outcome of 153 children with JMML (96 males, 57 females; median age at HSCT 2.7 yrs [0.3–11.5]) given a HSCT after a preparative regimen consisting of busulfan, cyclophosphamide, and melphalan. Results: Thirty-seven patients (pts) were transplanted from an HLA-identical sibling donor (MSD) and 116 from a matched unrelated donor (UD). Stem cell source was bone marrow (n = 122) or peripheral blood (n = 31). GVHD prophylaxis was CSA only in 25 (68%) MSD procedures, CSA/MTX/ATG was administered in 88 (76%) of UD-HSCT recipients. All but 9 pts engrafted. The cumulative incidence of grades II-IV acute GVHD was 44% (37–52). Thirty-three of the 133 pts at risk developed chronic GVHD, which was limited in 20 and extensive in 13 pts. With a median follow-up of 3.7 years (0.1–17.5), the 5-year leukemia-free survival (LFS) was 61% (53–69), while the cumulative incidence of non-relapse mortality (NRM) and relapse (CIR) were 13% (8–20) and 26% (20–35), respectively. There was no difference in outcome between MSD and UD-HSCT recipients. Of the 153 pts, 76 had a somatic PTPN11 mutation, 21 had neurofibromatosis type 1, 22 belonged to the NRAS- and 18 to the KRAS-mutated subgroup, while RAS pathway alterations were absent in 16 pts (“all negative”). 5-year CIR was higher in PTPN11-mutated JMML (35%) compared to that of the NF1 (24%), NRAS (23%), KRAS (11%) or all negative subtypes (14%). Methylation status was high (HM), intermediate (IM) or low (LM) in 61, 52 or 40 pts, respectively. 5-year LFS and CIR of pts of the LM class was similar to that noted in the IM class with 76% vs 69%, and 8% vs 13%, respectively. In contrast, children of the HM class had a significantly inferior LFS (44%, 31–57, p < 0.01) due to a high CIR (50%, 38–65, p < 0.01). NRM in the 3 methylation groups (LM 16%, IM 19%, HM 6%) did not differ. There was a clear correlation between methylation class and molecular genetic subtype: PTPN11-mutated JMML was less common in the LM class and the proportion of KRAS-mutated pts was highest in the LM class. Also, patients in the HM class had a higher median age at HSCT (3.8 yrs) than pts in the IM (2.1 yrs) or LM class (1.1 yrs). Multivariate analysis identified methylation class (HM vs IM: RR 5.3 [1.8–15.3], HM vs LM RR 7.6 [1.6 – 37.3]) as the only independent variable predicting relapse when analyzed with age at HSCT, platelet count and molecular genetic type (PTPN11-mutated vs others). Summary/Conclusion: Patient outcome in genome-wide methylation classes nicely recapitulated earlier data applying a DNA methylation score of candidate gene regions (Olk-Batz, Blood 2011). Thus, DNA methylation classifiers are exceptionally consistent allowing prospective assignment of DNA methylation categories for molecularly-driven risk stratification. Future research needs to be directed at better understanding the mechanistic link of epigenetic dysregulation and resistance to treatment.

PS1455 RESPONSE TO UP‐FRONT AZACITIDINE IN JUVENILE MYELOMONOCYTIC LEUKEMIA (JMML): INTERIM ANALYSIS OF THE PROSPECTIVE EUROPEAN MULTICENTER STUDY AZA‐JMML‐001

Background:JMML is a chemotherapy‐resistant neoplasia of early childhood. Allogeneic hematopoietic stem cell transplantation (allo‐HSCT) is the only curative therapy, being able to cure approximately 50% of these children. Relapse is the major cause of treatment failure, with chemotherapy prior to HSCT being notably unsuccessful. Novel therapies controlling JMML prior to HSCT are urgently needed.Aims:We conducted a phase 2, multicenter, open‐label study to evaluate pharmacodynamics, safety, and antileukemia activity of azacitidine monotherapy prior to HSCT in patients with newly diagnosed JMML.Methods:Azacitidine was administered at 75 mg/m2/day intravenously on Days 1–7 of a 28‐day cycle for 3 to 6 cycles. The primary endpoint was the number of patients achieving clinical complete remission or clinical partial remission (cPR) at Cycle 3 Day 28 (C3D28); secondary endpoints included overall survival following HSCT.Results:Between September 2015 and November 2017, 18 JMML patients (13 PTPN11‐, 3 NRAS‐, 1 KRAS‐, 1 NF1‐mutated), aged 0.2–7.0 years, were enrolled in the study. Median (range) white blood cell (WBC) count, platelet count, and spleen size were: 19.7 (4.3–59.0) × 109/L, 28 (7–85) × 109/L, and 4 (2–14) cm below the costal margin, respectively. DNA methylation class (Lipka et al. Nat Comm. 2017;8:2126; n = 18) was high, intermediate, or low in 11, 5, and 2 patients, respectively. Sixteen patients completed 3 cycles of therapy and 5 of them completed 6 cycles. Two patients discontinued treatment before completing 3 cycles due to disease progression. Six patients (33%) experienced ≥1 grade 3 or 4 manageable adverse event, consistent with the known azacitidine safety profile. Eleven patients (61%) achieved cPR at C3D28 and 7 had progressive disease either at C3D28 or prior. Importantly, 8 of the 15 patients who needed platelet transfusions before or shortly after treatment initiation did not require transfusions at the time of HSCT. Seven of these 8 platelet responders had normalized their platelet count (≥130 × 109/L). Palpable spleen size decreased in 11 responders by a median of 3.5 cm after 3 cycles and ranged from 0 to 2 cm below the costal margin after 6 cycles. Seventeen patients received allo‐HSCT from a human leukocyte antigen‐compatible related or unrelated donor following a busulfan‐ (n = 15) or treosulfan‐based (n = 2) preparative regimen after a median of 57 days (36–112) from last azacitidine dose. Fourteen out of 16 transplanted patients were leukemia‐free at median follow‐up of 15.6 months (0.8–22.5) after HSCT. Two children (both high‐methylation class) given HSCT relapsed after the allograft. Sixteen of the 18 patients were alive at a median follow‐up of 22.2 months (14.2–33.1). One patient who discontinued treatment before Cycle 3 died from disease progression, and 1 non‐responder child died from graft failure.Summary/Conclusion:This study showed azacitidine monotherapy was well tolerated in children with newly diagnosed JMML. Although the long‐term advantage of azacitidine therapy remains to be fully assessed, both decrease in spleen size and significant platelet responses observed demonstrate that the drug was effective in JMML and provided clinical benefit to patients with JMML in this study. This clinical trial has shown that azacitidine therapy prior to HSCT may be considered for patients with JMML.

Upfront azacitidine (AZA) in juvenile myelomonocytic leukemia (JMML): Interim analysis of the prospective AZA-JMML-001 study.

10031 Background: Hematopoietic stem cell transplantation (HSCT) is the only curative therapy for JMML patients (pts). Novel therapies controlling the disorder prior to HSCT are urgently needed. A phase 2, multicenter, open-label study was conducted to evaluate safety and anti-leukemia activity of AZA monotherapy prior to HSCT in pts with newly diagnosed (ND) JMML. Methods: AZA (75 mg/m2 IV) was administered once daily on days 1–7 of each 28-day cycle (C). Primary endpoint was number of pts with clinical complete remission or clinical partial remission (cPR) at C3 day (D) 28 (C3D28). Results: 18 JMML pts (13 PTPN11-, 3 NRAS-, 1 KRAS-, 1 NF1-mutated) were enrolled from 09/2015 to 11/2017. Median (range) white blood cell and platelet (Plt) counts were 19.7 (4.3–59.0) × 109/L and 28 (7–85) × 109/L, respectively. DNA methylation class (MC) was high, intermediate (int), or low in 11, 5, and 2 pts, respectively. 16 pts completed C3 and 5 pts C6. 2 pts discontinued treatment (Tx) pre-C3D28 due to disease progression (PD). 6 pts (33%) had ≥ 1 grade (Gr) 3–4 manageable adverse event (AE) related to AZA. Most common Gr 3–4 AEs related to AZA were neutropenia (2) and anemia (2). 11 pts (61%) were in cPR at C3D28; 7 had PD at C3D28 or prior. All 7 pts of the int/low MC and 4/11 in high MC achieved cPR. 17 pts received HSCT at median of 58 days (37–518) from last AZA dose; 14 were leukemia-free at a median follow-up of 15.7 months (0.1–31.7) after HSCT. 2 pts (high MC) given HSCT relapsed after allograft. 16/18 pts were alive at a median follow-up of 19.8 months (2.6–37.3) from diagnosis. 1 pt discontinuing Tx prior to C3 died from PD; 1 non-responder died from transplant-related causes. Plt response in pts with cPR prompted retrospective comparison of Plt counts at time of HSCT with a historical registry control cohort. Pts with NF1-mutated JMML with higher Plt counts versus other genetic subtypes were excluded. While 7/16 (44%) study pts had Plt counts ≥ 100 × 109/L at HSCT, only 10/58 (17%) historical cohort pts reached this cutoff ( P &lt; 0.01). Conclusions: This study shows that AZA monotherapy was well tolerated in pts with ND JMML. Although the long-term advantage of AZA Tx remains to be fully assessed, responses show it was effective in JMML and provided clinical benefit to pts in this study. Clinical trial information: NCT02447666.

Impact of predictive impact of MGMT promoter methylation in malignant astrocytomas depends on the methylation subgroup.

2013 Background: O6-methylguanine DNA-methyl transferase (MGMT) status is predictive for alkylating chemotherapy in most series, but there are non-benefitting subgroups. Despite multiple attempts, MGMT has not been unambiguously established as a predictive biomarker for patients with malignant gliomas. Further, these tumors are to be better classified according to global methylation profiles. Methods: Long-term efficacy data of the NOA-08 trial (NCT01502241) that compared efficacy and safety of radiotherapy (RT, n= 176) to temozolomide (TMZ, n= 193) in patients &gt; 65 years with anaplastic astrocytoma (AA) or GB as well as genome-wide DNA methylation patterns and copy number variations assessed by methylation arrays in a biomarker subset ( n= 104) and an independent cohort ( n= 380) have been used to assess the interaction between MGMT status and methylation subgroups. Results: In the long-term update of NOA-08 patients with MGMT methylated tumors had longer OS and EFS when treated with TMZ (18.4 [13.9-24.4] months and 8.5 [6.9-13.3] months) versus RT (9.6 [6.4-13.7] months and 4.8 [4.3-6.2] months, HR 0.44 [0.27-0.70], p &lt; 0.001 for OS and 0.46 [0.29-0.73], p = 0.001 for EFS). These data compared favorably with recently published data from patients treated with chemoradiation (Perry et al. NEJM 2017). Importantly, only patients with glioblastomas of the methylation class receptor tyrosine kinase II (RTKII) and mesenchymal but not RTK I demonstrated the predictive impact of MGMT in the NOA and the independent validation cohort. Conclusions: MGMT promoter methylation as a strong but methylation subclass-dependent predictive biomarker for the use of alkylating chemotherapy in malignant gliomas. The data call for embedding of MGMT tests into global methylation analyses for all patients with malignant gliomas potentially treated with alkylating chemotherapy.

Integrated phenotype-genotype approach in diagnosis and classification of common central nervous system tumours.

After nearly a century of histological classification of central nervous system tumours, the 2016 revised WHO classification has incorporated molecular features with clinical and prognostic relevance into brain tumour classification. In this review, we discuss the latest integrated phenotype-genotype approach to the most common intrinsic brain tumours in adults and children. The key genetic mutations and abnormalities, essential to the definition of these tumours, in line with the current WHO classification are described. Practical dilemmas, including 'difficult' tumours, the utility of DNA methylation classifiers and relevant recent advances post-WHO 2016 consensus are also discussed.

J-108 Role of DNA methylation in prediction of human papillomavirus persistence and carcinogenesis

J-108 Role of DNA methylation in prediction of human papillomavirus persistence and carcinogenesis

Genomic analysis demonstrates that histologically-defined astroblastomas are molecularly heterogeneous and that tumors with MN1 rearrangement exhibit the most favorable prognosis

Astroblastoma (AB) is a rare CNS tumor demonstrating abundant astroblastomatous pseudorosettes. Its molecular features have not been comprehensively studied and its status as a tumor entity is controversial. We analyzed a cohort of 27 histologically-defined ABs using DNA methylation profiling, copy number analysis, FISH and site-directed sequencing. Most cases demonstrated mutually exclusive MN1 rearrangements (n = 10) or BRAFV600E mutations (n = 7). Two additional cases harbored RELA rearrangements. Other cases lacked these specific genetic alterations (n = 8). By DNA methylation profiling, tumors with MN1 or RELA rearrangement clustered with high-grade neuroepithelial tumor with MN1 alteration (HGNET-MN1) and RELA-fusion ependymoma, respectively. In contrast, BRAFV600E-mutant tumors grouped with pleomorphic xanthoastrocytoma (PXA). Six additional tumors clustered with either supratentorial pilocytic astrocytoma and ganglioglioma (LGG-PA/GG-ST), normal or reactive cerebrum, or with no defined DNA methylation class. While certain histologic features favored one genetic group over another, no group could be reliably distinguished by histopathology alone. Survival analysis between genetic AB subtypes was limited by sample size, but showed that MN1-rearranged AB tumors were characterized by better overall survival compared to other genetic subtypes, in fact, significantly better than BRAFV600E-mutant tumors (P = 0.013). Our data confirm that histologically-defined ABs are molecularly heterogeneous and do not represent a single entity. They rather encompass several low- to higher-grade glial tumors including neuroepithelial tumors with MN1 rearrangement, PXA-like tumors, RELA ependymomas, and possibly yet uncharacterized lesions. Genetic subtyping of tumors exhibiting AB histology, particularly determination of MN1 and BRAFV600E status, is necessary for important prognostic and possible treatment implications.

231 - TOF-MS based urine DNA methylation classifier: A fast and effective technique for non-invasive diagnosis and monitoring of bladder cancer

231 - TOF-MS based urine DNA methylation classifier: A fast and effective technique for non-invasive diagnosis and monitoring of bladder cancer

Papillary glioneuronal tumor (PGNT) exhibits a characteristic methylation profile and fusions involving PRKCA.

Papillary glioneuronal tumor (PGNT) is a WHO-defined brain tumor entity that poses a major diagnostic challenge. Recently, SLC44A1-PRKCA fusions have been described in PGNT. We subjected 28 brain tumors from different institutions histologically diagnosed as PGNT to molecular and morphological analysis. Array-based methylation analysis revealed that 17/28 tumors exhibited methylation profiles typical for other tumor entities, mostly dysembryoplastic neuroepithelial tumor and hemispheric pilocytic astrocytoma. Conversely, 11/28 tumors exhibited a unique profile, thus constituting a distinct methylation class PGNT. By screening the extended Heidelberg cohort containing over 25,000 CNS tumors, we identified three additional tumors belonging to this methylation cluster but originally histologically diagnosed otherwise. RNA sequencing for the detection of SLC44A1-PRKCA fusions could be performed on 19 of the tumors, 10 of them belonging to the methylation class PGNT. In two additional cases, SLC44A1-PRKCA fusions were confirmed by FISH. We detected fusions involving PRKCA in all cases of this methylation class with material available for analyses: the canonical SLC44A1-PRKCA fusion was observed in 11/12 tumors, while the remaining case exhibited a NOTCH1-PRKCA fusion. Neither of the fusions was found in the tumors belonging to other methylation classes. Our results point towards a high misclassification rate of the morphological diagnosis PGNT and clearly demonstrate the necessity of molecular analyses. PRKCA fusions are highly diagnostic for PGNT, and detection by RNA sequencing enables the identification of rare fusion partners. Methylation analysis recognizes a unique methylation class PGNT irrespective of the nature of the PRKCA fusion.

Identification of potential blood biomarkers for Parkinson\u2019s disease by gene expression and DNA methylation data integration analysis

BackgroundBlood-based gene expression or epigenetic biomarkers of Parkinson’s disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible.MethodsWhole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5′—C—phosphate—G—3′ (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data.ResultsEighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD.ConclusionsGene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.

DNA methylation associates with survival in non-metastatic clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer and is associated with poor prognosis if metastasized. Up to one third of patients with local disease at diagnosis will develop metastasis after nephrectomy, and there is a need for new molecular markers to identify patients with high risk of tumor progression. In the present study, we performed genome-wide promoter DNA methylation analysis at diagnosis to identify DNA methylation profiles associated with risk for progress.MethodDiagnostic tissue samples from 115 ccRCC patients were analysed by Illumina HumanMethylation450K arrays and methylation status of 155,931 promoter associated CpGs were related to genetic aberrations, gene expression and clinicopathological parameters.ResultsThe ccRCC samples separated into two clusters (cluster A/B) based on genome-wide promoter methylation status. The samples in these clusters differed in tumor diameter (p < 0.001), TNM stage (p < 0.001), morphological grade (p < 0.001), and patients outcome (5 year cancer specific survival (pCSS5yr) p < 0.001 and cumulative incidence of progress (pCIP5yr) p < 0.001. An integrated genomic and epigenomic analysis in the ccRCCs, revealed significant correlations between the total number of genetic aberrations and total number of hypermethylated CpGs (R = 0.435, p < 0.001), and predicted mitotic age (R = 0.407, p < 0.001). We identified a promoter methylation classifier (PMC) panel consisting of 172 differently methylated CpGs accompanying progress of disease. Classifying non-metastatic patients using the PMC panel showed that PMC high tumors had a worse prognosis compared with the PMC low tumors (pCIP5yr 38% vs. 8%, p = 0.001), which was confirmed in non-metastatic ccRCCs in the publically available TCGA-KIRC dataset (pCIP5yr 39% vs. 16%, p < 0.001).ConclusionDNA methylation analysis at diagnosis in ccRCC has the potential to improve outcome-prediction in non-metastatic patients at diagnosis.

Epigenetic Classifiers for Precision Diagnosis of Brain Tumors.

DNA methylation profiling has proven to be a powerful analytical tool, which can accurately identify the tissue of origin of a wide range of benign and malignant neoplasms. Using microarray-based profiling and supervised machine learning algorithms, we and other groups have recently unraveled DNA methylation signatures capable of aiding the histomolecular diagnosis of different tumor types. We have explored the methylomes of metastatic brain tumors from patients with lung cancer, breast cancer, and cutaneous melanoma and primary brain neoplasms to build epigenetic classifiers. Our brain metastasis methylation (BrainMETH) classifier has the ability to determine the type of brain tumor, the origin of the metastases, and the clinical-therapeutic subtype for patients with breast cancer brain metastases. To facilitate the translation of these epigenetic classifiers into clinical practice, we selected and validated the most informative genomic regions utilizing quantitative methylation-specific polymerase chain reaction (qMSP). We believe that the refinement, expansion, integration, and clinical validation of BrainMETH and other recently developed epigenetic classifiers will significantly contribute to the development of more comprehensive and accurate systems for the personalized management of patients with brain metastases.

Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis

Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis

Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis

Early diagnosis improves melanoma survival, yet the histopathological diagnosis of cutaneous primary melanoma can be challenging, even for expert dermatopathologists. Analysis of epigenetic alterations, such as DNA methylation, that occur in melanoma can aid in its early diagnosis. Using a genome-wide methylation screening, we assessed CpG methylation in a diverse set of 89 primary invasive melanomas, 73 nevi, and 41 melanocytic proliferations of uncertain malignant potential, classified based on interobserver review by dermatopathologists. Melanomas and nevi were split into training and validation sets. Predictive modeling in the training set using ElasticNet identified a 40-CpG classifier distinguishing 60 melanomas from 48 nevi. High diagnostic accuracy (area under the receiver operator characteristic curve= 0.996, sensitivity= 96.6%, and specificity= 100.0%) was independently confirmed in the validation set (29 melanomas, 25 nevi) and other published sample sets. The 40-CpG melanoma classifier included homeobox transcription factors and genes with roles in stem cell pluripotency or the nervous system. Application of the 40-CpG melanoma classifier to the diagnostically uncertain samples assigned melanoma or nevus status, potentially offering a diagnostic tool to assist dermatopathologists. In summary, the robust, accurate 40-CpG melanoma classifier offers a promising assay for improving primary melanoma diagnosis.

Significance of molecular classification of ependymomas: C11orf95-RELA fusion-negative supratentorial ependymomas are a heterogeneous group of tumors

Extensive molecular analyses of ependymal tumors have revealed that supratentorial and posterior fossa ependymomas have distinct molecular profiles and are likely to be different diseases. The presence of C11orf95-RELA fusion genes in a subset of supratentorial ependymomas (ST-EPN) indicated the existence of molecular subgroups. However, the pathogenesis of RELA fusion-negative ependymomas remains elusive. To investigate the molecular pathogenesis of these tumors and validate the molecular classification of ependymal tumors, we conducted thorough molecular analyses of 113 locally diagnosed ependymal tumors from 107 patients in the Japan Pediatric Molecular Neuro-Oncology Group. All tumors were histopathologically reviewed and 12 tumors were re-classified as non-ependymomas. A combination of RT-PCR, FISH, and RNA sequencing identified RELA fusion in 19 of 29 histologically verified ST-EPN cases, whereas another case was diagnosed as ependymoma RELA fusion-positive via the methylation classifier (68.9%). Among the 9 RELA fusion-negative ST-EPN cases, either the YAP1 fusion, BCOR tandem duplication, EP300-BCORL1 fusion, or FOXO1-STK24 fusion was detected in single cases. Methylation classification did not identify a consistent molecular class within this group. Genome-wide methylation profiling successfully sub-classified posterior fossa ependymoma (PF-EPN) into PF-EPN-A (PFA) and PF-EPN-B (PFB). A multivariate analysis using Cox regression confirmed that PFA was the sole molecular marker which was independently associated with patient survival. A clinically applicable pyrosequencing assay was developed to determine the PFB subgroup with 100% specificity using the methylation status of 3 genes, CRIP1, DRD4 and LBX2. Our results emphasized the significance of molecular classification in the diagnosis of ependymomas. RELA fusion-negative ST-EPN appear to be a heterogeneous group of tumors that do not fall into any of the existing molecular subgroups and are unlikely to form a single category.

DNA Methylation Subgroups in Juvenile Myelomonocytic Leukemia: An International Collaborative Analysis and Development of a Common Diagnostic Platform

Juvenile myelomonocytic leukemia (JMML) is a rare myeloproliferative neoplasm of early childhood characterized by Ras pathway mutations and aberrant DNA methylation. Despite allogeneic hematopoietic stem cell transplantation (HSCT) approx. 30% of patients (pts) succumb to resistant leukemia. Slowly regressing disease in the absence of HSCT is, however, noted in some pts. Mutational patterns and known clinical risk factors are insufficient to fully explain this heterogeneity. Three independent recent studies demonstrated the potential of DNA methylation profiling to identify clinically meaningful risk groups (Lipka et al., Nat Commun 2017; Stieglitz et al., Nat Commun 2017; Murakami et al., Blood 2018).The aim of this work was to establish an international consensus for the classification of JMML based on DNA methylation, to systematically describe the biological and clinical features of the subgroups identified and to develop a molecular classifier that enables the prospective assignment of DNA methylation categories.In a collaborative effort, we re-analyzed three well-annotated Illumina 450k methylation array data sets. In total, data from 292 pts with JMML or Noonan syndrome-associated myeloproliferative disorder (NS/MPD; EWOG-MDS, Europe: 147 pts, Nagoya, Japan: 106 pts, UCSF, USA: 39 pts) were available. Methylation data from 285 pts passed our quality control and were included in the present analysis. Of these, 256 (89.8%) pts had been diagnosed with JMML and 29 (10.2%) with NS/MPD. Mean age at diagnosis was 1.9 yrs. Levels of fetal hemoglobin (HbF) were available in 228/285 pts and elevated for age in 61%. Driver mutations affecting the Ras pathway were identified in 92% of JMML pts (PTPN11: 36%, NF1: 11%, NRAS: 15%, KRAS: 15%, CBL: 14%), and monosomy 7 in 14%. Initial exploratory analysis revealed batch effects that could, at least in part, be explained by the different ethnical backgrounds of the pts but also included a technical component. Therefore, we stringently filtered probes containing SNPs and performed batch correction using an empirical Bayes framework (Combat). CpG dinucleotides (CpGs) showing variable methylation across normal hematopoietic cell types were excluded from the analysis to avoid confounding with differential cell type composition between the samples.Unsupervised consensus clustering using the 5000 most variable CpGs identified three stable methylation clusters in this inter-group patient cohort. According to their DNA methylation levels, the clusters were designated “high methylation” (HM), “intermediate methylation” (IM) and “low methylation” (LM). Overall, 29.5%, 23.5%, and 47.0% of the cohort of JMML and NS/MPD pts were assigned to the HM, IM, and LM clusters, respectively. The methylation clusters showed a highly significant association with specific Ras-pathway mutations and with known clinical risk factors. All NS/MPD pts clustered with the LM subgroup and showed the lowest methylation levels. The HM cluster was enriched for somatic PTPN11 mutations, elevated HbF and older age, while the LM cluster was enriched for NRAS and CBL mutations, normal HbF and age <2yrs. KRAS mutations as well as monosomy 7 were significantly enriched in the IM cluster. Comparison of clusterassignments made in the present study to those from the original publications found only 3.9% (11/285) discordant cases.This encouraged us to establish a low-dimensional DNA methylation classifier for JMML that could be applied in a prospective setting. Therefore, we split the intergroup cohort randomly into a training (N=202) and a validation cohort (N=83) and trained an extreme gradient boosting machine (xgboost). When using as few as 10 CpGs, the resulting model predicted methylation clusters with 94% accuracy in the validation cohort.This inter-group meta-analysis is the single largest dataset of JMML patients to date and demonstrates the robustness of the JMML methylation signature across continents of origin and its power to identify biologically and clinically distinct JMML subgroups. Our ongoing efforts include developing a sequencing-based assay to predict DNA methylation clusters and to validate this assay using an independent cohort of 60 pts from the three participating research groups. This assay would allow for inclusion of DNA methylation as a biomarker into prospective clinical trials to assist in molecularly driven risk-stratification of JMML. DisclosuresNiemeyer:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Prognostic effect of whole chromosomal aberration signatures in standard-risk, non-WNT/non-SHH medulloblastoma: a retrospective, molecular analysis of the HIT-SIOP PNET 4 trial.

SummaryBackgroundMost children with medulloblastoma fall within the standard-risk clinical disease group defined by absence of high-risk features (metastatic disease, large-cell/anaplastic histology, and MYC amplification), which includes 50–60% of patients and has a 5-year event-free survival of 75–85%. Within standard-risk medulloblastoma, patients in the WNT subgroup are established as having a favourable prognosis; however, outcome prediction for the remaining majority of patients is imprecise. We sought to identify novel prognostic biomarkers to enable improved risk-adapted therapies.MethodsThe HIT-SIOP PNET 4 trial recruited 338 patients aged 4–21 years with medulloblastoma between Jan 1, 2001, and Dec 31, 2006, in 120 treatment institutions in seven European countries to investigate hyperfractionated radiotherapy versus standard radiotherapy. In this retrospective analysis, we assessed the remaining tumour samples from patients in the HIT-SIOP PNET 4 trial (n=136). We assessed the clinical behaviour of the molecularly defined WNT and SHH subgroups, and identified novel independent prognostic markers and models for standard-risk patients with non-WNT/non-SHH disease. Because of the scarcity and low quality of available genomic material, we used a mass spectrometry-minimal methylation classifier assay (MS-MIMIC) to assess methylation subgroup and a molecular inversion probe array to detect genome-wide copy number aberrations. Prognostic biomarkers and models identified were validated in an independent, demographically matched cohort (n=70) of medulloblastoma patients with non-WNT/non-SHH standard-risk disease treated with conventional therapies (maximal surgical resection followed by adjuvant craniospinal irradiation [all patients] and chemotherapy [65 of 70 patients], at UK Children's Cancer and Leukaemia Group and European Society for Paediatric Oncology (SIOPE) associated treatment centres between 1990 and 2014. These samples were analysed by Illumina 450k DNA methylation microarray. HIT-SIOP PNET 4 is registered with ClinicalTrials.gov, number NCT01351870.FindingsWe analysed methylation subgroup, genome-wide copy number aberrations, and mutational features in 136 assessable tumour samples from the HIT-SIOP PNET 4 cohort, representing 40% of the 338 patients in the trial cohort. This cohort of 136 samples consisted of 28 (21%) classified as WNT, 17 (13%) as SHH, and 91 (67%) as non-WNT/non-SHH (we considered Group3 and Group4 medulloblastoma together in our analysis because of their similar molecular and clinical features). Favourable outcomes for WNT tumours were confirmed in patients younger than 16 years, and all relapse events in SHH (four [24%] of 17) occurred in patients with TP53 mutation (TP53mut) or chromosome 17p loss. A novel whole chromosomal aberration signature associated with increased ploidy and multiple non-random whole chromosomal aberrations was identified in 38 (42%) of the 91 samples from patients with non-WNT/non-SHH medulloblastoma in the HIT-SIOP PNET 4 cohort. Biomarkers associated with this whole chromosomal aberration signature (at least two of chromosome 7 gain, chromosome 8 loss, and chromosome 11 loss) predicted favourable prognosis. Patients with non-WNT/non-SHH medulloblastoma could be reclassified by these markers as having favourable-risk or high-risk disease. In patients in the HIT-SIOP PNET4 cohort with non-WNT/non-SHH medulloblastoma, with a median follow-up of 6·7 years (IQR 5·8–8·2), 5-year event-free survival was 100% in the favourable-risk group and 68% (95% CI 57·5–82·7; p=0·00014) in the high-risk group. In the validation cohort, with a median follow-up of 5·6 years (IQR 3·1–8·1), 5-year event-free survival was 94·7% (95% CI 85·2–100) in the favourable-risk group and 58·6% (95% CI 45·1–76·1) in the high-risk group (hazard ratio 9·41, 95% CI 1·25–70·57; p=0·029). Our comprehensive molecular investigation identified subgroup-specific risk models which allowed 69 (51%) of 134 accessible patients from the standard-risk medulloblastoma HIT-SIOP PNET 4 cohort to be assigned to a favourable-risk group.InterpretationWe define a whole chromosomal signature that allows the assignment of non-WNT/non-SHH medulloblastoma patients normally classified as standard-risk into favourable-risk and high-risk categories. In addition to patients younger than 16 years with WNT tumours, patients with non-WNT/non-SHH tumours with our defined whole chromosomal aberration signature and patients with SHH-TP53wild-type tumours should be considered for therapy de-escalation in future biomarker-driven, risk-adapted clinical trials. The remaining subgroups of patients with high-risk medulloblastoma might benefit from more intensive therapies.FundingCancer Research UK, Swedish Childhood Cancer Foundation, French Ministry of Health/French National Cancer Institute, and the German Children's Cancer Foundation.

P05.51 Prognostic impact of genetic alterations and methylation class in meningioma

P05.51 Prognostic impact of genetic alterations and methylation class in meningioma