scholarly journals EPCT-06. PRECISION ONCOLOGY IN THE PEDIATRIC TARGETED THERAPY 2.0 PROGRAM

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i47-i48
Author(s):  
Jonas Ecker ◽  
Florian Selt ◽  
Andrey Korshunov ◽  
David Capper ◽  
Nicola Dikow ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Sanger Sequencing ◽  
Methylation Array ◽  
Dna Methylation Array ◽  
The Impact ◽  
Gene Panel Sequencing ◽  
Panel Sequencing

Abstract Introduction Precise diagnoses and robust detection of actionable alterations is required for individualized treatments. By using extended molecular diagnostics, the Pediatric Targeted Therapy (PTT) 2.0 program aims at the improvement of diagnostic accuracy and detection of actionable alterations for pediatric high-risk patients. The impact of these analyses on clinical management is reported. Methods Pediatric patients with relapsed or progressive tumors after standard of care treatment were included, independent of histological diagnosis. Formalin fixed paraffin embedded material and a blood sample for germline correction were requested. DNA methylation array, targeted gene panel sequencing (130 genes), RNA and Sanger sequencing in selected cases, and immunohistochemistry (IHC) of selected markers (pERK, pAKT, pS6, PD-L1) were performed. A questionnaire-based follow-up was used to determine the clinical impact of the analysis. Results We enrolled n=263 patients from February 2017 to February 2019. Complete molecular analysis was possible for n=260 cases (99%). The most common entities were brain tumors (n=172/260, 65%). In brain tumors, DNA methylation array alone allowed robust diagnostic classification (score of >=0.9) in n=104/172 cases (60%). Actionable targets as detected by copy number calculation, gene panel sequencing, RNA sequencing and IHC were found in n=94/172 (55%) brain tumor cases. The most common actionable targets in brain tumors were MAPK (pERK, BRAF fusions, BRAF V600E), mTOR (pS6), PI3K (pAKT), CDK4/6 (CDKN2A/B loss), and immune checkpoints (PD-L1). Pathogenic germline alterations with clinical relevance were identified in n=12/172 brain tumor cases (6.9%) and were confirmed by Sanger sequencing, 5/12 (41%) of which were previously unknown. Clinical follow-up of subsequent treatment and outcome are ongoing. Conclusion The combination of next-generation diagnostics such as methylation arrays and targeted sequencing in addition to selected IHC markers added robust information with regard to diagnosis and actionable alterations. The impact on clinical decision-making and on outcome is currently being evaluated.

scholarly journals Intraoperative DNA methylation classification of brain tumors impacts neurosurgical strategy

2021 ◽  
Author(s):  
Luna Djirackor ◽  
Skarphedinn Halldorsson ◽  
Pitt Niehusmann ◽  
Henning Leske ◽  
David Capper ◽  
...  
Keyword(s):  
Machine Learning ◽  
Dna Methylation ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Frozen Section ◽  
Machine Learning Algorithms ◽  
Nanopore Sequencing ◽  
Low Coverage ◽  
The Impact

Abstract Background Brain tumor surgery must balance the benefit of maximal resection against the risk of inflicting severe damage. The impact of increased resection is diagnosis specific. However, the precise diagnosis is typically uncertain at surgery due to limitations of imaging and intraoperative histomorphological methods. Novel and accurate strategies for brain tumor classification are necessary to support personalized intraoperative neurosurgical treatment decisions. Here, we describe a fast and cost-efficient workflow for intraoperative classification of brain tumors based on DNA methylation profiles generated by low coverage nanopore sequencing and machine learning algorithms. Methods We evaluated six independent cohorts containing 105 patients, including 50 pediatric and 55 adult patients. Ultra-low coverage whole genome sequencing was performed on nanopore flow cells. Data was analyzed using copy number variation and ad hoc random forest classifier for the genome-wide methylation-based classification of the tumor. Results Concordant classification was obtained between nanopore DNA methylation analysis and a full neuropathological evaluation in 93 of 105 (89%) cases. The analysis demonstrated correct diagnosis in 6/6 cases where frozen section evaluation was inconclusive. Results could be returned to the operating room at a median of 97 minutes (range 91-161 minutes). Precise classification of the tumor entity and subtype would have supported modification of the surgical strategy in 12 out of 20 patients evaluated intraoperatively. Conclusion Intraoperative nanopore sequencing combined with machine learning diagnostics was robust, sensitive, and rapid. This strategy allowed DNA methylation-based classification of the tumor to be returned to the surgeon within a timeframe that supports intraoperative decision-making.

scholarly journals NEXT-GENERATION NEUROPATHOLOGY - IMPROVING DIAGNOSTIC ACCURACY FOR BRAIN TUMORS USING DNA METHYLATION ARRAY-BASED MOLECULAR PROFILING

2014 ◽  
Vol 16 (suppl 3) ◽  
pp. iii4-iii4 ◽  
Author(s):  
D. T. W. Jones ◽  
D. Capper ◽  
M. Sill ◽  
V. Hovestadt ◽  
P. Lichter ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Brain Tumors ◽  
Diagnostic Accuracy ◽  
Molecular Profiling ◽  
Next Generation ◽  
Methylation Array ◽  
Dna Methylation Array

scholarly journals PATH-11. PROSPECTIVE (EPI-)GENETIC CLASSIFICATION OF > 1,000 PEDIATRIC CNS TUMORS—THE MNP 2.0 STUDY

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii426-iii426
Author(s):  
Dominik Sturm ◽  
Felix Sahm ◽  
Felipe Andreiuolo ◽  
David Capper ◽  
Marco Gessi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Gene Panel ◽  
Cns Tumors ◽  
Lower Grade ◽  
High Grade ◽  
Sequencing Data ◽  
Cns Tumor ◽  
Gene Panel Sequencing ◽  
Tumor Entities ◽  
Panel Sequencing

Abstract The large variety of CNS tumor entities affecting children and adolescents, some of which are exceedingly rare, results in very diverging patient outcomes and renders accurate diagnosis challenging. To assess the diagnostic utility of routine DNA methylation-based CNS tumor classification and gene panel sequencing, the Molecular Neuropathology 2.0 study prospectively integrated these (epi-)genetic analyses with reference neuropathological diagnostics as an international trial for newly-diagnosed pediatric patients. In a four-year period, 1,215 patients with sufficient tissue were enrolled from 65 centers, receiving a reference neuropathological diagnosis according to the WHO classification in >97%. Using 10 FFPE sections as input, DNA methylation analysis was successfully performed in 95% of cases, of which 78% with sufficient tumor cell content were assigned to a distinct epigenetic tumor class. The remaining 22% did not match any of 82 represented classes, indicating novel rare tumor entities. Targeted gene panel sequencing of >130 genes performed for 96% of patients with matched blood samples detected diagnostically, prognostically, or therapeutically relevant somatic alterations in 48%. Germline DNA sequencing data indicated potential predisposition syndromes in ~10% of patients. Discrepant results by neuropathological and epigenetic classification (29%) were enriched in histological high-grade gliomas and implicated clinical relevance in 5% of all cases. Clinical follow-up suggests improved survival for some patients with high-grade glioma histology and lower-grade molecular profiles. Routine (epi-)genetic profiling at the time of primary diagnosis adds a valuable layer of information to neuropathological diagnostics and will improve clinical management of CNS tumors.

scholarly journals EWAS Data Hub: a resource of DNA methylation array data and metadata

2019 ◽  
Vol 48 (D1) ◽  
pp. D890-D895 ◽  
Author(s):  
Zhuang Xiong ◽  
Mengwei Li ◽  
Fei Yang ◽  
Yingke Ma ◽  
Jian Sang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Cell Types ◽  
Great Promise ◽  
Methylation Array ◽  
Array Data ◽  
The Past ◽  
Comprehensive Collection ◽  
Dna Methylation Array ◽  
Brain Parts

Abstract Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

scholarly journals Epigenetic Profiling for the Molecular Classification of Metastatic Brain Tumors

2018 ◽  
Author(s):  
Javier I. J. Orozco ◽  
Theo A. Knijnenburg ◽  
Ayla O. Manughian-Peter ◽  
Matthew P. Salomon ◽  
Garni Barkhoudarian ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Metastases ◽  
Metastatic Tumor ◽  
Molecular Classification ◽  
Supervised Machine Learning ◽  
Lung Cancers ◽  
Specific Pcr ◽  
Histopathologic Evaluation

AbstractOptimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet these challenges, we generated genome-scale DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n=96). Using supervised machine learning and integration of multiple DNA methylomes from normal, primary, and metastatic tumor specimens (n=1,860), we unraveled epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically-relevant subtypes. BrainMETH predictions were supported by routine histopathologic evaluation. We further characterized and validated the most predictive genomic regions in a large cohort of brain tumors (n=165) using quantitative methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

scholarly journals Postoperative Hypoalbuminemia: Prevalence, Risk Factors, Association with Postoperative Pneumonia in Brain Tumors Patients Undergoing Craniotomy

2021 ◽  
Author(s):  
Da-wei Zhao ◽  
Xu-yang Zhang ◽  
Kai-yan Wei ◽  
Yi-bin Jiang ◽  
Dan Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Operation Time ◽  
Postoperative Pneumonia ◽  
Tumor Surgery ◽  
Regression Analyses ◽  
Brain Tumor Surgery ◽  
The Impact ◽  
Preoperative Albumin

Abstract Hypoalbuminemia is associatied with poor outcome in patients undergoing surgery intervention. The main aim for this study was to investigate the incidence and the risk factors of postoperative hypoalbuminemia and assessed the impact of postoperative hypoalbuminemia on complications in patients undergoing brain tumor surgery. This retrospective study included 372 consecutive patients who underwent brain tumors surgery from January 2017 to December 2019. The patients were divided into hypoalbuminemia (< 35 g/L) and non-hypoalbuminemia group (≥ 35 g/L) based on postoperative albumin levels. Logistic regression analyses were used to determine risk factors. Of the total 372 patients, 333 (89.5%) developed hypoalbuminemia after surgery. Hypoalbuminemia was associated with operation time (OR 1.011, P < 0.001), preoperative albumin (OR 0.864, P = 0.015) and peroperative globulin (OR 1.192, P = 0.004). Postoperative pneumonia had a higher incidence in patients with than without hypoalbuminemia (41.1% vs 23.1%, P = 0.029). The independent predictors of postoperative pneumonia were age (OR 1.053, P < 0.001), operation time (OR 1.003, P = 0.013) and lower postoperative albumin (OR 0.946, P = 0.018). Postoperative hypoalbuminemia has a higher incidence with the increase of operation time, and is associated with postoperative pneumonia in patients undergoing brain tumor surgery.

scholarly journals MBRS-14. INTEGRATING CLINICAL AND GENOMIC CHARACTERISTICS IN PEDIATRIC MEDULLOBLASTOMA SUBTYPES IN A SINGLE COHORT IN TAIWAN

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii400-iii401
Author(s):  
Kuo-Sheng Wu ◽  
Tai-Tong Wong
Keyword(s):  
Dna Methylation ◽  
Cluster Analysis ◽  
Treatment Strategies ◽  
Clinical Results ◽  
Tumor Location ◽  
Molecular Subgroups ◽  
Methylation Array ◽  
Metastatic Rate ◽  
Pediatric Medulloblastoma ◽  
Dna Methylation Array

Abstract BACKGROUND Medulloblastoma (MB) was classified to 4 molecular subgroups: WNT, SHH, group 3 (G3), and group 4 (G4) with the demographic and clinical differences. In 2017, The heterogeneity within MB was proposed, and 12 subtypes with distinct molecular and clinical characteristics. PATIENTS AND METHODS: PATIENTS AND METHODS We retrieved 52 MBs in children to perform RNA-Seq and DNA methylation array. Subtype cluster analysis performed by similarity network fusion (SNF) method. With clinical results and molecular profiles, the characteristics including age, gender, histological variants, tumor location, metastasis status, survival, cytogenetic and genetic aberrations among MB subtypes were identified. RESULTS In this cohort series, 52 childhood MBs were classified into 11 subtypes by SNF cluster analysis. WNT tumors shown no metastasis and 100% survival rate. All WNT tumors located on midline in 4th ventricle. Monosomy 6 presented in WNT α, but not in β subtype. SHH α and β occurred in children, while SHH γ in infant. Among SHH tumors, α subtype showed the worst outcome. G3 γ showed the highest metastatic rate and worst survival associated with MYC amplification. G4 α has the highest metastatic rate, however G4 γ showed the worst survival. CONCLUSION We identified molecular subgroups and subtypes of MBs based on gene expression and DNA methylation profile in children in our cohort series. The results may contribute to the establishment of nation-wide correlated optimal diagnosis and treatment strategies for MBs in infant and children.

Access to radiation oncology centers with brain tumor treatment expertise for patients with resectable brain tumors.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18509-e18509
Author(s):  
Mehee Choi ◽  
Brian P. Martin ◽  
Lisa Misell ◽  
Joseph M. Zabramski ◽  
David G. Brachman
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Access To Care ◽  
Radiation Treatment ◽  
Fold Increase ◽  
Tumor Treatment ◽  
Brain Radiotherapy ◽  
The Us ◽  
Brain Radiation

e18509 Background: Many patients with brain tumors face challenges with access to care. For rural patients, prolonged travel times may limit access to appropriate radiotherapy. Radiation centers (RCs) offering specialized brain radiotherapy, e.g., stereotactic radiosurgery (SRS), are geographically limited. Utilization of brain brachytherapy at the time of resection offers an option for such patients, but technical challenges have limited the adoption. To address the limitations of traditional brachytherapy, a device with Cs-131 seeds embedded in a bioresorbable collagen tile (GammaTile, GT Medical Technologies, Tempe, AZ USA) was developed. GammaTile (GT) is FDA-cleared for permanent implantation at the time of resection for all recurrent intracranial tumors and for newly diagnosed malignant intracranial neoplasms. To investigate if wider availability of this treatment could possibly lower the geographic barrier to access to care, we mapped the US population against existing RCs with brain tumor expertise and neurosurgery centers (NSCs) performing craniotomies. Methods: We analyzed 2018 CMS claims data using CPT codes for single- and multi-fraction SRS to identify RCs with brain tumor treatment expertise and mapped these against the population. Using similar methodology, using CPT codes for craniotomies, we identified NSCs, as any facility performing craniotomies is potentially eligible to implant GT. Results: 135 RCs used CPT codes for SRS. 193-, 119-, 82-, and 52-million Americans lived >30-, >60-, >90-, and >120-minutes from one of these centers, respectively. 530 NSCs preform craniotomies, including ≥1 in every state, a 4-fold increase over the number of RCs offering SRS. Conclusions: For many patients, substantial travel distances limit their access to RCs with brain tumor treatment expertise. In contrast, the 530 craniotomy-performing NSCs have far greater geographic dispersion. The option of undergoing brain radiation with GT implantation at the time of brain tumor craniotomy brings treatment closer to millions, ensures compliance, and reduces additional travel for follow-up radiation treatment.[Table: see text]

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