9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genome wide DNA methylation analysis identifies novel molecular subgroups and predicts survival in neuroblastoma

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Neuroblastoma is the most common malignancy in infancy, accounting for 15% of childhood cancer deaths. Outcome for the high-risk disease remains poor. DNA-methylation patterns are significantly altered in all cancer types and can be utilised for disease stratification.

          Methods

          Genome-wide DNA methylation ( n = 223), gene expression ( n = 130), genetic/clinical data ( n = 213), whole-exome sequencing ( n = 130) was derived from the TARGET study. Methylation data were derived from HumanMethylation450 BeadChip arrays. t-SNE was used for the segregation of molecular subgroups. A separate validation cohort of 105 cases was studied.

          Results

          Five distinct neuroblastoma molecular subgroups were identified, based on genome-wide DNA-methylation patterns, with unique features in each, including three subgroups associated with known prognostic features and two novel subgroups. As expected, Cluster-4 (infant diagnosis) had significantly better 5-year progression-free survival (PFS) than the four other clusters. However, in addition, the molecular subgrouping identified multiple patient subsets with highly increased risk, most notably infant patients that do not map to Cluster-4 (PFS 50% vs 80% for Cluster-4 infants, P = 0.005), and allowed identification of subgroup-specific methylation differences that may reflect important biological differences within neuroblastoma.

          Conclusions

          Methylation-based clustering of neuroblastoma reveals novel molecular subgroups, with distinct molecular/clinical characteristics and identifies a subgroup of higher-risk infant patients.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: not found

          Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

          The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. http://bioconductor.org/packages/release/bioc/html/minfi.html. khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary data are available at Bioinformatics online.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            DNA methylation and its basic function.

            In the mammalian genome, DNA methylation is an epigenetic mechanism involving the transfer of a methyl group onto the C5 position of the cytosine to form 5-methylcytosine. DNA methylation regulates gene expression by recruiting proteins involved in gene repression or by inhibiting the binding of transcription factor(s) to DNA. During development, the pattern of DNA methylation in the genome changes as a result of a dynamic process involving both de novo DNA methylation and demethylation. As a consequence, differentiated cells develop a stable and unique DNA methylation pattern that regulates tissue-specific gene transcription. In this chapter, we will review the process of DNA methylation and demethylation in the nervous system. We will describe the DNA (de)methylation machinery and its association with other epigenetic mechanisms such as histone modifications and noncoding RNAs. Intriguingly, postmitotic neurons still express DNA methyltransferases and components involved in DNA demethylation. Moreover, neuronal activity can modulate their pattern of DNA methylation in response to physiological and environmental stimuli. The precise regulation of DNA methylation is essential for normal cognitive function. Indeed, when DNA methylation is altered as a result of developmental mutations or environmental risk factors, such as drug exposure and neural injury, mental impairment is a common side effect. The investigation into DNA methylation continues to show a rich and complex picture about epigenetic gene regulation in the central nervous system and provides possible therapeutic targets for the treatment of neuropsychiatric disorders.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found

              DNA methylation-based classification of central nervous system tumours

              Summary Accurate pathological diagnosis is crucial for optimal management of cancer patients. For the ~100 known central nervous system (CNS) tumour entities, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumour types. We herein present the development of a comprehensive approach for DNA methylation-based CNS tumour classification across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that availability of this method may have substantial impact on diagnostic precision compared with standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility we have designed a free online classifier tool (www.molecularneuropathology.org) requiring no additional onsite data processing. Our results provide a blueprint for the generation of machine learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
                Bookmark

                Author and article information

                Contributors
                Gordon.Strathdee@ncl.ac.uk
                Journal
                Br J Cancer
                Br J Cancer
                British Journal of Cancer
                Nature Publishing Group UK (London )
                0007-0920
                1532-1827
                29 September 2022
                29 September 2022
                23 November 2022
                : 127
                : 11
                : 2006-2015
                Affiliations
                [1 ]GRID grid.1006.7, ISNI 0000 0001 0462 7212, Biosciences Institute, Newcastle University Centre for Cancer, , Newcastle University, ; Newcastle, UK
                [2 ]GRID grid.239552.a, ISNI 0000 0001 0680 8770, Division of Oncology and Center for Childhood Cancer Research, , Children’s Hospital of Philadelphia, ; Philadelphia, PA USA
                [3 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Children’s Hospital Los Angeles, The Saban Research Institute and Keck School of Medicine, , University of Southern California, ; Los Angeles, CA USA
                [4 ]GRID grid.510964.f, Hopp Children’s Cancer Center Heidelberg (KiTZ), ; Heidelberg, Germany
                [5 ]GRID grid.7497.d, ISNI 0000 0004 0492 0584, Division of Neuroblastoma Genomics, , German Cancer Research Center (DKFZ), ; Heidelberg, Germany
                [6 ]GRID grid.1006.7, ISNI 0000 0001 0462 7212, Translational and Clinical Research Institute, Newcastle University Centre for Cancer, , Newcastle University, ; Newcastle, UK
                [7 ]GRID grid.42629.3b, ISNI 0000000121965555, Department of Applied Sciences, , Northumbria University, ; Newcastle, UK
                Author information
                http://orcid.org/0000-0002-8088-7929
                http://orcid.org/0000-0001-9681-8429
                Article
                1988
                10.1038/s41416-022-01988-z
                9681858
                36175618
                7db136e6-b091-4253-b4fe-cbb2f8078dff
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 September 2021
                : 22 August 2022
                : 8 September 2022
                Funding
                Funded by: National Institute of Health
                Funded by: National Institute of Health and Funding by the EU
                Funded by: Kidscan Children's Cancer Research
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2022

                Oncology & Radiotherapy
                paediatric cancer,cancer epigenetics
                Oncology & Radiotherapy
                paediatric cancer, cancer epigenetics

                Comments

                Comment on this article