Review ArticleCopy number assessment in the genomic analysis of CNS neoplasia: An evidence-based review from the cancer genomics consortium (CGC) working group on primary CNS tumors
Introduction
Primary central nervous system (CNS) tumors are a heterogeneous group of neoplasms comprising more than 100 histologically distinct types. They can arise in both adults and children from a variety of cell types, including glial cells, neurons and those derived from the meninges [91]. It has become increasingly clear that appropriate clinical management of these tumors relies heavily on an integration of both histologic criteria and genomic data. Indeed, the 2016 WHO Classification of Tumors of the Central Nervous System incorporated genomic data into diagnostic algorithms [64]. Identification of acquired copy number aberrations (CNA) provides information about critical diagnostic, prognostic, and therapeutic biomarkers ([104] and [97,105]). The correlation of CNA and gene mutation profiles with histological features permits more accurate diagnoses and prognoses and supports the creation of personalized treatment plans.
There are striking differences between pediatric and adult brain tumors, including disease incidence, most common tumor types and location, genomic alterations, treatment strategies, and prognosis. The incidence of CNS tumors in children and adolescents ≤19 years old is 5.9 per 100,000 versus 29.9 per 100,000 in adults [20]. Pediatric brain tumors are more likely to be located in the infratentorial parts of the brain (often affecting movement and coordination), while adult brain tumors are more likely to develop in the supratentorial areas of the brain (affecting memory, language, and thought). Embryonal tumors, especially medulloblastomas, and low-grade gliomas are the most common brain tumors in children, while the most common adult brain tumors are meningioma and glioblastoma (GBM). It is not surprising, then, that the genomic profiles of childhood brain tumors may not always align with the adult tumor subgroupings and often represent biologically distinct neoplasms [64]. For example, pediatric diffuse gliomas may display an H3F3A K27M mutation distinct from many histologically similar adult counterparts. This genomic difference and the tumor's midline location warrant the establishment of a new entry specifically for this typically pediatric brain tumor - diffuse midline glioma, H3 K27M-mutant – and provide a justification for targeted therapy. Prognostically, pediatric patients often carry better prognoses than do their adult counterparts. More than 75% of children diagnosed at 18 months or younger survive at least five years, with over two-thirds of them having more durable remissions. In contrast, the five-year survival rate for adult CNS tumors is approximately 35% ([2], [81]). Finally, treatment for childhood brain tumors usually differs from treatment for adult tumors. Recent studies have shown good long-term pediatric outcomes with only surgery and therapy with targeted agents. This can help avoid or reduce doses of radiation therapy in these young patients to minimize long-term cognitive, endocrinological, and psychological damage [11].
Since the 1990s, genomic CNA have been detected using conventional cytogenetic analysis (i.e., karyotyping) and fluorescence in situ hybridization (FISH). However, the clinical utility of these technologies has been limited by their relatively low resolution, the requirement for karyotype analysis of viable and dividing cells, and the fact that FISH provides only a targeted interrogation of the genome. In contrast, chromosomal microarray analysis (CMA) is a high-resolution and sensitive approach to genome-wide evaluation of copy number and can be deployed with either fresh or formalin fixed-paraffin embedded (FFPE) tissues. Given the importance of identifying acquired CNA in the clinical management of patients with primary brain tumors, many diagnostic genetic laboratories in the United States have adopted CMA as a first-tier test [104]. In this article, we summarize the current knowledge of common CNA associated with primary CNS tumors and their clinical impact on diagnosis, prognosis, and therapeutic management. We also propose best practices for the analysis, interpretation and reporting of CNAs detected in the analysis of CNS tumors, using the most common of these entities as examples.
Section snippets
Background
The acquisition of genomic data has been gaining importance in terms of understanding, diagnosing, and treating central nervous system (CNS) neoplasia, particularly over the last decade. Most recently, this impact has been codified in the 2016 update to the 7th edition of the World Health Organization (WHO) guidelines for the diagnosis of CNS neoplasia [64]. In this update, the WHO included genomic data as part of the definition of several diagnostic entities and highlights the necessity of
Platform selection
Many different CMA platforms are in clinical use, including array-based comparative genomic hybridization (aCGH) and a variety of single nucleotide polymorphism (SNP) arrays. The advantages of many aCGH platforms include longer probe lengths (60 to 65-mers), relatively high signal to noise ratios, and the option to customize probe coverage over selected areas of the genome; of note, some aCGH platforms are also designed for SNP detection. In contrast, most SNP probes are shorter (25-mers) but
Overview of pathological and genomic features of CNS tumors
Below, we give brief synopses of a selection of the most common primary CNS lesions analyzed genomically, with a focus on relevant copy number aberrations further explored in the accompanying tables. Salient clinical and pathological data are summarized with a particular focus on entities that may prove difficult to distinguish by traditional histologic analysis; these data are provided with an eye toward informing cytogeneticists and molecular pathologists of known histopathologic limitations
Infiltrating gliomas
Infiltrating gliomas – those with the capacity to invade the brain parenchyma as single cells and frustrate clinical efforts at local control – display somewhat different behaviors and genomic backgrounds in adult and pediatric patients [3]. Infiltrating gliomas in adults are principally defined by the presence or absence of isocitrate dehydrogenase 1 or 2 (IDH1/2) mutations [3,64,91]. This particular criterion has been accepted as a means of tumor classification; the WHO naming convention for
H3 K27M mutant tumors
These infiltrative gliomas with a K27M mutation in H3F3A or HIS1H3B/C are primarily of astrocytic lineage and typically arise along midline structures [64]. 20% show recurrent activating mutations in ACVR1 [16], [118]. They are observed more frequently in children than in adults and are marked by aggressive clinical behavior. Histologically they are a diverse group, with 10% meeting criteria for WHO Grade II tumors and the remainder classified by light microscopy as higher grade. As such, the
Low grade gliomas
Low grade gliomas (LGG), are also described as low grade neuroepithelial tumors to highlight the presence of both glial and neuronal differentiation. LGG comprise a category of tumors that are usually well-circumscribed, show little infiltration of the surrounding brain, display generally indolent behavior, and may be amenable to cure by surgical resection. Most are WHO grade I, though some can be higher grade. Many of these lesions are more commonly seen in children, though they also occur in
Meningiomas
Meningiomas are common primary CNS tumors that typically present as well-demarcated masses arising from the dura mater. They are graded by histologic features, according to WHO criteria, from grades I to III. WHO grade I meningiomas may be referred to as benign meningiomas as they carry lower risks of recurrence and progression compared with that of higher-grade counterparts. Copy number evaluations of these lower grade tumors show two common profiles, including monosomy 22 as a sole aberration
Ependymomas
Ependymomas are a group of glial tumors affecting both adults and children that vary widely in terms of aggressiveness, which in turn may correlate more with clinicopathologic and genomic features than with histologic findings. While ependymomas most often arise in the supratentorial region or the posterior fossa, they can also develop in the spinal cord. Regardless of location, reliance on histology alone for prognoses has been imperfect for tumor classification. The addition of cytogenetic
Embryonal tumors
Previously termed primitive neuroectodermal tumors (PNET), embryonal neoplasms comprise a group of tumors seen primarily in the pediatric age group that are histologically characterized by a poorly differentiated or undifferentiated appearance. Embryonal neoplasms are overall aggressive tumors and are designated as WHO grade IV, though some do respond well to treatment. Classically, these tumors were named based upon the location where they arose. Modern genomic investigation has provided even
Choroid plexus papillomas
Choroid plexus papillomas (CPP, WHO grade I) and atypical choroid plexus papillomas (aCPP, WHO grade II) are histologically and genetically similar tumors distinguished primarily by the degree of mitotic activity found on histologic examination, with aCPP displaying more frequent mitoses than CPP. These tumors arise intraventricularly near choroid plexus tissue, and share a morphologic resemblance to non-neoplastic choroid plexus [64]. In terms of copy number aberrations, CPP and aCPP tend to
Conclusion
Our understanding of the biology and diagnosis of primary CNS tumors has grown exponentially in the last decade, and this is appropriately reflected in the 2016 WHO, which correctly incorporates genomic data into the diagnostic algorithm. DNA copy number data comprises a portion of the genomic information incorporated into the 2016 WHO guidelines as well as other ongoing efforts to improve classification; many of the relevant CNAs can be detected by CMA analysis. Along these lines, CMA is most
Acknowledgments
The authors state that they have no conflicts of interest to disclose. We would like to thank the Board of Directors and membership of the Cancer Genomics Consortium for their assistance in the review and completion of this manuscript.
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From Banding to BAM Files: Genomics Informs Diagnosis and Precision Medicine for Brain Tumors
2020, Surgical Pathology ClinicsCitation Excerpt :Technological improvements in both the probe density and the array design of CMAs have resulted in marked changes. With increased density, CMAs can now readily detect alterations often as small as ∼50 kb, and optimized design facilitates use of DNA extracted from FFPE material.20 CMA does not have the ability to identify evidence of balanced rearrangements20; however, intragenic copy-number alterations may be suggestive of unbalanced rearrangements.