• Users Online: 253
  • Print this page
  • Email this page


 
 
Table of Contents
EDITORIAL
Year : 2020  |  Volume : 3  |  Issue : 3  |  Page : 83-89

To do genomics or not do? This is the question


1 Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
2 Department of Pathology, Hong Kong Children's Hospital, Hong Kong Special Administrative Region, China
3 Department of Pediatric Oncology, Hong Kong Children's Hospital, Hong Kong Special Administrative Region, China
4 Department of Neurosurgery, Division of Neurosurgery, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China

Date of Submission07-Aug-2020
Date of Decision22-Aug-2020
Date of Acceptance28-Aug-2020
Date of Web Publication17-Oct-2020

Correspondence Address:
Prof. Ho-Keung Ng
Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
China
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/glioma.glioma_22_20

Rights and Permissions

How to cite this article:
Ng HK, Chan AK, Kan NC, Ku DT, Chan DT, Li KK. To do genomics or not do? This is the question. Glioma 2020;3:83-9

How to cite this URL:
Ng HK, Chan AK, Kan NC, Ku DT, Chan DT, Li KK. To do genomics or not do? This is the question. Glioma [serial online] 2020 [cited 2022 Nov 28];3:83-9. Available from: http://www.jglioma.com/text.asp?2020/3/3/83/298394


  Surely, More (Genomics) Must Be Better, or Is It? Top


This article is more of an opinion piece of how to best make use of single-gene and genomics in the molecular diagnosis of brain tumors. It is not a comprehensive review of the entire field, and hence the topics discussed are selective, and references are not meant to be complete.

Major advances in the understandings of the molecular pathogenesis of brain tumors have now rendered molecular diagnostics a necessary component of their pathologic diagnoses.[1] A new World Health Organization (WHO) classification of nervous system tumors will soon go public as this article goes to press, is likely to further deepen the need for molecular diagnostics in neuro-oncology, as the WHO experts built on the principles established in 2016.[2] However, currently, there is such an array of molecular tests and range of biomarkers that both pathologists and clinicians are left wondering what needs to be ticked on a menu of biomarkers, especially when presented to them by commercial companies. This is especially the case in some countries where molecular diagnostics for cancers, as promoted by the companies, are commonly done. There is a natural tendency, as per the habit of physicians investigating patients that if in doubt for tests, just tick all. The “all” surely must be genomics or next-generation sequencing (NGS). To the patients and lay public, surely, “more” tests must be better than “fewer” and therefore, genomics must be superior to single-gene studies.

In brain tumor molecular diagnostics, single-gene tests not only include, for example, IDH sequencing, BRAF V600E sequencing, 1p19q codeletion, H3 sequencing, BRAF fluorescent in situ hybridization (FISH), and should also include the so-called molecular immunohistochemistry (IHC) such as immunostaining for IDH1, BRAF, and H3K27M, which is usually fairly reliable and reflective of underlying mutations. IHC tests expression of single genes, and so is really a single gene test, although low cost. [Table 1] lists some of the available IHC tests relatively unique to diagnoses of the central nervous system (CNS) tumors. These antibodies are different from the antibodies pathologists conventionally used, for example, NeuN, cytokeratin, which most of the time does not have relevance to molecular grouping or stratification and clinicians, in general, cannot decode from a pathology report. In contrast, most well-informed clinicians understand the importance of IDH1 immunostaining or the importance of p53 staining in an SHH medulloblastoma. NGS includes whole-genome sequencing, whole-exome sequencing, RNAseq, target sequencing, or integrated genomics that can look at both mutation and fusions.[3] Other genomic methods look at single-nucleotide changes in the form of various arrays, which can also detect copy number changes. The two genomic platforms commonly used in routine clinical settings are Illumina and ion torrent (thermo fisher). The Illumina platform is based on sequencing by the synthesis of the complementary strand and incorporation of fluorescent and terminated nucleotides.[4] The Ion Torrent is also based on sequencing by synthesis, but the detection is based on the release of hydrogen ions during sequencing.[5] Methylation profiling using the Illumina platform is now a very important genomic method looking at the overall epigenetic pattern of CNS tumors by which a diagnosis can be given from the clustering.[6] More on methylation profiling below. Nanostring is a widely used nonpolymerase chain reaction (PCR) technique.[7] It uses sequence-specific probes to digitally measure transcripts of target genes and fusion genes.
Table 1: Molecular of immunohistochemical markers and their indications in brain tumors

Click here to view


All the genomic methods have been extensively utilized in research, for clustering of tumors by bioinformatics hierarchies and searching for new biomarkers critical in driving certain tumor groups. Aside from diagnosis, genomic tests also allow screening of potential targets for available drugs. The latter is very important for patients who are already failing first and second line treatments. However, there is also a financial side to genomic tests and in many countries, the cost for molecular diagnostics will be borne by the patients, especially those with a nationalized health system where the availability and the type of molecular tissue diagnostics are controlled by the government like where the authors work.

Some clinicians have a rather simplistic view that once you send the pathologists the tissues, they should have a reasonable histological diagnosis (the low end of things) in a week or so and then everything else, especially for finding drug targets, can be sent off for NGS for the high end of things. Every information needed for diagnosis and further treatment should then be with the results coming back in a month's time. This view is particularly prevalent in countries where tests merit a higher cost than pathologists' opinions.

The reality is a little more complicated than the “just do the NGS will you?” approach. Molecular diagnostics are of three purposes: classification or the diagnosis, prognosis, and prediction to treatment. For example, 1p19q codeletion empowers the pathologists to establish the histological diagnosis of oligodendrogliomas, and FISH takes only 2 days if done in the same department like us. 1p19q codeletion is also a prognostic marker, imparting a good prognosis to an infiltrative glioma.[8] MGMT is the classical predictive marker.[9],[10] Positivity for MGMT methylation predicts a more likely response to treatment with alkylating agents. The three purposes are related and biomarkers overlap. For example, MGMT is also a good prognostic marker for the regular adult glioblastomas and 1p19q is also a classifier as well as a prognosticator. An NGS result blind to critical single gene result can potentially give a confusing picture in brain tumor diagnostics. A single molecular aberration can be found in more than one group of tumors.


  The Need for Single Gene Tests for Quick, Precise Diagnoses Top


Molecular diagnostics may be trendy, but in essence, the pathologist's job, right from the beginning of our profession, has not changed: Giving a name to the tumor biopsied or resected not only tells the so-called cell of origin in an academic sense, i.e., classification, but the name has always been expected to be able to convey a meaning as to prognosis and the necessary treatments to clinicians and patients. Once you say a tumor is an oligodendroglioma by the name, any patient can go on the Internet and find out this is a glioma of good prognosis and is also more responsive to chemotherapy than other gliomas. We, as general pathologists, understand that once we say small cell lung carcinoma by histology, there will be an expectation for poor survival and the need for chemotherapy rather than radical surgery. To achieve these aims for neuropathology reporting, a consensus group of neuropathologists recommended a multi-layered integrated diagnosis combining histology, WHO grade, and molecular features.[2] However, actually, the role of the pathologists as to satisfying demands from patients and clinicians for a name, the prognosis, and guidance to treatment has never changed. Molecular diagnostics merely added a layer of sophistication and precision to the tools that are available to pathologists. Prognostication from molecular diagnostics is especially important for brain tumor patients because there is no good tumor staging scheme except in medulloblastomas. The situation is different with the other common cancers, for example, the lung, breast, colorectum, where tumor staging often has an over-riding significance over histology or molecular changes for prognosis and adjuvant treatment.

The astute readers will realize that for the three purposes of molecular diagnostics, I have only mentioned single-gene studies. The role of single-gene studies is more critical in brain tumor classification and prognostication than other cancers in the body. As general pathologists too, we diagnose adenocarcinoma of the lung on hematoxylin and eosin section, and perhaps one or two IHCs. Then, the work is done for the regular pathologists. One can now safely pass the block to the molecular diagnostic laboratory for further workup for therapeutic targets, either using single-gene studies or NGS. The situation is more or less the same for the common cancers, for example, colorectal carcinoma as their histological classification is relatively simple compared to CNS tumors.

In the CNS, even glioblastomas, the most common primary tumor, actually comprise less than roughly 30% of all brain tumors, including both children and adults encountered in the neuropathology laboratories.[11] The rest is a complicated patchwork of diverse entities. In many situations, it is important to have an algorithm for different diagnostic scenarios for brain tumors where most of the time, the single-gene studies will give the clinicians and the patient the critical answer within a few days. For example, it is important when faced with an oligodendroglial looking tumor in adults, one can have the 1p19q status established usually by FISH and IDH status established usually by IHC or sequencing as quickly as possible so that a definitive answer, for example, oligodendrgolioma, Grade II, can be given out. This will be highly appreciated by clinicians and patients. While 1p19q codeletion status can be established by genomics, for example, methylation studies or arrays, I will personally not want to sign out a provisional histological diagnosis like “probably oligodendroglioma awaiting 1p19q,” only to find out several weeks later from a methylation profile that tumor is in fact not 1p19q nondeleted and then one has to amend the original diagnosis. This will create immense confusion to patient and clinicians. Hence, it is vital to have a quick single-gene diagnostic on 1p19q most commonly FISH, available before one goes onto the genomics. Hence, the single-gene tests, although they may look untrendy and low-tech, give pathologists, clinicians, and patients some vital information that cannot be replaced easily by the genomics.

A set of single-gene diagnostics, combining molecular IHC, sequencing, and FISH, must be established in every histology laboratory receiving brain tumor tissue as a first line [Table 1], [Table 2], [Table 3]. A number of scenarios should be set up, and the algorithms of the diagnostic approach in the laboratories should be established. For example, when faced with an adult low-grade glioma, the determination of 1p19q and IDH status will be needed much earlier than potential drug targets from NGS. Biopsy of a brainstem tumor from a child should be tested quickly for H2K27M mutation irrespective of the grade of histology. The establishment of whether BRAF fusion is present is the first step to determine whether a tumor is likely to be pilocytic astrocytoma and therefore, discussion for post-resection adjuvant therapy is much less urgent or indeed needed. The early confirmation of TERTp mutation in an adult glioma low-grade by histology will re-classify the tumor as molecular glioblastoma, and adjuvant post-operative treatment will be required reasonably soon after the operation. Examples are many, and it is not the intention of this article to review all the diagnostic algorithms faced by pathologists down the microscope, and the readers are advised to refer to the excellent publications listed in the references.
Table 2: Single-gene sequencing needed immediately at the histology laboratory dealing with brain tumors

Click here to view
Table 3: Fluorescent in situ hybridization tests desirable at the histology laboratory dealing with brain tumors

Click here to view



  The Challenge of the Medulloblastoma Diagnostics Top


The molecular diagnostics of medulloblastoma pose a different challenge as the categorizing of medulloblastomas into the four groups, Wnt, SHH, Group 3 and Group 4 was based on transcriptomes and not mutations or other genetic aberrations, in their initial discovery.[12],[13] The challenge is even bigger for the other purposes of molecular diagnostics, namely prognosis and prediction for treatment, as these four groups are literally four tumors, despite the histological similarity, as to their prognosis and treatment regimens. The separation of treatment for risk groups in medulloblastoma, which is a combination of risk stratification depending on molecular groups, single-gene parameters, and clinical stage, is still at its infancy but nonetheless, for everyone charged with the diagnosis and treatment of medulloblastoma patients, knowledge of the molecular groups is a must-know early event and will always enter into consideration for clinical decision. The groups can just about be assigned by a battery of single-gene tests including IHCs and FISH [Table 1] and [Table 2], but this battery of tests is more likely just be able to assign a tumor as Wnt, SHH and non-Wnt, non-SHH without further separating the latter into Groups 3 and 4.[14],[15] IHC for p53 is also needed for subdividing the SHH group with relevance for risk stratification and also the potential for genetic counseling.[16]

Currently, the most common methods to achieve molecular grouping in medulloblastomas are by Nanostring or methylation profiling. Nanostring is a non-PCR, non-enzymatic hybridization methodology that Northcott et al. has devised to take advantage of the expression of 22 genes that differ in the four molecular groups of medulloblastomas.[17] Methylation profile mentioned above is also a widely used method of assigning molecular groups of medulloblastomas.[18],[19] Nanostring method is cheaper, faster but suffers from the fact that the method may not distinguish medulloblastomas from histologic mimics, for example, glioblastoma. The latter must be excluded by histology. The pros and cons for methylation profiling are discussed below.

While schemes of molecular diagnostics for risk stratification in medulloblastomas vary, [Table 4] demonstrates a commonly used scheme adapted from Sickkids, Toronto.[16]
Table 4: Risk stratification of medulloblastoma

Click here to view



  The Array of Genomics Top


This article may seem to be down-playing the importance of genomic diagnostics for brain tumors. We have no such intention, and in fact, genomics is increasingly important in brain tumor diagnosis and, in time, will be future of molecular diagnostics of brain tumors. In the WHO 2020 classification, the diagnosis of most brain tumors will carry a clause “desirable” (as opposed to essential) diagnostic criterion based on methylation profiling. Most histopathology laboratories are regarded by hospital administrations as “low-tech” and will not have the full range of NGS equipment available on site, methylation EPIC profiling, nanostring, etc., A lot of genomic work will still be needed to be sent to outside sources, may that be a company or a core facility of the institution. Moreover, currently, there are no commercial NGS tests that specifically cater for brain tumors. Most of the commercially available NGS platforms are “pan-cancer.” That is understandable from a commercial sense as the other cancers are so much commoner than brain tumors. The leading neuro-oncology centers in the USA run their own panels testing both mutations as well as some fusions, for example, UCSF, Pittsburgh.

Genomics gives two types of information. Molecular aberrations may be part of the diagnostic algorithms that were described, for example, 1p19q codeletion, BRAF fusion, epidermal growth factor receptor copy number gains. The other information they can give very powerfully is potential drug targets, especially those that are not regularly tested by single-gene studies. The search for potential drug targets is important for oncologists and patients, especially at recurrence, as these patients would have failed the standard-of-care therapy for that tumor type. Moreover at that juncture, how accurate the “name” is no longer so important. While those drugs may not be regarded as standard-of-care for that type of therapy, in salvage therapy, oncologists and patients probably are looking for anything that can potentially work. For the common scenario of adult glioblastomas, where the diagnosis is usually not difficult, and the essential aim is probably to look for drug targets after the standard-of-care therapies are exhausted at a recurrence, a general pan-cancer panel of target sequencing is a reasonable diagnostic option. The exception is perhaps ependymoma, where so far, treatment does not seem to depend on chemotherapy, so search for drug targets can be regarded as questionable. The nanostring platform offers a non-PCR, RNA-based platform, which aside from the transcriptome analysis for grouping of medulloblastoma mentioned above, can in addition, be utilized to test for fusion genes common to pediatric gliomas.[17],[20],[21] [Table 5] lists the panels we use, which are adapted from panels used by Sickkids, Toronto.
Table 5: Panels of fusion genes in pediatric gliomas detected by Nanostring

Click here to view


Therapy for recurrent tumor, second-line chemotherapy, is now an important part of oncology practice and probably more so in neuro-oncology. Patients with brain tumors die of their recurrences rather than metastases or sepsis as with patients with other cancers, and tissue availability for recurrent tumor is scanty as up until recently, recurrent brain tumors are not often resected or biopsied. The latter trend is being modified these days as increasingly, brain tumor patients live longer, especially among children with brain tumors, and a second operation when tumors recur either for debulking or just for tissue sampling for molecular testing becomes more common. This is the scenario when NGS is most useful. The identification of a potential drug target from NGS is still a specialized task beyond most pathologists and advice is often sought from specialized companies after NGS. NGS panels catering for therapeutics have potentially different emphases from those catering for diagnosis and classification. Moreover, a large target sequencing panel can also uncover the hypermutator phenotype, a cause for resistance to chemotherapy.[22],[23],[24]


  If in Doubt, Just Do the Methylomes? Top


As noted in the previous paragraphs, methylation profiling offers an exciting and apparently fit-all solution to molecular diagnostics of brain tumors. The German Cancer Research Centre (DKFZ) developed a machine-learning-based CNS tumor classifier.[6] The classifier initially incorporated a reference cohort comprising 2801 samples from 81 tumor classes.[6] Methylation data in IDAT files generated by the Illumina HumanMethylation450 (450K) or methylation EPIC (850K) array can be uploaded to www.molecularneuropathology.org for tumor classification. The current Classifier (version v11b4) is based on the analysis of 10,000 CpG sites present on both arrays.

In addition to assigning a diagnosis, the DKFZ classifier also gives some essential information of copy number variation, for example, 1p19q and the specific methylation of a set of genes characteristic to gliomas, the G-CIMP status, can also be worked out and gives critical information to prognosis in adult gliomas.[25],[26] Methylation profile also gives the MGMT status, very useful information both for prediction to chemotherapy in adult gliomas as well as their prognostication.[25] Methylation profiling is also the only known reliable way to separate PFA and PFB for ependymomas. It is, however, not without limitations. The assay is relatively expensive and must be run in batches of 8. Thus, obtaining the genome-wide methylation profiling within days expected by clinicians is almost impossible. However most importantly, it does not give information for fusion genes nor mutations, which form the basis for selecting novel drug therapy. Hence, it will have limited use if the finding of drug target, for example, in the scenario of tumor recurrence as described above, is the main purpose of the biopsy.


  So Back to the Future Top


The WHO classification of CNS tumors in 2016 for the first time laid down a few molecular features as diagnostic criteria, namely 1p19q, IDH status. The upcoming classification in 2020 will include essential and desirable diagnostic criteria for many other entities. This article is more of an opinion piece rather than a review, and cannot claim to cover the molecular diagnostic features of all CNS tumors. Aside from medulloblastoma, which was mentioned above, molecular diagnostics are especially important in the field of pediatric neuro-oncology. The vast majority of pediatric low-grade gliomas have molecular features which, although not tying to the histological features so well, are nonetheless very prognostic. Similarly, infantile gliomas are now known to have their unique molecular footprints.[21],[27] Moreover, in the non-meningioma extra-axial tumors, many CNS tumors overlap with their bone and soft tissue counterparts and, similar to them, will require molecular diagnostics for their diagnosis. They include CIC-rearranged sarcoma, Ewing's sarcoma, and DICER-1 mutant sarcoma.

So from now on, for all pathology laboratories that deal with brain tumors, the availability or access to molecular diagnostics will be a must. The skills that are required are eyes that can discern the diagnostic dilemma in question, the algorithms utilizing mostly single-gene tests that give a quick and molecular-based diagnosis, and genomics that will help in difficult diagnoses or unravel potential targets. Methylation profiles will always be a great adjunct to assist the first two goals and will be extensively quoted in the upcoming WHO 2020 Classification. However for the time being, because of cost concern, it is only used by the authors in diagnostically difficult cases. In the more advanced centers, methylation profiles may be done in all cases side by side with histology.

Financial support and sponsorship

The molecular studies mentioned in this review are supported by the Children Cancer Foundation, Hong Kong Special Administrative Region, China; and Health and Medical Research Fund (HMRF), the Food and Health Bureau of Hong Kong Special Administrative Region, China (reference number: 07180736).

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Horbinski C, Ligon KL, Brastianos P, Huse JT, Venere M, Chang S, et al. The medical necessity of advanced molecular testing in the diagnosis and treatment of brain tumor patients. Neuro Oncol 2019;21:1498-508.  Back to cited text no. 1
    
2.
Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of tumors of the central nervous system: A summary. Acta Neuropathol 2016;131:803-20.  Back to cited text no. 2
    
3.
Meyerson M, Gabriel S, Getz G. Advances in understanding cancer genomes through second-generation sequencing. Nat Rev Genet 2010;11:685-96.  Back to cited text no. 3
    
4.
Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature 2008;456:53-9.  Back to cited text no. 4
    
5.
Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature 2011;475:348-52.  Back to cited text no. 5
    
6.
Capper D, Jones DT, Sill M, Hovestadt V, Schrimpf D, Sturm D, et al. DNA methylation-based classification of central nervous system tumours. Nature 2018;555:469-74.  Back to cited text no. 6
    
7.
Geiss GK, Bumgarner RE, Birditt B, Dahl T, Dowidar N, Dunaway DL, et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol 2008;26:317-25.  Back to cited text no. 7
    
8.
Kristensen BW, Priesterbach-Ackley LP, Petersen JK, Wesseling P. Molecular pathology of tumors of the central nervous system. Ann Oncol 2019;30:1265-78.  Back to cited text no. 8
    
9.
Brandner S, von Deimling A. Diagnostic, prognostic and predictive relevance of molecular markers in gliomas. Neuropathol Appl Neurobiol 2015;41:694-720.  Back to cited text no. 9
    
10.
Jansen M, Yip S, Louis DN. Molecular pathology in adult gliomas: Diagnostic, prognostic, and predictive markers. Lancet Neurol 2010;9:717-26.  Back to cited text no. 10
    
11.
Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan JS. CBTRUS Statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2011-2015. Neuro Oncol 2018;20:iv1-86.  Back to cited text no. 11
    
12.
Thompson MC, Fuller C, Hogg TL, Dalton J, Finkelstein D, Lau CC, et al. Genomics identifies medulloblastoma subgroups that are enriched for specific genetic alterations. J Clin Oncol 2006;24:1924-31.  Back to cited text no. 12
    
13.
Taylor MD, Northcott PA, Korshunov A, Remke M, Cho YJ, Clifford SC, et al. Molecular subgroups of medulloblastoma: The current consensus. Acta Neuropathol 2012;123:465-72.  Back to cited text no. 13
    
14.
D'Arcy CE, Nobre LF, Arnaldo A, Ramaswamy V, Taylor MD, Naz-Hazrati L, et al. Immunohistochemical and nanoString-Based Subgrouping of Clinical Medulloblastoma Samples. J Neuropathol Exp Neurol 2020;79:437-47.  Back to cited text no. 14
    
15.
Ellison DW, Dalton J, Kocak M, Nicholson SL, Fraga C, Neale G, et al. Medulloblastoma: Clinicopathological correlates of SHH, WNT, and non-SHH/WNT molecular subgroups. Acta Neuropathol 2011;121:381-96.  Back to cited text no. 15
    
16.
Ramaswamy V, Remke M, Bouffet E, Bailey S, Clifford SC, Doz F, et al. Risk stratification of childhood medulloblastoma in the molecular era: The current consensus. Acta Neuropathol 2016;131:821-31.  Back to cited text no. 16
    
17.
Northcott PA, Shih DJ, Remke M, Cho YJ, Kool M, Hawkins C, et al. Rapid, reliable, and reproducible molecular sub-grouping of clinical medulloblastoma samples. Acta Neuropathol 2012;123:615-26.  Back to cited text no. 17
    
18.
Schwalbe EC, Williamson D, Lindsey JC, Hamilton D, Ryan SL, Megahed H, et al. DNA methylation profiling of medulloblastoma allows robust subclassification and improved outcome prediction using formalin-fixed biopsies. Acta Neuropathol 2013;125:359-71.  Back to cited text no. 18
    
19.
Hovestadt V, Remke M, Kool M, Pietsch T, Northcott PA, Fischer R, et al. Robust molecular subgrouping and copy-number profiling of medulloblastoma from small amounts of archival tumour material using high-density DNA methylation arrays. Acta Neuropathol 2013;125:913-6.  Back to cited text no. 19
    
20.
Ryall S, Arnoldo A, Krishnatry R, Mistry M, Khor K, Sheth J, et al. Multiplex detection of pediatric low-grade glioma signature fusion transcripts and duplications using the NanoString nCounter system. J Neuropathol Exp Neurol 2017;76:562-70.  Back to cited text no. 20
    
21.
Guerreiro Stucklin AS, Ryall S, Fukuoka K, Zapotocky M, Lassaletta A, Li C, et al. Alterations in ALK/ROS1/NTRK/MET drive a group of infantile hemispheric gliomas. Nat Commun 2019;10:4343.  Back to cited text no. 21
    
22.
Shi ZF, Li KK, Kwan JS, Yang RR, Aibaidula A, Tang Q, et al. Whole-exome sequencing revealed mutational profiles of giant cell glioblastomas. Brain Pathol 2019;29:782-92.  Back to cited text no. 22
    
23.
Johnson BE, Mazor T, Hong C, Barnes M, Aihara K, McLean CY, et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science 2014;343:189-93.  Back to cited text no. 23
    
24.
Indraccolo S, Lombardi G, Fassan M, Pasqualini L, Giunco S, Marcato R, et al. Genetic, Epigenetic, and immunologic profiling of MMR-deficient relapsed glioblastoma. Clin Cancer Res 2019;25:1828-37.  Back to cited text no. 24
    
25.
Capper D, Stichel D, Sahm F, Jones DTW, Schrimpf D, Sill M, et al. Practical implementation of DNA methylation and copy-number-based CNS tumor diagnostics: The heidelberg experience. Acta Neuropathol 2018;136:181-210.  Back to cited text no. 25
    
26.
Ceccarelli M, Barthel FP, Malta TM, Sabedot TS, Salama SR, Murray BA, et al. Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse Glioma. Cell 2016;164:550-63.  Back to cited text no. 26
    
27.
Clarke M, Mackay A, Ismer B, Pickles JC, Tatevossian RG, Newman S, et al. Infant high-grade gliomas comprise multiple subgroups characterized by novel targetable gene fusions and favorable outcomes. Cancer Discov 2020;10:942-63.  Back to cited text no. 27
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


This article has been cited by
1 Combinations of Single-Gene Biomarkers Can Precisely Stratify 1,028 Adult Gliomas for Prognostication
Aden Ka-Yin Chan, Zhi-Feng Shi, Kay Ka-Wai Li, Wei-Wei Wang, Hong Chen, Nellie Yuk-Fei Chung, Danny Tat-Ming Chan, Wai-Sang Poon, Herbert Ho-fung Loong, Xian-Zhi Liu, Zhen-Yu Zhang, Ying Mao, Ho-Keung Ng
Frontiers in Oncology. 2022; 12
[Pubmed] | [DOI]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Surely, More (Ge...
The Need for Sin...
The Challenge of...
The Array of Gen...
If in Doubt, Jus...
So Back to the F...
References
Article Tables

 Article Access Statistics
    Viewed3199    
    Printed72    
    Emailed0    
    PDF Downloaded243    
    Comments [Add]    
    Cited by others 1    

Recommend this journal