Literature DB >> 24289128

Genomic and transcriptome analysis revealing an oncogenic functional module in meningiomas.

Xiao Chang1, Lingling Shi, Fan Gao, Jonathan Russin, Liyun Zeng, Shuhan He, Thomas C Chen, Steven L Giannotta, Daniel J Weisenberger, Gabriel Zada, Kai Wang, William J Mack.   

Abstract

OBJECT: Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%-5% display malignant pathological features. The key molecular pathways involved in malignant transformation remain to be determined.
METHODS: Illumina expression microarrays were used to assess gene expression levels, and Illumina single-nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant meningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). A weighted gene coexpression network approach was used to identify coexpression modules associated with malignancy.
RESULTS: At the genomic level, malignant meningiomas had more chromosomal losses than atypical and benign meningiomas, with average length of 528, 203, and 34 megabases, respectively. Monosomic loss of chromosome 22 was confirmed to be one of the primary chromosomal level abnormalities in all subtypes of meningiomas. At the transcriptome level, the authors identified 23 coexpression modules from the weighted gene coexpression network. Gene functional enrichment analysis highlighted a module with 356 genes that was highly related to tumorigenesis. Four intramodular hubs within the module (GAB2, KLF2, ID1, and CTF1) were oncogenic in other cancers such as leukemia. A putative meningioma tumor suppressor MN1 was also identified in this module with differential expression between malignant and benign meningiomas.
CONCLUSIONS: The authors' genomic and transcriptome analysis of meningiomas provides novel insights into the molecular pathways involved in malignant transformation of meningiomas, with implications for molecular heterogeneity of the disease.

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Year:  2013        PMID: 24289128     DOI: 10.3171/2013.10.FOCUS13326

Source DB:  PubMed          Journal:  Neurosurg Focus        ISSN: 1092-0684            Impact factor:   4.047


  14 in total

1.  Identification of novel fusion transcripts in meningioma.

Authors:  A Basit Khan; Ron Gadot; Arya Shetty; James C Bayley; Caroline C Hadley; Maria F Cardenas; Ali Jalali; Akdes S Harmanci; Arif O Harmanci; David A Wheeler; Tiemo J Klisch; Akash J Patel
Journal:  J Neurooncol       Date:  2020-09-19       Impact factor: 4.130

2.  Exome sequencing on malignant meningiomas identified mutations in neurofibromatosis type 2 (NF2) and meningioma 1 (MN1) genes.

Authors:  Xu Zhang; Haiying Jia; Yao Lu; Chengliang Dong; Jinghui Hou; Zheng Wang; Feng Wang; Hongbin Zhong; Lin Wang; Kai Wang
Journal:  Discov Med       Date:  2014-12       Impact factor: 2.970

3.  Gene Coexpression and Evolutionary Conservation Analysis of the Human Preimplantation Embryos.

Authors:  Tiancheng Liu; Lin Yu; Guohui Ding; Zhen Wang; Lei Liu; Hong Li; Yixue Li
Journal:  Biomed Res Int       Date:  2015-07-27       Impact factor: 3.411

4.  Transcriptomic analysis of aggressive meningiomas identifies PTTG1 and LEPR as prognostic biomarkers independent of WHO grade.

Authors:  Melissa Schmidt; Andreas Mock; Christine Jungk; Felix Sahm; Anna Theresa Ull; Rolf Warta; Katrin Lamszus; Konstantinos Gousias; Ralf Ketter; Saskia Roesch; Carmen Rapp; Sebastian Schefzyk; Steffi Urbschat; Bernd Lahrmann; Almuth F Kessler; Mario Löhr; Christian Senft; Niels Grabe; David Reuss; Philipp Beckhove; Manfred Westphal; Andreas von Deimling; Andreas Unterberg; Matthias Simon; Christel Herold-Mende
Journal:  Oncotarget       Date:  2016-03-22

5.  Identification of key genes and pathways in meningioma by bioinformatics analysis.

Authors:  Junxi Dai; Yanbin Ma; Shenghua Chu; Nanyang Le; Jun Cao; Yang Wang
Journal:  Oncol Lett       Date:  2018-03-29       Impact factor: 2.967

6.  Integrated Transcriptomic Analysis Reveals the Molecular Mechanism of Meningiomas by Weighted Gene Coexpression Network Analysis.

Authors:  Biao Yang; Shuxun Wei; Yan-Bin Ma; Sheng-Hua Chu
Journal:  Biomed Res Int       Date:  2020-06-10       Impact factor: 3.411

Review 7.  Molecular Genetics of Intracranial Meningiomas with Emphasis on Canonical Wnt Signalling.

Authors:  Nives Pećina-Šlaus; Anja Kafka; Mirna Lechpammer
Journal:  Cancers (Basel)       Date:  2016-07-15       Impact factor: 6.639

8.  Differentially Expressed MicroRNAs in Meningiomas Grades I and II Suggest Shared Biomarkers with Malignant Tumors.

Authors:  Mohamed Raafat El-Gewely; Morten Andreassen; Mari Walquist; Anita Ursvik; Erik Knutsen; Mona Nystad; Dag H Coucheron; Kristin Smistad Myrmel; Rune Hennig; Steinar D Johansen
Journal:  Cancers (Basel)       Date:  2016-03-03       Impact factor: 6.639

9.  RNA-seq transcriptome analysis of formalin fixed, paraffin-embedded canine meningioma.

Authors:  Jennifer K Grenier; Polly A Foureman; Erica A Sloma; Andrew D Miller
Journal:  PLoS One       Date:  2017-10-26       Impact factor: 3.240

Review 10.  Multi-Omics Analysis in Initiation and Progression of Meningiomas: From Pathogenesis to Diagnosis.

Authors:  Jiachen Liu; Congcong Xia; Gaiqing Wang
Journal:  Front Oncol       Date:  2020-08-28       Impact factor: 6.244

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