Abstract
Although several researches have explored the similarity across development and tumorigenesis in cellular behavior and underlying molecular mechanisms, not many have investigated the developmental characteristics at proteomic level and further extended to cancer clinical outcome. In this study, we used iTRAQ to quantify the protein expression changes during macaque rhesus brain development from fetuses at gestation 70 days to after born 5 years. Then, we performed weighted gene co-expression network analysis (WGCNA) on protein expression data of brain development to identify co-expressed modules that highly expressed on distinct development stages, including early stage, middle stage and late stage. Moreover, we used the univariate cox regression model to evaluate the prognostic potentials of these genes in two independent glioblastoma multiforme (GBM) datasets. The results showed that the modules highly expressed on early stage contained more reproducible prognostic genes, including ILF2, CCT7, CCT4, RPL10A, MSN, PRPS1, TFRC and APEX1. These genes were not only associated with clinical outcome, but also tended to influence chemoresponse. These signatures identified from embryonic brain development might contribute to precise prediction of GBM prognosis and identification of novel drug targets in GBM therapies. Thus, the development could become a viable reference model for researching cancers, including identifying novel prognostic markers and promoting new therapies.
Highlights
Malignant gliomas are the most lethal and common brain tumor in adults
Substantial research effort has focused on identification markers of genetic alterations in glioblastoma multiforme (GBM) that may associate with prognosis and may help to define subclasses of GBM patients [9, 10], such as TP53 mutation, EGFR mutation and PTEN mutation [11,12,13]
While these resources all have their own merit for uncovering the mechanism www.impactjournals.com/oncotarget of malignant gliomas and promoting related therapies, they all focus on tumor samples and not concern other processes correlated with tumor progression such as brain development
Summary
Malignant gliomas are the most lethal and common brain tumor in adults. The most biologically aggressive subtype is glioblastoma multiforme (GBM) [1,2,3,4]. Substantial research effort has focused on identification markers of genetic alterations in GBMs that may associate with prognosis and may help to define subclasses of GBM patients [9, 10], such as TP53 mutation, EGFR mutation and PTEN mutation [11,12,13]. While these resources all have their own merit for uncovering the mechanism www.impactjournals.com/oncotarget of malignant gliomas and promoting related therapies, they all focus on tumor samples and not concern other processes correlated with tumor progression such as brain development. They just obtain the transcriptome data, in consideration of the disagreement between mRNA level and protein level [19, 20], the proteome data could provide some novel and essential information
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