Omosome level, among the five BIBS39 variation classes, cnLOH is the major type, which is distributed over all chromosomes. Furthermore, we have validated many variations at the cytoband level (Table 3). For instance, we found duplications on 7q31.31, 7q31.32, 7q31.33, 7q33, 7q34, 7q35 and 7q36.1 in HGG, which is in agreement with gains of 7q reported in both grades [37]. We discovered hemizygous CP21 deletions on numerous cytobands (e.g., 6q12, 6q13, 6q14.1, 6q16.3, 6q21, 6q22.1, 6q23.1, 6q24.1, 13q12.2, 13q13.1, 13q14.12, 13q21.1, 19q12, and 19q13.11) in line with losses of 6q, 13q, and 19q in HGG [37,44]. There have been some contradicting results in this study; for example, we only identified duplications on 1p in LGG and hemizygous deletions on 19q in HGG but LOHs on 1p-19q were reported in both grades by another group [41]. We also have some novel findings specific to Chinese populations and observed the complicated and altered roles of traditional tumor-related genes in our study. For example, KIT gains in 2 LGG and 2 HGG, MGMT gains in 1 LGG and 3 HGG, MXI1 gains in 1 LGG and 3 HGG, DMBT1 gains in 1 LGG and 3 HGG, IDH1 only gains in one LGG. Thus, TSGs and oncogenes are relative and conditionsensitive concept, i.e., TSGs in one sample may be oncogenes in another. We finally inferred that TSGs not only can be lost butalso can be gained, whereas oncogenes appear generally being gained in these tumors. We did not find any obvious major pathways shared 
by LGG and HGG but identified 6 and 2 subclasses from the major class “lipid metabolism” shared by the two grades, respectively. In HGG, we noticed some interesting variations, including AASS (4 gains) in “lysine degradation” and CHRM2 (4 gains), CYSLTR2 (2 gains and 2 losses), GRM8 (4 gains), HTR2A (2 gains and 2 losses), and MLNR (2 gains and 2 losses) in “neuroactive ligand-receptor interaction”. We further found variations of GRM8 (2 gains) and CYSLTR2 (1 loss), HTR2A (1 loss), MLNR (1 loss) in LGG. Gains in the four LGG are CYP2J2, CYP4A11, CYP4A22, PLA2G2A, PLA2G2C, PLA2G2D, PLA2G2E, PLA2G2F, and PLA2G5, and they are involved in “arachidonic acid metabolism”. Looking into well-known oncogenes and TSGs, we identified gains of EGFR in “de novo glioma pathway” (2 in LGG and 3 in HGG), as well as MDM2 (1 in LGG and 3 in HGG) and PTEN (1 in HGG), and losses of CDKN2A (2 in HGG). In “secondary glioma pathway”, gains of PDGFA (1 in LGG and 2 in HGG), PDGFRA (2 in LGG and 2 in HGG) and CDK4 (1 in LGG and 2 in HGG) and RB1 (2 in HGG), and losses of RB1 (1 in LGG and 2 in HGG) are also identified. Our study was designed to uncover molecular differences between LGG and HGG, which are largely based on pathology, morphology, and degree of malignancy, and for which we know that altered genomic regions of HGG are more severe than those of LGG and that patient survival time is shorter in HGG (data not shown). Based on our study, we hope to associate genetics to clinical 12926553 outcomes in three crucial aspects of fighting the disease, including diagnosis, treatment, and prognosis. First, specific andGenomic Aberration Patterns in GliomasFigure 1. A network of pathways related to LGG, HGG, and others. The abbreviations for KEGG pathways used in this analysis are listed as follows. AAM: Arachidonic acid metabolism; LAM: Linoleic acid metabolism; ALAM: alpha-Linolenic acid metabolism; ELM: Ether lipid metabolism; GPM: Glycerophospholipid metabolism; PD: Prion diseases; GNRH: GnRH signaling pathway; LTD:.Omosome level, among the five variation classes, cnLOH is the major type, which is distributed over all chromosomes. Furthermore, we have validated many variations at the cytoband level (Table 3). For instance, we found duplications on 7q31.31, 7q31.32, 7q31.33, 7q33, 7q34, 7q35 and 7q36.1 in HGG, which is in agreement with gains of 7q reported in both grades [37]. We discovered hemizygous deletions on numerous cytobands (e.g., 6q12, 6q13, 6q14.1, 6q16.3, 6q21, 6q22.1, 6q23.1, 6q24.1, 13q12.2, 13q13.1, 13q14.12, 13q21.1, 19q12, and 19q13.11) in line with losses of 6q, 13q, and 19q in HGG [37,44]. There have been some contradicting results in this study; for example, we only identified duplications on 1p in LGG and hemizygous deletions on 19q in HGG but LOHs on 1p-19q were reported in both grades by another group [41]. We also have some novel findings specific to Chinese populations and observed the complicated and altered roles of traditional tumor-related genes in our study. For example, KIT gains in 2 LGG and 2 HGG, MGMT gains in 1 LGG and 3 HGG, MXI1 gains in 1 LGG and 3 HGG, DMBT1 gains in 1 LGG and 3 HGG, IDH1 only gains in one LGG. Thus, TSGs and oncogenes are relative and conditionsensitive concept, i.e., TSGs in one sample may be oncogenes in another. We finally inferred that TSGs not only can be lost butalso can be gained, whereas oncogenes appear generally being gained in these tumors. We did not find any obvious major pathways shared by LGG and HGG but identified 6 and 2 subclasses from the major class “lipid metabolism” shared by the two grades, respectively. In HGG, we noticed some interesting variations, including AASS (4 gains) in “lysine degradation” and CHRM2 (4 gains), CYSLTR2 (2 gains and 2 losses), GRM8 (4 gains), HTR2A (2 gains and 2 losses), and MLNR (2 gains and 2 losses) in “neuroactive ligand-receptor interaction”. We further found variations of GRM8 (2 gains) and CYSLTR2 (1 loss), HTR2A (1 loss), MLNR (1 loss) in LGG. Gains in the four LGG are CYP2J2, CYP4A11, CYP4A22, PLA2G2A, PLA2G2C, PLA2G2D, PLA2G2E, PLA2G2F, and PLA2G5, and they are involved in “arachidonic acid metabolism”. Looking into well-known oncogenes and TSGs, we identified gains of EGFR in “de novo glioma pathway” (2 in LGG and 3 in HGG), as well as MDM2 (1 in LGG and 3 in HGG) and PTEN (1 in HGG), and losses of CDKN2A (2 in HGG). In “secondary glioma pathway”, gains of PDGFA (1 in LGG and 2 in HGG), PDGFRA (2 in LGG and 2 in HGG) and CDK4 (1 in LGG and 2 in HGG) and RB1 (2 in HGG), and losses of RB1 (1 in LGG and 2 in HGG) are also identified. Our study was designed to uncover molecular differences between LGG and HGG, which are largely based on pathology, morphology, and degree of malignancy, and for which we know that altered genomic regions of HGG are more severe than those of LGG and that patient survival time is shorter in HGG (data not shown). Based on our study, we hope to associate genetics to clinical 12926553 outcomes in three crucial aspects of fighting the disease, 
including diagnosis, treatment, and prognosis. First, specific andGenomic Aberration Patterns in GliomasFigure 1. A network of pathways related to LGG, HGG, and others. The abbreviations for KEGG pathways used in this analysis are listed as follows. AAM: Arachidonic acid metabolism; LAM: Linoleic acid metabolism; ALAM: alpha-Linolenic acid metabolism; ELM: Ether lipid metabolism; GPM: Glycerophospholipid metabolism; PD: Prion diseases; GNRH: GnRH signaling pathway; LTD:.