This pipeline maps genes, with mutation or copy number alteration AND this alteration is highly correlated with mRNA expression, to pathways curated in the KEGG and BIOCARTA databases. It identifies pathways significantly enriched with these genes. The pipeline also identifies pathways significantly enriched with marker genes of each expression subtype of cancer.
genes with mutation: identified by the Mutation_Significance pipeline
genes with copy number alteration: identified by the CopyNumber_Gistic2 pipeline
correlation between copy number and mRNA expression: identified by the Correlate_CopyNumber_vs_mRNA pipeline
marker genes and expression subtypes: identified by the mRNAConsensusClustering pipeline
There are 3 genes with significant mutation (Q value <= 0.1) and 254 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 2000 for subtype 1, 2000 for subtype 2, 2000 for subtype 3. Pathways significantly enriched with these genes (Q value <= 0.01) are identified :
0 pathways significantly enriched with genes with copy number alteration or mutation.
0 pathways significantly enriched with marker genes of gene expression subtype 1
0 pathways significantly enriched with marker genes of gene expression subtype 2
0 pathways significantly enriched with marker genes of gene expression subtype 3
Table 1. Get Full Table Top Pathways enriched with genes with copy number alteration or mutation. Nof Genes : No. of genes in this pathway. Nof CNV_Mut : No. of genes with copy number alteration or mutation in this pathway. Enrichment , P value and Q value : See Methods & Data below. CNV_Mut Genes in Pathway: genes with copy number alteration or mutation in this pathway.
Pathway | Nof Genes | Nof CNV_Mut | Enrichment | P value | Q value |
---|---|---|---|---|---|
BIOCARTA_RACCYCD_PATHWAY | 26 | 4 | 3.6 | 0.0003 | 0.044 |
KEGG_UBIQUITIN_MEDIATED_PROTEOLYSIS | 137 | 8 | 2.3 | 0.0002 | 0.044 |
BIOCARTA_TOLL_PATHWAY | 37 | 4 | 3.2 | 0.001 | 0.12 |
BIOCARTA_PYK2_PATHWAY | 29 | 3 | 3.1 | 0.0047 | 0.17 |
BIOCARTA_MAPK_PATHWAY | 87 | 5 | 2.2 | 0.0043 | 0.17 |
CCNE1,CHUK,RB1,IKBKB
BTRC,CUL1,UBE2D3,UBOX5,UBE2G2,UBE2M,UBE3C,UBE4A
CHUK,MAP2K4,IKBKB,EIF2AK2
SRC,MAP2K4,CALM3
MAX,MAP3K4,CHUK,MAP2K4,IKBKB
Table 2. Get Full Table Top Pathways enriched with marker genes of gene expression subtype 1 . Nof Genes : No. of genes in this pathway. Nof Marker : No. of marker genes of gene expression subtype 1 in this pathway. Enrichment , P value and Q value : See Methods & Data below. Marker Gene in Pathway: markers of gene expression subtype 1 in this pathway
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
KEGG_INSULIN_SIGNALING_PATHWAY | 137 | 24 | 1 | 0.0005 | 0.17 |
BIOCARTA_RELA_PATHWAY | 16 | 1 | -0.49 | 0.76 | 1 |
BIOCARTA_NO1_PATHWAY | 31 | 3 | 0.19 | 0.48 | 1 |
BIOCARTA_CSK_PATHWAY | 24 | 2 | 0.05 | 0.57 | 1 |
BIOCARTA_AMI_PATHWAY | 20 | 3 | 0.78 | 0.24 | 1 |
PRKACG,RAPGEF1,BRAF,PTPRF,PIK3CB,SOCS3,KHSRP,PHKA1,G6PC2,MAP2K1,ACACB,RPS6,PTPN1,PRKAG3,SHC3,SHC2,PHKG1,FLOT1,EXOC7,SORBS1,CALML3,PDE3A,LIPE,PYGB
RIPK1
PRKACG,PDE3A,CHRM1
PRKACG,ZAP70
F7,PROC,F2
Table 3. Get Full Table Top Pathways enriched with marker genes of gene expression subtype 2 . Nof Genes : No. of genes in this pathway. Nof Marker : No. of marker genes of gene expression subtype 2 in this pathway. Enrichment , P value and Q value : See Methods & Data below. Marker Gene in Pathway: markers of gene expression subtype 2 in this pathway
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
BIOCARTA_ARF_PATHWAY | 17 | 7 | 2.2 | 0.0003 | 0.035 |
KEGG_MAPK_SIGNALING_PATHWAY | 267 | 41 | 0.81 | 0.0002 | 0.035 |
KEGG_MELANOGENESIS | 102 | 20 | 1.2 | 0.0003 | 0.035 |
KEGG_STEROID_BIOSYNTHESIS | 17 | 6 | 2.1 | 0.0015 | 0.087 |
KEGG_OXIDATIVE_PHOSPHORYLATION | 133 | 20 | 0.99 | 0.0016 | 0.087 |
POLR1A,POLR1C,POLR1B,CDKN2A,RAC1,ABL1,TWIST1
MAP3K8,PTPRR,PLA2G2A,IL1R2,CACNB4,KRAS,RAC1,MAP2K1,MAP2K3,PLA2G4A,JMJD7-PLA2G4B,FGF5,FLNC,FLNB,FLNA,MAP3K13,MAP3K11,MKNK2,SOS1,RPS6KA3,DUSP7,FGF19,FGF11,PRKACA,RELA,STK4,STK3,MAP4K4,ARRB2,TRAF2,ATF2,PTPN5,ATF4,CACNA1D,CACNA1B,MAX,PAK1,PRKCA,MAP3K3,RASGRP4,MAPK8IP3
ADCY1,ADCY6,MC1R,PRKACA,CREB3L4,WNT5A,KRAS,MAP2K1,PLCB3,PRKCA,LEF1,KIT,TCF7L2,CALML6,GNAO1,CREB3,FZD5,WNT7B,FZD10,WNT7A
TM7SF2,GLB1,CEL,CYP51A1,LSS,SC4MOL
COX5A,NDUFA4L2,COX8A,PPA1,COX11,ATP6V0D1,ATP6V0D2,ATP5H,COX15,ATP6V1C1,ATP5G2,COX7A2L,NDUFB1,NDUFA8,NDUFA1,SDHA,SDHB,ATP6V1E2,SDHD,ATP6V0A1
Table 4. Get Full Table Top Pathways enriched with marker genes of gene expression subtype 3 . Nof Genes : No. of genes in this pathway. Nof Marker : No. of marker genes of gene expression subtype 3 in this pathway. Enrichment , P value and Q value : See Methods & Data below. Marker Gene in Pathway: markers of gene expression subtype 3 in this pathway
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
BIOCARTA_BCR_PATHWAY | 35 | 7 | 1.2 | 0.022 | 0.7 |
BIOCARTA_FMLP_PATHWAY | 37 | 8 | 1.4 | 0.0094 | 0.7 |
BIOCARTA_EDG1_PATHWAY | 27 | 6 | 1.4 | 0.023 | 0.7 |
BIOCARTA_GPCR_PATHWAY | 35 | 7 | 1.2 | 0.022 | 0.7 |
BIOCARTA_IGF1MTOR_PATHWAY | 20 | 5 | 1.5 | 0.023 | 0.7 |
BTK,FOS,RAC1,PPP3CB,PPP3CC,SHC1,CALM2
GNA15,RAC1,PPP3CB,PPP3CC,PLCB1,NCF2,GNGT1,CALM2
PDGFA,GNAI1,AKT1,RAC1,PLCB1,GNGT1
GNAI1,FOS,PPP3CB,PPP3CC,GNGT1,GNAQ,CALM2
INPPL1,RPS6,PTEN,AKT1,EIF2B5
Let genes with copy number alteration or mutation be query genes. Let marker genes of specific identified subtypes be query genes. The Enrichment is calculated as:
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Enrichment = log2 (# of query genes in the pathway/# No of query genes) - log2 (# of genes in the pathway/# of human genes)
The statistical signficance of the pathways that are enriched with genes with copy number alteration or mutation, and the pathways that are enriched with markers genes of specific identified subtypes is measured by P value.
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P value = Fisher exact P value
The Q value is for adjusting P value for multiple testing. A public available R package is used to calculate the Q value.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.