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 14 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 1094 for subtype 1, 1094 for subtype 2, 1094 for subtype 3, 1094 for subtype 4. Pathways significantly enriched with these genes (Q value <= 0.01) are identified :
7 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
16 pathways significantly enriched with marker genes of gene expression subtype 4
Pathway | Nof Genes | Nof CNV_Mut | Enrichment | P value | Q value |
---|---|---|---|---|---|
BIOCARTA_G1_PATHWAY | 28 | 5 | 3.8 | 0 | 0.0056 |
BIOCARTA_TEL_PATHWAY | 18 | 4 | 4.1 | 0.0001 | 0.0056 |
BIOCARTA_ARF_PATHWAY | 17 | 4 | 4.2 | 0.0001 | 0.0056 |
KEGG_UBIQUITIN_MEDIATED_PROTEOLYSIS | 137 | 9 | 2.4 | 0.0001 | 0.0056 |
KEGG_RIBOSOME | 87 | 7 | 2.7 | 0.0001 | 0.0074 |
CDKN2A,TFDP1,SKP2,TP53,RB1
XRCC5,TP53,RB1,PTEN
TP53,RB1,CDKN2A,PIK3CA
SAE1,CUL1,SKP2,KEAP1,FBXW7,UBE2L3,UBE2F,UBE2S,CUL4A
RPL18,RPS19,RPS16,RPL37,RPL38,RPL28,MRPL23
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
KEGG_ENDOCYTOSIS | 183 | 21 | 1.3 | 0.0001 | 0.032 |
KEGG_TIGHT_JUNCTION | 134 | 17 | 1.4 | 0.0002 | 0.032 |
KEGG_ADHERENS_JUNCTION | 75 | 10 | 1.5 | 0.0026 | 0.28 |
KEGG_GLYCOSAMINOGLYCAN_BIOSYNTHESIS_CHONDROITIN_SULFATE | 22 | 5 | 2.2 | 0.0034 | 0.28 |
BIOCARTA_MPR_PATHWAY | 34 | 6 | 1.9 | 0.0052 | 0.35 |
HRAS,VPS4B,EGFR,ARRB1,SH3GL1,ERBB3,ASAP2,TRAF6,AP2M1,PARD6A,NEDD4,IL8RA,IL8RB,BRD8,LDLRAP1,ADRB2,EEA1,KIT,VPS36,TFRC,RNF41
HRAS,OCLN,AMOTL1,CSNK2A1,F11R,CSDA,CGN,MYL5,GNAI1,PPP2R2C,PARD6A,CLDN7,CLDN9,PPP2R2A,CLDN16,MLLT4,TJP3
IQGAP1,CSNK2A1,EGFR,MAPK1,TCF7L1,PVRL4,MLLT4,SMAD3,SNAI1,FYN
CHST3,XYLT2,CHST11,CHST14,CHSY1
HRAS,GNAI1,PAQR7,ACTR3,ACTR2,MAPK1
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
BIOCARTA_AGR_PATHWAY | 36 | 11 | 1.8 | 0.0002 | 0.023 |
KEGG_DRUG_METABOLISM_OTHER_ENZYMES | 51 | 13 | 1.6 | 0.0002 | 0.023 |
BIOCARTA_INTRINSIC_PATHWAY | 23 | 8 | 2 | 0.0005 | 0.034 |
KEGG_NEUROTROPHIN_SIGNALING_PATHWAY | 126 | 23 | 1 | 0.0005 | 0.034 |
BIOCARTA_AMI_PATHWAY | 20 | 7 | 2 | 0.001 | 0.049 |
ITGB1,PXN,CDC42,DMD,PAK1,NRG2,DVL1,LAMA2,MAPK1,PSG1,MAPK3
CYP3A5,IMPDH1,UMPS,UGT2B10,UGT2B15,XDH,TK1,UCK1,UCK2,UGT2B28,UPB1,TPMT,DPYD
F12,F10,COL4A6,COL4A5,PROC,F5,FGA,FGB
MAGED1,BRAF,IRS1,MAPK1,MAPK3,RIPK2,IRAK4,ARHGDIB,PLCG1,ABL1,CDC42,CRKL,ZNF274,CALML3,CAMK2B,CALML5,PIK3R3,YWHAB,RPS6KA3,MAPK12,RPS6KA1,RPS6KA2,YWHAQ
F10,F7,COL4A6,COL4A5,PROC,FGA,FGB
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
KEGG_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P450 | 70 | 8 | 2.2 | 0.0003 | 0.11 |
KEGG_DRUG_METABOLISM_CYTOCHROME_P450 | 72 | 7 | 2 | 0.002 | 0.13 |
KEGG_ECM_RECEPTOR_INTERACTION | 84 | 8 | 1.9 | 0.0012 | 0.13 |
KEGG_ADHERENS_JUNCTION | 75 | 7 | 1.9 | 0.0023 | 0.13 |
KEGG_HYPERTROPHIC_CARDIOMYOPATHY_HCM | 85 | 8 | 1.9 | 0.0011 | 0.13 |
CYP3A4,CYP3A5,CYP3A7,AKR1C3,GSTM4,AKR1C1,ALDH3B2,GSTO1
CYP3A4,CYP3A5,CYP3A7,GSTM4,ALDH3B2,FMO4,GSTO1
SDC2,ITGB3,ITGAV,THBS1,THBS2,COL4A2,COL4A1,ITGA1
ERBB2,PVRL1,RAC2,SORBS1,TGFBR1,SNAI1,FYN
SGCD,ITGB3,TPM1,ITGAV,IL6,ACTC1,ITGA1,CACNA1C
Pathway | Nof Genes | Nof Marker | Enrichment | P value | Q value |
---|---|---|---|---|---|
KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION | 267 | 48 | 1 | 0 | 0 |
KEGG_CELL_ADHESION_MOLECULES_CAMS | 134 | 38 | 1.7 | 0 | 0 |
KEGG_TYPE_I_DIABETES_MELLITUS | 44 | 15 | 2 | 0 | 0 |
KEGG_AUTOIMMUNE_THYROID_DISEASE | 53 | 17 | 2 | 0 | 0 |
KEGG_ALLOGRAFT_REJECTION | 38 | 15 | 2.3 | 0 | 0 |
OSMR,IFNE,CD40,CCR6,CCR2,CX3CR1,PDGFRA,IL1R2,CD70,KDR,FLT3LG,IL20RB,CXCL5,CSF1,CCL21,IL8,CCL11,CCL13,PDGFB,IL15,TGFB1,IL11,TGFB2,CSF3R,IL15RA,PDGFC,C19orf10,IL24,BMPR2,CCL5,EGF,CXCL16,IL22RA2,CXCR4,IFNGR2,LTB,IL18RAP,IFNAR1,AMH,TNFSF13B,NGFR,ACVR1,TNFRSF8,PF4,TNFRSF1A,TNFRSF1B,FLT1,TNFSF4
MPZL1,PTPRM,HLA-A,HLA-C,CD40,HLA-B,HLA-E,HLA-G,HLA-F,PHOX2A,CD34,HLA-DPA1,HLA-DRA,ITGAM,ALCAM,CTLA4,ITGA6,CLDN8,CLDN3,HLA-DMB,HLA-DMA,ESAM,NRXN3,ICAM3,CD86,CD80,CLDN1,CNTN1,VCAN,JAM3,HLA-DQB1,CDH1,CDH5,VCAM1,SELPLG,CD28,SELL,SELE
HLA-DQB1,HLA-DMB,HLA-DMA,CD28,HLA-A,HLA-C,HLA-B,HLA-E,HLA-G,HLA-F,CD86,CD80,HLA-DPA1,HSPD1,HLA-DRA
HLA-DMB,HLA-DMA,HLA-A,HLA-C,HLA-B,CD40,HLA-E,HLA-G,HLA-F,CD86,CD80,HLA-DPA1,HLA-DRA,HLA-DQB1,TSHB,CD28,CTLA4
HLA-DQB1,HLA-DMB,HLA-DMA,CD28,HLA-A,HLA-C,HLA-B,CD40,HLA-E,HLA-G,HLA-F,CD86,CD80,HLA-DPA1,HLA-DRA
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:
-
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.
-
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.