Correlation between gene mutation status and molecular subtypes
Stomach Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1HX19X7
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene mutation status and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1HX19X7
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.

Summary

Testing the association between mutation status of 47 genes and 6 molecular subtypes across 116 patients, 14 significant findings detected with P value < 0.05 and Q value < 0.25.

  • CBWD1 mutation correlated to 'CN_CNMF'.

  • PGM5 mutation correlated to 'CN_CNMF'.

  • TP53 mutation correlated to 'CN_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • PIK3CA mutation correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • ACVR2A mutation correlated to 'CN_CNMF'.

  • ARID1A mutation correlated to 'CN_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • IRF2 mutation correlated to 'CN_CNMF'.

  • RNF43 mutation correlated to 'CN_CNMF'.

  • PHF2 mutation correlated to 'CN_CNMF'.

  • POM121L12 mutation correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 47 genes and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 14 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nMutated (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
PIK3CA 24 (21%) 92 0.000604
(0.15) 		1.59e-06
(0.000411) 		0.412
(1.00) 		0.84
(1.00) 		0.0857
(1.00) 		0.000704
(0.174)
TP53 52 (45%) 64 5.72e-05
(0.0146) 		0.0203
(1.00) 		1
(1.00) 		0.236
(1.00) 		0.00526
(1.00) 		3.69e-05
(0.00947)
ARID1A 22 (19%) 94 7.73e-05
(0.0196) 		0.0145
(1.00) 		0.488
(1.00) 		0.274
(1.00) 		0.00562
(1.00) 		0.000467
(0.116)
CBWD1 14 (12%) 102 0.000115
(0.0289) 		0.0773
(1.00) 		0.457
(1.00) 		0.213
(1.00) 		0.0561
(1.00) 		0.193
(1.00)
PGM5 16 (14%) 100 6.89e-06
(0.00178) 		0.00344
(0.843) 		0.281
(1.00) 		0.157
(1.00) 		0.262
(1.00) 		0.162
(1.00)
ACVR2A 13 (11%) 103 0.000145
(0.0363) 		0.0238
(1.00) 		0.698
(1.00) 		0.424
(1.00) 		0.0246
(1.00) 		0.0563
(1.00)
IRF2 8 (7%) 108 6.38e-05
(0.0162) 		0.0497
(1.00) 		1
(1.00) 		0.279
(1.00) 		0.197
(1.00) 		0.278
(1.00)
RNF43 13 (11%) 103 5.9e-05
(0.015) 		0.0289
(1.00) 		0.698
(1.00) 		0.732
(1.00) 		0.184
(1.00) 		0.0507
(1.00)
PHF2 12 (10%) 104 0.00013
(0.0327) 		0.0238
(1.00) 		0.664
(1.00) 		0.0472
(1.00) 		0.0414
(1.00) 		0.0272
(1.00)
POM121L12 7 (6%) 109 0.000787
(0.194) 		0.253
(1.00) 		1
(1.00) 		0.745
(1.00) 		0.85
(1.00) 		0.309
(1.00)
KRAS 14 (12%) 102 0.107
(1.00) 		0.411
(1.00) 		1
(1.00) 		0.299
(1.00) 		0.271
(1.00) 		0.706
(1.00)
RPL22 9 (8%) 107 0.0234
(1.00) 		0.412
(1.00) 		0.0729
(1.00) 		0.282
(1.00) 		0.28
(1.00)
TRIM48 10 (9%) 106 0.0137
(1.00) 		0.206
(1.00) 		1
(1.00) 		1
(1.00) 		0.103
(1.00) 		0.173
(1.00)
XPOT 6 (5%) 110 0.0136
(1.00) 		0.345
(1.00) 		1
(1.00) 		0.327
(1.00) 		0.0539
(1.00)
RHOA 7 (6%) 109 0.146
(1.00) 		0.851
(1.00) 		0.488
(1.00) 		0.383
(1.00) 		0.683
(1.00)
OR8H3 10 (9%) 106 0.611
(1.00) 		0.0907
(1.00) 		0.108
(1.00) 		0.101
(1.00) 		0.873
(1.00) 		0.205
(1.00)
EDNRB 12 (10%) 104 0.33
(1.00) 		0.545
(1.00) 		0.412
(1.00) 		0.84
(1.00) 		0.405
(1.00) 		0.162
(1.00)
ZNF804B 18 (16%) 98 0.202
(1.00) 		0.0568
(1.00) 		0.281
(1.00) 		0.885
(1.00) 		0.177
(1.00) 		0.209
(1.00)
IAPP 4 (3%) 112 0.385
(1.00) 		1
(1.00) 		0.131
(1.00) 		0.569
(1.00)
PCDH15 22 (19%) 94 0.766
(1.00) 		0.916
(1.00) 		0.721
(1.00) 		0.885
(1.00) 		0.71
(1.00) 		0.952
(1.00)
SPRYD5 8 (7%) 108 0.166
(1.00) 		0.05
(1.00) 		1
(1.00) 		0.643
(1.00) 		0.307
(1.00) 		0.805
(1.00)
TUSC3 9 (8%) 107 0.237
(1.00) 		0.547
(1.00) 		0.488
(1.00) 		1
(1.00) 		0.815
(1.00)
FGF22 3 (3%) 113 0.0354
(1.00) 		1
(1.00) 		1
(1.00) 		0.324
(1.00)
HLA-B 9 (8%) 107 0.0491
(1.00) 		0.00377
(0.92) 		0.607
(1.00) 		1
(1.00) 		0.869
(1.00) 		0.666
(1.00)
PTH2 3 (3%) 113 1
(1.00) 		0.125
(1.00) 		0.143
(1.00) 		0.8
(1.00)
C17ORF63 3 (3%) 113 0.759
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
SMAD4 7 (6%) 109 0.406
(1.00) 		0.741
(1.00) 		1
(1.00) 		0.745
(1.00) 		0.85
(1.00) 		1
(1.00)
POTEG 6 (5%) 110 0.183
(1.00) 		0.556
(1.00) 		1
(1.00) 		1
(1.00) 		0.662
(1.00) 		0.36
(1.00)
WBSCR17 12 (10%) 104 0.0529
(1.00) 		0.00743
(1.00) 		0.607
(1.00) 		0.643
(1.00) 		0.241
(1.00) 		0.451
(1.00)
TPTE 14 (12%) 102 0.868
(1.00) 		0.895
(1.00) 		0.412
(1.00) 		0.84
(1.00) 		0.212
(1.00) 		0.498
(1.00)
CDH1 11 (9%) 105 0.112
(1.00) 		0.531
(1.00) 		0.607
(1.00) 		0.745
(1.00) 		0.0812
(1.00) 		0.0936
(1.00)
CPS1 13 (11%) 103 0.447
(1.00) 		0.296
(1.00) 		1
(1.00) 		0.863
(1.00) 		0.902
(1.00) 		0.132
(1.00)
INO80E 5 (4%) 111 0.25
(1.00) 		0.607
(1.00) 		0.279
(1.00) 		0.348
(1.00) 		1
(1.00)
ELF3 5 (4%) 111 0.0484
(1.00) 		0.227
(1.00) 		1
(1.00) 		0.622
(1.00) 		0.077
(1.00)
PARK2 9 (8%) 107 0.0755
(1.00) 		0.0388
(1.00) 		1
(1.00) 		0.45
(1.00) 		0.869
(1.00) 		0.28
(1.00)
LARP4B 5 (4%) 111 0.0132
(1.00) 		0.206
(1.00) 		1
(1.00) 		0.622
(1.00) 		0.077
(1.00)
OR6K3 6 (5%) 110 0.0756
(1.00) 		0.472
(1.00) 		1
(1.00) 		0.387
(1.00) 		0.522
(1.00) 		0.868
(1.00)
TM7SF4 7 (6%) 109 0.146
(1.00) 		0.296
(1.00) 		0.488
(1.00) 		0.85
(1.00) 		0.267
(1.00)
UPF3A 6 (5%) 110 0.22
(1.00) 		0.206
(1.00) 		0.607
(1.00) 		0.745
(1.00) 		0.522
(1.00) 		0.222
(1.00)
C7ORF63 5 (4%) 111 0.0132
(1.00) 		1
(1.00) 		1
(1.00) 		0.622
(1.00) 		0.507
(1.00)
KDM4B 10 (9%) 106 0.00512
(1.00) 		0.05
(1.00) 		0.345
(1.00) 		0.45
(1.00) 		0.873
(1.00) 		0.627
(1.00)
KIAA0748 7 (6%) 109 0.344
(1.00) 		0.507
(1.00) 		1
(1.00) 		0.256
(1.00) 		0.599
(1.00)
OR8B4 3 (3%) 113 0.407
(1.00) 		0.00894
(1.00) 		1
(1.00) 		0.604
(1.00)
RASA1 9 (8%) 107 0.0654
(1.00) 		0.355
(1.00) 		0.664
(1.00) 		0.73
(1.00) 		0.175
(1.00) 		0.495
(1.00)
SLITRK6 10 (9%) 106 0.553
(1.00) 		0.934
(1.00) 		0.108
(1.00) 		0.745
(1.00) 		0.174
(1.00) 		0.835
(1.00)
TP53TG5 4 (3%) 112 0.12
(1.00) 		1
(1.00) 		1
(1.00) 		0.808
(1.00)
LHCGR 7 (6%) 109 0.76
(1.00) 		0.815
(1.00) 		0.488
(1.00) 		0.709
(1.00) 		0.267
(1.00)
'CBWD1 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000115 (Fisher's exact test), Q value = 0.029

Table S1.  Gene #1: 'CBWD1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
CBWD1 MUTATED 8 1 5
CBWD1 WILD-TYPE 12 54 35

Figure S1.  Get High-res Image Gene #1: 'CBWD1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'PGM5 MUTATION STATUS' versus 'CN_CNMF'

P value = 6.89e-06 (Fisher's exact test), Q value = 0.0018

Table S2.  Gene #3: 'PGM5 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
PGM5 MUTATED 10 2 4
PGM5 WILD-TYPE 10 53 36

Figure S2.  Get High-res Image Gene #3: 'PGM5 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 5.72e-05 (Fisher's exact test), Q value = 0.015

Table S3.  Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
TP53 MUTATED 4 36 11
TP53 WILD-TYPE 16 19 29

Figure S3.  Get High-res Image Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 3.69e-05 (Fisher's exact test), Q value = 0.0095

Table S4.  Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 56 32
TP53 MUTATED 22 20 9
TP53 WILD-TYPE 5 36 23

Figure S4.  Get High-res Image Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'PIK3CA MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000604 (Fisher's exact test), Q value = 0.15

Table S5.  Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
PIK3CA MUTATED 9 4 11
PIK3CA WILD-TYPE 11 51 29

Figure S5.  Get High-res Image Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'PIK3CA MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 1.59e-06 (Fisher's exact test), Q value = 0.00041

Table S6.  Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 9 14 25 20
PIK3CA MUTATED 9 4 3 2
PIK3CA WILD-TYPE 0 10 22 18

Figure S6.  Get High-res Image Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'PIK3CA MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000704 (Fisher's exact test), Q value = 0.17

Table S7.  Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 56 32
PIK3CA MUTATED 2 20 2
PIK3CA WILD-TYPE 25 36 30

Figure S7.  Get High-res Image Gene #8: 'PIK3CA MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'ACVR2A MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000145 (Fisher's exact test), Q value = 0.036

Table S8.  Gene #9: 'ACVR2A MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
ACVR2A MUTATED 4 0 9
ACVR2A WILD-TYPE 16 55 31

Figure S8.  Get High-res Image Gene #9: 'ACVR2A MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'ARID1A MUTATION STATUS' versus 'CN_CNMF'

P value = 7.73e-05 (Fisher's exact test), Q value = 0.02

Table S9.  Gene #11: 'ARID1A MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
ARID1A MUTATED 10 3 9
ARID1A WILD-TYPE 10 52 31

Figure S9.  Get High-res Image Gene #11: 'ARID1A MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'ARID1A MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000467 (Fisher's exact test), Q value = 0.12

Table S10.  Gene #11: 'ARID1A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 56 32
ARID1A MUTATED 0 18 4
ARID1A WILD-TYPE 27 38 28

Figure S10.  Get High-res Image Gene #11: 'ARID1A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'IRF2 MUTATION STATUS' versus 'CN_CNMF'

P value = 6.38e-05 (Fisher's exact test), Q value = 0.016

Table S11.  Gene #15: 'IRF2 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
IRF2 MUTATED 6 0 2
IRF2 WILD-TYPE 14 55 38

Figure S11.  Get High-res Image Gene #15: 'IRF2 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'RNF43 MUTATION STATUS' versus 'CN_CNMF'

P value = 5.9e-05 (Fisher's exact test), Q value = 0.015

Table S12.  Gene #26: 'RNF43 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
RNF43 MUTATED 8 1 4
RNF43 WILD-TYPE 12 54 36

Figure S12.  Get High-res Image Gene #26: 'RNF43 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'PHF2 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.00013 (Fisher's exact test), Q value = 0.033

Table S13.  Gene #28: 'PHF2 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
PHF2 MUTATED 6 0 6
PHF2 WILD-TYPE 14 55 34

Figure S13.  Get High-res Image Gene #28: 'PHF2 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'POM121L12 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000787 (Fisher's exact test), Q value = 0.19

Table S14.  Gene #43: 'POM121L12 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 55 40
POM121L12 MUTATED 0 0 7
POM121L12 WILD-TYPE 20 55 33

Figure S14.  Get High-res Image Gene #43: 'POM121L12 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

  • Mutation data file = STAD-TP.mutsig.cluster.txt

  • Molecular subtypes file = STAD-TP.transferedmergedcluster.txt

  • Number of patients = 116

  • Number of significantly mutated genes = 47

  • Number of Molecular subtypes = 6

  • Exclude genes that fewer than K tumors have mutations, K = 3

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[2] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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