Correlation between gene mutation status and molecular subtypes
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1V40SMS
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/C1V40SMS
Overview
Introduction

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

Summary

Testing the association between mutation status of 38 genes and 10 molecular subtypes across 248 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

  • CTNNB1 mutation correlated to 'MRNA_CNMF',  'CN_CNMF',  'RPPA_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • PIK3R1 mutation correlated to 'METHLYATION_CNMF'.

  • PTEN mutation correlated to 'MRNA_CHIERARCHICAL',  'CN_CNMF',  'METHLYATION_CNMF',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • KRAS mutation correlated to 'MRNA_CHIERARCHICAL'.

  • TP53 mutation correlated to 'MRNA_CNMF',  'MRNA_CHIERARCHICAL',  'CN_CNMF',  'METHLYATION_CNMF',  'RPPA_CNMF',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • CTCF mutation correlated to 'CN_CNMF'.

  • ARID1A mutation correlated to 'CN_CNMF'.

  • SIN3A mutation correlated to 'MIRSEQ_CHIERARCHICAL'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 38 genes and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 26 significant findings detected.

Clinical
Features 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nMutated (%) nWild-Type Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Chi-square test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test
TP53 69 (28%) 179 3.88e-05
(0.0129) 		1.72e-07
(5.84e-05) 		1.05e-28
(3.71e-26) 		1.13e-12
(3.94e-10) 		2.01e-05
(0.00674) 		0.0014
(0.457) 		2.25e-16
(7.92e-14) 		6.8e-15
(2.39e-12) 		3.68e-09
(1.26e-06) 		8.17e-09
(2.79e-06)
PTEN 161 (65%) 87 0.00428
(1.00) 		0.000357
(0.118) 		1.45e-20
(5.11e-18) 		1.43e-12
(4.96e-10) 		0.0257
(1.00) 		0.183
(1.00) 		1.07e-13
(3.76e-11) 		1.87e-12
(6.48e-10) 		1.21e-09
(4.15e-07) 		5.92e-13
(2.07e-10)
CTNNB1 74 (30%) 174 4.9e-07
(0.000166) 		0.00115
(0.378) 		2.57e-05
(0.00861) 		0.00327
(1.00) 		1.29e-10
(4.43e-08) 		0.112
(1.00) 		4.21e-11
(1.45e-08) 		0.0115
(1.00) 		0.0196
(1.00) 		9.13e-06
(0.00308)
PIK3R1 83 (33%) 165 0.0667
(1.00) 		0.0221
(1.00) 		0.00515
(1.00) 		3.22e-05
(0.0108) 		0.649
(1.00) 		0.877
(1.00) 		0.00627
(1.00) 		0.0144
(1.00) 		0.0147
(1.00) 		0.00249
(0.805)
KRAS 53 (21%) 195 0.203
(1.00) 		0.000742
(0.244) 		0.0035
(1.00) 		0.119
(1.00) 		0.297
(1.00) 		0.855
(1.00) 		0.00123
(0.402) 		0.922
(1.00) 		0.0421
(1.00) 		0.209
(1.00)
CTCF 45 (18%) 203 0.149
(1.00) 		0.421
(1.00) 		0.000169
(0.0559) 		0.0481
(1.00) 		0.0784
(1.00) 		0.848
(1.00) 		0.00834
(1.00) 		0.00233
(0.755) 		0.0116
(1.00) 		0.134
(1.00)
ARID1A 83 (33%) 165 0.265
(1.00) 		0.0115
(1.00) 		5.37e-06
(0.00181) 		0.233
(1.00) 		0.0271
(1.00) 		1
(1.00) 		0.0478
(1.00) 		0.00899
(1.00) 		0.0204
(1.00) 		0.144
(1.00)
SIN3A 21 (8%) 227 0.00479
(1.00) 		0.604
(1.00) 		0.00607
(1.00) 		0.129
(1.00) 		0.19
(1.00) 		0.000116
(0.0384) 		0.511
(1.00) 		0.457
(1.00)
PPP2R1A 27 (11%) 221 0.076
(1.00) 		0.0518
(1.00) 		0.0284
(1.00) 		0.0121
(1.00) 		0.141
(1.00) 		0.313
(1.00) 		0.0531
(1.00) 		0.00974
(1.00) 		0.0665
(1.00) 		0.0052
(1.00)
PIK3CA 132 (53%) 116 0.859
(1.00) 		0.203
(1.00) 		0.529
(1.00) 		0.678
(1.00) 		0.366
(1.00) 		0.365
(1.00) 		0.573
(1.00) 		0.523
(1.00) 		0.401
(1.00) 		0.502
(1.00)
PRKAR1B 4 (2%) 244 0.99
(1.00) 		0.509
(1.00) 		0.887
(1.00) 		1
(1.00) 		0.506
(1.00) 		0.116
(1.00) 		0.789
(1.00) 		0.691
(1.00)
RPL22 31 (12%) 217 0.0531
(1.00) 		0.16
(1.00) 		0.0116
(1.00) 		0.00862
(1.00) 		0.0153
(1.00) 		0.26
(1.00) 		0.438
(1.00) 		0.0496
(1.00) 		0.213
(1.00) 		0.901
(1.00)
FBXW7 39 (16%) 209 0.225
(1.00) 		0.692
(1.00) 		0.339
(1.00) 		0.0677
(1.00) 		0.106
(1.00) 		0.107
(1.00) 		0.0442
(1.00) 		0.147
(1.00) 		0.356
(1.00) 		0.0798
(1.00)
SPOP 21 (8%) 227 0.349
(1.00) 		1
(1.00) 		0.909
(1.00) 		0.356
(1.00) 		0.834
(1.00) 		0.415
(1.00) 		0.0337
(1.00) 		0.654
(1.00) 		0.606
(1.00) 		0.799
(1.00)
ARID5B 29 (12%) 219 0.961
(1.00) 		0.459
(1.00) 		0.05
(1.00) 		0.136
(1.00) 		0.164
(1.00) 		0.182
(1.00) 		0.0622
(1.00) 		0.407
(1.00) 		0.342
(1.00) 		0.593
(1.00)
FGFR2 31 (12%) 217 0.385
(1.00) 		0.293
(1.00) 		0.364
(1.00) 		0.897
(1.00) 		0.97
(1.00) 		0.829
(1.00) 		0.911
(1.00) 		0.0492
(1.00) 		0.647
(1.00) 		1
(1.00)
CCND1 15 (6%) 233 0.631
(1.00) 		0.833
(1.00) 		0.124
(1.00) 		0.495
(1.00) 		0.374
(1.00) 		0.338
(1.00) 		0.0595
(1.00) 		0.21
(1.00) 		0.43
(1.00) 		0.757
(1.00)
SMTNL2 9 (4%) 239 0.188
(1.00) 		0.588
(1.00) 		0.603
(1.00) 		1
(1.00) 		0.831
(1.00) 		0.0235
(1.00) 		0.789
(1.00) 		1
(1.00)
NFE2L2 15 (6%) 233 0.0905
(1.00) 		0.833
(1.00) 		0.00201
(0.652) 		0.631
(1.00) 		0.248
(1.00) 		1
(1.00) 		0.538
(1.00) 		0.62
(1.00) 		0.342
(1.00) 		0.593
(1.00)
CHD4 35 (14%) 213 0.0986
(1.00) 		0.284
(1.00) 		0.551
(1.00) 		0.907
(1.00) 		0.97
(1.00) 		0.287
(1.00) 		0.563
(1.00) 		0.698
(1.00) 		0.471
(1.00) 		0.951
(1.00)
RBMX 13 (5%) 235 0.191
(1.00) 		0.18
(1.00) 		0.233
(1.00) 		0.386
(1.00) 		0.0124
(1.00) 		1
(1.00) 		0.0912
(1.00) 		0.106
(1.00) 		0.813
(1.00) 		0.868
(1.00)
FAM9A 14 (6%) 234 0.84
(1.00) 		0.27
(1.00) 		0.178
(1.00) 		0.0227
(1.00) 		0.384
(1.00) 		0.0329
(1.00) 		0.0266
(1.00) 		0.225
(1.00)
MORC4 20 (8%) 228 0.583
(1.00) 		0.18
(1.00) 		0.0651
(1.00) 		0.28
(1.00) 		0.212
(1.00) 		0.0332
(1.00) 		0.341
(1.00) 		0.119
(1.00) 		0.317
(1.00) 		0.562
(1.00)
HPD 7 (3%) 241 0.564
(1.00) 		0.776
(1.00) 		0.447
(1.00) 		0.651
(1.00) 		0.0411
(1.00) 		0.592
(1.00) 		1
(1.00) 		1
(1.00)
CASP8 17 (7%) 231 0.381
(1.00) 		0.0595
(1.00) 		0.119
(1.00) 		0.626
(1.00) 		0.154
(1.00) 		0.269
(1.00) 		0.134
(1.00) 		0.031
(1.00) 		0.464
(1.00) 		1
(1.00)
FOXA2 12 (5%) 236 0.507
(1.00) 		0.795
(1.00) 		0.0719
(1.00) 		0.744
(1.00) 		0.0551
(1.00) 		1
(1.00) 		0.678
(1.00) 		0.778
(1.00)
ABI1 4 (2%) 244 0.821
(1.00) 		0.64
(1.00) 		0.637
(1.00) 		0.67
(1.00) 		0.702
(1.00)
DNER 18 (7%) 230 0.191
(1.00) 		0.0515
(1.00) 		0.00333
(1.00) 		0.597
(1.00) 		0.0217
(1.00) 		0.581
(1.00) 		0.751
(1.00) 		0.0168
(1.00) 		1
(1.00) 		0.881
(1.00)
BCOR 30 (12%) 218 0.687
(1.00) 		0.405
(1.00) 		0.00798
(1.00) 		0.0253
(1.00) 		0.512
(1.00) 		0.5
(1.00) 		0.027
(1.00) 		0.0458
(1.00) 		0.863
(1.00) 		0.44
(1.00)
BRS3 15 (6%) 233 0.536
(1.00) 		0.151
(1.00) 		0.15
(1.00) 		0.519
(1.00) 		0.392
(1.00) 		0.54
(1.00) 		0.143
(1.00) 		0.0329
(1.00) 		0.551
(1.00) 		0.589
(1.00)
NRAS 9 (4%) 239 0.645
(1.00) 		0.316
(1.00) 		1
(1.00) 		0.589
(1.00) 		0.357
(1.00)
SGK1 15 (6%) 233 0.381
(1.00) 		0.0595
(1.00) 		0.0598
(1.00) 		0.625
(1.00) 		0.226
(1.00) 		0.0954
(1.00) 		0.288
(1.00) 		0.601
(1.00) 		0.813
(1.00) 		0.868
(1.00)
TIAL1 11 (4%) 237 0.381
(1.00) 		0.405
(1.00) 		0.303
(1.00) 		0.0634
(1.00) 		0.564
(1.00) 		0.744
(1.00) 		0.551
(1.00) 		0.508
(1.00) 		0.342
(1.00) 		0.725
(1.00)
RPL14 7 (3%) 241 0.902
(1.00) 		0.874
(1.00) 		0.479
(1.00) 		1
(1.00) 		0.343
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
SLC48A1 5 (2%) 243 0.736
(1.00) 		0.639
(1.00) 		0.803
(1.00) 		0.372
(1.00) 		0.886
(1.00) 		0.517
(1.00) 		0.789
(1.00) 		0.691
(1.00)
ZFHX3 44 (18%) 204 0.375
(1.00) 		0.0299
(1.00) 		0.0451
(1.00) 		0.0629
(1.00) 		0.318
(1.00) 		0.179
(1.00) 		0.139
(1.00) 		0.789
(1.00) 		0.536
(1.00) 		0.974
(1.00)
RNF43 12 (5%) 236 0.133
(1.00) 		0.151
(1.00) 		0.215
(1.00) 		0.377
(1.00) 		0.296
(1.00) 		1
(1.00) 		0.128
(1.00) 		0.0688
(1.00) 		0.338
(1.00) 		0.262
(1.00)
ZNF263 8 (3%) 240 0.0242
(1.00) 		0.0595
(1.00) 		0.483
(1.00) 		0.386
(1.00) 		0.611
(1.00) 		1
(1.00) 		0.464
(1.00) 		1
(1.00) 		0.43
(1.00) 		0.589
(1.00)
'CTNNB1 MUTATION STATUS' versus 'MRNA_CNMF'

P value = 4.9e-07 (Fisher's exact test), Q value = 0.00017

Table S1.  Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 12 18 11 10
CTNNB1 MUTATED 0 3 4 10
CTNNB1 WILD-TYPE 12 15 7 0

Figure S1.  Get High-res Image Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

'CTNNB1 MUTATION STATUS' versus 'CN_CNMF'

P value = 2.57e-05 (Chi-square test), Q value = 0.0086

Table S2.  Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 157 5 56 6 10 8
CTNNB1 MUTATED 59 2 2 4 4 1
CTNNB1 WILD-TYPE 98 3 54 2 6 7

Figure S2.  Get High-res Image Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'CTNNB1 MUTATION STATUS' versus 'RPPA_CNMF'

P value = 1.29e-10 (Chi-square test), Q value = 4.4e-08

Table S3.  Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #5: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 39 36 37 10 40 24
CTNNB1 MUTATED 6 10 6 0 32 10
CTNNB1 WILD-TYPE 33 26 31 10 8 14

Figure S3.  Get High-res Image Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #5: 'RPPA_CNMF'

'CTNNB1 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 4.21e-11 (Chi-square test), Q value = 1.5e-08

Table S4.  Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 45 74 24 27 70
CTNNB1 MUTATED 1 13 6 20 31
CTNNB1 WILD-TYPE 44 61 18 7 39

Figure S4.  Get High-res Image Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'CTNNB1 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 9.13e-06 (Fisher's exact test), Q value = 0.0031

Table S5.  Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 22 57 27 10
CTNNB1 MUTATED 2 16 1 8
CTNNB1 WILD-TYPE 20 41 26 2

Figure S5.  Get High-res Image Gene #3: 'CTNNB1 MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'PIK3R1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 3.22e-05 (Fisher's exact test), Q value = 0.011

Table S6.  Gene #4: 'PIK3R1 MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 43 41 51
PIK3R1 MUTATED 5 12 28
PIK3R1 WILD-TYPE 38 29 23

Figure S6.  Get High-res Image Gene #4: 'PIK3R1 MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

'PTEN MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 0.000357 (Fisher's exact test), Q value = 0.12

Table S7.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 17 18 16
PTEN MUTATED 15 14 4
PTEN WILD-TYPE 2 4 12

Figure S7.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'PTEN MUTATION STATUS' versus 'CN_CNMF'

P value = 1.45e-20 (Chi-square test), Q value = 5.1e-18

Table S8.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 157 5 56 6 10 8
PTEN MUTATED 130 2 5 5 7 7
PTEN WILD-TYPE 27 3 51 1 3 1

Figure S8.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'PTEN MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 1.43e-12 (Fisher's exact test), Q value = 5e-10

Table S9.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 43 41 51
PTEN MUTATED 7 30 44
PTEN WILD-TYPE 36 11 7

Figure S9.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

'PTEN MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 1.07e-13 (Chi-square test), Q value = 3.8e-11

Table S10.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 45 74 24 27 70
PTEN MUTATED 9 68 13 18 50
PTEN WILD-TYPE 36 6 11 9 20

Figure S10.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'PTEN MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.87e-12 (Fisher's exact test), Q value = 6.5e-10

Table S11.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 10 136 94
PTEN MUTATED 9 113 36
PTEN WILD-TYPE 1 23 58

Figure S11.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

'PTEN MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 1.21e-09 (Fisher's exact test), Q value = 4.1e-07

Table S12.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #9: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 36 55 25
PTEN MUTATED 10 49 11
PTEN WILD-TYPE 26 6 14

Figure S12.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #9: 'MIRSEQ_MATURE_CNMF'

'PTEN MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 5.92e-13 (Fisher's exact test), Q value = 2.1e-10

Table S13.  Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 22 57 27 10
PTEN MUTATED 6 52 5 7
PTEN WILD-TYPE 16 5 22 3

Figure S13.  Get High-res Image Gene #6: 'PTEN MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'KRAS MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 0.000742 (Fisher's exact test), Q value = 0.24

Table S14.  Gene #8: 'KRAS MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 17 18 16
KRAS MUTATED 9 1 1
KRAS WILD-TYPE 8 17 15

Figure S14.  Get High-res Image Gene #8: 'KRAS MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'MRNA_CNMF'

P value = 3.88e-05 (Fisher's exact test), Q value = 0.013

Table S15.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 12 18 11 10
TP53 MUTATED 2 13 1 0
TP53 WILD-TYPE 10 5 10 10

Figure S15.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

'TP53 MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 1.72e-07 (Fisher's exact test), Q value = 5.8e-05

Table S16.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 17 18 16
TP53 MUTATED 3 0 13
TP53 WILD-TYPE 14 18 3

Figure S16.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 1.05e-28 (Chi-square test), Q value = 3.7e-26

Table S17.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 157 5 56 6 10 8
TP53 MUTATED 11 2 50 0 3 2
TP53 WILD-TYPE 146 3 6 6 7 6

Figure S17.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'TP53 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 1.13e-12 (Fisher's exact test), Q value = 3.9e-10

Table S18.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 43 41 51
TP53 MUTATED 31 4 5
TP53 WILD-TYPE 12 37 46

Figure S18.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #4: 'METHLYATION_CNMF'

'TP53 MUTATION STATUS' versus 'RPPA_CNMF'

P value = 2.01e-05 (Chi-square test), Q value = 0.0067

Table S19.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 39 36 37 10 40 24
TP53 MUTATED 9 19 4 2 2 8
TP53 WILD-TYPE 30 17 33 8 38 16

Figure S19.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'RPPA_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 2.25e-16 (Chi-square test), Q value = 7.9e-14

Table S20.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 45 74 24 27 70
TP53 MUTATED 35 5 7 4 13
TP53 WILD-TYPE 10 69 17 23 57

Figure S20.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6.8e-15 (Fisher's exact test), Q value = 2.4e-12

Table S21.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 10 136 94
TP53 MUTATED 6 10 48
TP53 WILD-TYPE 4 126 46

Figure S21.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 3.68e-09 (Fisher's exact test), Q value = 1.3e-06

Table S22.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #9: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 36 55 25
TP53 MUTATED 25 5 6
TP53 WILD-TYPE 11 50 19

Figure S22.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #9: 'MIRSEQ_MATURE_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 8.17e-09 (Fisher's exact test), Q value = 2.8e-06

Table S23.  Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 22 57 27 10
TP53 MUTATED 9 5 20 2
TP53 WILD-TYPE 13 52 7 8

Figure S23.  Get High-res Image Gene #9: 'TP53 MUTATION STATUS' versus Clinical Feature #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'CTCF MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000169 (Chi-square test), Q value = 0.056

Table S24.  Gene #11: 'CTCF MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 157 5 56 6 10 8
CTCF MUTATED 39 0 0 0 0 3
CTCF WILD-TYPE 118 5 56 6 10 5

Figure S24.  Get High-res Image Gene #11: 'CTCF MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'ARID1A MUTATION STATUS' versus 'CN_CNMF'

P value = 5.37e-06 (Chi-square test), Q value = 0.0018

Table S25.  Gene #12: 'ARID1A MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 157 5 56 6 10 8
ARID1A MUTATED 69 2 4 1 0 4
ARID1A WILD-TYPE 88 3 52 5 10 4

Figure S25.  Get High-res Image Gene #12: 'ARID1A MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'SIN3A MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000116 (Fisher's exact test), Q value = 0.038

Table S26.  Gene #34: 'SIN3A MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 10 136 94
SIN3A MUTATED 4 4 13
SIN3A WILD-TYPE 6 132 81

Figure S26.  Get High-res Image Gene #34: 'SIN3A MUTATION STATUS' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

Methods & Data
Input

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

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

  • Number of patients = 248

  • Number of significantly mutated genes = 38

  • Number of Molecular subtypes = 10

  • 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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[3] 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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