Correlation between gene mutation status and selected clinical features
Prostate Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1GX4B1T
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 44 genes and 11 clinical features across 498 patients, 6 significant findings detected with Q value < 0.25.

  • TP53 mutation correlated to 'PATHOLOGY_T_STAGE',  'PATHOLOGY_N_STAGE',  'NUMBER_OF_LYMPH_NODES', and 'GLEASON_SCORE'.

  • ZMYM3 mutation correlated to 'GLEASON_SCORE'.

  • ZFP36L2 mutation correlated to 'Time to Death'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 44 genes and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 6 significant findings detected.

Clinical
Features
Time
to
Death
YEARS
TO
BIRTH
PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
RADIATION
THERAPY
HISTOLOGICAL
TYPE
RESIDUAL
TUMOR
NUMBER
OF
LYMPH
NODES
GLEASON
SCORE
PSA
VALUE
RACE
nMutated (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Wilcoxon-test Wilcoxon-test Wilcoxon-test Fisher's exact test
TP53 57 (11%) 441 0.294
(1.00)
0.883
(1.00)
0.00309
(0.249)
0.0029
(0.249)
0.191
(1.00)
0.686
(1.00)
0.0103
(0.623)
0.000136
(0.0219)
1.97e-09
(9.55e-07)
0.0284
(0.888)
1
(1.00)
ZMYM3 12 (2%) 486 0.445
(1.00)
0.126
(1.00)
0.0725
(1.00)
0.248
(1.00)
0.129
(1.00)
1
(1.00)
0.0799
(1.00)
0.213
(1.00)
0.00304
(0.249)
0.453
(1.00)
1
(1.00)
ZFP36L2 4 (1%) 494 7.89e-05
(0.0191)
0.63
(1.00)
0.224
(1.00)
0.562
(1.00)
0.342
(1.00)
1
(1.00)
0.657
(1.00)
0.644
(1.00)
0.728
(1.00)
0.133
(1.00)
SPOP 57 (11%) 441 0.798
(1.00)
0.349
(1.00)
0.348
(1.00)
0.123
(1.00)
1
(1.00)
0.686
(1.00)
0.128
(1.00)
0.0867
(1.00)
0.903
(1.00)
0.208
(1.00)
0.553
(1.00)
PTEN 17 (3%) 481 0.619
(1.00)
0.524
(1.00)
1
(1.00)
0.747
(1.00)
1
(1.00)
0.411
(1.00)
0.612
(1.00)
0.495
(1.00)
0.362
(1.00)
0.0127
(0.682)
1
(1.00)
NUDT11 11 (2%) 487 0.688
(1.00)
0.0964
(1.00)
0.452
(1.00)
0.404
(1.00)
0.161
(1.00)
1
(1.00)
0.584
(1.00)
0.371
(1.00)
0.476
(1.00)
0.651
(1.00)
1
(1.00)
MLL2 29 (6%) 469 0.444
(1.00)
0.185
(1.00)
0.0792
(1.00)
1
(1.00)
0.762
(1.00)
0.599
(1.00)
0.908
(1.00)
0.997
(1.00)
0.0211
(0.786)
0.222
(1.00)
1
(1.00)
CTNNB1 13 (3%) 485 0.456
(1.00)
0.423
(1.00)
0.678
(1.00)
0.134
(1.00)
1
(1.00)
0.331
(1.00)
0.2
(1.00)
0.0847
(1.00)
0.197
(1.00)
0.992
(1.00)
1
(1.00)
PIK3CA 14 (3%) 484 0.431
(1.00)
0.133
(1.00)
0.453
(1.00)
0.698
(1.00)
1
(1.00)
0.352
(1.00)
0.00674
(0.466)
0.342
(1.00)
0.0197
(0.786)
0.309
(1.00)
1
(1.00)
KDM6A 13 (3%) 485 0.681
(1.00)
0.145
(1.00)
0.0838
(1.00)
0.477
(1.00)
0.38
(1.00)
1
(1.00)
0.0951
(1.00)
0.249
(1.00)
0.529
(1.00)
0.454
(1.00)
1
(1.00)
FOXA1 28 (6%) 470 0.378
(1.00)
0.193
(1.00)
0.914
(1.00)
0.0952
(1.00)
0.745
(1.00)
0.586
(1.00)
0.73
(1.00)
0.0982
(1.00)
0.962
(1.00)
0.411
(1.00)
0.0539
(1.00)
MLL3 29 (6%) 469 0.133
(1.00)
0.791
(1.00)
0.434
(1.00)
1
(1.00)
0.0628
(1.00)
0.599
(1.00)
0.728
(1.00)
0.69
(1.00)
0.175
(1.00)
0.405
(1.00)
1
(1.00)
GAGE2A 5 (1%) 493 0.84
(1.00)
0.518
(1.00)
0.441
(1.00)
1
(1.00)
0.503
(1.00)
1
(1.00)
0.722
(1.00)
0.325
(1.00)
0.911
(1.00)
0.544
(1.00)
TNRC18 9 (2%) 489 0.476
(1.00)
0.264
(1.00)
0.286
(1.00)
0.646
(1.00)
0.0725
(1.00)
1
(1.00)
0.371
(1.00)
0.658
(1.00)
0.243
(1.00)
0.368
(1.00)
AGAP6 5 (1%) 493 0.783
(1.00)
0.929
(1.00)
0.108
(1.00)
0.589
(1.00)
0.503
(1.00)
0.142
(1.00)
0.238
(1.00)
0.271
(1.00)
0.151
(1.00)
0.548
(1.00)
IDH1 6 (1%) 492 0.667
(1.00)
0.315
(1.00)
0.477
(1.00)
1
(1.00)
0.568
(1.00)
1
(1.00)
0.0537
(1.00)
0.787
(1.00)
0.017
(0.786)
0.526
(1.00)
GATA6 4 (1%) 494 0.837
(1.00)
0.324
(1.00)
0.672
(1.00)
0.562
(1.00)
0.428
(1.00)
1
(1.00)
1
(1.00)
0.737
(1.00)
0.728
(1.00)
0.0385
(0.888)
SMG7 8 (2%) 490 0.645
(1.00)
0.0879
(1.00)
0.287
(1.00)
0.361
(1.00)
0.602
(1.00)
1
(1.00)
1
(1.00)
0.162
(1.00)
0.939
(1.00)
0.271
(1.00)
1
(1.00)
CNTNAP1 9 (2%) 489 0.791
(1.00)
0.21
(1.00)
1
(1.00)
0.619
(1.00)
0.279
(1.00)
0.242
(1.00)
0.227
(1.00)
0.573
(1.00)
0.233
(1.00)
0.278
(1.00)
CDKN1B 6 (1%) 492 0.689
(1.00)
0.316
(1.00)
0.109
(1.00)
1
(1.00)
0.568
(1.00)
1
(1.00)
0.0723
(1.00)
0.941
(1.00)
0.897
(1.00)
0.811
(1.00)
1
(1.00)
EOMES 5 (1%) 493 0.488
(1.00)
0.483
(1.00)
0.106
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.46
(1.00)
0.325
(1.00)
0.902
(1.00)
0.282
(1.00)
NBPF1 9 (2%) 489 0.719
(1.00)
0.404
(1.00)
0.114
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.0835
(1.00)
0.763
(1.00)
0.0383
(0.888)
0.637
(1.00)
1
(1.00)
LMOD2 6 (1%) 492 0.831
(1.00)
0.699
(1.00)
0.717
(1.00)
1
(1.00)
0.503
(1.00)
1
(1.00)
1
(1.00)
0.941
(1.00)
0.859
(1.00)
0.0904
(1.00)
EHHADH 5 (1%) 493 0.708
(1.00)
0.431
(1.00)
0.686
(1.00)
1
(1.00)
0.128
(1.00)
1
(1.00)
0.721
(1.00)
0.941
(1.00)
0.57
(1.00)
0.746
(1.00)
MED12 8 (2%) 490 0.737
(1.00)
0.377
(1.00)
0.761
(1.00)
0.619
(1.00)
1
(1.00)
1
(1.00)
0.112
(1.00)
0.49
(1.00)
0.304
(1.00)
0.93
(1.00)
1
(1.00)
ZNF709 5 (1%) 493 0.708
(1.00)
0.459
(1.00)
0.244
(1.00)
0.589
(1.00)
0.128
(1.00)
1
(1.00)
0.22
(1.00)
0.271
(1.00)
0.212
(1.00)
0.468
(1.00)
TCEB3 4 (1%) 494 0.871
(1.00)
0.384
(1.00)
1
(1.00)
0.461
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.641
(1.00)
0.467
(1.00)
0.931
(1.00)
MED15 7 (1%) 491 0.718
(1.00)
0.193
(1.00)
1
(1.00)
0.357
(1.00)
0.568
(1.00)
1
(1.00)
0.764
(1.00)
0.191
(1.00)
0.212
(1.00)
0.149
(1.00)
0.164
(1.00)
ERF 5 (1%) 493 0.72
(1.00)
0.302
(1.00)
0.105
(1.00)
0.589
(1.00)
0.503
(1.00)
1
(1.00)
0.459
(1.00)
0.325
(1.00)
0.0758
(1.00)
0.721
(1.00)
ERN1 4 (1%) 494 0.78
(1.00)
0.283
(1.00)
0.675
(1.00)
0.562
(1.00)
1
(1.00)
1
(1.00)
0.238
(1.00)
0.875
(1.00)
0.812
(1.00)
0.37
(1.00)
MLLT10 5 (1%) 493 0.766
(1.00)
0.498
(1.00)
1
(1.00)
0.589
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.271
(1.00)
0.704
(1.00)
0.218
(1.00)
1
(1.00)
ZFHX3 16 (3%) 482 0.641
(1.00)
0.198
(1.00)
1
(1.00)
0.716
(1.00)
0.706
(1.00)
0.392
(1.00)
0.354
(1.00)
0.71
(1.00)
0.0366
(0.888)
0.634
(1.00)
0.26
(1.00)
FMN1 4 (1%) 494 0.78
(1.00)
0.234
(1.00)
0.0668
(1.00)
0.562
(1.00)
0.0838
(1.00)
1
(1.00)
0.659
(1.00)
0.633
(1.00)
0.467
(1.00)
0.0266
(0.888)
AKT1 3 (1%) 495 0.841
(1.00)
0.998
(1.00)
0.586
(1.00)
0.461
(1.00)
0.342
(1.00)
1
(1.00)
1
(1.00)
0.641
(1.00)
0.944
(1.00)
0.908
(1.00)
ATM 22 (4%) 476 0.324
(1.00)
0.563
(1.00)
0.073
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.0772
(1.00)
0.841
(1.00)
0.314
(1.00)
0.804
(1.00)
0.347
(1.00)
STRC 5 (1%) 493 0.802
(1.00)
0.515
(1.00)
0.243
(1.00)
0.159
(1.00)
1
(1.00)
1
(1.00)
0.22
(1.00)
0.12
(1.00)
0.212
(1.00)
0.468
(1.00)
APC 10 (2%) 488 0.179
(1.00)
0.607
(1.00)
0.577
(1.00)
1
(1.00)
0.613
(1.00)
1
(1.00)
0.164
(1.00)
0.559
(1.00)
0.0377
(0.888)
0.767
(1.00)
MYOT 5 (1%) 493 0.725
(1.00)
0.019
(0.786)
0.244
(1.00)
0.562
(1.00)
1
(1.00)
0.142
(1.00)
0.22
(1.00)
0.875
(1.00)
0.0344
(0.888)
0.409
(1.00)
KIRREL 6 (1%) 492 0.725
(1.00)
0.736
(1.00)
0.721
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.742
(1.00)
0.884
(1.00)
0.605
(1.00)
0.453
(1.00)
1
(1.00)
PGBD2 3 (1%) 495 0.752
(1.00)
0.032
(0.888)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.395
(1.00)
0.0619
(1.00)
0.897
(1.00)
LOC100132247 3 (1%) 495 0.887
(1.00)
0.45
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.0878
(1.00)
0.605
(1.00)
0.944
(1.00)
0.788
(1.00)
EMG1 4 (1%) 494 0.469
(1.00)
0.736
(1.00)
0.672
(1.00)
1
(1.00)
1
(1.00)
0.115
(1.00)
0.421
(1.00)
0.325
(1.00)
0.977
(1.00)
0.295
(1.00)
CDH16 4 (1%) 494 0.811
(1.00)
0.932
(1.00)
0.226
(1.00)
1
(1.00)
0.428
(1.00)
1
(1.00)
0.42
(1.00)
0.395
(1.00)
0.188
(1.00)
0.439
(1.00)
KRT25 6 (1%) 492 0.829
(1.00)
0.407
(1.00)
0.477
(1.00)
0.233
(1.00)
0.177
(1.00)
1
(1.00)
0.46
(1.00)
0.268
(1.00)
0.147
(1.00)
0.645
(1.00)
1
(1.00)
'TP53 MUTATION STATUS' versus 'PATHOLOGY_T_STAGE'

P value = 0.00309 (Fisher's exact test), Q value = 0.25

Table S1.  Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'PATHOLOGY_T_STAGE'

nPatients T2 T3 T4
ALL 188 293 10
TP53 MUTATED 11 44 2
TP53 WILD-TYPE 177 249 8

Figure S1.  Get High-res Image Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'PATHOLOGY_T_STAGE'

'TP53 MUTATION STATUS' versus 'PATHOLOGY_N_STAGE'

P value = 0.0029 (Fisher's exact test), Q value = 0.25

Table S2.  Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY_N_STAGE'

nPatients 0 1
ALL 346 79
TP53 MUTATED 37 19
TP53 WILD-TYPE 309 60

Figure S2.  Get High-res Image Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY_N_STAGE'

'TP53 MUTATION STATUS' versus 'NUMBER_OF_LYMPH_NODES'

P value = 0.000136 (Wilcoxon-test), Q value = 0.022

Table S3.  Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #8: 'NUMBER_OF_LYMPH_NODES'

nPatients Mean (Std.Dev)
ALL 407 0.4 (1.4)
TP53 MUTATED 53 1.2 (2.3)
TP53 WILD-TYPE 354 0.3 (1.1)

Figure S3.  Get High-res Image Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #8: 'NUMBER_OF_LYMPH_NODES'

'TP53 MUTATION STATUS' versus 'GLEASON_SCORE'

P value = 1.97e-09 (Wilcoxon-test), Q value = 9.5e-07

Table S4.  Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #9: 'GLEASON_SCORE'

nPatients Mean (Std.Dev)
ALL 498 7.6 (1.0)
TP53 MUTATED 57 8.4 (0.9)
TP53 WILD-TYPE 441 7.5 (1.0)

Figure S4.  Get High-res Image Gene #2: 'TP53 MUTATION STATUS' versus Clinical Feature #9: 'GLEASON_SCORE'

'ZMYM3 MUTATION STATUS' versus 'GLEASON_SCORE'

P value = 0.00304 (Wilcoxon-test), Q value = 0.25

Table S5.  Gene #31: 'ZMYM3 MUTATION STATUS' versus Clinical Feature #9: 'GLEASON_SCORE'

nPatients Mean (Std.Dev)
ALL 498 7.6 (1.0)
ZMYM3 MUTATED 12 8.5 (0.9)
ZMYM3 WILD-TYPE 486 7.6 (1.0)

Figure S5.  Get High-res Image Gene #31: 'ZMYM3 MUTATION STATUS' versus Clinical Feature #9: 'GLEASON_SCORE'

'ZFP36L2 MUTATION STATUS' versus 'Time to Death'

P value = 7.89e-05 (logrank test), Q value = 0.019

Table S6.  Gene #37: 'ZFP36L2 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 498 10 0.8 - 165.2 (30.4)
ZFP36L2 MUTATED 4 1 25.9 - 49.9 (33.0)
ZFP36L2 WILD-TYPE 494 9 0.8 - 165.2 (30.4)

Figure S6.  Get High-res Image Gene #37: 'ZFP36L2 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

Methods & Data
Input
  • Mutation data file = sample_sig_gene_table.txt from Mutsig_2CV pipeline

  • Processed Mutation data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/PRAD-TP/22592901/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/PRAD-TP/22506989/PRAD-TP.merged_data.txt

  • Number of patients = 498

  • Number of significantly mutated genes = 44

  • Number of selected clinical features = 11

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

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

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

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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] 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)
[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)