Correlation between copy number variations of arm-level result and selected clinical features
Prostate Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
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 (2014): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C18S4NCS
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 57 arm-level events and 14 clinical features across 184 patients, 23 significant findings detected with Q value < 0.25.

  • 4q gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.

  • 5p gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.

  • 9p gain cnv correlated to 'PSA_VALUE'.

  • 9q gain cnv correlated to 'PSA_VALUE'.

  • 12q gain cnv correlated to 'GLEASON_SCORE_PRIMARY' and 'PSA_VALUE'.

  • 17q gain cnv correlated to 'PSA_VALUE'.

  • 18p gain cnv correlated to 'PSA_VALUE'.

  • 18q gain cnv correlated to 'PSA_VALUE'.

  • 19q gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.

  • 20q gain cnv correlated to 'GLEASON_SCORE_PRIMARY' and 'PSA_VALUE'.

  • 21q gain cnv correlated to 'GLEASON_SCORE_PRIMARY'.

  • 4p loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.

  • 4q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.

  • 6p loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.

  • 9p loss cnv correlated to 'PSA_VALUE'.

  • 12q loss cnv correlated to 'PSA_VALUE'.

  • 17q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.

  • 18q loss cnv correlated to 'GLEASON_SCORE'.

  • 19p loss cnv correlated to 'PSA_RESULT_PREOP'.

  • 19q loss cnv correlated to 'PSA_RESULT_PREOP'.

  • 20q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 57 arm-level events and 14 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 23 significant findings detected.

Clinical
Features
Time
to
Death
AGE PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
COMPLETENESS
OF
RESECTION
NUMBER
OF
LYMPH
NODES
GLEASON
SCORE
COMBINED
GLEASON
SCORE
PRIMARY
GLEASON
SCORE
SECONDARY
GLEASON
SCORE
PSA
RESULT
PREOP
DAYS
TO
PREOP
PSA
PSA
VALUE
DAYS
TO
PSA
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Fisher's exact test t-test t-test t-test t-test t-test t-test t-test t-test t-test
12q gain 3 (2%) 181 100
(1.00)
0.182
(1.00)
1
(1.00)
0.286
(1.00)
0.546
(1.00)
0.703
(1.00)
0.858
(1.00)
1.76e-26
(1.37e-23)
0.295
(1.00)
0.95
(1.00)
0.103
(1.00)
0.177
(1.00)
0.000125
(0.0966)
0.327
(1.00)
20q gain 5 (3%) 179 100
(1.00)
0.0618
(1.00)
0.0219
(1.00)
1
(1.00)
0.355
(1.00)
0.000785
(0.594)
0.327
(1.00)
1.37e-26
(1.08e-23)
0.99
(1.00)
0.135
(1.00)
0.492
(1.00)
0.62
(1.00)
0.000273
(0.209)
0.0846
(1.00)
4q gain 3 (2%) 181 100
(1.00)
0.241
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.000787
(0.594)
0.858
(1.00)
0.713
(1.00)
8.13e-06
(0.00633)
0.95
(1.00)
0.935
(1.00)
0.662
(1.00)
0.000884
(0.659)
0.156
(1.00)
5p gain 3 (2%) 181 100
(1.00)
0.719
(1.00)
0.313
(1.00)
0.286
(1.00)
0.164
(1.00)
0.703
(1.00)
0.245
(1.00)
0.32
(1.00)
8.13e-06
(0.00633)
0.0498
(1.00)
0.43
(1.00)
0.897
(1.00)
9p gain 7 (4%) 177 100
(1.00)
0.212
(1.00)
0.557
(1.00)
0.0265
(1.00)
0.65
(1.00)
0.231
(1.00)
0.596
(1.00)
0.636
(1.00)
0.811
(1.00)
0.196
(1.00)
0.181
(1.00)
0.439
(1.00)
0.00018
(0.139)
0.778
(1.00)
9q gain 14 (8%) 170 100
(1.00)
0.393
(1.00)
0.0324
(1.00)
0.0055
(1.00)
0.334
(1.00)
0.143
(1.00)
0.0385
(1.00)
0.0111
(1.00)
0.477
(1.00)
0.0388
(1.00)
0.1
(1.00)
0.267
(1.00)
0.000249
(0.192)
0.847
(1.00)
17q gain 4 (2%) 180 100
(1.00)
0.631
(1.00)
0.22
(1.00)
0.0556
(1.00)
0.607
(1.00)
0.316
(1.00)
0.472
(1.00)
0.341
(1.00)
0.872
(1.00)
0.418
(1.00)
0.749
(1.00)
0.591
(1.00)
0.000225
(0.174)
0.024
(1.00)
18p gain 7 (4%) 177 100
(1.00)
0.371
(1.00)
0.286
(1.00)
0.122
(1.00)
1
(1.00)
0.518
(1.00)
0.596
(1.00)
0.831
(1.00)
0.37
(1.00)
0.402
(1.00)
0.914
(1.00)
0.359
(1.00)
0.000202
(0.156)
0.796
(1.00)
18q gain 3 (2%) 181 100
(1.00)
0.332
(1.00)
0.313
(1.00)
1
(1.00)
1
(1.00)
0.000787
(0.594)
0.604
(1.00)
0.615
(1.00)
0.751
(1.00)
0.641
(1.00)
0.0329
(1.00)
0.368
(1.00)
0.000281
(0.215)
0.887
(1.00)
19q gain 3 (2%) 181 100
(1.00)
0.876
(1.00)
0.0413
(1.00)
0.286
(1.00)
0.546
(1.00)
0.703
(1.00)
0.0219
(1.00)
0.117
(1.00)
6.74e-67
(5.31e-64)
0.0226
(1.00)
0.546
(1.00)
0.8
(1.00)
0.99
(1.00)
0.416
(1.00)
21q gain 3 (2%) 181 100
(1.00)
0.0813
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.000787
(0.594)
0.245
(1.00)
1.76e-26
(1.37e-23)
0.497
(1.00)
0.258
(1.00)
0.0349
(1.00)
0.308
(1.00)
0.000485
(0.369)
0.393
(1.00)
4p loss 4 (2%) 180 100
(1.00)
0.886
(1.00)
0.667
(1.00)
0.00372
(1.00)
0.164
(1.00)
0.122
(1.00)
0.00728
(1.00)
1.55e-26
(1.22e-23)
0.0277
(1.00)
0.00782
(1.00)
0.302
(1.00)
0.722
(1.00)
4q loss 3 (2%) 181 100
(1.00)
0.77
(1.00)
1
(1.00)
0.286
(1.00)
0.703
(1.00)
0.0471
(1.00)
1.76e-26
(1.37e-23)
0.114
(1.00)
0.0498
(1.00)
0.496
(1.00)
0.276
(1.00)
6p loss 7 (4%) 177 100
(1.00)
0.122
(1.00)
0.167
(1.00)
0.0265
(1.00)
0.65
(1.00)
0.179
(1.00)
0.157
(1.00)
1.06e-26
(8.33e-24)
0.785
(1.00)
0.0437
(1.00)
0.233
(1.00)
0.505
(1.00)
0.363
(1.00)
0.661
(1.00)
9p loss 8 (4%) 176 100
(1.00)
0.896
(1.00)
0.0591
(1.00)
0.0396
(1.00)
1
(1.00)
0.266
(1.00)
0.0592
(1.00)
0.0224
(1.00)
0.282
(1.00)
0.0487
(1.00)
0.457
(1.00)
0.668
(1.00)
0.000256
(0.197)
0.723
(1.00)
12q loss 7 (4%) 177 100
(1.00)
0.199
(1.00)
0.219
(1.00)
0.161
(1.00)
1
(1.00)
0.615
(1.00)
0.17
(1.00)
0.179
(1.00)
0.329
(1.00)
0.109
(1.00)
0.873
(1.00)
0.612
(1.00)
0.00027
(0.207)
0.67
(1.00)
17q loss 4 (2%) 180 100
(1.00)
0.206
(1.00)
0.667
(1.00)
0.363
(1.00)
0.259
(1.00)
0.821
(1.00)
0.126
(1.00)
1.55e-26
(1.22e-23)
0.402
(1.00)
0.138
(1.00)
0.6
(1.00)
0.234
(1.00)
0.982
(1.00)
0.958
(1.00)
18q loss 35 (19%) 149 100
(1.00)
0.631
(1.00)
0.211
(1.00)
0.0237
(1.00)
0.0705
(1.00)
0.171
(1.00)
0.00124
(0.926)
0.0473
(1.00)
0.000697
(0.529)
0.000259
(0.199)
0.139
(1.00)
0.979
(1.00)
0.388
(1.00)
0.202
(1.00)
19p loss 4 (2%) 180 100
(1.00)
0.00295
(1.00)
0.401
(1.00)
1
(1.00)
0.607
(1.00)
0.000786
(0.594)
0.667
(1.00)
0.93
(1.00)
0.642
(1.00)
0.724
(1.00)
2.74e-05
(0.0213)
0.196
(1.00)
0.735
(1.00)
0.153
(1.00)
19q loss 4 (2%) 180 100
(1.00)
0.00295
(1.00)
0.401
(1.00)
1
(1.00)
0.607
(1.00)
0.000786
(0.594)
0.667
(1.00)
0.93
(1.00)
0.642
(1.00)
0.724
(1.00)
2.74e-05
(0.0213)
0.196
(1.00)
0.735
(1.00)
0.153
(1.00)
20q loss 4 (2%) 180 100
(1.00)
0.362
(1.00)
0.142
(1.00)
1
(1.00)
0.259
(1.00)
0.000786
(0.594)
0.667
(1.00)
1.55e-26
(1.22e-23)
0.592
(1.00)
0.724
(1.00)
0.33
(1.00)
0.556
(1.00)
0.0183
(1.00)
0.528
(1.00)
1p gain 5 (3%) 179 100
(1.00)
0.956
(1.00)
0.0219
(1.00)
0.432
(1.00)
1
(1.00)
0.957
(1.00)
0.327
(1.00)
0.169
(1.00)
0.661
(1.00)
0.135
(1.00)
0.0723
(1.00)
0.469
(1.00)
0.572
(1.00)
0.862
(1.00)
1q gain 8 (4%) 176 100
(1.00)
0.886
(1.00)
0.0591
(1.00)
0.599
(1.00)
0.687
(1.00)
0.636
(1.00)
0.213
(1.00)
0.0116
(1.00)
0.816
(1.00)
0.0993
(1.00)
0.0842
(1.00)
0.581
(1.00)
0.739
(1.00)
0.398
(1.00)
3p gain 16 (9%) 168 100
(1.00)
0.0311
(1.00)
0.00642
(1.00)
0.678
(1.00)
1
(1.00)
0.504
(1.00)
0.0396
(1.00)
0.042
(1.00)
0.246
(1.00)
0.00773
(1.00)
0.596
(1.00)
0.591
(1.00)
0.266
(1.00)
0.163
(1.00)
3q gain 20 (11%) 164 100
(1.00)
0.0102
(1.00)
0.00513
(1.00)
0.447
(1.00)
0.693
(1.00)
0.439
(1.00)
0.0728
(1.00)
0.0182
(1.00)
0.717
(1.00)
0.0194
(1.00)
0.195
(1.00)
0.442
(1.00)
0.00473
(1.00)
0.0674
(1.00)
4p gain 4 (2%) 180 100
(1.00)
0.0813
(1.00)
0.667
(1.00)
1
(1.00)
0.607
(1.00)
0.000786
(0.594)
0.379
(1.00)
0.93
(1.00)
0.158
(1.00)
0.418
(1.00)
0.947
(1.00)
0.481
(1.00)
0.00055
(0.418)
0.821
(1.00)
7p gain 33 (18%) 151 100
(1.00)
0.176
(1.00)
0.163
(1.00)
0.195
(1.00)
0.1
(1.00)
0.249
(1.00)
0.0425
(1.00)
0.131
(1.00)
0.138
(1.00)
0.0511
(1.00)
0.097
(1.00)
0.336
(1.00)
0.453
(1.00)
0.412
(1.00)
7q gain 30 (16%) 154 100
(1.00)
0.338
(1.00)
0.183
(1.00)
0.74
(1.00)
0.137
(1.00)
0.338
(1.00)
0.0644
(1.00)
0.174
(1.00)
0.168
(1.00)
0.0728
(1.00)
0.203
(1.00)
0.213
(1.00)
0.596
(1.00)
0.275
(1.00)
8p gain 21 (11%) 163 100
(1.00)
0.188
(1.00)
0.193
(1.00)
0.243
(1.00)
0.575
(1.00)
0.985
(1.00)
0.00388
(1.00)
0.0511
(1.00)
0.0147
(1.00)
0.00317
(1.00)
0.0816
(1.00)
0.383
(1.00)
0.323
(1.00)
0.191
(1.00)
8q gain 34 (18%) 150 100
(1.00)
0.839
(1.00)
0.264
(1.00)
0.335
(1.00)
0.576
(1.00)
0.665
(1.00)
0.00431
(1.00)
0.00274
(1.00)
0.274
(1.00)
0.00886
(1.00)
0.158
(1.00)
0.106
(1.00)
0.909
(1.00)
0.298
(1.00)
10p gain 6 (3%) 178 100
(1.00)
0.661
(1.00)
0.739
(1.00)
1
(1.00)
0.0785
(1.00)
0.000785
(0.594)
0.515
(1.00)
0.53
(1.00)
0.0688
(1.00)
0.173
(1.00)
0.844
(1.00)
0.18
(1.00)
0.488
(1.00)
0.0537
(1.00)
10q gain 7 (4%) 177 100
(1.00)
0.551
(1.00)
0.557
(1.00)
0.494
(1.00)
0.0475
(1.00)
0.438
(1.00)
0.596
(1.00)
0.744
(1.00)
0.672
(1.00)
0.211
(1.00)
0.545
(1.00)
0.7
(1.00)
0.349
(1.00)
0.235
(1.00)
11p gain 8 (4%) 176 100
(1.00)
0.967
(1.00)
0.0591
(1.00)
0.201
(1.00)
0.456
(1.00)
0.718
(1.00)
0.104
(1.00)
0.0196
(1.00)
0.534
(1.00)
0.0672
(1.00)
0.785
(1.00)
0.313
(1.00)
0.000354
(0.271)
0.555
(1.00)
11q gain 8 (4%) 176 100
(1.00)
0.967
(1.00)
0.0591
(1.00)
0.201
(1.00)
0.456
(1.00)
0.718
(1.00)
0.104
(1.00)
0.0196
(1.00)
0.534
(1.00)
0.0672
(1.00)
0.785
(1.00)
0.313
(1.00)
0.000354
(0.271)
0.555
(1.00)
16p gain 9 (5%) 175 100
(1.00)
0.361
(1.00)
0.00395
(1.00)
0.201
(1.00)
0.732
(1.00)
0.718
(1.00)
0.0523
(1.00)
0.00996
(1.00)
0.478
(1.00)
0.063
(1.00)
0.696
(1.00)
0.989
(1.00)
0.574
(1.00)
0.684
(1.00)
16q gain 3 (2%) 181 100
(1.00)
0.147
(1.00)
0.313
(1.00)
1
(1.00)
1
(1.00)
0.604
(1.00)
0.117
(1.00)
0.295
(1.00)
0.641
(1.00)
0.12
(1.00)
0.56
(1.00)
1p loss 4 (2%) 180 100
(1.00)
0.843
(1.00)
0.667
(1.00)
1
(1.00)
1
(1.00)
0.000786
(0.594)
0.285
(1.00)
0.341
(1.00)
0.402
(1.00)
0.309
(1.00)
0.226
(1.00)
0.251
(1.00)
0.784
(1.00)
0.505
(1.00)
5p loss 3 (2%) 181 100
(1.00)
0.738
(1.00)
0.0413
(1.00)
0.0297
(1.00)
0.546
(1.00)
0.28
(1.00)
0.248
(1.00)
0.117
(1.00)
0.497
(1.00)
0.258
(1.00)
0.533
(1.00)
0.569
(1.00)
0.541
(1.00)
0.468
(1.00)
5q loss 5 (3%) 179 100
(1.00)
0.63
(1.00)
0.0999
(1.00)
0.00868
(1.00)
0.355
(1.00)
0.167
(1.00)
0.0129
(1.00)
0.0167
(1.00)
0.0625
(1.00)
0.00471
(1.00)
0.78
(1.00)
0.694
(1.00)
0.731
(1.00)
0.551
(1.00)
6q loss 12 (7%) 172 100
(1.00)
0.907
(1.00)
0.33
(1.00)
0.0251
(1.00)
1
(1.00)
0.127
(1.00)
0.0303
(1.00)
0.00618
(1.00)
0.331
(1.00)
0.00898
(1.00)
0.154
(1.00)
0.639
(1.00)
0.417
(1.00)
0.514
(1.00)
8p loss 59 (32%) 125 100
(1.00)
0.17
(1.00)
0.0254
(1.00)
0.42
(1.00)
0.122
(1.00)
0.13
(1.00)
0.316
(1.00)
0.0425
(1.00)
0.00273
(1.00)
0.521
(1.00)
0.196
(1.00)
0.203
(1.00)
0.329
(1.00)
0.0927
(1.00)
8q loss 10 (5%) 174 100
(1.00)
0.0507
(1.00)
0.0386
(1.00)
0.0739
(1.00)
0.542
(1.00)
0.153
(1.00)
0.0635
(1.00)
0.122
(1.00)
0.204
(1.00)
0.0577
(1.00)
0.364
(1.00)
0.422
(1.00)
0.247
(1.00)
0.917
(1.00)
9q loss 4 (2%) 180 100
(1.00)
0.0286
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.000786
(0.594)
0.285
(1.00)
0.93
(1.00)
0.0859
(1.00)
0.0921
(1.00)
0.987
(1.00)
0.239
(1.00)
0.000475
(0.362)
0.49
(1.00)
10p loss 13 (7%) 171 100
(1.00)
0.87
(1.00)
0.0044
(1.00)
0.0339
(1.00)
0.43
(1.00)
0.256
(1.00)
0.0226
(1.00)
0.00421
(1.00)
0.354
(1.00)
0.0101
(1.00)
0.225
(1.00)
0.589
(1.00)
0.269
(1.00)
0.11
(1.00)
10q loss 15 (8%) 169 100
(1.00)
0.788
(1.00)
0.0892
(1.00)
0.0112
(1.00)
0.616
(1.00)
0.195
(1.00)
0.00587
(1.00)
0.0231
(1.00)
0.026
(1.00)
0.00162
(1.00)
0.274
(1.00)
0.619
(1.00)
0.0302
(1.00)
0.177
(1.00)
12p loss 17 (9%) 167 100
(1.00)
0.832
(1.00)
0.45
(1.00)
0.00344
(1.00)
0.539
(1.00)
0.135
(1.00)
0.0887
(1.00)
0.0366
(1.00)
0.583
(1.00)
0.0749
(1.00)
0.463
(1.00)
0.354
(1.00)
0.819
(1.00)
0.519
(1.00)
13q loss 28 (15%) 156 100
(1.00)
0.0895
(1.00)
0.863
(1.00)
0.0288
(1.00)
0.878
(1.00)
0.189
(1.00)
0.0201
(1.00)
0.12
(1.00)
0.0791
(1.00)
0.00584
(1.00)
0.355
(1.00)
0.945
(1.00)
0.639
(1.00)
0.723
(1.00)
14q loss 9 (5%) 175 100
(1.00)
0.349
(1.00)
0.0821
(1.00)
0.243
(1.00)
0.456
(1.00)
0.543
(1.00)
0.0249
(1.00)
0.00996
(1.00)
0.24
(1.00)
0.0303
(1.00)
0.391
(1.00)
0.43
(1.00)
0.159
(1.00)
0.61
(1.00)
15q loss 12 (7%) 172 100
(1.00)
0.835
(1.00)
0.0127
(1.00)
0.00362
(1.00)
1
(1.00)
0.0738
(1.00)
0.00802
(1.00)
0.00102
(0.757)
0.209
(1.00)
0.00717
(1.00)
0.457
(1.00)
0.44
(1.00)
0.339
(1.00)
0.669
(1.00)
16p loss 14 (8%) 170 100
(1.00)
0.989
(1.00)
0.855
(1.00)
0.364
(1.00)
0.267
(1.00)
0.000778
(0.59)
0.254
(1.00)
0.381
(1.00)
0.406
(1.00)
0.114
(1.00)
0.396
(1.00)
0.197
(1.00)
0.0137
(1.00)
0.238
(1.00)
16q loss 40 (22%) 144 100
(1.00)
0.814
(1.00)
0.204
(1.00)
0.126
(1.00)
0.486
(1.00)
0.26
(1.00)
0.00641
(1.00)
0.00513
(1.00)
0.25
(1.00)
0.00252
(1.00)
0.0324
(1.00)
0.402
(1.00)
0.707
(1.00)
0.516
(1.00)
17p loss 27 (15%) 157 100
(1.00)
0.891
(1.00)
0.0878
(1.00)
0.00821
(1.00)
1
(1.00)
0.0894
(1.00)
0.00328
(1.00)
0.00513
(1.00)
0.147
(1.00)
0.00237
(1.00)
0.106
(1.00)
0.498
(1.00)
0.142
(1.00)
0.72
(1.00)
18p loss 24 (13%) 160 100
(1.00)
0.605
(1.00)
0.122
(1.00)
0.0721
(1.00)
0.18
(1.00)
0.151
(1.00)
0.00852
(1.00)
0.0238
(1.00)
0.0444
(1.00)
0.00208
(1.00)
0.192
(1.00)
0.552
(1.00)
0.888
(1.00)
0.218
(1.00)
20p loss 7 (4%) 177 100
(1.00)
0.539
(1.00)
0.0634
(1.00)
0.494
(1.00)
0.65
(1.00)
0.674
(1.00)
0.958
(1.00)
0.0311
(1.00)
0.252
(1.00)
0.947
(1.00)
0.232
(1.00)
0.594
(1.00)
0.00488
(1.00)
0.417
(1.00)
21q loss 8 (4%) 176 100
(1.00)
0.67
(1.00)
0.121
(1.00)
0.00251
(1.00)
1
(1.00)
0.1
(1.00)
0.114
(1.00)
0.0791
(1.00)
0.3
(1.00)
0.133
(1.00)
0.143
(1.00)
0.394
(1.00)
0.793
(1.00)
0.893
(1.00)
22q loss 16 (9%) 168 100
(1.00)
0.911
(1.00)
0.0562
(1.00)
0.0112
(1.00)
0.509
(1.00)
0.187
(1.00)
0.00236
(1.00)
0.000427
(0.326)
0.156
(1.00)
0.00351
(1.00)
0.765
(1.00)
0.202
(1.00)
0.543
(1.00)
0.775
(1.00)
xq loss 10 (5%) 174 100
(1.00)
0.859
(1.00)
0.276
(1.00)
0.0739
(1.00)
1
(1.00)
0.233
(1.00)
0.0293
(1.00)
0.0045
(1.00)
0.425
(1.00)
0.0267
(1.00)
0.386
(1.00)
0.135
(1.00)
0.915
(1.00)
0.542
(1.00)
'4q gain' versus 'GLEASON_SCORE_SECONDARY'

P value = 8.13e-06 (t-test), Q value = 0.0063

Table S1.  Gene #6: '4q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

nPatients Mean (Std.Dev)
ALL 184 3.8 (0.6)
4Q GAIN MUTATED 3 4.0 (0.0)
4Q GAIN WILD-TYPE 181 3.8 (0.6)

Figure S1.  Get High-res Image Gene #6: '4q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

'5p gain' versus 'GLEASON_SCORE_SECONDARY'

P value = 8.13e-06 (t-test), Q value = 0.0063

Table S2.  Gene #7: '5p gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

nPatients Mean (Std.Dev)
ALL 184 3.8 (0.6)
5P GAIN MUTATED 3 4.0 (0.0)
5P GAIN WILD-TYPE 181 3.8 (0.6)

Figure S2.  Get High-res Image Gene #7: '5p gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

'9p gain' versus 'PSA_VALUE'

P value = 0.00018 (t-test), Q value = 0.14

Table S3.  Gene #12: '9p gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
9P GAIN MUTATED 6 0.1 (0.1)
9P GAIN WILD-TYPE 156 1.5 (4.6)

Figure S3.  Get High-res Image Gene #12: '9p gain' versus Clinical Feature #13: 'PSA_VALUE'

'9q gain' versus 'PSA_VALUE'

P value = 0.000249 (t-test), Q value = 0.19

Table S4.  Gene #13: '9q gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
9Q GAIN MUTATED 11 0.1 (0.1)
9Q GAIN WILD-TYPE 151 1.5 (4.6)

Figure S4.  Get High-res Image Gene #13: '9q gain' versus Clinical Feature #13: 'PSA_VALUE'

'12q gain' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.76e-26 (t-test), Q value = 1.4e-23

Table S5.  Gene #18: '12q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
12Q GAIN MUTATED 3 4.0 (0.0)
12Q GAIN WILD-TYPE 181 3.5 (0.6)

Figure S5.  Get High-res Image Gene #18: '12q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'12q gain' versus 'PSA_VALUE'

P value = 0.000125 (t-test), Q value = 0.097

Table S6.  Gene #18: '12q gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
12Q GAIN MUTATED 3 0.1 (0.0)
12Q GAIN WILD-TYPE 159 1.5 (4.5)

Figure S6.  Get High-res Image Gene #18: '12q gain' versus Clinical Feature #13: 'PSA_VALUE'

'17q gain' versus 'PSA_VALUE'

P value = 0.000225 (t-test), Q value = 0.17

Table S7.  Gene #21: '17q gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
17Q GAIN MUTATED 4 0.1 (0.1)
17Q GAIN WILD-TYPE 158 1.5 (4.5)

Figure S7.  Get High-res Image Gene #21: '17q gain' versus Clinical Feature #13: 'PSA_VALUE'

'18p gain' versus 'PSA_VALUE'

P value = 0.000202 (t-test), Q value = 0.16

Table S8.  Gene #22: '18p gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
18P GAIN MUTATED 6 0.1 (0.1)
18P GAIN WILD-TYPE 156 1.5 (4.6)

Figure S8.  Get High-res Image Gene #22: '18p gain' versus Clinical Feature #13: 'PSA_VALUE'

'18q gain' versus 'PSA_VALUE'

P value = 0.000281 (t-test), Q value = 0.22

Table S9.  Gene #23: '18q gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
18Q GAIN MUTATED 3 0.1 (0.0)
18Q GAIN WILD-TYPE 159 1.5 (4.5)

Figure S9.  Get High-res Image Gene #23: '18q gain' versus Clinical Feature #13: 'PSA_VALUE'

'19q gain' versus 'GLEASON_SCORE_SECONDARY'

P value = 6.74e-67 (t-test), Q value = 5.3e-64

Table S10.  Gene #24: '19q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

nPatients Mean (Std.Dev)
ALL 184 3.8 (0.6)
19Q GAIN MUTATED 3 5.0 (0.0)
19Q GAIN WILD-TYPE 181 3.8 (0.6)

Figure S10.  Get High-res Image Gene #24: '19q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

'20q gain' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.37e-26 (t-test), Q value = 1.1e-23

Table S11.  Gene #25: '20q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
20Q GAIN MUTATED 5 4.0 (0.0)
20Q GAIN WILD-TYPE 179 3.5 (0.6)

Figure S11.  Get High-res Image Gene #25: '20q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'20q gain' versus 'PSA_VALUE'

P value = 0.000273 (t-test), Q value = 0.21

Table S12.  Gene #25: '20q gain' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
20Q GAIN MUTATED 5 0.1 (0.1)
20Q GAIN WILD-TYPE 157 1.5 (4.6)

Figure S12.  Get High-res Image Gene #25: '20q gain' versus Clinical Feature #13: 'PSA_VALUE'

'21q gain' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.76e-26 (t-test), Q value = 1.4e-23

Table S13.  Gene #26: '21q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
21Q GAIN MUTATED 3 4.0 (0.0)
21Q GAIN WILD-TYPE 181 3.5 (0.6)

Figure S13.  Get High-res Image Gene #26: '21q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'4p loss' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.55e-26 (t-test), Q value = 1.2e-23

Table S14.  Gene #28: '4p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
4P LOSS MUTATED 4 4.0 (0.0)
4P LOSS WILD-TYPE 180 3.5 (0.6)

Figure S14.  Get High-res Image Gene #28: '4p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'4q loss' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.76e-26 (t-test), Q value = 1.4e-23

Table S15.  Gene #29: '4q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
4Q LOSS MUTATED 3 4.0 (0.0)
4Q LOSS WILD-TYPE 181 3.5 (0.6)

Figure S15.  Get High-res Image Gene #29: '4q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'6p loss' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.06e-26 (t-test), Q value = 8.3e-24

Table S16.  Gene #32: '6p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
6P LOSS MUTATED 7 4.0 (0.0)
6P LOSS WILD-TYPE 177 3.5 (0.6)

Figure S16.  Get High-res Image Gene #32: '6p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'9p loss' versus 'PSA_VALUE'

P value = 0.000256 (t-test), Q value = 0.2

Table S17.  Gene #36: '9p loss' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
9P LOSS MUTATED 7 0.1 (0.1)
9P LOSS WILD-TYPE 155 1.5 (4.6)

Figure S17.  Get High-res Image Gene #36: '9p loss' versus Clinical Feature #13: 'PSA_VALUE'

'12q loss' versus 'PSA_VALUE'

P value = 0.00027 (t-test), Q value = 0.21

Table S18.  Gene #41: '12q loss' versus Clinical Feature #13: 'PSA_VALUE'

nPatients Mean (Std.Dev)
ALL 162 1.4 (4.5)
12Q LOSS MUTATED 7 0.1 (0.1)
12Q LOSS WILD-TYPE 155 1.5 (4.6)

Figure S18.  Get High-res Image Gene #41: '12q loss' versus Clinical Feature #13: 'PSA_VALUE'

'17q loss' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.55e-26 (t-test), Q value = 1.2e-23

Table S19.  Gene #48: '17q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
17Q LOSS MUTATED 4 4.0 (0.0)
17Q LOSS WILD-TYPE 180 3.5 (0.6)

Figure S19.  Get High-res Image Gene #48: '17q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

'18q loss' versus 'GLEASON_SCORE'

P value = 0.000259 (t-test), Q value = 0.2

Table S20.  Gene #50: '18q loss' versus Clinical Feature #10: 'GLEASON_SCORE'

nPatients Mean (Std.Dev)
ALL 184 7.3 (0.8)
18Q LOSS MUTATED 35 7.9 (1.1)
18Q LOSS WILD-TYPE 149 7.2 (0.6)

Figure S20.  Get High-res Image Gene #50: '18q loss' versus Clinical Feature #10: 'GLEASON_SCORE'

'19p loss' versus 'PSA_RESULT_PREOP'

P value = 2.74e-05 (t-test), Q value = 0.021

Table S21.  Gene #51: '19p loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

nPatients Mean (Std.Dev)
ALL 182 10.4 (10.2)
19P LOSS MUTATED 4 4.5 (1.3)
19P LOSS WILD-TYPE 178 10.5 (10.3)

Figure S21.  Get High-res Image Gene #51: '19p loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

'19q loss' versus 'PSA_RESULT_PREOP'

P value = 2.74e-05 (t-test), Q value = 0.021

Table S22.  Gene #52: '19q loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

nPatients Mean (Std.Dev)
ALL 182 10.4 (10.2)
19Q LOSS MUTATED 4 4.5 (1.3)
19Q LOSS WILD-TYPE 178 10.5 (10.3)

Figure S22.  Get High-res Image Gene #52: '19q loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

'20q loss' versus 'GLEASON_SCORE_PRIMARY'

P value = 1.55e-26 (t-test), Q value = 1.2e-23

Table S23.  Gene #54: '20q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

nPatients Mean (Std.Dev)
ALL 184 3.5 (0.6)
20Q LOSS MUTATED 4 4.0 (0.0)
20Q LOSS WILD-TYPE 180 3.5 (0.6)

Figure S23.  Get High-res Image Gene #54: '20q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

  • Clinical data file = PRAD-TP.merged_data.txt

  • Number of patients = 184

  • Number of significantly arm-level cnvs = 57

  • Number of selected clinical features = 14

  • Exclude regions 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

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' 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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] 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)
[4] 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)