Correlation between copy number variations of arm-level result and selected clinical features
Adrenocortical Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1QV3KGN
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1QV3KGN
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 82 arm-level events and 8 clinical features across 90 patients, 12 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'Time to Death'.

  • 10q gain cnv correlated to 'Time to Death' and 'NEOPLASM_DISEASESTAGE'.

  • 11p gain cnv correlated to 'Time to Death'.

  • 11q gain cnv correlated to 'Time to Death'.

  • 4p loss cnv correlated to 'Time to Death' and 'PATHOLOGY_T_STAGE'.

  • 4q loss cnv correlated to 'Time to Death'.

  • 16p loss cnv correlated to 'Time to Death'.

  • 17p loss cnv correlated to 'Time to Death'.

  • 19p loss cnv correlated to 'Time to Death'.

  • 22q loss cnv correlated to 'Time to Death'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 82 arm-level events and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 12 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		NEOPLASM
DISEASESTAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		GENDER RACE ETHNICITY
nCNV (%) 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 Fisher's exact test
10q gain 26 (29%) 64 0.00415
(0.244) 		0.266
(1.00) 		0.00167
(0.137) 		0.00589
(0.254) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.421
(1.00)
4p loss 10 (11%) 80 0.000123
(0.0213) 		0.542
(1.00) 		0.0179
(0.456) 		0.00393
(0.244) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
2p gain 13 (14%) 77 0.000329
(0.0432) 		0.818
(1.00) 		0.377
(1.00) 		0.145
(0.97) 		0.347
(1.00) 		0.205
(0.974) 		0.171
(0.974) 		0.587
(1.00)
11p gain 5 (6%) 85 0.00013
(0.0213) 		0.364
(1.00) 		0.157
(0.97) 		0.0415
(0.697) 		1
(1.00) 		0.656
(1.00) 		1
(1.00) 		0.569
(1.00)
11q gain 6 (7%) 84 6.59e-05
(0.0213) 		0.698
(1.00) 		0.118
(0.947) 		0.0625
(0.806) 		1
(1.00) 		0.66
(1.00) 		1
(1.00) 		1
(1.00)
4q loss 11 (12%) 79 1.53e-05
(0.01) 		0.805
(1.00) 		0.0223
(0.472) 		0.00596
(0.254) 		1
(1.00) 		0.742
(1.00) 		1
(1.00) 		1
(1.00)
16p loss 6 (7%) 84 0.00069
(0.0755) 		0.418
(1.00) 		0.118
(0.947) 		0.0508
(0.752) 		0.526
(1.00) 		1
(1.00) 		1
(1.00) 		0.444
(1.00)
17p loss 32 (36%) 58 0.00124
(0.116) 		0.535
(1.00) 		0.059
(0.791) 		0.139
(0.97) 		0.73
(1.00) 		0.246
(1.00) 		0.7
(1.00) 		0.409
(1.00)
19p loss 5 (6%) 85 0.00299
(0.218) 		0.603
(1.00) 		0.197
(0.974) 		0.286
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
22q loss 48 (53%) 42 0.00446
(0.244) 		0.236
(1.00) 		0.187
(0.974) 		0.0812
(0.929) 		1
(1.00) 		0.374
(1.00) 		1
(1.00) 		0.117
(0.947)
1p gain 4 (4%) 86 0.0866
(0.929) 		0.487
(1.00) 		1
(1.00) 		0.746
(1.00) 		1
(1.00) 		0.294
(1.00) 		0.147
(0.97) 		1
(1.00)
1q gain 8 (9%) 82 0.0458
(0.734) 		0.798
(1.00) 		0.734
(1.00) 		0.456
(1.00) 		0.589
(1.00) 		0.047
(0.734) 		0.245
(1.00) 		0.548
(1.00)
2q gain 12 (13%) 78 0.0097
(0.335) 		0.767
(1.00) 		0.153
(0.97) 		0.238
(1.00) 		1
(1.00) 		0.0516
(0.752) 		0.171
(0.974) 		0.645
(1.00)
3p gain 13 (14%) 77 0.28
(1.00) 		0.323
(1.00) 		0.585
(1.00) 		0.929
(1.00) 		1
(1.00) 		0.759
(1.00) 		1
(1.00) 		1
(1.00)
3q gain 15 (17%) 75 0.392
(1.00) 		0.423
(1.00) 		0.337
(1.00) 		0.757
(1.00) 		0.677
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
4p gain 37 (41%) 53 0.196
(0.974) 		0.941
(1.00) 		0.792
(1.00) 		0.842
(1.00) 		1
(1.00) 		0.654
(1.00) 		1
(1.00) 		0.421
(1.00)
4q gain 33 (37%) 57 0.0958
(0.938) 		0.97
(1.00) 		0.96
(1.00) 		0.929
(1.00) 		1
(1.00) 		0.495
(1.00) 		1
(1.00) 		0.669
(1.00)
5p gain 57 (63%) 33 0.386
(1.00) 		0.854
(1.00) 		0.696
(1.00) 		0.89
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.226
(0.996)
5q gain 53 (59%) 37 0.746
(1.00) 		0.62
(1.00) 		0.566
(1.00) 		0.797
(1.00) 		1
(1.00) 		1
(1.00) 		0.181
(0.974) 		0.115
(0.947)
6p gain 18 (20%) 72 0.531
(1.00) 		0.0275
(0.545) 		0.497
(1.00) 		0.256
(1.00) 		0.679
(1.00) 		0.588
(1.00) 		0.0921
(0.929) 		0.0548
(0.782)
6q gain 16 (18%) 74 0.898
(1.00) 		0.2
(0.974) 		0.113
(0.947) 		0.174
(0.974) 		0.2
(0.974) 		0.399
(1.00) 		0.0591
(0.791) 		0.613
(1.00)
7p gain 48 (53%) 42 0.718
(1.00) 		0.51
(1.00) 		0.168
(0.974) 		0.233
(1.00) 		0.336
(1.00) 		1
(1.00) 		0.217
(0.974) 		0.435
(1.00)
7q gain 48 (53%) 42 0.43
(1.00) 		0.859
(1.00) 		0.107
(0.947) 		0.225
(0.996) 		0.336
(1.00) 		1
(1.00) 		0.216
(0.974) 		0.115
(0.947)
8p gain 32 (36%) 58 0.254
(1.00) 		0.508
(1.00) 		0.442
(1.00) 		0.638
(1.00) 		0.484
(1.00) 		1
(1.00) 		0.292
(1.00) 		0.421
(1.00)
8q gain 38 (42%) 52 0.701
(1.00) 		0.49
(1.00) 		0.346
(1.00) 		0.539
(1.00) 		0.51
(1.00) 		1
(1.00) 		0.341
(1.00) 		0.7
(1.00)
9p gain 20 (22%) 70 0.27
(1.00) 		0.716
(1.00) 		0.0591
(0.791) 		0.324
(1.00) 		0.00792
(0.289) 		0.791
(1.00) 		1
(1.00) 		0.374
(1.00)
9q gain 29 (32%) 61 0.0157
(0.456) 		0.663
(1.00) 		0.0377
(0.673) 		0.0884
(0.929) 		0.013
(0.427) 		0.477
(1.00) 		1
(1.00) 		0.421
(1.00)
10p gain 25 (28%) 65 0.0299
(0.561) 		0.397
(1.00) 		0.00658
(0.254) 		0.0161
(0.456) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.421
(1.00)
12p gain 64 (71%) 26 0.94
(1.00) 		0.287
(1.00) 		0.7
(1.00) 		0.611
(1.00) 		1
(1.00) 		0.464
(1.00) 		0.65
(1.00) 		0.0898
(0.929)
12q gain 64 (71%) 26 0.965
(1.00) 		0.415
(1.00) 		0.702
(1.00) 		0.65
(1.00) 		0.718
(1.00) 		0.464
(1.00) 		0.0822
(0.929) 		0.0898
(0.929)
13q gain 6 (7%) 84 0.961
(1.00) 		0.651
(1.00) 		0.735
(1.00) 		0.721
(1.00) 		0.526
(1.00) 		1
(1.00) 		1
(1.00) 		0.548
(1.00)
14q gain 21 (23%) 69 0.204
(0.974) 		0.426
(1.00) 		0.182
(0.974) 		0.311
(1.00) 		0.241
(1.00) 		0.606
(1.00) 		1
(1.00) 		0.374
(1.00)
15q gain 11 (12%) 79 0.956
(1.00) 		0.46
(1.00) 		0.796
(1.00) 		0.714
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
16p gain 49 (54%) 41 0.386
(1.00) 		0.576
(1.00) 		0.595
(1.00) 		0.284
(1.00) 		1
(1.00) 		0.187
(0.974) 		0.728
(1.00) 		0.439
(1.00)
16q gain 47 (52%) 43 0.255
(1.00) 		0.929
(1.00) 		0.832
(1.00) 		0.611
(1.00) 		1
(1.00) 		0.269
(1.00) 		0.115
(0.947) 		0.699
(1.00)
17p gain 5 (6%) 85 0.293
(1.00) 		0.622
(1.00) 		0.158
(0.97) 		0.109
(0.947) 		1
(1.00) 		1
(1.00) 		0.146
(0.97) 		0.444
(1.00)
17q gain 7 (8%) 83 0.138
(0.97) 		0.488
(1.00) 		0.691
(1.00) 		0.47
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.548
(1.00)
18p gain 6 (7%) 84 0.14
(0.97) 		0.452
(1.00) 		0.343
(1.00) 		0.331
(1.00) 		1
(1.00) 		1
(1.00) 		0.212
(0.974) 		1
(1.00)
18q gain 5 (6%) 85 0.329
(1.00) 		0.833
(1.00) 		0.831
(1.00) 		0.286
(1.00) 		1
(1.00) 		0.656
(1.00) 		0.18
(0.974) 		0.569
(1.00)
19p gain 56 (62%) 34 0.369
(1.00) 		0.119
(0.947) 		0.176
(0.974) 		0.205
(0.974) 		0.737
(1.00) 		0.821
(1.00) 		1
(1.00) 		0.124
(0.947)
19q gain 52 (58%) 38 0.403
(1.00) 		0.0203
(0.456) 		0.199
(0.974) 		0.326
(1.00) 		0.182
(0.974) 		0.378
(1.00) 		1
(1.00) 		0.124
(0.947)
20p gain 46 (51%) 44 0.169
(0.974) 		0.495
(1.00) 		0.338
(1.00) 		0.798
(1.00) 		1
(1.00) 		0.188
(0.974) 		0.493
(1.00) 		1
(1.00)
20q gain 49 (54%) 41 0.604
(1.00) 		0.964
(1.00) 		0.32
(1.00) 		0.856
(1.00) 		0.336
(1.00) 		0.187
(0.974) 		0.215
(0.974) 		0.71
(1.00)
21q gain 31 (34%) 59 0.761
(1.00) 		0.154
(0.97) 		0.935
(1.00) 		0.94
(1.00) 		0.0836
(0.929) 		0.818
(1.00) 		0.274
(1.00) 		0.443
(1.00)
22q gain 3 (3%) 87 0.153
(0.97) 		0.208
(0.974) 		1
(1.00) 		1
(1.00) 		0.307
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
xp gain 42 (47%) 48 0.51
(1.00) 		0.916
(1.00) 		0.866
(1.00) 		0.872
(1.00) 		1
(1.00) 		0.828
(1.00) 		0.353
(1.00) 		0.115
(0.947)
xq gain 41 (46%) 49 0.354
(1.00) 		0.77
(1.00) 		0.546
(1.00) 		0.913
(1.00) 		0.327
(1.00) 		0.824
(1.00) 		0.343
(1.00) 		0.435
(1.00)
1p loss 29 (32%) 61 0.921
(1.00) 		0.866
(1.00) 		0.956
(1.00) 		0.951
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
1q loss 20 (22%) 70 0.779
(1.00) 		0.317
(1.00) 		0.563
(1.00) 		0.744
(1.00) 		0.445
(1.00) 		0.599
(1.00) 		1
(1.00) 		1
(1.00)
2p loss 17 (19%) 73 0.039
(0.673) 		0.442
(1.00) 		1
(1.00) 		0.721
(1.00) 		1
(1.00) 		0.576
(1.00) 		1
(1.00) 		1
(1.00)
2q loss 15 (17%) 75 0.0711
(0.898) 		0.689
(1.00) 		0.616
(1.00) 		0.761
(1.00) 		1
(1.00) 		0.767
(1.00) 		1
(1.00) 		1
(1.00)
3p loss 20 (22%) 70 0.0935
(0.929) 		0.614
(1.00) 		0.0912
(0.929) 		0.341
(1.00) 		1
(1.00) 		0.293
(1.00) 		1
(1.00) 		1
(1.00)
3q loss 20 (22%) 70 0.155
(0.97) 		0.907
(1.00) 		0.178
(0.974) 		0.563
(1.00) 		1
(1.00) 		0.599
(1.00) 		0.251
(1.00) 		0.277
(1.00)
5p loss 8 (9%) 82 0.135
(0.97) 		0.676
(1.00) 		0.188
(0.974) 		0.151
(0.97) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.548
(1.00)
5q loss 7 (8%) 83 0.562
(1.00) 		0.342
(1.00) 		0.0747
(0.925) 		0.142
(0.97) 		0.584
(1.00) 		0.228
(0.996) 		1
(1.00) 		1
(1.00)
6p loss 19 (21%) 71 0.118
(0.947) 		0.35
(1.00) 		0.0826
(0.929) 		0.148
(0.97) 		0.445
(1.00) 		1
(1.00) 		1
(1.00) 		0.571
(1.00)
6q loss 22 (24%) 68 0.0283
(0.545) 		0.254
(1.00) 		0.00659
(0.254) 		0.0186
(0.456) 		0.706
(1.00) 		0.453
(1.00) 		1
(1.00) 		1
(1.00)
7p loss 5 (6%) 85 0.115
(0.947) 		0.718
(1.00) 		0.331
(1.00) 		0.286
(1.00) 		1
(1.00) 		0.0461
(0.734) 		1
(1.00) 		1
(1.00)
7q loss 6 (7%) 84 0.0205
(0.456) 		0.61
(1.00) 		0.0384
(0.673) 		0.0196
(0.456) 		1
(1.00) 		0.411
(1.00) 		1
(1.00) 		1
(1.00)
8p loss 16 (18%) 74 0.731
(1.00) 		0.768
(1.00) 		0.67
(1.00) 		0.97
(1.00) 		0.365
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
8q loss 12 (13%) 78 0.994
(1.00) 		0.639
(1.00) 		0.581
(1.00) 		1
(1.00) 		0.107
(0.947) 		0.534
(1.00) 		1
(1.00) 		1
(1.00)
9p loss 20 (22%) 70 0.181
(0.974) 		0.506
(1.00) 		0.843
(1.00) 		0.621
(1.00) 		0.683
(1.00) 		0.599
(1.00) 		1
(1.00) 		0.645
(1.00)
9q loss 11 (12%) 79 0.871
(1.00) 		0.427
(1.00) 		0.213
(0.974) 		0.428
(1.00) 		0.596
(1.00) 		1
(1.00) 		1
(1.00) 		0.569
(1.00)
10p loss 12 (13%) 78 0.348
(1.00) 		0.934
(1.00) 		0.183
(0.974) 		1
(1.00) 		0.134
(0.97) 		1
(1.00) 		1
(1.00) 		0.444
(1.00)
10q loss 10 (11%) 80 0.42
(1.00) 		0.298
(1.00) 		0.307
(1.00) 		0.714
(1.00) 		0.317
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
11p loss 24 (27%) 66 0.561
(1.00) 		0.722
(1.00) 		0.131
(0.97) 		0.603
(1.00) 		0.706
(1.00) 		0.455
(1.00) 		1
(1.00) 		1
(1.00)
11q loss 23 (26%) 67 0.198
(0.974) 		0.563
(1.00) 		0.0273
(0.545) 		0.162
(0.974) 		1
(1.00) 		0.317
(1.00) 		1
(1.00) 		0.569
(1.00)
12p loss 5 (6%) 85 0.189
(0.974) 		0.241
(1.00) 		0.33
(1.00) 		0.287
(1.00) 		1
(1.00) 		0.335
(1.00) 		1
(1.00) 		1
(1.00)
12q loss 4 (4%) 86 0.0627
(0.806) 		0.463
(1.00) 		0.333
(1.00) 		0.289
(1.00) 		1
(1.00) 		0.606
(1.00) 		1
(1.00) 		1
(1.00)
13q loss 39 (43%) 51 0.0899
(0.929) 		0.536
(1.00) 		0.484
(1.00) 		0.919
(1.00) 		0.51
(1.00) 		0.51
(1.00) 		0.506
(1.00) 		1
(1.00)
14q loss 18 (20%) 72 0.695
(1.00) 		0.793
(1.00) 		0.832
(1.00) 		0.779
(1.00) 		0.68
(1.00) 		0.782
(1.00) 		0.22
(0.982) 		0.129
(0.97)
15q loss 21 (23%) 69 0.61
(1.00) 		0.519
(1.00) 		0.652
(1.00) 		0.702
(1.00) 		1
(1.00) 		0.606
(1.00) 		1
(1.00) 		0.664
(1.00)
16q loss 5 (6%) 85 0.0202
(0.456) 		0.214
(0.974) 		0.248
(1.00) 		0.139
(0.97) 		0.461
(1.00) 		1
(1.00) 		1
(1.00) 		0.444
(1.00)
17q loss 24 (27%) 66 0.0157
(0.456) 		0.964
(1.00) 		0.192
(0.974) 		0.362
(1.00) 		0.706
(1.00) 		0.00587
(0.254) 		1
(1.00) 		0.664
(1.00)
18p loss 37 (41%) 53 0.548
(1.00) 		0.892
(1.00) 		0.209
(0.974) 		0.494
(1.00) 		1
(1.00) 		0.37
(1.00) 		0.289
(1.00) 		1
(1.00)
18q loss 35 (39%) 55 0.889
(1.00) 		0.747
(1.00) 		0.274
(1.00) 		0.518
(1.00) 		1
(1.00) 		0.11
(0.947) 		0.272
(1.00) 		1
(1.00)
19q loss 4 (4%) 86 0.0783
(0.929) 		0.124
(0.947) 		0.874
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
20p loss 9 (10%) 81 0.816
(1.00) 		0.595
(1.00) 		0.556
(1.00) 		0.747
(1.00) 		1
(1.00) 		0.156
(0.97) 		0.277
(1.00) 		0.548
(1.00)
20q loss 3 (3%) 87 0.385
(1.00) 		0.582
(1.00) 		0.704
(1.00) 		0.526
(1.00) 		1
(1.00) 		0.549
(1.00) 		1
(1.00) 		0.321
(1.00)
21q loss 15 (17%) 75 0.0209
(0.456) 		0.468
(1.00) 		0.671
(1.00) 		0.418
(1.00) 		1
(1.00) 		0.565
(1.00) 		1
(1.00) 		1
(1.00)
xp loss 16 (18%) 74 0.748
(1.00) 		0.0502
(0.752) 		0.861
(1.00) 		0.864
(1.00) 		0.677
(1.00) 		0.778
(1.00) 		1
(1.00) 		0.571
(1.00)
xq loss 15 (17%) 75 0.671
(1.00) 		0.12
(0.947) 		0.697
(1.00) 		0.552
(1.00) 		0.194
(0.974) 		1
(1.00) 		1
(1.00) 		0.571
(1.00)
'2p gain' versus 'Time to Death'

P value = 0.000329 (logrank test), Q value = 0.043

Table S1.  Gene #3: '2p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
2P GAIN MUTATED 13 10 0.0 - 91.3 (16.4)
2P GAIN WILD-TYPE 77 22 4.1 - 153.6 (38.5)

Figure S1.  Get High-res Image Gene #3: '2p gain' versus Clinical Feature #1: 'Time to Death'

'10q gain' versus 'Time to Death'

P value = 0.00415 (logrank test), Q value = 0.24

Table S2.  Gene #20: '10q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
10Q GAIN MUTATED 26 14 0.0 - 91.3 (32.0)
10Q GAIN WILD-TYPE 64 18 4.1 - 153.6 (42.9)

Figure S2.  Get High-res Image Gene #20: '10q gain' versus Clinical Feature #1: 'Time to Death'

'10q gain' versus 'NEOPLASM_DISEASESTAGE'

P value = 0.00167 (Fisher's exact test), Q value = 0.14

Table S3.  Gene #20: '10q gain' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

nPatients STAGE I STAGE II STAGE III STAGE IV
ALL 9 43 18 18
10Q GAIN MUTATED 0 8 6 11
10Q GAIN WILD-TYPE 9 35 12 7

Figure S3.  Get High-res Image Gene #20: '10q gain' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

'11p gain' versus 'Time to Death'

P value = 0.00013 (logrank test), Q value = 0.021

Table S4.  Gene #21: '11p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
11P GAIN MUTATED 5 5 0.0 - 60.9 (14.3)
11P GAIN WILD-TYPE 85 27 4.1 - 153.6 (36.3)

Figure S4.  Get High-res Image Gene #21: '11p gain' versus Clinical Feature #1: 'Time to Death'

'11q gain' versus 'Time to Death'

P value = 6.59e-05 (logrank test), Q value = 0.021

Table S5.  Gene #22: '11q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
11Q GAIN MUTATED 6 6 12.6 - 60.9 (16.2)
11Q GAIN WILD-TYPE 84 26 0.0 - 153.6 (37.4)

Figure S5.  Get High-res Image Gene #22: '11q gain' versus Clinical Feature #1: 'Time to Death'

'4p loss' versus 'Time to Death'

P value = 0.000123 (logrank test), Q value = 0.021

Table S6.  Gene #48: '4p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
4P LOSS MUTATED 10 7 4.1 - 46.5 (18.1)
4P LOSS WILD-TYPE 80 25 0.0 - 153.6 (39.5)

Figure S6.  Get High-res Image Gene #48: '4p loss' versus Clinical Feature #1: 'Time to Death'

'4p loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00393 (Fisher's exact test), Q value = 0.24

Table S7.  Gene #48: '4p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T1 T2 T3 T4
ALL 9 48 11 20
4P LOSS MUTATED 1 2 0 7
4P LOSS WILD-TYPE 8 46 11 13

Figure S7.  Get High-res Image Gene #48: '4p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'4q loss' versus 'Time to Death'

P value = 1.53e-05 (logrank test), Q value = 0.01

Table S8.  Gene #49: '4q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
4Q LOSS MUTATED 11 8 4.1 - 46.5 (18.1)
4Q LOSS WILD-TYPE 79 24 0.0 - 153.6 (39.6)

Figure S8.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #1: 'Time to Death'

'16p loss' versus 'Time to Death'

P value = 0.00069 (logrank test), Q value = 0.075

Table S9.  Gene #69: '16p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
16P LOSS MUTATED 6 5 12.6 - 39.4 (18.1)
16P LOSS WILD-TYPE 84 27 0.0 - 153.6 (39.0)

Figure S9.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #1: 'Time to Death'

'17p loss' versus 'Time to Death'

P value = 0.00124 (logrank test), Q value = 0.12

Table S10.  Gene #71: '17p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
17P LOSS MUTATED 32 18 4.1 - 91.3 (31.5)
17P LOSS WILD-TYPE 58 14 0.0 - 153.6 (41.3)

Figure S10.  Get High-res Image Gene #71: '17p loss' versus Clinical Feature #1: 'Time to Death'

'19p loss' versus 'Time to Death'

P value = 0.00299 (logrank test), Q value = 0.22

Table S11.  Gene #75: '19p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
19P LOSS MUTATED 5 4 12.6 - 44.5 (18.1)
19P LOSS WILD-TYPE 85 28 0.0 - 153.6 (38.5)

Figure S11.  Get High-res Image Gene #75: '19p loss' versus Clinical Feature #1: 'Time to Death'

'22q loss' versus 'Time to Death'

P value = 0.00446 (logrank test), Q value = 0.24

Table S12.  Gene #80: '22q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 90 32 0.0 - 153.6 (36.3)
22Q LOSS MUTATED 48 24 0.0 - 121.2 (37.4)
22Q LOSS WILD-TYPE 42 8 12.0 - 153.6 (35.1)

Figure S12.  Get High-res Image Gene #80: '22q loss' versus Clinical Feature #1: 'Time to Death'

Methods & Data
Input

  • Copy number data file = broad_values_by_arm.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/ACC-TP/15081747/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/ACC-TP/15074660/ACC-TP.merged_data.txt

  • Number of patients = 90

  • Number of significantly arm-level cnvs = 82

  • Number of selected clinical features = 8

  • 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

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)
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