Correlation between copy number variations of arm-level result and selected clinical features
Liver Hepatocellular Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1M61JHF
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/C1M61JHF
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 12 clinical features across 362 patients, 20 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'GENDER'.

  • 2q gain cnv correlated to 'GENDER'.

  • 8q gain cnv correlated to 'GENDER'.

  • 12p gain cnv correlated to 'HISTOLOGICAL_TYPE'.

  • 20p gain cnv correlated to 'Time to Death'.

  • 22q gain cnv correlated to 'PATHOLOGY_T_STAGE'.

  • 3p loss cnv correlated to 'PATHOLOGY_T_STAGE' and 'HISTOLOGICAL_TYPE'.

  • 4q loss cnv correlated to 'RACE'.

  • 7q loss cnv correlated to 'Time to Death'.

  • 10q loss cnv correlated to 'RACE'.

  • 12q loss cnv correlated to 'PATHOLOGIC_STAGE'.

  • 13q loss cnv correlated to 'PATHOLOGY_T_STAGE'.

  • 15q loss cnv correlated to 'Time to Death'.

  • 16p loss cnv correlated to 'YEARS_TO_BIRTH' and 'RACE'.

  • 16q loss cnv correlated to 'YEARS_TO_BIRTH' and 'RACE'.

  • 17p loss cnv correlated to 'PATHOLOGIC_STAGE'.

  • xp loss cnv correlated to 'GENDER'.

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 12 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 20 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		PATHOLOGIC
STAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		PATHOLOGY
M
STAGE 		GENDER RADIATION
THERAPY 		HISTOLOGICAL
TYPE 		RESIDUAL
TUMOR 		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 Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
3p loss 50 (14%) 312 0.716
(1.00) 		0.165
(0.659) 		0.0134
(0.355) 		0.00276
(0.227) 		0.361
(0.811) 		0.444
(0.86) 		0.328
(0.798) 		0.599
(0.956) 		0.00345
(0.227) 		0.388
(0.823) 		0.971
(1.00) 		1
(1.00)
16p loss 109 (30%) 253 0.0601
(0.58) 		0.00401
(0.227) 		0.296
(0.772) 		0.386
(0.823) 		0.251
(0.736) 		0.607
(0.956) 		0.325
(0.797) 		0.11
(0.601) 		1
(1.00) 		0.131
(0.625) 		0.00408
(0.227) 		0.23
(0.736)
16q loss 144 (40%) 218 0.0944
(0.58) 		0.000265
(0.0766) 		0.103
(0.601) 		0.0828
(0.58) 		0.579
(0.954) 		1
(1.00) 		0.357
(0.811) 		0.708
(1.00) 		0.732
(1.00) 		0.633
(0.966) 		2e-05
(0.0197) 		0.392
(0.823)
2p gain 44 (12%) 318 0.136
(0.625) 		0.108
(0.601) 		0.0898
(0.58) 		0.0855
(0.58) 		0.043
(0.549) 		0.0727
(0.58) 		9.35e-05
(0.046) 		1
(1.00) 		0.39
(0.823) 		0.0724
(0.58) 		0.275
(0.748) 		0.675
(0.999)
2q gain 40 (11%) 322 0.141
(0.63) 		0.441
(0.858) 		0.153
(0.647) 		0.143
(0.63) 		0.335
(0.801) 		0.0727
(0.58) 		0.000466
(0.0766) 		1
(1.00) 		0.349
(0.809) 		0.219
(0.736) 		0.718
(1.00) 		0.653
(0.98)
8q gain 185 (51%) 177 0.879
(1.00) 		0.133
(0.625) 		0.211
(0.729) 		0.337
(0.801) 		0.595
(0.956) 		1
(1.00) 		0.00103
(0.127) 		0.121
(0.613) 		0.637
(0.966) 		1
(1.00) 		0.0331
(0.477) 		1
(1.00)
12p gain 40 (11%) 322 0.0526
(0.58) 		0.436
(0.856) 		0.228
(0.736) 		0.0816
(0.58) 		1
(1.00) 		1
(1.00) 		0.28
(0.748) 		1
(1.00) 		0.00507
(0.249) 		0.772
(1.00) 		0.963
(1.00) 		1
(1.00)
20p gain 107 (30%) 255 0.00367
(0.227) 		0.0274
(0.456) 		0.0854
(0.58) 		0.118
(0.61) 		1
(1.00) 		0.0924
(0.58) 		0.219
(0.736) 		0.678
(0.999) 		1
(1.00) 		0.328
(0.798) 		0.814
(1.00) 		1
(1.00)
22q gain 48 (13%) 314 0.622
(0.963) 		0.905
(1.00) 		0.0241
(0.443) 		0.00323
(0.227) 		0.326
(0.797) 		1
(1.00) 		0.244
(0.736) 		0.6
(0.956) 		0.424
(0.852) 		0.312
(0.786) 		0.939
(1.00) 		1
(1.00)
4q loss 146 (40%) 216 0.198
(0.704) 		0.00536
(0.251) 		0.332
(0.8) 		0.515
(0.914) 		0.57
(0.949) 		0.324
(0.797) 		0.25
(0.736) 		0.707
(1.00) 		0.735
(1.00) 		0.438
(0.856) 		0.00151
(0.155) 		0.396
(0.829)
7q loss 21 (6%) 341 0.000467
(0.0766) 		0.421
(0.851) 		0.949
(1.00) 		0.881
(1.00) 		1
(1.00) 		1
(1.00) 		0.0147
(0.358) 		0.346
(0.808) 		1
(1.00) 		0.13
(0.625) 		0.142
(0.63) 		0.546
(0.936)
10q loss 74 (20%) 288 0.102
(0.601) 		0.943
(1.00) 		0.353
(0.809) 		0.196
(0.702) 		0.485
(0.899) 		0.583
(0.955) 		0.576
(0.954) 		1
(1.00) 		0.0286
(0.456) 		0.444
(0.86) 		0.00033
(0.0766) 		1
(1.00)
12q loss 33 (9%) 329 0.218
(0.736) 		0.0873
(0.58) 		0.00375
(0.227) 		0.498
(0.91) 		1
(1.00) 		0.0566
(0.58) 		0.696
(1.00) 		1
(1.00) 		0.58
(0.954) 		0.0937
(0.58) 		0.209
(0.726) 		0.344
(0.805)
13q loss 118 (33%) 244 0.181
(0.69) 		0.56
(0.944) 		0.0711
(0.58) 		0.00158
(0.155) 		1
(1.00) 		0.6
(0.956) 		0.12
(0.613) 		0.434
(0.856) 		0.248
(0.736) 		0.0815
(0.58) 		0.916
(1.00) 		1
(1.00)
15q loss 65 (18%) 297 0.00493
(0.249) 		0.807
(1.00) 		0.0289
(0.456) 		0.00945
(0.321) 		0.086
(0.58) 		0.583
(0.955) 		0.884
(1.00) 		1
(1.00) 		0.742
(1.00) 		0.78
(1.00) 		0.207
(0.724) 		0.71
(1.00)
17p loss 179 (49%) 183 0.00862
(0.314) 		0.552
(0.941) 		0.00092
(0.127) 		0.0118
(0.342) 		0.247
(0.736) 		0.622
(0.963) 		1
(1.00) 		1
(1.00) 		0.638
(0.966) 		0.282
(0.753) 		0.302
(0.773) 		0.412
(0.844)
xp loss 92 (25%) 270 0.291
(0.766) 		0.0766
(0.58) 		0.789
(1.00) 		0.464
(0.874) 		1
(1.00) 		1
(1.00) 		0.00416
(0.227) 		0.379
(0.823) 		0.419
(0.851) 		0.392
(0.823) 		0.513
(0.913) 		1
(1.00)
1p gain 56 (15%) 306 0.799
(1.00) 		0.136
(0.625) 		0.454
(0.863) 		0.12
(0.613) 		1
(1.00) 		1
(1.00) 		0.161
(0.658) 		1
(1.00) 		1
(1.00) 		0.259
(0.744) 		0.0765
(0.58) 		0.234
(0.736)
1q gain 220 (61%) 142 0.966
(1.00) 		0.51
(0.911) 		0.51
(0.911) 		0.611
(0.956) 		0.56
(0.944) 		0.3
(0.773) 		0.563
(0.944) 		0.709
(1.00) 		0.133
(0.625) 		0.647
(0.974) 		0.147
(0.632) 		1
(1.00)
3p gain 35 (10%) 327 0.244
(0.736) 		0.539
(0.936) 		0.325
(0.797) 		0.794
(1.00) 		0.25
(0.736) 		0.351
(0.809) 		0.13
(0.625) 		1
(1.00) 		1
(1.00) 		0.241
(0.736) 		0.776
(1.00) 		0.373
(0.821)
3q gain 38 (10%) 324 0.0473
(0.574) 		0.727
(1.00) 		0.332
(0.8) 		0.782
(1.00) 		0.269
(0.744) 		0.362
(0.811) 		0.145
(0.63) 		1
(1.00) 		0.635
(0.966) 		0.275
(0.748) 		0.629
(0.966) 		0.153
(0.647)
4p gain 26 (7%) 336 0.121
(0.613) 		0.704
(1.00) 		0.632
(0.966) 		0.59
(0.956) 		1
(1.00) 		1
(1.00) 		0.125
(0.618) 		1
(1.00) 		1
(1.00) 		0.878
(1.00) 		1
(1.00) 		0.61
(0.956)
4q gain 7 (2%) 355 0.931
(1.00) 		0.24
(0.736) 		0.759
(1.00) 		0.68
(0.999) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.17
(0.662) 		0.579
(0.954) 		0.238
(0.736)
5p gain 135 (37%) 227 0.07
(0.58) 		0.116
(0.603) 		0.337
(0.801) 		0.0721
(0.58) 		0.554
(0.942) 		1
(1.00) 		0.726
(1.00) 		0.108
(0.601) 		0.732
(1.00) 		0.834
(1.00) 		0.933
(1.00) 		1
(1.00)
5q gain 107 (30%) 255 0.246
(0.736) 		0.067
(0.58) 		0.92
(1.00) 		0.358
(0.811) 		0.563
(0.944) 		1
(1.00) 		0.107
(0.601) 		0.0264
(0.456) 		1
(1.00) 		0.677
(0.999) 		0.822
(1.00) 		0.54
(0.936)
6p gain 114 (31%) 248 0.292
(0.766) 		0.157
(0.654) 		0.541
(0.936) 		0.231
(0.736) 		0.555
(0.942) 		0.596
(0.956) 		0.332
(0.8) 		0.438
(0.856) 		0.715
(1.00) 		0.61
(0.956) 		0.285
(0.757) 		0.363
(0.811)
6q gain 64 (18%) 298 0.302
(0.773) 		0.738
(1.00) 		0.196
(0.702) 		0.233
(0.736) 		1
(1.00) 		0.14
(0.63) 		0.237
(0.736) 		1
(1.00) 		1
(1.00) 		0.244
(0.736) 		0.348
(0.809) 		0.0639
(0.58)
7p gain 109 (30%) 253 0.813
(1.00) 		0.0159
(0.372) 		0.382
(0.823) 		0.741
(1.00) 		0.196
(0.702) 		1
(1.00) 		0.325
(0.797) 		1
(1.00) 		0.709
(1.00) 		0.777
(1.00) 		0.26
(0.744) 		0.548
(0.936)
7q gain 109 (30%) 253 0.606
(0.956) 		0.00712
(0.292) 		0.375
(0.822) 		0.456
(0.866) 		0.201
(0.712) 		1
(1.00) 		1
(1.00) 		0.437
(0.856) 		0.705
(1.00) 		0.97
(1.00) 		0.109
(0.601) 		0.234
(0.736)
8p gain 78 (22%) 284 0.758
(1.00) 		0.0909
(0.58) 		0.984
(1.00) 		0.879
(1.00) 		1
(1.00) 		1
(1.00) 		0.0391
(0.506) 		0.164
(0.659) 		0.372
(0.821) 		0.128
(0.623) 		0.142
(0.63) 		0.488
(0.899)
9p gain 19 (5%) 343 0.854
(1.00) 		0.205
(0.722) 		0.0806
(0.58) 		0.123
(0.613) 		1
(1.00) 		0.222
(0.736) 		0.321
(0.796) 		1
(1.00) 		0.0746
(0.58) 		0.206
(0.724) 		0.301
(0.773) 		0.488
(0.899)
9q gain 21 (6%) 341 0.718
(1.00) 		0.144
(0.63) 		0.126
(0.618) 		0.0922
(0.58) 		1
(1.00) 		0.234
(0.736) 		0.0514
(0.58) 		1
(1.00) 		0.418
(0.851) 		0.252
(0.736) 		0.706
(1.00) 		0.546
(0.936)
10p gain 61 (17%) 301 0.19
(0.699) 		0.00988
(0.324) 		0.0897
(0.58) 		0.0901
(0.58) 		1
(1.00) 		0.14
(0.63) 		1
(1.00) 		0.321
(0.796) 		0.378
(0.823) 		0.85
(1.00) 		0.354
(0.809) 		0.253
(0.736)
10q gain 37 (10%) 325 0.812
(1.00) 		0.136
(0.625) 		0.102
(0.601) 		0.0917
(0.58) 		1
(1.00) 		0.0605
(0.58) 		0.457
(0.866) 		0.499
(0.91) 		0.625
(0.965) 		0.914
(1.00) 		0.961
(1.00) 		0.144
(0.63)
11p gain 17 (5%) 345 0.452
(0.863) 		0.807
(1.00) 		0.386
(0.823) 		0.252
(0.736) 		1
(1.00) 		0.196
(0.702) 		0.428
(0.854) 		1
(1.00) 		1
(1.00) 		0.0139
(0.358) 		0.85
(1.00) 		1
(1.00)
11q gain 18 (5%) 344 0.38
(0.823) 		0.634
(0.966) 		0.239
(0.736) 		0.088
(0.58) 		1
(1.00) 		0.222
(0.736) 		0.298
(0.773) 		1
(1.00) 		1
(1.00) 		0.0205
(0.421) 		0.723
(1.00) 		1
(1.00)
12q gain 46 (13%) 316 0.887
(1.00) 		0.401
(0.833) 		0.0584
(0.58) 		0.064
(0.58) 		0.353
(0.809) 		1
(1.00) 		0.309
(0.779) 		0.603
(0.956) 		0.0612
(0.58) 		0.427
(0.854) 		1
(1.00) 		0.67
(0.995)
13q gain 23 (6%) 339 0.233
(0.736) 		0.952
(1.00) 		0.131
(0.625) 		0.644
(0.971) 		0.21
(0.726) 		0.247
(0.736) 		0.105
(0.601) 		0.374
(0.821) 		1
(1.00) 		0.235
(0.736) 		0.544
(0.936) 		0.184
(0.692)
14q gain 23 (6%) 339 0.525
(0.927) 		0.461
(0.872) 		0.498
(0.91) 		0.54
(0.936) 		1
(1.00) 		0.196
(0.702) 		0.248
(0.736) 		1
(1.00) 		0.107
(0.601) 		0.0915
(0.58) 		0.189
(0.699) 		0.565
(0.945)
15q gain 33 (9%) 329 0.508
(0.911) 		0.994
(1.00) 		0.444
(0.86) 		0.351
(0.809) 		1
(1.00) 		1
(1.00) 		0.696
(1.00) 		1
(1.00) 		0.192
(0.7) 		0.903
(1.00) 		0.603
(0.956) 		0.344
(0.805)
16p gain 29 (8%) 333 0.389
(0.823) 		0.144
(0.63) 		0.313
(0.786) 		0.251
(0.736) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.105
(0.601) 		0.0818
(0.58) 		0.575
(0.954) 		0.386
(0.823) 		0.61
(0.956)
16q gain 15 (4%) 347 0.701
(1.00) 		0.0495
(0.58) 		0.254
(0.737) 		0.166
(0.659) 		1
(1.00) 		1
(1.00) 		0.783
(1.00) 		0.271
(0.744) 		0.0232
(0.438) 		0.355
(0.809) 		0.229
(0.736) 		0.399
(0.831)
17p gain 30 (8%) 332 0.834
(1.00) 		0.568
(0.949) 		0.212
(0.73) 		0.163
(0.659) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.544
(0.936) 		0.0853
(0.58) 		0.276
(0.748) 		0.612
(0.956)
17q gain 93 (26%) 269 0.604
(0.956) 		0.499
(0.91) 		0.434
(0.856) 		0.186
(0.692) 		0.576
(0.954) 		0.266
(0.744) 		0.0949
(0.58) 		1
(1.00) 		0.825
(1.00) 		0.0594
(0.58) 		0.0879
(0.58) 		1
(1.00)
18p gain 35 (10%) 327 0.823
(1.00) 		0.42
(0.851) 		0.115
(0.601) 		0.16
(0.658) 		1
(1.00) 		0.34
(0.802) 		0.849
(1.00) 		1
(1.00) 		1
(1.00) 		0.0942
(0.58) 		0.0629
(0.58) 		1
(1.00)
18q gain 27 (7%) 335 0.77
(1.00) 		0.153
(0.647) 		0.0586
(0.58) 		0.161
(0.658) 		1
(1.00) 		0.271
(0.744) 		0.668
(0.994) 		1
(1.00) 		1
(1.00) 		0.0361
(0.489) 		0.184
(0.692) 		1
(1.00)
19p gain 54 (15%) 308 0.379
(0.823) 		0.501
(0.91) 		0.0798
(0.58) 		0.913
(1.00) 		0.396
(0.829) 		0.0124
(0.348) 		0.0388
(0.506) 		1
(1.00) 		0.481
(0.895) 		0.106
(0.601) 		0.262
(0.744) 		0.424
(0.852)
19q gain 70 (19%) 292 0.364
(0.811) 		0.27
(0.744) 		0.173
(0.674) 		0.773
(1.00) 		0.47
(0.878) 		0.0248
(0.443) 		0.317
(0.791) 		1
(1.00) 		0.757
(1.00) 		0.165
(0.659) 		0.681
(0.999) 		0.302
(0.773)
20q gain 111 (31%) 251 0.0221
(0.427) 		0.0387
(0.506) 		0.187
(0.694) 		0.111
(0.601) 		1
(1.00) 		0.598
(0.956) 		0.541
(0.936) 		0.679
(0.999) 		1
(1.00) 		0.35
(0.809) 		0.887
(1.00) 		0.762
(1.00)
21q gain 26 (7%) 336 0.476
(0.889) 		0.663
(0.99) 		0.0177
(0.396) 		0.011
(0.342) 		1
(1.00) 		1
(1.00) 		0.827
(1.00) 		1
(1.00) 		0.493
(0.905) 		0.02
(0.421) 		0.338
(0.801) 		1
(1.00)
xp gain 41 (11%) 321 0.693
(1.00) 		0.404
(0.835) 		0.965
(1.00) 		0.782
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.176
(0.681) 		1
(1.00) 		0.429
(0.854) 		0.19
(0.699) 		1
(1.00)
xq gain 63 (17%) 299 0.409
(0.839) 		0.671
(0.996) 		0.996
(1.00) 		0.989
(1.00) 		1
(1.00) 		1
(1.00) 		0.18
(0.688) 		0.0971
(0.586) 		0.735
(1.00) 		0.854
(1.00) 		0.25
(0.736) 		0.707
(1.00)
1p loss 81 (22%) 281 0.683
(1) 		0.335
(0.801) 		0.5
(0.91) 		0.362
(0.811) 		0.544
(0.936) 		0.0554
(0.58) 		0.279
(0.748) 		0.355
(0.809) 		0.289
(0.762) 		0.331
(0.8) 		0.791
(1.00) 		1
(1.00)
1q loss 22 (6%) 340 0.0462
(0.572) 		0.51
(0.911) 		0.48
(0.894) 		0.339
(0.802) 		0.168
(0.659) 		1
(1.00) 		0.641
(0.969) 		1
(1.00) 		0.437
(0.856) 		0.276
(0.748) 		0.652
(0.979) 		1
(1.00)
2p loss 31 (9%) 331 0.751
(1.00) 		0.797
(1.00) 		0.717
(1.00) 		0.634
(0.966) 		1
(1.00) 		1
(1.00) 		0.315
(0.787) 		0.452
(0.863) 		0.557
(0.943) 		0.234
(0.736) 		0.714
(1.00) 		0.612
(0.956)
2q loss 36 (10%) 326 0.748
(1.00) 		0.25
(0.736) 		0.95
(1.00) 		0.959
(1.00) 		1
(1.00) 		1
(1.00) 		0.707
(1.00) 		0.511
(0.911) 		0.614
(0.957) 		0.125
(0.618) 		0.719
(1.00) 		1
(1.00)
3q loss 38 (10%) 324 0.268
(0.744) 		0.147
(0.632) 		0.11
(0.601) 		0.0509
(0.58) 		0.288
(0.762) 		1
(1.00) 		0.467
(0.877) 		1
(1.00) 		0.063
(0.58) 		0.595
(0.956) 		0.963
(1.00) 		1
(1.00)
4p loss 106 (29%) 256 0.449
(0.863) 		0.0801
(0.58) 		0.0363
(0.489) 		0.136
(0.625) 		0.191
(0.699) 		0.0864
(0.58) 		0.108
(0.601) 		1
(1.00) 		1
(1.00) 		0.419
(0.851) 		0.0519
(0.58) 		0.0663
(0.58)
5p loss 28 (8%) 334 0.305
(0.777) 		0.0506
(0.58) 		0.397
(0.829) 		0.227
(0.736) 		0.25
(0.736) 		1
(1.00) 		0.528
(0.932) 		0.401
(0.833) 		0.0284
(0.456) 		0.889
(1.00) 		0.262
(0.744) 		1
(1.00)
5q loss 39 (11%) 323 0.107
(0.601) 		0.0594
(0.58) 		0.222
(0.736) 		0.0144
(0.358) 		0.298
(0.773) 		1
(1.00) 		0.856
(1.00) 		0.522
(0.923) 		0.0149
(0.358) 		0.917
(1.00) 		0.57
(0.949) 		1
(1.00)
6p loss 27 (7%) 335 0.892
(1.00) 		0.621
(0.963) 		0.177
(0.685) 		0.327
(0.798) 		0.23
(0.736) 		0.294
(0.771) 		0.0298
(0.458) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.183
(0.692) 		1
(1.00)
6q loss 91 (25%) 271 0.51
(0.911) 		0.0115
(0.342) 		0.315
(0.787) 		0.702
(1.00) 		0.168
(0.659) 		0.305
(0.777) 		0.0197
(0.421) 		0.201
(0.712) 		0.415
(0.85) 		1
(1.00) 		0.628
(0.966) 		1
(1.00)
7p loss 16 (4%) 346 0.0937
(0.58) 		0.511
(0.911) 		0.965
(1.00) 		0.829
(1.00) 		1
(1.00) 		1
(1.00) 		0.166
(0.659) 		0.271
(0.744) 		1
(1.00) 		0.387
(0.823) 		0.759
(1.00) 		0.445
(0.86)
8p loss 186 (51%) 176 0.681
(0.999) 		0.18
(0.688) 		0.246
(0.736) 		0.592
(0.956) 		0.116
(0.603) 		1
(1.00) 		0.91
(1.00) 		1
(1.00) 		0.0252
(0.443) 		0.563
(0.944) 		0.0922
(0.58) 		1
(1.00)
8q loss 42 (12%) 320 0.597
(0.956) 		0.917
(1.00) 		0.427
(0.854) 		0.611
(0.956) 		0.279
(0.748) 		0.404
(0.835) 		0.0532
(0.58) 		1
(1.00) 		0.672
(0.996) 		0.548
(0.936) 		0.657
(0.984) 		1
(1.00)
9p loss 115 (32%) 247 0.111
(0.601) 		0.0292
(0.456) 		0.267
(0.744) 		0.801
(1.00) 		0.246
(0.736) 		0.105
(0.601) 		0.0704
(0.58) 		1
(1.00) 		1
(1.00) 		0.43
(0.854) 		0.186
(0.692) 		0.236
(0.736)
9q loss 105 (29%) 257 0.114
(0.601) 		0.806
(1.00) 		0.0727
(0.58) 		0.563
(0.944) 		0.0205
(0.421) 		0.0674
(0.58) 		0.214
(0.733) 		1
(1.00) 		1
(1.00) 		0.303
(0.773) 		0.735
(1.00) 		0.358
(0.811)
10p loss 44 (12%) 318 0.285
(0.757) 		0.168
(0.659) 		0.154
(0.647) 		0.307
(0.777) 		0.279
(0.748) 		1
(1.00) 		0.863
(1.00) 		0.603
(0.956) 		0.0555
(0.58) 		0.605
(0.956) 		0.21
(0.726) 		1
(1.00)
11p loss 61 (17%) 301 0.486
(0.899) 		0.698
(1.00) 		0.00814
(0.308) 		0.013
(0.355) 		0.0757
(0.58) 		0.544
(0.936) 		0.764
(1.00) 		1
(1.00) 		0.0672
(0.58) 		0.601
(0.956) 		0.827
(1.00) 		0.242
(0.736)
11q loss 70 (19%) 292 0.555
(0.942) 		0.453
(0.863) 		0.0357
(0.489) 		0.0886
(0.58) 		0.112
(0.601) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.0969
(0.586) 		0.489
(0.9) 		0.919
(1.00) 		0.0808
(0.58)
12p loss 61 (17%) 301 0.505
(0.911) 		0.446
(0.86) 		0.0174
(0.396) 		0.366
(0.813) 		0.0757
(0.58) 		0.157
(0.654) 		0.547
(0.936) 		0.606
(0.956) 		1
(1.00) 		0.25
(0.736) 		0.432
(0.855) 		0.465
(0.874)
14q loss 106 (29%) 256 0.0593
(0.58) 		0.115
(0.601) 		0.0453
(0.572) 		0.00688
(0.292) 		1
(1.00) 		0.598
(0.956) 		0.266
(0.744) 		1
(1.00) 		0.36
(0.811) 		0.707
(1.00) 		0.0738
(0.58) 		0.534
(0.936)
17q loss 37 (10%) 325 0.0593
(0.58) 		0.134
(0.625) 		0.00685
(0.292) 		0.137
(0.625) 		0.0245
(0.443) 		0.373
(0.821) 		0.264
(0.744) 		1
(1.00) 		0.0117
(0.342) 		1
(1.00) 		0.137
(0.625) 		0.373
(0.821)
18p loss 72 (20%) 290 0.766
(1.00) 		0.423
(0.852) 		0.734
(1.00) 		0.739
(1.00) 		0.508
(0.911) 		1
(1.00) 		0.259
(0.744) 		0.133
(0.625) 		0.00916
(0.321) 		0.837
(1.00) 		0.77
(1.00) 		0.729
(1.00)
18q loss 77 (21%) 285 0.788
(1.00) 		0.948
(1.00) 		0.716
(1.00) 		1
(1.00) 		0.529
(0.932) 		0.228
(0.736) 		0.337
(0.801) 		0.0342
(0.48) 		0.0465
(0.572) 		0.26
(0.744) 		1
(1.00) 		0.159
(0.657)
19p loss 54 (15%) 308 0.0787
(0.58) 		0.0218
(0.427) 		0.618
(0.961) 		0.507
(0.911) 		0.405
(0.835) 		1
(1.00) 		0.115
(0.601) 		0.6
(0.956) 		0.482
(0.895) 		0.388
(0.823) 		0.0561
(0.58) 		0.431
(0.854)
19q loss 38 (10%) 324 0.122
(0.613) 		0.0313
(0.467) 		0.249
(0.736) 		0.379
(0.823) 		0.307
(0.777) 		1
(1.00) 		0.145
(0.63) 		1
(1.00) 		0.636
(0.966) 		0.364
(0.811) 		0.0625
(0.58) 		0.638
(0.966)
20p loss 24 (7%) 338 0.867
(1.00) 		0.148
(0.634) 		0.184
(0.692) 		0.453
(0.863) 		1
(1.00) 		0.271
(0.744) 		0.825
(1.00) 		0.388
(0.823) 		0.0577
(0.58) 		0.668
(0.994) 		0.652
(0.979) 		0.599
(0.956)
20q loss 12 (3%) 350 0.341
(0.804) 		0.421
(0.851) 		0.266
(0.744) 		0.696
(1.00) 		1
(1.00) 		1
(1.00) 		0.531
(0.932) 		0.222
(0.736) 		0.0837
(0.58) 		0.255
(0.737) 		0.448
(0.862) 		0.349
(0.809)
21q loss 108 (30%) 254 0.0334
(0.477) 		0.272
(0.744) 		0.389
(0.823) 		0.914
(1.00) 		0.221
(0.736) 		0.102
(0.601) 		0.0841
(0.58) 		1
(1.00) 		0.114
(0.601) 		0.521
(0.923) 		0.661
(0.989) 		0.535
(0.936)
22q loss 66 (18%) 296 0.406
(0.835) 		0.277
(0.748) 		0.127
(0.621) 		0.0325
(0.477) 		1
(1.00) 		0.577
(0.954) 		0.383
(0.823) 		0.614
(0.957) 		0.0278
(0.456) 		0.0217
(0.427) 		0.00791
(0.308) 		0.0601
(0.58)
xq loss 68 (19%) 294 0.794
(1.00) 		0.0661
(0.58) 		0.834
(1.00) 		0.468
(0.877) 		0.462
(0.872) 		0.583
(0.955) 		0.0303
(0.458) 		0.626
(0.966) 		0.158
(0.656) 		0.636
(0.966) 		0.162
(0.658) 		1
(1.00)
'2p gain' versus 'GENDER'

P value = 9.35e-05 (Fisher's exact test), Q value = 0.046

Table S1.  Gene #3: '2p gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 115 247
2P GAIN MUTATED 26 18
2P GAIN WILD-TYPE 89 229

Figure S1.  Get High-res Image Gene #3: '2p gain' versus Clinical Feature #7: 'GENDER'

'2q gain' versus 'GENDER'

P value = 0.000466 (Fisher's exact test), Q value = 0.077

Table S2.  Gene #4: '2q gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 115 247
2Q GAIN MUTATED 23 17
2Q GAIN WILD-TYPE 92 230

Figure S2.  Get High-res Image Gene #4: '2q gain' versus Clinical Feature #7: 'GENDER'

'8q gain' versus 'GENDER'

P value = 0.00103 (Fisher's exact test), Q value = 0.13

Table S3.  Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 115 247
8Q GAIN MUTATED 44 141
8Q GAIN WILD-TYPE 71 106

Figure S3.  Get High-res Image Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

'12p gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00507 (Fisher's exact test), Q value = 0.25

Table S4.  Gene #23: '12p gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 2 353 7
12P GAIN MUTATED 0 36 4
12P GAIN WILD-TYPE 2 317 3

Figure S4.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'20p gain' versus 'Time to Death'

P value = 0.00367 (logrank test), Q value = 0.23

Table S5.  Gene #36: '20p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 358 129 0.0 - 120.8 (19.8)
20P GAIN MUTATED 105 49 0.3 - 114.3 (17.6)
20P GAIN WILD-TYPE 253 80 0.0 - 120.8 (20.4)

Figure S5.  Get High-res Image Gene #36: '20p gain' versus Clinical Feature #1: 'Time to Death'

'22q gain' versus 'PATHOLOGY_T_STAGE'

P value = 0.00323 (Fisher's exact test), Q value = 0.23

Table S6.  Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 182 92 74 12
22Q GAIN MUTATED 13 17 16 2
22Q GAIN WILD-TYPE 169 75 58 10

Figure S6.  Get High-res Image Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00276 (Fisher's exact test), Q value = 0.23

Table S7.  Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 182 92 74 12
3P LOSS MUTATED 14 16 17 3
3P LOSS WILD-TYPE 168 76 57 9

Figure S7.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00345 (Fisher's exact test), Q value = 0.23

Table S8.  Gene #46: '3p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 2 353 7
3P LOSS MUTATED 1 45 4
3P LOSS WILD-TYPE 1 308 3

Figure S8.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'4q loss' versus 'RACE'

P value = 0.00151 (Fisher's exact test), Q value = 0.16

Table S9.  Gene #49: '4q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 157 17 177
4Q LOSS MUTATED 0 80 9 57
4Q LOSS WILD-TYPE 1 77 8 120

Figure S9.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #11: 'RACE'

'7q loss' versus 'Time to Death'

P value = 0.000467 (logrank test), Q value = 0.077

Table S10.  Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 358 129 0.0 - 120.8 (19.8)
7Q LOSS MUTATED 21 14 0.2 - 76.4 (13.6)
7Q LOSS WILD-TYPE 337 115 0.0 - 120.8 (20.0)

Figure S10.  Get High-res Image Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'RACE'

P value = 0.00033 (Fisher's exact test), Q value = 0.077

Table S11.  Gene #61: '10q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 157 17 177
10Q LOSS MUTATED 0 38 10 26
10Q LOSS WILD-TYPE 1 119 7 151

Figure S11.  Get High-res Image Gene #61: '10q loss' versus Clinical Feature #11: 'RACE'

'12q loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00375 (Fisher's exact test), Q value = 0.23

Table S12.  Gene #65: '12q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 171 85 3 60 8 7 3 1 2
12Q LOSS MUTATED 12 9 1 5 2 0 3 0 0
12Q LOSS WILD-TYPE 159 76 2 55 6 7 0 1 2

Figure S12.  Get High-res Image Gene #65: '12q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'13q loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00158 (Fisher's exact test), Q value = 0.16

Table S13.  Gene #66: '13q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 182 92 74 12
13Q LOSS MUTATED 49 38 22 9
13Q LOSS WILD-TYPE 133 54 52 3

Figure S13.  Get High-res Image Gene #66: '13q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'15q loss' versus 'Time to Death'

P value = 0.00493 (logrank test), Q value = 0.25

Table S14.  Gene #68: '15q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 358 129 0.0 - 120.8 (19.8)
15Q LOSS MUTATED 63 31 0.2 - 102.7 (13.4)
15Q LOSS WILD-TYPE 295 98 0.0 - 120.8 (20.9)

Figure S14.  Get High-res Image Gene #68: '15q loss' versus Clinical Feature #1: 'Time to Death'

'16p loss' versus 'YEARS_TO_BIRTH'

P value = 0.00401 (Wilcoxon-test), Q value = 0.23

Table S15.  Gene #69: '16p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 359 59.7 (12.7)
16P LOSS MUTATED 108 57.1 (12.9)
16P LOSS WILD-TYPE 251 60.8 (12.5)

Figure S15.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16p loss' versus 'RACE'

P value = 0.00408 (Fisher's exact test), Q value = 0.23

Table S16.  Gene #69: '16p loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 157 17 177
16P LOSS MUTATED 0 62 6 40
16P LOSS WILD-TYPE 1 95 11 137

Figure S16.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #11: 'RACE'

'16q loss' versus 'YEARS_TO_BIRTH'

P value = 0.000265 (Wilcoxon-test), Q value = 0.077

Table S17.  Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 359 59.7 (12.7)
16Q LOSS MUTATED 143 56.9 (12.9)
16Q LOSS WILD-TYPE 216 61.6 (12.3)

Figure S17.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16q loss' versus 'RACE'

P value = 2e-05 (Fisher's exact test), Q value = 0.02

Table S18.  Gene #70: '16q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 157 17 177
16Q LOSS MUTATED 0 84 7 50
16Q LOSS WILD-TYPE 1 73 10 127

Figure S18.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #11: 'RACE'

'17p loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00092 (Fisher's exact test), Q value = 0.13

Table S19.  Gene #71: '17p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 171 85 3 60 8 7 3 1 2
17P LOSS MUTATED 68 49 2 33 3 7 3 1 1
17P LOSS WILD-TYPE 103 36 1 27 5 0 0 0 1

Figure S19.  Get High-res Image Gene #71: '17p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'xp loss' versus 'GENDER'

P value = 0.00416 (Fisher's exact test), Q value = 0.23

Table S20.  Gene #81: 'xp loss' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 115 247
XP LOSS MUTATED 18 74
XP LOSS WILD-TYPE 97 173

Figure S20.  Get High-res Image Gene #81: 'xp loss' versus Clinical Feature #7: 'GENDER'

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/LIHC-TP/19782291/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LIHC-TP/19775332/LIHC-TP.merged_data.txt

  • Number of patients = 362

  • Number of significantly arm-level cnvs = 82

  • Number of selected clinical features = 12

  • 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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