Bladder Urothelial Carcinoma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
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 74 arm-level results and 11 clinical features across 131 patients, 8 significant findings detected with Q value < 0.25.

  • 4p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 5q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 9q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 14q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

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

  • 17p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 6p loss cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

  • 16q loss cnv correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 74 arm-level results and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER KARNOFSKY
PERFORMANCE
SCORE 		NUMBERPACKYEARSSMOKED TOBACCOSMOKINGHISTORYINDICATOR DISTANT
METASTASIS 		LYMPH
NODE
METASTASIS 		NUMBER
OF
LYMPH
NODES 		TUMOR
STAGECODE 		NEOPLASM
DISEASESTAGE
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test t-test t-test Fisher's exact test Chi-square test t-test t-test Fisher's exact test
4p gain 8 (6%) 123 0.0892
(1.00) 		0.819
(1.00) 		0.679
(1.00) 		0.394
(1.00) 		0.569
(1.00) 		0.274
(1.00) 		0.408
(1.00) 		0.000201
(0.143) 		0.266
(1.00)
5q gain 18 (14%) 113 0.297
(1.00) 		0.543
(1.00) 		0.56
(1.00) 		0.36
(1.00) 		0.982
(1.00) 		0.865
(1.00) 		1
(1.00) 		0.0944
(1.00) 		7.18e-05
(0.0513) 		0.0349
(1.00)
9q gain 11 (8%) 120 0.0825
(1.00) 		0.256
(1.00) 		0.467
(1.00) 		0.786
(1.00) 		0.0328
(1.00) 		0.828
(1.00) 		0.257
(1.00) 		0.168
(1.00) 		2.87e-06
(0.00206) 		0.000995
(0.706)
14q gain 11 (8%) 120 0.955
(1.00) 		0.633
(1.00) 		0.467
(1.00) 		0.471
(1.00) 		0.341
(1.00) 		0.348
(1.00) 		0.439
(1.00) 		0.422
(1.00) 		7.1e-05
(0.0508) 		0.468
(1.00)
16p gain 10 (8%) 121 4.1e-05
(0.0294) 		0.455
(1.00) 		0.27
(1.00) 		0.616
(1.00) 		0.212
(1.00) 		0.431
(1.00) 		0.0787
(1.00) 		0.819
(1.00) 		0.068
(1.00) 		0.856
(1.00)
17p gain 8 (6%) 123 0.415
(1.00) 		0.964
(1.00) 		0.415
(1.00) 		0.683
(1.00) 		0.952
(1.00) 		0.336
(1.00) 		0.26
(1.00) 		3.04e-06
(0.00218) 		0.0306
(1.00)
6p loss 16 (12%) 115 0.927
(1.00) 		0.565
(1.00) 		0.548
(1.00) 		6.63e-05
(0.0474) 		0.661
(1.00) 		0.56
(1.00) 		0.5
(1.00) 		0.0729
(1.00) 		0.349
(1.00) 		0.0549
(1.00)
16q loss 15 (11%) 116 0.718
(1.00) 		0.31
(1.00) 		0.354
(1.00) 		0.191
(1.00) 		0.946
(1.00) 		7.37e-05
(0.0525) 		0.866
(1.00) 		0.0526
(1.00) 		0.344
(1.00) 		0.578
(1.00)
1p gain 14 (11%) 117 0.0844
(1.00) 		0.49
(1.00) 		0.341
(1.00) 		0.494
(1.00) 		0.385
(1.00) 		0.908
(1.00) 		0.526
(1.00) 		0.0129
(1.00) 		0.66
(1.00) 		0.447
(1.00)
1q gain 28 (21%) 103 0.0303
(1.00) 		0.0209
(1.00) 		0.631
(1.00) 		0.257
(1.00) 		0.704
(1.00) 		0.487
(1.00) 		0.355
(1.00) 		0.266
(1.00) 		0.962
(1.00) 		0.45
(1.00)
2p gain 23 (18%) 108 0.468
(1.00) 		0.853
(1.00) 		0.000384
(0.273) 		0.257
(1.00) 		0.778
(1.00) 		0.626
(1.00) 		0.544
(1.00) 		0.486
(1.00) 		0.501
(1.00) 		0.543
(1.00)
2q gain 10 (8%) 121 0.62
(1.00) 		0.632
(1.00) 		0.712
(1.00) 		0.257
(1.00) 		0.443
(1.00) 		0.455
(1.00) 		0.614
(1.00) 		0.262
(1.00) 		0.316
(1.00) 		0.141
(1.00)
3p gain 28 (21%) 103 0.546
(1.00) 		0.285
(1.00) 		0.337
(1.00) 		0.869
(1.00) 		0.923
(1.00) 		0.942
(1.00) 		0.728
(1.00) 		0.0406
(1.00) 		0.228
(1.00) 		0.0632
(1.00)
3q gain 37 (28%) 94 0.192
(1.00) 		0.405
(1.00) 		0.119
(1.00) 		0.665
(1.00) 		0.673
(1.00) 		0.815
(1.00) 		0.48
(1.00) 		0.0504
(1.00) 		0.223
(1.00) 		0.129
(1.00)
4q gain 3 (2%) 128 0.303
(1.00) 		0.515
(1.00) 		1
(1.00) 		0.284
(1.00) 		0.86
(1.00) 		1
(1.00) 		0.691
(1.00) 		0.402
(1.00)
5p gain 38 (29%) 93 0.755
(1.00) 		0.369
(1.00) 		0.658
(1.00) 		0.0924
(1.00) 		0.417
(1.00) 		0.33
(1.00) 		0.934
(1.00) 		0.00252
(1.00) 		0.0538
(1.00) 		0.375
(1.00)
6p gain 7 (5%) 124 0.237
(1.00) 		0.379
(1.00) 		1
(1.00) 		0.45
(1.00) 		0.989
(1.00) 		0.378
(1.00) 		1
(1.00) 		0.55
(1.00) 		0.00801
(1.00) 		0.802
(1.00)
6q gain 4 (3%) 127 0.249
(1.00) 		0.591
(1.00) 		0.572
(1.00) 		0.778
(1.00) 		0.0663
(1.00) 		0.689
(1.00) 		0.131
(1.00) 		0.0076
(1.00) 		0.566
(1.00)
7p gain 39 (30%) 92 0.497
(1.00) 		0.366
(1.00) 		0.662
(1.00) 		0.141
(1.00) 		0.361
(1.00) 		0.0967
(1.00) 		0.633
(1.00) 		0.208
(1.00) 		0.736
(1.00) 		0.272
(1.00)
7q gain 37 (28%) 94 0.629
(1.00) 		0.518
(1.00) 		0.0454
(1.00) 		0.212
(1.00) 		0.146
(1.00) 		0.407
(1.00) 		0.547
(1.00) 		0.0916
(1.00) 		0.879
(1.00) 		0.326
(1.00)
8p gain 14 (11%) 117 0.902
(1.00) 		0.185
(1.00) 		1
(1.00) 		0.821
(1.00) 		0.214
(1.00) 		0.125
(1.00) 		0.861
(1.00) 		0.615
(1.00) 		0.0016
(1.00) 		0.555
(1.00)
8q gain 35 (27%) 96 0.933
(1.00) 		0.465
(1.00) 		1
(1.00) 		0.315
(1.00) 		0.231
(1.00) 		0.855
(1.00) 		0.706
(1.00) 		0.833
(1.00) 		0.016
(1.00) 		0.195
(1.00)
9p gain 13 (10%) 118 0.037
(1.00) 		0.0242
(1.00) 		0.183
(1.00) 		0.842
(1.00) 		0.0265
(1.00) 		0.0819
(1.00) 		0.431
(1.00) 		0.633
(1.00) 		0.00161
(1.00) 		0.0995
(1.00)
10p gain 26 (20%) 105 0.842
(1.00) 		0.817
(1.00) 		1
(1.00) 		0.593
(1.00) 		0.715
(1.00) 		0.764
(1.00) 		0.65
(1.00) 		0.278
(1.00) 		0.666
(1.00) 		0.0815
(1.00)
10q gain 7 (5%) 124 0.402
(1.00) 		0.113
(1.00) 		1
(1.00) 		0.689
(1.00) 		0.861
(1.00) 		0.392
(1.00) 		0.21
(1.00) 		0.535
(1.00) 		0.275
(1.00)
11p gain 6 (5%) 125 0.0551
(1.00) 		0.109
(1.00) 		0.336
(1.00) 		0.0875
(1.00) 		0.618
(1.00) 		0.204
(1.00) 		0.74
(1.00) 		0.275
(1.00) 		0.1
(1.00) 		0.531
(1.00)
11q gain 6 (5%) 125 0.177
(1.00) 		0.498
(1.00) 		0.336
(1.00) 		0.624
(1.00) 		0.631
(1.00) 		0.577
(1.00) 		1
(1.00) 		0.383
(1.00) 		0.337
(1.00) 		0.687
(1.00)
12p gain 22 (17%) 109 0.939
(1.00) 		0.844
(1.00) 		1
(1.00) 		0.465
(1.00) 		0.944
(1.00) 		0.45
(1.00) 		0.908
(1.00) 		0.957
(1.00) 		0.0205
(1.00) 		0.169
(1.00)
12q gain 17 (13%) 114 0.36
(1.00) 		0.464
(1.00) 		0.237
(1.00) 		0.347
(1.00) 		0.532
(1.00) 		0.847
(1.00) 		0.372
(1.00) 		0.845
(1.00) 		0.0816
(1.00) 		0.0515
(1.00)
13q gain 21 (16%) 110 0.383
(1.00) 		0.597
(1.00) 		1
(1.00) 		0.64
(1.00) 		0.145
(1.00) 		0.935
(1.00) 		0.156
(1.00) 		0.417
(1.00) 		0.871
(1.00) 		0.602
(1.00)
15q gain 4 (3%) 127 0.0836
(1.00) 		0.828
(1.00) 		1
(1.00) 		0.51
(1.00) 		0.248
(1.00) 		0.603
(1.00) 		0.922
(1.00) 		1
(1.00)
16q gain 12 (9%) 119 0.00157
(1.00) 		0.319
(1.00) 		0.0733
(1.00) 		0.468
(1.00) 		0.439
(1.00) 		0.401
(1.00) 		0.369
(1.00) 		0.684
(1.00) 		0.0525
(1.00) 		0.724
(1.00)
17q gain 23 (18%) 108 0.64
(1.00) 		0.917
(1.00) 		1
(1.00) 		0.0421
(1.00) 		0.28
(1.00) 		0.064
(1.00) 		0.204
(1.00) 		0.0652
(1.00) 		0.936
(1.00) 		0.102
(1.00)
18p gain 23 (18%) 108 0.598
(1.00) 		0.654
(1.00) 		0.598
(1.00) 		0.469
(1.00) 		0.375
(1.00) 		0.0722
(1.00) 		0.335
(1.00) 		0.456
(1.00) 		0.666
(1.00) 		0.543
(1.00)
18q gain 7 (5%) 124 0.026
(1.00) 		0.788
(1.00) 		1
(1.00) 		0.848
(1.00) 		0.204
(1.00) 		0.175
(1.00) 		0.889
(1.00) 		0.269
(1.00) 		0.802
(1.00)
19p gain 13 (10%) 118 0.94
(1.00) 		0.876
(1.00) 		1
(1.00) 		0.136
(1.00) 		0.662
(1.00) 		0.507
(1.00) 		1
(1.00) 		0.752
(1.00) 		0.0634
(1.00) 		0.555
(1.00)
19q gain 26 (20%) 105 0.248
(1.00) 		0.951
(1.00) 		0.218
(1.00) 		0.226
(1.00) 		0.575
(1.00) 		0.359
(1.00) 		0.85
(1.00) 		0.839
(1.00) 		0.739
(1.00) 		0.858
(1.00)
20p gain 48 (37%) 83 0.324
(1.00) 		0.844
(1.00) 		0.143
(1.00) 		0.753
(1.00) 		0.435
(1.00) 		0.578
(1.00) 		0.191
(1.00) 		0.803
(1.00) 		0.419
(1.00) 		0.591
(1.00)
20q gain 52 (40%) 79 0.734
(1.00) 		0.4
(1.00) 		1
(1.00) 		0.632
(1.00) 		0.279
(1.00) 		0.0815
(1.00) 		1
(1.00) 		0.923
(1.00) 		0.402
(1.00) 		0.433
(1.00)
21q gain 24 (18%) 107 0.437
(1.00) 		0.216
(1.00) 		1
(1.00) 		0.907
(1.00) 		0.639
(1.00) 		0.756
(1.00) 		0.69
(1.00) 		0.152
(1.00) 		0.929
(1.00) 		0.0205
(1.00)
22q gain 11 (8%) 120 0.0761
(1.00) 		0.544
(1.00) 		0.729
(1.00) 		0.606
(1.00) 		0.487
(1.00) 		0.00709
(1.00) 		0.829
(1.00) 		0.256
(1.00) 		0.54
(1.00) 		0.733
(1.00)
Xq gain 6 (5%) 125 0.351
(1.00) 		0.829
(1.00) 		0.641
(1.00) 		0.503
(1.00) 		0.845
(1.00) 		0.0686
(1.00) 		0.12
(1.00) 		0.723
(1.00) 		0.531
(1.00)
2p loss 7 (5%) 124 0.588
(1.00) 		0.654
(1.00) 		0.679
(1.00) 		0.904
(1.00) 		0.238
(1.00) 		0.535
(1.00) 		0.76
(1.00) 		0.307
(1.00) 		0.328
(1.00)
2q loss 15 (11%) 116 0.0228
(1.00) 		0.652
(1.00) 		0.76
(1.00) 		0.492
(1.00) 		0.251
(1.00) 		0.89
(1.00) 		1
(1.00) 		0.179
(1.00) 		0.253
(1.00) 		0.578
(1.00)
3p loss 9 (7%) 122 0.943
(1.00) 		0.645
(1.00) 		0.228
(1.00) 		0.494
(1.00) 		0.048
(1.00) 		0.804
(1.00) 		0.557
(1.00) 		0.862
(1.00) 		0.919
(1.00)
4p loss 25 (19%) 106 0.503
(1.00) 		0.922
(1.00) 		1
(1.00) 		0.0948
(1.00) 		0.541
(1.00) 		0.871
(1.00) 		0.183
(1.00) 		0.0338
(1.00) 		0.261
(1.00) 		0.358
(1.00)
4q loss 23 (18%) 108 0.71
(1.00) 		0.825
(1.00) 		0.795
(1.00) 		0.0948
(1.00) 		0.951
(1.00) 		0.925
(1.00) 		0.204
(1.00) 		0.839
(1.00) 		0.721
(1.00) 		0.422
(1.00)
5p loss 12 (9%) 119 0.38
(1.00) 		0.325
(1.00) 		0.177
(1.00) 		0.0998
(1.00) 		0.976
(1.00) 		0.152
(1.00) 		0.829
(1.00) 		0.97
(1.00) 		0.787
(1.00) 		0.151
(1.00)
5q loss 32 (24%) 99 0.998
(1.00) 		0.335
(1.00) 		0.815
(1.00) 		0.666
(1.00) 		0.262
(1.00) 		0.18
(1.00) 		0.135
(1.00) 		0.381
(1.00) 		0.378
(1.00) 		0.286
(1.00)
6q loss 27 (21%) 104 0.428
(1.00) 		0.874
(1.00) 		0.62
(1.00) 		0.242
(1.00) 		0.352
(1.00) 		0.029
(1.00) 		0.117
(1.00) 		0.129
(1.00) 		0.235
(1.00) 		0.0253
(1.00)
8p loss 47 (36%) 84 0.233
(1.00) 		0.575
(1.00) 		0.296
(1.00) 		0.29
(1.00) 		0.162
(1.00) 		1
(1.00) 		0.0183
(1.00) 		0.347
(1.00) 		0.552
(1.00) 		0.272
(1.00)
8q loss 5 (4%) 126 0.531
(1.00) 		0.0862
(1.00) 		0.599
(1.00) 		0.883
(1.00) 		0.697
(1.00) 		0.106
(1.00) 		0.767
(1.00) 		0.26
(1.00) 		0.473
(1.00)
9p loss 38 (29%) 93 0.955
(1.00) 		0.517
(1.00) 		0.278
(1.00) 		0.743
(1.00) 		0.284
(1.00) 		0.167
(1.00) 		0.182
(1.00) 		0.722
(1.00) 		0.892
(1.00) 		0.663
(1.00)
9q loss 36 (27%) 95 0.812
(1.00) 		0.876
(1.00) 		0.185
(1.00) 		0.651
(1.00) 		0.198
(1.00) 		0.444
(1.00) 		0.54
(1.00) 		0.606
(1.00) 		0.0671
(1.00) 		0.614
(1.00)
10p loss 18 (14%) 113 0.481
(1.00) 		0.896
(1.00) 		1
(1.00) 		0.0186
(1.00) 		0.804
(1.00) 		0.0333
(1.00) 		0.264
(1.00) 		0.809
(1.00) 		0.0409
(1.00) 		0.839
(1.00)
10q loss 26 (20%) 105 0.427
(1.00) 		0.0231
(1.00) 		0.805
(1.00) 		0.134
(1.00) 		0.744
(1.00) 		0.238
(1.00) 		0.924
(1.00) 		0.719
(1.00) 		0.849
(1.00) 		0.7
(1.00)
11p loss 43 (33%) 88 0.617
(1.00) 		0.218
(1.00) 		0.67
(1.00) 		0.0359
(1.00) 		0.982
(1.00) 		0.747
(1.00) 		0.0437
(1.00) 		0.771
(1.00) 		0.241
(1.00) 		0.0363
(1.00)
11q loss 32 (24%) 99 0.715
(1.00) 		0.53
(1.00) 		0.815
(1.00) 		0.708
(1.00) 		0.325
(1.00) 		0.486
(1.00) 		0.261
(1.00) 		0.268
(1.00) 		0.203
(1.00) 		0.537
(1.00)
12p loss 5 (4%) 126 0.937
(1.00) 		0.298
(1.00) 		0.33
(1.00) 		0.678
(1.00) 		0.173
(1.00) 		1
(1.00) 		0.767
(1.00) 		0.877
(1.00) 		0.862
(1.00)
12q loss 8 (6%) 123 0.102
(1.00) 		0.75
(1.00) 		0.679
(1.00) 		0.528
(1.00) 		0.923
(1.00) 		0.947
(1.00) 		1
(1.00) 		0.199
(1.00) 		0.515
(1.00) 		0.906
(1.00)
13q loss 18 (14%) 113 0.874
(1.00) 		0.685
(1.00) 		0.24
(1.00) 		0.0159
(1.00) 		0.723
(1.00) 		0.0649
(1.00) 		0.786
(1.00) 		0.813
(1.00) 		0.582
(1.00) 		0.559
(1.00)
14q loss 22 (17%) 109 0.21
(1.00) 		0.241
(1.00) 		0.28
(1.00) 		0.772
(1.00) 		0.719
(1.00) 		0.827
(1.00) 		0.741
(1.00) 		0.546
(1.00) 		0.676
(1.00) 		0.149
(1.00)
15q loss 15 (11%) 116 0.472
(1.00) 		0.824
(1.00) 		0.528
(1.00) 		0.763
(1.00) 		0.883
(1.00) 		0.194
(1.00) 		0.12
(1.00) 		0.956
(1.00) 		0.946
(1.00) 		0.672
(1.00)
16p loss 14 (11%) 117 0.459
(1.00) 		0.205
(1.00) 		0.188
(1.00) 		0.0945
(1.00) 		0.443
(1.00) 		0.00404
(1.00) 		0.861
(1.00) 		0.554
(1.00) 		0.976
(1.00) 		0.832
(1.00)
17p loss 36 (27%) 95 0.347
(1.00) 		0.712
(1.00) 		0.659
(1.00) 		0.856
(1.00) 		0.358
(1.00) 		0.663
(1.00) 		0.375
(1.00) 		0.556
(1.00) 		0.706
(1.00) 		0.73
(1.00)
17q loss 5 (4%) 126 0.887
(1.00) 		0.407
(1.00) 		1
(1.00) 		0.77
(1.00) 		0.526
(1.00) 		1
(1.00) 		1
(1.00) 		0.0281
(1.00) 		0.46
(1.00)
18p loss 19 (15%) 112 0.162
(1.00) 		0.0506
(1.00) 		0.568
(1.00) 		0.295
(1.00) 		0.674
(1.00) 		0.966
(1.00) 		0.713
(1.00) 		0.718
(1.00) 		0.855
(1.00) 		0.495
(1.00)
18q loss 36 (27%) 95 0.0375
(1.00) 		0.0232
(1.00) 		0.259
(1.00) 		0.57
(1.00) 		0.379
(1.00) 		0.412
(1.00) 		0.806
(1.00) 		0.92
(1.00) 		0.897
(1.00) 		0.336
(1.00)
19p loss 8 (6%) 123 0.341
(1.00) 		0.913
(1.00) 		1
(1.00) 		0.929
(1.00) 		0.307
(1.00) 		0.00531
(1.00) 		0.0237
(1.00) 		0.265
(1.00) 		0.0237
(1.00)
19q loss 3 (2%) 128 0.000889
(0.631) 		0.9
(1.00) 		0.572
(1.00) 		0.399
(1.00) 		0.604
(1.00) 		0.677
(1.00) 		0.692
(1.00) 		0.781
(1.00)
20p loss 5 (4%) 126 0.834
(1.00) 		0.223
(1.00) 		1
(1.00) 		0.00596
(1.00) 		0.402
(1.00) 		1
(1.00) 		0.885
(1.00) 		0.724
(1.00) 		1
(1.00)
21q loss 14 (11%) 117 0.996
(1.00) 		0.0204
(1.00) 		0.75
(1.00) 		0.383
(1.00) 		0.894
(1.00) 		0.961
(1.00) 		0.33
(1.00) 		0.174
(1.00) 		0.697
(1.00) 		0.465
(1.00)
22q loss 25 (19%) 106 0.115
(1.00) 		0.518
(1.00) 		0.799
(1.00) 		0.187
(1.00) 		0.808
(1.00) 		0.109
(1.00) 		0.119
(1.00) 		0.311
(1.00) 		0.627
(1.00) 		0.583
(1.00)
Xq loss 4 (3%) 127 0.31
(1.00) 		0.714
(1.00) 		1
(1.00) 		0.349
(1.00) 		0.602
(1.00) 		1
(1.00) 		0.00471
(1.00) 		0.0305
(1.00)
'4p gain mutation analysis' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000201 (t-test), Q value = 0.14

Table S1.  Gene #7: '4p gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 98 1.9 (3.8)
4P GAIN MUTATED 5 0.2 (0.4)
4P GAIN WILD-TYPE 93 2.0 (3.8)

Figure S1.  Get High-res Image Gene #7: '4p gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'5q gain mutation analysis' versus 'NUMBER.OF.LYMPH.NODES'

P value = 7.18e-05 (t-test), Q value = 0.051

Table S2.  Gene #10: '5q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 98 1.9 (3.8)
5Q GAIN MUTATED 12 0.2 (0.5)
5Q GAIN WILD-TYPE 86 2.1 (4.0)

Figure S2.  Get High-res Image Gene #10: '5q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'9q gain mutation analysis' versus 'NUMBER.OF.LYMPH.NODES'

P value = 2.87e-06 (t-test), Q value = 0.0021

Table S3.  Gene #18: '9q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 98 1.9 (3.8)
9Q GAIN MUTATED 9 0.0 (0.0)
9Q GAIN WILD-TYPE 89 2.1 (3.9)

Figure S3.  Get High-res Image Gene #18: '9q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'14q gain mutation analysis' versus 'NUMBER.OF.LYMPH.NODES'

P value = 7.1e-05 (t-test), Q value = 0.051

Table S4.  Gene #26: '14q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 98 1.9 (3.8)
14Q GAIN MUTATED 6 0.2 (0.4)
14Q GAIN WILD-TYPE 92 2.0 (3.9)

Figure S4.  Get High-res Image Gene #26: '14q gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'16p gain mutation analysis' versus 'Time to Death'

P value = 4.1e-05 (logrank test), Q value = 0.029

Table S5.  Gene #28: '16p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 124 32 0.1 - 131.2 (7.0)
16P GAIN MUTATED 10 5 0.8 - 9.7 (4.5)
16P GAIN WILD-TYPE 114 27 0.1 - 131.2 (7.1)

Figure S5.  Get High-res Image Gene #28: '16p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'17p gain mutation analysis' versus 'NUMBER.OF.LYMPH.NODES'

P value = 3.04e-06 (t-test), Q value = 0.0022

Table S6.  Gene #30: '17p gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 98 1.9 (3.8)
17P GAIN MUTATED 5 0.0 (0.0)
17P GAIN WILD-TYPE 93 2.0 (3.8)

Figure S6.  Get High-res Image Gene #30: '17p gain mutation analysis' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'6p loss mutation analysis' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 6.63e-05 (t-test), Q value = 0.047

Table S7.  Gene #48: '6p loss mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

nPatients Mean (Std.Dev)
ALL 37 78.1 (16.3)
6P LOSS MUTATED 4 90.0 (0.0)
6P LOSS WILD-TYPE 33 76.7 (16.7)

Figure S7.  Get High-res Image Gene #48: '6p loss mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

'16q loss mutation analysis' versus 'TOBACCOSMOKINGHISTORYINDICATOR'

P value = 7.37e-05 (t-test), Q value = 0.053

Table S8.  Gene #64: '16q loss mutation analysis' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

nPatients Mean (Std.Dev)
ALL 125 2.6 (1.1)
16Q LOSS MUTATED 15 3.4 (0.6)
16Q LOSS WILD-TYPE 110 2.5 (1.1)

Figure S8.  Get High-res Image Gene #64: '16q loss mutation analysis' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

Methods & Data
Input

  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Clinical data file = BLCA-TP.clin.merged.picked.txt

  • Number of patients = 131

  • Number of significantly arm-level cnvs = 74

  • 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

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[5] 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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