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 73 arm-level results and 7 clinical features across 114 patients, 5 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'GENDER'.

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

  • 16q loss cnv correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

  • 21q loss cnv correlated to 'AGE' and 'KARNOFSKY.PERFORMANCE.SCORE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 73 arm-level results and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 5 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER KARNOFSKY
PERFORMANCE
SCORE 		NUMBERPACKYEARSSMOKED STOPPEDSMOKINGYEAR TOBACCOSMOKINGHISTORYINDICATOR
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test t-test t-test t-test
21q loss 11 (10%) 103 0.603
(1.00) 		0.000289
(0.14) 		1
(1.00) 		8.23e-05
(0.0402) 		0.787
(1.00) 		0.182
(1.00) 		0.743
(1.00)
2p gain 22 (19%) 92 0.358
(1.00) 		0.91
(1.00) 		0.000438
(0.212) 		0.228
(1.00) 		0.679
(1.00) 		0.00891
(1.00) 		0.596
(1.00)
6p loss 15 (13%) 99 0.986
(1.00) 		0.49
(1.00) 		0.547
(1.00) 		8.85e-05
(0.0431) 		0.681
(1.00) 		0.937
(1.00) 		0.538
(1.00)
16q loss 14 (12%) 100 0.802
(1.00) 		0.253
(1.00) 		0.344
(1.00) 		0.167
(1.00) 		0.728
(1.00) 		0.175
(1.00) 		0.000181
(0.0878)
1p gain 13 (11%) 101 0.134
(1.00) 		0.16
(1.00) 		1
(1.00) 		0.214
(1.00) 		0.685
(1.00) 		0.534
(1.00) 		0.281
(1.00)
1q gain 24 (21%) 90 0.0241
(1.00) 		0.0129
(1.00) 		0.801
(1.00) 		0.228
(1.00) 		0.708
(1.00) 		0.211
(1.00) 		0.0602
(1.00)
2q gain 9 (8%) 105 0.562
(1.00) 		0.535
(1.00) 		0.702
(1.00) 		0.228
(1.00) 		0.465
(1.00) 		0.00189
(0.909) 		0.409
(1.00)
3p gain 25 (22%) 89 0.406
(1.00) 		0.348
(1.00) 		0.311
(1.00) 		0.954
(1.00) 		0.646
(1.00) 		0.653
(1.00) 		0.898
(1.00)
3q gain 33 (29%) 81 0.123
(1.00) 		0.208
(1.00) 		0.171
(1.00) 		0.752
(1.00) 		0.644
(1.00) 		0.264
(1.00) 		0.939
(1.00)
4p gain 8 (7%) 106 0.0663
(1.00) 		0.839
(1.00) 		0.444
(1.00) 		0.239
(1.00) 		0.95
(1.00) 		0.673
(1.00)
4q gain 3 (3%) 111 0.289
(1.00) 		0.506
(1.00) 		1
(1.00) 		0.215
(1.00) 		0.941
(1.00)
5p gain 34 (30%) 80 0.665
(1.00) 		0.298
(1.00) 		0.363
(1.00) 		0.107
(1.00) 		0.609
(1.00) 		0.452
(1.00) 		0.494
(1.00)
5q gain 16 (14%) 98 0.286
(1.00) 		0.421
(1.00) 		0.228
(1.00) 		0.282
(1.00) 		0.721
(1.00) 		0.74
(1.00) 		0.634
(1.00)
6p gain 7 (6%) 107 0.0847
(1.00) 		0.589
(1.00) 		1
(1.00) 		0.462
(1.00) 		0.742
(1.00) 		0.457
(1.00) 		0.421
(1.00)
6q gain 4 (4%) 110 0.0893
(1.00) 		0.97
(1.00) 		0.573
(1.00) 		0.917
(1.00) 		0.988
(1.00) 		0.0765
(1.00)
7p gain 35 (31%) 79 0.387
(1.00) 		0.561
(1.00) 		0.503
(1.00) 		0.16
(1.00) 		0.768
(1.00) 		0.81
(1.00) 		0.173
(1.00)
7q gain 35 (31%) 79 0.718
(1.00) 		0.643
(1.00) 		0.0664
(1.00) 		0.242
(1.00) 		0.233
(1.00) 		0.849
(1.00) 		0.38
(1.00)
8p gain 14 (12%) 100 0.994
(1.00) 		0.189
(1.00) 		0.755
(1.00) 		0.853
(1.00) 		0.13
(1.00) 		0.0497
(1.00) 		0.152
(1.00)
8q gain 33 (29%) 81 0.554
(1.00) 		0.37
(1.00) 		1
(1.00) 		0.342
(1.00) 		0.281
(1.00) 		0.463
(1.00) 		0.774
(1.00)
9p gain 13 (11%) 101 0.0226
(1.00) 		0.0252
(1.00) 		0.111
(1.00) 		0.809
(1.00) 		0.065
(1.00) 		0.704
(1.00) 		0.113
(1.00)
9q gain 11 (10%) 103 0.0616
(1.00) 		0.266
(1.00) 		0.487
(1.00) 		0.802
(1.00) 		0.0692
(1.00) 		0.257
(1.00) 		0.71
(1.00)
10p gain 24 (21%) 90 0.39
(1.00) 		0.934
(1.00) 		1
(1.00) 		0.83
(1.00) 		0.53
(1.00) 		0.303
(1.00) 		0.652
(1.00)
10q gain 7 (6%) 107 0.453
(1.00) 		0.114
(1.00) 		1
(1.00) 		0.571
(1.00) 		0.364
(1.00) 		0.807
(1.00)
11p gain 6 (5%) 108 0.0881
(1.00) 		0.113
(1.00) 		0.187
(1.00) 		0.0762
(1.00) 		0.506
(1.00) 		0.0695
(1.00) 		0.23
(1.00)
11q gain 7 (6%) 107 0.389
(1.00) 		0.31
(1.00) 		0.187
(1.00) 		0.817
(1.00) 		0.837
(1.00) 		0.437
(1.00) 		0.535
(1.00)
12p gain 22 (19%) 92 0.806
(1.00) 		0.804
(1.00) 		0.791
(1.00) 		0.491
(1.00) 		0.734
(1.00) 		0.514
(1.00) 		0.561
(1.00)
12q gain 17 (15%) 97 0.268
(1.00) 		0.48
(1.00) 		0.149
(1.00) 		0.361
(1.00) 		0.82
(1.00) 		0.423
(1.00) 		0.973
(1.00)
13q gain 19 (17%) 95 0.366
(1.00) 		0.738
(1.00) 		1
(1.00) 		0.575
(1.00) 		0.255
(1.00) 		0.88
(1.00) 		0.647
(1.00)
14q gain 10 (9%) 104 0.6
(1.00) 		0.81
(1.00) 		0.456
(1.00) 		0.497
(1.00) 		0.254
(1.00) 		0.527
(1.00) 		0.383
(1.00)
15q gain 4 (4%) 110 0.111
(1.00) 		0.817
(1.00) 		1
(1.00) 		0.466
(1.00)
16p gain 9 (8%) 105 0.00107
(0.518) 		0.388
(1.00) 		0.252
(1.00) 		0.638
(1.00) 		0.2
(1.00) 		0.304
(1.00)
16q gain 11 (10%) 103 0.0252
(1.00) 		0.272
(1.00) 		0.0671
(1.00) 		0.495
(1.00) 		0.37
(1.00) 		0.848
(1.00) 		0.269
(1.00)
17p gain 8 (7%) 106 0.506
(1.00) 		0.982
(1.00) 		0.681
(1.00) 		0.813
(1.00) 		0.618
(1.00) 		0.973
(1.00)
17q gain 19 (17%) 95 0.603
(1.00) 		0.532
(1.00) 		0.778
(1.00) 		0.0871
(1.00) 		0.482
(1.00) 		0.47
(1.00) 		0.277
(1.00)
18p gain 21 (18%) 93 0.743
(1.00) 		0.778
(1.00) 		0.588
(1.00) 		0.431
(1.00) 		0.246
(1.00) 		0.316
(1.00) 		0.0822
(1.00)
18q gain 7 (6%) 107 0.0485
(1.00) 		0.807
(1.00) 		1
(1.00) 		0.628
(1.00) 		0.525
(1.00) 		0.23
(1.00)
19p gain 13 (11%) 101 0.828
(1.00) 		0.904
(1.00) 		1
(1.00) 		0.117
(1.00) 		0.498
(1.00) 		0.551
(1.00) 		0.571
(1.00)
19q gain 26 (23%) 88 0.18
(1.00) 		0.889
(1.00) 		0.329
(1.00) 		0.179
(1.00) 		0.182
(1.00) 		0.479
(1.00) 		0.449
(1.00)
20p gain 47 (41%) 67 0.66
(1.00) 		0.916
(1.00) 		0.395
(1.00) 		0.674
(1.00) 		0.111
(1.00) 		0.174
(1.00) 		0.831
(1.00)
20q gain 48 (42%) 66 0.47
(1.00) 		0.361
(1.00) 		0.677
(1.00) 		0.705
(1.00) 		0.0458
(1.00) 		0.163
(1.00) 		0.11
(1.00)
21q gain 22 (19%) 92 0.287
(1.00) 		0.268
(1.00) 		1
(1.00) 		0.849
(1.00) 		0.442
(1.00) 		0.673
(1.00) 		0.851
(1.00)
22q gain 11 (10%) 103 0.0625
(1.00) 		0.556
(1.00) 		0.724
(1.00) 		0.562
(1.00) 		0.34
(1.00) 		0.205
(1.00) 		0.00924
(1.00)
Xq gain 6 (5%) 108 0.607
(1.00) 		0.678
(1.00) 		0.663
(1.00) 		0.377
(1.00) 		0.488
(1.00)
2p loss 7 (6%) 107 0.643
(1.00) 		0.666
(1.00) 		0.672
(1.00) 		0.827
(1.00) 		0.191
(1.00) 		0.903
(1.00) 		0.596
(1.00)
2q loss 15 (13%) 99 0.0373
(1.00) 		0.626
(1.00) 		0.756
(1.00) 		0.549
(1.00) 		0.168
(1.00) 		0.934
(1.00) 		0.99
(1.00)
3p loss 9 (8%) 105 0.962
(1.00) 		0.671
(1.00) 		0.252
(1.00) 		0.366
(1.00) 		0.77
(1.00) 		0.0635
(1.00)
4p loss 22 (19%) 92 0.576
(1.00) 		0.811
(1.00) 		1
(1.00) 		0.0813
(1.00) 		0.591
(1.00) 		0.608
(1.00) 		0.791
(1.00)
4q loss 21 (18%) 93 0.786
(1.00) 		0.881
(1.00) 		0.792
(1.00) 		0.0813
(1.00) 		0.856
(1.00) 		0.409
(1.00) 		0.835
(1.00)
5p loss 12 (11%) 102 0.318
(1.00) 		0.305
(1.00) 		0.303
(1.00) 		0.0871
(1.00) 		0.858
(1.00) 		0.212
(1.00) 		0.118
(1.00)
5q loss 26 (23%) 88 0.568
(1.00) 		0.375
(1.00) 		1
(1.00) 		0.811
(1.00) 		0.0918
(1.00) 		0.574
(1.00) 		0.261
(1.00)
6q loss 26 (23%) 88 0.318
(1.00) 		0.838
(1.00) 		0.625
(1.00) 		0.21
(1.00) 		0.138
(1.00) 		0.202
(1.00) 		0.0661
(1.00)
8p loss 39 (34%) 75 0.0745
(1.00) 		0.96
(1.00) 		0.515
(1.00) 		0.248
(1.00) 		0.477
(1.00) 		0.276
(1.00) 		0.82
(1.00)
8q loss 4 (4%) 110 0.551
(1.00) 		0.136
(1.00) 		0.298
(1.00) 		0.86
(1.00) 		0.664
(1.00) 		0.868
(1.00)
9p loss 36 (32%) 78 0.776
(1.00) 		0.527
(1.00) 		0.26
(1.00) 		0.809
(1.00) 		0.287
(1.00) 		0.352
(1.00) 		0.14
(1.00)
9q loss 34 (30%) 80 0.64
(1.00) 		0.896
(1.00) 		0.17
(1.00) 		0.726
(1.00) 		0.187
(1.00) 		0.524
(1.00) 		0.41
(1.00)
10p loss 18 (16%) 96 0.525
(1.00) 		0.957
(1.00) 		0.776
(1.00) 		0.0164
(1.00) 		0.541
(1.00) 		0.525
(1.00) 		0.00369
(1.00)
10q loss 24 (21%) 90 0.505
(1.00) 		0.0518
(1.00) 		0.801
(1.00) 		0.192
(1.00) 		0.503
(1.00) 		0.825
(1.00) 		0.0536
(1.00)
11p loss 39 (34%) 75 0.437
(1.00) 		0.155
(1.00) 		0.658
(1.00) 		0.04
(1.00) 		0.695
(1.00) 		0.84
(1.00) 		0.732
(1.00)
11q loss 29 (25%) 85 0.83
(1.00) 		0.613
(1.00) 		0.81
(1.00) 		0.747
(1.00) 		0.253
(1.00) 		0.57
(1.00) 		0.499
(1.00)
12p loss 5 (4%) 109 0.986
(1.00) 		0.309
(1.00) 		0.321
(1.00) 		0.905
(1.00) 		0.195
(1.00)
12q loss 8 (7%) 106 0.126
(1.00) 		0.778
(1.00) 		0.444
(1.00) 		0.545
(1.00) 		0.824
(1.00) 		0.877
(1.00) 		0.97
(1.00)
13q loss 16 (14%) 98 0.799
(1.00) 		0.695
(1.00) 		0.228
(1.00) 		0.0137
(1.00) 		0.666
(1.00) 		0.658
(1.00) 		0.00728
(1.00)
14q loss 19 (17%) 95 0.216
(1.00) 		0.479
(1.00) 		0.271
(1.00) 		0.725
(1.00) 		0.0781
(1.00) 		0.0562
(1.00) 		0.789
(1.00)
15q loss 14 (12%) 100 0.196
(1.00) 		0.893
(1.00) 		0.523
(1.00) 		0.761
(1.00) 		0.703
(1.00) 		0.936
(1.00) 		0.271
(1.00)
16p loss 13 (11%) 101 0.39
(1.00) 		0.162
(1.00) 		0.111
(1.00) 		0.0815
(1.00) 		0.641
(1.00) 		0.733
(1.00) 		0.00886
(1.00)
17p loss 35 (31%) 79 0.232
(1.00) 		0.773
(1.00) 		0.823
(1.00) 		0.76
(1.00) 		0.232
(1.00) 		0.936
(1.00) 		0.565
(1.00)
17q loss 5 (4%) 109 0.812
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.725
(1.00) 		0.611
(1.00) 		0.885
(1.00)
18p loss 18 (16%) 96 0.114
(1.00) 		0.0547
(1.00) 		0.568
(1.00) 		0.31
(1.00) 		0.499
(1.00) 		0.379
(1.00) 		0.797
(1.00)
18q loss 33 (29%) 81 0.0173
(1.00) 		0.043
(1.00) 		0.171
(1.00) 		0.637
(1.00) 		0.554
(1.00) 		0.233
(1.00) 		0.242
(1.00)
19p loss 7 (6%) 107 0.938
(1.00) 		0.672
(1.00) 		1
(1.00) 		0.332
(1.00) 		0.184
(1.00) 		0.499
(1.00)
19q loss 4 (4%) 110 0.339
(1.00) 		0.777
(1.00) 		0.573
(1.00) 		0.373
(1.00)
20p loss 4 (4%) 110 0.897
(1.00) 		0.24
(1.00) 		1
(1.00) 		0.0395
(1.00) 		0.107
(1.00) 		0.679
(1.00)
22q loss 23 (20%) 91 0.192
(1.00) 		0.601
(1.00) 		0.794
(1.00) 		0.162
(1.00) 		0.63
(1.00) 		0.998
(1.00) 		0.084
(1.00)
'2p gain mutation analysis' versus 'GENDER'

P value = 0.000438 (Fisher's exact test), Q value = 0.21

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

nPatients FEMALE MALE
ALL 31 83
2P GAIN MUTATED 13 9
2P GAIN WILD-TYPE 18 74

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

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

P value = 8.85e-05 (t-test), Q value = 0.043

Table S2.  Gene #48: '6p loss mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

nPatients Mean (Std.Dev)
ALL 35 77.7 (16.6)
6P LOSS MUTATED 4 90.0 (0.0)
6P LOSS WILD-TYPE 31 76.1 (17.1)

Figure S2.  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 = 0.000181 (t-test), Q value = 0.088

Table S3.  Gene #64: '16q loss mutation analysis' versus Clinical Feature #7: 'TOBACCOSMOKINGHISTORYINDICATOR'

nPatients Mean (Std.Dev)
ALL 108 2.6 (1.1)
16Q LOSS MUTATED 14 3.4 (0.6)
16Q LOSS WILD-TYPE 94 2.5 (1.2)

Figure S3.  Get High-res Image Gene #64: '16q loss mutation analysis' versus Clinical Feature #7: 'TOBACCOSMOKINGHISTORYINDICATOR'

'21q loss mutation analysis' versus 'AGE'

P value = 0.000289 (t-test), Q value = 0.14

Table S4.  Gene #72: '21q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 113 67.2 (11.1)
21Q LOSS MUTATED 11 58.5 (6.2)
21Q LOSS WILD-TYPE 102 68.2 (11.1)

Figure S4.  Get High-res Image Gene #72: '21q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'21q loss mutation analysis' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 8.23e-05 (t-test), Q value = 0.04

Table S5.  Gene #72: '21q loss mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

nPatients Mean (Std.Dev)
ALL 35 77.7 (16.6)
21Q LOSS MUTATED 5 90.0 (0.0)
21Q LOSS WILD-TYPE 30 75.7 (17.2)

Figure S5.  Get High-res Image Gene #72: '21q loss mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

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 = 114

  • Number of significantly arm-level cnvs = 73

  • Number of selected clinical features = 7

  • 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

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] 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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle