Breast Invasive Carcinoma: Correlation between copy number variations of arm-level result and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/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 78 arm-level results and 5 clinical features across 820 patients, 4 significant findings detected with Q value < 0.25.

  • 7q gain cnv correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION' and 'NEOADJUVANT.THERAPY'.

  • 1p loss cnv correlated to 'AGE'.

  • 16q loss cnv correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 78 arm-level results and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 4 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER RADIATIONS
RADIATION
REGIMENINDICATION 		NEOADJUVANT
THERAPY
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Fisher's exact test
7q gain 120 (15%) 700 0.366
(1.00) 		0.964
(1.00) 		0.0304
(1.00) 		0.000157
(0.061) 		0.000432
(0.167)
1p loss 120 (15%) 700 0.13
(1.00) 		3.17e-05
(0.0124) 		1
(1.00) 		0.198
(1.00) 		0.0639
(1.00)
16q loss 357 (44%) 463 0.326
(1.00) 		0.000191
(0.0742) 		0.513
(1.00) 		0.0671
(1.00) 		0.884
(1.00)
1p gain 102 (12%) 718 0.446
(1.00) 		0.187
(1.00) 		1
(1.00) 		0.316
(1.00) 		0.509
(1.00)
1q gain 470 (57%) 350 0.0147
(1.00) 		0.989
(1.00) 		0.74
(1.00) 		0.212
(1.00) 		1
(1.00)
2p gain 56 (7%) 764 0.893
(1.00) 		0.788
(1.00) 		1
(1.00) 		0.329
(1.00) 		0.666
(1.00)
2q gain 30 (4%) 790 0.396
(1.00) 		0.27
(1.00) 		1
(1.00) 		0.0443
(1.00) 		0.44
(1.00)
3p gain 43 (5%) 777 0.116
(1.00) 		0.101
(1.00) 		1
(1.00) 		0.269
(1.00) 		0.872
(1.00)
3q gain 107 (13%) 713 0.467
(1.00) 		0.811
(1.00) 		1
(1.00) 		0.713
(1.00) 		0.334
(1.00)
4p gain 33 (4%) 787 0.114
(1.00) 		0.55
(1.00) 		1
(1.00) 		1
(1.00) 		0.356
(1.00)
4q gain 29 (4%) 791 0.0321
(1.00) 		0.515
(1.00) 		1
(1.00) 		1
(1.00) 		0.846
(1.00)
5p gain 168 (20%) 652 0.55
(1.00) 		0.05
(1.00) 		1
(1.00) 		0.0184
(1.00) 		0.207
(1.00)
5q gain 96 (12%) 724 0.785
(1.00) 		0.00473
(1.00) 		1
(1.00) 		0.0097
(1.00) 		0.175
(1.00)
6p gain 108 (13%) 712 0.903
(1.00) 		0.645
(1.00) 		1
(1.00) 		0.178
(1.00) 		0.914
(1.00)
6q gain 66 (8%) 754 0.059
(1.00) 		0.19
(1.00) 		0.532
(1.00) 		0.448
(1.00) 		0.505
(1.00)
7p gain 155 (19%) 665 0.777
(1.00) 		0.169
(1.00) 		0.0149
(1.00) 		0.00145
(0.559) 		0.00694
(1.00)
8p gain 177 (22%) 643 0.876
(1.00) 		0.0343
(1.00) 		1
(1.00) 		0.366
(1.00) 		0.724
(1.00)
8q gain 385 (47%) 435 0.35
(1.00) 		0.0471
(1.00) 		0.319
(1.00) 		0.0313
(1.00) 		0.0811
(1.00)
9p gain 64 (8%) 756 0.135
(1.00) 		0.514
(1.00) 		1
(1.00) 		0.0656
(1.00) 		0.222
(1.00)
9q gain 49 (6%) 771 0.927
(1.00) 		0.501
(1.00) 		0.427
(1.00) 		0.223
(1.00) 		0.358
(1.00)
10p gain 118 (14%) 702 0.73
(1.00) 		0.686
(1.00) 		0.372
(1.00) 		0.197
(1.00) 		0.679
(1.00)
10q gain 35 (4%) 785 0.778
(1.00) 		0.302
(1.00) 		1
(1.00) 		0.421
(1.00) 		0.28
(1.00)
11p gain 46 (6%) 774 0.687
(1.00) 		0.755
(1.00) 		0.407
(1.00) 		0.859
(1.00) 		1
(1.00)
11q gain 40 (5%) 780 0.0056
(1.00) 		0.0787
(1.00) 		1
(1.00) 		0.447
(1.00) 		0.501
(1.00)
12p gain 106 (13%) 714 0.483
(1.00) 		0.133
(1.00) 		0.328
(1.00) 		0.0842
(1.00) 		0.449
(1.00)
12q gain 89 (11%) 731 0.614
(1.00) 		0.0171
(1.00) 		0.0107
(1.00) 		0.288
(1.00) 		0.726
(1.00)
13q gain 45 (5%) 775 0.0254
(1.00) 		0.884
(1.00) 		1
(1.00) 		0.276
(1.00) 		0.203
(1.00)
14q gain 70 (9%) 750 0.406
(1.00) 		0.902
(1.00) 		1
(1.00) 		0.882
(1.00) 		0.796
(1.00)
15q gain 40 (5%) 780 0.782
(1.00) 		0.687
(1.00) 		0.364
(1.00) 		0.337
(1.00) 		0.24
(1.00)
16p gain 247 (30%) 573 0.139
(1.00) 		0.0235
(1.00) 		0.731
(1.00) 		0.53
(1.00) 		0.635
(1.00)
16q gain 61 (7%) 759 0.0644
(1.00) 		0.325
(1.00) 		0.503
(1.00) 		0.637
(1.00) 		0.212
(1.00)
17p gain 50 (6%) 770 0.369
(1.00) 		0.23
(1.00) 		0.0997
(1.00) 		0.393
(1.00) 		0.879
(1.00)
17q gain 146 (18%) 674 0.715
(1.00) 		0.794
(1.00) 		0.0115
(1.00) 		0.589
(1.00) 		0.107
(1.00)
18p gain 74 (9%) 746 0.0838
(1.00) 		0.0487
(1.00) 		0.575
(1.00) 		0.00879
(1.00) 		0.8
(1.00)
18q gain 68 (8%) 752 0.249
(1.00) 		0.424
(1.00) 		0.543
(1.00) 		0.0235
(1.00) 		0.792
(1.00)
19p gain 67 (8%) 753 0.108
(1.00) 		0.934
(1.00) 		0.163
(1.00) 		0.295
(1.00) 		0.598
(1.00)
19q gain 86 (10%) 734 0.218
(1.00) 		0.809
(1.00) 		0.242
(1.00) 		0.137
(1.00) 		0.637
(1.00)
20p gain 204 (25%) 616 0.0931
(1.00) 		0.284
(1.00) 		0.237
(1.00) 		0.924
(1.00) 		0.801
(1.00)
20q gain 256 (31%) 564 0.158
(1.00) 		0.801
(1.00) 		0.147
(1.00) 		0.929
(1.00) 		0.638
(1.00)
21q gain 102 (12%) 718 0.0915
(1.00) 		0.122
(1.00) 		1
(1.00) 		0.133
(1.00) 		0.509
(1.00)
22q gain 34 (4%) 786 0.551
(1.00) 		0.102
(1.00) 		1
(1.00) 		0.301
(1.00) 		0.469
(1.00)
1q loss 20 (2%) 800 0.313
(1.00) 		0.032
(1.00) 		1
(1.00) 		0.591
(1.00) 		1
(1.00)
2p loss 66 (8%) 754 0.776
(1.00) 		0.343
(1.00) 		1
(1.00) 		0.879
(1.00) 		0.69
(1.00)
2q loss 80 (10%) 740 0.559
(1.00) 		0.857
(1.00) 		1
(1.00) 		0.489
(1.00) 		0.903
(1.00)
3p loss 132 (16%) 688 0.0786
(1.00) 		0.0276
(1.00) 		1
(1.00) 		1
(1.00) 		0.768
(1.00)
3q loss 47 (6%) 773 0.0108
(1.00) 		0.182
(1.00) 		1
(1.00) 		0.723
(1.00) 		0.64
(1.00)
4p loss 181 (22%) 639 0.53
(1.00) 		0.125
(1.00) 		1
(1.00) 		0.921
(1.00) 		0.599
(1.00)
4q loss 146 (18%) 674 0.755
(1.00) 		0.633
(1.00) 		0.374
(1.00) 		0.45
(1.00) 		0.394
(1.00)
5p loss 73 (9%) 747 0.369
(1.00) 		0.652
(1.00) 		0.57
(1.00) 		0.664
(1.00) 		0.0733
(1.00)
5q loss 127 (15%) 693 0.595
(1.00) 		0.0327
(1.00) 		1
(1.00) 		0.648
(1.00) 		0.0874
(1.00)
6p loss 119 (15%) 701 0.778
(1.00) 		0.0349
(1.00) 		0.372
(1.00) 		0.482
(1.00) 		1
(1.00)
6q loss 178 (22%) 642 0.901
(1.00) 		0.0134
(1.00) 		0.218
(1.00) 		0.617
(1.00) 		0.86
(1.00)
7p loss 57 (7%) 763 0.694
(1.00) 		0.244
(1.00) 		1
(1.00) 		0.871
(1.00) 		0.118
(1.00)
7q loss 76 (9%) 744 0.0992
(1.00) 		0.0773
(1.00) 		1
(1.00) 		0.776
(1.00) 		0.316
(1.00)
8p loss 277 (34%) 543 0.0414
(1.00) 		0.963
(1.00) 		0.496
(1.00) 		0.221
(1.00) 		0.249
(1.00)
8q loss 46 (6%) 774 0.628
(1.00) 		0.134
(1.00) 		1
(1.00) 		0.719
(1.00) 		0.435
(1.00)
9p loss 183 (22%) 637 0.00385
(1.00) 		0.379
(1.00) 		0.118
(1.00) 		0.374
(1.00) 		0.0364
(1.00)
9q loss 146 (18%) 674 0.18
(1.00) 		0.32
(1.00) 		0.205
(1.00) 		0.746
(1.00) 		0.0711
(1.00)
10p loss 85 (10%) 735 0.115
(1.00) 		0.0345
(1.00) 		0.609
(1.00) 		0.223
(1.00) 		0.0738
(1.00)
10q loss 125 (15%) 695 0.00105
(0.406) 		0.27
(1.00) 		0.369
(1.00) 		0.566
(1.00) 		0.226
(1.00)
11p loss 175 (21%) 645 0.00257
(0.986) 		0.896
(1.00) 		0.693
(1.00) 		0.687
(1.00) 		0.929
(1.00)
11q loss 277 (34%) 543 0.182
(1.00) 		0.622
(1.00) 		0.174
(1.00) 		0.663
(1.00) 		0.54
(1.00)
12p loss 82 (10%) 738 0.539
(1.00) 		0.267
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.548
(1.00)
12q loss 69 (8%) 751 0.443
(1.00) 		0.503
(1.00) 		1
(1.00) 		0.179
(1.00) 		1
(1.00)
13q loss 259 (32%) 561 0.14
(1.00) 		0.132
(1.00) 		0.474
(1.00) 		0.79
(1.00) 		0.876
(1.00)
14q loss 139 (17%) 681 0.0046
(1.00) 		0.665
(1.00) 		0.37
(1.00) 		0.66
(1.00) 		0.0527
(1.00)
15q loss 159 (19%) 661 0.128
(1.00) 		0.396
(1.00) 		0.219
(1.00) 		0.532
(1.00) 		0.713
(1.00)
16p loss 79 (10%) 741 0.485
(1.00) 		0.376
(1.00) 		0.212
(1.00) 		0.675
(1.00) 		0.713
(1.00)
17p loss 371 (45%) 449 0.238
(1.00) 		0.0419
(1.00) 		0.739
(1.00) 		0.0968
(1.00) 		0.273
(1.00)
17q loss 151 (18%) 669 0.482
(1.00) 		0.327
(1.00) 		0.379
(1.00) 		0.594
(1.00) 		0.779
(1.00)
18p loss 172 (21%) 648 0.0179
(1.00) 		0.00744
(1.00) 		0.693
(1.00) 		0.361
(1.00) 		0.722
(1.00)
18q loss 179 (22%) 641 0.103
(1.00) 		0.0276
(1.00) 		0.692
(1.00) 		0.618
(1.00) 		0.334
(1.00)
19p loss 86 (10%) 734 0.643
(1.00) 		0.883
(1.00) 		0.609
(1.00) 		0.224
(1.00) 		0.0981
(1.00)
19q loss 63 (8%) 757 0.48
(1.00) 		0.652
(1.00) 		1
(1.00) 		0.0881
(1.00) 		0.0197
(1.00)
20p loss 54 (7%) 766 0.00473
(1.00) 		0.586
(1.00) 		0.46
(1.00) 		0.869
(1.00) 		0.77
(1.00)
20q loss 23 (3%) 797 0.0889
(1.00) 		0.179
(1.00) 		1
(1.00) 		0.802
(1.00) 		0.188
(1.00)
21q loss 82 (10%) 738 0.702
(1.00) 		0.639
(1.00) 		0.61
(1.00) 		0.584
(1.00) 		0.116
(1.00)
22q loss 282 (34%) 538 0.193
(1.00) 		0.433
(1.00) 		0.288
(1.00) 		0.0819
(1.00) 		0.878
(1.00)
'7q gain mutation analysis' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000157 (Fisher's exact test), Q value = 0.061

Table S1.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients NO YES
ALL 191 629
7Q GAIN MUTATED 45 75
7Q GAIN WILD-TYPE 146 554

Figure S1.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'7q gain mutation analysis' versus 'NEOADJUVANT.THERAPY'

P value = 0.000432 (Fisher's exact test), Q value = 0.17

Table S2.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'NEOADJUVANT.THERAPY'

nPatients NO YES
ALL 296 524
7Q GAIN MUTATED 61 59
7Q GAIN WILD-TYPE 235 465

Figure S2.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'NEOADJUVANT.THERAPY'

'1p loss mutation analysis' versus 'AGE'

P value = 3.17e-05 (t-test), Q value = 0.012

Table S3.  Gene #40: '1p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 819 58.4 (13.2)
1P LOSS MUTATED 120 63.0 (12.6)
1P LOSS WILD-TYPE 699 57.6 (13.2)

Figure S3.  Get High-res Image Gene #40: '1p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'16q loss mutation analysis' versus 'AGE'

P value = 0.000191 (t-test), Q value = 0.074

Table S4.  Gene #68: '16q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 819 58.4 (13.2)
16Q LOSS MUTATED 357 60.3 (13.0)
16Q LOSS WILD-TYPE 462 56.9 (13.3)

Figure S4.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

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

  • Clinical data file = BRCA.clin.merged.picked.txt

  • Number of patients = 820

  • Number of significantly arm-level cnvs = 78

  • Number of selected clinical features = 5

  • 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)
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