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 80 arm-level results and 5 clinical features across 838 patients, one significant finding detected with Q value < 0.25.

  • 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 80 arm-level results and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding 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
16q loss 362 (43%) 476 0.0269
(1.00) 		0.000381
(0.152) 		1
(1.00) 		0.512
(1.00) 		0.424
(1.00)
1p gain 90 (11%) 748 0.175
(1.00) 		0.371
(1.00) 		1
(1.00) 		0.025
(1.00) 		0.0483
(1.00)
1q gain 448 (53%) 390 0.0771
(1.00) 		0.27
(1.00) 		1
(1.00) 		0.289
(1.00) 		0.885
(1.00)
2p gain 47 (6%) 791 0.768
(1.00) 		0.616
(1.00) 		1
(1.00) 		0.482
(1.00) 		0.755
(1.00)
2q gain 25 (3%) 813 0.984
(1.00) 		0.947
(1.00) 		1
(1.00) 		0.00679
(1.00) 		0.0946
(1.00)
3p gain 49 (6%) 789 0.838
(1.00) 		0.0902
(1.00) 		1
(1.00) 		0.604
(1.00) 		0.759
(1.00)
3q gain 93 (11%) 745 0.32
(1.00) 		0.842
(1.00) 		0.608
(1.00) 		1
(1.00) 		0.819
(1.00)
4p gain 29 (3%) 809 0.0699
(1.00) 		0.475
(1.00) 		1
(1.00) 		0.509
(1.00) 		0.432
(1.00)
4q gain 27 (3%) 811 0.0264
(1.00) 		0.351
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 156 (19%) 682 0.0671
(1.00) 		0.0261
(1.00) 		0.677
(1.00) 		0.0362
(1.00) 		0.116
(1.00)
5q gain 96 (11%) 742 0.226
(1.00) 		0.00259
(1.00) 		1
(1.00) 		0.124
(1.00) 		0.311
(1.00)
6p gain 93 (11%) 745 0.877
(1.00) 		0.136
(1.00) 		1
(1.00) 		0.0132
(1.00) 		0.209
(1.00)
6q gain 58 (7%) 780 0.274
(1.00) 		0.0561
(1.00) 		0.477
(1.00) 		0.633
(1.00) 		0.888
(1.00)
7p gain 150 (18%) 688 0.882
(1.00) 		0.0815
(1.00) 		0.0118
(1.00) 		0.0257
(1.00) 		0.0244
(1.00)
7q gain 108 (13%) 730 0.471
(1.00) 		0.515
(1.00) 		0.0197
(1.00) 		0.0145
(1.00) 		0.00993
(1.00)
8p gain 156 (19%) 682 0.744
(1.00) 		0.107
(1.00) 		0.677
(1.00) 		0.676
(1.00) 		1
(1.00)
8q gain 357 (43%) 481 0.726
(1.00) 		0.0168
(1.00) 		0.507
(1.00) 		0.0485
(1.00) 		0.827
(1.00)
9p gain 65 (8%) 773 0.487
(1.00) 		0.542
(1.00) 		1
(1.00) 		0.286
(1.00) 		0.347
(1.00)
9q gain 52 (6%) 786 0.716
(1.00) 		0.297
(1.00) 		1
(1.00) 		0.0624
(1.00) 		0.551
(1.00)
10p gain 105 (13%) 733 0.818
(1.00) 		0.687
(1.00) 		0.612
(1.00) 		0.325
(1.00) 		0.514
(1.00)
10q gain 44 (5%) 794 0.718
(1.00) 		0.343
(1.00) 		1
(1.00) 		0.201
(1.00) 		0.0238
(1.00)
11p gain 62 (7%) 776 0.661
(1.00) 		0.838
(1.00) 		0.501
(1.00) 		0.643
(1.00) 		1
(1.00)
11q gain 44 (5%) 794 0.0515
(1.00) 		0.828
(1.00) 		1
(1.00) 		0.855
(1.00) 		1
(1.00)
12p gain 110 (13%) 728 0.792
(1.00) 		0.394
(1.00) 		0.021
(1.00) 		0.228
(1.00) 		0.457
(1.00)
12q gain 83 (10%) 755 0.164
(1.00) 		0.112
(1.00) 		0.0507
(1.00) 		0.342
(1.00) 		0.81
(1.00)
13q gain 44 (5%) 794 0.816
(1.00) 		0.923
(1.00) 		1
(1.00) 		0.584
(1.00) 		0.873
(1.00)
14q gain 75 (9%) 763 0.25
(1.00) 		0.531
(1.00) 		1
(1.00) 		0.322
(1.00) 		0.615
(1.00)
15q gain 43 (5%) 795 0.615
(1.00) 		0.757
(1.00) 		0.379
(1.00) 		0.194
(1.00) 		0.0744
(1.00)
16p gain 234 (28%) 604 0.613
(1.00) 		0.027
(1.00) 		1
(1.00) 		0.414
(1.00) 		0.263
(1.00)
16q gain 53 (6%) 785 0.186
(1.00) 		0.77
(1.00) 		0.446
(1.00) 		1
(1.00) 		0.143
(1.00)
17p gain 44 (5%) 794 0.612
(1.00) 		0.473
(1.00) 		0.0091
(1.00) 		1
(1.00) 		1
(1.00)
17q gain 117 (14%) 721 0.8
(1.00) 		0.902
(1.00) 		0.0259
(1.00) 		0.814
(1.00) 		0.0978
(1.00)
18p gain 82 (10%) 756 0.0614
(1.00) 		0.0343
(1.00) 		0.606
(1.00) 		0.0397
(1.00) 		0.904
(1.00)
18q gain 70 (8%) 768 0.136
(1.00) 		0.407
(1.00) 		0.546
(1.00) 		0.107
(1.00) 		0.606
(1.00)
19p gain 65 (8%) 773 0.13
(1.00) 		0.26
(1.00) 		0.15
(1.00) 		0.0476
(1.00) 		0.687
(1.00)
19q gain 80 (10%) 758 0.0206
(1.00) 		0.659
(1.00) 		0.209
(1.00) 		0.405
(1.00) 		0.807
(1.00)
20p gain 229 (27%) 609 0.0458
(1.00) 		0.0869
(1.00) 		0.0683
(1.00) 		0.855
(1.00) 		0.747
(1.00)
20q gain 263 (31%) 575 0.149
(1.00) 		0.405
(1.00) 		0.149
(1.00) 		0.599
(1.00) 		0.816
(1.00)
21q gain 98 (12%) 740 0.045
(1.00) 		0.0329
(1.00) 		1
(1.00) 		0.0564
(1.00) 		0.433
(1.00)
22q gain 38 (5%) 800 0.819
(1.00) 		0.35
(1.00) 		1
(1.00) 		0.846
(1.00) 		1
(1.00)
Xq gain 20 (2%) 818 0.123
(1.00) 		0.109
(1.00) 		1
(1.00) 		0.282
(1.00) 		1
(1.00)
1p loss 112 (13%) 726 0.235
(1.00) 		0.00888
(1.00) 		1
(1.00) 		0.339
(1.00) 		0.0906
(1.00)
1q loss 20 (2%) 818 0.997
(1.00) 		0.627
(1.00) 		1
(1.00) 		0.795
(1.00) 		0.814
(1.00)
2p loss 71 (8%) 767 0.963
(1.00) 		0.198
(1.00) 		1
(1.00) 		0.38
(1.00) 		0.7
(1.00)
2q loss 85 (10%) 753 0.758
(1.00) 		0.356
(1.00) 		0.61
(1.00) 		0.42
(1.00) 		0.812
(1.00)
3p loss 89 (11%) 749 0.0182
(1.00) 		0.0418
(1.00) 		0.609
(1.00) 		0.428
(1.00) 		0.559
(1.00)
3q loss 45 (5%) 793 0.113
(1.00) 		0.0677
(1.00) 		1
(1.00) 		0.0687
(1.00) 		0.873
(1.00)
4p loss 175 (21%) 663 0.471
(1.00) 		0.265
(1.00) 		1
(1.00) 		0.162
(1.00) 		0.0266
(1.00)
4q loss 146 (17%) 692 0.492
(1.00) 		0.868
(1.00) 		0.372
(1.00) 		0.283
(1.00) 		0.184
(1.00)
5p loss 68 (8%) 770 0.124
(1.00) 		0.0875
(1.00) 		0.535
(1.00) 		1
(1.00) 		0.187
(1.00)
5q loss 119 (14%) 719 0.436
(1.00) 		0.119
(1.00) 		0.623
(1.00) 		0.727
(1.00) 		0.0499
(1.00)
6p loss 107 (13%) 731 0.267
(1.00) 		0.0795
(1.00) 		0.613
(1.00) 		0.272
(1.00) 		0.914
(1.00)
6q loss 164 (20%) 674 0.931
(1.00) 		0.00479
(1.00) 		0.218
(1.00) 		0.15
(1.00) 		0.717
(1.00)
7p loss 46 (5%) 792 0.538
(1.00) 		0.393
(1.00) 		1
(1.00) 		0.283
(1.00) 		0.528
(1.00)
7q loss 61 (7%) 777 0.135
(1.00) 		0.184
(1.00) 		1
(1.00) 		0.433
(1.00) 		0.678
(1.00)
8p loss 262 (31%) 576 0.00314
(1.00) 		0.478
(1.00) 		1
(1.00) 		0.725
(1.00) 		1
(1.00)
8q loss 42 (5%) 796 0.0039
(1.00) 		0.704
(1.00) 		1
(1.00) 		0.853
(1.00) 		0.621
(1.00)
9p loss 181 (22%) 657 0.00975
(1.00) 		0.938
(1.00) 		0.415
(1.00) 		0.553
(1.00) 		0.0548
(1.00)
9q loss 139 (17%) 699 0.0173
(1.00) 		0.61
(1.00) 		0.175
(1.00) 		1
(1.00) 		0.0656
(1.00)
10p loss 70 (8%) 768 0.0761
(1.00) 		0.351
(1.00) 		1
(1.00) 		0.769
(1.00) 		0.195
(1.00)
10q loss 106 (13%) 732 0.00524
(1.00) 		0.622
(1.00) 		0.612
(1.00) 		0.714
(1.00) 		0.196
(1.00)
11p loss 132 (16%) 706 0.0256
(1.00) 		0.385
(1.00) 		0.368
(1.00) 		1
(1.00) 		0.323
(1.00)
11q loss 216 (26%) 622 0.291
(1.00) 		0.636
(1.00) 		0.0542
(1.00) 		0.515
(1.00) 		0.46
(1.00)
12p loss 65 (8%) 773 0.0923
(1.00) 		0.949
(1.00) 		0.518
(1.00) 		0.545
(1.00) 		0.282
(1.00)
12q loss 50 (6%) 788 0.22
(1.00) 		0.189
(1.00) 		1
(1.00) 		0.491
(1.00) 		0.448
(1.00)
13q loss 252 (30%) 586 0.0663
(1.00) 		0.158
(1.00) 		0.464
(1.00) 		0.79
(1.00) 		0.754
(1.00)
14q loss 125 (15%) 713 0.00889
(1.00) 		0.165
(1.00) 		0.37
(1.00) 		0.82
(1.00) 		0.189
(1.00)
15q loss 152 (18%) 686 0.233
(1.00) 		0.15
(1.00) 		0.377
(1.00) 		0.398
(1.00) 		0.852
(1.00)
16p loss 51 (6%) 787 0.691
(1.00) 		0.966
(1.00) 		0.0994
(1.00) 		1
(1.00) 		0.881
(1.00)
17p loss 352 (42%) 486 0.358
(1.00) 		0.0414
(1.00) 		0.741
(1.00) 		0.161
(1.00) 		0.243
(1.00)
17q loss 138 (16%) 700 0.641
(1.00) 		0.269
(1.00) 		0.369
(1.00) 		0.913
(1.00) 		0.56
(1.00)
18p loss 166 (20%) 672 0.0067
(1.00) 		0.00141
(0.562) 		1
(1.00) 		0.759
(1.00) 		0.928
(1.00)
18q loss 166 (20%) 672 0.0449
(1.00) 		0.00105
(0.42) 		1
(1.00) 		0.609
(1.00) 		0.418
(1.00)
19p loss 67 (8%) 771 0.584
(1.00) 		0.338
(1.00) 		1
(1.00) 		0.296
(1.00) 		0.507
(1.00)
19q loss 54 (6%) 784 0.885
(1.00) 		0.906
(1.00) 		1
(1.00) 		0.74
(1.00) 		0.559
(1.00)
20p loss 48 (6%) 790 0.00149
(0.592) 		0.844
(1.00) 		0.413
(1.00) 		1
(1.00) 		0.217
(1.00)
20q loss 25 (3%) 813 0.803
(1.00) 		0.935
(1.00) 		1
(1.00) 		0.813
(1.00) 		0.0354
(1.00)
21q loss 84 (10%) 754 0.989
(1.00) 		0.74
(1.00) 		0.61
(1.00) 		0.893
(1.00) 		0.0551
(1.00)
22q loss 284 (34%) 554 0.136
(1.00) 		0.871
(1.00) 		0.176
(1.00) 		0.0584
(1.00) 		1
(1.00)
Xq loss 31 (4%) 807 0.0598
(1.00) 		0.596
(1.00) 		0.0406
(1.00) 		0.671
(1.00) 		1
(1.00)
'16q loss mutation analysis' versus 'AGE'

P value = 0.000381 (t-test), Q value = 0.15

Table S1.  Gene #69: '16q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 837 58.5 (13.2)
16Q LOSS MUTATED 362 60.3 (13.0)
16Q LOSS WILD-TYPE 475 57.1 (13.3)

Figure S1.  Get High-res Image Gene #69: '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 = 838

  • Number of significantly arm-level cnvs = 80

  • 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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