Breast Invasive 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 80 arm-level results and 4 clinical features across 843 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 4 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
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test
16q loss 368 (44%) 475 0.017
(1.00) 		0.00033
(0.106) 		1
(1.00) 		0.566
(1.00)
1p gain 88 (10%) 755 0.193
(1.00) 		0.48
(1.00) 		1
(1.00) 		0.0161
(1.00)
1q gain 449 (53%) 394 0.075
(1.00) 		0.262
(1.00) 		1
(1.00) 		0.329
(1.00)
2p gain 48 (6%) 795 0.781
(1.00) 		0.685
(1.00) 		1
(1.00) 		0.379
(1.00)
2q gain 25 (3%) 818 0.972
(1.00) 		0.957
(1.00) 		1
(1.00) 		0.00656
(1.00)
3p gain 51 (6%) 792 0.846
(1.00) 		0.0585
(1.00) 		1
(1.00) 		0.733
(1.00)
3q gain 95 (11%) 748 0.317
(1.00) 		0.717
(1.00) 		0.608
(1.00) 		1
(1.00)
4p gain 29 (3%) 814 0.0672
(1.00) 		0.485
(1.00) 		1
(1.00) 		0.51
(1.00)
4q gain 27 (3%) 816 0.0252
(1.00) 		0.359
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 159 (19%) 684 0.107
(1.00) 		0.0427
(1.00) 		0.681
(1.00) 		0.0478
(1.00)
5q gain 97 (12%) 746 0.332
(1.00) 		0.00255
(0.809) 		1
(1.00) 		0.125
(1.00)
6p gain 93 (11%) 750 0.86
(1.00) 		0.168
(1.00) 		1
(1.00) 		0.00947
(1.00)
6q gain 57 (7%) 786 0.266
(1.00) 		0.0586
(1.00) 		0.469
(1.00) 		0.627
(1.00)
7p gain 149 (18%) 694 0.847
(1.00) 		0.077
(1.00) 		0.0111
(1.00) 		0.0191
(1.00)
7q gain 107 (13%) 736 0.508
(1.00) 		0.57
(1.00) 		0.0943
(1.00) 		0.00994
(1.00)
8p gain 160 (19%) 683 0.975
(1.00) 		0.115
(1.00) 		0.682
(1.00) 		0.917
(1.00)
8q gain 355 (42%) 488 0.897
(1.00) 		0.0139
(1.00) 		0.504
(1.00) 		0.0704
(1.00)
9p gain 65 (8%) 778 0.503
(1.00) 		0.526
(1.00) 		1
(1.00) 		0.285
(1.00)
9q gain 53 (6%) 790 0.434
(1.00) 		0.311
(1.00) 		1
(1.00) 		0.132
(1.00)
10p gain 106 (13%) 737 0.768
(1.00) 		0.618
(1.00) 		0.612
(1.00) 		0.326
(1.00)
10q gain 44 (5%) 799 0.788
(1.00) 		0.339
(1.00) 		1
(1.00) 		0.359
(1.00)
11p gain 63 (7%) 780 0.615
(1.00) 		0.767
(1.00) 		0.505
(1.00) 		0.757
(1.00)
11q gain 44 (5%) 799 0.0485
(1.00) 		0.813
(1.00) 		1
(1.00) 		0.855
(1.00)
12p gain 109 (13%) 734 0.665
(1.00) 		0.361
(1.00) 		0.0199
(1.00) 		0.276
(1.00)
12q gain 83 (10%) 760 0.105
(1.00) 		0.0806
(1.00) 		0.05
(1.00) 		0.34
(1.00)
13q gain 44 (5%) 799 0.803
(1.00) 		0.94
(1.00) 		1
(1.00) 		0.583
(1.00)
14q gain 76 (9%) 767 0.256
(1.00) 		0.554
(1.00) 		1
(1.00) 		0.394
(1.00)
15q gain 45 (5%) 798 0.609
(1.00) 		0.761
(1.00) 		0.391
(1.00) 		0.208
(1.00)
16p gain 234 (28%) 609 0.607
(1.00) 		0.0524
(1.00) 		1
(1.00) 		0.319
(1.00)
16q gain 52 (6%) 791 0.0455
(1.00) 		0.806
(1.00) 		0.438
(1.00) 		1
(1.00)
17p gain 45 (5%) 798 0.643
(1.00) 		0.449
(1.00) 		0.00953
(1.00) 		1
(1.00)
17q gain 120 (14%) 723 0.797
(1.00) 		0.662
(1.00) 		0.0277
(1.00) 		0.907
(1.00)
18p gain 83 (10%) 760 0.12
(1.00) 		0.0419
(1.00) 		0.608
(1.00) 		0.0412
(1.00)
18q gain 71 (8%) 772 0.136
(1.00) 		0.415
(1.00) 		0.549
(1.00) 		0.142
(1.00)
19p gain 67 (8%) 776 0.0953
(1.00) 		0.261
(1.00) 		0.156
(1.00) 		0.07
(1.00)
19q gain 82 (10%) 761 0.0129
(1.00) 		0.677
(1.00) 		0.215
(1.00) 		0.414
(1.00)
20p gain 231 (27%) 612 0.0448
(1.00) 		0.12
(1.00) 		0.069
(1.00) 		0.716
(1.00)
20q gain 265 (31%) 578 0.14
(1.00) 		0.533
(1.00) 		0.149
(1.00) 		0.484
(1.00)
21q gain 98 (12%) 745 0.0414
(1.00) 		0.0355
(1.00) 		1
(1.00) 		0.0429
(1.00)
22q gain 39 (5%) 804 0.804
(1.00) 		0.35
(1.00) 		1
(1.00) 		0.846
(1.00)
Xq gain 20 (2%) 823 0.119
(1.00) 		0.112
(1.00) 		1
(1.00) 		0.281
(1.00)
1p loss 115 (14%) 728 0.191
(1.00) 		0.0111
(1.00) 		1
(1.00) 		0.407
(1.00)
1q loss 20 (2%) 823 0.987
(1.00) 		0.639
(1.00) 		1
(1.00) 		0.794
(1.00)
2p loss 69 (8%) 774 0.655
(1.00) 		0.232
(1.00) 		1
(1.00) 		0.18
(1.00)
2q loss 83 (10%) 760 0.514
(1.00) 		0.411
(1.00) 		1
(1.00) 		0.22
(1.00)
3p loss 88 (10%) 755 0.0422
(1.00) 		0.0411
(1.00) 		0.609
(1.00) 		0.354
(1.00)
3q loss 44 (5%) 799 0.267
(1.00) 		0.0692
(1.00) 		1
(1.00) 		0.0439
(1.00)
4p loss 176 (21%) 667 0.455
(1.00) 		0.25
(1.00) 		1
(1.00) 		0.162
(1.00)
4q loss 147 (17%) 696 0.479
(1.00) 		0.891
(1.00) 		0.372
(1.00) 		0.284
(1.00)
5p loss 67 (8%) 776 0.14
(1.00) 		0.12
(1.00) 		0.527
(1.00) 		0.881
(1.00)
5q loss 118 (14%) 725 0.413
(1.00) 		0.154
(1.00) 		0.621
(1.00) 		0.815
(1.00)
6p loss 105 (12%) 738 0.312
(1.00) 		0.18
(1.00) 		0.611
(1.00) 		0.177
(1.00)
6q loss 160 (19%) 683 0.861
(1.00) 		0.00936
(1.00) 		0.221
(1.00) 		0.0782
(1.00)
7p loss 46 (5%) 797 0.526
(1.00) 		0.404
(1.00) 		1
(1.00) 		0.281
(1.00)
7q loss 62 (7%) 781 0.135
(1.00) 		0.227
(1.00) 		1
(1.00) 		0.437
(1.00)
8p loss 263 (31%) 580 0.022
(1.00) 		0.315
(1.00) 		1
(1.00) 		0.861
(1.00)
8q loss 44 (5%) 799 0.00363
(1.00) 		0.599
(1.00) 		1
(1.00) 		0.718
(1.00)
9p loss 182 (22%) 661 0.0258
(1.00) 		0.983
(1.00) 		0.415
(1.00) 		0.692
(1.00)
9q loss 139 (16%) 704 0.0198
(1.00) 		0.509
(1.00) 		0.173
(1.00) 		0.913
(1.00)
10p loss 68 (8%) 775 0.0628
(1.00) 		0.225
(1.00) 		1
(1.00) 		0.655
(1.00)
10q loss 105 (12%) 738 0.00326
(1.00) 		0.508
(1.00) 		0.611
(1.00) 		0.622
(1.00)
11p loss 141 (17%) 702 0.0209
(1.00) 		0.536
(1.00) 		0.37
(1.00) 		0.744
(1.00)
11q loss 218 (26%) 625 0.169
(1.00) 		0.718
(1.00) 		0.055
(1.00) 		0.516
(1.00)
12p loss 64 (8%) 779 0.0969
(1.00) 		0.971
(1.00) 		0.51
(1.00) 		0.443
(1.00)
12q loss 49 (6%) 794 0.229
(1.00) 		0.202
(1.00) 		1
(1.00) 		0.603
(1.00)
13q loss 254 (30%) 589 0.0809
(1.00) 		0.156
(1.00) 		0.465
(1.00) 		0.79
(1.00)
14q loss 123 (15%) 720 0.00774
(1.00) 		0.204
(1.00) 		0.371
(1.00) 		0.909
(1.00)
15q loss 152 (18%) 691 0.221
(1.00) 		0.14
(1.00) 		0.376
(1.00) 		0.342
(1.00)
16p loss 52 (6%) 791 0.688
(1.00) 		0.971
(1.00) 		0.102
(1.00) 		1
(1.00)
17p loss 351 (42%) 492 0.336
(1.00) 		0.0194
(1.00) 		0.742
(1.00) 		0.188
(1.00)
17q loss 135 (16%) 708 0.604
(1.00) 		0.248
(1.00) 		0.368
(1.00) 		0.912
(1.00)
18p loss 166 (20%) 677 0.00617
(1.00) 		0.00114
(0.365) 		1
(1.00) 		0.61
(1.00)
18q loss 166 (20%) 677 0.0407
(1.00) 		0.00123
(0.391) 		1
(1.00) 		0.61
(1.00)
19p loss 64 (8%) 779 0.533
(1.00) 		0.44
(1.00) 		1
(1.00) 		0.282
(1.00)
19q loss 50 (6%) 793 0.633
(1.00) 		0.785
(1.00) 		1
(1.00) 		0.73
(1.00)
20p loss 51 (6%) 792 0.00363
(1.00) 		0.811
(1.00) 		0.431
(1.00) 		0.865
(1.00)
20q loss 27 (3%) 816 0.579
(1.00) 		0.855
(1.00) 		1
(1.00) 		0.36
(1.00)
21q loss 84 (10%) 759 0.987
(1.00) 		0.718
(1.00) 		0.61
(1.00) 		1
(1.00)
22q loss 284 (34%) 559 0.122
(1.00) 		0.823
(1.00) 		0.173
(1.00) 		0.048
(1.00)
Xq loss 30 (4%) 813 0.0544
(1.00) 		0.554
(1.00) 		0.0377
(1.00) 		0.511
(1.00)
'16q loss mutation analysis' versus 'AGE'

P value = 0.00033 (t-test), Q value = 0.11

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

nPatients Mean (Std.Dev)
ALL 842 58.5 (13.2)
16Q LOSS MUTATED 368 60.4 (12.8)
16Q LOSS WILD-TYPE 474 57.1 (13.4)

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-TP.clin.merged.picked.txt

  • Number of patients = 843

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 4

  • 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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