Ovarian Serous Cystadenocarcinoma: 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 6 clinical features across 552 patients, 8 significant findings detected with Q value < 0.25.

  • 3q gain cnv correlated to 'AGE'.

  • 10p gain cnv correlated to 'AGE'.

  • 12p gain cnv correlated to 'AGE'.

  • 12q gain cnv correlated to 'AGE'.

  • 20p gain cnv correlated to 'AGE'.

  • 20q gain cnv correlated to 'AGE'.

  • 6q loss cnv correlated to 'AGE'.

  • 9q 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 6 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 PRIMARY
SITE
OF
DISEASE 		KARNOFSKY
PERFORMANCE
SCORE 		RADIATIONS
RADIATION
REGIMENINDICATION 		NEOADJUVANT
THERAPY
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test Fisher's exact test Fisher's exact test
3q gain 256 (46%) 296 0.781
(1.00) 		0.000338
(0.155) 		0.465
(1.00) 		0.517
(1.00) 		0.253
(1.00) 		0.102
(1.00)
10p gain 154 (28%) 398 0.474
(1.00) 		9.88e-06
(0.00456) 		0.149
(1.00) 		0.281
(1.00) 		1
(1.00) 		0.227
(1.00)
12p gain 213 (39%) 339 0.281
(1.00) 		5.52e-06
(0.00256) 		0.275
(1.00) 		0.0439
(1.00) 		0.562
(1.00) 		0.219
(1.00)
12q gain 121 (22%) 431 0.126
(1.00) 		9.7e-06
(0.00448) 		0.21
(1.00) 		0.261
(1.00) 		1
(1.00) 		0.599
(1.00)
20p gain 233 (42%) 319 0.202
(1.00) 		2.2e-05
(0.0101) 		0.324
(1.00) 		0.0439
(1.00) 		0.576
(1.00) 		0.0787
(1.00)
20q gain 273 (49%) 279 0.213
(1.00) 		0.000384
(0.175) 		0.749
(1.00) 		0.279
(1.00) 		0.62
(1.00) 		0.329
(1.00)
6q loss 237 (43%) 315 0.732
(1.00) 		9.37e-06
(0.00434) 		1
(1.00) 		0.248
(1.00) 		1
(1.00) 		0.743
(1.00)
9q loss 274 (50%) 278 0.78
(1.00) 		0.000147
(0.0675) 		0.185
(1.00) 		0.417
(1.00) 		0.622
(1.00) 		1
(1.00)
1p gain 109 (20%) 443 0.206
(1.00) 		0.183
(1.00) 		0.0258
(1.00) 		0.106
(1.00) 		0.101
(1.00) 		0.683
(1.00)
1q gain 180 (33%) 372 0.775
(1.00) 		0.00782
(1.00) 		0.104
(1.00) 		0.0796
(1.00) 		1
(1.00) 		1
(1.00)
2p gain 145 (26%) 407 0.138
(1.00) 		0.000702
(0.32) 		1
(1.00) 		0.485
(1.00) 		1
(1.00) 		0.711
(1.00)
2q gain 114 (21%) 438 0.203
(1.00) 		0.0113
(1.00) 		1
(1.00) 		0.964
(1.00) 		0.501
(1.00) 		0.688
(1.00)
3p gain 110 (20%) 442 0.763
(1.00) 		0.00143
(0.648) 		0.59
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.173
(1.00)
4p gain 38 (7%) 514 0.127
(1.00) 		0.695
(1.00) 		0.249
(1.00) 		0.747
(1.00) 		1
(1.00) 		0.671
(1.00)
4q gain 16 (3%) 536 0.832
(1.00) 		0.736
(1.00) 		1
(1.00) 		1
(1.00) 		0.518
(1.00)
5p gain 169 (31%) 383 0.287
(1.00) 		0.187
(1.00) 		0.0877
(1.00) 		0.976
(1.00) 		1
(1.00) 		1
(1.00)
5q gain 39 (7%) 513 0.765
(1.00) 		0.227
(1.00) 		0.255
(1.00) 		0.614
(1.00) 		1
(1.00) 		0.523
(1.00)
6p gain 162 (29%) 390 0.102
(1.00) 		0.0231
(1.00) 		0.337
(1.00) 		0.00643
(1.00) 		0.559
(1.00) 		0.285
(1.00)
6q gain 65 (12%) 487 0.575
(1.00) 		0.0406
(1.00) 		0.395
(1.00) 		0.15
(1.00) 		1
(1.00) 		0.236
(1.00)
7p gain 135 (24%) 417 0.77
(1.00) 		0.0153
(1.00) 		0.252
(1.00) 		0.0427
(1.00) 		1
(1.00) 		0.528
(1.00)
7q gain 177 (32%) 375 0.0687
(1.00) 		0.0242
(1.00) 		0.385
(1.00) 		0.00141
(0.642) 		0.555
(1.00) 		0.295
(1.00)
8p gain 71 (13%) 481 0.412
(1.00) 		0.7
(1.00) 		1
(1.00) 		0.657
(1.00) 		0.339
(1.00) 		0.0744
(1.00)
8q gain 255 (46%) 297 0.137
(1.00) 		0.353
(1.00) 		0.752
(1.00) 		0.981
(1.00) 		1
(1.00) 		0.23
(1.00)
9p gain 70 (13%) 482 0.851
(1.00) 		0.0858
(1.00) 		1
(1.00) 		0.599
(1.00) 		1
(1.00) 		0.87
(1.00)
9q gain 28 (5%) 524 0.631
(1.00) 		0.589
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
10q gain 74 (13%) 478 0.341
(1.00) 		0.167
(1.00) 		0.439
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.203
(1.00)
11p gain 49 (9%) 503 0.0848
(1.00) 		0.64
(1.00) 		1
(1.00) 		0.407
(1.00) 		1
(1.00) 		0.0836
(1.00)
11q gain 91 (16%) 461 0.603
(1.00) 		0.0385
(1.00) 		1
(1.00) 		0.192
(1.00) 		1
(1.00) 		0.561
(1.00)
13q gain 53 (10%) 499 0.843
(1.00) 		0.0127
(1.00) 		1
(1.00) 		0.232
(1.00) 		0.262
(1.00) 		0.094
(1.00)
14q gain 31 (6%) 521 0.466
(1.00) 		0.909
(1.00) 		0.207
(1.00) 		0.392
(1.00) 		1
(1.00) 		1
(1.00)
15q gain 26 (5%) 526 0.358
(1.00) 		0.724
(1.00) 		1
(1.00) 		1
(1.00) 		0.8
(1.00)
16p gain 38 (7%) 514 0.141
(1.00) 		0.267
(1.00) 		1
(1.00) 		0.0292
(1.00) 		1
(1.00) 		0.83
(1.00)
16q gain 17 (3%) 535 0.674
(1.00) 		0.886
(1.00) 		1
(1.00) 		0.22
(1.00) 		1
(1.00) 		1
(1.00)
17p gain 18 (3%) 534 0.934
(1.00) 		0.764
(1.00) 		1
(1.00) 		0.767
(1.00) 		1
(1.00) 		0.219
(1.00)
17q gain 41 (7%) 511 0.595
(1.00) 		0.227
(1.00) 		1
(1.00) 		0.913
(1.00) 		1
(1.00) 		0.541
(1.00)
18p gain 89 (16%) 463 0.311
(1.00) 		0.0797
(1.00) 		1
(1.00) 		0.557
(1.00) 		1
(1.00) 		0.0255
(1.00)
18q gain 43 (8%) 509 0.556
(1.00) 		0.563
(1.00) 		1
(1.00) 		0.252
(1.00) 		1
(1.00) 		0.308
(1.00)
19p gain 114 (21%) 438 0.501
(1.00) 		0.0171
(1.00) 		0.605
(1.00) 		0.31
(1.00) 		0.501
(1.00) 		0.788
(1.00)
19q gain 92 (17%) 460 0.323
(1.00) 		0.0424
(1.00) 		0.519
(1.00) 		0.657
(1.00) 		0.422
(1.00) 		0.465
(1.00)
21q gain 77 (14%) 475 0.139
(1.00) 		0.0316
(1.00) 		1
(1.00) 		0.407
(1.00) 		1
(1.00) 		0.876
(1.00)
22q gain 13 (2%) 539 0.344
(1.00) 		0.206
(1.00) 		1
(1.00) 		0.00339
(1.00) 		1
(1.00) 		0.28
(1.00)
1p loss 40 (7%) 512 0.553
(1.00) 		0.352
(1.00) 		1
(1.00) 		0.464
(1.00) 		0.202
(1.00) 		0.531
(1.00)
1q loss 25 (5%) 527 0.685
(1.00) 		0.846
(1.00) 		1
(1.00) 		0.498
(1.00) 		0.13
(1.00) 		0.112
(1.00)
2p loss 27 (5%) 525 0.502
(1.00) 		0.601
(1.00) 		1
(1.00) 		0.0731
(1.00) 		1
(1.00) 		0.801
(1.00)
2q loss 29 (5%) 523 0.691
(1.00) 		0.199
(1.00) 		0.195
(1.00) 		0.102
(1.00) 		1
(1.00) 		0.224
(1.00)
3p loss 78 (14%) 474 0.337
(1.00) 		0.592
(1.00) 		1
(1.00) 		0.339
(1.00) 		0.367
(1.00) 		0.117
(1.00)
3q loss 22 (4%) 530 0.116
(1.00) 		0.389
(1.00) 		1
(1.00) 		0.498
(1.00) 		0.115
(1.00) 		0.158
(1.00)
4p loss 280 (51%) 272 0.572
(1.00) 		0.137
(1.00) 		0.492
(1.00) 		0.546
(1.00) 		1
(1.00) 		0.587
(1.00)
4q loss 320 (58%) 232 0.92
(1.00) 		0.115
(1.00) 		0.322
(1.00) 		0.44
(1.00) 		1
(1.00) 		0.509
(1.00)
5p loss 100 (18%) 452 0.318
(1.00) 		0.351
(1.00) 		1
(1.00) 		0.482
(1.00) 		0.452
(1.00) 		0.572
(1.00)
5q loss 213 (39%) 339 0.971
(1.00) 		0.895
(1.00) 		0.775
(1.00) 		0.621
(1.00) 		0.562
(1.00) 		0.314
(1.00)
6p loss 134 (24%) 418 0.498
(1.00) 		0.00682
(1.00) 		0.672
(1.00) 		0.503
(1.00) 		0.567
(1.00) 		0.526
(1.00)
7p loss 106 (19%) 446 0.462
(1.00) 		0.162
(1.00) 		0.575
(1.00) 		0.139
(1.00) 		1
(1.00) 		1
(1.00)
7q loss 54 (10%) 498 0.801
(1.00) 		0.447
(1.00) 		0.338
(1.00) 		0.921
(1.00) 		0.266
(1.00) 		0.145
(1.00)
8p loss 289 (52%) 263 0.491
(1.00) 		0.257
(1.00) 		0.75
(1.00) 		0.254
(1.00) 		1
(1.00) 		0.383
(1.00)
8q loss 70 (13%) 482 0.509
(1.00) 		0.28
(1.00) 		1
(1.00) 		0.0604
(1.00) 		1
(1.00) 		0.87
(1.00)
9p loss 243 (44%) 309 0.714
(1.00) 		0.0286
(1.00) 		0.159
(1.00) 		0.957
(1.00) 		0.585
(1.00) 		0.274
(1.00)
10p loss 89 (16%) 463 0.979
(1.00) 		0.529
(1.00) 		1
(1.00) 		0.995
(1.00) 		0.0691
(1.00) 		0.302
(1.00)
10q loss 117 (21%) 435 0.541
(1.00) 		0.917
(1.00) 		1
(1.00) 		0.862
(1.00) 		0.00933
(1.00) 		0.0631
(1.00)
11p loss 182 (33%) 370 0.435
(1.00) 		0.175
(1.00) 		1
(1.00) 		0.621
(1.00) 		0.254
(1.00) 		0.817
(1.00)
11q loss 120 (22%) 432 0.362
(1.00) 		0.0888
(1.00) 		0.626
(1.00) 		0.243
(1.00) 		0.521
(1.00) 		0.694
(1.00)
12p loss 63 (11%) 489 0.469
(1.00) 		0.0427
(1.00) 		1
(1.00) 		0.169
(1.00) 		1
(1.00) 		0.231
(1.00)
12q loss 99 (18%) 453 0.678
(1.00) 		0.0122
(1.00) 		1
(1.00) 		0.737
(1.00) 		1
(1.00) 		0.57
(1.00)
13q loss 266 (48%) 286 0.904
(1.00) 		0.753
(1.00) 		0.482
(1.00) 		0.449
(1.00) 		1
(1.00) 		0.327
(1.00)
14q loss 197 (36%) 355 0.215
(1.00) 		0.387
(1.00) 		0.408
(1.00) 		0.637
(1.00) 		0.556
(1.00) 		0.427
(1.00)
15q loss 228 (41%) 324 0.809
(1.00) 		0.0571
(1.00) 		0.312
(1.00) 		0.596
(1.00) 		0.572
(1.00) 		0.0475
(1.00)
16p loss 283 (51%) 269 0.319
(1.00) 		0.265
(1.00) 		0.749
(1.00) 		0.0109
(1.00) 		0.615
(1.00) 		0.745
(1.00)
16q loss 388 (70%) 164 0.295
(1.00) 		0.0344
(1.00) 		1
(1.00) 		0.0549
(1.00) 		0.558
(1.00) 		0.405
(1.00)
17p loss 419 (76%) 133 0.783
(1.00) 		0.0148
(1.00) 		0.246
(1.00) 		0.671
(1.00) 		0.146
(1.00) 		0.899
(1.00)
17q loss 317 (57%) 235 0.166
(1.00) 		0.0337
(1.00) 		1
(1.00) 		0.299
(1.00) 		0.578
(1.00) 		0.0615
(1.00)
18p loss 198 (36%) 354 0.301
(1.00) 		0.612
(1.00) 		0.408
(1.00) 		0.709
(1.00) 		0.0457
(1.00) 		0.174
(1.00)
18q loss 267 (48%) 285 0.704
(1.00) 		0.24
(1.00) 		0.25
(1.00) 		0.167
(1.00) 		0.113
(1.00) 		0.192
(1.00)
19p loss 169 (31%) 383 0.841
(1.00) 		0.615
(1.00) 		0.769
(1.00) 		0.77
(1.00) 		0.223
(1.00) 		1
(1.00)
19q loss 186 (34%) 366 0.539
(1.00) 		0.519
(1.00) 		0.8
(1.00) 		0.725
(1.00) 		0.554
(1.00) 		0.819
(1.00)
20p loss 45 (8%) 507 0.055
(1.00) 		0.141
(1.00) 		1
(1.00) 		0.921
(1.00) 		0.226
(1.00) 		0.692
(1.00)
20q loss 23 (4%) 529 0.152
(1.00) 		0.887
(1.00) 		1
(1.00) 		1
(1.00) 		0.411
(1.00)
21q loss 159 (29%) 393 0.549
(1.00) 		0.876
(1.00) 		0.744
(1.00) 		0.725
(1.00) 		1
(1.00) 		0.632
(1.00)
22q loss 393 (71%) 159 0.662
(1.00) 		0.97
(1.00) 		0.0742
(1.00) 		0.737
(1.00) 		0.561
(1.00) 		0.548
(1.00)
'3q gain mutation analysis' versus 'AGE'

P value = 0.000338 (t-test), Q value = 0.15

Table S1.  Gene #6: '3q gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
3Q GAIN MUTATED 251 61.7 (11.5)
3Q GAIN WILD-TYPE 290 58.1 (11.5)

Figure S1.  Get High-res Image Gene #6: '3q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'10p gain mutation analysis' versus 'AGE'

P value = 9.88e-06 (t-test), Q value = 0.0046

Table S2.  Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
10P GAIN MUTATED 150 63.2 (10.8)
10P GAIN WILD-TYPE 391 58.4 (11.6)

Figure S2.  Get High-res Image Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'12p gain mutation analysis' versus 'AGE'

P value = 5.52e-06 (t-test), Q value = 0.0026

Table S3.  Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
12P GAIN MUTATED 207 62.6 (11.2)
12P GAIN WILD-TYPE 334 58.0 (11.5)

Figure S3.  Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'12q gain mutation analysis' versus 'AGE'

P value = 9.7e-06 (t-test), Q value = 0.0045

Table S4.  Gene #24: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
12Q GAIN MUTATED 117 63.9 (11.0)
12Q GAIN WILD-TYPE 424 58.6 (11.5)

Figure S4.  Get High-res Image Gene #24: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'20p gain mutation analysis' versus 'AGE'

P value = 2.2e-05 (t-test), Q value = 0.01

Table S5.  Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
20P GAIN MUTATED 228 62.2 (11.5)
20P GAIN WILD-TYPE 313 57.9 (11.4)

Figure S5.  Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'20q gain mutation analysis' versus 'AGE'

P value = 0.000384 (t-test), Q value = 0.18

Table S6.  Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
20Q GAIN MUTATED 267 61.5 (11.9)
20Q GAIN WILD-TYPE 274 58.0 (11.0)

Figure S6.  Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'6q loss mutation analysis' versus 'AGE'

P value = 9.37e-06 (t-test), Q value = 0.0043

Table S7.  Gene #51: '6q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
6Q LOSS MUTATED 231 57.2 (10.9)
6Q LOSS WILD-TYPE 310 61.6 (11.8)

Figure S7.  Get High-res Image Gene #51: '6q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'9q loss mutation analysis' versus 'AGE'

P value = 0.000147 (t-test), Q value = 0.068

Table S8.  Gene #57: '9q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.7 (11.6)
9Q LOSS MUTATED 268 61.7 (11.7)
9Q LOSS WILD-TYPE 273 57.9 (11.2)

Figure S8.  Get High-res Image Gene #57: '9q loss mutation analysis' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

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

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

  • Number of patients = 552

  • Number of significantly arm-level cnvs = 78

  • Number of selected clinical features = 6

  • 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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