Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and selected clinical features
(Regional_Metastatic 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 8 clinical features across 147 patients, 2 significant findings detected with Q value < 0.25.

  • 18p gain cnv correlated to 'NEOPLASM.DISEASESTAGE'.

  • 18q gain cnv correlated to 'NEOPLASM.DISEASESTAGE'.

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 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE PRIMARY
SITE
OF
DISEASE 		GENDER DISTANT
METASTASIS 		LYMPH
NODE
METASTASIS 		TUMOR
STAGECODE 		NEOPLASM
DISEASESTAGE
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Chi-square test Chi-square test t-test Chi-square test
18p gain 19 (13%) 128 0.976
(1.00) 		0.104
(1.00) 		0.777
(1.00) 		0.305
(1.00) 		0.541
(1.00) 		0.26
(1.00) 		4.46e-06
(0.00226)
18q gain 10 (7%) 137 0.643
(1.00) 		0.537
(1.00) 		0.25
(1.00) 		0.743
(1.00) 		0.983
(1.00) 		0.326
(1.00) 		1.13e-07
(5.72e-05)
1p gain 20 (14%) 127 0.073
(1.00) 		0.0546
(1.00) 		0.258
(1.00) 		1
(1.00) 		0.904
(1.00) 		0.22
(1.00) 		0.0385
(1.00)
1q gain 48 (33%) 99 0.213
(1.00) 		0.924
(1.00) 		0.153
(1.00) 		0.581
(1.00) 		0.689
(1.00) 		0.165
(1.00) 		0.388
(1.00)
2p gain 16 (11%) 131 0.843
(1.00) 		0.412
(1.00) 		0.534
(1.00) 		0.789
(1.00) 		0.94
(1.00) 		0.0729
(1.00) 		0.428
(1.00)
2q gain 15 (10%) 132 0.624
(1.00) 		0.709
(1.00) 		0.351
(1.00) 		1
(1.00) 		0.947
(1.00) 		0.175
(1.00) 		0.537
(1.00)
3p gain 12 (8%) 135 0.342
(1.00) 		0.867
(1.00) 		0.158
(1.00) 		0.754
(1.00) 		0.973
(1.00) 		0.052
(1.00) 		0.396
(1.00)
3q gain 15 (10%) 132 0.533
(1.00) 		0.303
(1.00) 		0.196
(1.00) 		0.778
(1.00) 		0.947
(1.00) 		0.0635
(1.00) 		0.652
(1.00)
4p gain 14 (10%) 133 0.104
(1.00) 		0.07
(1.00) 		0.742
(1.00) 		0.565
(1.00) 		0.961
(1.00) 		0.111
(1.00) 		0.102
(1.00)
4q gain 12 (8%) 135 0.207
(1.00) 		0.0782
(1.00) 		0.732
(1.00) 		1
(1.00) 		0.978
(1.00) 		0.315
(1.00) 		0.114
(1.00)
5p gain 13 (9%) 134 0.358
(1.00) 		0.829
(1.00) 		0.303
(1.00) 		0.771
(1.00) 		0.386
(1.00) 		0.689
(1.00) 		0.145
(1.00)
5q gain 5 (3%) 142 0.602
(1.00) 		0.339
(1.00) 		1
(1.00) 		0.993
(1.00) 		0.57
(1.00) 		0.726
(1.00)
6p gain 45 (31%) 102 0.242
(1.00) 		0.34
(1.00) 		0.534
(1.00) 		0.138
(1.00) 		0.72
(1.00) 		0.443
(1.00) 		0.243
(1.00)
6q gain 9 (6%) 138 0.65
(1.00) 		0.557
(1.00) 		1
(1.00) 		0.721
(1.00) 		0.177
(1.00) 		0.895
(1.00) 		0.437
(1.00)
7p gain 63 (43%) 84 0.21
(1.00) 		0.596
(1.00) 		0.124
(1.00) 		0.297
(1.00) 		0.138
(1.00) 		0.0588
(1.00) 		0.0459
(1.00)
7q gain 62 (42%) 85 0.557
(1.00) 		0.555
(1.00) 		0.241
(1.00) 		0.601
(1.00) 		0.145
(1.00) 		0.0684
(1.00) 		0.0173
(1.00)
8p gain 29 (20%) 118 0.894
(1.00) 		0.422
(1.00) 		0.0546
(1.00) 		0.668
(1.00) 		0.239
(1.00) 		0.492
(1.00) 		0.167
(1.00)
8q gain 46 (31%) 101 0.246
(1.00) 		0.366
(1.00) 		0.0992
(1.00) 		0.266
(1.00) 		0.413
(1.00) 		0.25
(1.00) 		0.453
(1.00)
9p gain 3 (2%) 144 0.0314
(1.00) 		0.561
(1.00) 		0.285
(1.00) 		0.998
(1.00) 		0.0535
(1.00) 		0.518
(1.00)
9q gain 3 (2%) 144 0.873
(1.00) 		1
(1.00) 		0.285
(1.00) 		0.998
(1.00) 		0.288
(1.00) 		0.959
(1.00)
11p gain 9 (6%) 138 0.915
(1.00) 		0.29
(1.00) 		0.687
(1.00) 		0.493
(1.00) 		0.983
(1.00) 		0.0395
(1.00) 		0.718
(1.00)
11q gain 6 (4%) 141 0.856
(1.00) 		0.33
(1.00) 		1
(1.00) 		0.424
(1.00) 		0.993
(1.00) 		0.758
(1.00) 		0.602
(1.00)
12p gain 16 (11%) 131 0.776
(1.00) 		0.685
(1.00) 		0.213
(1.00) 		0.419
(1.00) 		0.0217
(1.00) 		0.102
(1.00) 		0.0487
(1.00)
12q gain 7 (5%) 140 0.948
(1.00) 		0.421
(1.00) 		0.671
(1.00) 		0.422
(1.00) 		0.99
(1.00) 		0.0248
(1.00) 		0.0736
(1.00)
13q gain 21 (14%) 126 0.724
(1.00) 		0.851
(1.00) 		0.586
(1.00) 		0.808
(1.00) 		0.571
(1.00) 		0.243
(1.00) 		0.319
(1.00)
14q gain 12 (8%) 135 0.77
(1.00) 		0.975
(1.00) 		1
(1.00) 		1
(1.00) 		0.973
(1.00) 		0.783
(1.00) 		0.394
(1.00)
15q gain 21 (14%) 126 0.478
(1.00) 		0.673
(1.00) 		1
(1.00) 		0.808
(1.00) 		0.894
(1.00) 		0.337
(1.00) 		0.552
(1.00)
16p gain 12 (8%) 135 0.305
(1.00) 		0.667
(1.00) 		0.158
(1.00) 		0.754
(1.00) 		0.961
(1.00) 		0.493
(1.00) 		0.509
(1.00)
16q gain 10 (7%) 137 0.55
(1.00) 		0.922
(1.00) 		0.25
(1.00) 		0.743
(1.00) 		0.973
(1.00) 		0.0711
(1.00) 		0.529
(1.00)
17p gain 13 (9%) 134 0.661
(1.00) 		0.627
(1.00) 		0.192
(1.00) 		0.544
(1.00) 		0.285
(1.00) 		0.96
(1.00) 		0.00352
(1.00)
17q gain 21 (14%) 126 0.165
(1.00) 		0.0484
(1.00) 		1
(1.00) 		0.466
(1.00) 		0.597
(1.00) 		0.68
(1.00) 		0.141
(1.00)
19p gain 7 (5%) 140 0.497
(1.00) 		0.834
(1.00) 		0.198
(1.00) 		0.698
(1.00) 		0.987
(1.00) 		0.988
(1.00) 		0.0163
(1.00)
19q gain 11 (7%) 136 0.386
(1.00) 		0.332
(1.00) 		1
(1.00) 		0.0529
(1.00) 		0.967
(1.00) 		0.431
(1.00) 		0.0848
(1.00)
20p gain 43 (29%) 104 0.946
(1.00) 		0.852
(1.00) 		0.524
(1.00) 		1
(1.00) 		0.394
(1.00) 		0.911
(1.00) 		0.489
(1.00)
20q gain 53 (36%) 94 0.371
(1.00) 		0.844
(1.00) 		0.687
(1.00) 		0.858
(1.00) 		0.17
(1.00) 		0.964
(1.00) 		0.391
(1.00)
21q gain 17 (12%) 130 0.181
(1.00) 		0.955
(1.00) 		0.238
(1.00) 		0.293
(1.00) 		0.471
(1.00) 		0.296
(1.00) 		0.0448
(1.00)
22q gain 37 (25%) 110 0.27
(1.00) 		0.435
(1.00) 		0.0753
(1.00) 		0.843
(1.00) 		0.726
(1.00) 		0.0151
(1.00) 		0.0135
(1.00)
1p loss 12 (8%) 135 0.255
(1.00) 		0.657
(1.00) 		0.48
(1.00) 		0.346
(1.00) 		0.978
(1.00) 		0.722
(1.00) 		0.0378
(1.00)
1q loss 4 (3%) 143 0.469
(1.00) 		0.0384
(1.00) 		0.0421
(1.00) 		0.127
(1.00) 		0.996
(1.00) 		0.963
(1.00) 		0.589
(1.00)
2p loss 14 (10%) 133 0.741
(1.00) 		0.772
(1.00) 		0.52
(1.00) 		1
(1.00) 		0.967
(1.00) 		0.974
(1.00) 		0.237
(1.00)
2q loss 13 (9%) 134 0.801
(1.00) 		0.411
(1.00) 		0.734
(1.00) 		0.544
(1.00) 		0.285
(1.00) 		0.916
(1.00) 		0.122
(1.00)
3p loss 10 (7%) 137 0.563
(1.00) 		0.235
(1.00) 		0.0583
(1.00) 		0.743
(1.00) 		0.983
(1.00) 		0.562
(1.00) 		0.0458
(1.00)
3q loss 12 (8%) 135 0.697
(1.00) 		0.562
(1.00) 		0.48
(1.00) 		0.346
(1.00) 		0.973
(1.00) 		0.722
(1.00) 		0.0767
(1.00)
4p loss 15 (10%) 132 0.894
(1.00) 		0.617
(1.00) 		0.196
(1.00) 		0.156
(1.00) 		0.386
(1.00) 		0.856
(1.00) 		0.37
(1.00)
4q loss 16 (11%) 131 0.763
(1.00) 		0.591
(1.00) 		0.213
(1.00) 		0.0945
(1.00) 		0.00137
(0.692) 		0.774
(1.00) 		0.267
(1.00)
5p loss 18 (12%) 129 0.401
(1.00) 		0.16
(1.00) 		1
(1.00) 		0.435
(1.00) 		0.94
(1.00) 		0.896
(1.00) 		0.939
(1.00)
5q loss 31 (21%) 116 0.659
(1.00) 		0.943
(1.00) 		1
(1.00) 		0.677
(1.00) 		0.6
(1.00) 		0.561
(1.00) 		0.941
(1.00)
6p loss 11 (7%) 136 0.304
(1.00) 		0.275
(1.00) 		0.724
(1.00) 		0.52
(1.00) 		0.967
(1.00) 		0.889
(1.00) 		0.796
(1.00)
6q loss 53 (36%) 94 0.561
(1.00) 		0.116
(1.00) 		0.106
(1.00) 		0.474
(1.00) 		0.443
(1.00) 		0.6
(1.00) 		0.143
(1.00)
8p loss 16 (11%) 131 0.398
(1.00) 		0.902
(1.00) 		0.36
(1.00) 		0.789
(1.00) 		0.386
(1.00) 		0.707
(1.00) 		0.298
(1.00)
9p loss 82 (56%) 65 0.0466
(1.00) 		0.648
(1.00) 		0.0503
(1.00) 		1
(1.00) 		0.456
(1.00) 		0.0427
(1.00) 		0.103
(1.00)
9q loss 61 (41%) 86 0.255
(1.00) 		0.0166
(1.00) 		0.115
(1.00) 		0.0796
(1.00) 		0.272
(1.00) 		0.463
(1.00) 		0.0884
(1.00)
10p loss 64 (44%) 83 0.0328
(1.00) 		0.34
(1.00) 		0.0792
(1.00) 		0.164
(1.00) 		0.719
(1.00) 		0.168
(1.00) 		0.698
(1.00)
10q loss 71 (48%) 76 0.0866
(1.00) 		0.0132
(1.00) 		0.0547
(1.00) 		0.389
(1.00) 		0.375
(1.00) 		0.533
(1.00) 		0.742
(1.00)
11p loss 35 (24%) 112 0.516
(1.00) 		0.33
(1.00) 		0.821
(1.00) 		0.547
(1.00) 		0.296
(1.00) 		0.373
(1.00) 		0.136
(1.00)
11q loss 39 (27%) 108 0.911
(1.00) 		0.904
(1.00) 		1
(1.00) 		0.697
(1.00) 		0.33
(1.00) 		0.31
(1.00) 		0.0488
(1.00)
12p loss 8 (5%) 139 0.31
(1.00) 		0.732
(1.00) 		0.396
(1.00) 		0.454
(1.00) 		0.00286
(1.00) 		0.882
(1.00) 		0.559
(1.00)
12q loss 15 (10%) 132 0.458
(1.00) 		0.618
(1.00) 		0.0492
(1.00) 		0.156
(1.00) 		0.0145
(1.00) 		0.865
(1.00) 		0.62
(1.00)
13q loss 23 (16%) 124 0.314
(1.00) 		0.487
(1.00) 		0.792
(1.00) 		1
(1.00) 		0.00129
(0.654) 		0.291
(1.00) 		0.362
(1.00)
14q loss 35 (24%) 112 0.827
(1.00) 		0.95
(1.00) 		0.497
(1.00) 		1
(1.00) 		0.33
(1.00) 		0.519
(1.00) 		0.536
(1.00)
15q loss 12 (8%) 135 0.324
(1.00) 		0.185
(1.00) 		0.158
(1.00) 		1
(1.00) 		0.231
(1.00) 		0.513
(1.00) 		0.737
(1.00)
16p loss 9 (6%) 138 0.325
(1.00) 		0.834
(1.00) 		0.687
(1.00) 		0.721
(1.00) 		0.983
(1.00) 		0.84
(1.00) 		0.0223
(1.00)
16q loss 20 (14%) 127 0.0649
(1.00) 		0.265
(1.00) 		1
(1.00) 		1
(1.00) 		0.571
(1.00) 		0.256
(1.00) 		0.0595
(1.00)
17p loss 33 (22%) 114 0.769
(1.00) 		0.266
(1.00) 		0.247
(1.00) 		0.541
(1.00) 		0.298
(1.00) 		0.592
(1.00) 		0.791
(1.00)
17q loss 12 (8%) 135 0.776
(1.00) 		0.759
(1.00) 		0.295
(1.00) 		1
(1.00) 		0.0201
(1.00) 		0.823
(1.00) 		0.844
(1.00)
18p loss 26 (18%) 121 0.708
(1.00) 		0.502
(1.00) 		0.446
(1.00) 		0.499
(1.00) 		0.837
(1.00) 		0.214
(1.00) 		0.293
(1.00)
18q loss 24 (16%) 123 0.694
(1.00) 		0.314
(1.00) 		1
(1.00) 		0.492
(1.00) 		0.686
(1.00) 		0.427
(1.00) 		0.237
(1.00)
19p loss 14 (10%) 133 0.693
(1.00) 		0.148
(1.00) 		0.52
(1.00) 		0.00602
(1.00) 		0.0145
(1.00) 		0.602
(1.00) 		0.222
(1.00)
19q loss 15 (10%) 132 0.922
(1.00) 		0.406
(1.00) 		1
(1.00) 		0.156
(1.00) 		0.00514
(1.00) 		0.4
(1.00) 		0.379
(1.00)
20p loss 6 (4%) 141 0.225
(1.00) 		0.551
(1.00) 		0.147
(1.00) 		1
(1.00) 		0.0408
(1.00) 		0.84
(1.00) 		0.574
(1.00)
21q loss 18 (12%) 129 0.946
(1.00) 		0.722
(1.00) 		0.565
(1.00) 		0.795
(1.00) 		0.923
(1.00) 		0.661
(1.00) 		0.0093
(1.00)
22q loss 12 (8%) 135 0.629
(1.00) 		0.467
(1.00) 		0.158
(1.00) 		0.346
(1.00) 		0.337
(1.00) 		0.99
(1.00) 		0.469
(1.00)
Xq loss 4 (3%) 143 0.711
(1.00) 		0.675
(1.00) 		1
(1.00) 		0.0145
(1.00) 		0.998
(1.00) 		0.986
(1.00) 		0.747
(1.00)
'18p gain mutation analysis' versus 'NEOPLASM.DISEASESTAGE'

P value = 4.46e-06 (Chi-square test), Q value = 0.0023

Table S1.  Gene #30: '18p gain mutation analysis' versus Clinical Feature #8: 'NEOPLASM.DISEASESTAGE'

nPatients I OR II NOS STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE IIC STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
ALL 1 16 8 13 17 7 8 4 8 5 16 21 4
18P GAIN MUTATED 1 3 0 0 1 0 0 4 1 3 2 3 0
18P GAIN WILD-TYPE 0 13 8 13 16 7 8 0 7 2 14 18 4

Figure S1.  Get High-res Image Gene #30: '18p gain mutation analysis' versus Clinical Feature #8: 'NEOPLASM.DISEASESTAGE'

'18q gain mutation analysis' versus 'NEOPLASM.DISEASESTAGE'

P value = 1.13e-07 (Chi-square test), Q value = 5.7e-05

Table S2.  Gene #31: '18q gain mutation analysis' versus Clinical Feature #8: 'NEOPLASM.DISEASESTAGE'

nPatients I OR II NOS STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE IIC STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
ALL 1 16 8 13 17 7 8 4 8 5 16 21 4
18Q GAIN MUTATED 1 1 0 0 0 0 0 3 0 2 0 2 0
18Q GAIN WILD-TYPE 0 15 8 13 17 7 8 1 8 3 16 19 4

Figure S2.  Get High-res Image Gene #31: '18q gain mutation analysis' versus Clinical Feature #8: 'NEOPLASM.DISEASESTAGE'

Methods & Data
Input

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

  • Clinical data file = SKCM-Regional_Metastatic.clin.merged.picked.txt

  • Number of patients = 147

  • Number of significantly arm-level cnvs = 73

  • Number of selected clinical features = 8

  • 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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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)
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