Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and selected clinical features
(Regional_LN 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 72 arm-level results and 7 clinical features across 112 patients, one significant finding detected with Q value < 0.25.

  • 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 72 arm-level results and 7 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 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 t-test Chi-square test
18q gain 6 (5%) 106 0.648
(1.00) 		0.989
(1.00) 		0.663
(1.00) 		1
(1.00) 		0.656
(1.00) 		0.000517
(0.221)
1p gain 12 (11%) 100 0.842
(1.00) 		0.191
(1.00) 		0.751
(1.00) 		1
(1.00) 		0.103
(1.00) 		0.905
(1.00)
1q gain 33 (29%) 79 0.531
(1.00) 		0.84
(1.00) 		0.374
(1.00) 		1
(1.00) 		0.116
(1.00) 		0.714
(1.00)
2p gain 10 (9%) 102 0.962
(1.00) 		0.382
(1.00) 		1
(1.00) 		1
(1.00) 		0.255
(1.00) 		0.435
(1.00)
2q gain 9 (8%) 103 0.756
(1.00) 		0.705
(1.00) 		1
(1.00) 		1
(1.00) 		0.542
(1.00) 		0.685
(1.00)
3p gain 7 (6%) 105 0.577
(1.00) 		0.946
(1.00) 		0.676
(1.00) 		1
(1.00) 		0.174
(1.00) 		0.623
(1.00)
3q gain 8 (7%) 104 0.901
(1.00) 		0.00716
(1.00) 		0.703
(1.00) 		1
(1.00) 		0.722
(1.00) 		0.945
(1.00)
4p gain 10 (9%) 102 0.209
(1.00) 		0.258
(1.00) 		0.281
(1.00) 		1
(1.00) 		0.954
(1.00) 		0.0101
(1.00)
4q gain 10 (9%) 102 0.385
(1.00) 		0.121
(1.00) 		0.501
(1.00) 		1
(1.00) 		0.695
(1.00) 		0.00206
(0.874)
5p gain 12 (11%) 100 0.409
(1.00) 		0.734
(1.00) 		1
(1.00) 		0.399
(1.00) 		0.812
(1.00) 		0.366
(1.00)
5q gain 5 (4%) 107 0.555
(1.00) 		0.647
(1.00) 		1
(1.00) 		0.571
(1.00) 		0.775
(1.00)
6p gain 35 (31%) 77 0.986
(1.00) 		0.366
(1.00) 		0.0303
(1.00) 		1
(1.00) 		0.809
(1.00) 		0.562
(1.00)
6q gain 8 (7%) 104 0.334
(1.00) 		0.801
(1.00) 		0.703
(1.00) 		1
(1.00) 		0.916
(1.00) 		0.527
(1.00)
7p gain 44 (39%) 68 0.869
(1.00) 		0.746
(1.00) 		1
(1.00) 		0.209
(1.00) 		0.229
(1.00) 		0.062
(1.00)
7q gain 44 (39%) 68 0.528
(1.00) 		0.466
(1.00) 		1
(1.00) 		0.218
(1.00) 		0.478
(1.00) 		0.0452
(1.00)
8p gain 18 (16%) 94 0.983
(1.00) 		0.184
(1.00) 		0.421
(1.00) 		0.271
(1.00) 		0.8
(1.00) 		0.538
(1.00)
8q gain 31 (28%) 81 0.533
(1.00) 		0.258
(1.00) 		0.261
(1.00) 		0.483
(1.00) 		0.724
(1.00) 		0.953
(1.00)
9q gain 4 (4%) 108 0.889
(1.00) 		0.588
(1.00) 		1
(1.00) 		0.463
(1.00) 		0.799
(1.00)
11p gain 8 (7%) 104 0.995
(1.00) 		0.494
(1.00) 		1
(1.00) 		1
(1.00) 		0.241
(1.00) 		0.503
(1.00)
11q gain 5 (4%) 107 0.927
(1.00) 		0.617
(1.00) 		1
(1.00) 		1
(1.00) 		0.934
(1.00) 		0.471
(1.00)
12p gain 10 (9%) 102 0.368
(1.00) 		0.929
(1.00) 		0.722
(1.00) 		0.176
(1.00) 		0.328
(1.00) 		0.756
(1.00)
12q gain 4 (4%) 108 0.942
(1.00) 		0.582
(1.00) 		0.307
(1.00) 		1
(1.00) 		0.00575
(1.00) 		0.354
(1.00)
13q gain 15 (13%) 97 0.569
(1.00) 		0.75
(1.00) 		0.23
(1.00) 		1
(1.00) 		0.12
(1.00) 		0.154
(1.00)
14q gain 9 (8%) 103 0.303
(1.00) 		0.654
(1.00) 		0.718
(1.00) 		1
(1.00) 		0.874
(1.00) 		0.849
(1.00)
15q gain 16 (14%) 96 0.703
(1.00) 		0.79
(1.00) 		0.772
(1.00) 		1
(1.00) 		0.789
(1.00) 		0.678
(1.00)
16p gain 6 (5%) 106 0.778
(1.00) 		0.744
(1.00) 		0.374
(1.00) 		1
(1.00) 		0.377
(1.00) 		0.634
(1.00)
16q gain 6 (5%) 106 0.778
(1.00) 		0.838
(1.00) 		1
(1.00) 		1
(1.00) 		0.0441
(1.00) 		0.698
(1.00)
17p gain 8 (7%) 104 0.733
(1.00) 		0.0317
(1.00) 		0.254
(1.00) 		1
(1.00) 		0.991
(1.00) 		0.000914
(0.39)
17q gain 15 (13%) 97 0.101
(1.00) 		0.0133
(1.00) 		0.23
(1.00) 		1
(1.00) 		0.907
(1.00) 		0.0456
(1.00)
18p gain 14 (12%) 98 0.726
(1.00) 		0.247
(1.00) 		0.361
(1.00) 		1
(1.00) 		0.222
(1.00) 		0.000619
(0.264)
19p gain 8 (7%) 104 0.378
(1.00) 		0.481
(1.00) 		0.254
(1.00) 		1
(1.00) 		0.93
(1.00) 		0.113
(1.00)
19q gain 9 (8%) 103 0.378
(1.00) 		0.383
(1.00) 		0.135
(1.00) 		1
(1.00) 		0.478
(1.00) 		0.0854
(1.00)
20p gain 31 (28%) 81 0.889
(1.00) 		0.447
(1.00) 		1
(1.00) 		0.499
(1.00) 		0.992
(1.00) 		0.499
(1.00)
20q gain 39 (35%) 73 0.301
(1.00) 		0.721
(1.00) 		0.831
(1.00) 		0.608
(1.00) 		0.989
(1.00) 		0.512
(1.00)
21q gain 11 (10%) 101 0.672
(1.00) 		0.303
(1.00) 		0.315
(1.00) 		1
(1.00) 		0.917
(1.00) 		0.276
(1.00)
22q gain 24 (21%) 88 0.199
(1.00) 		0.485
(1.00) 		0.808
(1.00) 		0.608
(1.00) 		0.303
(1.00) 		0.139
(1.00)
1p loss 8 (7%) 104 0.948
(1.00) 		0.722
(1.00) 		0.254
(1.00) 		1
(1.00) 		0.689
(1.00) 		0.269
(1.00)
2p loss 12 (11%) 100 0.822
(1.00) 		0.897
(1.00) 		1
(1.00) 		1
(1.00) 		0.997
(1.00) 		0.501
(1.00)
2q loss 11 (10%) 101 0.608
(1.00) 		0.643
(1.00) 		0.315
(1.00) 		0.313
(1.00) 		0.974
(1.00) 		0.328
(1.00)
3p loss 5 (4%) 107 0.775
(1.00) 		0.424
(1.00) 		0.647
(1.00) 		1
(1.00) 		0.971
(1.00) 		0.0424
(1.00)
3q loss 8 (7%) 104 0.716
(1.00) 		0.422
(1.00) 		0.254
(1.00) 		1
(1.00) 		0.981
(1.00) 		0.0314
(1.00)
4p loss 9 (8%) 103 0.782
(1.00) 		0.813
(1.00) 		0.457
(1.00) 		0.313
(1.00) 		0.691
(1.00) 		0.827
(1.00)
4q loss 10 (9%) 102 0.912
(1.00) 		0.772
(1.00) 		0.281
(1.00) 		0.0174
(1.00) 		0.516
(1.00) 		0.708
(1.00)
5p loss 14 (12%) 98 0.302
(1.00) 		0.177
(1.00) 		0.128
(1.00) 		1
(1.00) 		0.88
(1.00) 		0.647
(1.00)
5q loss 24 (21%) 88 0.593
(1.00) 		0.955
(1.00) 		0.224
(1.00) 		0.628
(1.00) 		0.727
(1.00) 		0.882
(1.00)
6p loss 9 (8%) 103 0.243
(1.00) 		0.0178
(1.00) 		1
(1.00) 		1
(1.00) 		0.294
(1.00) 		0.749
(1.00)
6q loss 40 (36%) 72 0.961
(1.00) 		0.0106
(1.00) 		0.531
(1.00) 		0.243
(1.00) 		0.323
(1.00) 		0.195
(1.00)
8p loss 14 (12%) 98 0.976
(1.00) 		0.521
(1.00) 		0.761
(1.00) 		0.371
(1.00) 		0.798
(1.00) 		0.586
(1.00)
8q loss 3 (3%) 109 0.0353
(1.00) 		0.23
(1.00) 		1
(1.00) 		0.989
(1.00) 		0.756
(1.00)
9p loss 57 (51%) 55 0.119
(1.00) 		0.935
(1.00) 		0.839
(1.00) 		0.495
(1.00) 		0.351
(1.00) 		0.167
(1.00)
9q loss 42 (38%) 70 0.153
(1.00) 		0.0222
(1.00) 		0.293
(1.00) 		0.0809
(1.00) 		0.659
(1.00) 		0.133
(1.00)
10p loss 45 (40%) 67 0.0595
(1.00) 		0.504
(1.00) 		0.0215
(1.00) 		0.831
(1.00) 		0.585
(1.00) 		0.636
(1.00)
10q loss 49 (44%) 63 0.0992
(1.00) 		0.0561
(1.00) 		0.153
(1.00) 		0.13
(1.00) 		0.778
(1.00) 		0.552
(1.00)
11p loss 26 (23%) 86 0.877
(1.00) 		0.222
(1.00) 		1
(1.00) 		0.415
(1.00) 		0.183
(1.00) 		0.143
(1.00)
11q loss 30 (27%) 82 0.467
(1.00) 		0.779
(1.00) 		0.82
(1.00) 		0.466
(1.00) 		0.0694
(1.00) 		0.131
(1.00)
12p loss 5 (4%) 107 0.838
(1.00) 		0.637
(1.00) 		0.647
(1.00) 		0.0979
(1.00) 		0.00969
(1.00) 		0.344
(1.00)
12q loss 8 (7%) 104 0.894
(1.00) 		0.407
(1.00) 		0.105
(1.00) 		0.137
(1.00) 		0.0853
(1.00) 		0.831
(1.00)
13q loss 17 (15%) 95 0.915
(1.00) 		0.709
(1.00) 		1
(1.00) 		0.00498
(1.00) 		0.376
(1.00) 		0.17
(1.00)
14q loss 25 (22%) 87 0.757
(1.00) 		0.86
(1.00) 		1
(1.00) 		0.45
(1.00) 		0.675
(1.00) 		0.486
(1.00)
15q loss 7 (6%) 105 0.238
(1.00) 		0.344
(1.00) 		0.676
(1.00) 		0.218
(1.00) 		0.534
(1.00) 		0.176
(1.00)
16p loss 8 (7%) 104 0.152
(1.00) 		0.994
(1.00) 		0.703
(1.00) 		1
(1.00) 		0.885
(1.00) 		0.043
(1.00)
16q loss 16 (14%) 96 0.103
(1.00) 		0.216
(1.00) 		1
(1.00) 		0.476
(1.00) 		0.807
(1.00) 		0.0989
(1.00)
17p loss 28 (25%) 84 0.406
(1.00) 		0.0765
(1.00) 		1
(1.00) 		0.302
(1.00) 		0.46
(1.00) 		0.829
(1.00)
17q loss 13 (12%) 99 0.854
(1.00) 		0.759
(1.00) 		0.54
(1.00) 		0.233
(1.00) 		0.0287
(1.00) 		0.692
(1.00)
18p loss 18 (16%) 94 0.692
(1.00) 		0.58
(1.00) 		0.0246
(1.00) 		1
(1.00) 		0.203
(1.00) 		0.718
(1.00)
18q loss 18 (16%) 94 0.478
(1.00) 		0.886
(1.00) 		0.0934
(1.00) 		0.546
(1.00) 		0.365
(1.00) 		0.627
(1.00)
19p loss 12 (11%) 100 0.833
(1.00) 		0.225
(1.00) 		0.00851
(1.00) 		0.067
(1.00) 		0.0717
(1.00) 		0.0267
(1.00)
19q loss 12 (11%) 100 0.532
(1.00) 		0.13
(1.00) 		0.187
(1.00) 		0.047
(1.00) 		0.0909
(1.00) 		0.0317
(1.00)
20p loss 3 (3%) 109 0.166
(1.00) 		0.318
(1.00) 		0.23
(1.00) 		1
(1.00) 		0.576
(1.00) 		0.437
(1.00)
21q loss 15 (13%) 97 0.917
(1.00) 		0.714
(1.00) 		1
(1.00) 		1
(1.00) 		0.75
(1.00) 		0.0496
(1.00)
22q loss 7 (6%) 105 0.587
(1.00) 		0.262
(1.00) 		1
(1.00) 		0.251
(1.00) 		0.989
(1.00) 		0.633
(1.00)
Xq loss 3 (3%) 109 0.361
(1.00) 		0.0287
(1.00) 		1
(1.00) 		0.989
(1.00) 		0.862
(1.00)
'18q gain mutation analysis' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000517 (Chi-square test), Q value = 0.22

Table S1.  Gene #30: '18q gain mutation analysis' versus Clinical Feature #7: '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 15 7 11 13 5 5 2 4 3 10 18 3
18Q GAIN MUTATED 1 1 0 0 0 0 0 1 0 1 0 1 0
18Q GAIN WILD-TYPE 0 14 7 11 13 5 5 1 4 2 10 17 3

Figure S1.  Get High-res Image Gene #30: '18q gain mutation analysis' versus Clinical Feature #7: 'NEOPLASM.DISEASESTAGE'

Methods & Data
Input

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

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

  • Number of patients = 112

  • Number of significantly arm-level cnvs = 72

  • Number of selected clinical features = 7

  • 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)
[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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[5] 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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