Skin Cutaneous Melanoma: Correlation between copy number variation genes (focal) and selected clinical features
(BRAF_Hotspot_Mutants cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.

Summary

Testing the association between copy number variation 36 arm-level results and 8 clinical features across 67 patients, one significant finding detected with Q value < 0.25.

  • Amp Peak 5(6p25.3) cnv correlated to 'Time to Death'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 36 arm-level results and 8 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 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
Amp Peak 5(6p25 3) 32 (48%) 35 0.000576
(0.145)
0.241
(1.00)
1
(1.00)
1
(1.00)
0.477
(1.00)
0.447
(1.00)
0.691
(1.00)
Amp Peak 1(1q43) 34 (51%) 33 0.21
(1.00)
0.681
(1.00)
0.498
(1.00)
0.437
(1.00)
0.289
(1.00)
0.775
(1.00)
0.975
(1.00)
Amp Peak 2(2q36 2) 18 (27%) 49 0.992
(1.00)
0.363
(1.00)
0.316
(1.00)
0.141
(1.00)
0.386
(1.00)
0.371
(1.00)
0.805
(1.00)
Amp Peak 3(3p13) 17 (25%) 50 0.145
(1.00)
0.754
(1.00)
0.384
(1.00)
0.231
(1.00)
0.798
(1.00)
0.583
(1.00)
0.562
(1.00)
Amp Peak 4(5p15 33) 24 (36%) 43 0.373
(1.00)
0.178
(1.00)
0.419
(1.00)
1
(1.00)
0.508
(1.00)
0.684
(1.00)
0.838
(1.00)
Amp Peak 6(7q21 11) 49 (73%) 18 0.887
(1.00)
0.515
(1.00)
0.697
(1.00)
0.0847
(1.00)
0.386
(1.00)
0.3
(1.00)
0.226
(1.00)
Amp Peak 7(7q34) 55 (82%) 12 0.739
(1.00)
0.0314
(1.00)
0.806
(1.00)
0.187
(1.00)
0.899
(1.00)
0.493
(1.00)
0.151
(1.00)
Amp Peak 8(8q21 13) 36 (54%) 31 0.341
(1.00)
0.968
(1.00)
0.189
(1.00)
0.436
(1.00)
0.272
(1.00)
0.419
(1.00)
0.46
(1.00)
Amp Peak 9(8q24 21) 37 (55%) 30 0.43
(1.00)
0.63
(1.00)
0.2
(1.00)
0.607
(1.00)
0.248
(1.00)
0.476
(1.00)
0.454
(1.00)
Amp Peak 10(12q15) 10 (15%) 57 0.99
(1.00)
0.782
(1.00)
0.773
(1.00)
0.478
(1.00)
0.899
(1.00)
0.254
(1.00)
0.574
(1.00)
Amp Peak 11(15q26 2) 24 (36%) 43 0.608
(1.00)
0.89
(1.00)
0.365
(1.00)
0.175
(1.00)
0.401
(1.00)
0.442
(1.00)
0.229
(1.00)
Amp Peak 12(17q24 3) 24 (36%) 43 0.406
(1.00)
0.173
(1.00)
1
(1.00)
0.418
(1.00)
0.388
(1.00)
0.68
(1.00)
0.377
(1.00)
Amp Peak 13(19p13 2) 17 (25%) 50 0.96
(1.00)
0.381
(1.00)
0.924
(1.00)
0.0388
(1.00)
0.173
(1.00)
0.652
(1.00)
0.349
(1.00)
Amp Peak 14(22q13 32) 28 (42%) 39 0.968
(1.00)
0.317
(1.00)
0.189
(1.00)
0.117
(1.00)
0.419
(1.00)
0.167
(1.00)
0.713
(1.00)
Del Peak 1(1p36 31) 20 (30%) 47 0.186
(1.00)
0.342
(1.00)
1
(1.00)
1
(1.00)
0.386
(1.00)
0.253
(1.00)
0.635
(1.00)
Del Peak 2(1p22 1) 24 (36%) 43 0.833
(1.00)
0.204
(1.00)
0.235
(1.00)
1
(1.00)
0.4
(1.00)
0.61
(1.00)
0.278
(1.00)
Del Peak 3(2q37 3) 18 (27%) 49 0.735
(1.00)
0.764
(1.00)
0.582
(1.00)
0.566
(1.00)
0.151
(1.00)
0.955
(1.00)
0.73
(1.00)
Del Peak 4(3p26 1) 16 (24%) 51 0.259
(1.00)
0.233
(1.00)
0.722
(1.00)
0.129
(1.00)
0.794
(1.00)
0.201
(1.00)
0.795
(1.00)
Del Peak 5(3q27 2) 13 (19%) 54 0.112
(1.00)
0.899
(1.00)
0.47
(1.00)
0.00619
(1.00)
0.754
(1.00)
0.354
(1.00)
0.481
(1.00)
Del Peak 6(4p16 3) 15 (22%) 52 0.301
(1.00)
0.0267
(1.00)
0.0491
(1.00)
1
(1.00)
0.281
(1.00)
0.961
(1.00)
0.546
(1.00)
Del Peak 7(4q34 3) 18 (27%) 49 0.0558
(1.00)
0.379
(1.00)
0.189
(1.00)
0.771
(1.00)
0.386
(1.00)
0.824
(1.00)
0.619
(1.00)
Del Peak 8(5q11 2) 24 (36%) 43 0.423
(1.00)
0.188
(1.00)
0.669
(1.00)
0.594
(1.00)
0.322
(1.00)
0.737
(1.00)
0.345
(1.00)
Del Peak 9(5q31 3) 32 (48%) 35 0.265
(1.00)
0.801
(1.00)
0.509
(1.00)
1
(1.00)
0.534
(1.00)
0.848
(1.00)
0.328
(1.00)
Del Peak 10(6q25 2) 45 (67%) 22 0.248
(1.00)
0.196
(1.00)
1
(1.00)
1
(1.00)
0.508
(1.00)
0.38
(1.00)
0.491
(1.00)
Del Peak 11(6q27) 44 (66%) 23 0.243
(1.00)
0.21
(1.00)
1
(1.00)
1
(1.00)
0.529
(1.00)
0.44
(1.00)
0.643
(1.00)
Del Peak 12(9p21 3) 54 (81%) 13 0.907
(1.00)
0.461
(1.00)
0.255
(1.00)
0.521
(1.00)
0.281
(1.00)
0.583
(1.00)
0.749
(1.00)
Del Peak 13(9q21 2) 34 (51%) 33 0.893
(1.00)
0.929
(1.00)
0.0935
(1.00)
0.0684
(1.00)
0.272
(1.00)
0.198
(1.00)
0.387
(1.00)
Del Peak 14(10q21 1) 48 (72%) 19 0.867
(1.00)
0.564
(1.00)
0.673
(1.00)
0.0199
(1.00)
0.173
(1.00)
0.45
(1.00)
0.746
(1.00)
Del Peak 15(10q23 31) 51 (76%) 16 0.878
(1.00)
0.538
(1.00)
0.918
(1.00)
0.0129
(1.00)
0.127
(1.00)
0.371
(1.00)
0.642
(1.00)
Del Peak 16(11q22 3) 36 (54%) 31 0.304
(1.00)
0.437
(1.00)
0.774
(1.00)
0.122
(1.00)
0.282
(1.00)
0.0686
(1.00)
0.369
(1.00)
Del Peak 17(12q24 32) 11 (16%) 56 0.725
(1.00)
0.621
(1.00)
0.704
(1.00)
0.157
(1.00)
0.12
(1.00)
0.291
(1.00)
0.447
(1.00)
Del Peak 18(14q31 1) 23 (34%) 44 0.28
(1.00)
0.333
(1.00)
1
(1.00)
0.584
(1.00)
0.275
(1.00)
0.401
(1.00)
0.313
(1.00)
Del Peak 19(15q21 1) 13 (19%) 54 0.161
(1.00)
0.876
(1.00)
0.622
(1.00)
0.327
(1.00)
0.0606
(1.00)
0.691
(1.00)
0.92
(1.00)
Del Peak 20(16q23 3) 19 (28%) 48 0.548
(1.00)
0.383
(1.00)
0.351
(1.00)
0.0436
(1.00)
0.374
(1.00)
0.465
(1.00)
0.146
(1.00)
Del Peak 21(17q12) 19 (28%) 48 0.181
(1.00)
0.974
(1.00)
0.874
(1.00)
0.389
(1.00)
0.173
(1.00)
0.834
(1.00)
0.27
(1.00)
Del Peak 22(19p13 3) 24 (36%) 43 0.6
(1.00)
0.922
(1.00)
0.892
(1.00)
0.286
(1.00)
0.0732
(1.00)
0.728
(1.00)
0.204
(1.00)
'Amp Peak 5(6p25.3) mutation analysis' versus 'Time to Death'

P value = 0.000576 (logrank test), Q value = 0.15

Table S1.  Gene #5: 'Amp Peak 5(6p25.3) mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 36 19 4.2 - 98.8 (15.0)
AMP PEAK 5(6P25.3) MUTATED 14 12 4.2 - 98.8 (12.1)
AMP PEAK 5(6P25.3) WILD-TYPE 22 7 4.4 - 84.7 (26.1)

Figure S1.  Get High-res Image Gene #5: 'Amp Peak 5(6p25.3) mutation analysis' versus Clinical Feature #1: 'Time to Death'

Methods & Data
Input
  • Mutation data file = all_lesions.conf_99.cnv.cluster.txt

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

  • Number of patients = 67

  • Number of significantly arm-level cnvs = 36

  • 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)
[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)