Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and selected clinical features<BR>(BRAF_Hotspot

Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result 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 arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 70 arm-level results and 8 clinical features across 67 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 70 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
18q gain	4 (6%)	63		0.794 (1.00)	0.475 (1.00)	0.294 (1.00)	0.991 (1.00)	0.953 (1.00)		4.1e-05 (0.0195)
1p gain	3 (4%)	64		0.254 (1.00)	0.0768 (1.00)	0.249 (1.00)	0.991 (1.00)	0.962 (1.00)		0.139 (1.00)
1q gain	16 (24%)	51	0.686 (1.00)	0.802 (1.00)	0.106 (1.00)	0.762 (1.00)	0.786 (1.00)	0.648 (1.00)		0.774 (1.00)
2p gain	6 (9%)	61	0.076 (1.00)	0.00329 (1.00)	0.192 (1.00)	0.167 (1.00)	0.964 (1.00)	0.0207 (1.00)		0.689 (1.00)
2q gain	6 (9%)	61	0.076 (1.00)	0.00329 (1.00)	0.192 (1.00)	0.167 (1.00)	0.964 (1.00)	0.0207 (1.00)		0.689 (1.00)
3p gain	4 (6%)	63	0.696 (1.00)	0.469 (1.00)	0.0247 (1.00)	0.593 (1.00)	0.984 (1.00)	0.415 (1.00)		0.92 (1.00)
3q gain	5 (7%)	62	0.68 (1.00)	0.55 (1.00)	0.0514 (1.00)	1 (1.00)	0.975 (1.00)	0.567 (1.00)		0.968 (1.00)
4p gain	5 (7%)	62	0.824 (1.00)	0.0886 (1.00)	1 (1.00)	1 (1.00)	0.975 (1.00)	0.277 (1.00)		0.065 (1.00)
4q gain	5 (7%)	62	0.824 (1.00)	0.225 (1.00)	0.758 (1.00)	1 (1.00)	0.984 (1.00)	0.339 (1.00)		0.137 (1.00)
5p gain	7 (10%)	60	0.318 (1.00)	0.831 (1.00)	0.47 (1.00)	1 (1.00)	0.0823 (1.00)	0.799 (1.00)		0.227 (1.00)
6p gain	15 (22%)	52	0.379 (1.00)	0.695 (1.00)	0.529 (1.00)	0.542 (1.00)	0.311 (1.00)	0.894 (1.00)		0.715 (1.00)
6q gain	5 (7%)	62		0.687 (1.00)	0.581 (1.00)	1 (1.00)	0.0202 (1.00)	0.941 (1.00)		0.501 (1.00)
7p gain	40 (60%)	27	0.224 (1.00)	0.635 (1.00)	0.394 (1.00)	0.0363 (1.00)	0.379 (1.00)	0.408 (1.00)		0.524 (1.00)
7q gain	44 (66%)	23	0.275 (1.00)	0.483 (1.00)	0.388 (1.00)	0.027 (1.00)	0.4 (1.00)	0.514 (1.00)		0.249 (1.00)
8p gain	12 (18%)	55	0.242 (1.00)	0.859 (1.00)	0.593 (1.00)	0.086 (1.00)	0.246 (1.00)	0.189 (1.00)		0.537 (1.00)
8q gain	23 (34%)	44	0.14 (1.00)	0.702 (1.00)	0.941 (1.00)	0.0606 (1.00)	0.25 (1.00)	0.388 (1.00)		0.541 (1.00)
11p gain	5 (7%)	62		0.116 (1.00)	0.758 (1.00)	1 (1.00)	0.975 (1.00)	0.183 (1.00)		0.248 (1.00)
11q gain	3 (4%)	64		0.123 (1.00)	1 (1.00)	1 (1.00)	0.991 (1.00)	0.962 (1.00)		0.507 (1.00)
12p gain	11 (16%)	56	0.595 (1.00)	0.0175 (1.00)	0.704 (1.00)	0.0862 (1.00)	0.246 (1.00)	0.271 (1.00)		0.241 (1.00)
12q gain	5 (7%)	62	0.705 (1.00)	0.592 (1.00)	1 (1.00)	0.163 (1.00)	0.975 (1.00)	0.0166 (1.00)		0.294 (1.00)
13q gain	8 (12%)	59	0.383 (1.00)	0.326 (1.00)	0.318 (1.00)	1 (1.00)	0.951 (1.00)	0.00839 (1.00)		0.0353 (1.00)
14q gain	5 (7%)	62	0.544 (1.00)	0.606 (1.00)	0.581 (1.00)	0.163 (1.00)	0.975 (1.00)	0.01 (1.00)		0.689 (1.00)
15q gain	11 (16%)	56	0.372 (1.00)	0.02 (1.00)	0.884 (1.00)	0.316 (1.00)	0.878 (1.00)	0.478 (1.00)		0.507 (1.00)
16p gain	5 (7%)	62	0.34 (1.00)	0.0672 (1.00)	0.581 (1.00)	1 (1.00)	0.975 (1.00)	0.238 (1.00)		0.137 (1.00)
16q gain	6 (9%)	61	0.34 (1.00)	0.0374 (1.00)	0.794 (1.00)	0.655 (1.00)	0.964 (1.00)	0.0622 (1.00)		0.282 (1.00)
17p gain	7 (10%)	60	0.52 (1.00)	0.374 (1.00)	0.689 (1.00)	1 (1.00)	0.964 (1.00)	0.953 (1.00)		0.311 (1.00)
17q gain	6 (9%)	61	0.52 (1.00)	0.0546 (1.00)	1 (1.00)	1 (1.00)	0.964 (1.00)	0.953 (1.00)		0.311 (1.00)
18p gain	10 (15%)	57	0.545 (1.00)	0.342 (1.00)	0.882 (1.00)	0.478 (1.00)	0.166 (1.00)	0.207 (1.00)		0.077 (1.00)
19p gain	6 (9%)	61		0.479 (1.00)	0.794 (1.00)	0.655 (1.00)	0.0467 (1.00)	0.899 (1.00)		0.0183 (1.00)
19q gain	7 (10%)	60	0.503 (1.00)	0.352 (1.00)	0.47 (1.00)	0.675 (1.00)	0.951 (1.00)	0.661 (1.00)		0.0134 (1.00)
20p gain	24 (36%)	43	0.17 (1.00)	0.0232 (1.00)	0.892 (1.00)	0.0564 (1.00)	0.284 (1.00)	0.657 (1.00)		0.38 (1.00)
20q gain	28 (42%)	39	0.389 (1.00)	0.095 (1.00)	1 (1.00)	0.00818 (1.00)	0.233 (1.00)	0.638 (1.00)		0.424 (1.00)
21q gain	4 (6%)	63		0.0329 (1.00)	0.0895 (1.00)	0.294 (1.00)	0.984 (1.00)	0.402 (1.00)		0.35 (1.00)
22q gain	17 (25%)	50	0.85 (1.00)	0.419 (1.00)	0.0189 (1.00)	0.147 (1.00)	0.127 (1.00)	0.0658 (1.00)		0.485 (1.00)
1p loss	6 (9%)	61	0.831 (1.00)	0.936 (1.00)	0.794 (1.00)	0.655 (1.00)	0.964 (1.00)	0.0343 (1.00)		0.824 (1.00)
1q loss	4 (6%)	63	0.588 (1.00)	0.214 (1.00)	0.137 (1.00)	1 (1.00)	0.984 (1.00)	0.17 (1.00)		0.845 (1.00)
2p loss	7 (10%)	60	0.943 (1.00)	0.781 (1.00)	0.831 (1.00)	0.206 (1.00)	0.964 (1.00)	0.844 (1.00)		0.335 (1.00)
2q loss	7 (10%)	60	0.696 (1.00)	0.654 (1.00)	0.831 (1.00)	0.034 (1.00)	0.0467 (1.00)	0.899 (1.00)		0.157 (1.00)
3p loss	9 (13%)	58	0.893 (1.00)	0.827 (1.00)	0.0217 (1.00)	0.461 (1.00)	0.951 (1.00)	0.5 (1.00)		0.723 (1.00)
3q loss	9 (13%)	58	0.881 (1.00)	0.5 (1.00)	0.176 (1.00)	0.142 (1.00)	0.935 (1.00)	0.62 (1.00)		0.615 (1.00)
4p loss	4 (6%)	63		0.0146 (1.00)	1 (1.00)	1 (1.00)	0.000558 (0.264)	0.891 (1.00)
4q loss	4 (6%)	63		0.0146 (1.00)	1 (1.00)	1 (1.00)	0.000558 (0.264)	0.891 (1.00)
5p loss	9 (13%)	58	0.0475 (1.00)	0.662 (1.00)	0.156 (1.00)	0.707 (1.00)	0.964 (1.00)	0.84 (1.00)		0.503 (1.00)
5q loss	20 (30%)	47	0.35 (1.00)	0.504 (1.00)	0.257 (1.00)	1 (1.00)	0.422 (1.00)	0.922 (1.00)		0.663 (1.00)
6p loss	6 (9%)	61	0.943 (1.00)	0.599 (1.00)	0.0523 (1.00)	0.386 (1.00)	0.964 (1.00)	0.165 (1.00)		0.872 (1.00)
6q loss	31 (46%)	36	0.558 (1.00)	0.0639 (1.00)	0.223 (1.00)	0.608 (1.00)	0.534 (1.00)	0.299 (1.00)		0.473 (1.00)
8p loss	7 (10%)	60	0.453 (1.00)	0.415 (1.00)	0.831 (1.00)	0.675 (1.00)	0.0823 (1.00)	0.835 (1.00)		0.225 (1.00)
9p loss	38 (57%)	29	0.758 (1.00)	0.103 (1.00)	0.14 (1.00)	1 (1.00)	0.297 (1.00)	0.368 (1.00)		0.323 (1.00)
9q loss	29 (43%)	38	0.544 (1.00)	0.875 (1.00)	0.048 (1.00)	0.114 (1.00)	0.199 (1.00)	0.54 (1.00)		0.122 (1.00)
10p loss	36 (54%)	31	0.782 (1.00)	0.955 (1.00)	0.163 (1.00)	0.122 (1.00)	0.233 (1.00)	0.0557 (1.00)		0.591 (1.00)
10q loss	45 (67%)	22	0.928 (1.00)	0.59 (1.00)	0.0838 (1.00)	0.0264 (1.00)	0.233 (1.00)	0.0304 (1.00)		0.61 (1.00)
11p loss	13 (19%)	54	0.468 (1.00)	0.786 (1.00)	0.313 (1.00)	0.101 (1.00)	0.0269 (1.00)	0.0735 (1.00)		0.135 (1.00)
11q loss	15 (22%)	52	0.321 (1.00)	0.714 (1.00)	0.305 (1.00)	0.0679 (1.00)	0.0815 (1.00)	0.194 (1.00)		0.0948 (1.00)
12p loss	3 (4%)	64		0.658 (1.00)	0.639 (1.00)	0.0321 (1.00)	0.0595 (1.00)	0.584 (1.00)		0.694 (1.00)
12q loss	4 (6%)	63		0.62 (1.00)	1 (1.00)	0.1 (1.00)	0.0595 (1.00)	0.584 (1.00)		0.694 (1.00)
13q loss	10 (15%)	57	0.952 (1.00)	0.299 (1.00)	0.179 (1.00)	0.718 (1.00)	0.0804 (1.00)	0.331 (1.00)		0.582 (1.00)
14q loss	18 (27%)	49	0.262 (1.00)	0.238 (1.00)	1 (1.00)	0.771 (1.00)	0.195 (1.00)	0.5 (1.00)		0.296 (1.00)
15q loss	6 (9%)	61		0.945 (1.00)	0.654 (1.00)	0.0852 (1.00)	0.0467 (1.00)	0.84 (1.00)		0.639 (1.00)
16p loss	5 (7%)	62	0.906 (1.00)	0.244 (1.00)	1 (1.00)	0.321 (1.00)	0.984 (1.00)	0.915 (1.00)		0.586 (1.00)
16q loss	10 (15%)	57	0.769 (1.00)	0.402 (1.00)	1 (1.00)	0.277 (1.00)	0.123 (1.00)	0.175 (1.00)		0.149 (1.00)
17p loss	12 (18%)	55	0.31 (1.00)	0.616 (1.00)	0.261 (1.00)	0.187 (1.00)	0.21 (1.00)	0.425 (1.00)		0.741 (1.00)
17q loss	5 (7%)	62		0.785 (1.00)	0.758 (1.00)	1 (1.00)	0.288 (1.00)	0.809 (1.00)		0.658 (1.00)
18p loss	16 (24%)	51	0.773 (1.00)	0.892 (1.00)	0.0226 (1.00)	0.762 (1.00)	0.777 (1.00)	0.322 (1.00)		0.118 (1.00)
18q loss	17 (25%)	50	0.708 (1.00)	0.322 (1.00)	0.297 (1.00)	0.551 (1.00)	0.386 (1.00)	0.748 (1.00)		0.218 (1.00)
19p loss	6 (9%)	61	0.618 (1.00)	0.299 (1.00)	1 (1.00)	0.0852 (1.00)	0.00915 (1.00)	0.0325 (1.00)		0.246 (1.00)
19q loss	8 (12%)	59	0.936 (1.00)	0.82 (1.00)	0.132 (1.00)	0.423 (1.00)	0.00915 (1.00)	0.0397 (1.00)		0.454 (1.00)
20p loss	3 (4%)	64	0.735 (1.00)	0.731 (1.00)	0.639 (1.00)	1 (1.00)	0.991 (1.00)	0.962 (1.00)		0.328 (1.00)
21q loss	8 (12%)	59	0.486 (1.00)	0.558 (1.00)	1 (1.00)	1 (1.00)	0.935 (1.00)	0.413 (1.00)		0.00595 (1.00)
22q loss	4 (6%)	63	0.656 (1.00)	0.0806 (1.00)	1 (1.00)	1 (1.00)	0.984 (1.00)	0.904 (1.00)		0.54 (1.00)
Xq loss	4 (6%)	63	0.861 (1.00)	0.441 (1.00)	0.34 (1.00)	0.1 (1.00)	0.991 (1.00)	0.953 (1.00)		0.0304 (1.00)

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

P value = 4.1e-05 (Chi-square test), Q value = 0.019

Table S1. Gene #28: '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 IIC	STAGE III	STAGE IIIA	STAGE IIIB	STAGE IIIC	STAGE IV
ALL	2	10	2	5	8	3	2	5	2	7	9	3
18Q GAIN MUTATED	2	1	0	0	0	0	0	0	0	0	0	0
18Q GAIN WILD-TYPE	0	9	2	5	8	3	2	5	2	7	9	3

Figure S1. Get High-res Image Gene #28: '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-BRAF_Hotspot_Mutants.clin.merged.picked.txt
Number of patients = 67
Number of significantly arm-level cnvs = 70
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)

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