Bladder Urothelial Carcinoma: 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 71 arm-level results and 4 clinical features across 88 patients, one significant finding detected with Q value < 0.25.

21q 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 71 arm-level results and 4 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	KARNOFSKY PERFORMANCE SCORE
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	t-test
21q loss	9 (10%)	79	0.401 (1.00)	0.000475 (0.126)	1 (1.00)	0.00389 (1.00)
1p gain	11 (12%)	77	0.324 (1.00)	0.178 (1.00)	0.301 (1.00)	0.471 (1.00)
1q gain	20 (23%)	68	0.122 (1.00)	0.0138 (1.00)	0.783 (1.00)	0.111 (1.00)
2p gain	18 (20%)	70	0.453 (1.00)	0.938 (1.00)	0.00335 (0.88)	0.875 (1.00)
2q gain	5 (6%)	83	0.673 (1.00)	0.0323 (1.00)	0.64 (1.00)	0.875 (1.00)
3p gain	19 (22%)	69	0.617 (1.00)	0.97 (1.00)	1 (1.00)	0.554 (1.00)
3q gain	24 (27%)	64	0.179 (1.00)	0.0759 (1.00)	0.442 (1.00)	0.992 (1.00)
4p gain	8 (9%)	80	0.0819 (1.00)	0.847 (1.00)	0.426 (1.00)
4q gain	4 (5%)	84	0.905 (1.00)	0.241 (1.00)	1 (1.00)
5p gain	26 (30%)	62	0.901 (1.00)	0.433 (1.00)	0.801 (1.00)	0.0757 (1.00)
5q gain	13 (15%)	75	0.53 (1.00)	0.956 (1.00)	0.329 (1.00)	0.486 (1.00)
6p gain	5 (6%)	83	0.116 (1.00)	0.894 (1.00)	0.64 (1.00)
6q gain	3 (3%)	85	0.124 (1.00)	0.836 (1.00)	0.55 (1.00)
7p gain	29 (33%)	59	0.371 (1.00)	0.471 (1.00)	1 (1.00)	0.174 (1.00)
7q gain	28 (32%)	60	0.625 (1.00)	0.966 (1.00)	0.321 (1.00)	0.112 (1.00)
8p gain	14 (16%)	74	0.931 (1.00)	0.18 (1.00)	0.536 (1.00)	0.835 (1.00)
8q gain	31 (35%)	57	0.734 (1.00)	0.403 (1.00)	0.629 (1.00)	0.558 (1.00)
9p gain	12 (14%)	76	0.0337 (1.00)	0.0411 (1.00)	0.0957 (1.00)	0.808 (1.00)
9q gain	11 (12%)	77	0.07 (1.00)	0.0776 (1.00)	1 (1.00)	0.789 (1.00)
10p gain	19 (22%)	69	0.496 (1.00)	0.388 (1.00)	0.782 (1.00)	0.835 (1.00)
10q gain	5 (6%)	83	0.474 (1.00)	0.474 (1.00)	0.64 (1.00)
11p gain	4 (5%)	84	0.696 (1.00)	0.254 (1.00)	0.308 (1.00)	0.0907 (1.00)
11q gain	3 (3%)	85	0.674 (1.00)	0.481 (1.00)	0.55 (1.00)
12p gain	18 (20%)	70	0.965 (1.00)	0.766 (1.00)	0.251 (1.00)	0.333 (1.00)
12q gain	14 (16%)	74	0.293 (1.00)	0.817 (1.00)	0.0553 (1.00)	0.267 (1.00)
13q gain	16 (18%)	72	0.278 (1.00)	0.354 (1.00)	1 (1.00)	0.447 (1.00)
14q gain	8 (9%)	80	0.573 (1.00)	0.729 (1.00)	0.697 (1.00)	0.46 (1.00)
15q gain	4 (5%)	84	0.152 (1.00)	0.811 (1.00)	1 (1.00)
16p gain	8 (9%)	80	0.00254 (0.671)	0.415 (1.00)	0.243 (1.00)
16q gain	10 (11%)	78	0.0415 (1.00)	0.287 (1.00)	0.0622 (1.00)
17p gain	6 (7%)	82	0.466 (1.00)	0.084 (1.00)	0.366 (1.00)
17q gain	14 (16%)	74	0.763 (1.00)	0.746 (1.00)	0.754 (1.00)
18p gain	15 (17%)	73	0.65 (1.00)	0.866 (1.00)	0.769 (1.00)	0.978 (1.00)
18q gain	6 (7%)	82	0.0272 (1.00)	0.798 (1.00)	1 (1.00)
19p gain	9 (10%)	79	0.505 (1.00)	0.833 (1.00)	1 (1.00)	0.471 (1.00)
19q gain	18 (20%)	70	0.278 (1.00)	0.829 (1.00)	0.165 (1.00)	0.058 (1.00)
20p gain	36 (41%)	52	0.423 (1.00)	0.411 (1.00)	0.0989 (1.00)	0.895 (1.00)
20q gain	37 (42%)	51	0.485 (1.00)	0.911 (1.00)	0.817 (1.00)	0.474 (1.00)
21q gain	17 (19%)	71	0.222 (1.00)	0.147 (1.00)	0.771 (1.00)	0.65 (1.00)
22q gain	9 (10%)	79	0.0766 (1.00)	0.603 (1.00)	0.265 (1.00)	0.808 (1.00)
Xq gain	5 (6%)	83	0.452 (1.00)	0.826 (1.00)	0.64 (1.00)
2p loss	5 (6%)	83	0.703 (1.00)	0.302 (1.00)	1 (1.00)	0.396 (1.00)
2q loss	11 (12%)	77	0.0407 (1.00)	0.195 (1.00)	0.492 (1.00)	0.396 (1.00)
3p loss	7 (8%)	81	0.911 (1.00)	0.605 (1.00)	0.671 (1.00)
4p loss	14 (16%)	74	0.702 (1.00)	0.888 (1.00)	0.754 (1.00)	0.0355 (1.00)
4q loss	15 (17%)	73	0.894 (1.00)	0.68 (1.00)	1 (1.00)	0.0355 (1.00)
5p loss	9 (10%)	79	0.32 (1.00)	0.319 (1.00)	0.448 (1.00)	0.00428 (1.00)
5q loss	19 (22%)	69	0.462 (1.00)	0.829 (1.00)	1 (1.00)	0.75 (1.00)
6p loss	11 (12%)	77	0.137 (1.00)	0.602 (1.00)	1 (1.00)	0.00428 (1.00)
6q loss	17 (19%)	71	0.404 (1.00)	0.924 (1.00)	0.771 (1.00)	0.00367 (0.962)
8p loss	27 (31%)	61	0.175 (1.00)	0.623 (1.00)	0.62 (1.00)	0.356 (1.00)
8q loss	3 (3%)	85	0.548 (1.00)	0.318 (1.00)	0.222 (1.00)
9p loss	28 (32%)	60	0.69 (1.00)	0.392 (1.00)	0.0265 (1.00)	0.792 (1.00)
9q loss	25 (28%)	63	0.542 (1.00)	0.674 (1.00)	0.075 (1.00)	0.823 (1.00)
10p loss	13 (15%)	75	0.381 (1.00)	0.894 (1.00)	1 (1.00)	0.0355 (1.00)
10q loss	14 (16%)	74	0.418 (1.00)	0.153 (1.00)	0.754 (1.00)	0.00428 (1.00)
11p loss	31 (35%)	57	0.849 (1.00)	0.0972 (1.00)	0.814 (1.00)	0.348 (1.00)
11q loss	24 (27%)	64	0.879 (1.00)	0.814 (1.00)	0.607 (1.00)	0.541 (1.00)
13q loss	13 (15%)	75	0.972 (1.00)	0.854 (1.00)	0.058 (1.00)	0.00428 (1.00)
14q loss	13 (15%)	75	0.342 (1.00)	0.641 (1.00)	0.747 (1.00)	0.789 (1.00)
15q loss	12 (14%)	76	0.356 (1.00)	0.302 (1.00)	1 (1.00)	0.942 (1.00)
16p loss	11 (12%)	77	0.207 (1.00)	0.172 (1.00)	0.161 (1.00)	0.058 (1.00)
16q loss	10 (11%)	78	0.813 (1.00)	0.138 (1.00)	0.166 (1.00)	0.125 (1.00)
17p loss	29 (33%)	59	0.109 (1.00)	0.283 (1.00)	1 (1.00)	0.448 (1.00)
17q loss	4 (5%)	84	0.777 (1.00)	0.56 (1.00)	1 (1.00)
18p loss	13 (15%)	75	0.11 (1.00)	0.0922 (1.00)	0.527 (1.00)	0.699 (1.00)
18q loss	22 (25%)	66	0.0249 (1.00)	0.0358 (1.00)	0.11 (1.00)	0.69 (1.00)
19p loss	4 (5%)	84	0.795 (1.00)	0.631 (1.00)	0.583 (1.00)
19q loss	3 (3%)	85	0.708 (1.00)	0.793 (1.00)	1 (1.00)
20p loss	3 (3%)	85	0.833 (1.00)	0.49 (1.00)	1 (1.00)
22q loss	17 (19%)	71	0.449 (1.00)	0.686 (1.00)	0.381 (1.00)	0.396 (1.00)

'21q loss mutation analysis' versus 'AGE'

P value = 0.000475 (t-test), Q value = 0.13

Table S1. Gene #70: '21q loss mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	87	67.2 (11.0)
21Q LOSS MUTATED	9	57.7 (6.1)
21Q LOSS WILD-TYPE	78	68.3 (11.0)

Figure S1. Get High-res Image Gene #70: '21q loss mutation analysis' versus Clinical Feature #2: 'AGE'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = BLCA.clin.merged.picked.txt
Number of patients = 88
Number of significantly arm-level cnvs = 71
Number of selected clinical features = 4
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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