Kidney Renal Clear Cell 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 70 arm-level results and 8 clinical features across 489 patients, 5 significant findings detected with Q value < 0.25.

5p gain cnv correlated to 'AGE'.
4q loss cnv correlated to 'PATHOLOGY.T'.
13q loss cnv correlated to 'Time to Death' and 'PATHOLOGY.T'.
19p loss 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 70 arm-level results and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 5 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	KARNOFSKY PERFORMANCE SCORE	PATHOLOGY T	PATHOLOGY N	PATHOLOGICSPREAD(M)	NEOADJUVANT THERAPY
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
13q loss	35 (7%)	454	9.02e-05 (0.0476)	0.0205 (1.00)	0.717 (1.00)	0.00419 (1.00)	0.00032 (0.168)	0.63 (1.00)	0.0468 (1.00)	1 (1.00)
5p gain	152 (31%)	337	0.657 (1.00)	7.99e-05 (0.0422)	0.473 (1.00)	0.664 (1.00)	0.00728 (1.00)	0.796 (1.00)	0.343 (1.00)	0.177 (1.00)
4q loss	30 (6%)	459	0.00995 (1.00)	0.53 (1.00)	0.43 (1.00)	0.0261 (1.00)	0.000394 (0.207)	1 (1.00)	0.033 (1.00)	0.272 (1.00)
19p loss	5 (1%)	484	6.81e-05 (0.036)	0.684 (1.00)	1 (1.00)		0.00979 (1.00)	0.266 (1.00)	0.567 (1.00)	1 (1.00)
1p gain	10 (2%)	479	0.941 (1.00)	0.997 (1.00)	0.744 (1.00)		0.407 (1.00)	1 (1.00)	0.656 (1.00)	1 (1.00)
1q gain	37 (8%)	452	0.839 (1.00)	0.0198 (1.00)	0.721 (1.00)	0.518 (1.00)	0.567 (1.00)	0.12 (1.00)	0.634 (1.00)	0.326 (1.00)
2p gain	45 (9%)	444	0.926 (1.00)	0.0905 (1.00)	0.188 (1.00)	0.563 (1.00)	0.639 (1.00)	1 (1.00)	0.278 (1.00)	1 (1.00)
2q gain	50 (10%)	439	0.352 (1.00)	0.0512 (1.00)	0.0114 (1.00)	0.159 (1.00)	0.761 (1.00)	0.23 (1.00)	0.15 (1.00)	1 (1.00)
3q gain	25 (5%)	464	0.642 (1.00)	0.844 (1.00)	0.667 (1.00)	0.0875 (1.00)	0.362 (1.00)	0.278 (1.00)	0.0853 (1.00)	0.0228 (1.00)
4p gain	9 (2%)	480	0.0583 (1.00)	0.798 (1.00)	0.726 (1.00)		0.091 (1.00)	0.0873 (1.00)	1 (1.00)	1 (1.00)
4q gain	9 (2%)	480	0.346 (1.00)	0.184 (1.00)	1 (1.00)		0.155 (1.00)	0.421 (1.00)	1 (1.00)	1 (1.00)
5q gain	231 (47%)	258	0.228 (1.00)	0.00468 (1.00)	0.849 (1.00)	0.944 (1.00)	0.137 (1.00)	0.327 (1.00)	0.708 (1.00)	0.671 (1.00)
6p gain	5 (1%)	484	0.531 (1.00)	0.264 (1.00)	1 (1.00)		0.407 (1.00)	1 (1.00)	0.567 (1.00)	1 (1.00)
6q gain	4 (1%)	485	0.462 (1.00)	0.491 (1.00)	1 (1.00)		0.148 (1.00)	1 (1.00)	0.487 (1.00)	1 (1.00)
7p gain	125 (26%)	364	0.871 (1.00)	0.434 (1.00)	0.0813 (1.00)	0.893 (1.00)	0.203 (1.00)	0.29 (1.00)	0.0306 (1.00)	0.606 (1.00)
7q gain	126 (26%)	363	0.805 (1.00)	0.552 (1.00)	0.039 (1.00)	0.699 (1.00)	0.186 (1.00)	0.413 (1.00)	0.0151 (1.00)	0.111 (1.00)
8p gain	19 (4%)	470	0.454 (1.00)	0.495 (1.00)	0.0884 (1.00)	0.757 (1.00)	0.0038 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
8q gain	38 (8%)	451	0.489 (1.00)	0.198 (1.00)	0.158 (1.00)	0.297 (1.00)	0.00444 (1.00)	0.639 (1.00)	1 (1.00)	1 (1.00)
9p gain	9 (2%)	480	0.298 (1.00)	0.343 (1.00)	0.0708 (1.00)		0.177 (1.00)	1 (1.00)	0.367 (1.00)	1 (1.00)
9q gain	7 (1%)	482	0.748 (1.00)	0.384 (1.00)	0.244 (1.00)		0.00433 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
10p gain	5 (1%)	484	0.711 (1.00)	0.0955 (1.00)	0.347 (1.00)		0.0273 (1.00)	1 (1.00)	0.567 (1.00)	0.0503 (1.00)
10q gain	3 (1%)	486	0.478 (1.00)	0.34 (1.00)	0.0415 (1.00)		0.301 (1.00)	1 (1.00)	1 (1.00)	0.0304 (1.00)
11p gain	16 (3%)	473	0.981 (1.00)	0.949 (1.00)	0.795 (1.00)	0.115 (1.00)	0.0296 (1.00)	1 (1.00)	0.082 (1.00)	0.154 (1.00)
11q gain	15 (3%)	474	0.616 (1.00)	0.444 (1.00)	0.784 (1.00)		0.0363 (1.00)	1 (1.00)	0.264 (1.00)	0.145 (1.00)
12p gain	72 (15%)	417	0.0587 (1.00)	0.214 (1.00)	0.503 (1.00)	0.404 (1.00)	0.0161 (1.00)	0.534 (1.00)	0.0203 (1.00)	0.159 (1.00)
12q gain	74 (15%)	415	0.0861 (1.00)	0.267 (1.00)	0.356 (1.00)	0.404 (1.00)	0.0217 (1.00)	1 (1.00)	0.0339 (1.00)	0.166 (1.00)
13q gain	16 (3%)	473	0.323 (1.00)	0.987 (1.00)	0.795 (1.00)		0.148 (1.00)	1 (1.00)	0.722 (1.00)	0.00949 (1.00)
14q gain	5 (1%)	484	0.438 (1.00)	0.518 (1.00)	1 (1.00)		0.0221 (1.00)	1 (1.00)	0.567 (1.00)	1 (1.00)
15q gain	14 (3%)	475	0.867 (1.00)	0.954 (1.00)	0.779 (1.00)		0.233 (1.00)	0.465 (1.00)	0.46 (1.00)	1 (1.00)
16p gain	66 (13%)	423	0.568 (1.00)	0.0783 (1.00)	0.269 (1.00)	0.4 (1.00)	0.857 (1.00)	0.0837 (1.00)	0.716 (1.00)	0.137 (1.00)
16q gain	59 (12%)	430	0.444 (1.00)	0.0752 (1.00)	0.112 (1.00)	0.191 (1.00)	0.73 (1.00)	0.144 (1.00)	1 (1.00)	0.476 (1.00)
17p gain	17 (3%)	472	0.297 (1.00)	0.464 (1.00)	1 (1.00)		0.188 (1.00)	0.544 (1.00)	0.491 (1.00)	0.163 (1.00)
17q gain	22 (4%)	467	0.46 (1.00)	0.191 (1.00)	0.647 (1.00)	0.161 (1.00)	0.2 (1.00)	1 (1.00)	0.226 (1.00)	0.206 (1.00)
18p gain	17 (3%)	472	0.105 (1.00)	0.659 (1.00)	0.0404 (1.00)		0.922 (1.00)	1 (1.00)	0.491 (1.00)	1 (1.00)
18q gain	16 (3%)	473	0.105 (1.00)	0.889 (1.00)	0.106 (1.00)		0.721 (1.00)	1 (1.00)	0.486 (1.00)	1 (1.00)
19p gain	24 (5%)	465	0.625 (1.00)	0.412 (1.00)	0.827 (1.00)	0.161 (1.00)	0.544 (1.00)	1 (1.00)	0.775 (1.00)	0.223 (1.00)
19q gain	28 (6%)	461	0.858 (1.00)	0.374 (1.00)	0.683 (1.00)	0.161 (1.00)	0.491 (1.00)	1 (1.00)	0.414 (1.00)	0.0284 (1.00)
20p gain	50 (10%)	439	0.841 (1.00)	0.965 (1.00)	0.0272 (1.00)	0.473 (1.00)	0.172 (1.00)	0.702 (1.00)	0.0129 (1.00)	0.418 (1.00)
20q gain	52 (11%)	437	0.807 (1.00)	0.459 (1.00)	0.0656 (1.00)	0.473 (1.00)	0.13 (1.00)	0.702 (1.00)	0.0638 (1.00)	0.431 (1.00)
21q gain	33 (7%)	456	0.11 (1.00)	0.313 (1.00)	0.851 (1.00)	0.161 (1.00)	0.422 (1.00)	1 (1.00)	0.618 (1.00)	1 (1.00)
22q gain	23 (5%)	466	0.957 (1.00)	0.803 (1.00)	0.823 (1.00)		0.17 (1.00)	1 (1.00)	0.375 (1.00)	1 (1.00)
1p loss	35 (7%)	454	0.575 (1.00)	0.326 (1.00)	0.274 (1.00)	0.115 (1.00)	0.263 (1.00)	1 (1.00)	0.632 (1.00)	1 (1.00)
1q loss	21 (4%)	468	0.409 (1.00)	0.926 (1.00)	0.353 (1.00)		0.21 (1.00)	0.506 (1.00)	0.546 (1.00)	1 (1.00)
2p loss	12 (2%)	477	0.895 (1.00)	0.857 (1.00)	0.556 (1.00)		0.0126 (1.00)	1 (1.00)	0.702 (1.00)	1 (1.00)
2q loss	13 (3%)	476	0.722 (1.00)	0.906 (1.00)	0.557 (1.00)		0.0343 (1.00)	1 (1.00)	0.702 (1.00)	1 (1.00)
3p loss	371 (76%)	118	0.109 (1.00)	0.536 (1.00)	1 (1.00)	0.788 (1.00)	0.00183 (0.956)	0.584 (1.00)	0.0557 (1.00)	0.0935 (1.00)
3q loss	90 (18%)	399	0.2 (1.00)	0.013 (1.00)	0.0497 (1.00)	0.0535 (1.00)	0.0285 (1.00)	1 (1.00)	0.0738 (1.00)	0.59 (1.00)
4p loss	31 (6%)	458	0.0124 (1.00)	0.932 (1.00)	1 (1.00)	0.0176 (1.00)	0.00303 (1.00)	1 (1.00)	0.298 (1.00)	0.28 (1.00)
6p loss	60 (12%)	429	0.27 (1.00)	0.219 (1.00)	0.00374 (1.00)	0.499 (1.00)	0.62 (1.00)	0.391 (1.00)	0.337 (1.00)	0.482 (1.00)
6q loss	95 (19%)	394	0.786 (1.00)	0.343 (1.00)	0.0558 (1.00)	0.851 (1.00)	0.959 (1.00)	0.152 (1.00)	0.636 (1.00)	0.251 (1.00)
8p loss	93 (19%)	396	0.433 (1.00)	0.164 (1.00)	0.227 (1.00)	0.0817 (1.00)	0.278 (1.00)	0.0498 (1.00)	0.873 (1.00)	1 (1.00)
8q loss	40 (8%)	449	0.285 (1.00)	0.795 (1.00)	0.0156 (1.00)	0.00425 (1.00)	0.919 (1.00)	0.375 (1.00)	0.176 (1.00)	1 (1.00)
9p loss	84 (17%)	405	0.00702 (1.00)	0.0339 (1.00)	0.0115 (1.00)	0.0261 (1.00)	0.37 (1.00)	1 (1.00)	0.00428 (1.00)	0.206 (1.00)
9q loss	84 (17%)	405	0.0217 (1.00)	0.0178 (1.00)	0.0232 (1.00)	0.0473 (1.00)	0.143 (1.00)	0.746 (1.00)	0.00428 (1.00)	0.206 (1.00)
10p loss	34 (7%)	455	0.718 (1.00)	0.413 (1.00)	0.853 (1.00)	0.00413 (1.00)	0.0159 (1.00)	1 (1.00)	0.628 (1.00)	1 (1.00)
10q loss	55 (11%)	434	0.216 (1.00)	0.095 (1.00)	0.135 (1.00)	0.66 (1.00)	0.00682 (1.00)	0.649 (1.00)	1 (1.00)	1 (1.00)
11p loss	4 (1%)	485	0.00131 (0.686)	0.737 (1.00)	1 (1.00)		0.816 (1.00)	0.143 (1.00)	0.487 (1.00)	1 (1.00)
11q loss	7 (1%)	482	0.326 (1.00)	0.38 (1.00)	0.43 (1.00)		0.707 (1.00)	0.322 (1.00)	0.293 (1.00)	1 (1.00)
12p loss	3 (1%)	486	0.837 (1.00)	0.73 (1.00)	1 (1.00)		0.743 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
12q loss	4 (1%)	485	0.179 (1.00)	0.59 (1.00)	1 (1.00)		1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
14q loss	157 (32%)	332	0.204 (1.00)	0.145 (1.00)	0.362 (1.00)	0.508 (1.00)	0.0724 (1.00)	0.195 (1.00)	0.347 (1.00)	0.0387 (1.00)
15q loss	11 (2%)	478	0.521 (1.00)	0.0482 (1.00)	0.755 (1.00)		0.406 (1.00)	0.373 (1.00)	0.68 (1.00)	1 (1.00)
16q loss	6 (1%)	483	0.256 (1.00)	0.0574 (1.00)	0.67 (1.00)		0.0124 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
17p loss	28 (6%)	461	0.00811 (1.00)	0.304 (1.00)	0.311 (1.00)	0.115 (1.00)	0.358 (1.00)	0.608 (1.00)	0.172 (1.00)	0.256 (1.00)
17q loss	13 (3%)	476	0.875 (1.00)	0.95 (1.00)	0.236 (1.00)		0.125 (1.00)	1 (1.00)	0.432 (1.00)	0.127 (1.00)
18p loss	44 (9%)	445	0.214 (1.00)	0.06 (1.00)	0.509 (1.00)	0.482 (1.00)	0.249 (1.00)	0.671 (1.00)	0.378 (1.00)	0.377 (1.00)
18q loss	50 (10%)	439	0.408 (1.00)	0.158 (1.00)	0.348 (1.00)	0.482 (1.00)	0.47 (1.00)	1 (1.00)	0.308 (1.00)	0.418 (1.00)
20p loss	6 (1%)	483	0.754 (1.00)	0.958 (1.00)	1 (1.00)		0.881 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
21q loss	31 (6%)	458	0.822 (1.00)	0.922 (1.00)	1 (1.00)		0.00679 (1.00)	0.336 (1.00)	0.202 (1.00)	1 (1.00)
22q loss	11 (2%)	478	0.0956 (1.00)	0.0317 (1.00)	0.755 (1.00)		0.0964 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)

'5p gain mutation analysis' versus 'AGE'

P value = 7.99e-05 (t-test), Q value = 0.042

Table S1. Gene #8: '5p gain mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	488	60.6 (12.2)
5P GAIN MUTATED	152	63.8 (11.6)
5P GAIN WILD-TYPE	336	59.2 (12.2)

Figure S1. Get High-res Image Gene #8: '5p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'4q loss mutation analysis' versus 'PATHOLOGY.T'

P value = 0.000394 (Fisher's exact test), Q value = 0.21

Table S2. Gene #46: '4q loss mutation analysis' versus Clinical Feature #5: 'PATHOLOGY.T'

nPatients	T1	T2	T3	T4
ALL	239	64	175	11
4Q LOSS MUTATED	6	3	18	3
4Q LOSS WILD-TYPE	233	61	157	8

Figure S2. Get High-res Image Gene #46: '4q loss mutation analysis' versus Clinical Feature #5: 'PATHOLOGY.T'

'13q loss mutation analysis' versus 'Time to Death'

P value = 9.02e-05 (logrank test), Q value = 0.048

Table S3. Gene #59: '13q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	486	156	0.1 - 111.0 (34.9)
13Q LOSS MUTATED	35	17	0.1 - 66.2 (18.4)
13Q LOSS WILD-TYPE	451	139	0.1 - 111.0 (36.2)

Figure S3. Get High-res Image Gene #59: '13q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'13q loss mutation analysis' versus 'PATHOLOGY.T'

P value = 0.00032 (Fisher's exact test), Q value = 0.17

Table S4. Gene #59: '13q loss mutation analysis' versus Clinical Feature #5: 'PATHOLOGY.T'

nPatients	T1	T2	T3	T4
ALL	239	64	175	11
13Q LOSS MUTATED	11	1	19	4
13Q LOSS WILD-TYPE	228	63	156	7

Figure S4. Get High-res Image Gene #59: '13q loss mutation analysis' versus Clinical Feature #5: 'PATHOLOGY.T'

'19p loss mutation analysis' versus 'Time to Death'

P value = 6.81e-05 (logrank test), Q value = 0.036

Table S5. Gene #67: '19p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	486	156	0.1 - 111.0 (34.9)
19P LOSS MUTATED	5	5	7.3 - 32.6 (28.5)
19P LOSS WILD-TYPE	481	151	0.1 - 111.0 (35.5)

Figure S5. Get High-res Image Gene #67: '19p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = KIRC.clin.merged.picked.txt
Number of patients = 489
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

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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