Liver Hepatocellular Carcinoma: Correlation between copy number variations of arm-level result and selected clinical features<BR>(primary solid tumor cohort)

Liver Hepatocellular Carcinoma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor 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 64 arm-level results and 8 clinical features across 68 patients, one significant finding detected with Q value < 0.25.

18p 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 64 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	GENDER	DISTANT METASTASIS	LYMPH NODE METASTASIS	COMPLETENESS OF RESECTION	TUMOR STAGECODE	NEOPLASM DISEASESTAGE
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	t-test	Chi-square test
18p loss	7 (10%)	61	0.00678 (1.00)	0.000506 (0.221)	0.691 (1.00)	0.709 (1.00)	0.271 (1.00)	1 (1.00)		0.703 (1.00)
1p gain	8 (12%)	60	0.507 (1.00)	0.145 (1.00)	1 (1.00)	0.208 (1.00)	0.122 (1.00)	0.0782 (1.00)		0.0681 (1.00)
1q gain	36 (53%)	32	0.995 (1.00)	0.863 (1.00)	0.208 (1.00)	0.524 (1.00)	0.507 (1.00)	0.916 (1.00)		0.153 (1.00)
2p gain	8 (12%)	60	0.349 (1.00)	0.105 (1.00)	0.12 (1.00)	0.491 (1.00)	0.323 (1.00)	0.207 (1.00)		0.893 (1.00)
2q gain	7 (10%)	61	0.483 (1.00)	0.209 (1.00)	0.0875 (1.00)	0.709 (1.00)	0.485 (1.00)	0.474 (1.00)		0.893 (1.00)
3p gain	3 (4%)	65	0.87 (1.00)	0.042 (1.00)	1 (1.00)	1 (1.00)	0.0232 (1.00)	0.618 (1.00)		0.000998 (0.434)
3q gain	3 (4%)	65	0.87 (1.00)	0.042 (1.00)	1 (1.00)	1 (1.00)	0.0232 (1.00)	0.618 (1.00)		0.000998 (0.434)
4p gain	5 (7%)	63	0.786 (1.00)	0.215 (1.00)	0.337 (1.00)	1 (1.00)	1 (1.00)	0.805 (1.00)		0.662 (1.00)
5p gain	20 (29%)	48	0.387 (1.00)	0.107 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.812 (1.00)		0.954 (1.00)
5q gain	14 (21%)	54	0.442 (1.00)	0.133 (1.00)	1 (1.00)	1 (1.00)	0.798 (1.00)	0.688 (1.00)		0.887 (1.00)
6p gain	13 (19%)	55	0.127 (1.00)	0.696 (1.00)	0.355 (1.00)	0.273 (1.00)	0.606 (1.00)	0.0847 (1.00)		0.474 (1.00)
6q gain	9 (13%)	59	0.0769 (1.00)	0.241 (1.00)	0.476 (1.00)	0.176 (1.00)	0.75 (1.00)	0.0445 (1.00)		0.261 (1.00)
7p gain	18 (26%)	50	0.772 (1.00)	0.622 (1.00)	0.395 (1.00)	1 (1.00)	0.832 (1.00)	0.792 (1.00)		0.973 (1.00)
7q gain	19 (28%)	49	0.415 (1.00)	0.554 (1.00)	0.574 (1.00)	0.56 (1.00)	0.683 (1.00)	0.792 (1.00)		0.868 (1.00)
8p gain	11 (16%)	57	0.268 (1.00)	0.637 (1.00)	0.305 (1.00)	0.188 (1.00)	1 (1.00)	0.102 (1.00)		0.212 (1.00)
8q gain	33 (49%)	35	0.614 (1.00)	0.745 (1.00)	0.454 (1.00)	0.518 (1.00)	0.355 (1.00)	0.841 (1.00)		0.669 (1.00)
9p gain	3 (4%)	65		0.856 (1.00)	0.283 (1.00)	1 (1.00)	1 (1.00)	0.618 (1.00)		0.925 (1.00)
9q gain	3 (4%)	65		0.856 (1.00)	0.283 (1.00)	1 (1.00)	1 (1.00)	0.618 (1.00)		0.925 (1.00)
10p gain	5 (7%)	63	0.0729 (1.00)	0.365 (1.00)	0.337 (1.00)	0.108 (1.00)	0.0679 (1.00)	0.434 (1.00)		0.925 (1.00)
12q gain	3 (4%)	65		0.927 (1.00)	0.283 (1.00)	0.565 (1.00)	1 (1.00)	0.618 (1.00)		0.97 (1.00)
15q gain	5 (7%)	63	0.511 (1.00)	0.309 (1.00)	0.337 (1.00)	0.371 (1.00)	0.221 (1.00)	0.805 (1.00)		0.482 (1.00)
16p gain	3 (4%)	65	0.00316 (1.00)	0.142 (1.00)	1 (1.00)	0.282 (1.00)	0.251 (1.00)	1 (1.00)
17p gain	3 (4%)	65	0.288 (1.00)	0.691 (1.00)	0.283 (1.00)	0.0748 (1.00)	0.0686 (1.00)	0.618 (1.00)
17q gain	17 (25%)	51	0.112 (1.00)	0.702 (1.00)	0.571 (1.00)	0.663 (1.00)	0.404 (1.00)	0.921 (1.00)		0.874 (1.00)
18q gain	3 (4%)	65	0.522 (1.00)	0.567 (1.00)	1 (1.00)	0.565 (1.00)	0.568 (1.00)	0.618 (1.00)		0.376 (1.00)
19p gain	5 (7%)	63	0.431 (1.00)	0.597 (1.00)	0.0489 (1.00)	1 (1.00)	0.662 (1.00)	1 (1.00)		0.703 (1.00)
19q gain	7 (10%)	61	0.572 (1.00)	0.804 (1.00)	0.0875 (1.00)	0.709 (1.00)	0.485 (1.00)	0.571 (1.00)		0.665 (1.00)
20p gain	12 (18%)	56	0.0785 (1.00)	0.0748 (1.00)	0.321 (1.00)	0.596 (1.00)	0.312 (1.00)	0.0793 (1.00)		0.674 (1.00)
20q gain	13 (19%)	55	0.139 (1.00)	0.0498 (1.00)	0.52 (1.00)	0.793 (1.00)	0.347 (1.00)	0.0243 (1.00)		0.531 (1.00)
21q gain	4 (6%)	64	0.415 (1.00)	0.567 (1.00)	0.122 (1.00)	0.617 (1.00)	0.604 (1.00)	1 (1.00)		0.662 (1.00)
22q gain	7 (10%)	61	0.134 (1.00)	0.026 (1.00)	0.233 (1.00)	0.709 (1.00)	0.0579 (1.00)	0.841 (1.00)		0.0113 (1.00)
Xq gain	4 (6%)	64	0.123 (1.00)	0.169 (1.00)	1 (1.00)	0.153 (1.00)	0.604 (1.00)	0.726 (1.00)		0.623 (1.00)
1p loss	13 (19%)	55	0.888 (1.00)	0.953 (1.00)	0.52 (1.00)	1 (1.00)	0.265 (1.00)	1 (1.00)		0.117 (1.00)
1q loss	4 (6%)	64	0.851 (1.00)	0.0444 (1.00)	0.61 (1.00)	0.617 (1.00)	0.0192 (1.00)	1 (1.00)		0.000998 (0.434)
2p loss	3 (4%)	65			0.283 (1.00)	1 (1.00)	1 (1.00)	0.618 (1.00)		0.91 (1.00)
2q loss	4 (6%)	64		0.00697 (1.00)	0.61 (1.00)	1 (1.00)	1 (1.00)	0.207 (1.00)		0.992 (1.00)
3p loss	5 (7%)	63	0.866 (1.00)	0.729 (1.00)	0.337 (1.00)	1 (1.00)	1 (1.00)	0.805 (1.00)		0.736 (1.00)
3q loss	3 (4%)	65	0.674 (1.00)	0.345 (1.00)	0.283 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
4p loss	9 (13%)	59	0.257 (1.00)	0.917 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)		0.919 (1.00)
4q loss	16 (24%)	52	0.504 (1.00)	0.984 (1.00)	0.773 (1.00)	1 (1.00)	1 (1.00)	0.917 (1.00)		0.69 (1.00)
5q loss	4 (6%)	64	0.00285 (1.00)	0.982 (1.00)	1 (1.00)	0.617 (1.00)	0.604 (1.00)	0.318 (1.00)		0.925 (1.00)
6q loss	11 (16%)	57	0.428 (1.00)	0.84 (1.00)	0.5 (1.00)	1 (1.00)	1 (1.00)	0.372 (1.00)		0.986 (1.00)
7p loss	5 (7%)	63	0.523 (1.00)	0.695 (1.00)	0.0489 (1.00)	1 (1.00)	0.662 (1.00)	0.805 (1.00)		0.0323 (1.00)
7q loss	7 (10%)	61	0.656 (1.00)	0.465 (1.00)	0.233 (1.00)	0.472 (1.00)	1 (1.00)	0.335 (1.00)		0.227 (1.00)
8p loss	30 (44%)	38	0.252 (1.00)	0.108 (1.00)	0.307 (1.00)	0.78 (1.00)	0.226 (1.00)	1 (1.00)		0.389 (1.00)
8q loss	5 (7%)	63	0.394 (1.00)	0.814 (1.00)	0.337 (1.00)	1 (1.00)	0.662 (1.00)	0.434 (1.00)		0.149 (1.00)
9p loss	16 (24%)	52	0.937 (1.00)	0.504 (1.00)	0.773 (1.00)	1 (1.00)	0.816 (1.00)	0.516 (1.00)		0.631 (1.00)
9q loss	14 (21%)	54	0.646 (1.00)	0.545 (1.00)	0.755 (1.00)	1 (1.00)	1 (1.00)	0.567 (1.00)		0.672 (1.00)
10p loss	3 (4%)	65	0.574 (1.00)	0.0303 (1.00)	0.547 (1.00)	0.282 (1.00)	1 (1.00)	0.201 (1.00)
10q loss	12 (18%)	56	0.237 (1.00)	0.724 (1.00)	0.741 (1.00)	0.596 (1.00)	0.58 (1.00)	0.316 (1.00)		0.681 (1.00)
11p loss	5 (7%)	63	0.643 (1.00)	0.348 (1.00)	0.337 (1.00)	1 (1.00)	0.221 (1.00)	0.805 (1.00)		0.376 (1.00)
11q loss	8 (12%)	60	0.618 (1.00)	0.409 (1.00)	1 (1.00)	1 (1.00)	0.727 (1.00)	0.0384 (1.00)		0.423 (1.00)
12p loss	4 (6%)	64	0.323 (1.00)	0.224 (1.00)	0.61 (1.00)	0.336 (1.00)	0.066 (1.00)	0.726 (1.00)		0.0099 (1.00)
13q loss	23 (34%)	45	0.397 (1.00)	0.255 (1.00)	1 (1.00)	0.26 (1.00)	0.855 (1.00)	0.214 (1.00)		0.148 (1.00)
14q loss	22 (32%)	46	0.563 (1.00)	0.56 (1.00)	0.591 (1.00)	0.72 (1.00)	0.189 (1.00)	0.602 (1.00)		0.219 (1.00)
15q loss	7 (10%)	61	0.803 (1.00)	0.354 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.841 (1.00)		0.863 (1.00)
16p loss	14 (21%)	54	0.84 (1.00)	0.568 (1.00)	1 (1.00)	0.301 (1.00)	0.235 (1.00)	0.00851 (1.00)		0.0306 (1.00)
16q loss	22 (32%)	46	0.891 (1.00)	0.303 (1.00)	0.591 (1.00)	0.119 (1.00)	0.501 (1.00)	0.17 (1.00)		0.374 (1.00)
17p loss	28 (41%)	40	0.247 (1.00)	0.382 (1.00)	1 (1.00)	0.0468 (1.00)	0.0611 (1.00)	0.399 (1.00)		0.67 (1.00)
17q loss	3 (4%)	65	0.818 (1.00)	0.0172 (1.00)	0.283 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
18q loss	9 (13%)	59	0.0875 (1.00)	0.000836 (0.364)	0.71 (1.00)	1 (1.00)	0.235 (1.00)	1 (1.00)		0.831 (1.00)
19p loss	5 (7%)	63	0.33 (1.00)	0.235 (1.00)	0.153 (1.00)	1 (1.00)	1 (1.00)	0.295 (1.00)		0.847 (1.00)
21q loss	9 (13%)	59	0.0284 (1.00)	0.82 (1.00)	0.0217 (1.00)	1 (1.00)	1 (1.00)	0.251 (1.00)		0.664 (1.00)
22q loss	9 (13%)	59	0.484 (1.00)	0.738 (1.00)	0.0579 (1.00)	1 (1.00)	0.512 (1.00)	0.0661 (1.00)		0.59 (1.00)

'18p loss mutation analysis' versus 'AGE'

P value = 0.000506 (t-test), Q value = 0.22

Table S1. Gene #60: '18p loss mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	66	61.5 (14.2)
18P LOSS MUTATED	7	73.6 (6.4)
18P LOSS WILD-TYPE	59	60.0 (14.2)

Figure S1. Get High-res Image Gene #60: '18p loss mutation analysis' versus Clinical Feature #2: 'AGE'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = LIHC-TP.clin.merged.picked.txt
Number of patients = 68
Number of significantly arm-level cnvs = 64
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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