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

Cervical Squamous Cell 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 44 arm-level results and 10 clinical features across 34 patients, 2 significant findings detected with Q value < 0.25.

15q gain cnv correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.
19q gain cnv correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 44 arm-level results and 10 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.


		Clinical Features	Time to Death	AGE	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	NUMBERPACKYEARSSMOKED	TOBACCOSMOKINGHISTORYINDICATOR	DISTANT METASTASIS	LYMPH NODE METASTASIS	NUMBER OF LYMPH NODES	TUMOR STAGECODE
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	t-test	t-test	Fisher's exact test	Fisher's exact test	t-test	t-test
15q gain	3 (9%)	31	0.745 (1.00)	0.771 (1.00)	0.511 (1.00)	0.535 (1.00)		9.97e-05 (0.0363)	1 (1.00)	0.279 (1.00)	0.00565 (1.00)
19q gain	6 (18%)	28	0.104 (1.00)	0.87 (1.00)	1 (1.00)	0.000344 (0.125)	0.985 (1.00)	0.439 (1.00)	1 (1.00)	0.611 (1.00)	0.914 (1.00)
1p gain	7 (21%)	27	0.814 (1.00)	0.0637 (1.00)	0.19 (1.00)	1 (1.00)		0.528 (1.00)	0.339 (1.00)	1 (1.00)	0.917 (1.00)
1q gain	15 (44%)	19	0.553 (1.00)	0.129 (1.00)	0.264 (1.00)	0.151 (1.00)	0.969 (1.00)	0.862 (1.00)	0.106 (1.00)	1 (1.00)	0.463 (1.00)
2p gain	3 (9%)	31	0.0598 (1.00)	0.717 (1.00)	0.511 (1.00)	0.239 (1.00)		0.769 (1.00)	0.532 (1.00)	1 (1.00)
3p gain	3 (9%)	31	0.688 (1.00)	0.791 (1.00)	0.159 (1.00)	1 (1.00)		0.589 (1.00)	0.22 (1.00)	0.537 (1.00)	0.414 (1.00)
3q gain	21 (62%)	13	0.113 (1.00)	0.132 (1.00)	0.359 (1.00)	0.709 (1.00)	0.268 (1.00)	0.404 (1.00)	1 (1.00)	0.696 (1.00)	0.565 (1.00)
5p gain	8 (24%)	26	0.667 (1.00)	0.452 (1.00)	0.707 (1.00)	1 (1.00)		0.888 (1.00)	0.339 (1.00)	0.641 (1.00)	0.241 (1.00)
6p gain	6 (18%)	28	0.221 (1.00)	0.191 (1.00)	0.64 (1.00)	0.363 (1.00)		0.235 (1.00)	0.633 (1.00)	1 (1.00)	0.8 (1.00)
7q gain	4 (12%)	30	0.268 (1.00)	0.273 (1.00)	0.243 (1.00)	0.0889 (1.00)		0.321 (1.00)	0.568 (1.00)	0.611 (1.00)	0.556 (1.00)
8p gain	4 (12%)	30	0.747 (1.00)	0.294 (1.00)	1 (1.00)	1 (1.00)		0.888 (1.00)	0.28 (1.00)	1 (1.00)	0.443 (1.00)
8q gain	7 (21%)	27	0.547 (1.00)	0.357 (1.00)	0.67 (1.00)	1 (1.00)		0.645 (1.00)	1 (1.00)	1 (1.00)	0.704 (1.00)
10p gain	3 (9%)	31	0.283 (1.00)	0.459 (1.00)	0.511 (1.00)	0.535 (1.00)		0.294 (1.00)	1 (1.00)	0.537 (1.00)	0.414 (1.00)
12p gain	6 (18%)	28	0.418 (1.00)	0.366 (1.00)	0.0422 (1.00)	1 (1.00)		0.218 (1.00)	0.0559 (1.00)	1 (1.00)	0.917 (1.00)
12q gain	4 (12%)	30	0.469 (1.00)	0.575 (1.00)	0.243 (1.00)	0.58 (1.00)		0.321 (1.00)	0.076 (1.00)	0.611 (1.00)	0.556 (1.00)
14q gain	3 (9%)	31	0.158 (1.00)	0.82 (1.00)	0.511 (1.00)	1 (1.00)		0.339 (1.00)	1 (1.00)	0.537 (1.00)	0.593 (1.00)
16p gain	4 (12%)	30	0.745 (1.00)	0.818 (1.00)	0.243 (1.00)	1 (1.00)		0.769 (1.00)	1 (1.00)	0.537 (1.00)	0.414 (1.00)
16q gain	3 (9%)	31		0.205 (1.00)	0.159 (1.00)	1 (1.00)			1 (1.00)	1 (1.00)
18p gain	3 (9%)	31	0.355 (1.00)	0.304 (1.00)	0.159 (1.00)	0.239 (1.00)		0.401 (1.00)	1 (1.00)	0.537 (1.00)	0.593 (1.00)
20p gain	11 (32%)	23	0.119 (1.00)	0.993 (1.00)	0.207 (1.00)	1 (1.00)	0.0279 (1.00)	0.72 (1.00)	0.675 (1.00)	0.425 (1.00)	0.519 (1.00)
20q gain	12 (35%)	22	0.00689 (1.00)	0.332 (1.00)	0.456 (1.00)	1 (1.00)	0.0279 (1.00)	0.517 (1.00)	0.675 (1.00)	1 (1.00)	0.872 (1.00)
21q gain	3 (9%)	31	0.158 (1.00)	0.0898 (1.00)	0.511 (1.00)	0.239 (1.00)		0.589 (1.00)	1 (1.00)	0.537 (1.00)	0.593 (1.00)
22q gain	5 (15%)	29	0.355 (1.00)	0.167 (1.00)	0.331 (1.00)	1 (1.00)		0.671 (1.00)	1 (1.00)	0.611 (1.00)	0.556 (1.00)
3p loss	9 (26%)	25	0.403 (1.00)	0.23 (1.00)	1 (1.00)	1 (1.00)	0.193 (1.00)	0.805 (1.00)	1 (1.00)	0.372 (1.00)	0.247 (1.00)
4p loss	14 (41%)	20	0.808 (1.00)	0.317 (1.00)	1 (1.00)	1 (1.00)	0.265 (1.00)	0.883 (1.00)	0.226 (1.00)	1 (1.00)	0.269 (1.00)
4q loss	5 (15%)	29	0.221 (1.00)	0.796 (1.00)	1 (1.00)	0.3 (1.00)	0.937 (1.00)	0.943 (1.00)	0.568 (1.00)	0.126 (1.00)	0.181 (1.00)
5q loss	11 (32%)	23	0.277 (1.00)	0.113 (1.00)	0.754 (1.00)	0.271 (1.00)	0.646 (1.00)	0.744 (1.00)	0.675 (1.00)	1 (1.00)	0.721 (1.00)
7p loss	4 (12%)	30	0.838 (1.00)	0.116 (1.00)	1 (1.00)	0.0889 (1.00)	0.977 (1.00)	0.502 (1.00)	0.568 (1.00)	0.611 (1.00)	0.411 (1.00)
7q loss	4 (12%)	30	0.00503 (1.00)	0.391 (1.00)	1 (1.00)	0.0889 (1.00)	0.907 (1.00)	0.222 (1.00)	0.532 (1.00)	0.537 (1.00)	0.383 (1.00)
8p loss	10 (29%)	24	0.272 (1.00)	0.708 (1.00)	0.746 (1.00)	0.692 (1.00)		0.387 (1.00)	1 (1.00)	1 (1.00)	0.704 (1.00)
9p loss	4 (12%)	30	0.0398 (1.00)	0.742 (1.00)	1 (1.00)	0.58 (1.00)		0.345 (1.00)	0.532 (1.00)	1 (1.00)	0.718 (1.00)
9q loss	3 (9%)	31	0.0487 (1.00)	0.353 (1.00)	1 (1.00)	1 (1.00)		0.248 (1.00)	0.532 (1.00)	1 (1.00)	0.718 (1.00)
10p loss	7 (21%)	27	0.118 (1.00)	0.553 (1.00)	1 (1.00)	0.178 (1.00)	0.52 (1.00)	0.167 (1.00)	0.076 (1.00)	0.0472 (1.00)	0.175 (1.00)
10q loss	6 (18%)	28	0.0684 (1.00)	0.704 (1.00)	1 (1.00)	0.363 (1.00)	0.77 (1.00)	0.0717 (1.00)	0.287 (1.00)	0.0156 (1.00)	0.111 (1.00)
11p loss	7 (21%)	27	0.418 (1.00)	0.535 (1.00)	1 (1.00)	0.656 (1.00)		0.119 (1.00)	0.158 (1.00)	1 (1.00)	0.277 (1.00)
11q loss	7 (21%)	27	0.838 (1.00)	0.767 (1.00)	1 (1.00)	0.178 (1.00)	0.977 (1.00)	0.666 (1.00)	0.339 (1.00)	0.641 (1.00)	0.241 (1.00)
12p loss	6 (18%)	28	0.439 (1.00)	0.0155 (1.00)	0.64 (1.00)	0.638 (1.00)		0.524 (1.00)	1 (1.00)	0.626 (1.00)	0.261 (1.00)
13q loss	8 (24%)	26	0.317 (1.00)	0.911 (1.00)	0.707 (1.00)	1 (1.00)		0.723 (1.00)	0.642 (1.00)	1 (1.00)	0.277 (1.00)
17p loss	10 (29%)	24	0.219 (1.00)	0.249 (1.00)	0.746 (1.00)	0.692 (1.00)	0.568 (1.00)	0.662 (1.00)	1 (1.00)	1 (1.00)	0.322 (1.00)
17q loss	3 (9%)	31	0.825 (1.00)	0.529 (1.00)	1 (1.00)	1 (1.00)		0.861 (1.00)	0.532 (1.00)	1 (1.00)	0.718 (1.00)
18p loss	6 (18%)	28	0.74 (1.00)	0.478 (1.00)	0.146 (1.00)	0.0703 (1.00)	0.0279 (1.00)	0.235 (1.00)	1 (1.00)	0.626 (1.00)	0.261 (1.00)
18q loss	7 (21%)	27	0.875 (1.00)	0.653 (1.00)	0.124 (1.00)	0.178 (1.00)	0.0279 (1.00)	0.119 (1.00)	0.633 (1.00)	0.372 (1.00)	0.154 (1.00)
19p loss	4 (12%)	30	0.34 (1.00)	0.457 (1.00)	1 (1.00)	0.0889 (1.00)		0.693 (1.00)	1 (1.00)	1 (1.00)
21q loss	6 (18%)	28	0.376 (1.00)	0.966 (1.00)	1 (1.00)	0.145 (1.00)		0.0676 (1.00)	1 (1.00)	0.372 (1.00)	0.672 (1.00)

'15q gain mutation analysis' versus 'TOBACCOSMOKINGHISTORYINDICATOR'

P value = 9.97e-05 (t-test), Q value = 0.036

Table S1. Gene #15: '15q gain mutation analysis' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

	nPatients	Mean (Std.Dev)
ALL	33	1.8 (1.1)
15Q GAIN MUTATED	3	1.0 (0.0)
15Q GAIN WILD-TYPE	30	1.9 (1.1)

Figure S1. Get High-res Image Gene #15: '15q gain mutation analysis' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

'19q gain mutation analysis' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000344 (Fisher's exact test), Q value = 0.12

Table S2. Gene #19: '19q gain mutation analysis' versus Clinical Feature #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients	NO	YES
ALL	11	23
19Q GAIN MUTATED	6	0
19Q GAIN WILD-TYPE	5	23

Figure S2. Get High-res Image Gene #19: '19q gain mutation analysis' versus Clinical Feature #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = CESC-TP.clin.merged.picked.txt
Number of patients = 34
Number of significantly arm-level cnvs = 44
Number of selected clinical features = 10
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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