Correlation between copy number variations of arm-level result and selected clinical features

Pancreatic Adenocarcinoma (Primary solid tumor)

16 April 2014 | analyses__2014_04_16

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1VQ31B3

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 events and 12 clinical features across 72 patients, 3 significant findings detected with Q value < 0.25.

3p gain cnv correlated to 'Time to Death'.
7p gain cnv correlated to 'COMPLETENESS.OF.RESECTION'.
7q gain cnv correlated to 'COMPLETENESS.OF.RESECTION'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 64 arm-level events and 12 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.


		Clinical Features	Time to Death	AGE	NEOPLASM DISEASESTAGE	PATHOLOGY T STAGE	PATHOLOGY N STAGE	PATHOLOGY M STAGE	GENDER	HISTOLOGICAL TYPE	NUMBERPACKYEARSSMOKED	YEAROFTOBACCOSMOKINGONSET	COMPLETENESS OF RESECTION	NUMBER OF LYMPH NODES
	nCNV (%)	nWild-Type	logrank test	t-test	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	t-test	t-test	Fisher's exact test	t-test
3p gain	5 (7%)	67	1.03e-05 (0.00733)	0.688 (1.00)	0.748 (1.00)	0.41 (1.00)	0.595 (1.00)	0.501 (1.00)	0.357 (1.00)	1 (1.00)			1 (1.00)	0.485 (1.00)
7p gain	18 (25%)	54	0.945 (1.00)	0.754 (1.00)	0.693 (1.00)	0.181 (1.00)	1 (1.00)	1 (1.00)	0.415 (1.00)	0.778 (1.00)	0.00217 (1.00)	0.79 (1.00)	0.000239 (0.17)	0.336 (1.00)
7q gain	16 (22%)	56	0.813 (1.00)	0.779 (1.00)	0.471 (1.00)	0.336 (1.00)	0.327 (1.00)	0.895 (1.00)	0.778 (1.00)	1 (1.00)	0.000703 (0.496)	0.407 (1.00)	0.000263 (0.186)	0.163 (1.00)
1p gain	5 (7%)	67	0.929 (1.00)	0.342 (1.00)	0.449 (1.00)	1 (1.00)	0.32 (1.00)	0.248 (1.00)	1 (1.00)	1 (1.00)			0.697 (1.00)	0.943 (1.00)
1q gain	15 (21%)	57	0.895 (1.00)	0.696 (1.00)	0.285 (1.00)	0.332 (1.00)	1 (1.00)	0.0941 (1.00)	0.0795 (1.00)	1 (1.00)	0.546 (1.00)	0.0514 (1.00)	0.856 (1.00)	0.563 (1.00)
2p gain	6 (8%)	66	0.927 (1.00)	0.34 (1.00)	0.791 (1.00)	1 (1.00)	0.639 (1.00)	0.0759 (1.00)	0.674 (1.00)	1 (1.00)	0.303 (1.00)	0.245 (1.00)	0.433 (1.00)	0.511 (1.00)
2q gain	6 (8%)	66	0.927 (1.00)	0.34 (1.00)	0.791 (1.00)	1 (1.00)	0.639 (1.00)	0.0759 (1.00)	0.674 (1.00)	1 (1.00)	0.303 (1.00)	0.245 (1.00)	0.433 (1.00)	0.511 (1.00)
3q gain	8 (11%)	64	0.00325 (1.00)	0.706 (1.00)	0.123 (1.00)	0.171 (1.00)	0.189 (1.00)	0.305 (1.00)	0.26 (1.00)	1 (1.00)			0.566 (1.00)	0.512 (1.00)
5p gain	9 (12%)	63	0.322 (1.00)	0.00366 (1.00)	0.862 (1.00)	1 (1.00)	0.683 (1.00)	1 (1.00)	0.478 (1.00)	0.63 (1.00)	0.0379 (1.00)	0.0395 (1.00)	0.163 (1.00)	0.671 (1.00)
5q gain	5 (7%)	67	0.468 (1.00)	0.0636 (1.00)	0.748 (1.00)	0.41 (1.00)	0.595 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)			1 (1.00)	0.179 (1.00)
8p gain	9 (12%)	63	0.00568 (1.00)	0.551 (1.00)	0.582 (1.00)	0.585 (1.00)	0.683 (1.00)	0.815 (1.00)	1 (1.00)	1 (1.00)			0.253 (1.00)	0.564 (1.00)
8q gain	18 (25%)	54	0.487 (1.00)	0.995 (1.00)	0.817 (1.00)	0.672 (1.00)	0.367 (1.00)	0.335 (1.00)	0.415 (1.00)	1 (1.00)	0.551 (1.00)	0.839 (1.00)	0.226 (1.00)	0.595 (1.00)
10p gain	3 (4%)	69	0.448 (1.00)	0.838 (1.00)	0.95 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)			0.351 (1.00)	0.836 (1.00)
10q gain	5 (7%)	67	0.429 (1.00)	0.354 (1.00)	0.553 (1.00)	1 (1.00)	1 (1.00)	0.179 (1.00)	0.357 (1.00)	1 (1.00)			0.433 (1.00)	0.92 (1.00)
11p gain	7 (10%)	65	0.856 (1.00)	0.793 (1.00)	0.837 (1.00)	1 (1.00)	1 (1.00)	0.213 (1.00)	0.429 (1.00)	1 (1.00)			0.0311 (1.00)	0.228 (1.00)
11q gain	6 (8%)	66	0.0304 (1.00)	0.0489 (1.00)	0.791 (1.00)	1 (1.00)	0.639 (1.00)	0.404 (1.00)	0.674 (1.00)	1 (1.00)			0.433 (1.00)	0.596 (1.00)
12p gain	7 (10%)	65	0.0598 (1.00)	0.223 (1.00)	0.654 (1.00)	0.527 (1.00)	0.67 (1.00)	0.773 (1.00)	0.107 (1.00)	0.138 (1.00)			0.0474 (1.00)	0.279 (1.00)
12q gain	6 (8%)	66	0.00293 (1.00)	0.359 (1.00)	0.718 (1.00)	1 (1.00)	0.327 (1.00)	0.534 (1.00)	0.199 (1.00)	0.104 (1.00)			0.0158 (1.00)	0.194 (1.00)
13q gain	4 (6%)	68	0.209 (1.00)	0.992 (1.00)	0.868 (1.00)	1 (1.00)	0.566 (1.00)	1 (1.00)	0.614 (1.00)	0.346 (1.00)			0.586 (1.00)	0.888 (1.00)
14q gain	8 (11%)	64	0.731 (1.00)	0.444 (1.00)	0.507 (1.00)	1 (1.00)	0.67 (1.00)	0.389 (1.00)	1 (1.00)	1 (1.00)	0.00315 (1.00)	0.905 (1.00)	0.113 (1.00)	0.37 (1.00)
15q gain	4 (6%)	68	0.0246 (1.00)	0.119 (1.00)	0.868 (1.00)	1 (1.00)	0.566 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)			0.657 (1.00)	0.246 (1.00)
16p gain	7 (10%)	65	0.665 (1.00)	0.149 (1.00)	0.612 (1.00)	0.527 (1.00)	0.359 (1.00)	0.358 (1.00)	0.429 (1.00)	0.533 (1.00)	0.000477 (0.338)	0.513 (1.00)	0.0129 (1.00)	0.477 (1.00)
16q gain	8 (11%)	64	0.606 (1.00)	0.119 (1.00)	0.717 (1.00)	0.578 (1.00)	0.409 (1.00)	0.305 (1.00)	0.71 (1.00)	0.584 (1.00)	0.000477 (0.338)	0.513 (1.00)	0.0183 (1.00)	0.675 (1.00)
17q gain	3 (4%)	69	0.0933 (1.00)	0.886 (1.00)	0.95 (1.00)	1 (1.00)	1 (1.00)	0.343 (1.00)	1 (1.00)	1 (1.00)				0.813 (1.00)
18p gain	8 (11%)	64	0.371 (1.00)	0.0753 (1.00)	0.682 (1.00)	1 (1.00)	0.409 (1.00)	0.305 (1.00)	0.71 (1.00)	0.175 (1.00)			0.202 (1.00)	0.0122 (1.00)
19p gain	3 (4%)	69	0.772 (1.00)	0.531 (1.00)	0.927 (1.00)	1 (1.00)	0.566 (1.00)	0.343 (1.00)	1 (1.00)	1 (1.00)				0.134 (1.00)
19q gain	8 (11%)	64	0.869 (1.00)	0.948 (1.00)	0.308 (1.00)	1 (1.00)	0.67 (1.00)	1 (1.00)	0.71 (1.00)	1 (1.00)	0.00292 (1.00)	0.72 (1.00)	0.387 (1.00)	0.128 (1.00)
20p gain	12 (17%)	60	0.462 (1.00)	0.0121 (1.00)	0.402 (1.00)	0.33 (1.00)	1 (1.00)	1 (1.00)	0.111 (1.00)	1 (1.00)	0.157 (1.00)	0.525 (1.00)	0.0729 (1.00)	0.772 (1.00)
20q gain	13 (18%)	59	0.468 (1.00)	0.00674 (1.00)	0.413 (1.00)	0.602 (1.00)	1 (1.00)	0.871 (1.00)	0.0632 (1.00)	1 (1.00)	0.157 (1.00)	0.525 (1.00)	0.111 (1.00)	0.607 (1.00)
22q gain	4 (6%)	68	0.662 (1.00)	0.594 (1.00)	0.968 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.614 (1.00)	1 (1.00)			1 (1.00)	0.683 (1.00)
xq gain	3 (4%)	69		0.0628 (1.00)	0.0441 (1.00)	1 (1.00)	1 (1.00)	0.627 (1.00)	1 (1.00)	1 (1.00)			0.586 (1.00)	0.407 (1.00)
1p loss	11 (15%)	61	0.0961 (1.00)	0.507 (1.00)	0.665 (1.00)	0.585 (1.00)	1 (1.00)	0.0345 (1.00)	0.189 (1.00)	0.414 (1.00)	0.297 (1.00)	0.117 (1.00)	0.651 (1.00)	0.239 (1.00)
1q loss	4 (6%)	68	0.0587 (1.00)	0.347 (1.00)	0.968 (1.00)	1 (1.00)	1 (1.00)	0.687 (1.00)	0.614 (1.00)	1 (1.00)			0.657 (1.00)	0.72 (1.00)
2p loss	6 (8%)	66	0.314 (1.00)	0.709 (1.00)	0.946 (1.00)	1 (1.00)	1 (1.00)	0.763 (1.00)	1 (1.00)	0.477 (1.00)			0.0776 (1.00)	0.446 (1.00)
3p loss	12 (17%)	60	0.843 (1.00)	0.383 (1.00)	0.891 (1.00)	1 (1.00)	1 (1.00)	0.731 (1.00)	0.111 (1.00)	1 (1.00)	0.0954 (1.00)	0.513 (1.00)	0.0556 (1.00)	0.175 (1.00)
3q loss	9 (12%)	63	0.509 (1.00)	0.842 (1.00)	0.849 (1.00)	0.585 (1.00)	1 (1.00)	0.815 (1.00)	0.151 (1.00)	0.63 (1.00)	0.000477 (0.338)	0.513 (1.00)	0.116 (1.00)	0.456 (1.00)
4p loss	10 (14%)	62	0.0952 (1.00)	0.835 (1.00)	0.803 (1.00)	1 (1.00)	0.683 (1.00)	0.195 (1.00)	0.0847 (1.00)	0.374 (1.00)	0.952 (1.00)	0.805 (1.00)	0.618 (1.00)	0.988 (1.00)
4q loss	9 (12%)	63	0.549 (1.00)	0.685 (1.00)	0.709 (1.00)	1 (1.00)	0.409 (1.00)	0.521 (1.00)	0.0278 (1.00)	0.333 (1.00)	0.724 (1.00)	0.805 (1.00)	0.445 (1.00)	0.21 (1.00)
5p loss	3 (4%)	69	0.469 (1.00)	0.499 (1.00)	0.927 (1.00)	1 (1.00)	0.566 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)				0.858 (1.00)
5q loss	7 (10%)	65	0.761 (1.00)	0.434 (1.00)	0.637 (1.00)	1 (1.00)	0.179 (1.00)	0.773 (1.00)	1 (1.00)	0.533 (1.00)	0.0014 (0.986)	0.284 (1.00)	0.0158 (1.00)	0.142 (1.00)
6p loss	24 (33%)	48	0.372 (1.00)	0.298 (1.00)	0.606 (1.00)	0.412 (1.00)	0.774 (1.00)	0.221 (1.00)	0.211 (1.00)	1 (1.00)	0.319 (1.00)	0.622 (1.00)	0.364 (1.00)	0.585 (1.00)
6q loss	30 (42%)	42	0.715 (1.00)	0.416 (1.00)	0.62 (1.00)	0.227 (1.00)	0.582 (1.00)	0.0662 (1.00)	1 (1.00)	0.372 (1.00)	0.415 (1.00)	0.625 (1.00)	0.461 (1.00)	0.73 (1.00)
8p loss	10 (14%)	62	0.977 (1.00)	0.44 (1.00)	0.803 (1.00)	1 (1.00)	0.683 (1.00)	0.384 (1.00)	0.307 (1.00)	0.214 (1.00)			0.307 (1.00)	0.811 (1.00)
9p loss	29 (40%)	43	0.0777 (1.00)	0.671 (1.00)	0.118 (1.00)	0.23 (1.00)	0.269 (1.00)	0.285 (1.00)	1 (1.00)	0.826 (1.00)	0.106 (1.00)	0.0726 (1.00)	0.355 (1.00)	0.301 (1.00)
9q loss	19 (26%)	53	0.0795 (1.00)	0.966 (1.00)	0.435 (1.00)	0.667 (1.00)	0.762 (1.00)	0.454 (1.00)	1 (1.00)	0.792 (1.00)	0.232 (1.00)	0.284 (1.00)	0.208 (1.00)	0.514 (1.00)
10p loss	12 (17%)	60	0.282 (1.00)	0.172 (1.00)	0.407 (1.00)	0.33 (1.00)	1 (1.00)	0.137 (1.00)	0.343 (1.00)	1 (1.00)	0.839 (1.00)	0.483 (1.00)	0.352 (1.00)	0.458 (1.00)
10q loss	11 (15%)	61	0.309 (1.00)	0.201 (1.00)	0.826 (1.00)	1 (1.00)	0.718 (1.00)	0.175 (1.00)	0.514 (1.00)	1 (1.00)	0.412 (1.00)	0.218 (1.00)	0.307 (1.00)	0.147 (1.00)
11p loss	6 (8%)	66	0.794 (1.00)	0.355 (1.00)	0.946 (1.00)	1 (1.00)	1 (1.00)	0.404 (1.00)	1 (1.00)	1 (1.00)			0.716 (1.00)	0.39 (1.00)
11q loss	6 (8%)	66	0.243 (1.00)	0.886 (1.00)	0.946 (1.00)	1 (1.00)	1 (1.00)	0.763 (1.00)	1 (1.00)	0.477 (1.00)			0.235 (1.00)	0.176 (1.00)
12p loss	9 (12%)	63	0.314 (1.00)	0.394 (1.00)	0.439 (1.00)	0.585 (1.00)	0.409 (1.00)	0.0817 (1.00)	0.478 (1.00)	0.333 (1.00)	0.0954 (1.00)	0.806 (1.00)	0.116 (1.00)	0.569 (1.00)
12q loss	10 (14%)	62	0.24 (1.00)	0.236 (1.00)	0.803 (1.00)	1 (1.00)	0.683 (1.00)	0.0548 (1.00)	0.735 (1.00)	0.374 (1.00)	0.182 (1.00)	0.806 (1.00)	0.195 (1.00)	0.496 (1.00)
13q loss	11 (15%)	61	0.851 (1.00)	0.49 (1.00)	0.411 (1.00)	0.585 (1.00)	0.269 (1.00)	0.341 (1.00)	0.514 (1.00)	0.295 (1.00)	0.182 (1.00)	0.851 (1.00)	0.0729 (1.00)	0.176 (1.00)
14q loss	5 (7%)	67	0.977 (1.00)	0.774 (1.00)	0.748 (1.00)	0.41 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.17 (1.00)	0.598 (1.00)	0.71 (1.00)	0.433 (1.00)	0.204 (1.00)
15q loss	10 (14%)	62	0.827 (1.00)	0.945 (1.00)	0.509 (1.00)	1 (1.00)	0.683 (1.00)	0.195 (1.00)	0.307 (1.00)	0.214 (1.00)	0.144 (1.00)	0.668 (1.00)	0.445 (1.00)	0.488 (1.00)
17p loss	27 (38%)	45	0.117 (1.00)	0.972 (1.00)	0.276 (1.00)	0.0405 (1.00)	0.781 (1.00)	0.695 (1.00)	1 (1.00)	0.344 (1.00)	0.323 (1.00)	0.487 (1.00)	0.00672 (1.00)	0.506 (1.00)
17q loss	10 (14%)	62	0.399 (1.00)	0.976 (1.00)	0.756 (1.00)	0.583 (1.00)	1 (1.00)	0.473 (1.00)	0.307 (1.00)	0.214 (1.00)			0.0421 (1.00)	0.12 (1.00)
18p loss	25 (35%)	47	0.831 (1.00)	0.0708 (1.00)	0.0997 (1.00)	0.227 (1.00)	0.387 (1.00)	0.489 (1.00)	1 (1.00)	1 (1.00)	0.0723 (1.00)	0.795 (1.00)	0.434 (1.00)	0.468 (1.00)
18q loss	38 (53%)	34	0.439 (1.00)	0.988 (1.00)	0.158 (1.00)	1 (1.00)	0.79 (1.00)	0.162 (1.00)	0.814 (1.00)	1 (1.00)	0.733 (1.00)	0.0726 (1.00)	0.0259 (1.00)	0.802 (1.00)
19p loss	8 (11%)	64	0.691 (1.00)	0.83 (1.00)	0.507 (1.00)	1 (1.00)	0.67 (1.00)	0.389 (1.00)	0.71 (1.00)	1 (1.00)	0.982 (1.00)	0.0739 (1.00)	0.253 (1.00)	0.125 (1.00)
19q loss	5 (7%)	67	0.876 (1.00)	0.897 (1.00)	0.449 (1.00)	1 (1.00)	1 (1.00)	0.179 (1.00)	1 (1.00)	1 (1.00)			0.433 (1.00)	0.533 (1.00)
20p loss	7 (10%)	65	0.00261 (1.00)	0.849 (1.00)	0.637 (1.00)	0.527 (1.00)	0.179 (1.00)	0.773 (1.00)	1 (1.00)	0.533 (1.00)	0.73 (1.00)		0.113 (1.00)	0.312 (1.00)
21q loss	24 (33%)	48	0.113 (1.00)	0.42 (1.00)	0.29 (1.00)	0.0871 (1.00)	0.265 (1.00)	0.0709 (1.00)	0.803 (1.00)	0.845 (1.00)	0.829 (1.00)	0.472 (1.00)	0.0817 (1.00)	0.0942 (1.00)
22q loss	14 (19%)	58	0.741 (1.00)	0.444 (1.00)	0.496 (1.00)	0.332 (1.00)	0.726 (1.00)	0.184 (1.00)	0.0346 (1.00)	0.491 (1.00)	0.881 (1.00)	0.453 (1.00)	0.263 (1.00)	0.395 (1.00)
xq loss	6 (8%)	66	0.831 (1.00)	0.866 (1.00)	0.946 (1.00)	1 (1.00)	1 (1.00)	0.404 (1.00)	1 (1.00)	1 (1.00)	0.759 (1.00)	0.0597 (1.00)	0.716 (1.00)	0.226 (1.00)

'3p gain' versus 'Time to Death'

P value = 1.03e-05 (logrank test), Q value = 0.0073

Table S1. Gene #5: '3p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	69	29	0.0 - 49.4 (7.2)
3P GAIN MUTATED	5	3	0.1 - 4.8 (2.5)
3P GAIN WILD-TYPE	64	26	0.0 - 49.4 (8.0)

Figure S1. Get High-res Image Gene #5: '3p gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'COMPLETENESS.OF.RESECTION'

P value = 0.000239 (Fisher's exact test), Q value = 0.17

Table S2. Gene #9: '7p gain' versus Clinical Feature #11: 'COMPLETENESS.OF.RESECTION'

nPatients	R0	R1	RX
ALL	43	24	2
7P GAIN MUTATED	4	10	2
7P GAIN WILD-TYPE	39	14	0

Figure S2. Get High-res Image Gene #9: '7p gain' versus Clinical Feature #11: 'COMPLETENESS.OF.RESECTION'

'7q gain' versus 'COMPLETENESS.OF.RESECTION'

P value = 0.000263 (Fisher's exact test), Q value = 0.19

Table S3. Gene #10: '7q gain' versus Clinical Feature #11: 'COMPLETENESS.OF.RESECTION'

nPatients	R0	R1	RX
ALL	43	24	2
7Q GAIN MUTATED	3	9	2
7Q GAIN WILD-TYPE	40	15	0

Figure S3. Get High-res Image Gene #10: '7q gain' versus Clinical Feature #11: 'COMPLETENESS.OF.RESECTION'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Clinical data file = PAAD-TP.merged_data.txt
Number of patients = 72
Number of significantly arm-level cnvs = 64
Number of selected clinical features = 12
Exclude regions 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

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

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[4] 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)

[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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