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

Glioblastoma Multiforme (Primary solid tumor)

02 April 2015 | analyses__2015_04_02

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 (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C12B8X1S

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 82 arm-level events and 8 clinical features across 570 patients, 14 significant findings detected with Q value < 0.25.

7p gain cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
7q gain cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
10p gain cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
20p gain cnv correlated to 'YEARS_TO_BIRTH'.
20q gain cnv correlated to 'YEARS_TO_BIRTH'.
6p loss cnv correlated to 'Time to Death'.
8p loss cnv correlated to 'RACE'.
10p loss cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
10q loss cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 82 arm-level events and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 14 significant findings detected.


		Clinical Features	Time to Death	YEARS TO BIRTH	GENDER	KARNOFSKY PERFORMANCE SCORE	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	RACE	ETHNICITY
	nCNV (%)	nWild-Type	logrank test	Wilcoxon-test	Fisher's exact test	Wilcoxon-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
7p gain	462 (81%)	108	4.94e-05 (0.00541)	2.26e-06 (0.000494)	0.744 (1.00)	0.984 (1.00)	0.0255 (0.689)	0.141 (1.00)	0.0625 (0.876)	0.27 (1.00)
7q gain	467 (82%)	103	9.81e-05 (0.00805)	7.86e-06 (0.00129)	0.222 (1.00)	0.83 (1.00)	0.0343 (0.804)	0.132 (1.00)	0.0381 (0.811)	0.249 (1.00)
10p gain	13 (2%)	557	0.00245 (0.134)	6.17e-05 (0.00578)	0.0405 (0.811)	0.359 (1.00)	0.276 (1.00)	0.767 (1.00)	0.0118 (0.455)	0.281 (1.00)
10p loss	476 (84%)	94	0.000303 (0.0181)	3.12e-09 (2.04e-06)	0.167 (1.00)	0.119 (0.969)	0.00606 (0.265)	0.719 (1.00)	0.111 (0.948)	0.133 (1.00)
10q loss	487 (85%)	83	0.00027 (0.0177)	1.35e-07 (4.42e-05)	0.466 (1.00)	0.0158 (0.545)	0.0524 (0.876)	0.706 (1.00)	0.0762 (0.876)	0.0911 (0.89)
20p gain	220 (39%)	350	0.344 (1.00)	2.43e-05 (0.00318)	0.334 (1.00)	0.583 (1.00)	0.486 (1.00)	0.523 (1.00)	0.0406 (0.811)	1 (1.00)
20q gain	218 (38%)	352	0.582 (1.00)	0.000127 (0.00922)	0.29 (1.00)	0.771 (1.00)	0.486 (1.00)	0.521 (1.00)	0.062 (0.876)	1 (1.00)
6p loss	86 (15%)	484	0.00309 (0.156)	0.382 (1.00)	0.811 (1.00)	0.518 (1.00)	0.631 (1.00)	0.71 (1.00)	0.256 (1.00)	0.702 (1.00)
8p loss	58 (10%)	512	0.78 (1.00)	0.172 (1.00)	0.157 (1.00)	0.405 (1.00)	0.614 (1.00)	0.381 (1.00)	0.004 (0.187)	0.619 (1.00)
1p gain	81 (14%)	489	0.366 (1.00)	0.462 (1.00)	0.624 (1.00)	0.229 (1.00)	0.0308 (0.749)	0.253 (1.00)	0.9 (1.00)	0.665 (1.00)
1q gain	88 (15%)	482	0.772 (1.00)	0.61 (1.00)	0.342 (1.00)	0.32 (1.00)	0.219 (1.00)	0.388 (1.00)	0.778 (1.00)	0.688 (1.00)
2p gain	37 (6%)	533	0.583 (1.00)	0.78 (1.00)	0.163 (1.00)	0.531 (1.00)	1 (1.00)	0.857 (1.00)	0.336 (1.00)	1 (1.00)
2q gain	36 (6%)	534	0.403 (1.00)	0.309 (1.00)	0.378 (1.00)	0.372 (1.00)	1 (1.00)	1 (1.00)	0.321 (1.00)	1 (1.00)
3p gain	57 (10%)	513	0.814 (1.00)	0.0443 (0.854)	0.319 (1.00)	0.705 (1.00)	0.708 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
3q gain	63 (11%)	507	0.668 (1.00)	0.11 (0.948)	0.413 (1.00)	0.645 (1.00)	0.497 (1.00)	0.672 (1.00)	0.931 (1.00)	1 (1.00)
4p gain	36 (6%)	534	0.795 (1.00)	0.494 (1.00)	0.86 (1.00)	0.0787 (0.885)	1 (1.00)	0.585 (1.00)	0.567 (1.00)	0.576 (1.00)
4q gain	33 (6%)	537	0.905 (1.00)	0.566 (1.00)	0.468 (1.00)	0.075 (0.876)	1 (1.00)	0.342 (1.00)	0.529 (1.00)	1 (1.00)
5p gain	49 (9%)	521	0.74 (1.00)	0.69 (1.00)	0.169 (1.00)	0.216 (1.00)	0.0621 (0.876)	0.874 (1.00)	1 (1.00)	0.299 (1.00)
5q gain	41 (7%)	529	0.386 (1.00)	0.522 (1.00)	0.134 (1.00)	0.752 (1.00)	0.106 (0.943)	0.608 (1.00)	0.83 (1.00)	0.612 (1.00)
6p gain	24 (4%)	546	0.358 (1.00)	0.5 (1.00)	0.671 (1.00)	0.752 (1.00)	1 (1.00)	0.268 (1.00)	0.479 (1.00)	1 (1.00)
6q gain	23 (4%)	547	0.283 (1.00)	0.251 (1.00)	1 (1.00)	0.718 (1.00)	1 (1.00)	0.651 (1.00)	0.56 (1.00)	1 (1.00)
8p gain	52 (9%)	518	0.936 (1.00)	0.815 (1.00)	0.657 (1.00)	0.579 (1.00)	0.632 (1.00)	0.877 (1.00)	0.316 (1.00)	1 (1.00)
8q gain	59 (10%)	511	0.429 (1.00)	0.373 (1.00)	0.482 (1.00)	0.681 (1.00)	0.57 (1.00)	1 (1.00)	0.71 (1.00)	1 (1.00)
9p gain	47 (8%)	523	0.375 (1.00)	0.642 (1.00)	0.164 (1.00)	0.896 (1.00)	0.155 (1.00)	0.872 (1.00)	0.294 (1.00)	0.241 (1.00)
9q gain	70 (12%)	500	0.928 (1.00)	0.925 (1.00)	0.153 (1.00)	0.838 (1.00)	0.376 (1.00)	0.892 (1.00)	0.293 (1.00)	0.644 (1.00)
10q gain	3 (1%)	567	0.353 (1.00)	0.662 (1.00)	0.565 (1.00)		1 (1.00)	0.254 (1.00)	1 (1.00)	0.0727 (0.876)
11p gain	17 (3%)	553	0.589 (1.00)	0.961 (1.00)	0.806 (1.00)	0.382 (1.00)	1 (1.00)	0.601 (1.00)	0.595 (1.00)	0.335 (1.00)
11q gain	14 (2%)	556	0.261 (1.00)	0.117 (0.969)	0.267 (1.00)	0.169 (1.00)	0.458 (1.00)	0.16 (1.00)	1 (1.00)	0.3 (1.00)
12p gain	59 (10%)	511	0.631 (1.00)	0.31 (1.00)	0.482 (1.00)	0.621 (1.00)	0.929 (1.00)	0.559 (1.00)	0.928 (1.00)	1 (1.00)
12q gain	48 (8%)	522	0.949 (1.00)	0.617 (1.00)	0.218 (1.00)	0.743 (1.00)	0.555 (1.00)	0.632 (1.00)	0.138 (1.00)	0.612 (1.00)
13q gain	10 (2%)	560	0.466 (1.00)	0.011 (0.449)	0.202 (1.00)	0.071 (0.876)	0.566 (1.00)	0.0888 (0.889)	1 (1.00)	1 (1.00)
14q gain	22 (4%)	548	0.291 (1.00)	0.0581 (0.876)	0.513 (1.00)	0.461 (1.00)	0.0948 (0.901)	0.818 (1.00)	0.83 (1.00)	1 (1.00)
15q gain	24 (4%)	546	0.296 (1.00)	0.879 (1.00)	0.527 (1.00)	0.0894 (0.889)	0.828 (1.00)	0.187 (1.00)	0.842 (1.00)	1 (1.00)
16p gain	38 (7%)	532	0.0408 (0.811)	0.859 (1.00)	0.306 (1.00)	0.94 (1.00)	1 (1.00)	0.0505 (0.876)	0.461 (1.00)	1 (1.00)
16q gain	37 (6%)	533	0.16 (1.00)	0.88 (1.00)	0.606 (1.00)	0.832 (1.00)	1 (1.00)	0.0704 (0.876)	0.452 (1.00)	1 (1.00)
17p gain	48 (8%)	522	0.116 (0.969)	0.0255 (0.689)	0.28 (1.00)	0.377 (1.00)	0.412 (1.00)	0.337 (1.00)	0.409 (1.00)	1 (1.00)
17q gain	59 (10%)	511	0.0262 (0.689)	0.0136 (0.494)	0.576 (1.00)	0.459 (1.00)	0.666 (1.00)	0.309 (1.00)	0.488 (1.00)	0.376 (1.00)
18p gain	57 (10%)	513	0.606 (1.00)	0.39 (1.00)	0.67 (1.00)	0.228 (1.00)	0.0661 (0.876)	0.658 (1.00)	0.224 (1.00)	0.347 (1.00)
18q gain	57 (10%)	513	0.733 (1.00)	0.227 (1.00)	0.2 (1.00)	0.231 (1.00)	0.0656 (0.876)	0.46 (1.00)	0.397 (1.00)	1 (1.00)
19p gain	222 (39%)	348	0.485 (1.00)	0.939 (1.00)	0.792 (1.00)	0.974 (1.00)	0.591 (1.00)	0.855 (1.00)	0.547 (1.00)	0.551 (1.00)
19q gain	196 (34%)	374	0.634 (1.00)	0.48 (1.00)	0.59 (1.00)	0.841 (1.00)	0.848 (1.00)	0.574 (1.00)	0.304 (1.00)	0.357 (1.00)
21q gain	63 (11%)	507	0.633 (1.00)	0.0812 (0.885)	0.892 (1.00)	0.134 (1.00)	0.137 (1.00)	1 (1.00)	0.105 (0.943)	0.376 (1.00)
22q gain	34 (6%)	536	0.248 (1.00)	0.571 (1.00)	1 (1.00)	0.313 (1.00)	0.379 (1.00)	1 (1.00)	0.793 (1.00)	0.149 (1.00)
xp gain	15 (3%)	555	0.829 (1.00)	0.439 (1.00)	0.598 (1.00)	0.511 (1.00)	0.713 (1.00)	0.583 (1.00)	0.724 (1.00)	0.204 (1.00)
xq gain	16 (3%)	554	0.589 (1.00)	0.558 (1.00)	1 (1.00)	0.626 (1.00)	0.366 (1.00)	0.177 (1.00)	0.737 (1.00)	0.244 (1.00)
1p loss	15 (3%)	555	0.414 (1.00)	0.0514 (0.876)	0.425 (1.00)	0.81 (1.00)	0.486 (1.00)	0.583 (1.00)	0.735 (1.00)	1 (1.00)
1q loss	14 (2%)	556	0.337 (1.00)	0.0262 (0.689)	1 (1.00)	0.168 (1.00)	1 (1.00)	0.406 (1.00)	0.711 (1.00)	1 (1.00)
2p loss	31 (5%)	539	0.696 (1.00)	0.0823 (0.885)	0.0878 (0.889)	0.83 (1.00)	1 (1.00)	0.326 (1.00)	0.515 (1.00)	1 (1.00)
2q loss	31 (5%)	539	0.887 (1.00)	0.11 (0.948)	0.185 (1.00)	0.56 (1.00)	0.744 (1.00)	0.168 (1.00)	0.512 (1.00)	1 (1.00)
3p loss	40 (7%)	530	0.458 (1.00)	0.0696 (0.876)	1 (1.00)	0.978 (1.00)	0.569 (1.00)	0.0814 (0.885)	0.744 (1.00)	0.203 (1.00)
3q loss	34 (6%)	536	0.913 (1.00)	0.655 (1.00)	0.589 (1.00)	0.652 (1.00)	0.873 (1.00)	0.457 (1.00)	0.803 (1.00)	0.515 (1.00)
4p loss	53 (9%)	517	0.205 (1.00)	0.741 (1.00)	0.184 (1.00)	0.248 (1.00)	0.303 (1.00)	0.54 (1.00)	0.457 (1.00)	0.299 (1.00)
4q loss	54 (9%)	516	0.0283 (0.715)	0.124 (0.992)	0.771 (1.00)	0.293 (1.00)	1 (1.00)	0.65 (1.00)	0.599 (1.00)	0.28 (1.00)
5p loss	42 (7%)	528	0.0991 (0.929)	0.524 (1.00)	1 (1.00)	0.552 (1.00)	0.355 (1.00)	0.0254 (0.689)	0.103 (0.943)	0.203 (1.00)
5q loss	43 (8%)	527	0.106 (0.943)	0.574 (1.00)	1 (1.00)	0.739 (1.00)	0.194 (1.00)	0.0922 (0.89)	0.42 (1.00)	0.0486 (0.876)
6q loss	124 (22%)	446	0.235 (1.00)	0.753 (1.00)	0.299 (1.00)	0.724 (1.00)	0.738 (1.00)	0.914 (1.00)	0.247 (1.00)	0.477 (1.00)
7p loss	8 (1%)	562	0.454 (1.00)	0.0527 (0.876)	1 (1.00)	0.749 (1.00)	1 (1.00)	0.282 (1.00)	0.619 (1.00)	1 (1.00)
7q loss	6 (1%)	564	0.612 (1.00)	0.0239 (0.689)	1 (1.00)	0.307 (1.00)	1 (1.00)	0.669 (1.00)	0.517 (1.00)	1 (1.00)
8q loss	42 (7%)	528	0.071 (0.876)	0.209 (1.00)	0.417 (1.00)	0.255 (1.00)	0.895 (1.00)	0.865 (1.00)	0.28 (1.00)	1 (1.00)
9p loss	198 (35%)	372	0.48 (1.00)	0.584 (1.00)	0.719 (1.00)	0.562 (1.00)	0.968 (1.00)	0.575 (1.00)	0.51 (1.00)	0.0642 (0.876)
9q loss	93 (16%)	477	0.795 (1.00)	0.687 (1.00)	0.42 (1.00)	0.745 (1.00)	0.231 (1.00)	0.719 (1.00)	0.233 (1.00)	0.235 (1.00)
11p loss	99 (17%)	471	0.236 (1.00)	0.82 (1.00)	0.0709 (0.876)	0.638 (1.00)	0.482 (1.00)	0.638 (1.00)	0.638 (1.00)	0.7 (1.00)
11q loss	93 (16%)	477	0.986 (1.00)	0.357 (1.00)	0.42 (1.00)	0.801 (1.00)	0.806 (1.00)	0.335 (1.00)	0.953 (1.00)	0.229 (1.00)
12p loss	58 (10%)	512	0.853 (1.00)	0.61 (1.00)	0.48 (1.00)	0.76 (1.00)	0.664 (1.00)	0.381 (1.00)	0.206 (1.00)	1 (1.00)
12q loss	57 (10%)	513	0.976 (1.00)	0.656 (1.00)	0.568 (1.00)	0.594 (1.00)	0.36 (1.00)	0.883 (1.00)	0.22 (1.00)	0.328 (1.00)
13q loss	184 (32%)	386	0.941 (1.00)	0.794 (1.00)	1 (1.00)	0.718 (1.00)	0.56 (1.00)	0.703 (1.00)	0.395 (1.00)	0.759 (1.00)
14q loss	145 (25%)	425	0.847 (1.00)	0.794 (1.00)	0.327 (1.00)	0.781 (1.00)	0.513 (1.00)	0.759 (1.00)	0.278 (1.00)	0.31 (1.00)
15q loss	105 (18%)	465	0.896 (1.00)	0.0748 (0.876)	0.581 (1.00)	0.838 (1.00)	0.671 (1.00)	0.0383 (0.811)	0.957 (1.00)	0.254 (1.00)
16p loss	63 (11%)	507	0.12 (0.969)	0.308 (1.00)	0.683 (1.00)	0.882 (1.00)	0.186 (1.00)	0.0883 (0.889)	1 (1.00)	1 (1.00)
16q loss	82 (14%)	488	0.202 (1.00)	0.838 (1.00)	1 (1.00)	0.58 (1.00)	0.423 (1.00)	0.0563 (0.876)	0.648 (1.00)	0.696 (1.00)
17p loss	63 (11%)	507	0.725 (1.00)	0.492 (1.00)	0.413 (1.00)	0.923 (1.00)	0.861 (1.00)	0.156 (1.00)	1 (1.00)	1 (1.00)
17q loss	40 (7%)	530	0.755 (1.00)	0.468 (1.00)	0.503 (1.00)	0.708 (1.00)	0.894 (1.00)	0.0543 (0.876)	0.607 (1.00)	0.587 (1.00)
18p loss	70 (12%)	500	0.262 (1.00)	0.838 (1.00)	0.602 (1.00)	0.58 (1.00)	0.572 (1.00)	1 (1.00)	0.305 (1.00)	0.647 (1.00)
18q loss	62 (11%)	508	0.612 (1.00)	0.791 (1.00)	0.784 (1.00)	0.267 (1.00)	0.68 (1.00)	0.2 (1.00)	0.173 (1.00)	0.146 (1.00)
19p loss	27 (5%)	543	0.615 (1.00)	0.95 (1.00)	1 (1.00)	0.764 (1.00)	0.851 (1.00)	0.835 (1.00)	1 (1.00)	1 (1.00)
19q loss	35 (6%)	535	0.688 (1.00)	0.88 (1.00)	1 (1.00)	0.751 (1.00)	0.445 (1.00)	1 (1.00)	0.708 (1.00)	1 (1.00)
20p loss	18 (3%)	552	0.889 (1.00)	0.383 (1.00)	0.219 (1.00)	0.932 (1.00)	1 (1.00)	1 (1.00)	0.307 (1.00)	0.335 (1.00)
20q loss	16 (3%)	554	0.765 (1.00)	0.717 (1.00)	0.196 (1.00)	0.978 (1.00)	1 (1.00)	0.788 (1.00)	0.764 (1.00)	1 (1.00)
21q loss	42 (7%)	528	0.558 (1.00)	0.669 (1.00)	0.417 (1.00)	0.198 (1.00)	1 (1.00)	0.308 (1.00)	1 (1.00)	0.241 (1.00)
22q loss	181 (32%)	389	0.759 (1.00)	0.0895 (0.889)	0.854 (1.00)	0.471 (1.00)	0.789 (1.00)	0.848 (1.00)	0.675 (1.00)	1 (1.00)
xp loss	113 (20%)	457	0.231 (1.00)	0.58 (1.00)	0.335 (1.00)	0.572 (1.00)	0.953 (1.00)	0.656 (1.00)	0.135 (1.00)	0.714 (1.00)
xq loss	105 (18%)	465	0.214 (1.00)	0.613 (1.00)	0.32 (1.00)	0.497 (1.00)	0.822 (1.00)	0.732 (1.00)	0.211 (1.00)	0.469 (1.00)

'7p gain' versus 'Time to Death'

P value = 4.94e-05 (logrank test), Q value = 0.0054

Table S1. Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
7P GAIN MUTATED	461	385	0.1 - 127.6 (11.7)
7P GAIN WILD-TYPE	108	80	0.2 - 120.6 (14.8)

Figure S1. Get High-res Image Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'YEARS_TO_BIRTH'

P value = 2.26e-06 (Wilcoxon-test), Q value = 0.00049

Table S2. Gene #13: '7p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
7P GAIN MUTATED	462	59.6 (12.4)
7P GAIN WILD-TYPE	108	49.6 (19.4)

Figure S2. Get High-res Image Gene #13: '7p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'7q gain' versus 'Time to Death'

P value = 9.81e-05 (logrank test), Q value = 0.008

Table S3. Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
7Q GAIN MUTATED	466	386	0.1 - 127.6 (11.4)
7Q GAIN WILD-TYPE	103	79	0.2 - 120.6 (15.3)

Figure S3. Get High-res Image Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

'7q gain' versus 'YEARS_TO_BIRTH'

P value = 7.86e-06 (Wilcoxon-test), Q value = 0.0013

Table S4. Gene #14: '7q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
7Q GAIN MUTATED	467	59.6 (12.2)
7Q GAIN WILD-TYPE	103	49.4 (20.1)

Figure S4. Get High-res Image Gene #14: '7q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'10p gain' versus 'Time to Death'

P value = 0.00245 (logrank test), Q value = 0.13

Table S5. Gene #19: '10p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
10P GAIN MUTATED	13	8	0.4 - 100.0 (28.7)
10P GAIN WILD-TYPE	556	457	0.1 - 127.6 (11.8)

Figure S5. Get High-res Image Gene #19: '10p gain' versus Clinical Feature #1: 'Time to Death'

'10p gain' versus 'YEARS_TO_BIRTH'

P value = 6.17e-05 (Wilcoxon-test), Q value = 0.0058

Table S6. Gene #19: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
10P GAIN MUTATED	13	37.5 (17.4)
10P GAIN WILD-TYPE	557	58.2 (14.1)

Figure S6. Get High-res Image Gene #19: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'20p gain' versus 'YEARS_TO_BIRTH'

P value = 2.43e-05 (Wilcoxon-test), Q value = 0.0032

Table S7. Gene #36: '20p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
20P GAIN MUTATED	220	61.0 (13.0)
20P GAIN WILD-TYPE	350	55.7 (15.0)

Figure S7. Get High-res Image Gene #36: '20p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'20q gain' versus 'YEARS_TO_BIRTH'

P value = 0.000127 (Wilcoxon-test), Q value = 0.0092

Table S8. Gene #37: '20q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
20Q GAIN MUTATED	218	60.8 (13.3)
20Q GAIN WILD-TYPE	352	55.9 (15.0)

Figure S8. Get High-res Image Gene #37: '20q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'6p loss' versus 'Time to Death'

P value = 0.00309 (logrank test), Q value = 0.16

Table S9. Gene #52: '6p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
6P LOSS MUTATED	86	77	0.2 - 92.7 (9.5)
6P LOSS WILD-TYPE	483	388	0.1 - 127.6 (12.2)

Figure S9. Get High-res Image Gene #52: '6p loss' versus Clinical Feature #1: 'Time to Death'

'8p loss' versus 'RACE'

P value = 0.004 (Fisher's exact test), Q value = 0.19

Table S10. Gene #56: '8p loss' versus Clinical Feature #7: 'RACE'

nPatients	ASIAN	BLACK OR AFRICAN AMERICAN	WHITE
ALL	13	49	485
8P LOSS MUTATED	5	2	46
8P LOSS WILD-TYPE	8	47	439

Figure S10. Get High-res Image Gene #56: '8p loss' versus Clinical Feature #7: 'RACE'

'10p loss' versus 'Time to Death'

P value = 0.000303 (logrank test), Q value = 0.018

Table S11. Gene #60: '10p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
10P LOSS MUTATED	475	394	0.1 - 127.6 (11.8)
10P LOSS WILD-TYPE	94	71	0.4 - 115.9 (13.5)

Figure S11. Get High-res Image Gene #60: '10p loss' versus Clinical Feature #1: 'Time to Death'

'10p loss' versus 'YEARS_TO_BIRTH'

P value = 3.12e-09 (Wilcoxon-test), Q value = 2e-06

Table S12. Gene #60: '10p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
10P LOSS MUTATED	476	59.7 (12.7)
10P LOSS WILD-TYPE	94	47.9 (18.8)

Figure S12. Get High-res Image Gene #60: '10p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'10q loss' versus 'Time to Death'

P value = 0.00027 (logrank test), Q value = 0.018

Table S13. Gene #61: '10q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	569	465	0.1 - 127.6 (11.8)
10Q LOSS MUTATED	486	402	0.1 - 127.6 (11.7)
10Q LOSS WILD-TYPE	83	63	0.4 - 115.9 (14.1)

Figure S13. Get High-res Image Gene #61: '10q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'YEARS_TO_BIRTH'

P value = 1.35e-07 (Wilcoxon-test), Q value = 4.4e-05

Table S14. Gene #61: '10q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	570	57.7 (14.5)
10Q LOSS MUTATED	487	59.3 (13.1)
10Q LOSS WILD-TYPE	83	48.4 (18.6)

Figure S14. Get High-res Image Gene #61: '10q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

Methods & Data

Input

Copy number data file = broad_values_by_arm.txt from GISTIC pipeline
Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/GBM-TP/15096483/transformed.cor.cli.txt
Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/GBM-TP/15078636/GBM-TP.merged_data.txt
Number of patients = 570
Number of significantly arm-level cnvs = 82
Number of selected clinical features = 8
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

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] 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)

[3] 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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