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

Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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/C1GQ6W6C

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 68 arm-level events and 11 clinical features across 139 patients, 23 significant findings detected with Q value < 0.25.

1p gain cnv correlated to 'Time to Death'.
1q gain cnv correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', and 'PATHOLOGY.T.STAGE'.
6q gain cnv correlated to 'Time to Death'.
8q gain cnv correlated to 'Time to Death'.
17p gain cnv correlated to 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.T.STAGE', and 'PATHOLOGY.M.STAGE'.
17q gain cnv correlated to 'PATHOLOGY.M.STAGE'.
3q loss cnv correlated to 'Time to Death'.
8p loss cnv correlated to 'Time to Death'.
9p loss cnv correlated to 'NEOPLASM.DISEASESTAGE' and 'PATHOLOGY.T.STAGE'.
9q loss cnv correlated to 'PATHOLOGY.T.STAGE'.
11p loss cnv correlated to 'Time to Death'.
11q loss cnv correlated to 'Time to Death' and 'PATHOLOGY.T.STAGE'.
15q loss cnv correlated to 'Time to Death'.
16p loss cnv correlated to 'Time to Death'.
16q loss cnv correlated to 'Time to Death'.
17p loss cnv correlated to 'Time to Death'.
22q loss cnv correlated to 'PATHOLOGY.T.STAGE'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 68 arm-level events and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 23 significant findings detected.


		Clinical Features	Time to Death	AGE	NEOPLASM DISEASESTAGE	PATHOLOGY T STAGE	PATHOLOGY N STAGE	PATHOLOGY M STAGE	GENDER	KARNOFSKY PERFORMANCE SCORE	HISTOLOGICAL TYPE	NUMBERPACKYEARSSMOKED	YEAROFTOBACCOSMOKINGONSET
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	t-test	Fisher's exact test	t-test	t-test
1q gain	11 (8%)	128	3.7e-06 (0.00211)	0.375 (1.00)	0.000163 (0.0912)	6.89e-05 (0.0389)	0.379 (1.00)	0.13 (1.00)	0.0881 (1.00)		1 (1.00)
17p gain	81 (58%)	58	0.0772 (1.00)	0.0463 (1.00)	0.000111 (0.0625)	0.000432 (0.239)	0.227 (1.00)	2.33e-05 (0.0132)	0.024 (1.00)	0.246 (1.00)	1 (1.00)	0.352 (1.00)
9p loss	19 (14%)	120	0.00884 (1.00)	0.575 (1.00)	0.000155 (0.0872)	0.000215 (0.12)	0.21 (1.00)	0.0442 (1.00)	0.00727 (1.00)	0.37 (1.00)	1 (1.00)
11q loss	13 (9%)	126	1.31e-05 (0.00743)	0.0666 (1.00)	0.00056 (0.309)	0.000419 (0.232)	0.0585 (1.00)	0.18 (1.00)	0.532 (1.00)	0.341 (1.00)	0.452 (1.00)
1p gain	4 (3%)	135	6.27e-11 (3.59e-08)	0.437 (1.00)	0.0248 (1.00)	0.0119 (1.00)	0.0394 (1.00)	0.277 (1.00)	0.0823 (1.00)		1 (1.00)
6q gain	3 (2%)	136	2.7e-06 (0.00154)	0.254 (1.00)	0.0323 (1.00)	0.495 (1.00)		0.00273 (1.00)	0.554 (1.00)		0.125 (1.00)
8q gain	13 (9%)	126	1.27e-05 (0.00722)	0.82 (1.00)	0.0392 (1.00)	0.0331 (1.00)	0.0305 (1.00)	0.377 (1.00)	0.212 (1.00)	0.502 (1.00)	1 (1.00)
17q gain	94 (68%)	45	0.607 (1.00)	0.108 (1.00)	0.137 (1.00)	0.139 (1.00)	0.506 (1.00)	0.000309 (0.172)	0.114 (1.00)	0.651 (1.00)	0.664 (1.00)
3q loss	4 (3%)	135	1.54e-13 (8.86e-11)	0.203 (1.00)	0.00818 (1.00)	0.0119 (1.00)	0.164 (1.00)	0.277 (1.00)	0.584 (1.00)		0.163 (1.00)
8p loss	5 (4%)	134	0.000405 (0.225)	0.205 (1.00)	0.0309 (1.00)	0.504 (1.00)		0.0111 (1.00)	0.162 (1.00)		0.201 (1.00)
9q loss	20 (14%)	119	0.0168 (1.00)	0.904 (1.00)	0.00187 (1.00)	0.00015 (0.0845)	0.127 (1.00)	0.305 (1.00)	0.0624 (1.00)	0.385 (1.00)	0.593 (1.00)
11p loss	10 (7%)	129	0.000286 (0.16)	0.111 (1.00)	0.0576 (1.00)	0.109 (1.00)	0.164 (1.00)	0.594 (1.00)	0.169 (1.00)		0.367 (1.00)
15q loss	15 (11%)	124	0.000154 (0.0866)	0.135 (1.00)	0.0766 (1.00)	0.026 (1.00)	0.217 (1.00)	0.0814 (1.00)	0.385 (1.00)	0.724 (1.00)	1 (1.00)
16p loss	4 (3%)	135	1.51e-05 (0.00856)	0.663 (1.00)	0.199 (1.00)	0.145 (1.00)		1 (1.00)	0.0823 (1.00)		1 (1.00)
16q loss	4 (3%)	135	1.51e-05 (0.00856)	0.663 (1.00)	0.199 (1.00)	0.145 (1.00)		1 (1.00)	0.0823 (1.00)		1 (1.00)
17p loss	8 (6%)	131	2.22e-16 (1.28e-13)	0.731 (1.00)	0.000768 (0.419)	0.0125 (1.00)	0.00791 (1.00)	0.0408 (1.00)	0.0542 (1.00)	0.472 (1.00)	1 (1.00)
22q loss	34 (24%)	105	0.37 (1.00)	0.629 (1.00)	0.000658 (0.361)	0.000363 (0.202)	0.147 (1.00)	0.237 (1.00)	0.0184 (1.00)	0.433 (1.00)	1 (1.00)
2p gain	24 (17%)	115	0.0751 (1.00)	0.533 (1.00)	0.0675 (1.00)	0.522 (1.00)	0.203 (1.00)	0.00311 (1.00)	0.465 (1.00)	0.362 (1.00)	0.276 (1.00)
2q gain	26 (19%)	113	0.159 (1.00)	0.998 (1.00)	0.0169 (1.00)	0.567 (1.00)	0.127 (1.00)	0.00508 (1.00)	0.347 (1.00)	0.35 (1.00)	0.312 (1.00)
3p gain	39 (28%)	100	0.226 (1.00)	0.555 (1.00)	0.065 (1.00)	0.0271 (1.00)	1 (1.00)	0.345 (1.00)	0.307 (1.00)	0.0914 (1.00)	0.673 (1.00)
3q gain	45 (32%)	94	0.102 (1.00)	0.421 (1.00)	0.1 (1.00)	0.0506 (1.00)	1 (1.00)	0.14 (1.00)	0.173 (1.00)	0.283 (1.00)	1 (1.00)	0.379 (1.00)
4p gain	6 (4%)	133	0.0147 (1.00)	0.00417 (1.00)	0.0706 (1.00)	0.716 (1.00)	0.53 (1.00)	0.188 (1.00)	0.668 (1.00)		1 (1.00)
4q gain	5 (4%)	134	0.311 (1.00)	0.0137 (1.00)	0.301 (1.00)	0.654 (1.00)	0.284 (1.00)	0.688 (1.00)	1 (1.00)		1 (1.00)
5p gain	21 (15%)	118	0.395 (1.00)	0.631 (1.00)	0.216 (1.00)	0.229 (1.00)	0.862 (1.00)	0.405 (1.00)	0.61 (1.00)	0.336 (1.00)	0.591 (1.00)
5q gain	20 (14%)	119	0.116 (1.00)	0.968 (1.00)	0.306 (1.00)	0.337 (1.00)	1 (1.00)	0.385 (1.00)	0.793 (1.00)	0.336 (1.00)	0.593 (1.00)
6p gain	5 (4%)	134	0.053 (1.00)	0.679 (1.00)	0.0426 (1.00)	0.0407 (1.00)	0.434 (1.00)	0.00272 (1.00)	0.322 (1.00)		0.201 (1.00)
7p gain	81 (58%)	58	0.0927 (1.00)	0.445 (1.00)	0.00581 (1.00)	0.0167 (1.00)	1 (1.00)	0.139 (1.00)	0.133 (1.00)	0.189 (1.00)	0.401 (1.00)
7q gain	82 (59%)	57	0.084 (1.00)	0.376 (1.00)	0.0033 (1.00)	0.0111 (1.00)	1 (1.00)	0.183 (1.00)	0.0915 (1.00)	0.189 (1.00)	0.401 (1.00)
8p gain	10 (7%)	129	0.033 (1.00)	0.909 (1.00)	0.363 (1.00)	0.269 (1.00)	0.441 (1.00)	0.846 (1.00)	0.49 (1.00)		1 (1.00)
9p gain	3 (2%)	136	0.0855 (1.00)	0.938 (1.00)	0.0853 (1.00)	0.0923 (1.00)		0.663 (1.00)	1 (1.00)		1 (1.00)
10p gain	5 (4%)	134	0.509 (1.00)	0.942 (1.00)	0.235 (1.00)	0.504 (1.00)		0.373 (1.00)	1 (1.00)		1 (1.00)
10q gain	5 (4%)	134	0.509 (1.00)	0.942 (1.00)	0.235 (1.00)	0.504 (1.00)		0.373 (1.00)	1 (1.00)		1 (1.00)
11p gain	6 (4%)	133	0.0256 (1.00)	0.297 (1.00)	0.0426 (1.00)	0.0457 (1.00)	0.721 (1.00)	0.0109 (1.00)	1 (1.00)		1 (1.00)
11q gain	4 (3%)	135	0.766 (1.00)	0.126 (1.00)	0.178 (1.00)	0.0602 (1.00)	1 (1.00)	0.137 (1.00)	0.584 (1.00)		1 (1.00)
12p gain	55 (40%)	84	0.447 (1.00)	0.708 (1.00)	0.741 (1.00)	0.656 (1.00)	0.493 (1.00)	0.102 (1.00)	0.0918 (1.00)	0.736 (1.00)	0.0358 (1.00)	0.352 (1.00)
12q gain	55 (40%)	84	0.447 (1.00)	0.708 (1.00)	0.741 (1.00)	0.656 (1.00)	0.493 (1.00)	0.102 (1.00)	0.0918 (1.00)	0.736 (1.00)	0.0358 (1.00)	0.352 (1.00)
13q gain	15 (11%)	124	0.492 (1.00)	0.145 (1.00)	0.602 (1.00)	0.666 (1.00)		1 (1.00)	0.772 (1.00)	0.182 (1.00)	0.127 (1.00)
14q gain	3 (2%)	136			0.0573 (1.00)	0.0365 (1.00)		0.663 (1.00)	0.217 (1.00)		1 (1.00)
16p gain	72 (52%)	67	0.937 (1.00)	0.355 (1.00)	0.756 (1.00)	1 (1.00)	1 (1.00)	0.224 (1.00)	0.00544 (1.00)	0.488 (1.00)	0.429 (1.00)
16q gain	70 (50%)	69	0.277 (1.00)	0.537 (1.00)	0.63 (1.00)	0.757 (1.00)	0.804 (1.00)	0.0448 (1.00)	0.0273 (1.00)	0.327 (1.00)	0.441 (1.00)
18p gain	7 (5%)	132	0.902 (1.00)	0.576 (1.00)	0.467 (1.00)	0.529 (1.00)		0.0924 (1.00)	1 (1.00)	0.542 (1.00)	0.271 (1.00)
18q gain	5 (4%)	134	0.345 (1.00)	0.943 (1.00)	0.724 (1.00)	0.654 (1.00)		0.469 (1.00)	1 (1.00)		0.201 (1.00)
19p gain	3 (2%)	136	0.64 (1.00)	0.337 (1.00)	0.531 (1.00)	0.495 (1.00)	1 (1.00)	0.663 (1.00)	1 (1.00)		1 (1.00)
19q gain	3 (2%)	136	0.64 (1.00)	0.337 (1.00)	0.531 (1.00)	0.495 (1.00)	1 (1.00)	0.663 (1.00)	1 (1.00)		1 (1.00)
20p gain	46 (33%)	93	0.932 (1.00)	0.0655 (1.00)	0.461 (1.00)	0.444 (1.00)	0.876 (1.00)	0.853 (1.00)	1 (1.00)	0.402 (1.00)	0.093 (1.00)
20q gain	48 (35%)	91	0.604 (1.00)	0.0497 (1.00)	0.214 (1.00)	0.243 (1.00)	0.771 (1.00)	0.95 (1.00)	0.848 (1.00)	0.402 (1.00)	0.182 (1.00)
21q gain	6 (4%)	133	0.766 (1.00)	0.0268 (1.00)	0.551 (1.00)	0.25 (1.00)		0.505 (1.00)	0.668 (1.00)		1 (1.00)
xq gain	41 (29%)	98	0.927 (1.00)	0.885 (1.00)	0.05 (1.00)	0.043 (1.00)	1 (1.00)	0.353 (1.00)	0.0418 (1.00)	0.134 (1.00)	0.67 (1.00)	0.379 (1.00)
1p loss	16 (12%)	123	0.664 (1.00)	0.979 (1.00)	0.452 (1.00)	0.639 (1.00)	0.53 (1.00)	0.564 (1.00)	1 (1.00)	0.341 (1.00)	1 (1.00)
1q loss	10 (7%)	129	0.507 (1.00)	0.386 (1.00)	0.304 (1.00)	0.645 (1.00)		0.47 (1.00)	1 (1.00)	0.341 (1.00)	1 (1.00)
3p loss	11 (8%)	128	0.00962 (1.00)	0.147 (1.00)	0.000565 (0.312)	0.000711 (0.39)	0.864 (1.00)	0.0989 (1.00)	1 (1.00)		0.396 (1.00)
4p loss	11 (8%)	128	0.162 (1.00)	0.0519 (1.00)	0.00778 (1.00)	0.0025 (1.00)	0.0279 (1.00)	0.46 (1.00)	0.00314 (1.00)		1 (1.00)
4q loss	12 (9%)	127	0.769 (1.00)	0.231 (1.00)	0.0261 (1.00)	0.0242 (1.00)	0.267 (1.00)	0.114 (1.00)	0.044 (1.00)	0.724 (1.00)	1 (1.00)
5p loss	5 (4%)	134	0.00118 (0.641)	0.261 (1.00)	0.0436 (1.00)	0.0407 (1.00)	0.0624 (1.00)	0.277 (1.00)	0.162 (1.00)		1 (1.00)
5q loss	5 (4%)	134	0.0855 (1.00)	0.113 (1.00)	0.199 (1.00)	0.0407 (1.00)	0.0394 (1.00)	0.277 (1.00)	0.162 (1.00)		1 (1.00)
6p loss	11 (8%)	128	0.00679 (1.00)	0.405 (1.00)	0.0404 (1.00)	0.0308 (1.00)	0.108 (1.00)	1 (1.00)	0.0881 (1.00)	0.193 (1.00)	1 (1.00)
6q loss	13 (9%)	126	0.0651 (1.00)	0.947 (1.00)	0.0445 (1.00)	0.00544 (1.00)	0.136 (1.00)	0.542 (1.00)	0.0216 (1.00)	0.363 (1.00)	1 (1.00)
8q loss	3 (2%)	136	0.00974 (1.00)	0.641 (1.00)	0.109 (1.00)	0.22 (1.00)		0.137 (1.00)	0.217 (1.00)		1 (1.00)
10p loss	9 (6%)	130	0.204 (1.00)	0.638 (1.00)	0.0384 (1.00)	0.0282 (1.00)	0.0806 (1.00)	0.0993 (1.00)	0.453 (1.00)	0.403 (1.00)	1 (1.00)
10q loss	8 (6%)	131	0.151 (1.00)	0.456 (1.00)	0.0384 (1.00)	0.02 (1.00)	0.0806 (1.00)	0.0993 (1.00)	0.698 (1.00)	0.403 (1.00)	1 (1.00)
13q loss	12 (9%)	127	0.000764 (0.418)	0.216 (1.00)	0.0147 (1.00)	0.0118 (1.00)	0.0305 (1.00)	0.415 (1.00)	0.0011 (0.596)	0.341 (1.00)	1 (1.00)
14q loss	27 (19%)	112	0.206 (1.00)	0.861 (1.00)	0.00988 (1.00)	0.0893 (1.00)	0.105 (1.00)	0.134 (1.00)	0.243 (1.00)	0.356 (1.00)	1 (1.00)
18p loss	22 (16%)	117	0.00967 (1.00)	0.511 (1.00)	0.00454 (1.00)	0.00132 (0.714)	0.127 (1.00)	0.0821 (1.00)	0.613 (1.00)	0.765 (1.00)	1 (1.00)
18q loss	23 (17%)	116	0.00967 (1.00)	0.511 (1.00)	0.00196 (1.00)	0.00064 (0.352)	0.127 (1.00)	0.0751 (1.00)	0.327 (1.00)	0.765 (1.00)	1 (1.00)
19p loss	9 (6%)	130	0.224 (1.00)	0.606 (1.00)	0.0858 (1.00)	0.0282 (1.00)	0.171 (1.00)	0.606 (1.00)	0.453 (1.00)	0.741 (1.00)	1 (1.00)
19q loss	8 (6%)	131	0.109 (1.00)	0.909 (1.00)	0.0352 (1.00)	0.00766 (1.00)	0.171 (1.00)	0.413 (1.00)	0.243 (1.00)	0.741 (1.00)	1 (1.00)
21q loss	27 (19%)	112	0.979 (1.00)	0.695 (1.00)	0.00817 (1.00)	0.00686 (1.00)	0.379 (1.00)	0.136 (1.00)	0.243 (1.00)	0.891 (1.00)	1 (1.00)	0.408 (1.00)
xq loss	16 (12%)	123	0.00108 (0.59)	0.291 (1.00)	0.0194 (1.00)	0.0042 (1.00)	0.0823 (1.00)	0.179 (1.00)	0.0842 (1.00)	0.478 (1.00)	0.142 (1.00)

'1p gain' versus 'Time to Death'

P value = 6.27e-11 (logrank test), Q value = 3.6e-08

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

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
1P GAIN MUTATED	3	1	2.0 - 7.9 (3.7)
1P GAIN WILD-TYPE	124	14	0.0 - 194.8 (14.9)

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

'1q gain' versus 'Time to Death'

P value = 3.7e-06 (logrank test), Q value = 0.0021

Table S2. Gene #2: '1q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
1Q GAIN MUTATED	10	3	0.7 - 30.3 (5.8)
1Q GAIN WILD-TYPE	117	12	0.0 - 194.8 (15.9)

Figure S2. Get High-res Image Gene #2: '1q gain' versus Clinical Feature #1: 'Time to Death'

'1q gain' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000163 (Fisher's exact test), Q value = 0.091

Table S3. Gene #2: '1q gain' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE II	STAGE III	STAGE IV
ALL	77	11	31	10
1Q GAIN MUTATED	1	0	7	3
1Q GAIN WILD-TYPE	76	11	24	7

Figure S3. Get High-res Image Gene #2: '1q gain' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'1q gain' versus 'PATHOLOGY.T.STAGE'

P value = 6.89e-05 (Fisher's exact test), Q value = 0.039

Table S4. Gene #2: '1q gain' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
1Q GAIN MUTATED	1	0	10
1Q GAIN WILD-TYPE	81	17	30

Figure S4. Get High-res Image Gene #2: '1q gain' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'6q gain' versus 'Time to Death'

P value = 2.7e-06 (logrank test), Q value = 0.0015

Table S5. Gene #12: '6q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
6Q GAIN MUTATED	3	2	7.9 - 13.6 (9.6)
6Q GAIN WILD-TYPE	124	13	0.0 - 194.8 (14.9)

Figure S5. Get High-res Image Gene #12: '6q gain' versus Clinical Feature #1: 'Time to Death'

'8q gain' versus 'Time to Death'

P value = 1.27e-05 (logrank test), Q value = 0.0072

Table S6. Gene #16: '8q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
8Q GAIN MUTATED	12	4	0.2 - 43.2 (6.8)
8Q GAIN WILD-TYPE	115	11	0.0 - 194.8 (15.9)

Figure S6. Get High-res Image Gene #16: '8q gain' versus Clinical Feature #1: 'Time to Death'

'17p gain' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000111 (Fisher's exact test), Q value = 0.063

Table S7. Gene #28: '17p gain' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE II	STAGE III	STAGE IV
ALL	77	11	31	10
17P GAIN MUTATED	55	6	10	2
17P GAIN WILD-TYPE	22	5	21	8

Figure S7. Get High-res Image Gene #28: '17p gain' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'17p gain' versus 'PATHOLOGY.T.STAGE'

P value = 0.000432 (Fisher's exact test), Q value = 0.24

Table S8. Gene #28: '17p gain' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
17P GAIN MUTATED	57	11	13
17P GAIN WILD-TYPE	25	6	27

Figure S8. Get High-res Image Gene #28: '17p gain' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'17p gain' versus 'PATHOLOGY.M.STAGE'

P value = 2.33e-05 (Fisher's exact test), Q value = 0.013

Table S9. Gene #28: '17p gain' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

nPatients	M0	M1	MX
ALL	58	6	62
17P GAIN MUTATED	23	1	47
17P GAIN WILD-TYPE	35	5	15

Figure S9. Get High-res Image Gene #28: '17p gain' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

'17q gain' versus 'PATHOLOGY.M.STAGE'

P value = 0.000309 (Fisher's exact test), Q value = 0.17

Table S10. Gene #29: '17q gain' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

nPatients	M0	M1	MX
ALL	58	6	62
17Q GAIN MUTATED	29	3	51
17Q GAIN WILD-TYPE	29	3	11

Figure S10. Get High-res Image Gene #29: '17q gain' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

'3q loss' versus 'Time to Death'

P value = 1.54e-13 (logrank test), Q value = 8.9e-11

Table S11. Gene #41: '3q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
3Q LOSS MUTATED	4	3	3.7 - 21.6 (6.4)
3Q LOSS WILD-TYPE	123	12	0.0 - 194.8 (14.6)

Figure S11. Get High-res Image Gene #41: '3q loss' versus Clinical Feature #1: 'Time to Death'

'8p loss' versus 'Time to Death'

P value = 0.000405 (logrank test), Q value = 0.22

Table S12. Gene #48: '8p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
8P LOSS MUTATED	5	2	7.3 - 11.6 (10.1)
8P LOSS WILD-TYPE	122	13	0.0 - 194.8 (15.5)

Figure S12. Get High-res Image Gene #48: '8p loss' versus Clinical Feature #1: 'Time to Death'

'9p loss' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000155 (Fisher's exact test), Q value = 0.087

Table S13. Gene #50: '9p loss' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE II	STAGE III	STAGE IV
ALL	77	11	31	10
9P LOSS MUTATED	4	0	8	5
9P LOSS WILD-TYPE	73	11	23	5

Figure S13. Get High-res Image Gene #50: '9p loss' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'9p loss' versus 'PATHOLOGY.T.STAGE'

P value = 0.000215 (Fisher's exact test), Q value = 0.12

Table S14. Gene #50: '9p loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
9P LOSS MUTATED	4	2	13
9P LOSS WILD-TYPE	78	15	27

Figure S14. Get High-res Image Gene #50: '9p loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'9q loss' versus 'PATHOLOGY.T.STAGE'

P value = 0.00015 (Fisher's exact test), Q value = 0.085

Table S15. Gene #51: '9q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
9Q LOSS MUTATED	5	1	14
9Q LOSS WILD-TYPE	77	16	26

Figure S15. Get High-res Image Gene #51: '9q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'11p loss' versus 'Time to Death'

P value = 0.000286 (logrank test), Q value = 0.16

Table S16. Gene #54: '11p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
11P LOSS MUTATED	9	3	0.7 - 34.5 (8.8)
11P LOSS WILD-TYPE	118	12	0.0 - 194.8 (14.6)

Figure S16. Get High-res Image Gene #54: '11p loss' versus Clinical Feature #1: 'Time to Death'

'11q loss' versus 'Time to Death'

P value = 1.31e-05 (logrank test), Q value = 0.0074

Table S17. Gene #55: '11q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
11Q LOSS MUTATED	12	5	2.0 - 123.6 (9.9)
11Q LOSS WILD-TYPE	115	10	0.0 - 194.8 (15.1)

Figure S17. Get High-res Image Gene #55: '11q loss' versus Clinical Feature #1: 'Time to Death'

'11q loss' versus 'PATHOLOGY.T.STAGE'

P value = 0.000419 (Fisher's exact test), Q value = 0.23

Table S18. Gene #55: '11q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
11Q LOSS MUTATED	2	1	10
11Q LOSS WILD-TYPE	80	16	30

Figure S18. Get High-res Image Gene #55: '11q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'15q loss' versus 'Time to Death'

P value = 0.000154 (logrank test), Q value = 0.087

Table S19. Gene #58: '15q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
15Q LOSS MUTATED	14	4	0.1 - 34.8 (10.5)
15Q LOSS WILD-TYPE	113	11	0.0 - 194.8 (14.6)

Figure S19. Get High-res Image Gene #58: '15q loss' versus Clinical Feature #1: 'Time to Death'

'16p loss' versus 'Time to Death'

P value = 1.51e-05 (logrank test), Q value = 0.0086

Table S20. Gene #59: '16p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
16P LOSS MUTATED	3	2	0.7 - 21.6 (11.1)
16P LOSS WILD-TYPE	124	13	0.0 - 194.8 (14.6)

Figure S20. Get High-res Image Gene #59: '16p loss' versus Clinical Feature #1: 'Time to Death'

'16q loss' versus 'Time to Death'

P value = 1.51e-05 (logrank test), Q value = 0.0086

Table S21. Gene #60: '16q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
16Q LOSS MUTATED	3	2	0.7 - 21.6 (11.1)
16Q LOSS WILD-TYPE	124	13	0.0 - 194.8 (14.6)

Figure S21. Get High-res Image Gene #60: '16q loss' versus Clinical Feature #1: 'Time to Death'

'17p loss' versus 'Time to Death'

P value = 2.22e-16 (logrank test), Q value = 1.3e-13

Table S22. Gene #61: '17p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	127	15	0.0 - 194.8 (14.6)
17P LOSS MUTATED	6	4	0.2 - 11.3 (6.8)
17P LOSS WILD-TYPE	121	11	0.0 - 194.8 (15.9)

Figure S22. Get High-res Image Gene #61: '17p loss' versus Clinical Feature #1: 'Time to Death'

'22q loss' versus 'PATHOLOGY.T.STAGE'

P value = 0.000363 (Fisher's exact test), Q value = 0.2

Table S23. Gene #67: '22q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	82	17	40
22Q LOSS MUTATED	12	3	19
22Q LOSS WILD-TYPE	70	14	21

Figure S23. Get High-res Image Gene #67: '22q loss' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Clinical data file = KIRP-TP.merged_data.txt
Number of patients = 139
Number of significantly arm-level cnvs = 68
Number of selected clinical features = 11
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

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] 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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