(primary solid tumor cohort)
This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between copy number variation 79 arm-level results and 5 clinical features across 544 patients, 10 significant findings detected with Q value < 0.25.
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6p gain cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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6q gain cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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7p gain cnv correlated to 'AGE'.
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7q gain cnv correlated to 'AGE'.
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10p gain cnv correlated to 'AGE' and 'KARNOFSKY.PERFORMANCE.SCORE'.
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20p gain cnv correlated to 'AGE'.
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10p loss cnv correlated to 'Time to Death' and 'AGE'.
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10q loss cnv correlated to 'AGE'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 79 arm-level results and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 10 significant findings detected.
Clinical Features |
Time to Death |
AGE | GENDER |
KARNOFSKY PERFORMANCE SCORE |
RADIATIONS RADIATION REGIMENINDICATION |
||
nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | |
10p gain | 11 (2%) | 533 |
0.00302 (1.00) |
9.55e-05 (0.0371) |
0.0296 (1.00) |
0.000254 (0.098) |
1 (1.00) |
10p loss | 426 (78%) | 118 |
0.000152 (0.0586) |
1.26e-09 (4.92e-07) |
0.395 (1.00) |
0.358 (1.00) |
0.316 (1.00) |
6p gain | 7 (1%) | 537 |
0.1 (1.00) |
0.0989 (1.00) |
1 (1.00) |
0.000254 (0.098) |
0.438 (1.00) |
6q gain | 9 (2%) | 535 |
0.134 (1.00) |
0.0449 (1.00) |
0.745 (1.00) |
0.000254 (0.098) |
0.725 (1.00) |
7p gain | 423 (78%) | 121 |
0.00488 (1.00) |
5.79e-06 (0.00226) |
1 (1.00) |
0.53 (1.00) |
0.0976 (1.00) |
7q gain | 427 (78%) | 117 |
0.00601 (1.00) |
7.78e-06 (0.00303) |
0.594 (1.00) |
0.584 (1.00) |
0.148 (1.00) |
20p gain | 174 (32%) | 370 |
0.888 (1.00) |
0.000315 (0.121) |
0.707 (1.00) |
0.371 (1.00) |
0.279 (1.00) |
10q loss | 439 (81%) | 105 |
0.00068 (0.259) |
2.4e-07 (9.39e-05) |
0.58 (1.00) |
0.0968 (1.00) |
0.562 (1.00) |
1p gain | 38 (7%) | 506 |
0.607 (1.00) |
0.617 (1.00) |
0.606 (1.00) |
0.868 (1.00) |
0.476 (1.00) |
1q gain | 43 (8%) | 501 |
0.987 (1.00) |
0.503 (1.00) |
1 (1.00) |
0.979 (1.00) |
0.612 (1.00) |
2p gain | 18 (3%) | 526 |
0.577 (1.00) |
0.196 (1.00) |
0.219 (1.00) |
0.301 (1.00) |
0.448 (1.00) |
2q gain | 16 (3%) | 528 |
0.772 (1.00) |
0.501 (1.00) |
0.44 (1.00) |
0.737 (1.00) |
0.29 (1.00) |
3p gain | 30 (6%) | 514 |
0.124 (1.00) |
0.532 (1.00) |
1 (1.00) |
0.837 (1.00) |
0.322 (1.00) |
3q gain | 30 (6%) | 514 |
0.126 (1.00) |
0.437 (1.00) |
1 (1.00) |
0.892 (1.00) |
0.322 (1.00) |
4p gain | 15 (3%) | 529 |
0.0811 (1.00) |
0.0695 (1.00) |
0.791 (1.00) |
0.127 (1.00) |
0.407 (1.00) |
4q gain | 14 (3%) | 530 |
0.031 (1.00) |
0.342 (1.00) |
0.789 (1.00) |
0.146 (1.00) |
0.245 (1.00) |
5p gain | 28 (5%) | 516 |
0.916 (1.00) |
0.206 (1.00) |
0.697 (1.00) |
0.0435 (1.00) |
0.144 (1.00) |
5q gain | 21 (4%) | 523 |
0.711 (1.00) |
0.52 (1.00) |
0.497 (1.00) |
0.301 (1.00) |
0.238 (1.00) |
8p gain | 26 (5%) | 518 |
0.765 (1.00) |
0.553 (1.00) |
0.539 (1.00) |
0.402 (1.00) |
0.831 (1.00) |
8q gain | 31 (6%) | 513 |
0.833 (1.00) |
0.205 (1.00) |
0.345 (1.00) |
0.389 (1.00) |
1 (1.00) |
9p gain | 17 (3%) | 527 |
0.24 (1.00) |
0.0378 (1.00) |
0.314 (1.00) |
0.00622 (1.00) |
0.6 (1.00) |
9q gain | 32 (6%) | 512 |
0.0339 (1.00) |
0.0482 (1.00) |
0.0612 (1.00) |
0.0256 (1.00) |
0.439 (1.00) |
11p gain | 4 (1%) | 540 |
0.568 (1.00) |
0.383 (1.00) |
0.65 (1.00) |
0.841 (1.00) |
1 (1.00) |
11q gain | 7 (1%) | 537 |
0.152 (1.00) |
0.211 (1.00) |
0.254 (1.00) |
0.0913 (1.00) |
0.438 (1.00) |
12p gain | 40 (7%) | 504 |
0.928 (1.00) |
0.15 (1.00) |
1 (1.00) |
0.93 (1.00) |
0.6 (1.00) |
12q gain | 30 (6%) | 514 |
0.498 (1.00) |
0.667 (1.00) |
0.445 (1.00) |
0.554 (1.00) |
0.322 (1.00) |
13q gain | 3 (1%) | 541 |
0.991 (1.00) |
0.104 (1.00) |
0.0612 (1.00) |
0.0329 (1.00) |
|
14q gain | 6 (1%) | 538 |
0.0771 (1.00) |
0.816 (1.00) |
0.685 (1.00) |
0.514 (1.00) |
1 (1.00) |
15q gain | 5 (1%) | 539 |
0.427 (1.00) |
0.19 (1.00) |
1 (1.00) |
0.292 (1.00) |
0.659 (1.00) |
16p gain | 17 (3%) | 527 |
0.044 (1.00) |
0.0244 (1.00) |
0.13 (1.00) |
0.71 (1.00) |
0.11 (1.00) |
16q gain | 17 (3%) | 527 |
0.0449 (1.00) |
0.0676 (1.00) |
0.0422 (1.00) |
0.971 (1.00) |
0.291 (1.00) |
17p gain | 10 (2%) | 534 |
0.0168 (1.00) |
0.0354 (1.00) |
0.747 (1.00) |
0.0913 (1.00) |
1 (1.00) |
17q gain | 18 (3%) | 526 |
0.0339 (1.00) |
0.123 (1.00) |
1 (1.00) |
0.0318 (1.00) |
0.801 (1.00) |
18p gain | 26 (5%) | 518 |
0.848 (1.00) |
0.929 (1.00) |
1 (1.00) |
0.0964 (1.00) |
0.831 (1.00) |
18q gain | 28 (5%) | 516 |
0.82 (1.00) |
0.938 (1.00) |
0.697 (1.00) |
0.301 (1.00) |
0.836 (1.00) |
19p gain | 170 (31%) | 374 |
0.197 (1.00) |
0.452 (1.00) |
0.85 (1.00) |
0.795 (1.00) |
0.277 (1.00) |
19q gain | 147 (27%) | 397 |
0.141 (1.00) |
0.246 (1.00) |
0.694 (1.00) |
0.773 (1.00) |
0.837 (1.00) |
20q gain | 172 (32%) | 372 |
0.651 (1.00) |
0.000657 (0.251) |
0.573 (1.00) |
0.406 (1.00) |
0.167 (1.00) |
21q gain | 32 (6%) | 512 |
0.137 (1.00) |
0.856 (1.00) |
1 (1.00) |
0.634 (1.00) |
0.439 (1.00) |
22q gain | 11 (2%) | 533 |
0.97 (1.00) |
0.391 (1.00) |
1 (1.00) |
0.968 (1.00) |
0.516 (1.00) |
Xq gain | 3 (1%) | 541 |
0.128 (1.00) |
0.593 (1.00) |
1 (1.00) |
1 (1.00) |
|
1p loss | 5 (1%) | 539 |
0.0316 (1.00) |
0.707 (1.00) |
0.653 (1.00) |
0.868 (1.00) |
1 (1.00) |
1q loss | 4 (1%) | 540 |
0.721 (1.00) |
0.0658 (1.00) |
0.65 (1.00) |
0.0873 (1.00) |
1 (1.00) |
2p loss | 10 (2%) | 534 |
0.179 (1.00) |
0.516 (1.00) |
0.204 (1.00) |
0.76 (1.00) |
1 (1.00) |
2q loss | 9 (2%) | 535 |
0.235 (1.00) |
0.743 (1.00) |
0.328 (1.00) |
0.76 (1.00) |
0.725 (1.00) |
3p loss | 22 (4%) | 522 |
0.293 (1.00) |
0.0224 (1.00) |
1 (1.00) |
0.846 (1.00) |
0.0184 (1.00) |
3q loss | 16 (3%) | 528 |
0.774 (1.00) |
0.231 (1.00) |
0.44 (1.00) |
0.708 (1.00) |
0.29 (1.00) |
4p loss | 25 (5%) | 519 |
0.14 (1.00) |
0.297 (1.00) |
0.142 (1.00) |
0.825 (1.00) |
0.083 (1.00) |
4q loss | 24 (4%) | 520 |
0.21 (1.00) |
0.229 (1.00) |
0.67 (1.00) |
0.167 (1.00) |
0.51 (1.00) |
5p loss | 21 (4%) | 523 |
0.0545 (1.00) |
0.277 (1.00) |
0.821 (1.00) |
0.503 (1.00) |
0.238 (1.00) |
5q loss | 20 (4%) | 524 |
0.0597 (1.00) |
0.294 (1.00) |
0.645 (1.00) |
0.786 (1.00) |
0.33 (1.00) |
6p loss | 47 (9%) | 497 |
0.008 (1.00) |
0.761 (1.00) |
0.878 (1.00) |
0.711 (1.00) |
0.747 (1.00) |
6q loss | 79 (15%) | 465 |
0.277 (1.00) |
0.656 (1.00) |
0.534 (1.00) |
0.581 (1.00) |
0.897 (1.00) |
7p loss | 5 (1%) | 539 |
0.514 (1.00) |
0.658 (1.00) |
1 (1.00) |
0.61 (1.00) |
1 (1.00) |
7q loss | 4 (1%) | 540 |
0.617 (1.00) |
0.362 (1.00) |
1 (1.00) |
1 (1.00) |
|
8p loss | 34 (6%) | 510 |
0.972 (1.00) |
0.422 (1.00) |
0.209 (1.00) |
0.541 (1.00) |
0.0233 (1.00) |
8q loss | 21 (4%) | 523 |
0.995 (1.00) |
0.435 (1.00) |
0.497 (1.00) |
0.133 (1.00) |
0.00375 (1.00) |
9p loss | 160 (29%) | 384 |
0.748 (1.00) |
0.41 (1.00) |
0.773 (1.00) |
0.427 (1.00) |
0.42 (1.00) |
9q loss | 63 (12%) | 481 |
0.396 (1.00) |
0.575 (1.00) |
0.0139 (1.00) |
0.384 (1.00) |
0.776 (1.00) |
11p loss | 64 (12%) | 480 |
0.312 (1.00) |
0.222 (1.00) |
0.221 (1.00) |
0.89 (1.00) |
0.254 (1.00) |
11q loss | 55 (10%) | 489 |
0.96 (1.00) |
0.814 (1.00) |
0.772 (1.00) |
0.934 (1.00) |
0.0146 (1.00) |
12p loss | 37 (7%) | 507 |
0.598 (1.00) |
0.913 (1.00) |
0.864 (1.00) |
0.89 (1.00) |
0.586 (1.00) |
12q loss | 34 (6%) | 510 |
0.578 (1.00) |
0.992 (1.00) |
1 (1.00) |
0.61 (1.00) |
0.706 (1.00) |
13q loss | 134 (25%) | 410 |
0.978 (1.00) |
0.39 (1.00) |
0.417 (1.00) |
0.538 (1.00) |
0.749 (1.00) |
14q loss | 120 (22%) | 424 |
0.995 (1.00) |
0.891 (1.00) |
0.752 (1.00) |
0.769 (1.00) |
1 (1.00) |
15q loss | 62 (11%) | 482 |
0.433 (1.00) |
0.181 (1.00) |
0.132 (1.00) |
0.486 (1.00) |
0.25 (1.00) |
16p loss | 23 (4%) | 521 |
0.155 (1.00) |
0.119 (1.00) |
0.514 (1.00) |
0.0929 (1.00) |
1 (1.00) |
16q loss | 40 (7%) | 504 |
0.0807 (1.00) |
0.927 (1.00) |
1 (1.00) |
0.204 (1.00) |
1 (1.00) |
17p loss | 35 (6%) | 509 |
0.466 (1.00) |
0.285 (1.00) |
0.722 (1.00) |
0.643 (1.00) |
1 (1.00) |
17q loss | 19 (3%) | 525 |
0.936 (1.00) |
0.315 (1.00) |
0.815 (1.00) |
0.62 (1.00) |
0.626 (1.00) |
18p loss | 43 (8%) | 501 |
0.302 (1.00) |
0.768 (1.00) |
0.871 (1.00) |
0.625 (1.00) |
0.612 (1.00) |
18q loss | 38 (7%) | 506 |
0.384 (1.00) |
0.432 (1.00) |
0.497 (1.00) |
0.349 (1.00) |
0.589 (1.00) |
19p loss | 13 (2%) | 531 |
0.635 (1.00) |
0.187 (1.00) |
0.775 (1.00) |
0.58 (1.00) |
1 (1.00) |
19q loss | 18 (3%) | 526 |
0.194 (1.00) |
0.667 (1.00) |
1 (1.00) |
0.276 (1.00) |
0.801 (1.00) |
20p loss | 11 (2%) | 533 |
0.456 (1.00) |
0.14 (1.00) |
0.357 (1.00) |
0.7 (1.00) |
0.752 (1.00) |
20q loss | 10 (2%) | 534 |
0.473 (1.00) |
0.468 (1.00) |
0.527 (1.00) |
0.612 (1.00) |
0.304 (1.00) |
21q loss | 25 (5%) | 519 |
0.849 (1.00) |
0.235 (1.00) |
0.212 (1.00) |
0.629 (1.00) |
0.666 (1.00) |
22q loss | 138 (25%) | 406 |
0.647 (1.00) |
0.0288 (1.00) |
0.764 (1.00) |
0.613 (1.00) |
1 (1.00) |
Xq loss | 11 (2%) | 533 |
0.23 (1.00) |
0.0255 (1.00) |
0.759 (1.00) |
0.914 (1.00) |
0.516 (1.00) |
P value = 0.000254 (t-test), Q value = 0.098
Table S1. Gene #11: '6p gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 409 | 77.3 (14.7) |
6P GAIN MUTATED | 4 | 80.0 (0.0) |
6P GAIN WILD-TYPE | 405 | 77.3 (14.8) |
Figure S1. Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
![](D11V4.png)
P value = 0.000254 (t-test), Q value = 0.098
Table S2. Gene #12: '6q gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 409 | 77.3 (14.7) |
6Q GAIN MUTATED | 5 | 80.0 (0.0) |
6Q GAIN WILD-TYPE | 404 | 77.3 (14.8) |
Figure S2. Get High-res Image Gene #12: '6q gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
![](D12V4.png)
P value = 5.79e-06 (t-test), Q value = 0.0023
Table S3. Gene #13: '7p gain mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
7P GAIN MUTATED | 423 | 59.7 (12.2) |
7P GAIN WILD-TYPE | 121 | 51.3 (18.5) |
Figure S3. Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #2: 'AGE'
![](D13V2.png)
P value = 7.78e-06 (t-test), Q value = 0.003
Table S4. Gene #14: '7q gain mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
7Q GAIN MUTATED | 427 | 59.7 (12.1) |
7Q GAIN WILD-TYPE | 117 | 51.1 (19.1) |
Figure S4. Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #2: 'AGE'
![](D14V2.png)
P value = 9.55e-05 (t-test), Q value = 0.037
Table S5. Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
10P GAIN MUTATED | 11 | 34.3 (12.9) |
10P GAIN WILD-TYPE | 533 | 58.3 (13.9) |
Figure S5. Get High-res Image Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'AGE'
![](D19V2.png)
P value = 0.000254 (t-test), Q value = 0.098
Table S6. Gene #19: '10p gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 409 | 77.3 (14.7) |
10P GAIN MUTATED | 11 | 80.0 (0.0) |
10P GAIN WILD-TYPE | 398 | 77.2 (14.9) |
Figure S6. Get High-res Image Gene #19: '10p gain mutation analysis' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
![](D19V4.png)
P value = 0.000315 (t-test), Q value = 0.12
Table S7. Gene #35: '20p gain mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
20P GAIN MUTATED | 174 | 60.9 (13.1) |
20P GAIN WILD-TYPE | 370 | 56.4 (14.6) |
Figure S7. Get High-res Image Gene #35: '20p gain mutation analysis' versus Clinical Feature #2: 'AGE'
![](D35V2.png)
P value = 0.000152 (logrank test), Q value = 0.059
Table S8. Gene #58: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 544 | 411 | 0.1 - 127.6 (9.6) |
10P LOSS MUTATED | 426 | 323 | 0.1 - 127.6 (9.3) |
10P LOSS WILD-TYPE | 118 | 88 | 0.2 - 108.8 (10.8) |
Figure S8. Get High-res Image Gene #58: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'
![](D58V1.png)
P value = 1.26e-09 (t-test), Q value = 4.9e-07
Table S9. Gene #58: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
10P LOSS MUTATED | 426 | 60.3 (11.8) |
10P LOSS WILD-TYPE | 118 | 48.8 (18.3) |
Figure S9. Get High-res Image Gene #58: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'
![](D58V2.png)
P value = 2.4e-07 (t-test), Q value = 9.4e-05
Table S10. Gene #59: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 544 | 57.8 (14.3) |
10Q LOSS MUTATED | 439 | 59.8 (12.4) |
10Q LOSS WILD-TYPE | 105 | 49.6 (18.2) |
Figure S10. Get High-res Image Gene #59: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'
![](D59V2.png)
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Mutation data file = broad_values_by_arm.mutsig.cluster.txt
-
Clinical data file = GBM-TP.clin.merged.picked.txt
-
Number of patients = 544
-
Number of significantly arm-level cnvs = 79
-
Number of selected clinical features = 5
-
Exclude genes that fewer than K tumors have mutations, K = 3
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
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
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
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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.