Brain Lower Grade Glioma: Correlation between copy number variations of arm-level result and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/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 45 arm-level results and 7 clinical features across 144 patients, 15 significant findings detected with Q value < 0.25.

- 1p gain cnv correlated to 'Time to Death'.

- 7q gain cnv correlated to 'AGE'.

- 19q gain cnv correlated to 'Time to Death'.

- 20p gain cnv correlated to 'Time to Death'.

- 20q gain cnv correlated to 'Time to Death'.

- 1p loss cnv correlated to 'HISTOLOGICAL.TYPE' and 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- 10p loss cnv correlated to 'Time to Death' and 'AGE'.

- 10q loss cnv correlated to 'Time to Death' and 'AGE'.

- 11q loss cnv correlated to 'Time to Death'.

- 19q loss cnv correlated to 'HISTOLOGICAL.TYPE' and 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- 22q loss cnv correlated to 'Time to Death'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 45 arm-level results and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 15 significant findings detected.

|  | Clinical Features | Time to Death | AGE | GENDER | KARNOFSKY PERFORMANCE SCORE | HISTOLOGICAL TYPE | RADIATIONS RADIATION REGIMENINDICATION | NEOADJUVANT THERAPY
| nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test
1p loss | 41 (28%) | 103 | 0.113 (1.00) | 0.0555 (1.00) | 0.71 (1.00) | 0.941 (1.00) | 2.28e-14 (6.83e-12) | 0.000133 (0.0385) | 1 (1.00)
10p loss | 22 (15%) | 122 | 7.96e-10 (2.36e-07) | 6.65e-06 (0.00196) | 0.252 (1.00) | 0.441 (1.00) | 0.0238 (1.00) | 0.481 (1.00) | 0.648 (1.00)
10q loss | 23 (16%) | 121 | 1.68e-09 (4.96e-07) | 3.26e-06 (0.000962) | 0.174 (1.00) | 0.473 (1.00) | 0.0119 (1.00) | 0.358 (1.00) | 0.501 (1.00)
19q loss | 48 (33%) | 96 | 0.118 (1.00) | 0.154 (1.00) | 1 (1.00) | 0.985 (1.00) | 9.12e-11 (2.72e-08) | 0.000628 (0.179) | 0.48 (1.00)
1p gain | 4 (3%) | 140 | 1.49e-05 (0.00436) | 0.0686 (1.00) | 0.315 (1.00) |  | 0.0169 (1.00) | 1 (1.00) | 0.363 (1.00)
7q gain | 38 (26%) | 106 | 0.0137 (1.00) | 0.000511 (0.147) | 0.57 (1.00) | 0.649 (1.00) | 0.288 (1.00) | 0.249 (1.00) | 0.573 (1.00)
19q gain | 6 (4%) | 138 | 0.000433 (0.125) | 0.0488 (1.00) | 0.236 (1.00) | 0.315 (1.00) | 0.382 (1.00) | 0.402 (1.00) | 0.681 (1.00)
20p gain | 13 (9%) | 131 | 4.87e-05 (0.0142) | 0.0574 (1.00) | 0.559 (1.00) | 0.607 (1.00) | 0.12 (1.00) | 0.562 (1.00) | 0.778 (1.00)
20q gain | 11 (8%) | 133 | 0.000109 (0.0317) | 0.111 (1.00) | 0.531 (1.00) | 0.458 (1.00) | 0.222 (1.00) | 1 (1.00) | 1 (1.00)
11q loss | 3 (2%) | 141 | 0.000864 (0.246) | 0.193 (1.00) | 0.578 (1.00) |  | 0.0548 (1.00) | 0.273 (1.00) | 0.617 (1.00)
22q loss | 10 (7%) | 134 | 0.000265 (0.0764) | 0.886 (1.00) | 0.745 (1.00) | 0.21 (1.00) | 0.00569 (1.00) | 0.524 (1.00) | 0.53 (1.00)
1q gain | 6 (4%) | 138 | 0.142 (1.00) | 0.0366 (1.00) | 0.403 (1.00) | 0.457 (1.00) | 0.282 (1.00) | 1 (1.00) | 0.438 (1.00)
7p gain | 28 (19%) | 116 | 0.01 (1.00) | 0.0289 (1.00) | 0.136 (1.00) | 0.745 (1.00) | 0.205 (1.00) | 0.0861 (1.00) | 0.834 (1.00)
8p gain | 12 (8%) | 132 | 0.701 (1.00) | 0.935 (1.00) | 0.555 (1.00) | 0.511 (1.00) | 0.473 (1.00) | 0.123 (1.00) | 0.241 (1.00)
8q gain | 15 (10%) | 129 | 0.933 (1.00) | 0.496 (1.00) | 1 (1.00) | 0.75 (1.00) | 0.193 (1.00) | 0.405 (1.00) | 0.181 (1.00)
9p gain | 3 (2%) | 141 | 0.125 (1.00) | 0.0178 (1.00) | 0.578 (1.00) |  | 0.344 (1.00) | 1 (1.00) | 0.617 (1.00)
9q gain | 3 (2%) | 141 | 0.0527 (1.00) | 0.23 (1.00) | 0.578 (1.00) |  | 0.0548 (1.00) | 0.273 (1.00) | 0.617 (1.00)
10p gain | 17 (12%) | 127 | 0.513 (1.00) | 0.0081 (1.00) | 0.3 (1.00) | 0.179 (1.00) | 0.292 (1.00) | 0.433 (1.00) | 1 (1.00)
11p gain | 7 (5%) | 137 | 0.575 (1.00) | 0.526 (1.00) | 1 (1.00) | 0.102 (1.00) | 0.485 (1.00) | 0.702 (1.00) | 0.272 (1.00)
11q gain | 11 (8%) | 133 | 0.689 (1.00) | 0.32 (1.00) | 0.531 (1.00) | 0.479 (1.00) | 0.853 (1.00) | 1 (1.00) | 0.763 (1.00)
12p gain | 7 (5%) | 137 | 0.49 (1.00) | 0.019 (1.00) | 0.0195 (1.00) |  | 0.791 (1.00) | 1 (1.00) | 0.442 (1.00)
12q gain | 3 (2%) | 141 | 0.387 (1.00) | 0.00117 (0.332) | 0.259 (1.00) |  | 1 (1.00) | 0.565 (1.00) | 0.245 (1.00)
18p gain | 3 (2%) | 141 | 0.522 (1.00) | 0.858 (1.00) | 0.578 (1.00) |  | 0.0548 (1.00) | 0.565 (1.00) | 0.617 (1.00)
19p gain | 8 (6%) | 136 | 0.182 (1.00) | 0.00941 (1.00) | 0.466 (1.00) | 0.0931 (1.00) | 0.299 (1.00) | 0.144 (1.00) | 0.491 (1.00)
21q gain | 4 (3%) | 140 | 0.298 (1.00) | 0.996 (1.00) | 0.634 (1.00) |  | 0.453 (1.00) | 0.648 (1.00) | 0.62 (1.00)
1q loss | 7 (5%) | 137 | 0.495 (1.00) | 0.0302 (1.00) | 0.464 (1.00) | 0.128 (1.00) | 0.00279 (0.783) | 1 (1.00) | 1 (1.00)
3q loss | 7 (5%) | 137 | 0.598 (1.00) | 0.954 (1.00) | 0.699 (1.00) | 0.513 (1.00) | 0.298 (1.00) | 1 (1.00) | 0.717 (1.00)
4p loss | 13 (9%) | 131 | 0.119 (1.00) | 0.155 (1.00) | 0.152 (1.00) | 0.359 (1.00) | 0.0438 (1.00) | 0.139 (1.00) | 0.397 (1.00)
4q loss | 21 (15%) | 123 | 0.0918 (1.00) | 0.914 (1.00) | 0.354 (1.00) | 0.36 (1.00) | 0.268 (1.00) | 0.0979 (1.00) | 0.244 (1.00)
5p loss | 10 (7%) | 134 | 0.241 (1.00) | 0.915 (1.00) | 0.515 (1.00) | 0.181 (1.00) | 0.00665 (1.00) | 0.74 (1.00) | 0.53 (1.00)
5q loss | 7 (5%) | 137 | 0.0143 (1.00) | 0.912 (1.00) | 0.464 (1.00) | 0.44 (1.00) | 0.612 (1.00) | 0.242 (1.00) | 1 (1.00)
6q loss | 14 (10%) | 130 | 0.0087 (1.00) | 0.237 (1.00) | 0.274 (1.00) | 0.236 (1.00) | 0.00103 (0.293) | 0.00832 (1.00) | 0.272 (1.00)
9p loss | 29 (20%) | 115 | 0.00682 (1.00) | 0.0728 (1.00) | 0.675 (1.00) | 0.9 (1.00) | 0.055 (1.00) | 0.00543 (1.00) | 0.148 (1.00)
9q loss | 3 (2%) | 141 | 0.891 (1.00) | 0.0899 (1.00) | 0.578 (1.00) |  | 0.787 (1.00) | 0.565 (1.00) | 1 (1.00)
11p loss | 15 (10%) | 129 | 0.0807 (1.00) | 0.139 (1.00) | 1 (1.00) | 0.939 (1.00) | 0.00672 (1.00) | 0.405 (1.00) | 0.79 (1.00)
12q loss | 6 (4%) | 138 | 0.552 (1.00) | 0.618 (1.00) | 0.699 (1.00) |  | 0.195 (1.00) | 1 (1.00) | 0.681 (1.00)
13q loss | 17 (12%) | 127 | 0.306 (1.00) | 0.672 (1.00) | 1 (1.00) | 0.428 (1.00) | 0.899 (1.00) | 0.189 (1.00) | 0.448 (1.00)
14q loss | 16 (11%) | 128 | 0.00152 (0.43) | 0.194 (1.00) | 0.0339 (1.00) | 0.664 (1.00) | 0.123 (1.00) | 0.186 (1.00) | 0.792 (1.00)
15q loss | 9 (6%) | 135 | 0.952 (1.00) | 0.865 (1.00) | 0.3 (1.00) |  | 0.047 (1.00) | 0.158 (1.00) | 0.743 (1.00)
16q loss | 4 (3%) | 140 | 0.949 (1.00) | 0.176 (1.00) | 1 (1.00) |  | 0.827 (1.00) | 0.148 (1.00) | 1 (1.00)
18p loss | 10 (7%) | 134 | 0.662 (1.00) | 0.657 (1.00) | 0.745 (1.00) | 0.399 (1.00) | 0.12 (1.00) | 1 (1.00) | 0.53 (1.00)
18q loss | 12 (8%) | 132 | 0.248 (1.00) | 0.872 (1.00) | 0.363 (1.00) | 0.467 (1.00) | 0.0384 (1.00) | 0.762 (1.00) | 0.56 (1.00)
19p loss | 5 (3%) | 139 | 0.677 (1.00) | 0.673 (1.00) | 1 (1.00) |  | 0.448 (1.00) | 0.392 (1.00) | 0.679 (1.00)
21q loss | 5 (3%) | 139 | 0.955 (1.00) | 0.735 (1.00) | 1 (1.00) |  | 0.534 (1.00) | 1 (1.00) | 0.679 (1.00)
Xq loss | 3 (2%) | 141 | 0.294 (1.00) | 0.192 (1.00) | 1 (1.00) |  |  | 0.273 (1.00) | 0.617 (1.00)

'1p gain mutation analysis' versus 'Time to Death'

P value = 1.49e-05 (logrank test), Q value = 0.0044

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

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
1P GAIN MUTATED | 4 | 3 | 7.7 - 15.0 (11.4)
1P GAIN WILD-TYPE | 140 | 45 | 0.0 - 211.2 (18.9)

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

'7q gain mutation analysis' versus 'AGE'

P value = 0.000511 (t-test), Q value = 0.15

Table S2. Gene #4: '7q gain mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 144 | 42.7 (13.0)
7Q GAIN MUTATED | 38 | 49.6 (14.0)
7Q GAIN WILD-TYPE | 106 | 40.2 (11.7)

Figure S2. Get High-res Image Gene #4: '7q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'19q gain mutation analysis' versus 'Time to Death'

P value = 0.000433 (logrank test), Q value = 0.12

Table S3. Gene #16: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
19Q GAIN MUTATED | 6 | 4 | 4.1 - 26.3 (17.2)
19Q GAIN WILD-TYPE | 138 | 44 | 0.0 - 211.2 (18.4)

Figure S3. Get High-res Image Gene #16: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20p gain mutation analysis' versus 'Time to Death'

P value = 4.87e-05 (logrank test), Q value = 0.014

Table S4. Gene #17: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
20P GAIN MUTATED | 13 | 7 | 3.8 - 41.1 (16.8)
20P GAIN WILD-TYPE | 131 | 41 | 0.0 - 211.2 (19.0)

Figure S4. Get High-res Image Gene #17: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20q gain mutation analysis' versus 'Time to Death'

P value = 0.000109 (logrank test), Q value = 0.032

Table S5. Gene #18: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
20Q GAIN MUTATED | 11 | 6 | 4.7 - 41.1 (15.3)
20Q GAIN WILD-TYPE | 133 | 42 | 0.0 - 211.2 (18.9)

Figure S5. Get High-res Image Gene #18: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'1p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.28e-14 (Fisher's exact test), Q value = 6.8e-12

Table S6. Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 50 | 35 | 58
1P LOSS MUTATED | 2 | 2 | 37
1P LOSS WILD-TYPE | 48 | 33 | 21

Figure S6. Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'1p loss mutation analysis' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000133 (Fisher's exact test), Q value = 0.038

Table S7. Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients | NO | YES
--- | --- | ---
ALL | 86 | 58
1P LOSS MUTATED | 14 | 27
1P LOSS WILD-TYPE | 72 | 31

Figure S7. Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'10p loss mutation analysis' versus 'Time to Death'

P value = 7.96e-10 (logrank test), Q value = 2.4e-07

Table S8. Gene #30: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
10P LOSS MUTATED | 22 | 16 | 4.1 - 134.3 (10.9)
10P LOSS WILD-TYPE | 122 | 32 | 0.0 - 211.2 (21.0)

Figure S8. Get High-res Image Gene #30: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'AGE'

P value = 6.65e-06 (t-test), Q value = 0.002

Table S9. Gene #30: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 144 | 42.7 (13.0)
10P LOSS MUTATED | 22 | 54.6 (11.0)
10P LOSS WILD-TYPE | 122 | 40.6 (12.2)

Figure S9. Get High-res Image Gene #30: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'10q loss mutation analysis' versus 'Time to Death'

P value = 1.68e-09 (logrank test), Q value = 5e-07

Table S10. Gene #31: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
10Q LOSS MUTATED | 23 | 16 | 4.1 - 134.3 (11.5)
10Q LOSS WILD-TYPE | 121 | 32 | 0.0 - 211.2 (22.1)

Figure S10. Get High-res Image Gene #31: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10q loss mutation analysis' versus 'AGE'

P value = 3.26e-06 (t-test), Q value = 0.00096

Table S11. Gene #31: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 144 | 42.7 (13.0)
10Q LOSS MUTATED | 23 | 54.4 (10.8)
10Q LOSS WILD-TYPE | 121 | 40.5 (12.2)

Figure S11. Get High-res Image Gene #31: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'11q loss mutation analysis' versus 'Time to Death'

P value = 0.000864 (logrank test), Q value = 0.25

Table S12. Gene #33: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
11Q LOSS MUTATED | 3 | 3 | 11.5 - 41.1 (15.0)
11Q LOSS WILD-TYPE | 141 | 45 | 0.0 - 211.2 (18.0)

Figure S12. Get High-res Image Gene #33: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'19q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 9.12e-11 (Fisher's exact test), Q value = 2.7e-08

Table S13. Gene #42: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 50 | 35 | 58
19Q LOSS MUTATED | 7 | 3 | 38
19Q LOSS WILD-TYPE | 43 | 32 | 20

Figure S13. Get High-res Image Gene #42: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

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

P value = 0.000628 (Fisher's exact test), Q value = 0.18

Table S14. Gene #42: '19q loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients | NO | YES
--- | --- | ---
ALL | 86 | 58
19Q LOSS MUTATED | 19 | 29
19Q LOSS WILD-TYPE | 67 | 29

Figure S14. Get High-res Image Gene #42: '19q loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'22q loss mutation analysis' versus 'Time to Death'

P value = 0.000265 (logrank test), Q value = 0.076

Table S15. Gene #44: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 144 | 48 | 0.0 - 211.2 (18.0)
22Q LOSS MUTATED | 10 | 6 | 6.4 - 46.6 (16.8)
22Q LOSS WILD-TYPE | 134 | 42 | 0.0 - 211.2 (19.0)

Figure S15. Get High-res Image Gene #44: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

Methods & Data
Input

- Mutation data file = broad_values_by_arm.mutsig.cluster.txt

- Clinical data file = LGG.clin.merged.picked.txt

- Number of patients = 144

- Number of significantly arm-level cnvs = 45

- Number of selected clinical features = 7

- 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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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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