Brain Lower Grade Glioma: Correlation between copy number variations of arm-level result and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/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 49 arm-level results and 6 clinical features across 178 patients, 14 significant findings detected with Q value < 0.25.

- 12q 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'.

- 3p loss cnv correlated to 'AGE'.

- 6p loss cnv correlated to 'Time to Death'.

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

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

- 19q loss cnv correlated to 'HISTOLOGICAL.TYPE'.

- 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 49 arm-level results and 6 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 | AGE | GENDER | KARNOFSKY PERFORMANCE SCORE | HISTOLOGICAL TYPE | RADIATIONS RADIATION REGIMENINDICATION
| nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test
1p loss | 55 (31%) | 123 | 0.132 (1.00) | 0.019 (1.00) | 1 (1.00) | 0.78 (1.00) | 3.64e-15 (1.03e-12) | 0.000625 (0.168)
10p loss | 26 (15%) | 152 | 9.19e-11 (2.57e-08) | 1.95e-06 (0.00054) | 0.0522 (1.00) | 0.838 (1.00) | 0.023 (1.00) | 0.832 (1.00)
10q loss | 27 (15%) | 151 | 2.08e-10 (5.81e-08) | 1.03e-06 (0.000287) | 0.0332 (1.00) | 0.883 (1.00) | 0.0115 (1.00) | 0.676 (1.00)
12q gain | 4 (2%) | 174 | 0.195 (1.00) | 2.67e-05 (0.00731) | 0.137 (1.00) |  | 0.819 (1.00) | 1 (1.00)
19q gain | 6 (3%) | 172 | 0.000486 (0.131) | 0.0584 (1.00) | 0.241 (1.00) | 0.267 (1.00) | 0.496 (1.00) | 0.22 (1.00)
20p gain | 15 (8%) | 163 | 0.000193 (0.0524) | 0.0246 (1.00) | 0.18 (1.00) | 0.937 (1.00) | 0.406 (1.00) | 0.419 (1.00)
20q gain | 13 (7%) | 165 | 0.000463 (0.126) | 0.0479 (1.00) | 0.243 (1.00) | 0.847 (1.00) | 0.503 (1.00) | 0.774 (1.00)
3p loss | 4 (2%) | 174 | 0.89 (1.00) | 5.59e-06 (0.00154) | 0.637 (1.00) |  | 0.686 (1.00) | 0.336 (1.00)
6p loss | 5 (3%) | 173 | 0.000146 (0.0398) | 0.801 (1.00) | 1 (1.00) | 0.847 (1.00) | 0.449 (1.00) | 1 (1.00)
19q loss | 64 (36%) | 114 | 0.175 (1.00) | 0.0498 (1.00) | 0.753 (1.00) | 0.911 (1.00) | 2.56e-11 (7.19e-09) | 0.00824 (1.00)
22q loss | 13 (7%) | 165 | 1.61e-05 (0.00443) | 0.692 (1.00) | 0.562 (1.00) | 0.181 (1.00) | 0.00786 (1.00) | 0.264 (1.00)
1p gain | 6 (3%) | 172 | 0.00803 (1.00) | 0.171 (1.00) | 0.085 (1.00) | 0.167 (1.00) | 0.0221 (1.00) | 1 (1.00)
1q gain | 8 (4%) | 170 | 0.289 (1.00) | 0.00482 (1.00) | 0.289 (1.00) | 0.558 (1.00) | 0.486 (1.00) | 0.727 (1.00)
7p gain | 31 (17%) | 147 | 0.0119 (1.00) | 0.0904 (1.00) | 0.0722 (1.00) | 0.992 (1.00) | 0.184 (1.00) | 0.113 (1.00)
7q gain | 43 (24%) | 135 | 0.0189 (1.00) | 0.00311 (0.82) | 0.218 (1.00) | 0.665 (1.00) | 0.273 (1.00) | 0.22 (1.00)
8p gain | 12 (7%) | 166 | 0.702 (1.00) | 0.859 (1.00) | 0.56 (1.00) | 0.652 (1.00) | 0.281 (1.00) | 0.0391 (1.00)
8q gain | 15 (8%) | 163 | 0.932 (1.00) | 0.434 (1.00) | 1 (1.00) | 0.599 (1.00) | 0.097 (1.00) | 0.175 (1.00)
9p gain | 4 (2%) | 174 | 0.17 (1.00) | 0.00546 (1.00) | 0.314 (1.00) |  | 0.819 (1.00) | 1 (1.00)
9q gain | 4 (2%) | 174 | 0.0627 (1.00) | 0.0911 (1.00) | 0.314 (1.00) | 0.167 (1.00) | 0.219 (1.00) | 0.625 (1.00)
10p gain | 18 (10%) | 160 | 0.454 (1.00) | 0.026 (1.00) | 0.215 (1.00) | 0.109 (1.00) | 0.395 (1.00) | 0.135 (1.00)
11p gain | 9 (5%) | 169 | 0.606 (1.00) | 0.278 (1.00) | 1 (1.00) | 0.737 (1.00) | 0.467 (1.00) | 1 (1.00)
11q gain | 13 (7%) | 165 | 0.765 (1.00) | 0.186 (1.00) | 0.562 (1.00) | 0.59 (1.00) | 0.817 (1.00) | 0.774 (1.00)
12p gain | 9 (5%) | 169 | 0.761 (1.00) | 0.00201 (0.533) | 0.0108 (1.00) |  | 0.686 (1.00) | 1 (1.00)
18p gain | 4 (2%) | 174 | 0.555 (1.00) | 0.753 (1.00) | 0.314 (1.00) |  | 0.219 (1.00) | 0.336 (1.00)
19p gain | 8 (4%) | 170 | 0.182 (1.00) | 0.0121 (1.00) | 0.469 (1.00) | 0.0611 (1.00) | 0.332 (1.00) | 0.0709 (1.00)
21q gain | 4 (2%) | 174 | 0.291 (1.00) | 0.964 (1.00) | 0.637 (1.00) |  | 0.469 (1.00) | 0.625 (1.00)
1q loss | 7 (4%) | 171 | 0.497 (1.00) | 0.0369 (1.00) | 0.462 (1.00) | 0.114 (1.00) | 0.00523 (1.00) | 1 (1.00)
2p loss | 4 (2%) | 174 | 0.0729 (1.00) | 0.67 (1.00) | 0.637 (1.00) |  | 0.686 (1.00) | 0.625 (1.00)
2q loss | 3 (2%) | 175 | 0.521 (1.00) | 0.186 (1.00) | 0.262 (1.00) |  | 0.112 (1.00) | 0.595 (1.00)
3q loss | 9 (5%) | 169 | 0.619 (1.00) | 0.863 (1.00) | 0.734 (1.00) | 0.223 (1.00) | 0.427 (1.00) | 1 (1.00)
4p loss | 15 (8%) | 163 | 0.121 (1.00) | 0.255 (1.00) | 0.276 (1.00) | 0.554 (1.00) | 0.061 (1.00) | 0.289 (1.00)
4q loss | 24 (13%) | 154 | 0.0928 (1.00) | 0.864 (1.00) | 0.661 (1.00) | 0.383 (1.00) | 0.273 (1.00) | 0.271 (1.00)
5p loss | 10 (6%) | 168 | 0.242 (1.00) | 0.99 (1.00) | 0.52 (1.00) | 0.209 (1.00) | 0.00573 (1.00) | 0.345 (1.00)
5q loss | 7 (4%) | 171 | 0.0138 (1.00) | 0.82 (1.00) | 0.462 (1.00) | 0.167 (1.00) | 0.374 (1.00) | 0.126 (1.00)
6q loss | 19 (11%) | 159 | 0.00578 (1.00) | 0.134 (1.00) | 0.463 (1.00) | 0.185 (1.00) | 0.0305 (1.00) | 0.00633 (1.00)
9p loss | 34 (19%) | 144 | 0.00826 (1.00) | 0.0866 (1.00) | 1 (1.00) | 0.57 (1.00) | 0.087 (1.00) | 0.0039 (1.00)
9q loss | 6 (3%) | 172 | 0.918 (1.00) | 0.116 (1.00) | 0.404 (1.00) | 0.609 (1.00) | 0.576 (1.00) | 0.416 (1.00)
11p loss | 17 (10%) | 161 | 0.13 (1.00) | 0.167 (1.00) | 0.798 (1.00) | 0.826 (1.00) | 0.00156 (0.415) | 0.202 (1.00)
11q loss | 4 (2%) | 174 | 0.00128 (0.343) | 0.0652 (1.00) | 0.314 (1.00) |  | 0.219 (1.00) | 0.625 (1.00)
12q loss | 8 (4%) | 170 | 0.428 (1.00) | 0.887 (1.00) | 0.725 (1.00) | 0.852 (1.00) | 0.238 (1.00) | 0.727 (1.00)
13q loss | 27 (15%) | 151 | 0.229 (1.00) | 0.4 (1.00) | 0.836 (1.00) | 0.86 (1.00) | 1 (1.00) | 0.402 (1.00)
14q loss | 21 (12%) | 157 | 0.00187 (0.498) | 0.0189 (1.00) | 0.0324 (1.00) | 0.481 (1.00) | 0.148 (1.00) | 0.353 (1.00)
15q loss | 11 (6%) | 167 | 0.266 (1.00) | 0.575 (1.00) | 0.357 (1.00) | 0.807 (1.00) | 0.0536 (1.00) | 0.115 (1.00)
16q loss | 6 (3%) | 172 | 0.998 (1.00) | 0.178 (1.00) | 0.701 (1.00) |  | 0.88 (1.00) | 0.22 (1.00)
18p loss | 13 (7%) | 165 | 0.611 (1.00) | 0.245 (1.00) | 0.781 (1.00) | 0.491 (1.00) | 0.353 (1.00) | 1 (1.00)
18q loss | 15 (8%) | 163 | 0.749 (1.00) | 0.37 (1.00) | 0.423 (1.00) | 0.713 (1.00) | 0.13 (1.00) | 0.788 (1.00)
19p loss | 6 (3%) | 172 | 0.902 (1.00) | 0.625 (1.00) | 0.701 (1.00) | 0.114 (1.00) | 0.287 (1.00) | 1 (1.00)
21q loss | 5 (3%) | 173 | 0.958 (1.00) | 0.79 (1.00) | 1 (1.00) |  | 0.449 (1.00) | 1 (1.00)
Xq loss | 4 (2%) | 174 | 0.333 (1.00) | 0.608 (1.00) | 1 (1.00) |  | 0.787 (1.00) | 0.125 (1.00)

'12q gain mutation analysis' versus 'AGE'

P value = 2.67e-05 (t-test), Q value = 0.0073

Table S1. Gene #13: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 178 | 43.1 (13.4)
12Q GAIN MUTATED | 4 | 31.2 (2.4)
12Q GAIN WILD-TYPE | 174 | 43.4 (13.4)

Figure S1. Get High-res Image Gene #13: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

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

P value = 0.000486 (logrank test), Q value = 0.13

Table S2. Gene #16: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
19Q GAIN MUTATED | 6 | 4 | 4.1 - 26.3 (17.2)
19Q GAIN WILD-TYPE | 171 | 46 | 0.0 - 211.2 (14.5)

Figure S2. 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 = 0.000193 (logrank test), Q value = 0.052

Table S3. Gene #17: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
20P GAIN MUTATED | 15 | 7 | 3.8 - 41.1 (16.8)
20P GAIN WILD-TYPE | 162 | 43 | 0.0 - 211.2 (14.5)

Figure S3. 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 = 0.000463 (logrank test), Q value = 0.13

Table S4. Gene #18: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
20Q GAIN MUTATED | 13 | 6 | 4.7 - 41.1 (15.3)
20Q GAIN WILD-TYPE | 164 | 44 | 0.0 - 211.2 (14.6)

Figure S4. 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 = 3.64e-15 (Fisher's exact test), Q value = 1e-12

Table S5. Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 55 | 47 | 75
1P LOSS MUTATED | 2 | 6 | 47
1P LOSS WILD-TYPE | 53 | 41 | 28

Figure S5. 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 = 0.000625 (Fisher's exact test), Q value = 0.17

Table S6. Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients | NO | YES
--- | --- | ---
ALL | 96 | 82
1P LOSS MUTATED | 19 | 36
1P LOSS WILD-TYPE | 77 | 46

Figure S6. Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'3p loss mutation analysis' versus 'AGE'

P value = 5.59e-06 (t-test), Q value = 0.0015

Table S7. Gene #24: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 178 | 43.1 (13.4)
3P LOSS MUTATED | 4 | 31.0 (2.2)
3P LOSS WILD-TYPE | 174 | 43.4 (13.4)

Figure S7. Get High-res Image Gene #24: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'6p loss mutation analysis' versus 'Time to Death'

P value = 0.000146 (logrank test), Q value = 0.04

Table S8. Gene #30: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
6P LOSS MUTATED | 5 | 2 | 3.0 - 13.4 (6.4)
6P LOSS WILD-TYPE | 172 | 48 | 0.0 - 211.2 (15.2)

Figure S8. Get High-res Image Gene #30: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

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

P value = 9.19e-11 (logrank test), Q value = 2.6e-08

Table S9. Gene #34: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
10P LOSS MUTATED | 26 | 17 | 0.1 - 134.3 (8.6)
10P LOSS WILD-TYPE | 151 | 33 | 0.0 - 211.2 (15.8)

Figure S9. Get High-res Image Gene #34: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'AGE'

P value = 1.95e-06 (t-test), Q value = 0.00054

Table S10. Gene #34: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 178 | 43.1 (13.4)
10P LOSS MUTATED | 26 | 54.8 (11.1)
10P LOSS WILD-TYPE | 152 | 41.2 (12.8)

Figure S10. Get High-res Image Gene #34: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

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

P value = 2.08e-10 (logrank test), Q value = 5.8e-08

Table S11. Gene #35: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
10Q LOSS MUTATED | 27 | 17 | 0.1 - 134.3 (8.8)
10Q LOSS WILD-TYPE | 150 | 33 | 0.0 - 211.2 (16.0)

Figure S11. Get High-res Image Gene #35: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10q loss mutation analysis' versus 'AGE'

P value = 1.03e-06 (t-test), Q value = 0.00029

Table S12. Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 178 | 43.1 (13.4)
10Q LOSS MUTATED | 27 | 54.6 (10.9)
10Q LOSS WILD-TYPE | 151 | 41.1 (12.8)

Figure S12. Get High-res Image Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

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

P value = 2.56e-11 (Fisher's exact test), Q value = 7.2e-09

Table S13. Gene #46: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 55 | 47 | 75
19Q LOSS MUTATED | 8 | 7 | 49
19Q LOSS WILD-TYPE | 47 | 40 | 26

Figure S13. Get High-res Image Gene #46: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

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

P value = 1.61e-05 (logrank test), Q value = 0.0044

Table S14. Gene #48: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 177 | 50 | 0.0 - 211.2 (14.7)
22Q LOSS MUTATED | 13 | 7 | 0.1 - 46.6 (13.4)
22Q LOSS WILD-TYPE | 164 | 43 | 0.0 - 211.2 (14.8)

Figure S14. Get High-res Image Gene #48: '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-TP.clin.merged.picked.txt

- Number of patients = 178

- Number of significantly arm-level cnvs = 49

- Number of selected clinical features = 6

- 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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