Correlation between copy number variations of arm-level result and molecular subtypes
Prostate Adenocarcinoma (Primary solid tumor)
22 February 2013 | analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C19W0CQS
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C19W0CQS
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 26 arm-level results and 6 molecular subtypes across 177 patients, 8 significant findings detected with Q value < 0.25.

- 8q gain cnv correlated to 'CN_CNMF'.

- 8p loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MIRSEQ_CNMF'.

- 16q loss cnv correlated to 'CN_CNMF'.

- 17p loss cnv correlated to 'CN_CNMF'.

- 18p loss cnv correlated to 'CN_CNMF'.

- 18q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 26 arm-level results and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

|  | Molecular subtypes | CN CNMF | METHLYATION CNMF | MRNASEQ CNMF | MRNASEQ CHIERARCHICAL | MIRSEQ CNMF | MIRSEQ CHIERARCHICAL
| nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test
8p loss | 46 (26%) | 131 | 0.000144 (0.0196) | 0.000228 (0.0305) | 0.0164 (1.00) | 0.00406 (0.535) | 0.000165 (0.0222) | 0.681 (1.00)
8q gain | 17 (10%) | 160 | 1.19e-05 (0.00163) | 0.57 (1.00) | 0.438 (1.00) | 0.284 (1.00) | 0.262 (1.00) | 0.112 (1.00)
16q loss | 22 (12%) | 155 | 8.59e-06 (0.00119) | 0.112 (1.00) | 0.189 (1.00) | 0.078 (1.00) | 0.173 (1.00) | 0.615 (1.00)
17p loss | 18 (10%) | 159 | 6.04e-06 (0.00084) | 0.156 (1.00) | 0.299 (1.00) | 0.0355 (1.00) | 0.499 (1.00) | 0.604 (1.00)
18p loss | 19 (11%) | 158 | 2.66e-06 (0.000373) | 0.201 (1.00) | 0.661 (1.00) | 0.186 (1.00) | 0.0486 (1.00) | 0.0116 (1.00)
18q loss | 24 (14%) | 153 | 1.56e-09 (2.2e-07) | 0.419 (1.00) | 0.32 (1.00) | 0.0681 (1.00) | 0.087 (1.00) | 0.0668 (1.00)
1q gain | 4 (2%) | 173 | 0.214 (1.00) | 0.56 (1.00) |  |  | 0.53 (1.00) | 0.822 (1.00)
3p gain | 4 (2%) | 173 | 0.362 (1.00) | 0.824 (1.00) |  |  | 0.15 (1.00) | 0.29 (1.00)
3q gain | 6 (3%) | 171 | 0.19 (1.00) | 0.668 (1.00) | 0.109 (1.00) | 0.0238 (1.00) | 0.288 (1.00) | 0.1 (1.00)
7p gain | 15 (8%) | 162 | 0.0195 (1.00) | 0.09 (1.00) | 0.138 (1.00) | 0.637 (1.00) | 0.787 (1.00) | 0.573 (1.00)
7q gain | 12 (7%) | 165 | 0.0989 (1.00) | 0.171 (1.00) | 0.275 (1.00) | 0.926 (1.00) | 0.663 (1.00) | 0.376 (1.00)
8p gain | 8 (5%) | 169 | 0.0501 (1.00) | 1 (1.00) | 0.738 (1.00) | 0.44 (1.00) | 1 (1.00) | 0.707 (1.00)
9q gain | 5 (3%) | 172 | 0.0904 (1.00) | 0.387 (1.00) | 0.266 (1.00) | 0.823 (1.00) | 0.651 (1.00) | 0.845 (1.00)
12q gain | 3 (2%) | 174 | 0.16 (1.00) |  |  |  | 0.0331 (1.00) | 0.0756 (1.00)
16p gain | 3 (2%) | 174 | 0.459 (1.00) | 0.78 (1.00) |  |  | 0.458 (1.00) | 0.774 (1.00)
16q gain | 3 (2%) | 174 | 0.459 (1.00) | 0.78 (1.00) |  |  | 0.458 (1.00) | 0.774 (1.00)
5q loss | 3 (2%) | 174 | 0.0543 (1.00) | 0.0525 (1.00) |  |  | 0.114 (1.00) | 1 (1.00)
6q loss | 7 (4%) | 170 | 0.0278 (1.00) | 0.156 (1.00) | 0.132 (1.00) | 0.0111 (1.00) | 0.365 (1.00) | 0.125 (1.00)
8q loss | 4 (2%) | 173 | 0.0327 (1.00) | 0.387 (1.00) | 0.266 (1.00) | 0.102 (1.00) | 0.0423 (1.00) | 0.395 (1.00)
10p loss | 6 (3%) | 171 | 0.162 (1.00) | 0.285 (1.00) | 0.377 (1.00) | 0.448 (1.00) | 0.288 (1.00) | 0.122 (1.00)
10q loss | 5 (3%) | 172 | 0.387 (1.00) | 0.735 (1.00) | 0.53 (1.00) | 1 (1.00) | 0.57 (1.00) | 1 (1.00)
12p loss | 9 (5%) | 168 | 0.161 (1.00) | 0.073 (1.00) | 0.664 (1.00) | 1 (1.00) | 0.0539 (1.00) | 0.246 (1.00)
13q loss | 12 (7%) | 165 | 0.00359 (0.478) | 0.204 (1.00) | 0.0256 (1.00) | 0.302 (1.00) | 0.167 (1.00) | 0.375 (1.00)
20p loss | 4 (2%) | 173 | 0.57 (1.00) | 0.188 (1.00) | 0.329 (1.00) | 0.14 (1.00) | 0.00575 (0.753) | 0.0161 (1.00)
21q loss | 4 (2%) | 173 | 0.214 (1.00) | 0.493 (1.00) |  |  | 0.266 (1.00) | 1 (1.00)
22q loss | 6 (3%) | 171 | 0.0262 (1.00) | 0.388 (1.00) | 0.322 (1.00) | 0.113 (1.00) | 0.388 (1.00) | 1 (1.00)

'8q gain mutation analysis' versus 'CN_CNMF'

P value = 1.19e-05 (Fisher's exact test), Q value = 0.0016

Table S1. Gene #7: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
8Q GAIN MUTATED | 2 | 1 | 14 | 0
8Q GAIN WILD-TYPE | 37 | 82 | 40 | 1

Figure S1. Get High-res Image Gene #7: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000144 (Fisher's exact test), Q value = 0.02

Table S2. Gene #14: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
8P LOSS MUTATED | 7 | 13 | 26 | 0
8P LOSS WILD-TYPE | 32 | 70 | 28 | 1

Figure S2. Get High-res Image Gene #14: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000228 (Fisher's exact test), Q value = 0.03

Table S3. Gene #14: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 53 | 50 | 68
8P LOSS MUTATED | 11 | 4 | 27
8P LOSS WILD-TYPE | 42 | 46 | 41

Figure S3. Get High-res Image Gene #14: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'8p loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000165 (Fisher's exact test), Q value = 0.022

Table S4. Gene #14: '8p loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 45 | 46 | 25 | 60
8P LOSS MUTATED | 22 | 4 | 6 | 13
8P LOSS WILD-TYPE | 23 | 42 | 19 | 47

Figure S4. Get High-res Image Gene #14: '8p loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'16q loss mutation analysis' versus 'CN_CNMF'

P value = 8.59e-06 (Fisher's exact test), Q value = 0.0012

Table S5. Gene #20: '16q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
16Q LOSS MUTATED | 2 | 3 | 17 | 0
16Q LOSS WILD-TYPE | 37 | 80 | 37 | 1

Figure S5. Get High-res Image Gene #20: '16q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'17p loss mutation analysis' versus 'CN_CNMF'

P value = 6.04e-06 (Fisher's exact test), Q value = 0.00084

Table S6. Gene #21: '17p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
17P LOSS MUTATED | 0 | 3 | 15 | 0
17P LOSS WILD-TYPE | 39 | 80 | 39 | 1

Figure S6. Get High-res Image Gene #21: '17p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18p loss mutation analysis' versus 'CN_CNMF'

P value = 2.66e-06 (Fisher's exact test), Q value = 0.00037

Table S7. Gene #22: '18p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
18P LOSS MUTATED | 1 | 2 | 16 | 0
18P LOSS WILD-TYPE | 38 | 81 | 38 | 1

Figure S7. Get High-res Image Gene #22: '18p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18q loss mutation analysis' versus 'CN_CNMF'

P value = 1.56e-09 (Fisher's exact test), Q value = 2.2e-07

Table S8. Gene #23: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 39 | 83 | 54 | 1
18Q LOSS MUTATED | 0 | 3 | 21 | 0
18Q LOSS WILD-TYPE | 39 | 80 | 33 | 1

Figure S8. Get High-res Image Gene #23: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

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

- Molecular subtypes file = PRAD-TP.transferedmergedcluster.txt

- Number of patients = 177

- Number of significantly arm-level cnvs = 26

- Number of molecular subtypes = 6

- Exclude genes that fewer than K tumors have mutations, K = 3

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] 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)
[2] 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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