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 49 arm-level results and 7 clinical features across 160 patients, 12 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'.

  • 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'.

  • 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 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 12 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
10p loss 22 (14%) 138 7.85e-10
(2.54e-07) 		1.93e-05
(0.00619) 		0.25
(1.00) 		0.513
(1.00) 		0.0123
(1.00) 		0.485
(1.00) 		0.648
(1.00)
10q loss 23 (14%) 137 1.66e-09
(5.36e-07) 		1.05e-05
(0.00337) 		0.173
(1.00) 		0.552
(1.00) 		0.00706
(1.00) 		0.361
(1.00) 		0.501
(1.00)
12q gain 4 (2%) 156 0.189
(1.00) 		1.66e-05
(0.00532) 		0.137
(1.00) 		0.822
(1.00) 		1
(1.00) 		0.121
(1.00)
19q gain 6 (4%) 154 0.000393
(0.124) 		0.0614
(1.00) 		0.242
(1.00) 		0.298
(1.00) 		0.382
(1.00) 		0.402
(1.00) 		0.682
(1.00)
20p gain 14 (9%) 146 0.000114
(0.0365) 		0.0595
(1.00) 		0.27
(1.00) 		0.72
(1.00) 		0.221
(1.00) 		0.404
(1.00) 		0.583
(1.00)
20q gain 12 (8%) 148 0.000285
(0.0903) 		0.107
(1.00) 		0.363
(1.00) 		0.594
(1.00) 		0.355
(1.00) 		0.763
(1.00) 		1
(1.00)
1p loss 49 (31%) 111 0.158
(1.00) 		0.0127
(1.00) 		0.863
(1.00) 		0.806
(1.00) 		5.76e-15
(1.88e-12) 		0.000802
(0.252) 		0.864
(1.00)
11q loss 3 (2%) 157 0.000733
(0.231) 		0.212
(1.00) 		0.575
(1.00) 		0.0495
(1.00) 		0.272
(1.00) 		0.613
(1.00)
19q loss 57 (36%) 103 0.215
(1.00) 		0.0245
(1.00) 		0.74
(1.00) 		0.697
(1.00) 		1.09e-10
(3.54e-08) 		0.00415
(1.00) 		0.742
(1.00)
22q loss 11 (7%) 149 0.000234
(0.0743) 		0.679
(1.00) 		1
(1.00) 		0.223
(1.00) 		0.00357
(1.00) 		0.356
(1.00) 		0.762
(1.00)
1p gain 5 (3%) 155 0.00534
(1.00) 		0.345
(1.00) 		0.164
(1.00) 		0.00434
(1.00) 		1
(1.00) 		0.202
(1.00)
1q gain 7 (4%) 153 0.263
(1.00) 		0.0159
(1.00) 		0.459
(1.00) 		0.479
(1.00) 		0.484
(1.00) 		0.702
(1.00) 		0.268
(1.00)
7p gain 28 (18%) 132 0.00929
(1.00) 		0.0576
(1.00) 		0.0955
(1.00) 		0.815
(1.00) 		0.136
(1.00) 		0.0893
(1.00) 		0.837
(1.00)
7q gain 39 (24%) 121 0.0146
(1.00) 		0.00142
(0.443) 		0.457
(1.00) 		0.747
(1.00) 		0.291
(1.00) 		0.19
(1.00) 		0.717
(1.00)
8p gain 12 (8%) 148 0.684
(1.00) 		0.827
(1.00) 		0.56
(1.00) 		0.557
(1.00) 		0.355
(1.00) 		0.125
(1.00) 		0.239
(1.00)
8q gain 15 (9%) 145 0.914
(1.00) 		0.404
(1.00) 		1
(1.00) 		0.7
(1.00) 		0.134
(1.00) 		0.284
(1.00) 		0.179
(1.00)
9p gain 3 (2%) 157 0.13
(1.00) 		0.0216
(1.00) 		0.575
(1.00) 		0.339
(1.00) 		1
(1.00) 		0.613
(1.00)
9q gain 3 (2%) 157 0.0486
(1.00) 		0.26
(1.00) 		0.575
(1.00) 		0.0495
(1.00) 		0.272
(1.00) 		0.613
(1.00)
10p gain 18 (11%) 142 0.468
(1.00) 		0.0216
(1.00) 		0.213
(1.00) 		0.155
(1.00) 		0.388
(1.00) 		0.312
(1.00) 		1
(1.00)
11p gain 8 (5%) 152 0.569
(1.00) 		0.407
(1.00) 		1
(1.00) 		0.0922
(1.00) 		0.372
(1.00) 		1
(1.00) 		0.487
(1.00)
11q gain 13 (8%) 147 0.746
(1.00) 		0.199
(1.00) 		0.399
(1.00) 		0.522
(1.00) 		0.76
(1.00) 		1
(1.00) 		0.777
(1.00)
12p gain 8 (5%) 152 0.781
(1.00) 		0.00468
(1.00) 		0.0213
(1.00) 		0.53
(1.00) 		1
(1.00) 		0.278
(1.00)
18p gain 3 (2%) 157 0.515
(1.00) 		0.808
(1.00) 		0.575
(1.00) 		0.0495
(1.00) 		0.567
(1.00) 		0.613
(1.00)
19p gain 8 (5%) 152 0.171
(1.00) 		0.0128
(1.00) 		0.468
(1.00) 		0.0818
(1.00) 		0.329
(1.00) 		0.144
(1.00) 		0.487
(1.00)
21q gain 4 (2%) 156 0.284
(1.00) 		0.948
(1.00) 		0.637
(1.00) 		0.46
(1.00) 		0.647
(1.00) 		0.621
(1.00)
1q loss 7 (4%) 153 0.504
(1.00) 		0.0388
(1.00) 		0.459
(1.00) 		0.122
(1.00) 		0.00499
(1.00) 		1
(1.00) 		1
(1.00)
2p loss 3 (2%) 157 0.0173
(1.00) 		0.999
(1.00) 		1
(1.00) 		0.109
(1.00) 		1
(1.00) 		1
(1.00)
2q loss 3 (2%) 157 0.522
(1.00) 		0.178
(1.00) 		0.262
(1.00) 		0.109
(1.00) 		0.567
(1.00) 		1
(1.00)
3p loss 3 (2%) 157 0.943
(1.00) 		0.00131
(0.411) 		1
(1.00) 		0.109
(1.00) 		0.0652
(1.00) 		1
(1.00)
3q loss 7 (4%) 153 0.574
(1.00) 		0.852
(1.00) 		0.7
(1.00) 		0.492
(1.00) 		0.29
(1.00) 		1
(1.00) 		0.715
(1.00)
4p loss 14 (9%) 146 0.125
(1.00) 		0.215
(1.00) 		0.155
(1.00) 		0.513
(1.00) 		0.065
(1.00) 		0.255
(1.00) 		0.583
(1.00)
4q loss 22 (14%) 138 0.098
(1.00) 		0.722
(1.00) 		0.355
(1.00) 		0.508
(1.00) 		0.516
(1.00) 		0.167
(1.00) 		0.361
(1.00)
5p loss 10 (6%) 150 0.229
(1.00) 		0.952
(1.00) 		0.519
(1.00) 		0.19
(1.00) 		0.00394
(1.00) 		0.741
(1.00) 		0.527
(1.00)
5q loss 7 (4%) 153 0.0126
(1.00) 		0.783
(1.00) 		0.459
(1.00) 		0.349
(1.00) 		0.484
(1.00) 		0.242
(1.00) 		1
(1.00)
6p loss 3 (2%) 157 0.0274
(1.00) 		0.745
(1.00) 		1
(1.00) 		0.862
(1.00) 		0.339
(1.00) 		0.272
(1.00) 		1
(1.00)
6q loss 17 (11%) 143 0.0288
(1.00) 		0.13
(1.00) 		0.439
(1.00) 		0.217
(1.00) 		0.0234
(1.00) 		0.00139
(0.434) 		0.203
(1.00)
9p loss 31 (19%) 129 0.00632
(1.00) 		0.0913
(1.00) 		0.689
(1.00) 		0.687
(1.00) 		0.0541
(1.00) 		0.00202
(0.625) 		0.161
(1.00)
9q loss 4 (2%) 156 0.891
(1.00) 		0.123
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.621
(1.00)
11p loss 16 (10%) 144 0.116
(1.00) 		0.0518
(1.00) 		1
(1.00) 		1
(1.00) 		0.00152
(0.471) 		0.283
(1.00) 		0.603
(1.00)
12q loss 7 (4%) 153 0.443
(1.00) 		0.313
(1.00) 		1
(1.00) 		0.0766
(1.00) 		0.702
(1.00) 		1
(1.00)
13q loss 21 (13%) 139 0.364
(1.00) 		0.633
(1.00) 		0.814
(1.00) 		0.976
(1.00) 		0.915
(1.00) 		0.102
(1.00) 		0.486
(1.00)
14q loss 19 (12%) 141 0.0073
(1.00) 		0.0619
(1.00) 		0.0815
(1.00) 		0.539
(1.00) 		0.315
(1.00) 		0.321
(1.00) 		1
(1.00)
15q loss 10 (6%) 150 0.541
(1.00) 		0.761
(1.00) 		0.192
(1.00) 		0.0407
(1.00) 		0.0917
(1.00) 		1
(1.00)
16q loss 4 (2%) 156 0.939
(1.00) 		0.192
(1.00) 		1
(1.00) 		0.822
(1.00) 		0.147
(1.00) 		1
(1.00)
18p loss 12 (8%) 148 0.95
(1.00) 		0.386
(1.00) 		1
(1.00) 		0.588
(1.00) 		0.114
(1.00) 		1
(1.00) 		1
(1.00)
18q loss 14 (9%) 146 0.476
(1.00) 		0.548
(1.00) 		0.582
(1.00) 		0.891
(1.00) 		0.0326
(1.00) 		0.782
(1.00) 		1
(1.00)
19p loss 6 (4%) 154 0.89
(1.00) 		0.592
(1.00) 		0.7
(1.00) 		0.122
(1.00) 		0.437
(1.00) 		0.688
(1.00) 		1
(1.00)
21q loss 5 (3%) 155 0.94
(1.00) 		0.812
(1.00) 		1
(1.00) 		0.447
(1.00) 		1
(1.00) 		0.676
(1.00)
Xq loss 4 (2%) 156 0.319
(1.00) 		0.592
(1.00) 		1
(1.00) 		0.789
(1.00) 		0.147
(1.00) 		0.358
(1.00)
'12q gain mutation analysis' versus 'AGE'

P value = 1.66e-05 (t-test), Q value = 0.0053

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

nPatients Mean (Std.Dev)
ALL 160 43.3 (13.4)
12Q GAIN MUTATED 4 31.2 (2.4)
12Q GAIN WILD-TYPE 156 43.6 (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 = 0.000393 (logrank test), Q value = 0.12

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

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
19Q GAIN MUTATED 6 4 4.1 - 26.3 (17.2)
19Q GAIN WILD-TYPE 153 45 0.0 - 211.2 (17.4)

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 = 0.000114 (logrank test), Q value = 0.037

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

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
20P GAIN MUTATED 14 7 3.8 - 41.1 (17.2)
20P GAIN WILD-TYPE 145 42 0.0 - 211.2 (17.4)

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 = 0.000285 (logrank test), Q value = 0.09

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

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
20Q GAIN MUTATED 12 6 4.7 - 41.1 (16.1)
20Q GAIN WILD-TYPE 147 43 0.0 - 211.2 (17.5)

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 = 5.76e-15 (Fisher's exact test), Q value = 1.9e-12

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

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 53 39 67
1P LOSS MUTATED 2 4 43
1P LOSS WILD-TYPE 51 35 24

Figure S5.  Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

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

P value = 7.85e-10 (logrank test), Q value = 2.5e-07

Table S6.  Gene #34: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
10P LOSS MUTATED 22 16 4.1 - 134.3 (10.9)
10P LOSS WILD-TYPE 137 33 0.0 - 211.2 (17.9)

Figure S6.  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 = 1.93e-05 (t-test), Q value = 0.0062

Table S7.  Gene #34: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 160 43.3 (13.4)
10P LOSS MUTATED 22 54.6 (11.0)
10P LOSS WILD-TYPE 138 41.5 (12.9)

Figure S7.  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 = 1.66e-09 (logrank test), Q value = 5.4e-07

Table S8.  Gene #35: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
10Q LOSS MUTATED 23 16 4.1 - 134.3 (11.5)
10Q LOSS WILD-TYPE 136 33 0.0 - 211.2 (18.4)

Figure S8.  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 = 1.05e-05 (t-test), Q value = 0.0034

Table S9.  Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 160 43.3 (13.4)
10Q LOSS MUTATED 23 54.4 (10.8)
10Q LOSS WILD-TYPE 137 41.5 (12.9)

Figure S9.  Get High-res Image Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

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

P value = 0.000733 (logrank test), Q value = 0.23

Table S10.  Gene #37: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
11Q LOSS MUTATED 3 3 11.5 - 41.1 (15.0)
11Q LOSS WILD-TYPE 156 46 0.0 - 211.2 (17.4)

Figure S10.  Get High-res Image Gene #37: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

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

P value = 1.09e-10 (Fisher's exact test), Q value = 3.5e-08

Table S11.  Gene #46: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 53 39 67
19Q LOSS MUTATED 8 5 44
19Q LOSS WILD-TYPE 45 34 23

Figure S11.  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 = 0.000234 (logrank test), Q value = 0.074

Table S12.  Gene #48: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 159 49 0.0 - 211.2 (17.4)
22Q LOSS MUTATED 11 6 0.1 - 46.6 (15.8)
22Q LOSS WILD-TYPE 148 43 0.0 - 211.2 (17.4)

Figure S12.  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.clin.merged.picked.txt

  • Number of patients = 160

  • Number of significantly arm-level cnvs = 49

  • 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.

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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