Correlation between gene mutation status and selected clinical features
Glioblastoma Multiforme (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1HD7TDT
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 32 genes and 8 clinical features across 278 patients, 3 significant findings detected with Q value < 0.25.

  • IDH1 mutation correlated to 'Time to Death' and 'AGE'.

  • ATRX mutation correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 32 genes and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.

Clinical
Features
Time
to
Death
AGE GENDER KARNOFSKY
PERFORMANCE
SCORE
HISTOLOGICAL
TYPE
RADIATIONS
RADIATION
REGIMENINDICATION
RACE ETHNICITY
nMutated (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
IDH1 14 (5%) 264 0.000145
(0.0366)
3.92e-06
(0.000996)
0.392
(1.00)
0.123
(1.00)
0.494
(1.00)
0.04
(1.00)
0.0273
(1.00)
1
(1.00)
ATRX 16 (6%) 262 0.00321
(0.796)
1.49e-05
(0.00376)
0.593
(1.00)
0.057
(1.00)
0.545
(1.00)
0.279
(1.00)
0.0249
(1.00)
1
(1.00)
TP53 78 (28%) 200 0.0013
(0.324)
0.32
(1.00)
0.677
(1.00)
0.102
(1.00)
0.35
(1.00)
0.202
(1.00)
0.593
(1.00)
1
(1.00)
PIK3R1 32 (12%) 246 0.625
(1.00)
0.495
(1.00)
0.434
(1.00)
0.76
(1.00)
1
(1.00)
0.69
(1.00)
0.676
(1.00)
1
(1.00)
RB1 23 (8%) 255 0.214
(1.00)
0.949
(1.00)
0.654
(1.00)
0.0253
(1.00)
0.683
(1.00)
1
(1.00)
0.601
(1.00)
1
(1.00)
NF1 29 (10%) 249 0.165
(1.00)
0.134
(1.00)
0.84
(1.00)
0.241
(1.00)
1
(1.00)
0.54
(1.00)
1
(1.00)
1
(1.00)
PTEN 85 (31%) 193 0.393
(1.00)
0.324
(1.00)
0.588
(1.00)
0.829
(1.00)
0.0608
(1.00)
0.678
(1.00)
1
(1.00)
0.227
(1.00)
PIK3CA 28 (10%) 250 0.403
(1.00)
0.997
(1.00)
0.684
(1.00)
0.751
(1.00)
0.497
(1.00)
0.676
(1.00)
0.423
(1.00)
1
(1.00)
STAG2 12 (4%) 266 0.00285
(0.71)
0.849
(1.00)
0.761
(1.00)
0.0422
(1.00)
1
(1.00)
0.54
(1.00)
0.613
(1.00)
1
(1.00)
SEMG1 8 (3%) 270 0.252
(1.00)
0.176
(1.00)
0.715
(1.00)
0.284
(1.00)
1
(1.00)
0.722
(1.00)
0.493
(1.00)
1
(1.00)
RPL5 7 (3%) 271 0.838
(1.00)
0.803
(1.00)
0.256
(1.00)
0.423
(1.00)
1
(1.00)
0.431
(1.00)
0.449
(1.00)
1
(1.00)
SLC26A3 6 (2%) 272 0.686
(1.00)
0.279
(1.00)
0.424
(1.00)
0.678
(1.00)
1
(1.00)
0.183
(1.00)
1
(1.00)
1
(1.00)
MAP3K1 6 (2%) 272 0.909
(1.00)
0.295
(1.00)
0.424
(1.00)
0.652
(1.00)
1
(1.00)
0.401
(1.00)
1
(1.00)
1
(1.00)
BRAF 6 (2%) 272 0.142
(1.00)
0.918
(1.00)
1
(1.00)
0.279
(1.00)
0.027
(1.00)
0.401
(1.00)
0.399
(1.00)
1
(1.00)
EGFR 73 (26%) 205 0.705
(1.00)
0.695
(1.00)
0.257
(1.00)
0.382
(1.00)
0.451
(1.00)
0.565
(1.00)
0.413
(1.00)
1
(1.00)
PDGFRA 11 (4%) 267 0.494
(1.00)
0.0539
(1.00)
1
(1.00)
0.411
(1.00)
1
(1.00)
0.187
(1.00)
1
(1.00)
1
(1.00)
KDR 8 (3%) 270 0.621
(1.00)
0.499
(1.00)
0.266
(1.00)
0.754
(1.00)
0.323
(1.00)
0.722
(1.00)
1
(1.00)
1
(1.00)
TMPRSS6 6 (2%) 272 0.965
(1.00)
0.274
(1.00)
0.67
(1.00)
0.284
(1.00)
1
(1.00)
0.667
(1.00)
1
(1.00)
1
(1.00)
CHD8 8 (3%) 270 0.951
(1.00)
0.0224
(1.00)
0.141
(1.00)
0.238
(1.00)
1
(1.00)
0.446
(1.00)
1
(1.00)
1
(1.00)
SEMA3C 11 (4%) 267 0.21
(1.00)
0.995
(1.00)
0.751
(1.00)
0.739
(1.00)
1
(1.00)
0.514
(1.00)
0.0563
(1.00)
0.129
(1.00)
MMP13 5 (2%) 273 0.461
(1.00)
0.12
(1.00)
0.657
(1.00)
0.0658
(1.00)
1
(1.00)
0.174
(1.00)
1
(1.00)
1
(1.00)
PRKCD 3 (1%) 275 0.778
(1.00)
0.123
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.224
(1.00)
1
(1.00)
REN 5 (2%) 273 0.685
(1.00)
0.617
(1.00)
0.657
(1.00)
0.333
(1.00)
0.08
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
LRRC55 6 (2%) 272 0.00121
(0.304)
0.719
(1.00)
0.67
(1.00)
0.0955
(1.00)
1
(1.00)
0.667
(1.00)
0.4
(1.00)
1
(1.00)
MUC17 21 (8%) 257 0.325
(1.00)
0.5
(1.00)
0.817
(1.00)
0.782
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
CD209 5 (2%) 273 0.996
(1.00)
0.717
(1.00)
0.0579
(1.00)
0.605
(1.00)
1
(1.00)
0.667
(1.00)
1
(1.00)
1
(1.00)
DDX5 3 (1%) 275 0.117
(1.00)
0.0388
(1.00)
0.555
(1.00)
0.135
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
TP63 6 (2%) 272 0.659
(1.00)
0.994
(1.00)
0.67
(1.00)
0.479
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.0531
(1.00)
CD1D 4 (1%) 274 0.543
(1.00)
0.253
(1.00)
0.621
(1.00)
0.706
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
LZTR1 10 (4%) 268 0.668
(1.00)
0.234
(1.00)
0.101
(1.00)
0.739
(1.00)
0.17
(1.00)
0.735
(1.00)
1
(1.00)
0.00427
(1.00)
TEX15 8 (3%) 270 0.0768
(1.00)
0.94
(1.00)
0.715
(1.00)
0.748
(1.00)
1
(1.00)
0.277
(1.00)
0.494
(1.00)
1
(1.00)
FBN3 11 (4%) 267 0.245
(1.00)
0.94
(1.00)
0.532
(1.00)
0.943
(1.00)
0.189
(1.00)
0.348
(1.00)
0.612
(1.00)
1
(1.00)
'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 0.000145 (logrank test), Q value = 0.037

Table S1.  Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 278 210 0.1 - 73.8 (8.9)
IDH1 MUTATED 14 4 3.4 - 50.5 (18.8)
IDH1 WILD-TYPE 264 206 0.1 - 73.8 (8.6)

Figure S1.  Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'IDH1 MUTATION STATUS' versus 'AGE'

P value = 3.92e-06 (Wilcoxon-test), Q value = 0.001

Table S2.  Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 278 61.0 (13.0)
IDH1 MUTATED 14 40.0 (15.1)
IDH1 WILD-TYPE 264 62.2 (11.9)

Figure S2.  Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'ATRX MUTATION STATUS' versus 'AGE'

P value = 1.49e-05 (Wilcoxon-test), Q value = 0.0038

Table S3.  Gene #13: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 278 61.0 (13.0)
ATRX MUTATED 16 42.7 (16.4)
ATRX WILD-TYPE 262 62.2 (11.9)

Figure S3.  Get High-res Image Gene #13: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

Methods & Data
Input
  • Mutation data file = transformed.cor.cli.txt

  • Clinical data file = GBM-TP.merged_data.txt

  • Number of patients = 278

  • Number of significantly mutated genes = 32

  • Number of selected clinical features = 8

  • 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

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] 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)
[3] 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)