Correlation between gene mutation status and selected clinical features
Overview
Introduction

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

Summary

Testing the association between mutation status of 35 genes and 8 clinical features across 278 patients, 5 significant findings detected with Q value < 0.25.

  • TP53 mutation correlated to 'Time to Death'.

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

  • ATRX mutation correlated to 'YEARS_TO_BIRTH'.

  • LZTR1 mutation correlated to 'ETHNICITY'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 35 genes and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 5 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		GENDER RADIATION
THERAPY 		KARNOFSKY
PERFORMANCE
SCORE 		HISTOLOGICAL
TYPE 		RACE ETHNICITY
nMutated (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test
IDH1 14 (5%) 264 0.000559
(0.0522) 		3.92e-06
(0.0011) 		0.392
(1.00) 		0.139
(1.00) 		0.129
(1.00) 		0.499
(1.00) 		0.0275
(0.641) 		1
(1.00)
TP53 79 (28%) 199 0.00181
(0.127) 		0.325
(1.00) 		0.491
(1.00) 		0.103
(1.00) 		0.157
(1.00) 		0.308
(1.00) 		0.598
(1.00) 		1
(1.00)
ATRX 16 (6%) 262 0.00818
(0.36) 		1.49e-05
(0.00208) 		0.593
(1.00) 		0.746
(1.00) 		0.233
(1.00) 		0.548
(1.00) 		0.0259
(0.641) 		1
(1.00)
LZTR1 10 (4%) 268 0.69
(1.00) 		0.234
(1.00) 		0.101
(1.00) 		0.148
(1.00) 		0.296
(1.00) 		0.169
(1.00) 		1
(1.00) 		0.00427
(0.239)
PIK3R1 32 (12%) 246 0.935
(1.00) 		0.495
(1.00) 		0.434
(1.00) 		1
(1.00) 		0.62
(1.00) 		1
(1.00) 		0.679
(1.00) 		1
(1.00)
RB1 23 (8%) 255 0.287
(1.00) 		0.949
(1.00) 		0.654
(1.00) 		1
(1.00) 		0.0303
(0.641) 		0.685
(1.00) 		0.599
(1.00) 		1
(1.00)
NF1 29 (10%) 249 0.283
(1.00) 		0.134
(1.00) 		0.84
(1.00) 		0.591
(1.00) 		0.0592
(0.842) 		1
(1.00) 		1
(1.00) 		1
(1.00)
PTEN 85 (31%) 193 0.811
(1.00) 		0.324
(1.00) 		0.588
(1.00) 		0.0811
(0.946) 		0.983
(1.00) 		0.0602
(0.842) 		1
(1.00) 		0.227
(1.00)
PIK3CA 26 (9%) 252 0.213
(1.00) 		0.96
(1.00) 		0.831
(1.00) 		0.586
(1.00) 		0.721
(1.00) 		0.729
(1.00) 		0.381
(1.00) 		1
(1.00)
STAG2 12 (4%) 266 0.00899
(0.36) 		0.849
(1.00) 		0.761
(1.00) 		0.233
(1.00) 		0.107
(1.00) 		1
(1.00) 		0.615
(1.00) 		1
(1.00)
SLC26A3 6 (2%) 272 0.722
(1.00) 		0.279
(1.00) 		0.424
(1.00) 		0.594
(1.00) 		0.98
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
SEMG1 8 (3%) 270 0.366
(1.00) 		0.176
(1.00) 		0.715
(1.00) 		1
(1.00) 		0.547
(1.00) 		1
(1.00) 		0.497
(1.00) 		1
(1.00)
KDR 8 (3%) 270 0.661
(1.00) 		0.499
(1.00) 		0.266
(1.00) 		0.632
(1.00) 		0.634
(1.00) 		0.321
(1.00) 		1
(1.00) 		1
(1.00)
RPL5 7 (3%) 271 0.82
(1.00) 		0.803
(1.00) 		0.256
(1.00) 		0.61
(1.00) 		0.444
(1.00) 		1
(1.00) 		0.448
(1.00) 		1
(1.00)
MAP3K1 6 (2%) 272 0.691
(1.00) 		0.295
(1.00) 		0.424
(1.00) 		1
(1.00) 		0.767
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
BRAF 6 (2%) 272 0.244
(1.00) 		0.918
(1.00) 		1
(1.00) 		0.594
(1.00) 		0.742
(1.00) 		0.0278
(0.641) 		0.401
(1.00) 		1
(1.00)
EGFR 73 (26%) 205 0.727
(1.00) 		0.695
(1.00) 		0.257
(1.00) 		1
(1.00) 		0.343
(1.00) 		0.451
(1.00) 		0.41
(1.00) 		1
(1.00)
TMPRSS6 6 (2%) 272 0.963
(1.00) 		0.274
(1.00) 		0.67
(1.00) 		1
(1.00) 		0.293
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
PRKCD 3 (1%) 275 0.977
(1.00) 		0.123
(1.00) 		1
(1.00) 		0.44
(1.00) 		1
(1.00) 		0.226
(1.00) 		1
(1.00)
TP63 6 (2%) 272 0.334
(1.00) 		0.994
(1.00) 		0.67
(1.00) 		1
(1.00) 		0.697
(1.00) 		1
(1.00) 		1
(1.00) 		0.0531
(0.842)
PDGFRA 11 (4%) 267 0.665
(1.00) 		0.0539
(0.842) 		1
(1.00) 		0.413
(1.00) 		0.121
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
CHD8 8 (3%) 270 0.885
(1.00) 		0.0224
(0.641) 		0.141
(1.00) 		0.354
(1.00) 		0.261
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
IL4R 8 (3%) 270 0.145
(1.00) 		0.108
(1.00) 		0.0273
(0.641) 		0.354
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.496
(1.00) 		1
(1.00)
REN 5 (2%) 273 0.766
(1.00) 		0.617
(1.00) 		0.657
(1.00) 		1
(1.00) 		0.357
(1.00) 		0.0785
(0.946) 		1
(1.00) 		1
(1.00)
CD209 5 (2%) 273 0.671
(1.00) 		0.717
(1.00) 		0.0579
(0.842) 		1
(1.00) 		0.625
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
FBN3 11 (4%) 267 0.19
(1.00) 		0.94
(1.00) 		0.532
(1.00) 		1
(1.00) 		0.956
(1.00) 		0.19
(1.00) 		0.613
(1.00) 		1
(1.00)
MMP13 5 (2%) 273 0.686
(1.00) 		0.12
(1.00) 		0.657
(1.00) 		0.59
(1.00) 		0.0727
(0.925) 		1
(1.00) 		1
(1.00) 		1
(1.00)
TCF12 3 (1%) 275 0.957
(1.00) 		0.94
(1.00) 		0.555
(1.00) 		1
(1.00) 		0.625
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
IL18RAP 6 (2%) 272 0.708
(1.00) 		0.158
(1.00) 		0.67
(1.00) 		0.594
(1.00) 		0.188
(1.00) 		1
(1.00) 		0.401
(1.00) 		1
(1.00)
ODF4 3 (1%) 275 0.328
(1.00) 		0.568
(1.00) 		1
(1.00) 		0.44
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
KEL 15 (5%) 263 0.787
(1.00) 		0.543
(1.00) 		0.413
(1.00) 		0.476
(1.00) 		0.279
(1.00) 		1
(1.00) 		0.708
(1.00) 		1
(1.00)
TESK1 3 (1%) 275 0.595
(1.00) 		0.0671
(0.895) 		1
(1.00) 		0.44
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
MUC17 21 (8%) 257 0.281
(1.00) 		0.5
(1.00) 		0.817
(1.00) 		0.76
(1.00) 		0.643
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
FAM126B 4 (1%) 274 0.891
(1.00) 		0.7
(1.00) 		1
(1.00) 		1
(1.00) 		0.258
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
DDX5 3 (1%) 275 0.032
(0.641) 		0.0388
(0.725) 		0.555
(1.00) 		0.44
(1.00) 		0.135
(1.00) 		1
(1.00) 		1
(1.00)
'TP53 MUTATION STATUS' versus 'Time to Death'

P value = 0.00181 (logrank test), Q value = 0.13

Table S1.  Gene #1: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 278 215 0.1 - 120.6 (11.3)
TP53 MUTATED 79 54 0.4 - 69.9 (12.9)
TP53 WILD-TYPE 199 161 0.1 - 120.6 (10.4)

Figure S1.  Get High-res Image Gene #1: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 0.000559 (logrank test), Q value = 0.052

Table S2.  Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 278 215 0.1 - 120.6 (11.3)
IDH1 MUTATED 14 4 3.4 - 50.5 (21.9)
IDH1 WILD-TYPE 264 211 0.1 - 120.6 (11.0)

Figure S2.  Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'IDH1 MUTATION STATUS' versus 'YEARS_TO_BIRTH'

P value = 3.92e-06 (Wilcoxon-test), Q value = 0.0011

Table S3.  Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

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 S3.  Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'ATRX MUTATION STATUS' versus 'YEARS_TO_BIRTH'

P value = 1.49e-05 (Wilcoxon-test), Q value = 0.0021

Table S4.  Gene #13: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

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 S4.  Get High-res Image Gene #13: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'LZTR1 MUTATION STATUS' versus 'ETHNICITY'

P value = 0.00427 (Fisher's exact test), Q value = 0.24

Table S5.  Gene #28: 'LZTR1 MUTATION STATUS' versus Clinical Feature #8: 'ETHNICITY'

nPatients HISPANIC OR LATINO NOT HISPANIC OR LATINO
ALL 3 220
LZTR1 MUTATED 2 7
LZTR1 WILD-TYPE 1 213

Figure S5.  Get High-res Image Gene #28: 'LZTR1 MUTATION STATUS' versus Clinical Feature #8: 'ETHNICITY'

Methods & Data
Input

  • Mutation data file = sample_sig_gene_table.txt from Mutsig_2CV pipeline

  • Processed Mutation data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/GBM-TP/20063482/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/GBM-TP/19775175/GBM-TP.merged_data.txt

  • Number of patients = 278

  • Number of significantly mutated genes = 35

  • 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.

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)
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