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 51 genes and 6 clinical features across 168 patients, 10 significant findings detected with Q value < 0.25.

  • ATRX mutation correlated to 'AGE'.

  • IDH1 mutation correlated to 'Time to Death'.

  • CIC mutation correlated to 'HISTOLOGICAL.TYPE'.

  • TP53 mutation correlated to 'AGE',  'HISTOLOGICAL.TYPE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.

  • FUBP1 mutation correlated to 'HISTOLOGICAL.TYPE'.

  • NOTCH1 mutation correlated to 'HISTOLOGICAL.TYPE'.

  • EGFR mutation correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

  • PAX4 mutation correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 51 genes and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 10 significant findings detected.

Clinical
Features
Time
to
Death
AGE GENDER KARNOFSKY
PERFORMANCE
SCORE
HISTOLOGICAL
TYPE
RADIATIONS
RADIATION
REGIMENINDICATION
nMutated (%) nWild-Type logrank test t-test Fisher's exact test t-test Fisher's exact test Fisher's exact test
TP53 88 (52%) 80 0.101
(1.00)
6.07e-06
(0.00168)
0.276
(1.00)
0.592
(1.00)
3.08e-05
(0.00848)
0.000344
(0.0941)
ATRX 73 (43%) 95 0.124
(1.00)
0.000623
(0.168)
0.53
(1.00)
0.69
(1.00)
0.00168
(0.451)
0.019
(1.00)
IDH1 131 (78%) 37 2.4e-05
(0.00663)
0.113
(1.00)
0.0246
(1.00)
0.892
(1.00)
0.0133
(1.00)
1
(1.00)
CIC 35 (21%) 133 0.0537
(1.00)
0.437
(1.00)
0.706
(1.00)
0.535
(1.00)
1.43e-09
(3.98e-07)
0.087
(1.00)
FUBP1 19 (11%) 149 0.775
(1.00)
0.00573
(1.00)
0.806
(1.00)
0.694
(1.00)
0.000607
(0.165)
0.334
(1.00)
NOTCH1 16 (10%) 152 0.859
(1.00)
0.0196
(1.00)
0.115
(1.00)
0.111
(1.00)
0.000574
(0.156)
0.44
(1.00)
EGFR 8 (5%) 160 0.0261
(1.00)
0.00243
(0.648)
0.29
(1.00)
6.32e-11
(1.76e-08)
0.0689
(1.00)
1
(1.00)
PAX4 4 (2%) 164 0.367
(1.00)
0.000438
(0.12)
0.315
(1.00)
0.816
(1.00)
1
(1.00)
PIK3CA 15 (9%) 153 0.915
(1.00)
0.558
(1.00)
1
(1.00)
0.36
(1.00)
0.337
(1.00)
0.292
(1.00)
PIK3R1 12 (7%) 156 0.239
(1.00)
0.0323
(1.00)
0.559
(1.00)
0.696
(1.00)
0.745
(1.00)
0.773
(1.00)
PTEN 7 (4%) 161 0.194
(1.00)
0.365
(1.00)
0.463
(1.00)
0.0355
(1.00)
0.452
(1.00)
ARID1A 11 (7%) 157 0.058
(1.00)
0.794
(1.00)
0.118
(1.00)
0.353
(1.00)
0.622
(1.00)
0.547
(1.00)
TIMD4 5 (3%) 163 0.1
(1.00)
0.173
(1.00)
0.652
(1.00)
0.132
(1.00)
1
(1.00)
0.184
(1.00)
NF1 11 (7%) 157 0.0464
(1.00)
0.725
(1.00)
1
(1.00)
0.776
(1.00)
0.0514
(1.00)
0.0641
(1.00)
IDH2 6 (4%) 162 0.684
(1.00)
0.13
(1.00)
0.701
(1.00)
0.175
(1.00)
1
(1.00)
ZNF844 4 (2%) 164 0.35
(1.00)
0.997
(1.00)
1
(1.00)
0.693
(1.00)
1
(1.00)
IL32 4 (2%) 164 0.015
(1.00)
0.254
(1.00)
1
(1.00)
0.132
(1.00)
1
(1.00)
0.0445
(1.00)
TCF12 6 (4%) 162 0.972
(1.00)
0.554
(1.00)
0.085
(1.00)
0.671
(1.00)
1
(1.00)
0.418
(1.00)
ZBTB20 7 (4%) 161 0.163
(1.00)
0.64
(1.00)
0.7
(1.00)
0.488
(1.00)
0.0503
(1.00)
MUC7 4 (2%) 164 0.147
(1.00)
0.46
(1.00)
1
(1.00)
0.816
(1.00)
1
(1.00)
ZNF57 6 (4%) 162 0.247
(1.00)
0.756
(1.00)
0.404
(1.00)
0.151
(1.00)
1
(1.00)
PRAMEF11 5 (3%) 163 0.129
(1.00)
0.981
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
ANKRD30A 7 (4%) 161 0.274
(1.00)
0.0454
(1.00)
0.241
(1.00)
0.0647
(1.00)
1
(1.00)
ZNF91 5 (3%) 163 0.968
(1.00)
0.793
(1.00)
0.652
(1.00)
0.519
(1.00)
0.184
(1.00)
ZNF845 6 (4%) 162 0.347
(1.00)
0.796
(1.00)
1
(1.00)
0.885
(1.00)
0.218
(1.00)
SPDYE5 3 (2%) 165 0.00205
(0.548)
0.226
(1.00)
0.577
(1.00)
0.671
(1.00)
0.362
(1.00)
0.098
(1.00)
TPTE 6 (4%) 162 0.694
(1.00)
0.407
(1.00)
0.701
(1.00)
0.132
(1.00)
0.0149
(1.00)
0.218
(1.00)
C9ORF79 7 (4%) 161 0.389
(1.00)
0.535
(1.00)
0.463
(1.00)
0.0673
(1.00)
0.885
(1.00)
0.124
(1.00)
OR5A1 4 (2%) 164 0.17
(1.00)
0.657
(1.00)
0.636
(1.00)
0.693
(1.00)
0.624
(1.00)
NOX4 5 (3%) 163 0.483
(1.00)
0.493
(1.00)
1
(1.00)
0.735
(1.00)
1
(1.00)
DDX5 5 (3%) 163 0.157
(1.00)
0.965
(1.00)
1
(1.00)
0.398
(1.00)
0.605
(1.00)
0.664
(1.00)
PSD3 6 (4%) 162 0.959
(1.00)
0.604
(1.00)
0.404
(1.00)
0.875
(1.00)
0.575
(1.00)
0.687
(1.00)
KLKB1 5 (3%) 163 0.161
(1.00)
0.196
(1.00)
1
(1.00)
0.22
(1.00)
1
(1.00)
0.374
(1.00)
CYP2C19 3 (2%) 165 0.433
(1.00)
0.00646
(1.00)
0.261
(1.00)
0.787
(1.00)
0.249
(1.00)
OR4A16 4 (2%) 164 0.497
(1.00)
0.225
(1.00)
1
(1.00)
0.482
(1.00)
0.624
(1.00)
RPTN 5 (3%) 163 0.169
(1.00)
0.969
(1.00)
1
(1.00)
0.735
(1.00)
1
(1.00)
MYH2 7 (4%) 161 0.0858
(1.00)
0.388
(1.00)
1
(1.00)
0.132
(1.00)
0.0355
(1.00)
0.124
(1.00)
OR52B6 3 (2%) 165 0.915
(1.00)
0.8
(1.00)
1
(1.00)
0.26
(1.00)
0.598
(1.00)
SERPINB7 4 (2%) 164 0.822
(1.00)
0.19
(1.00)
0.636
(1.00)
0.574
(1.00)
0.624
(1.00)
PRDM9 5 (3%) 163 0.259
(1.00)
0.0461
(1.00)
0.652
(1.00)
0.389
(1.00)
0.374
(1.00)
ATG5 3 (2%) 165 0.849
(1.00)
0.546
(1.00)
0.577
(1.00)
0.517
(1.00)
0.626
(1.00)
1
(1.00)
C3ORF35 3 (2%) 165 0.495
(1.00)
0.724
(1.00)
1
(1.00)
1
(1.00)
0.249
(1.00)
SPRYD5 4 (2%) 164 0.403
(1.00)
0.657
(1.00)
1
(1.00)
0.0628
(1.00)
0.624
(1.00)
ZNF292 8 (5%) 160 0.725
(1.00)
0.0228
(1.00)
0.29
(1.00)
0.523
(1.00)
0.727
(1.00)
0.474
(1.00)
CREBZF 4 (2%) 164 0.722
(1.00)
0.22
(1.00)
0.315
(1.00)
0.297
(1.00)
0.482
(1.00)
1
(1.00)
MAX 4 (2%) 164 0.35
(1.00)
0.679
(1.00)
0.315
(1.00)
0.574
(1.00)
0.624
(1.00)
TPM1 4 (2%) 164 0.143
(1.00)
0.388
(1.00)
1
(1.00)
0.693
(1.00)
0.338
(1.00)
FSTL5 5 (3%) 163 0.938
(1.00)
0.634
(1.00)
1
(1.00)
0.277
(1.00)
0.374
(1.00)
C15ORF2 6 (4%) 162 0.628
(1.00)
0.379
(1.00)
0.701
(1.00)
0.33
(1.00)
0.687
(1.00)
ZNF860 4 (2%) 164 0.447
(1.00)
0.0606
(1.00)
0.636
(1.00)
0.482
(1.00)
0.624
(1.00)
OR9G9 3 (2%) 165 0.183
(1.00)
0.0207
(1.00)
1
(1.00)
0.468
(1.00)
0.249
(1.00)
'ATRX MUTATION STATUS' versus 'AGE'

P value = 0.000623 (t-test), Q value = 0.17

Table S1.  Gene #1: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 168 43.0 (13.4)
ATRX MUTATED 73 39.1 (12.6)
ATRX WILD-TYPE 95 46.1 (13.3)

Figure S1.  Get High-res Image Gene #1: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 2.4e-05 (logrank test), Q value = 0.0066

Table S2.  Gene #2: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 167 46 0.0 - 211.2 (15.1)
IDH1 MUTATED 130 29 0.0 - 182.3 (17.4)
IDH1 WILD-TYPE 37 17 0.1 - 211.2 (8.4)

Figure S2.  Get High-res Image Gene #2: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'CIC MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.43e-09 (Fisher's exact test), Q value = 4e-07

Table S3.  Gene #3: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 48 47 72
CIC MUTATED 1 3 31
CIC WILD-TYPE 47 44 41

Figure S3.  Get High-res Image Gene #3: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'TP53 MUTATION STATUS' versus 'AGE'

P value = 6.07e-06 (t-test), Q value = 0.0017

Table S4.  Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 168 43.0 (13.4)
TP53 MUTATED 88 38.7 (12.2)
TP53 WILD-TYPE 80 47.8 (13.1)

Figure S4.  Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 3.08e-05 (Fisher's exact test), Q value = 0.0085

Table S5.  Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 48 47 72
TP53 MUTATED 32 32 23
TP53 WILD-TYPE 16 15 49

Figure S5.  Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'TP53 MUTATION STATUS' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000344 (Fisher's exact test), Q value = 0.094

Table S6.  Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients NO YES
ALL 90 78
TP53 MUTATED 59 29
TP53 WILD-TYPE 31 49

Figure S6.  Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'FUBP1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000607 (Fisher's exact test), Q value = 0.16

Table S7.  Gene #5: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 48 47 72
FUBP1 MUTATED 1 2 16
FUBP1 WILD-TYPE 47 45 56

Figure S7.  Get High-res Image Gene #5: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'NOTCH1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000574 (Fisher's exact test), Q value = 0.16

Table S8.  Gene #8: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients ASTROCYTOMA OLIGOASTROCYTOMA OLIGODENDROGLIOMA
ALL 48 47 72
NOTCH1 MUTATED 1 1 14
NOTCH1 WILD-TYPE 47 46 58

Figure S8.  Get High-res Image Gene #8: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'EGFR MUTATION STATUS' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 6.32e-11 (t-test), Q value = 1.8e-08

Table S9.  Gene #20: 'EGFR MUTATION STATUS' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

nPatients Mean (Std.Dev)
ALL 88 88.3 (10.5)
EGFR MUTATED 4 80.0 (0.0)
EGFR WILD-TYPE 84 88.7 (10.6)

Figure S9.  Get High-res Image Gene #20: 'EGFR MUTATION STATUS' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

'PAX4 MUTATION STATUS' versus 'AGE'

P value = 0.000438 (t-test), Q value = 0.12

Table S10.  Gene #39: 'PAX4 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 168 43.0 (13.4)
PAX4 MUTATED 4 31.5 (3.0)
PAX4 WILD-TYPE 164 43.3 (13.4)

Figure S10.  Get High-res Image Gene #39: 'PAX4 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

Methods & Data
Input
  • Mutation data file = LGG-TP.mutsig.cluster.txt

  • Clinical data file = LGG-TP.clin.merged.picked.txt

  • Number of patients = 168

  • Number of significantly mutated genes = 51

  • 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.

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)