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 97 genes and 6 clinical features across 34 patients, 3 significant findings detected with Q value < 0.25.

  • SCRT1 mutation correlated to 'Time to Death' and 'AGE'.

  • MADCAM1 mutation correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 97 genes and 6 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 NEOPLASM
DISEASESTAGE
PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
GENDER
nMutated (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
SCRT1 4 (12%) 30 1.68e-05
(0.00935)
0.000254
(0.141)
0.693
(1.00)
0.788
(1.00)
0.075
(1.00)
1
(1.00)
MADCAM1 3 (9%) 31 0.0045
(1.00)
5.59e-05
(0.031)
0.161
(1.00)
0.0389
(1.00)
0.0394
(1.00)
1
(1.00)
NMU 7 (21%) 27 0.953
(1.00)
0.258
(1.00)
0.502
(1.00)
0.83
(1.00)
0.0181
(1.00)
0.398
(1.00)
LPPR2 3 (9%) 31 0.0026
(1.00)
0.726
(1.00)
0.253
(1.00)
1
(1.00)
SYT8 6 (18%) 28 0.648
(1.00)
0.27
(1.00)
0.916
(1.00)
1
(1.00)
1
(1.00)
0.175
(1.00)
RINL 8 (24%) 26 0.661
(1.00)
0.516
(1.00)
0.859
(1.00)
0.51
(1.00)
1
(1.00)
0.688
(1.00)
OBSCN 15 (44%) 19 0.382
(1.00)
0.0591
(1.00)
0.748
(1.00)
0.592
(1.00)
1
(1.00)
1
(1.00)
MAP1S 4 (12%) 30 0.28
(1.00)
0.161
(1.00)
0.693
(1.00)
1
(1.00)
0.454
(1.00)
1
(1.00)
GPRIN2 4 (12%) 30 0.884
(1.00)
0.907
(1.00)
0.356
(1.00)
1
(1.00)
1
(1.00)
0.601
(1.00)
ATP9B 3 (9%) 31 0.328
(1.00)
0.121
(1.00)
0.253
(1.00)
1
(1.00)
RREB1 4 (12%) 30 0.954
(1.00)
0.166
(1.00)
1
(1.00)
1
(1.00)
0.454
(1.00)
1
(1.00)
IDUA 6 (18%) 28 0.636
(1.00)
0.727
(1.00)
0.79
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
RGS9BP 6 (18%) 28 0.791
(1.00)
0.103
(1.00)
0.0884
(1.00)
0.327
(1.00)
1
(1.00)
0.656
(1.00)
WDR34 4 (12%) 30 0.759
(1.00)
0.0642
(1.00)
0.602
(1.00)
0.704
(1.00)
0.36
(1.00)
0.601
(1.00)
NOTCH2 3 (9%) 31 0.32
(1.00)
0.968
(1.00)
0.133
(1.00)
1
(1.00)
TMEM189 3 (9%) 31 0.337
(1.00)
0.244
(1.00)
1
(1.00)
1
(1.00)
TAF5 5 (15%) 29 0.383
(1.00)
0.455
(1.00)
0.693
(1.00)
0.788
(1.00)
0.454
(1.00)
0.335
(1.00)
LRP11 4 (12%) 30 0.312
(1.00)
0.724
(1.00)
1
(1.00)
0.601
(1.00)
FPGS 7 (21%) 27 0.314
(1.00)
0.024
(1.00)
0.923
(1.00)
0.83
(1.00)
0.225
(1.00)
1
(1.00)
TOR3A 13 (38%) 21 0.304
(1.00)
0.947
(1.00)
0.108
(1.00)
0.0979
(1.00)
0.611
(1.00)
0.481
(1.00)
ZNF517 17 (50%) 17 0.493
(1.00)
0.267
(1.00)
0.792
(1.00)
0.679
(1.00)
0.598
(1.00)
0.494
(1.00)
GLTPD2 10 (29%) 24 0.608
(1.00)
0.235
(1.00)
0.674
(1.00)
1
(1.00)
1
(1.00)
0.708
(1.00)
SEMA5B 7 (21%) 27 0.597
(1.00)
0.446
(1.00)
0.492
(1.00)
0.412
(1.00)
1
(1.00)
1
(1.00)
TNIP2 3 (9%) 31 0.287
(1.00)
0.774
(1.00)
1
(1.00)
1
(1.00)
HHIPL1 5 (15%) 29 0.909
(1.00)
0.968
(1.00)
0.312
(1.00)
0.66
(1.00)
0.119
(1.00)
1
(1.00)
HECTD2 3 (9%) 31 0.0118
(1.00)
0.337
(1.00)
0.829
(1.00)
0.704
(1.00)
1
(1.00)
0.227
(1.00)
ADAD2 10 (29%) 24 0.164
(1.00)
0.742
(1.00)
0.343
(1.00)
0.853
(1.00)
0.563
(1.00)
1
(1.00)
CTNNB1 7 (21%) 27 0.00515
(1.00)
0.239
(1.00)
0.712
(1.00)
0.51
(1.00)
0.225
(1.00)
0.0854
(1.00)
ZFPM1 19 (56%) 15 0.0784
(1.00)
0.828
(1.00)
0.0224
(1.00)
0.448
(1.00)
0.613
(1.00)
1
(1.00)
CLDN23 4 (12%) 30 0.996
(1.00)
0.39
(1.00)
0.531
(1.00)
0.424
(1.00)
0.454
(1.00)
1
(1.00)
CCDC105 4 (12%) 30 0.571
(1.00)
0.581
(1.00)
0.356
(1.00)
0.327
(1.00)
1
(1.00)
0.103
(1.00)
NOL9 7 (21%) 27 0.998
(1.00)
0.00558
(1.00)
0.244
(1.00)
0.37
(1.00)
1
(1.00)
1
(1.00)
ZNF598 7 (21%) 27 0.554
(1.00)
0.0053
(1.00)
0.0475
(1.00)
0.0439
(1.00)
0.557
(1.00)
1
(1.00)
THEM4 6 (18%) 28 0.08
(1.00)
0.827
(1.00)
1
(1.00)
0.788
(1.00)
0.454
(1.00)
0.656
(1.00)
LRIG1 16 (47%) 18 0.0659
(1.00)
0.997
(1.00)
0.593
(1.00)
0.194
(1.00)
1
(1.00)
0.303
(1.00)
MUC5B 8 (24%) 26 0.549
(1.00)
0.412
(1.00)
0.715
(1.00)
0.83
(1.00)
0.557
(1.00)
0.688
(1.00)
AMDHD1 10 (29%) 24 0.937
(1.00)
0.345
(1.00)
0.663
(1.00)
1
(1.00)
1
(1.00)
0.708
(1.00)
RNF149 3 (9%) 31 0.37
(1.00)
0.609
(1.00)
0.0996
(1.00)
0.0651
(1.00)
1
(1.00)
0.227
(1.00)
MSH3 3 (9%) 31 0.0326
(1.00)
0.917
(1.00)
0.161
(1.00)
0.105
(1.00)
0.36
(1.00)
1
(1.00)
ALPPL2 3 (9%) 31 0.328
(1.00)
0.828
(1.00)
0.829
(1.00)
0.704
(1.00)
1
(1.00)
1
(1.00)
SNED1 4 (12%) 30 0.195
(1.00)
0.704
(1.00)
0.531
(1.00)
0.424
(1.00)
0.075
(1.00)
1
(1.00)
OPRD1 11 (32%) 23 0.971
(1.00)
0.652
(1.00)
0.878
(1.00)
0.738
(1.00)
1
(1.00)
0.0255
(1.00)
CCDC102A 11 (32%) 23 0.217
(1.00)
0.121
(1.00)
0.0298
(1.00)
0.0751
(1.00)
0.272
(1.00)
1
(1.00)
KCTD3 4 (12%) 30 0.438
(1.00)
0.681
(1.00)
0.829
(1.00)
0.704
(1.00)
0.36
(1.00)
1
(1.00)
C1ORF106 6 (18%) 28 0.728
(1.00)
0.98
(1.00)
0.406
(1.00)
0.288
(1.00)
1
(1.00)
0.175
(1.00)
KCNK17 9 (26%) 25 0.176
(1.00)
0.672
(1.00)
0.738
(1.00)
1
(1.00)
0.284
(1.00)
0.438
(1.00)
LACTB 11 (32%) 23 0.79
(1.00)
0.284
(1.00)
0.0852
(1.00)
0.233
(1.00)
0.272
(1.00)
1
(1.00)
TRIOBP 9 (26%) 25 0.929
(1.00)
0.594
(1.00)
0.532
(1.00)
0.213
(1.00)
1
(1.00)
1
(1.00)
SARM1 5 (15%) 29 0.438
(1.00)
0.439
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
ERCC2 11 (32%) 23 0.185
(1.00)
0.835
(1.00)
0.942
(1.00)
1
(1.00)
0.611
(1.00)
0.465
(1.00)
NEFH 4 (12%) 30 0.987
(1.00)
0.848
(1.00)
0.531
(1.00)
0.788
(1.00)
0.075
(1.00)
1
(1.00)
KBTBD13 8 (24%) 26 0.482
(1.00)
0.271
(1.00)
0.663
(1.00)
0.534
(1.00)
0.284
(1.00)
0.688
(1.00)
IRX3 9 (26%) 25 0.361
(1.00)
0.809
(1.00)
0.216
(1.00)
0.619
(1.00)
1
(1.00)
0.118
(1.00)
MUC2 7 (21%) 27 0.243
(1.00)
0.133
(1.00)
0.058
(1.00)
0.0271
(1.00)
0.557
(1.00)
0.0854
(1.00)
GARS 14 (41%) 20 0.459
(1.00)
0.443
(1.00)
0.116
(1.00)
0.436
(1.00)
0.613
(1.00)
0.728
(1.00)
UQCRFS1 7 (21%) 27 0.702
(1.00)
0.907
(1.00)
0.492
(1.00)
0.412
(1.00)
0.225
(1.00)
1
(1.00)
ZNF628 5 (15%) 29 0.00972
(1.00)
0.747
(1.00)
0.762
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
ASPDH 11 (32%) 23 0.653
(1.00)
0.724
(1.00)
0.284
(1.00)
0.644
(1.00)
1
(1.00)
0.465
(1.00)
TPO 10 (29%) 24 0.916
(1.00)
0.772
(1.00)
0.198
(1.00)
0.339
(1.00)
0.287
(1.00)
0.259
(1.00)
GLTSCR2 4 (12%) 30 0.453
(1.00)
0.35
(1.00)
0.693
(1.00)
0.788
(1.00)
1
(1.00)
0.601
(1.00)
PANK2 7 (21%) 27 0.833
(1.00)
0.9
(1.00)
0.849
(1.00)
0.83
(1.00)
0.169
(1.00)
0.398
(1.00)
RNF39 3 (9%) 31 0.0782
(1.00)
0.069
(1.00)
0.253
(1.00)
1
(1.00)
MAL2 7 (21%) 27 0.957
(1.00)
0.0128
(1.00)
0.431
(1.00)
0.024
(1.00)
1
(1.00)
0.398
(1.00)
ZAR1 11 (32%) 23 0.168
(1.00)
0.924
(1.00)
0.25
(1.00)
0.358
(1.00)
1
(1.00)
0.141
(1.00)
KRTAP5-5 3 (9%) 31 0.0118
(1.00)
0.337
(1.00)
0.829
(1.00)
0.704
(1.00)
1
(1.00)
0.227
(1.00)
CRIPAK 6 (18%) 28 0.371
(1.00)
0.179
(1.00)
0.715
(1.00)
0.83
(1.00)
1
(1.00)
0.656
(1.00)
TP53 7 (21%) 27 0.0283
(1.00)
0.18
(1.00)
0.015
(1.00)
0.00258
(1.00)
0.169
(1.00)
1
(1.00)
BHLHE22 4 (12%) 30 0.381
(1.00)
0.985
(1.00)
1
(1.00)
0.788
(1.00)
0.454
(1.00)
1
(1.00)
RGMB 3 (9%) 31 0.578
(1.00)
0.932
(1.00)
0.829
(1.00)
0.704
(1.00)
0.36
(1.00)
1
(1.00)
APOE 6 (18%) 28 0.597
(1.00)
0.175
(1.00)
0.916
(1.00)
1
(1.00)
1
(1.00)
0.656
(1.00)
MEN1 3 (9%) 31 0.91
(1.00)
0.121
(1.00)
1
(1.00)
1
(1.00)
RASIP1 4 (12%) 30 0.306
(1.00)
0.445
(1.00)
1
(1.00)
0.788
(1.00)
0.454
(1.00)
0.601
(1.00)
ZC3H12D 3 (9%) 31 0.113
(1.00)
0.222
(1.00)
1
(1.00)
1
(1.00)
TSC22D2 7 (21%) 27 0.118
(1.00)
0.85
(1.00)
0.312
(1.00)
0.0368
(1.00)
0.169
(1.00)
1
(1.00)
COQ2 5 (15%) 29 0.791
(1.00)
0.306
(1.00)
0.916
(1.00)
1
(1.00)
1
(1.00)
0.335
(1.00)
DOK7 5 (15%) 29 0.204
(1.00)
0.564
(1.00)
0.147
(1.00)
0.0631
(1.00)
1
(1.00)
1
(1.00)
KNDC1 7 (21%) 27 0.251
(1.00)
0.497
(1.00)
0.406
(1.00)
0.288
(1.00)
1
(1.00)
1
(1.00)
PDCD6 3 (9%) 31 0.744
(1.00)
0.661
(1.00)
0.0416
(1.00)
0.0159
(1.00)
0.36
(1.00)
1
(1.00)
ATP6V0E2 4 (12%) 30 0.289
(1.00)
0.048
(1.00)
0.502
(1.00)
0.389
(1.00)
1
(1.00)
0.601
(1.00)
HES3 3 (9%) 31 0.385
(1.00)
0.198
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
PRKAR1A 3 (9%) 31 0.0583
(1.00)
0.877
(1.00)
0.161
(1.00)
0.105
(1.00)
0.36
(1.00)
0.227
(1.00)
ATOH8 3 (9%) 31 0.188
(1.00)
0.99
(1.00)
0.829
(1.00)
0.704
(1.00)
0.36
(1.00)
1
(1.00)
BTBD11 4 (12%) 30 0.055
(1.00)
0.646
(1.00)
0.602
(1.00)
0.424
(1.00)
0.454
(1.00)
1
(1.00)
PLIN5 4 (12%) 30 0.704
(1.00)
0.283
(1.00)
0.79
(1.00)
1
(1.00)
0.454
(1.00)
1
(1.00)
ASB16 4 (12%) 30 0.867
(1.00)
0.488
(1.00)
1
(1.00)
0.788
(1.00)
1
(1.00)
0.601
(1.00)
NPTX1 5 (15%) 29 0.237
(1.00)
0.101
(1.00)
0.147
(1.00)
0.0631
(1.00)
1
(1.00)
1
(1.00)
LRRN4 3 (9%) 31 0.438
(1.00)
0.397
(1.00)
0.602
(1.00)
1
(1.00)
0.36
(1.00)
1
(1.00)
CCDC96 4 (12%) 30 0.337
(1.00)
0.136
(1.00)
0.829
(1.00)
0.704
(1.00)
0.36
(1.00)
0.601
(1.00)
PCMTD1 3 (9%) 31 0.851
(1.00)
0.439
(1.00)
1
(1.00)
1
(1.00)
GLI3 5 (15%) 29 0.769
(1.00)
0.0234
(1.00)
0.602
(1.00)
0.424
(1.00)
1
(1.00)
1
(1.00)
MN1 3 (9%) 31 0.138
(1.00)
0.0816
(1.00)
1
(1.00)
0.389
(1.00)
0.36
(1.00)
0.227
(1.00)
C9ORF66 3 (9%) 31 0.834
(1.00)
0.365
(1.00)
0.502
(1.00)
0.236
(1.00)
1
(1.00)
1
(1.00)
KRTAP10-7 3 (9%) 31 0.289
(1.00)
0.765
(1.00)
1
(1.00)
1
(1.00)
ARRDC4 5 (15%) 29 0.652
(1.00)
0.58
(1.00)
0.916
(1.00)
1
(1.00)
0.538
(1.00)
1
(1.00)
VARS 3 (9%) 31 0.254
(1.00)
0.274
(1.00)
1
(1.00)
1
(1.00)
PLEC 6 (18%) 28 0.204
(1.00)
0.387
(1.00)
0.469
(1.00)
1
(1.00)
0.557
(1.00)
0.656
(1.00)
RCCD1 3 (9%) 31 0.348
(1.00)
0.605
(1.00)
1
(1.00)
1
(1.00)
'SCRT1 MUTATION STATUS' versus 'Time to Death'

P value = 1.68e-05 (logrank test), Q value = 0.0094

Table S1.  Gene #84: 'SCRT1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 34 8 6.9 - 121.2 (29.8)
SCRT1 MUTATED 4 2 6.9 - 18.1 (10.7)
SCRT1 WILD-TYPE 30 6 8.3 - 121.2 (32.0)

Figure S1.  Get High-res Image Gene #84: 'SCRT1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'SCRT1 MUTATION STATUS' versus 'AGE'

P value = 0.000254 (t-test), Q value = 0.14

Table S2.  Gene #84: 'SCRT1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 34 50.8 (14.3)
SCRT1 MUTATED 4 63.5 (3.7)
SCRT1 WILD-TYPE 30 49.1 (14.4)

Figure S2.  Get High-res Image Gene #84: 'SCRT1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'MADCAM1 MUTATION STATUS' versus 'AGE'

P value = 5.59e-05 (t-test), Q value = 0.031

Table S3.  Gene #92: 'MADCAM1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 34 50.8 (14.3)
MADCAM1 MUTATED 3 63.3 (2.1)
MADCAM1 WILD-TYPE 31 49.6 (14.4)

Figure S3.  Get High-res Image Gene #92: 'MADCAM1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

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

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

  • Number of patients = 34

  • Number of significantly mutated genes = 97

  • 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)