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 72 genes and 8 clinical features across 137 patients, 4 significant findings detected with Q value < 0.25.

  • OXA1L mutation correlated to 'LYMPH.NODE.METASTASIS'.

  • ACTL7B mutation correlated to 'LYMPH.NODE.METASTASIS'.

  • ANKRD20A4 mutation correlated to 'LYMPH.NODE.METASTASIS'.

  • VGLL1 mutation correlated to 'LYMPH.NODE.METASTASIS'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 72 genes and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 4 significant findings detected.

Clinical
Features
Time
to
Death
AGE PRIMARY
SITE
OF
DISEASE
GENDER DISTANT
METASTASIS
LYMPH
NODE
METASTASIS
TUMOR
STAGECODE
NEOPLASM
DISEASESTAGE
nMutated (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Chi-square test Chi-square test t-test Chi-square test
OXA1L 4 (3%) 133 0.509
(1.00)
0.151
(1.00)
0.573
(1.00)
1
(1.00)
0.996
(1.00)
5.17e-05
(0.0258)
0.294
(1.00)
ACTL7B 8 (6%) 129 0.352
(1.00)
0.595
(1.00)
0.681
(1.00)
1
(1.00)
0.994
(1.00)
9.98e-08
(5e-05)
0.0953
(1.00)
ANKRD20A4 4 (3%) 133 0.471
(1.00)
0.529
(1.00)
0.573
(1.00)
0.3
(1.00)
0.996
(1.00)
0.000139
(0.0691)
0.627
(1.00)
VGLL1 5 (4%) 132 0.983
(1.00)
0.229
(1.00)
0.332
(1.00)
0.168
(1.00)
0.996
(1.00)
3.75e-05
(0.0187)
0.929
(1.00)
CDKN2A 23 (17%) 114 0.585
(1.00)
0.781
(1.00)
0.42
(1.00)
0.629
(1.00)
0.9
(1.00)
0.625
(1.00)
0.749
(1.00)
TP53 23 (17%) 114 0.464
(1.00)
0.0129
(1.00)
1
(1.00)
1
(1.00)
0.918
(1.00)
0.08
(1.00)
0.223
(1.00)
BRAF 73 (53%) 64 0.683
(1.00)
0.127
(1.00)
0.232
(1.00)
0.592
(1.00)
0.608
(1.00)
0.575
(1.00)
0.521
(1.00)
C15ORF23 10 (7%) 127 0.85
(1.00)
0.652
(1.00)
0.698
(1.00)
1
(1.00)
0.982
(1.00)
0.629
(1.00)
0.602
(1.00)
ERVFRDE1 3 (2%) 134 0.00791
(1.00)
0.685
(1.00)
0.553
(1.00)
0.551
(1.00)
NRAS 39 (28%) 98 0.85
(1.00)
0.212
(1.00)
0.823
(1.00)
0.841
(1.00)
0.795
(1.00)
0.66
(1.00)
0.523
(1.00)
PTEN 12 (9%) 125 0.642
(1.00)
0.213
(1.00)
0.294
(1.00)
0.536
(1.00)
0.0442
(1.00)
0.845
(1.00)
0.08
(1.00)
PPP6C 14 (10%) 123 0.0232
(1.00)
0.721
(1.00)
0.739
(1.00)
1
(1.00)
0.0785
(1.00)
0.0621
(1.00)
0.685
(1.00)
PRB4 16 (12%) 121 0.13
(1.00)
0.0506
(1.00)
0.117
(1.00)
0.262
(1.00)
0.956
(1.00)
0.148
(1.00)
0.907
(1.00)
RAC1 9 (7%) 128 0.498
(1.00)
0.55
(1.00)
1
(1.00)
0.718
(1.00)
0.989
(1.00)
0.935
(1.00)
0.499
(1.00)
CDH9 23 (17%) 114 0.201
(1.00)
0.119
(1.00)
0.0156
(1.00)
0.812
(1.00)
0.89
(1.00)
0.267
(1.00)
0.207
(1.00)
STK19 9 (7%) 128 0.524
(1.00)
0.444
(1.00)
1
(1.00)
0.484
(1.00)
0.986
(1.00)
0.996
(1.00)
0.927
(1.00)
ADH1C 20 (15%) 117 0.445
(1.00)
0.286
(1.00)
0.407
(1.00)
0.451
(1.00)
0.935
(1.00)
0.117
(1.00)
0.642
(1.00)
TCEB3C 19 (14%) 118 0.703
(1.00)
0.611
(1.00)
0.772
(1.00)
0.115
(1.00)
0.927
(1.00)
0.478
(1.00)
0.296
(1.00)
DDX3X 14 (10%) 123 0.252
(1.00)
0.88
(1.00)
0.315
(1.00)
0.14
(1.00)
0.00912
(1.00)
0.993
(1.00)
0.834
(1.00)
TRAT1 9 (7%) 128 0.0232
(1.00)
0.232
(1.00)
0.436
(1.00)
1
(1.00)
0.986
(1.00)
0.0127
(1.00)
0.917
(1.00)
TTN 108 (79%) 29 0.124
(1.00)
0.805
(1.00)
1
(1.00)
0.185
(1.00)
0.252
(1.00)
0.209
(1.00)
0.836
(1.00)
GH2 10 (7%) 127 0.574
(1.00)
0.477
(1.00)
0.698
(1.00)
1
(1.00)
0.986
(1.00)
0.0136
(1.00)
0.0294
(1.00)
TFEC 13 (9%) 124 0.337
(1.00)
0.207
(1.00)
1
(1.00)
0.543
(1.00)
0.968
(1.00)
0.00767
(1.00)
0.648
(1.00)
IDH1 7 (5%) 130 0.548
(1.00)
0.0124
(1.00)
1
(1.00)
0.224
(1.00)
0.989
(1.00)
0.987
(1.00)
0.582
(1.00)
WDR12 9 (7%) 128 0.887
(1.00)
0.375
(1.00)
1
(1.00)
0.272
(1.00)
0.989
(1.00)
0.727
(1.00)
0.951
(1.00)
RGS18 7 (5%) 130 0.853
(1.00)
0.337
(1.00)
0.354
(1.00)
0.095
(1.00)
0.992
(1.00)
0.878
(1.00)
0.82
(1.00)
POF1B 17 (12%) 120 0.298
(1.00)
0.0388
(1.00)
0.546
(1.00)
0.79
(1.00)
0.942
(1.00)
0.169
(1.00)
0.945
(1.00)
OR5AC2 16 (12%) 121 0.897
(1.00)
0.813
(1.00)
0.763
(1.00)
1
(1.00)
0.949
(1.00)
0.706
(1.00)
0.4
(1.00)
VEGFC 13 (9%) 124 0.358
(1.00)
0.872
(1.00)
0.299
(1.00)
1
(1.00)
0.968
(1.00)
0.0184
(1.00)
0.424
(1.00)
RERG 9 (7%) 128 0.712
(1.00)
0.0934
(1.00)
0.685
(1.00)
0.718
(1.00)
0.989
(1.00)
0.00774
(1.00)
0.519
(1.00)
CCNE2 10 (7%) 127 0.0237
(1.00)
0.875
(1.00)
0.116
(1.00)
0.732
(1.00)
0.978
(1.00)
0.887
(1.00)
0.492
(1.00)
GPR141 12 (9%) 125 0.663
(1.00)
0.996
(1.00)
0.474
(1.00)
0.751
(1.00)
0.968
(1.00)
0.0775
(1.00)
0.393
(1.00)
GK2 17 (12%) 120 0.336
(1.00)
0.603
(1.00)
0.228
(1.00)
0.79
(1.00)
0.949
(1.00)
0.117
(1.00)
0.26
(1.00)
NAP1L2 12 (9%) 125 0.827
(1.00)
0.033
(1.00)
0.732
(1.00)
0.751
(1.00)
0.968
(1.00)
0.0523
(1.00)
0.724
(1.00)
SNAP91 18 (13%) 119 0.877
(1.00)
0.204
(1.00)
0.565
(1.00)
0.117
(1.00)
0.607
(1.00)
0.47
(1.00)
0.587
(1.00)
PRB2 20 (15%) 117 0.751
(1.00)
0.00623
(1.00)
0.0436
(1.00)
0.0732
(1.00)
0.927
(1.00)
0.361
(1.00)
0.407
(1.00)
TLL1 27 (20%) 110 0.95
(1.00)
0.125
(1.00)
0.128
(1.00)
0.181
(1.00)
0.847
(1.00)
0.0945
(1.00)
0.122
(1.00)
HBD 8 (6%) 129 0.196
(1.00)
0.809
(1.00)
0.198
(1.00)
1
(1.00)
0.986
(1.00)
0.98
(1.00)
0.441
(1.00)
GRXCR2 11 (8%) 126 0.37
(1.00)
0.694
(1.00)
1
(1.00)
0.751
(1.00)
0.982
(1.00)
0.0341
(1.00)
0.554
(1.00)
NOTCH2NL 9 (7%) 128 0.924
(1.00)
0.838
(1.00)
0.213
(1.00)
0.718
(1.00)
0.986
(1.00)
0.352
(1.00)
0.442
(1.00)
AREG 6 (4%) 131 0.492
(1.00)
0.293
(1.00)
1
(1.00)
0.403
(1.00)
0.994
(1.00)
0.00215
(1.00)
0.527
(1.00)
HBG2 6 (4%) 131 0.252
(1.00)
0.336
(1.00)
0.624
(1.00)
1
(1.00)
0.992
(1.00)
0.0069
(1.00)
0.454
(1.00)
SERPINB4 20 (15%) 117 0.827
(1.00)
0.283
(1.00)
0.407
(1.00)
0.0195
(1.00)
0.201
(1.00)
0.371
(1.00)
0.939
(1.00)
SPTLC3 14 (10%) 123 0.303
(1.00)
0.713
(1.00)
0.188
(1.00)
0.773
(1.00)
0.956
(1.00)
0.148
(1.00)
0.232
(1.00)
TAF1A 9 (7%) 128 0.024
(1.00)
0.884
(1.00)
0.685
(1.00)
0.484
(1.00)
0.222
(1.00)
0.737
(1.00)
0.798
(1.00)
CLVS2 13 (9%) 124 0.666
(1.00)
0.223
(1.00)
0.732
(1.00)
0.218
(1.00)
0.968
(1.00)
0.0794
(1.00)
0.806
(1.00)
CCDC102B 15 (11%) 122 0.794
(1.00)
0.486
(1.00)
0.751
(1.00)
0.773
(1.00)
0.962
(1.00)
0.115
(1.00)
0.814
(1.00)
OR4N2 15 (11%) 122 0.859
(1.00)
0.247
(1.00)
0.751
(1.00)
0.02
(1.00)
0.0604
(1.00)
0.26
(1.00)
0.814
(1.00)
OR8D4 9 (7%) 128 0.0395
(1.00)
0.62
(1.00)
0.685
(1.00)
1
(1.00)
0.986
(1.00)
0.0366
(1.00)
0.98
(1.00)
RBM11 10 (7%) 127 0.836
(1.00)
0.0147
(1.00)
0.452
(1.00)
0.495
(1.00)
0.978
(1.00)
0.0381
(1.00)
0.434
(1.00)
DEFB118 7 (5%) 130 0.107
(1.00)
0.64
(1.00)
1
(1.00)
1
(1.00)
0.989
(1.00)
0.0275
(1.00)
0.781
(1.00)
GRXCR1 13 (9%) 124 0.332
(1.00)
0.0168
(1.00)
0.299
(1.00)
1
(1.00)
0.968
(1.00)
0.845
(1.00)
0.506
(1.00)
RGPD3 22 (16%) 115 0.981
(1.00)
0.00584
(1.00)
0.784
(1.00)
0.0465
(1.00)
0.705
(1.00)
0.245
(1.00)
0.863
(1.00)
CA1 8 (6%) 129 0.851
(1.00)
0.881
(1.00)
1
(1.00)
0.267
(1.00)
0.992
(1.00)
0.891
(1.00)
0.936
(1.00)
HNF4G 15 (11%) 122 0.0487
(1.00)
0.114
(1.00)
1
(1.00)
0.385
(1.00)
0.956
(1.00)
0.012
(1.00)
0.774
(1.00)
SPAG16 12 (9%) 125 0.658
(1.00)
0.706
(1.00)
1
(1.00)
0.337
(1.00)
0.978
(1.00)
0.0759
(1.00)
0.842
(1.00)
PCDHB8 23 (17%) 114 0.559
(1.00)
0.498
(1.00)
0.788
(1.00)
0.231
(1.00)
0.927
(1.00)
0.377
(1.00)
0.576
(1.00)
HIST1H2AA 5 (4%) 132 0.567
(1.00)
0.822
(1.00)
0.591
(1.00)
1
(1.00)
0.994
(1.00)
0.963
(1.00)
0.973
(1.00)
OR10K2 14 (10%) 123 0.148
(1.00)
0.0061
(1.00)
0.739
(1.00)
0.14
(1.00)
0.968
(1.00)
0.174
(1.00)
0.59
(1.00)
PHGDH 8 (6%) 129 0.722
(1.00)
0.692
(1.00)
0.681
(1.00)
0.0514
(1.00)
0.992
(1.00)
0.00742
(1.00)
0.116
(1.00)
OR9K2 11 (8%) 126 0.604
(1.00)
0.0753
(1.00)
0.067
(1.00)
0.334
(1.00)
0.973
(1.00)
0.0952
(1.00)
0.684
(1.00)
LIN7A 8 (6%) 129 0.875
(1.00)
0.716
(1.00)
0.198
(1.00)
0.718
(1.00)
0.992
(1.00)
0.00897
(1.00)
0.858
(1.00)
USP17L2 13 (9%) 124 0.751
(1.00)
0.549
(1.00)
0.182
(1.00)
0.218
(1.00)
0.968
(1.00)
0.123
(1.00)
0.251
(1.00)
CYLC2 14 (10%) 123 0.468
(1.00)
0.171
(1.00)
0.52
(1.00)
0.14
(1.00)
0.968
(1.00)
0.0488
(1.00)
0.735
(1.00)
DEFB110 5 (4%) 132 0.12
(1.00)
0.994
(1.00)
0.591
(1.00)
0.168
(1.00)
0.994
(1.00)
0.000646
(0.32)
0.671
(1.00)
LCE1B 7 (5%) 130 0.0484
(1.00)
0.734
(1.00)
0.665
(1.00)
1
(1.00)
0.992
(1.00)
0.928
(1.00)
0.864
(1.00)
PARM1 10 (7%) 127 0.228
(1.00)
0.488
(1.00)
0.698
(1.00)
0.495
(1.00)
0.982
(1.00)
0.0267
(1.00)
0.0858
(1.00)
ACSM2B 24 (18%) 113 0.406
(1.00)
0.529
(1.00)
0.195
(1.00)
0.00368
(1.00)
0.89
(1.00)
0.413
(1.00)
0.971
(1.00)
BAGE2 7 (5%) 130 0.737
(1.00)
0.237
(1.00)
0.2
(1.00)
0.687
(1.00)
0.000505
(0.251)
0.00247
(1.00)
0.207
(1.00)
CECR6 6 (4%) 131 0.338
(1.00)
0.953
(1.00)
1
(1.00)
1
(1.00)
0.992
(1.00)
0.577
(1.00)
0.553
(1.00)
OR4M2 15 (11%) 122 0.774
(1.00)
0.000531
(0.263)
0.52
(1.00)
0.773
(1.00)
0.956
(1.00)
0.348
(1.00)
0.228
(1.00)
CERKL 10 (7%) 127 0.62
(1.00)
0.981
(1.00)
0.698
(1.00)
1
(1.00)
0.982
(1.00)
0.0547
(1.00)
0.858
(1.00)
'OXA1L MUTATION STATUS' versus 'LYMPH.NODE.METASTASIS'

P value = 5.17e-05 (Chi-square test), Q value = 0.026

Table S1.  Gene #37: 'OXA1L MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

nPatients N0 N1 N1A N1B N2 N2A N2B N2C N3 NX
ALL 71 2 6 11 1 4 10 4 15 1
OXA1L MUTATED 2 0 1 0 1 0 0 0 0 0
OXA1L WILD-TYPE 69 2 5 11 0 4 10 4 15 1

Figure S1.  Get High-res Image Gene #37: 'OXA1L MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

'ACTL7B MUTATION STATUS' versus 'LYMPH.NODE.METASTASIS'

P value = 9.98e-08 (Chi-square test), Q value = 5e-05

Table S2.  Gene #53: 'ACTL7B MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

nPatients N0 N1 N1A N1B N2 N2A N2B N2C N3 NX
ALL 71 2 6 11 1 4 10 4 15 1
ACTL7B MUTATED 3 0 0 0 1 0 0 0 0 1
ACTL7B WILD-TYPE 68 2 6 11 0 4 10 4 15 0

Figure S2.  Get High-res Image Gene #53: 'ACTL7B MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

'ANKRD20A4 MUTATION STATUS' versus 'LYMPH.NODE.METASTASIS'

P value = 0.000139 (Chi-square test), Q value = 0.069

Table S3.  Gene #62: 'ANKRD20A4 MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

nPatients N0 N1 N1A N1B N2 N2A N2B N2C N3 NX
ALL 71 2 6 11 1 4 10 4 15 1
ANKRD20A4 MUTATED 2 0 0 1 1 0 0 0 0 0
ANKRD20A4 WILD-TYPE 69 2 6 10 0 4 10 4 15 1

Figure S3.  Get High-res Image Gene #62: 'ANKRD20A4 MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

'VGLL1 MUTATION STATUS' versus 'LYMPH.NODE.METASTASIS'

P value = 3.75e-05 (Chi-square test), Q value = 0.019

Table S4.  Gene #64: 'VGLL1 MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

nPatients N0 N1 N1A N1B N2 N2A N2B N2C N3 NX
ALL 71 2 6 11 1 4 10 4 15 1
VGLL1 MUTATED 1 0 1 0 1 0 0 0 1 0
VGLL1 WILD-TYPE 70 2 5 11 0 4 10 4 14 1

Figure S4.  Get High-res Image Gene #64: 'VGLL1 MUTATION STATUS' versus Clinical Feature #6: 'LYMPH.NODE.METASTASIS'

Methods & Data
Input
  • Mutation data file = SKCM-Regional_Metastatic.mutsig.cluster.txt

  • Clinical data file = SKCM-Regional_Metastatic.clin.merged.picked.txt

  • Number of patients = 137

  • Number of significantly mutated genes = 72

  • 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

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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[5] 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)