Correlation between gene mutation status and selected clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
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 (2013): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1J101JZ
Overview
Introduction

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

Summary

Testing the association between mutation status of 7 genes and 15 clinical features across 385 patients, 8 significant findings detected with Q value < 0.25.

  • NRAS mutation correlated to 'PATHOLOGY.N.STAGE',  'HISTOLOGICAL.TYPE', and 'NUMBER.OF.LYMPH.NODES'.

  • BRAF mutation correlated to 'NEOPLASM.DISEASESTAGE',  'PATHOLOGY.T.STAGE',  'PATHOLOGY.N.STAGE',  'HISTOLOGICAL.TYPE', and 'EXTRATHYROIDAL.EXTENSION'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 7 genes and 15 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

Clinical
Features
Time
to
Death
AGE NEOPLASM
DISEASESTAGE
PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
PATHOLOGY
M
STAGE
GENDER HISTOLOGICAL
TYPE
RADIATIONS
RADIATION
REGIMENINDICATION
RADIATIONEXPOSURE EXTRATHYROIDAL
EXTENSION
COMPLETENESS
OF
RESECTION
NUMBER
OF
LYMPH
NODES
MULTIFOCALITY TUMOR
SIZE
nMutated (%) nWild-Type logrank test t-test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test t-test Fisher's exact test t-test
BRAF 232 (60%) 153 0.806
(1.00)
0.848
(1.00)
0.00245
(0.236)
0.000849
(0.0832)
0.000905
(0.0877)
0.0672
(1.00)
0.552
(1.00)
5.43e-20
(5.59e-18)
0.0323
(1.00)
0.591
(1.00)
2.09e-07
(2.13e-05)
0.587
(1.00)
0.618
(1.00)
0.752
(1.00)
0.231
(1.00)
NRAS 32 (8%) 353 0.478
(1.00)
0.748
(1.00)
0.0436
(1.00)
0.0788
(1.00)
0.000413
(0.0409)
0.348
(1.00)
0.674
(1.00)
1.55e-05
(0.00156)
0.61
(1.00)
1
(1.00)
0.105
(1.00)
0.739
(1.00)
0.000113
(0.0113)
0.194
(1.00)
0.851
(1.00)
HRAS 13 (3%) 372 0.52
(1.00)
0.616
(1.00)
0.339
(1.00)
0.436
(1.00)
0.549
(1.00)
0.262
(1.00)
0.745
(1.00)
0.0147
(1.00)
1
(1.00)
1
(1.00)
0.681
(1.00)
0.137
(1.00)
0.51
(1.00)
0.779
(1.00)
0.933
(1.00)
OTUD4 5 (1%) 380 0.65
(1.00)
0.709
(1.00)
0.911
(1.00)
1
(1.00)
0.671
(1.00)
0.241
(1.00)
0.336
(1.00)
0.436
(1.00)
1
(1.00)
1
(1.00)
0.67
(1.00)
1
(1.00)
0.00629
(0.597)
0.667
(1.00)
EIF1AX 6 (2%) 379 0.0796
(1.00)
0.135
(1.00)
0.969
(1.00)
1
(1.00)
0.625
(1.00)
0.468
(1.00)
0.171
(1.00)
0.0922
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.255
(1.00)
0.771
(1.00)
0.667
(1.00)
0.672
(1.00)
NUP93 4 (1%) 381 0.907
(1.00)
0.391
(1.00)
0.794
(1.00)
0.731
(1.00)
0.349
(1.00)
0.653
(1.00)
1
(1.00)
0.0157
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.498
(1.00)
0.609
(1.00)
0.342
(1.00)
0.995
(1.00)
NLRP6 3 (1%) 382 0.655
(1.00)
0.0342
(1.00)
0.815
(1.00)
0.157
(1.00)
0.605
(1.00)
0.132
(1.00)
1
(1.00)
0.668
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.525
(1.00)
0.6
(1.00)
'NRAS MUTATION STATUS' versus 'PATHOLOGY.N.STAGE'

P value = 0.000413 (Fisher's exact test), Q value = 0.041

Table S1.  Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #5: 'PATHOLOGY.N.STAGE'

nPatients 0 1
ALL 181 163
NRAS MUTATED 25 5
NRAS WILD-TYPE 156 158

Figure S1.  Get High-res Image Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #5: 'PATHOLOGY.N.STAGE'

'NRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.55e-05 (Fisher's exact test), Q value = 0.0016

Table S2.  Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients OTHER SPECIFY THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
ALL 6 267 83 29
NRAS MUTATED 0 13 19 0
NRAS WILD-TYPE 6 254 64 29

Figure S2.  Get High-res Image Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'NRAS MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000113 (t-test), Q value = 0.011

Table S3.  Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #13: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 302 3.3 (6.0)
NRAS MUTATED 25 1.0 (2.4)
NRAS WILD-TYPE 277 3.5 (6.2)

Figure S3.  Get High-res Image Gene #1: 'NRAS MUTATION STATUS' versus Clinical Feature #13: 'NUMBER.OF.LYMPH.NODES'

'BRAF MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.00245 (Chi-square test), Q value = 0.24

Table S4.  Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

nPatients STAGE I STAGE II STAGE III STAGE IV STAGE IVA STAGE IVC
ALL 220 43 83 2 30 5
BRAF MUTATED 129 17 59 0 23 3
BRAF WILD-TYPE 91 26 24 2 7 2

Figure S4.  Get High-res Image Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'BRAF MUTATION STATUS' versus 'PATHOLOGY.T.STAGE'

P value = 0.000849 (Fisher's exact test), Q value = 0.083

Table S5.  Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients T1 T2 T3 T4
ALL 113 133 124 13
BRAF MUTATED 67 65 88 11
BRAF WILD-TYPE 46 68 36 2

Figure S5.  Get High-res Image Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'BRAF MUTATION STATUS' versus 'PATHOLOGY.N.STAGE'

P value = 0.000905 (Fisher's exact test), Q value = 0.088

Table S6.  Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #5: 'PATHOLOGY.N.STAGE'

nPatients 0 1
ALL 181 163
BRAF MUTATED 96 115
BRAF WILD-TYPE 85 48

Figure S6.  Get High-res Image Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #5: 'PATHOLOGY.N.STAGE'

'BRAF MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 5.43e-20 (Fisher's exact test), Q value = 5.6e-18

Table S7.  Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients OTHER SPECIFY THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
ALL 6 267 83 29
BRAF MUTATED 3 187 15 27
BRAF WILD-TYPE 3 80 68 2

Figure S7.  Get High-res Image Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'BRAF MUTATION STATUS' versus 'EXTRATHYROIDAL.EXTENSION'

P value = 2.09e-07 (Fisher's exact test), Q value = 2.1e-05

Table S8.  Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #11: 'EXTRATHYROIDAL.EXTENSION'

nPatients MINIMAL (T3) MODERATE/ADVANCED (T4A) NONE VERY ADVANCED (T4B)
ALL 99 10 264 1
BRAF MUTATED 78 10 139 0
BRAF WILD-TYPE 21 0 125 1

Figure S8.  Get High-res Image Gene #2: 'BRAF MUTATION STATUS' versus Clinical Feature #11: 'EXTRATHYROIDAL.EXTENSION'

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

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

  • Number of patients = 385

  • Number of significantly mutated genes = 7

  • Number of selected clinical features = 15

  • 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

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

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[4] 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)
[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)