Correlation between gene mutation status and selected clinical features

Thyroid Adenocarcinoma (Primary solid tumor)

21 April 2013 | analyses__2013_04_21

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): Thyroid Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1W093WF

Overview

Introduction

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

Summary

Testing the association between mutation status of 33 genes and 15 clinical features across 289 patients, 5 significant findings detected with Q value < 0.25.

BRAF mutation correlated to 'HISTOLOGICAL.TYPE' and 'EXTRATHYROIDAL.EXTENSION'.
NRAS mutation correlated to 'HISTOLOGICAL.TYPE'.
PPTC7 mutation correlated to 'NUMBER.OF.LYMPH.NODES'.
ATAD2 mutation correlated to 'NUMBER.OF.LYMPH.NODES'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 33 genes and 15 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	AGE	GENDER	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	RADIATIONEXPOSURE	DISTANT METASTASIS	EXTRATHYROIDAL EXTENSION	LYMPH NODE METASTASIS	COMPLETENESS OF RESECTION	NUMBER OF LYMPH NODES	TUMOR STAGECODE	NEOPLASM DISEASESTAGE	MULTIFOCALITY	TUMOR SIZE
	nMutated (%)	nWild-Type	logrank test	t-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	Chi-square test	Fisher's exact test	t-test	t-test	Chi-square test	Fisher's exact test	t-test
BRAF	168 (58%)	121	0.271 (1.00)	0.791 (1.00)	0.341 (1.00)	7.79e-16 (3.43e-13)	0.0164 (1.00)	1 (1.00)	0.2 (1.00)	1.85e-08 (8.12e-06)	0.00179 (0.779)	0.981 (1.00)	0.378 (1.00)		0.0598 (1.00)	0.715 (1.00)	0.309 (1.00)
NRAS	23 (8%)	266	0.666 (1.00)	0.514 (1.00)	0.617 (1.00)	6.67e-06 (0.00291)	0.608 (1.00)	1 (1.00)	0.47 (1.00)	0.00644 (1.00)	0.00241 (1.00)	0.899 (1.00)	0.00277 (1.00)		0.153 (1.00)	0.514 (1.00)	0.503 (1.00)
PPTC7	3 (1%)	286	0.871 (1.00)	0.683 (1.00)	0.158 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.634 (1.00)	0.603 (1.00)	0.825 (1.00)	1 (1.00)	0.000295 (0.129)		0.973 (1.00)	0.608 (1.00)	0.963 (1.00)
ATAD2	4 (1%)	285	0.0505 (1.00)	0.376 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.648 (1.00)	0.0832 (1.00)	0.427 (1.00)	0.283 (1.00)	6.08e-07 (0.000266)		0.946 (1.00)	0.352 (1.00)	0.152 (1.00)
EMG1	6 (2%)	283	0.775 (1.00)	0.66 (1.00)	0.343 (1.00)	0.357 (1.00)	1 (1.00)	1 (1.00)	0.716 (1.00)	0.733 (1.00)	0.832 (1.00)	0.263 (1.00)	0.233 (1.00)		0.511 (1.00)	0.686 (1.00)	0.534 (1.00)
HRAS	11 (4%)	278	0.624 (1.00)	0.922 (1.00)	1 (1.00)	0.00549 (1.00)	1 (1.00)	1 (1.00)	0.187 (1.00)	0.816 (1.00)	0.418 (1.00)	0.126 (1.00)	0.832 (1.00)		0.136 (1.00)	0.362 (1.00)	0.404 (1.00)
PTTG1IP	4 (1%)	285	0.658 (1.00)	0.534 (1.00)	0.575 (1.00)	0.711 (1.00)	1 (1.00)	1 (1.00)	0.404 (1.00)	0.184 (1.00)	0.0412 (1.00)	1 (1.00)	0.615 (1.00)		0.946 (1.00)	0.124 (1.00)	0.0206 (1.00)
RPTN	8 (3%)	281	0.643 (1.00)	0.76 (1.00)	1 (1.00)	0.0645 (1.00)	1 (1.00)	1 (1.00)	0.559 (1.00)	0.763 (1.00)	0.0409 (1.00)	1 (1.00)	0.957 (1.00)		0.522 (1.00)	1 (1.00)	0.302 (1.00)
EIF1AX	4 (1%)	285	0.0623 (1.00)	0.191 (1.00)	0.051 (1.00)	0.178 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.132 (1.00)	0.134 (1.00)			0.971 (1.00)	0.608 (1.00)	0.249 (1.00)
CCDC15	5 (2%)	284	0.684 (1.00)	0.127 (1.00)	1 (1.00)	0.582 (1.00)	1 (1.00)	1 (1.00)	0.271 (1.00)	1 (1.00)	0.0214 (1.00)	1 (1.00)	0.229 (1.00)		0.752 (1.00)	0.373 (1.00)	0.478 (1.00)
ZNF845	5 (2%)	284	0.816 (1.00)	0.82 (1.00)	1 (1.00)	0.582 (1.00)	1 (1.00)	0.176 (1.00)	0.705 (1.00)	1 (1.00)	0.49 (1.00)	1 (1.00)	0.84 (1.00)		0.371 (1.00)	0.673 (1.00)	0.69 (1.00)
ZNF878	3 (1%)	286	0.667 (1.00)	0.365 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.16 (1.00)	1 (1.00)	0.421 (1.00)	1 (1.00)			0.892 (1.00)	0.249 (1.00)
TG	14 (5%)	275	0.0601 (1.00)	0.953 (1.00)	1 (1.00)	0.0047 (1.00)	1 (1.00)	1 (1.00)	0.302 (1.00)	0.603 (1.00)	0.852 (1.00)	1 (1.00)	0.416 (1.00)		0.883 (1.00)	1 (1.00)	0.944 (1.00)
PRB2	5 (2%)	284	0.0272 (1.00)	0.888 (1.00)	0.603 (1.00)	0.762 (1.00)	1 (1.00)	1 (1.00)	0.109 (1.00)	0.172 (1.00)	0.198 (1.00)	0.353 (1.00)			0.013 (1.00)	1 (1.00)	0.997 (1.00)
R3HDM2	4 (1%)	285	0.884 (1.00)	0.963 (1.00)	1 (1.00)	0.522 (1.00)	1 (1.00)	1 (1.00)	0.648 (1.00)	0.631 (1.00)	0.567 (1.00)	1 (1.00)			0.971 (1.00)	1 (1.00)	0.633 (1.00)
TMCO2	3 (1%)	286	0.19 (1.00)	0.945 (1.00)	0.158 (1.00)	0.672 (1.00)	1 (1.00)	0.135 (1.00)	1 (1.00)	0.0193 (1.00)	0.234 (1.00)	0.211 (1.00)			0.973 (1.00)	1 (1.00)	0.279 (1.00)
MUC7	5 (2%)	284	0.525 (1.00)	0.795 (1.00)	0.603 (1.00)	0.582 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.679 (1.00)	0.316 (1.00)	0.00905 (1.00)	0.818 (1.00)		0.371 (1.00)	0.373 (1.00)	0.768 (1.00)
LYPD3	3 (1%)	286	0.883 (1.00)	0.312 (1.00)	1 (1.00)	0.0253 (1.00)	1 (1.00)	1 (1.00)	0.634 (1.00)	1 (1.00)	0.825 (1.00)	0.211 (1.00)	0.492 (1.00)		0.973 (1.00)	0.108 (1.00)	0.00308 (1.00)
TMEM90B	3 (1%)	286	0.883 (1.00)	0.369 (1.00)	0.574 (1.00)	0.262 (1.00)	1 (1.00)	1 (1.00)	0.634 (1.00)	0.267 (1.00)	0.825 (1.00)	1 (1.00)	0.492 (1.00)		0.661 (1.00)	0.108 (1.00)
ZNF799	4 (1%)	285	0.739 (1.00)	0.589 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.631 (1.00)	0.0861 (1.00)	1 (1.00)			0.829 (1.00)	0.624 (1.00)
PPM1D	5 (2%)	284	0.658 (1.00)	0.578 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.679 (1.00)	0.185 (1.00)	1 (1.00)	0.0187 (1.00)		0.11 (1.00)	0.673 (1.00)	0.875 (1.00)
SYNPO2L	3 (1%)	286	0.126 (1.00)	0.19 (1.00)	1 (1.00)	0.672 (1.00)	1 (1.00)	0.0917 (1.00)	1 (1.00)	1 (1.00)	0.492 (1.00)	0.0149 (1.00)			0.141 (1.00)	1 (1.00)	0.934 (1.00)
KRAS	3 (1%)	286	0.901 (1.00)	0.919 (1.00)	0.574 (1.00)	0.385 (1.00)	1 (1.00)	1 (1.00)	0.634 (1.00)		0.825 (1.00)				0.973 (1.00)	0.608 (1.00)
SLC5A11	3 (1%)	286	0.775 (1.00)	0.261 (1.00)	0.574 (1.00)	0.385 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.603 (1.00)	0.694 (1.00)	1 (1.00)			0.973 (1.00)	1 (1.00)
PRG4	3 (1%)	286	0.756 (1.00)	0.703 (1.00)	1 (1.00)	0.0939 (1.00)	1 (1.00)	1 (1.00)	0.16 (1.00)	0.603 (1.00)	0.355 (1.00)	1 (1.00)	0.979 (1.00)		0.973 (1.00)	0.108 (1.00)	0.0151 (1.00)
SCUBE2	3 (1%)	286	0.75 (1.00)	0.48 (1.00)	1 (1.00)	0.672 (1.00)	1 (1.00)	1 (1.00)	0.634 (1.00)	1 (1.00)	0.421 (1.00)	1 (1.00)			0.833 (1.00)	0.608 (1.00)	0.0981 (1.00)
SLC26A11	3 (1%)	286	0.812 (1.00)	0.368 (1.00)	0.158 (1.00)	0.0939 (1.00)	1 (1.00)	1 (1.00)	0.16 (1.00)	0.603 (1.00)	0.825 (1.00)	1 (1.00)	0.322 (1.00)		0.772 (1.00)	0.608 (1.00)	0.16 (1.00)
ANKRD30A	4 (1%)	285	0.627 (1.00)	0.116 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.404 (1.00)	1 (1.00)	0.536 (1.00)	1 (1.00)	0.614 (1.00)		0.803 (1.00)	1 (1.00)
FAM155A	3 (1%)	286	0.858 (1.00)	0.201 (1.00)	1 (1.00)	0.672 (1.00)	1 (1.00)	1 (1.00)	0.286 (1.00)	0.603 (1.00)	0.825 (1.00)	1 (1.00)	0.651 (1.00)		0.973 (1.00)	0.108 (1.00)
ZFHX3	6 (2%)	283	0.871 (1.00)	0.559 (1.00)	1 (1.00)	0.277 (1.00)	0.226 (1.00)	1 (1.00)	0.716 (1.00)	0.124 (1.00)	0.126 (1.00)	0.66 (1.00)	0.581 (1.00)		0.681 (1.00)	0.107 (1.00)	0.367 (1.00)
ARMCX3	3 (1%)	286	0.836 (1.00)	0.5 (1.00)	0.574 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.603 (1.00)	0.492 (1.00)	1 (1.00)			0.772 (1.00)	1 (1.00)	0.0278 (1.00)
COL5A3	5 (2%)	284	0.755 (1.00)	0.377 (1.00)	0.335 (1.00)	0.458 (1.00)	1 (1.00)	1 (1.00)	0.424 (1.00)	1 (1.00)	0.843 (1.00)	0.592 (1.00)	0.166 (1.00)		0.752 (1.00)	0.197 (1.00)	0.096 (1.00)
CDC27	3 (1%)	286	0.667 (1.00)	0.824 (1.00)	0.574 (1.00)	1 (1.00)	1 (1.00)	0.135 (1.00)	0.634 (1.00)	1 (1.00)	0.492 (1.00)	1 (1.00)			0.892 (1.00)	0.608 (1.00)

'BRAF MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 7.79e-16 (Fisher's exact test), Q value = 3.4e-13

Table S1. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #4: '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	5	191	72	21
BRAF MUTATED	1	134	14	19
BRAF WILD-TYPE	4	57	58	2

Figure S1. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'

'BRAF MUTATION STATUS' versus 'EXTRATHYROIDAL.EXTENSION'

P value = 1.85e-08 (Fisher's exact test), Q value = 8.1e-06

Table S2. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'EXTRATHYROIDAL.EXTENSION'

nPatients	MINIMAL (T3)	MODERATE/ADVANCED (T4A)	NONE	VERY ADVANCED (T4B)
ALL	75	8	193	1
BRAF MUTATED	62	8	94	0
BRAF WILD-TYPE	13	0	99	1

Figure S2. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'EXTRATHYROIDAL.EXTENSION'

'NRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.67e-06 (Fisher's exact test), Q value = 0.0029

Table S3. Gene #4: 'NRAS MUTATION STATUS' versus Clinical Feature #4: '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	5	191	72	21
NRAS MUTATED	0	6	17	0
NRAS WILD-TYPE	5	185	55	21

Figure S3. Get High-res Image Gene #4: 'NRAS MUTATION STATUS' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'

'PPTC7 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000295 (t-test), Q value = 0.13

Table S4. Gene #15: 'PPTC7 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	224	3.0 (5.3)
PPTC7 MUTATED	3	0.3 (0.6)
PPTC7 WILD-TYPE	221	3.1 (5.4)

Figure S4. Get High-res Image Gene #15: 'PPTC7 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

'ATAD2 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 6.08e-07 (t-test), Q value = 0.00027

Table S5. Gene #22: 'ATAD2 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	224	3.0 (5.3)
ATAD2 MUTATED	4	0.2 (0.5)
ATAD2 WILD-TYPE	220	3.1 (5.4)

Figure S5. Get High-res Image Gene #22: 'ATAD2 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Methods & Data

Input

Mutation data file = THCA-TP.mutsig.cluster.txt
Clinical data file = THCA-TP.clin.merged.picked.txt
Number of patients = 289
Number of significantly mutated genes = 33
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

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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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)

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