Correlation between gene mutation status and selected clinical features

Thyroid Adenocarcinoma (Primary solid tumor)

22 February 2013 | analyses__2013_02_22

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/C1T72FP1

Overview

Introduction

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

Summary

Testing the association between mutation status of 23 genes and 14 clinical features across 229 patients, 6 significant findings detected with Q value < 0.25.

BRAF mutation correlated to 'HISTOLOGICAL.TYPE', 'EXTRATHYROIDAL.EXTENSION', and 'LYMPH.NODE.METASTASIS'.
HRAS mutation correlated to 'HISTOLOGICAL.TYPE'.
NRAS mutation correlated to 'HISTOLOGICAL.TYPE'.
PPTC7 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 23 genes and 14 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 6 significant findings detected.


		Clinical Features	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	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	127 (55%)	102	0.456 (1.00)	0.37 (1.00)	3.35e-19 (9.41e-17)	0.0137 (1.00)	0.734 (1.00)	0.558 (1.00)	1.81e-06 (0.000504)	0.000902 (0.249)	0.599 (1.00)	0.0899 (1.00)		0.115 (1.00)	0.892 (1.00)	0.0829 (1.00)
HRAS	10 (4%)	219	0.717 (1.00)	0.728 (1.00)	0.000161 (0.0447)	1 (1.00)	1 (1.00)	0.171 (1.00)	1 (1.00)	0.236 (1.00)	0.123 (1.00)	0.838 (1.00)		0.0358 (1.00)	0.338 (1.00)	0.463 (1.00)
NRAS	19 (8%)	210	0.742 (1.00)	0.289 (1.00)	3.97e-07 (0.000111)	0.606 (1.00)	0.56 (1.00)	0.338 (1.00)	0.0331 (1.00)	0.0061 (1.00)	1 (1.00)	0.0175 (1.00)		0.042 (1.00)	0.472 (1.00)	0.854 (1.00)
PPTC7	3 (1%)	226	0.735 (1.00)	0.174 (1.00)	0.608 (1.00)	1 (1.00)	1 (1.00)	0.579 (1.00)	1 (1.00)	0.857 (1.00)	1 (1.00)	0.000806 (0.223)		0.928 (1.00)	1 (1.00)	0.904 (1.00)
EMG1	5 (2%)	224	0.957 (1.00)	0.328 (1.00)	0.322 (1.00)	1 (1.00)	1 (1.00)	0.673 (1.00)	1 (1.00)	0.859 (1.00)	0.166 (1.00)	0.0689 (1.00)		0.331 (1.00)	0.671 (1.00)	0.184 (1.00)
RPTN	5 (2%)	224	0.922 (1.00)	0.611 (1.00)	0.322 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.0185 (1.00)	1 (1.00)	0.307 (1.00)		0.768 (1.00)	0.671 (1.00)	0.661 (1.00)
EIF1AX	3 (1%)	226	0.429 (1.00)	0.174 (1.00)	0.0775 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.0689 (1.00)	0.205 (1.00)			0.732 (1.00)	1 (1.00)	0.373 (1.00)
CCDC15	5 (2%)	224	0.145 (1.00)	1 (1.00)	0.361 (1.00)	1 (1.00)	1 (1.00)	0.138 (1.00)	1 (1.00)	0.00095 (0.261)	1 (1.00)	0.2 (1.00)		0.642 (1.00)	0.195 (1.00)	0.428 (1.00)
ZNF845	4 (2%)	225	0.152 (1.00)	1 (1.00)	0.579 (1.00)	1 (1.00)	1 (1.00)	0.664 (1.00)	0.568 (1.00)	0.628 (1.00)	1 (1.00)	0.861 (1.00)		0.0755 (1.00)	0.623 (1.00)	0.374 (1.00)
TG	10 (4%)	219	0.624 (1.00)	0.728 (1.00)	0.0505 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.949 (1.00)	0.465 (1.00)	0.589 (1.00)		0.987 (1.00)	1 (1.00)	0.727 (1.00)
PRB2	3 (1%)	226	0.274 (1.00)	1 (1.00)	0.608 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.568 (1.00)	0.643 (1.00)	1 (1.00)			0.732 (1.00)	1 (1.00)	0.539 (1.00)
R3HDM2	4 (2%)	225	0.995 (1.00)	1 (1.00)	0.309 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.598 (1.00)	0.603 (1.00)	1 (1.00)			0.927 (1.00)	1 (1.00)	0.546 (1.00)
ZNF799	3 (1%)	226	0.938 (1.00)	1 (1.00)	0.754 (1.00)	1 (1.00)	1 (1.00)	0.579 (1.00)	1 (1.00)	0.114 (1.00)	1 (1.00)			0.667 (1.00)	0.107 (1.00)
PPM1D	5 (2%)	224	0.534 (1.00)	1 (1.00)	0.873 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.375 (1.00)	0.233 (1.00)	1 (1.00)	0.0651 (1.00)		0.0425 (1.00)	1 (1.00)	0.805 (1.00)
KRAS	3 (1%)	226	0.877 (1.00)	0.567 (1.00)	0.102 (1.00)	1 (1.00)	1 (1.00)	0.579 (1.00)		0.857 (1.00)				0.928 (1.00)	1 (1.00)
SLC5A11	3 (1%)	226	0.272 (1.00)	0.567 (1.00)	0.608 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.736 (1.00)	1 (1.00)			0.928 (1.00)	0.607 (1.00)
SLC26A11	3 (1%)	226	0.403 (1.00)	0.174 (1.00)	0.286 (1.00)	1 (1.00)	1 (1.00)	0.0954 (1.00)	1 (1.00)	0.857 (1.00)	1 (1.00)	0.414 (1.00)		0.667 (1.00)	1 (1.00)	0.182 (1.00)
ANKRD30A	3 (1%)	226	0.293 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.579 (1.00)		0.676 (1.00)		0.997 (1.00)		0.42 (1.00)	1 (1.00)
FAM155A	3 (1%)	226	0.167 (1.00)	1 (1.00)	0.216 (1.00)	1 (1.00)	1 (1.00)	0.31 (1.00)	1 (1.00)	0.857 (1.00)	1 (1.00)	0.764 (1.00)		0.928 (1.00)	0.248 (1.00)
ZFHX3	5 (2%)	224	0.966 (1.00)	1 (1.00)	0.402 (1.00)	0.238 (1.00)	1 (1.00)	1 (1.00)	0.145 (1.00)	0.251 (1.00)	0.564 (1.00)	0.417 (1.00)		0.334 (1.00)	0.0609 (1.00)	0.46 (1.00)
ARMCX3	3 (1%)	226	0.531 (1.00)	0.567 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.52 (1.00)	1 (1.00)			0.667 (1.00)	0.607 (1.00)	0.0311 (1.00)
COL5A3	5 (2%)	224	0.41 (1.00)	0.328 (1.00)	0.76 (1.00)	1 (1.00)	1 (1.00)	0.673 (1.00)	1 (1.00)	0.878 (1.00)	0.564 (1.00)	0.262 (1.00)		0.642 (1.00)	0.372 (1.00)	0.159 (1.00)
CDC27	3 (1%)	226	0.79 (1.00)	0.567 (1.00)	1 (1.00)	1 (1.00)	0.13 (1.00)	0.579 (1.00)	0.568 (1.00)	0.52 (1.00)	1 (1.00)			0.786 (1.00)	1 (1.00)

'BRAF MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 3.35e-19 (Fisher's exact test), Q value = 9.4e-17

Table S1. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients	OTHER	THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL	THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED)	THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
ALL	17	121	67	24
BRAF MUTATED	3	92	11	21
BRAF WILD-TYPE	14	29	56	3

Figure S1. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

'BRAF MUTATION STATUS' versus 'EXTRATHYROIDAL.EXTENSION'

P value = 1.81e-06 (Fisher's exact test), Q value = 5e-04

Table S2. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #7: 'EXTRATHYROIDAL.EXTENSION'

nPatients	MINIMAL (T3)	MODERATE/ADVANCED (T4A)	NONE
ALL	50	3	165
BRAF MUTATED	42	3	78
BRAF WILD-TYPE	8	0	87

Figure S2. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #7: 'EXTRATHYROIDAL.EXTENSION'

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

P value = 0.000902 (Chi-square test), Q value = 0.25

Table S3. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'LYMPH.NODE.METASTASIS'

nPatients	N0	N1	N1A	N1B	NX
ALL	111	11	49	30	28
BRAF MUTATED	50	8	39	17	13
BRAF WILD-TYPE	61	3	10	13	15

Figure S3. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #8: 'LYMPH.NODE.METASTASIS'

'HRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000161 (Fisher's exact test), Q value = 0.045

Table S4. Gene #3: 'HRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients	OTHER	THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL	THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED)	THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
ALL	17	121	67	24
HRAS MUTATED	2	0	8	0
HRAS WILD-TYPE	15	121	59	24

Figure S4. Get High-res Image Gene #3: 'HRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

'NRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 3.97e-07 (Fisher's exact test), Q value = 0.00011

Table S5. Gene #4: 'NRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients	OTHER	THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL	THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED)	THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
ALL	17	121	67	24
NRAS MUTATED	2	1	16	0
NRAS WILD-TYPE	15	120	51	24

Figure S5. Get High-res Image Gene #4: 'NRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

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

P value = 0.000806 (t-test), Q value = 0.22

Table S6. Gene #12: 'PPTC7 MUTATION STATUS' versus Clinical Feature #10: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	181	2.7 (4.8)
PPTC7 MUTATED	3	0.3 (0.6)
PPTC7 WILD-TYPE	178	2.7 (4.9)

Figure S6. Get High-res Image Gene #12: 'PPTC7 MUTATION STATUS' versus Clinical Feature #10: '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 = 229
Number of significantly mutated genes = 23
Number of selected clinical features = 14
Exclude genes that fewer than K tumors have mutations, K = 3

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[2] 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)

[3] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[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)

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