Correlation between gene mutation status and selected clinical features

Colon/Rectal Adenocarcinoma (Primary solid tumor)

23 May 2013 | analyses__2013_05_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/C1S75DBZ

Overview

Introduction

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

Summary

Testing the association between mutation status of 21 genes and 11 clinical features across 224 patients, 6 significant findings detected with Q value < 0.25.

BRAF mutation correlated to 'HISTOLOGICAL.TYPE'.
TP53 mutation correlated to 'HISTOLOGICAL.TYPE'.
PIK3CA mutation correlated to 'NUMBER.OF.LYMPH.NODES'.
ACVR2A mutation correlated to 'NUMBER.OF.LYMPH.NODES'.
CRTC1 mutation correlated to 'NUMBER.OF.LYMPH.NODES'.
KRTAP5-5 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 21 genes and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 6 significant findings detected.


		Clinical Features	Time to Death	AGE	PRIMARY SITE OF DISEASE	GENDER	HISTOLOGICAL TYPE	DISTANT METASTASIS	LYMPH NODE METASTASIS	COMPLETENESS OF RESECTION	NUMBER OF LYMPH NODES	TUMOR STAGECODE	NEOPLASM DISEASESTAGE
	nMutated (%)	nWild-Type	logrank test	t-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
BRAF	22 (10%)	202	0.885 (1.00)	0.0839 (1.00)	0.0261 (1.00)	0.0702 (1.00)	1.88e-06 (0.000383)	0.394 (1.00)	0.989 (1.00)	0.611 (1.00)	0.599 (1.00)		0.148 (1.00)
TP53	120 (54%)	104	0.486 (1.00)	0.0605 (1.00)	0.0135 (1.00)	0.284 (1.00)	0.000232 (0.0468)	0.919 (1.00)	0.471 (1.00)	0.559 (1.00)	0.447 (1.00)		0.366 (1.00)
PIK3CA	33 (15%)	191	0.749 (1.00)	0.0855 (1.00)	0.227 (1.00)	0.851 (1.00)	0.0168 (1.00)	0.133 (1.00)	0.162 (1.00)	0.303 (1.00)	1.35e-05 (0.00274)		0.0203 (1.00)
ACVR2A	9 (4%)	215	0.266 (1.00)	0.454 (1.00)	0.282 (1.00)	0.0902 (1.00)	0.716 (1.00)	1 (1.00)	0.765 (1.00)	1 (1.00)	4.2e-08 (8.62e-06)		0.496 (1.00)
CRTC1	6 (3%)	218		0.0365 (1.00)	0.669 (1.00)	0.429 (1.00)	0.761 (1.00)	0.609 (1.00)	0.862 (1.00)	1 (1.00)	0.000496 (0.0996)		0.264 (1.00)
KRTAP5-5	4 (2%)	220		0.882 (1.00)	0.588 (1.00)	1 (1.00)	0.303 (1.00)	1 (1.00)	0.741 (1.00)	1 (1.00)	3.24e-11 (6.68e-09)		0.0267 (1.00)
APC	160 (71%)	64	0.351 (1.00)	0.404 (1.00)	0.0159 (1.00)	0.0753 (1.00)	0.108 (1.00)	0.66 (1.00)	0.627 (1.00)	0.191 (1.00)	0.938 (1.00)		0.949 (1.00)
FBXW7	38 (17%)	186	0.729 (1.00)	0.0555 (1.00)	0.341 (1.00)	0.374 (1.00)	0.0159 (1.00)	0.00407 (0.809)	0.952 (1.00)	0.0342 (1.00)	0.845 (1.00)		0.0568 (1.00)
NRAS	20 (9%)	204	0.0728 (1.00)	0.0434 (1.00)	0.8 (1.00)	0.0365 (1.00)	1 (1.00)	0.541 (1.00)	0.00667 (1.00)	0.469 (1.00)	0.0262 (1.00)		0.404 (1.00)
KRAS	96 (43%)	128	0.0211 (1.00)	0.113 (1.00)	0.027 (1.00)	0.685 (1.00)	0.0731 (1.00)	0.171 (1.00)	0.4 (1.00)	0.0373 (1.00)	0.204 (1.00)		0.741 (1.00)
SMAD4	26 (12%)	198	0.784 (1.00)	0.987 (1.00)	1 (1.00)	0.837 (1.00)	0.00657 (1.00)	0.795 (1.00)	0.995 (1.00)	0.83 (1.00)	0.326 (1.00)		0.97 (1.00)
FAM123B	25 (11%)	199	0.641 (1.00)	0.863 (1.00)	0.5 (1.00)	1 (1.00)	0.736 (1.00)	0.781 (1.00)	0.755 (1.00)	0.645 (1.00)	0.492 (1.00)		0.89 (1.00)
SMAD2	15 (7%)	209	0.863 (1.00)	0.713 (1.00)	0.779 (1.00)	0.293 (1.00)	0.465 (1.00)	1 (1.00)	0.7 (1.00)	0.746 (1.00)	0.0351 (1.00)		0.00252 (0.504)
TCF7L2	18 (8%)	206	0.28 (1.00)	0.404 (1.00)	0.785 (1.00)	0.624 (1.00)	0.439 (1.00)	0.736 (1.00)	0.0281 (1.00)	0.573 (1.00)	0.112 (1.00)		0.862 (1.00)
SOX9	10 (4%)	214	0.575 (1.00)	0.266 (1.00)	0.29 (1.00)	0.525 (1.00)	0.58 (1.00)	1 (1.00)	0.98 (1.00)	1 (1.00)	0.208 (1.00)		0.321 (1.00)
ELF3	6 (3%)	218	0.698 (1.00)	0.202 (1.00)	0.374 (1.00)	0.685 (1.00)	0.84 (1.00)	1 (1.00)	0.999 (1.00)	0.593 (1.00)	0.624 (1.00)		0.974 (1.00)
TNFRSF10C	6 (3%)	218		0.838 (1.00)	0.181 (1.00)	0.685 (1.00)	0.394 (1.00)	0.0634 (1.00)	0.614 (1.00)	0.0793 (1.00)	0.183 (1.00)		0.331 (1.00)
KIAA1804	15 (7%)	209	0.279 (1.00)	0.799 (1.00)	0.0177 (1.00)	0.425 (1.00)	0.0245 (1.00)	1 (1.00)	0.803 (1.00)	0.746 (1.00)	0.0135 (1.00)		0.846 (1.00)
ACOT4	3 (1%)	221		0.0265 (1.00)	0.555 (1.00)	1 (1.00)	0.398 (1.00)	0.375 (1.00)	0.97 (1.00)	0.36 (1.00)	0.651 (1.00)		0.986 (1.00)
PTEN	7 (3%)	217	0.535 (1.00)	0.0301 (1.00)	0.44 (1.00)	0.712 (1.00)	0.26 (1.00)	1 (1.00)	0.994 (1.00)	0.593 (1.00)	0.142 (1.00)		0.242 (1.00)
MYO1B	13 (6%)	211	0.354 (1.00)	0.632 (1.00)	1 (1.00)	0.777 (1.00)	0.364 (1.00)	0.267 (1.00)	0.861 (1.00)	0.458 (1.00)	0.126 (1.00)		0.258 (1.00)

'BRAF MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.88e-06 (Fisher's exact test), Q value = 0.00038

Table S1. Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	COLON ADENOCARCINOMA	COLON MUCINOUS ADENOCARCINOMA	RECTAL ADENOCARCINOMA	RECTAL MUCINOUS ADENOCARCINOMA
ALL	129	24	57	8
BRAF MUTATED	9	11	1	1
BRAF WILD-TYPE	120	13	56	7

Figure S1. Get High-res Image Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000232 (Fisher's exact test), Q value = 0.047

Table S2. Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	COLON ADENOCARCINOMA	COLON MUCINOUS ADENOCARCINOMA	RECTAL ADENOCARCINOMA	RECTAL MUCINOUS ADENOCARCINOMA
ALL	129	24	57	8
TP53 MUTATED	68	5	41	4
TP53 WILD-TYPE	61	19	16	4

Figure S2. Get High-res Image Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'PIK3CA MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 1.35e-05 (t-test), Q value = 0.0027

Table S3. Gene #9: 'PIK3CA MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	223	2.2 (4.8)
PIK3CA MUTATED	33	0.5 (1.4)
PIK3CA WILD-TYPE	190	2.5 (5.1)

Figure S3. Get High-res Image Gene #9: 'PIK3CA MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'ACVR2A MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 4.2e-08 (t-test), Q value = 8.6e-06

Table S4. Gene #12: 'ACVR2A MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	223	2.2 (4.8)
ACVR2A MUTATED	9	0.2 (0.4)
ACVR2A WILD-TYPE	214	2.3 (4.9)

Figure S4. Get High-res Image Gene #12: 'ACVR2A MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'CRTC1 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000496 (t-test), Q value = 0.1

Table S5. Gene #15: 'CRTC1 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	223	2.2 (4.8)
CRTC1 MUTATED	6	0.3 (0.8)
CRTC1 WILD-TYPE	217	2.3 (4.9)

Figure S5. Get High-res Image Gene #15: 'CRTC1 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'KRTAP5-5 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 3.24e-11 (t-test), Q value = 6.7e-09

Table S6. Gene #17: 'KRTAP5-5 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	223	2.2 (4.8)
KRTAP5-5 MUTATED	4	0.0 (0.0)
KRTAP5-5 WILD-TYPE	219	2.3 (4.8)

Figure S6. Get High-res Image Gene #17: 'KRTAP5-5 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

Methods & Data

Input

Mutation data file = COADREAD-TP.mutsig.cluster.txt
Clinical data file = COADREAD-TP.clin.merged.picked.txt
Number of patients = 224
Number of significantly mutated genes = 21
Number of selected clinical features = 11
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)

Made with Nozzle