Correlation between gene mutation status and selected clinical features

Stomach Adenocarcinoma (Primary solid tumor)

23 May 2013 | analyses__2013_05_23

Maintainer Information

Citation Information

doi:10.7908/C1988532

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/C1988532

Overview

Introduction

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

Summary

Testing the association between mutation status of 24 genes and 11 clinical features across 156 patients, 7 significant findings detected with Q value < 0.25.

TRIM48 mutation correlated to 'AGE' and 'NUMBER.OF.LYMPH.NODES'.
B2M mutation correlated to 'NEOPLASM.DISEASESTAGE'.
RNF43 mutation correlated to 'HISTOLOGICAL.TYPE'.
WSB2 mutation correlated to 'AGE', 'NUMBER.OF.LYMPH.NODES', and 'NEOPLASM.DISEASESTAGE'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 24 genes and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 7 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	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	Chi-square test	Fisher's exact test	Fisher's exact test	Chi-square test	Fisher's exact test	t-test	t-test	Chi-square test
WSB2	6 (4%)	150	0.255 (1.00)	1.76e-05 (0.00418)	0.402 (1.00)	0.152 (1.00)	1 (1.00)	0.401 (1.00)	0.594 (1.00)	0.799 (1.00)	1.63e-05 (0.00387)		0.000283 (0.0665)
TRIM48	11 (7%)	145	0.268 (1.00)	0.000832 (0.195)	0.527 (1.00)	0.71 (1.00)	0.36 (1.00)	0.812 (1.00)	0.711 (1.00)	0.598 (1.00)	1.37e-09 (3.28e-07)		0.0919 (1.00)
B2M	6 (4%)	150	0.65 (1.00)	0.595 (1.00)	0.222 (1.00)	0.775 (1.00)	1 (1.00)	0.401 (1.00)	0.505 (1.00)	0.799 (1.00)	0.0835 (1.00)		0.000878 (0.205)
RNF43	6 (4%)	150	0.00613 (1.00)	0.0653 (1.00)	0.222 (1.00)	0.000126 (0.0298)	1 (1.00)	0.401 (1.00)	0.456 (1.00)	0.178 (1.00)	0.455 (1.00)		0.611 (1.00)
PGM5	15 (10%)	141	0.391 (1.00)	0.00286 (0.657)	0.0496 (1.00)	0.843 (1.00)	0.46 (1.00)	1 (1.00)	0.396 (1.00)	0.623 (1.00)	0.964 (1.00)		0.00684 (1.00)
KRAS	16 (10%)	140	0.34 (1.00)	0.252 (1.00)	0.0652 (1.00)	0.336 (1.00)	1 (1.00)	1 (1.00)	0.604 (1.00)	0.0196 (1.00)	0.0271 (1.00)		0.101 (1.00)
CBWD1	18 (12%)	138	0.271 (1.00)	0.0466 (1.00)	0.0211 (1.00)	0.0858 (1.00)	0.527 (1.00)	1 (1.00)	0.555 (1.00)	0.84 (1.00)	0.00515 (1.00)		0.593 (1.00)
TP53	74 (47%)	82	0.113 (1.00)	0.977 (1.00)	0.253 (1.00)	0.0793 (1.00)	0.424 (1.00)	0.0612 (1.00)	0.896 (1.00)	0.136 (1.00)	0.922 (1.00)		0.651 (1.00)
PIK3CA	35 (22%)	121	0.685 (1.00)	0.0933 (1.00)	0.845 (1.00)	0.917 (1.00)	1 (1.00)	0.403 (1.00)	0.512 (1.00)	0.402 (1.00)	0.411 (1.00)		0.417 (1.00)
ARID1A	29 (19%)	127	0.0844 (1.00)	0.22 (1.00)	0.403 (1.00)	0.554 (1.00)	0.594 (1.00)	0.045 (1.00)	0.307 (1.00)	0.139 (1.00)	0.266 (1.00)		0.08 (1.00)
SMAD4	11 (7%)	145	0.116 (1.00)	0.283 (1.00)	0.527 (1.00)	0.84 (1.00)	1 (1.00)	0.812 (1.00)	0.567 (1.00)	0.271 (1.00)	0.872 (1.00)		0.727 (1.00)
RHOA	10 (6%)	146	0.139 (1.00)	0.0122 (1.00)	0.741 (1.00)	0.253 (1.00)	1 (1.00)	1 (1.00)	0.652 (1.00)	0.817 (1.00)	0.553 (1.00)		0.386 (1.00)
MXRA8	7 (4%)	149	0.361 (1.00)	0.212 (1.00)	0.441 (1.00)	0.958 (1.00)	1 (1.00)	0.0458 (1.00)	0.672 (1.00)	0.615 (1.00)	0.888 (1.00)		0.00257 (0.594)
IRF2	11 (7%)	145	0.845 (1.00)	0.403 (1.00)	0.353 (1.00)	0.885 (1.00)	1 (1.00)	0.511 (1.00)	0.427 (1.00)	0.0322 (1.00)	0.0214 (1.00)		0.682 (1.00)
CDH1	14 (9%)	142	0.489 (1.00)	0.0536 (1.00)	1 (1.00)	0.109 (1.00)	1 (1.00)	0.603 (1.00)	0.787 (1.00)	0.27 (1.00)	0.894 (1.00)		0.186 (1.00)
PTEN	11 (7%)	145	0.588 (1.00)	0.0266 (1.00)	0.0291 (1.00)	0.657 (1.00)	1 (1.00)	0.511 (1.00)	0.32 (1.00)	0.101 (1.00)	0.634 (1.00)		0.556 (1.00)
FBXW7	11 (7%)	145	0.659 (1.00)	0.0618 (1.00)	0.353 (1.00)	0.71 (1.00)	0.36 (1.00)	0.659 (1.00)	0.385 (1.00)	0.294 (1.00)	0.0998 (1.00)		0.572 (1.00)
PTH2	4 (3%)	152	0.514 (1.00)	0.658 (1.00)	0.304 (1.00)	0.899 (1.00)	1 (1.00)	1 (1.00)	0.143 (1.00)	1 (1.00)	0.779 (1.00)		0.234 (1.00)
FAM46D	5 (3%)	151	0.361 (1.00)	0.742 (1.00)	0.649 (1.00)	0.906 (1.00)	1 (1.00)	1 (1.00)	0.926 (1.00)	0.769 (1.00)	0.6 (1.00)		0.423 (1.00)
APC	25 (16%)	131	0.117 (1.00)	0.00959 (1.00)	1 (1.00)	0.56 (1.00)	0.59 (1.00)	0.9 (1.00)	0.284 (1.00)	0.608 (1.00)	0.544 (1.00)		0.142 (1.00)
MAP2K7	9 (6%)	147	0.16 (1.00)	0.0891 (1.00)	0.159 (1.00)	0.859 (1.00)	1 (1.00)	1 (1.00)	0.737 (1.00)	0.693 (1.00)	0.714 (1.00)		0.896 (1.00)
BCOR	13 (8%)	143	0.185 (1.00)	0.625 (1.00)	0.563 (1.00)	0.938 (1.00)	1 (1.00)	0.0963 (1.00)	0.82 (1.00)	0.348 (1.00)	0.801 (1.00)		0.604 (1.00)
TRPS1	22 (14%)	134	0.244 (1.00)	0.206 (1.00)	0.164 (1.00)	0.699 (1.00)	0.596 (1.00)	0.2 (1.00)	0.951 (1.00)	0.435 (1.00)	0.269 (1.00)		0.106 (1.00)
IAPP	4 (3%)	152		0.427 (1.00)	0.648 (1.00)	0.986 (1.00)	1 (1.00)	0.27 (1.00)	0.787 (1.00)	0.365 (1.00)	0.00164 (0.381)		0.394 (1.00)

'TRIM48 MUTATION STATUS' versus 'AGE'

P value = 0.000832 (t-test), Q value = 0.19

Table S1. Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	151	67.4 (10.8)
TRIM48 MUTATED	10	77.7 (7.3)
TRIM48 WILD-TYPE	141	66.7 (10.7)

Figure S1. Get High-res Image Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TRIM48 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 1.37e-09 (t-test), Q value = 3.3e-07

Table S2. Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	135	5.0 (6.9)
TRIM48 MUTATED	9	0.8 (0.8)
TRIM48 WILD-TYPE	126	5.3 (7.1)

Figure S2. Get High-res Image Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'B2M MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000878 (Chi-square test), Q value = 0.2

Table S3. Gene #14: 'B2M MUTATION STATUS' versus Clinical Feature #11: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE IA	STAGE IB	STAGE II	STAGE IIA	STAGE IIB	STAGE III	STAGE IIIA	STAGE IIIB	STAGE IIIC	STAGE IV
ALL	1	5	16	27	7	10	4	30	12	6	23
B2M MUTATED	1	1	0	2	0	0	0	0	1	0	1
B2M WILD-TYPE	0	4	16	25	7	10	4	30	11	6	22

Figure S3. Get High-res Image Gene #14: 'B2M MUTATION STATUS' versus Clinical Feature #11: 'NEOPLASM.DISEASESTAGE'

'RNF43 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000126 (Chi-square test), Q value = 0.03

Table S4. Gene #18: 'RNF43 MUTATION STATUS' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'

nPatients	STOMACH ADENOCARCINOMA DIFFUSE TYPE	STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS)	STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS)	STOMACH INTESTINAL ADENOCARCINOMA TUBULAR TYPE	STOMACH INTESTINAL ADENOCARCINOMA MUCINOUS TYPE	STOMACH INTESTINAL ADENOCARCINOMA PAPILLARY TYPE	STOMACH ADENOCARCINOMA SIGNET RING TYPE
ALL	23	78	30	10	10	3	1
RNF43 MUTATED	0	3	2	0	0	0	1
RNF43 WILD-TYPE	23	75	28	10	10	3	0

Figure S4. Get High-res Image Gene #18: 'RNF43 MUTATION STATUS' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'

'WSB2 MUTATION STATUS' versus 'AGE'

P value = 1.76e-05 (t-test), Q value = 0.0042

Table S5. Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	151	67.4 (10.8)
WSB2 MUTATED	6	83.3 (4.0)
WSB2 WILD-TYPE	145	66.8 (10.5)

Figure S5. Get High-res Image Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'WSB2 MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'

P value = 1.63e-05 (t-test), Q value = 0.0039

Table S6. Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	135	5.0 (6.9)
WSB2 MUTATED	6	1.0 (1.3)
WSB2 WILD-TYPE	129	5.2 (7.0)

Figure S6. Get High-res Image Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'WSB2 MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000283 (Chi-square test), Q value = 0.066

Table S7. Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #11: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE IA	STAGE IB	STAGE II	STAGE IIA	STAGE IIB	STAGE III	STAGE IIIA	STAGE IIIB	STAGE IIIC	STAGE IV
ALL	1	5	16	27	7	10	4	30	12	6	23
WSB2 MUTATED	1	1	1	3	0	0	0	0	0	0	0
WSB2 WILD-TYPE	0	4	15	24	7	10	4	30	12	6	23

Figure S7. Get High-res Image Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #11: 'NEOPLASM.DISEASESTAGE'

Methods & Data

Input

Mutation data file = STAD-TP.mutsig.cluster.txt
Clinical data file = STAD-TP.clin.merged.picked.txt
Number of patients = 156
Number of significantly mutated genes = 24
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)

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