Correlation between gene mutation status and selected clinical features

Stomach 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/C1XD101D

Overview

Introduction

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

Summary

Testing the association between mutation status of 26 genes and 11 clinical features across 219 patients, 7 significant findings detected with Q value < 0.25.

TRIM48 mutation correlated to 'AGE' and 'NUMBER.OF.LYMPH.NODES'.
MXRA8 mutation correlated to 'NEOPLASM.DISEASESTAGE'.
B2M mutation correlated to 'NEOPLASM.DISEASESTAGE'.
RNF43 mutation correlated to 'HISTOLOGICAL.TYPE'.
WSB2 mutation correlated to 'NEOPLASM.DISEASESTAGE' and 'NUMBER.OF.LYMPH.NODES'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 26 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	NEOPLASM DISEASESTAGE	PATHOLOGY T STAGE	PATHOLOGY N STAGE	PATHOLOGY M STAGE	GENDER	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	COMPLETENESS OF RESECTION	NUMBER OF LYMPH NODES
	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	Chi-square test	Fisher's exact test	Fisher's exact test	t-test
TRIM48	14 (6%)	205	0.818 (1.00)	0.000333 (0.0936)	0.153 (1.00)	0.097 (1.00)	0.378 (1.00)	0.612 (1.00)	0.786 (1.00)	0.589 (1.00)	0.33 (1.00)	0.374 (1.00)	0.000292 (0.0823)
WSB2	7 (3%)	212	0.664 (1.00)	0.0177 (1.00)	6.64e-05 (0.0189)	0.0135 (1.00)	0.311 (1.00)	0.325 (1.00)	0.248 (1.00)	0.257 (1.00)	1 (1.00)	1 (1.00)	3.68e-07 (0.000105)
MXRA8	10 (5%)	209	0.141 (1.00)	0.185 (1.00)	0.000499 (0.14)	0.0783 (1.00)	0.646 (1.00)	0.319 (1.00)	0.523 (1.00)	0.915 (1.00)	1 (1.00)	0.505 (1.00)	0.723 (1.00)
B2M	8 (4%)	211	0.452 (1.00)	0.355 (1.00)	0.000154 (0.0438)	0.283 (1.00)	0.732 (1.00)	0.372 (1.00)	0.716 (1.00)	0.498 (1.00)	1 (1.00)	1 (1.00)	0.506 (1.00)
RNF43	9 (4%)	210	0.0337 (1.00)	0.277 (1.00)	0.069 (1.00)	0.102 (1.00)	0.107 (1.00)	0.417 (1.00)	0.16 (1.00)	0.000256 (0.0726)	1 (1.00)	0.196 (1.00)	0.49 (1.00)
PIK3CA	48 (22%)	171	0.735 (1.00)	0.476 (1.00)	0.219 (1.00)	0.478 (1.00)	0.904 (1.00)	0.215 (1.00)	0.868 (1.00)	0.863 (1.00)	1 (1.00)	0.474 (1.00)	0.226 (1.00)
PGM5	22 (10%)	197	0.955 (1.00)	0.0233 (1.00)	0.0232 (1.00)	0.0149 (1.00)	0.891 (1.00)	0.745 (1.00)	0.00546 (1.00)	0.925 (1.00)	0.474 (1.00)	0.572 (1.00)	0.986 (1.00)
KRAS	25 (11%)	194	0.436 (1.00)	0.47 (1.00)	0.0676 (1.00)	0.775 (1.00)	0.5 (1.00)	1 (1.00)	0.0317 (1.00)	0.29 (1.00)	1 (1.00)	0.0265 (1.00)	0.0772 (1.00)
CBWD1	28 (13%)	191	0.348 (1.00)	0.0252 (1.00)	0.686 (1.00)	0.249 (1.00)	0.654 (1.00)	0.882 (1.00)	0.0219 (1.00)	0.0648 (1.00)	0.564 (1.00)	0.84 (1.00)	0.066 (1.00)
TP53	98 (45%)	121	0.183 (1.00)	0.665 (1.00)	0.75 (1.00)	0.492 (1.00)	0.864 (1.00)	0.0424 (1.00)	0.677 (1.00)	0.159 (1.00)	0.411 (1.00)	0.203 (1.00)	0.639 (1.00)
ARID1A	41 (19%)	178	0.224 (1.00)	0.294 (1.00)	0.277 (1.00)	0.135 (1.00)	0.42 (1.00)	0.133 (1.00)	0.597 (1.00)	0.326 (1.00)	0.597 (1.00)	0.242 (1.00)	0.263 (1.00)
SMAD4	19 (9%)	200	0.0325 (1.00)	0.377 (1.00)	0.759 (1.00)	1 (1.00)	0.783 (1.00)	0.585 (1.00)	0.625 (1.00)	0.837 (1.00)	1 (1.00)	0.439 (1.00)	0.438 (1.00)
RHOA	13 (6%)	206	0.828 (1.00)	0.291 (1.00)	0.775 (1.00)	0.87 (1.00)	0.744 (1.00)	1 (1.00)	0.572 (1.00)	0.4 (1.00)	1 (1.00)	0.783 (1.00)	0.268 (1.00)
IRF2	15 (7%)	204	0.96 (1.00)	0.8 (1.00)	0.339 (1.00)	0.112 (1.00)	0.501 (1.00)	0.645 (1.00)	0.593 (1.00)	0.763 (1.00)	1 (1.00)	0.0267 (1.00)	0.11 (1.00)
CDH1	18 (8%)	201	0.571 (1.00)	0.111 (1.00)	0.408 (1.00)	0.395 (1.00)	0.465 (1.00)	0.69 (1.00)	0.624 (1.00)	0.358 (1.00)	1 (1.00)	0.191 (1.00)	0.386 (1.00)
PTEN	14 (6%)	205	0.78 (1.00)	0.0497 (1.00)	0.328 (1.00)	0.87 (1.00)	0.434 (1.00)	0.474 (1.00)	0.0208 (1.00)	0.733 (1.00)	1 (1.00)	0.0514 (1.00)	0.249 (1.00)
FBXW7	19 (9%)	200	0.598 (1.00)	0.312 (1.00)	0.753 (1.00)	0.0999 (1.00)	0.984 (1.00)	1 (1.00)	0.812 (1.00)	0.575 (1.00)	0.424 (1.00)	0.362 (1.00)	0.0394 (1.00)
PTH2	4 (2%)	215	0.485 (1.00)	0.488 (1.00)	0.588 (1.00)	0.623 (1.00)	0.22 (1.00)	1 (1.00)	0.304 (1.00)	0.886 (1.00)	1 (1.00)	1 (1.00)	0.712 (1.00)
FAM46D	6 (3%)	213	0.243 (1.00)	0.568 (1.00)	0.803 (1.00)	0.38 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.995 (1.00)	1 (1.00)	1 (1.00)	0.645 (1.00)
APC	33 (15%)	186	0.11 (1.00)	0.0504 (1.00)	0.268 (1.00)	0.4 (1.00)	0.366 (1.00)	0.654 (1.00)	0.704 (1.00)	0.516 (1.00)	0.594 (1.00)	0.278 (1.00)	0.722 (1.00)
MAP2K7	14 (6%)	205	0.33 (1.00)	0.119 (1.00)	0.518 (1.00)	0.14 (1.00)	0.356 (1.00)	1 (1.00)	0.415 (1.00)	0.824 (1.00)	1 (1.00)	0.693 (1.00)	0.758 (1.00)
BCOR	16 (7%)	203	0.0103 (1.00)	0.137 (1.00)	0.386 (1.00)	0.886 (1.00)	0.617 (1.00)	0.0995 (1.00)	1 (1.00)	0.993 (1.00)	1 (1.00)	0.178 (1.00)	0.513 (1.00)
TRPS1	30 (14%)	189	0.99 (1.00)	0.381 (1.00)	0.159 (1.00)	0.972 (1.00)	0.856 (1.00)	0.56 (1.00)	0.427 (1.00)	0.846 (1.00)	1 (1.00)	0.381 (1.00)	0.924 (1.00)
C13ORF33	6 (3%)	213	0.332 (1.00)	0.367 (1.00)	0.00174 (0.483)	0.134 (1.00)	0.0359 (1.00)	1 (1.00)	0.684 (1.00)	0.873 (1.00)	0.155 (1.00)	1 (1.00)	0.198 (1.00)
HRCT1	4 (2%)	215	0.537 (1.00)	0.123 (1.00)	0.362 (1.00)	0.372 (1.00)	0.156 (1.00)	1 (1.00)	1 (1.00)	0.941 (1.00)	1 (1.00)	1 (1.00)	0.254 (1.00)
IAPP	4 (2%)	215	0.858 (1.00)	0.355 (1.00)	0.312 (1.00)	0.52 (1.00)	0.629 (1.00)	0.181 (1.00)	1 (1.00)	0.966 (1.00)	1 (1.00)	0.158 (1.00)	0.00157 (0.438)

'TRIM48 MUTATION STATUS' versus 'AGE'

P value = 0.000333 (t-test), Q value = 0.094

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

	nPatients	Mean (Std.Dev)
ALL	214	66.5 (10.9)
TRIM48 MUTATED	13	75.8 (7.3)
TRIM48 WILD-TYPE	201	65.9 (10.8)

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 = 0.000292 (t-test), Q value = 0.082

Table S2. Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	191	5.2 (7.5)
TRIM48 MUTATED	12	1.7 (2.5)
TRIM48 WILD-TYPE	179	5.4 (7.6)

Figure S2. Get High-res Image Gene #1: 'TRIM48 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

'MXRA8 MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000499 (Chi-square test), Q value = 0.14

Table S3. Gene #10: 'MXRA8 MUTATION STATUS' versus Clinical Feature #3: '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	7	22	24	21	28	3	34	23	18	24
MXRA8 MUTATED	1	0	1	0	2	0	0	0	1	3	2
MXRA8 WILD-TYPE	0	7	21	24	19	28	3	34	22	15	22

Figure S3. Get High-res Image Gene #10: 'MXRA8 MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'B2M MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000154 (Chi-square test), Q value = 0.044

Table S4. Gene #15: 'B2M MUTATION STATUS' versus Clinical Feature #3: '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	7	22	24	21	28	3	34	23	18	24
B2M MUTATED	1	1	0	0	2	0	0	0	2	1	1
B2M WILD-TYPE	0	6	22	24	19	28	3	34	21	17	23

Figure S4. Get High-res Image Gene #15: 'B2M MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'RNF43 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000256 (Chi-square test), Q value = 0.073

Table S5. Gene #19: 'RNF43 MUTATION STATUS' versus Clinical Feature #8: '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	31	108	34	26	13	5	1
RNF43 MUTATED	0	5	2	1	0	0	1
RNF43 WILD-TYPE	31	103	32	25	13	5	0

Figure S5. Get High-res Image Gene #19: 'RNF43 MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'WSB2 MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 6.64e-05 (Chi-square test), Q value = 0.019

Table S6. Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #3: '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	7	22	24	21	28	3	34	23	18	24
WSB2 MUTATED	1	1	1	2	1	0	0	0	1	0	0
WSB2 WILD-TYPE	0	6	21	22	20	28	3	34	22	18	24

Figure S6. Get High-res Image Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

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

P value = 3.68e-07 (t-test), Q value = 0.00011

Table S7. Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	191	5.2 (7.5)
WSB2 MUTATED	7	1.0 (1.2)
WSB2 WILD-TYPE	184	5.3 (7.6)

Figure S7. Get High-res Image Gene #21: 'WSB2 MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Methods & Data

Input

Mutation data file = STAD-TP.mutsig.cluster.txt
Clinical data file = STAD-TP.clin.merged.picked.txt
Number of patients = 219
Number of significantly mutated genes = 26
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

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)

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