Correlation between gene mutation status and molecular subtypes

Colorectal 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 molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C19G5K3Z

Overview

Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.

Summary

Testing the association between mutation status of 24 genes and 8 molecular subtypes across 223 patients, 9 significant findings detected with P value < 0.05 and Q value < 0.25.

FBXW7 mutation correlated to 'CN_CNMF'.
BRAF mutation correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', and 'CN_CNMF'.
KRAS mutation correlated to 'MRNA_CNMF' and 'MRNA_CHIERARCHICAL'.
TP53 mutation correlated to 'MRNA_CHIERARCHICAL' and 'CN_CNMF'.
PIK3CA mutation correlated to 'CN_CNMF'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 24 genes and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 9 significant findings detected.


		Clinical Features	MRNA CNMF	MRNA CHIERARCHICAL	CN CNMF	METHLYATION CNMF	RPPA CNMF	RPPA CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL
	nMutated (%)	nWild-Type	Fisher's exact 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	Fisher's exact test
BRAF	22 (10%)	201	9.13e-07 (0.000147)	2.31e-08 (3.74e-06)	9.56e-05 (0.015)		0.482 (1.00)	0.304 (1.00)	1 (1.00)	0.684 (1.00)
KRAS	96 (43%)	127	7.45e-05 (0.0118)	4.05e-05 (0.00644)	0.43 (1.00)	0.107 (1.00)	0.572 (1.00)	1 (1.00)	0.0218 (1.00)	0.0431 (1.00)
TP53	119 (53%)	104	0.00202 (0.311)	0.000482 (0.0752)	2.01e-12 (3.28e-10)		0.568 (1.00)	0.782 (1.00)	0.0307 (1.00)	0.567 (1.00)
FBXW7	38 (17%)	185	0.0592 (1.00)	0.0437 (1.00)	0.000494 (0.0766)		0.0112 (1.00)	0.0362 (1.00)	0.416 (1.00)	0.156 (1.00)
PIK3CA	33 (15%)	190	0.205 (1.00)	0.57 (1.00)	2.13e-05 (0.00341)		0.062 (1.00)	0.129 (1.00)	0.165 (1.00)	1 (1.00)
APC	160 (72%)	63	0.0076 (1.00)	0.0267 (1.00)	0.072 (1.00)		0.467 (1.00)	0.452 (1.00)	0.34 (1.00)	0.837 (1.00)
NRAS	20 (9%)	203	0.0465 (1.00)	0.125 (1.00)	0.0957 (1.00)		0.909 (1.00)	0.474 (1.00)	0.268 (1.00)	1 (1.00)
SMAD4	26 (12%)	197	0.0308 (1.00)	0.288 (1.00)	0.128 (1.00)		0.859 (1.00)	0.339 (1.00)	1 (1.00)	1 (1.00)
FAM123B	25 (11%)	198	0.0723 (1.00)	0.0918 (1.00)	0.00558 (0.843)		0.344 (1.00)	0.588 (1.00)	1 (1.00)	1 (1.00)
SMAD2	15 (7%)	208	0.133 (1.00)	0.518 (1.00)	0.353 (1.00)		0.592 (1.00)	0.133 (1.00)	1 (1.00)	1 (1.00)
TCF7L2	18 (8%)	205	1 (1.00)	0.413 (1.00)	0.00723 (1.00)		0.836 (1.00)	0.896 (1.00)	1 (1.00)	1 (1.00)
ACVR2A	9 (4%)	214	0.00717 (1.00)	0.184 (1.00)	0.0207 (1.00)		0.0952 (1.00)	0.469 (1.00)	0.173 (1.00)	1 (1.00)
SOX9	10 (4%)	213	0.129 (1.00)	0.123 (1.00)	0.00502 (0.763)		0.189 (1.00)	0.694 (1.00)	1 (1.00)	1 (1.00)
ELF3	6 (3%)	217	0.363 (1.00)	0.811 (1.00)	0.521 (1.00)		0.544 (1.00)	0.436 (1.00)	1 (1.00)	1 (1.00)
CRTC1	6 (3%)	217	0.123 (1.00)	0.165 (1.00)	0.898 (1.00)		0.175 (1.00)	0.482 (1.00)	1 (1.00)	1 (1.00)
TNFRSF10C	6 (3%)	217	0.317 (1.00)	0.287 (1.00)	0.165 (1.00)		0.278 (1.00)	0.378 (1.00)	1 (1.00)	1 (1.00)
KIAA1804	15 (7%)	208	0.267 (1.00)	0.397 (1.00)	0.0789 (1.00)		0.506 (1.00)	0.474 (1.00)	1 (1.00)	1 (1.00)
KRTAP5-5	4 (2%)	219	0.327 (1.00)	0.482 (1.00)	0.849 (1.00)		0.385 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
PTEN	7 (3%)	216	0.0276 (1.00)	0.337 (1.00)	0.0517 (1.00)		0.544 (1.00)	0.436 (1.00)	0.347 (1.00)	0.298 (1.00)
ACOT4	3 (1%)	220	0.255 (1.00)	0.49 (1.00)	0.515 (1.00)				1 (1.00)	1 (1.00)
MYO1B	13 (6%)	210	0.00862 (1.00)	0.00879 (1.00)	0.00463 (0.709)		0.0215 (1.00)	0.469 (1.00)	1 (1.00)	1 (1.00)
PCBP1	6 (3%)	217	0.234 (1.00)	0.811 (1.00)	0.707 (1.00)		0.648 (1.00)	0.482 (1.00)	1 (1.00)	1 (1.00)
GGT1	3 (1%)	220			0.175 (1.00)				1 (1.00)	1 (1.00)
ACVR1B	14 (6%)	209	0.374 (1.00)	0.316 (1.00)	0.0924 (1.00)		0.735 (1.00)	0.376 (1.00)	0.581 (1.00)	1 (1.00)

'FBXW7 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000494 (Fisher's exact test), Q value = 0.077

Table S1. Gene #2: 'FBXW7 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	77	82	56	5
FBXW7 MUTATED	4	24	9	1
FBXW7 WILD-TYPE	73	58	47	4

Figure S1. Get High-res Image Gene #2: 'FBXW7 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'BRAF MUTATION STATUS' versus 'MRNA_CNMF'

P value = 9.13e-07 (Fisher's exact test), Q value = 0.00015

Table S2. Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	42	57	67	39
BRAF MUTATED	13	1	1	5
BRAF WILD-TYPE	29	56	66	34

Figure S2. Get High-res Image Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

'BRAF MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 2.31e-08 (Fisher's exact test), Q value = 3.7e-06

Table S3. Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	40	48	61	56
BRAF MUTATED	1	0	18	1
BRAF WILD-TYPE	39	48	43	55

Figure S3. Get High-res Image Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'BRAF MUTATION STATUS' versus 'CN_CNMF'

P value = 9.56e-05 (Fisher's exact test), Q value = 0.015

Table S4. Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	77	82	56	5
BRAF MUTATED	1	18	3	0
BRAF WILD-TYPE	76	64	53	5

Figure S4. Get High-res Image Gene #4: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'KRAS MUTATION STATUS' versus 'MRNA_CNMF'

P value = 7.45e-05 (Fisher's exact test), Q value = 0.012

Table S5. Gene #5: 'KRAS MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	42	57	67	39
KRAS MUTATED	13	14	31	27
KRAS WILD-TYPE	29	43	36	12

Figure S5. Get High-res Image Gene #5: 'KRAS MUTATION STATUS' versus Clinical Feature #1: 'MRNA_CNMF'

'KRAS MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 4.05e-05 (Fisher's exact test), Q value = 0.0064

Table S6. Gene #5: 'KRAS MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	40	48	61	56
KRAS MUTATED	10	33	26	16
KRAS WILD-TYPE	30	15	35	40

Figure S6. Get High-res Image Gene #5: 'KRAS MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'MRNA_CHIERARCHICAL'

P value = 0.000482 (Fisher's exact test), Q value = 0.075

Table S7. Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	40	48	61	56
TP53 MUTATED	30	19	25	36
TP53 WILD-TYPE	10	29	36	20

Figure S7. Get High-res Image Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 2.01e-12 (Fisher's exact test), Q value = 3.3e-10

Table S8. Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	77	82	56	5
TP53 MUTATED	61	19	35	2
TP53 WILD-TYPE	16	63	21	3

Figure S8. Get High-res Image Gene #6: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

'PIK3CA MUTATION STATUS' versus 'CN_CNMF'

P value = 2.13e-05 (Fisher's exact test), Q value = 0.0034

Table S9. Gene #9: 'PIK3CA MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	77	82	56	5
PIK3CA MUTATED	4	23	3	2
PIK3CA WILD-TYPE	73	59	53	3

Figure S9. Get High-res Image Gene #9: 'PIK3CA MUTATION STATUS' versus Clinical Feature #3: 'CN_CNMF'

Methods & Data

Input

Mutation data file = COADREAD-TP.mutsig.cluster.txt
Molecular subtypes file = COADREAD-TP.transferedmergedcluster.txt
Number of patients = 223
Number of significantly mutated genes = 24
Number of Molecular subtypes = 8
Exclude genes that fewer than K tumors have mutations, K = 3

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] 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)

[2] 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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