Correlation between gene mutation status and molecular subtypes

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 molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1GQ6VR4

Overview

Introduction

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

Summary

Testing the association between mutation status of 21 genes and 8 molecular subtypes across 224 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 21 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%)	202	9.13e-07 (0.000131)	2.31e-08 (3.35e-06)	4.17e-05 (0.00592)		0.215 (1.00)	0.304 (1.00)	0.6 (1.00)	1 (1.00)
KRAS	96 (43%)	128	7.45e-05 (0.0105)	4.05e-05 (0.00579)	0.485 (1.00)	0.257 (1.00)	0.634 (1.00)	1 (1.00)	0.0688 (1.00)	0.735 (1.00)
TP53	120 (54%)	104	0.00202 (0.276)	0.000482 (0.0668)	7.28e-11 (1.06e-08)		0.453 (1.00)	0.782 (1.00)	0.0252 (1.00)	0.134 (1.00)
FBXW7	38 (17%)	186	0.0592 (1.00)	0.0437 (1.00)	0.000122 (0.0171)		0.00881 (1.00)	0.0362 (1.00)	0.356 (1.00)	0.118 (1.00)
PIK3CA	33 (15%)	191	0.205 (1.00)	0.57 (1.00)	0.00048 (0.0668)		0.0876 (1.00)	0.129 (1.00)	0.0853 (1.00)	1 (1.00)
APC	160 (71%)	64	0.0076 (1.00)	0.0267 (1.00)	0.221 (1.00)		0.653 (1.00)	0.452 (1.00)	0.689 (1.00)	0.464 (1.00)
NRAS	20 (9%)	204	0.0465 (1.00)	0.125 (1.00)	0.274 (1.00)		0.247 (1.00)	0.474 (1.00)	1 (1.00)	1 (1.00)
SMAD4	26 (12%)	198	0.0308 (1.00)	0.288 (1.00)	0.0355 (1.00)		0.521 (1.00)	0.339 (1.00)	1 (1.00)	0.846 (1.00)
FAM123B	25 (11%)	199	0.0723 (1.00)	0.0918 (1.00)	0.00539 (0.728)		0.536 (1.00)	0.588 (1.00)	1 (1.00)	0.459 (1.00)
SMAD2	15 (7%)	209	0.133 (1.00)	0.518 (1.00)	0.0393 (1.00)		0.533 (1.00)	0.133 (1.00)	1 (1.00)	0.711 (1.00)
TCF7L2	18 (8%)	206	1 (1.00)	0.413 (1.00)	0.417 (1.00)		0.737 (1.00)	0.896 (1.00)	1 (1.00)	0.23 (1.00)
ACVR2A	9 (4%)	215	0.00717 (0.961)	0.184 (1.00)	0.0325 (1.00)		0.429 (1.00)	0.469 (1.00)	1 (1.00)	0.545 (1.00)
SOX9	10 (4%)	214	0.129 (1.00)	0.123 (1.00)	0.00451 (0.613)		0.204 (1.00)	0.694 (1.00)	1 (1.00)	0.584 (1.00)
ELF3	6 (3%)	218	0.363 (1.00)	0.811 (1.00)	0.0514 (1.00)		0.612 (1.00)	0.436 (1.00)	1 (1.00)	0.406 (1.00)
CRTC1	6 (3%)	218	0.123 (1.00)	0.165 (1.00)	0.837 (1.00)		0.209 (1.00)	0.482 (1.00)	1 (1.00)	0.406 (1.00)
TNFRSF10C	6 (3%)	218	0.317 (1.00)	0.287 (1.00)	0.675 (1.00)		0.853 (1.00)	0.378 (1.00)	1 (1.00)	1 (1.00)
KRTAP5-5	4 (2%)	220	0.327 (1.00)	0.482 (1.00)	0.48 (1.00)		0.388 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
KIAA1804	15 (7%)	209	0.267 (1.00)	0.397 (1.00)	0.0659 (1.00)		0.758 (1.00)	0.474 (1.00)	1 (1.00)	0.736 (1.00)
ACOT4	3 (1%)	221	0.255 (1.00)	0.49 (1.00)	0.829 (1.00)				1 (1.00)	1 (1.00)
PTEN	7 (3%)	217	0.0276 (1.00)	0.337 (1.00)	0.0429 (1.00)		0.612 (1.00)	0.436 (1.00)	0.244 (1.00)	0.0575 (1.00)
MYO1B	13 (6%)	211	0.00862 (1.00)	0.00879 (1.00)	0.00752 (1.00)		0.013 (1.00)	0.469 (1.00)	1 (1.00)	0.653 (1.00)

'FBXW7 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000122 (Fisher's exact test), Q value = 0.017

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	86	83	36	16
FBXW7 MUTATED	4	24	8	2
FBXW7 WILD-TYPE	82	59	28	14

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 = 0.00013

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 = 3.3e-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 = 4.17e-05 (Fisher's exact test), Q value = 0.0059

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	86	83	36	16
BRAF MUTATED	1	18	3	0
BRAF WILD-TYPE	85	65	33	16

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 = 0.01

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 = 0.0058

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 = 0.067

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 = 7.28e-11 (Fisher's exact test), Q value = 1.1e-08

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	86	83	36	16
TP53 MUTATED	68	22	19	9
TP53 WILD-TYPE	18	61	17	7

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 = 0.00048 (Fisher's exact test), Q value = 0.067

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	86	83	36	16
PIK3CA MUTATED	5	22	2	3
PIK3CA WILD-TYPE	81	61	34	13

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 = 224
Number of significantly mutated genes = 21
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

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] 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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