Correlation between gene mutation status and molecular subtypes

Bladder Urothelial Carcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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 (2014): Correlation between gene mutation status and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1XD102V

Overview

Introduction

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

Summary

Testing the association between 'TP53 MUTATION ANALYSIS' and 10 molecular subtypes across 28 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.

No gene mutations related to molecuar subtypes.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 1 genes and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, no significant finding detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	RPPA CNMF	RPPA CHIERARCHICAL	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL	MIRSEQ MATURE CNMF	MIRSEQ MATURE CHIERARCHICAL
	nMutated (%)	nWild-Type	Chi-square test	Fisher's exact test	Chi-square 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
TP53	11 (39%)	17	0.746 (1.00)	0.787 (1.00)	0.112 (0.909)	0.292 (1.00)	0.0271 (0.271)	0.874 (1.00)	0.883 (1.00)	0.101 (0.909)	0.715 (1.00)	0.577 (1.00)

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.746 (Chi-square test), Q value = 1

Table S1. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_4	CLUS_5	CLUS_6	CLUS_7
ALL	3	11	3	4	4	1
TP53 MUTATED	1	3	1	2	2	1
TP53 WILD-TYPE	2	8	2	2	2	0

'TP53 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.787 (Fisher's exact test), Q value = 1

Table S2. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	6	12	10
TP53 MUTATED	3	5	3
TP53 WILD-TYPE	3	7	7

'TP53 MUTATION STATUS' versus 'RPPA_CNMF'

P value = 0.112 (Chi-square test), Q value = 0.91

Table S3. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #3: 'RPPA_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	6	5	11	1	2
TP53 MUTATED	1	1	8	0	1
TP53 WILD-TYPE	5	4	3	1	1

'TP53 MUTATION STATUS' versus 'RPPA_CHIERARCHICAL'

P value = 0.292 (Fisher's exact test), Q value = 1

Table S4. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	10	1	7	7
TP53 MUTATED	3	0	5	3
TP53 WILD-TYPE	7	1	2	4

'TP53 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.0271 (Fisher's exact test), Q value = 0.27

Table S5. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	5	11	4	8
TP53 MUTATED	2	6	3	0
TP53 WILD-TYPE	3	5	1	8

Figure S1. Get High-res Image Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.874 (Fisher's exact test), Q value = 1

Table S6. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	10	5	13
TP53 MUTATED	3	2	6
TP53 WILD-TYPE	7	3	7

'TP53 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.883 (Fisher's exact test), Q value = 1

Table S7. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	7	8	13
TP53 MUTATED	2	3	6
TP53 WILD-TYPE	5	5	7

'TP53 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.101 (Fisher's exact test), Q value = 0.91

Table S8. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	20	2	6
TP53 MUTATED	8	2	1
TP53 WILD-TYPE	12	0	5

'TP53 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.715 (Fisher's exact test), Q value = 1

Table S9. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	7	9	5	7
TP53 MUTATED	2	5	2	2
TP53 WILD-TYPE	5	4	3	5

'TP53 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.577 (Fisher's exact test), Q value = 1

Table S10. Gene #1: 'TP53 MUTATION STATUS' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	11	6	5	6
TP53 MUTATED	5	2	3	1
TP53 WILD-TYPE	6	4	2	5

Methods & Data

Input

Mutation data file = transformed.cor.cli.txt
Molecular subtypes file = BLCA-TP.transferedmergedcluster.txt
Number of patients = 28
Number of significantly mutated genes = 1: 'TP53 MUTATION ANALYSIS'
Number of Molecular subtypes = 10
Exclude genes that fewer than K tumors have mutations, K = 3

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[2] 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)

[3] 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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