Correlation between gene mutation status and molecular subtypes
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1DJ5D79
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/C1DJ5D79
Overview
Introduction

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

Summary

Testing the association between mutation status of 4 genes and 8 molecular subtypes across 39 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 4 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, no significant finding detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nMutated (%) nWild-Type 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
PIK3CA 9 (23%) 30 0.0461
(1.00) 		0.469
(1.00) 		0.25
(1.00) 		0.799
(1.00) 		0.874
(1.00) 		0.0741
(1.00) 		0.737
(1.00) 		0.524
(1.00)
TMCC1 4 (10%) 35 0.481
(1.00) 		0.703
(1.00) 		0.653
(1.00) 		1
(1.00) 		0.349
(1.00) 		0.435
(1.00) 		1
(1.00)
UGT3A2 3 (8%) 36 0.855
(1.00) 		0.051
(1.00) 		1
(1.00) 		1
(1.00) 		0.0263
(0.788) 		0.698
(1.00) 		0.0881
(1.00)
MAPK1 3 (8%) 36 0.0518
(1.00) 		0.705
(1.00) 		1
(1.00) 		1
(1.00) 		0.388
(1.00) 		0.792
(1.00) 		0.698
(1.00) 		1
(1.00)
'PIK3CA MUTATION STATUS' versus 'CN_CNMF'

P value = 0.0461 (Fisher's exact test), Q value = 1

Table S1.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 14 9 13
PIK3CA MUTATED 3 0 6
PIK3CA WILD-TYPE 11 9 7

Figure S1.  Get High-res Image Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #1: 'CN_CNMF'

'PIK3CA MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.469 (Chi-square test), Q value = 1

Table S2.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 12 7 2 6 6 4 2
PIK3CA MUTATED 5 2 0 0 1 1 0
PIK3CA WILD-TYPE 7 5 2 6 5 3 2
'PIK3CA MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.25 (Fisher's exact test), Q value = 1

Table S3.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 5 7 7
PIK3CA MUTATED 7 1 1 0
PIK3CA WILD-TYPE 12 4 6 7
'PIK3CA MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.799 (Fisher's exact test), Q value = 1

Table S4.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 2 29 7
PIK3CA MUTATED 0 8 1
PIK3CA WILD-TYPE 2 21 6
'PIK3CA MUTATION STATUS' versus 'MIRSEQ_CNMF'

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

Table S5.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 6 13
PIK3CA MUTATED 4 2 3
PIK3CA WILD-TYPE 16 4 10
'PIK3CA MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.0741 (Fisher's exact test), Q value = 1

Table S6.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 10 10
PIK3CA MUTATED 7 0 2
PIK3CA WILD-TYPE 12 10 8
'PIK3CA MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.737 (Fisher's exact test), Q value = 1

Table S7.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 24 5 10
PIK3CA MUTATED 5 2 2
PIK3CA WILD-TYPE 19 3 8
'PIK3CA MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.524 (Fisher's exact test), Q value = 1

Table S8.  Gene #1: 'PIK3CA MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 15 5
PIK3CA MUTATED 6 2 1
PIK3CA WILD-TYPE 13 13 4
'TMCC1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.481 (Chi-square test), Q value = 1

Table S9.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 12 7 2 6 6 4 2
TMCC1 MUTATED 3 0 0 1 0 0 0
TMCC1 WILD-TYPE 9 7 2 5 6 4 2
'TMCC1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.703 (Fisher's exact test), Q value = 1

Table S10.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 5 7 7
TMCC1 MUTATED 2 1 0 1
TMCC1 WILD-TYPE 17 4 7 6
'TMCC1 MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.653 (Fisher's exact test), Q value = 1

Table S11.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 2 29 7
TMCC1 MUTATED 0 4 0
TMCC1 WILD-TYPE 2 25 7
'TMCC1 MUTATION STATUS' versus 'MIRSEQ_CNMF'

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

Table S12.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 6 13
TMCC1 MUTATED 3 0 1
TMCC1 WILD-TYPE 17 6 12
'TMCC1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.349 (Fisher's exact test), Q value = 1

Table S13.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 10 10
TMCC1 MUTATED 2 2 0
TMCC1 WILD-TYPE 17 8 10
'TMCC1 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.435 (Fisher's exact test), Q value = 1

Table S14.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 24 5 10
TMCC1 MUTATED 4 0 0
TMCC1 WILD-TYPE 20 5 10
'TMCC1 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

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

Table S15.  Gene #2: 'TMCC1 MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 15 5
TMCC1 MUTATED 2 2 0
TMCC1 WILD-TYPE 17 13 5
'UGT3A2 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.855 (Chi-square test), Q value = 1

Table S16.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 12 7 2 6 6 4 2
UGT3A2 MUTATED 1 0 0 1 1 0 0
UGT3A2 WILD-TYPE 11 7 2 5 5 4 2
'UGT3A2 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.051 (Fisher's exact test), Q value = 1

Table S17.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 5 7 7
UGT3A2 MUTATED 0 1 0 2
UGT3A2 WILD-TYPE 19 4 7 5
'UGT3A2 MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

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

Table S18.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 2 29 7
UGT3A2 MUTATED 0 3 0
UGT3A2 WILD-TYPE 2 26 7
'UGT3A2 MUTATION STATUS' versus 'MIRSEQ_CNMF'

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

Table S19.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 6 13
UGT3A2 MUTATED 2 0 1
UGT3A2 WILD-TYPE 18 6 12
'UGT3A2 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.0263 (Fisher's exact test), Q value = 0.79

Table S20.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 10 10
UGT3A2 MUTATED 0 3 0
UGT3A2 WILD-TYPE 19 7 10

Figure S2.  Get High-res Image Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'UGT3A2 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.698 (Fisher's exact test), Q value = 1

Table S21.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 24 5 10
UGT3A2 MUTATED 3 0 0
UGT3A2 WILD-TYPE 21 5 10
'UGT3A2 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.0881 (Fisher's exact test), Q value = 1

Table S22.  Gene #3: 'UGT3A2 MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 15 5
UGT3A2 MUTATED 0 3 0
UGT3A2 WILD-TYPE 19 12 5
'MAPK1 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.0518 (Fisher's exact test), Q value = 1

Table S23.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 14 9 13
MAPK1 MUTATED 0 0 3
MAPK1 WILD-TYPE 14 9 10
'MAPK1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.705 (Chi-square test), Q value = 1

Table S24.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 12 7 2 6 6 4 2
MAPK1 MUTATED 2 0 0 1 0 0 0
MAPK1 WILD-TYPE 10 7 2 5 6 4 2
'MAPK1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

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

Table S25.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 5 7 7
MAPK1 MUTATED 2 0 0 1
MAPK1 WILD-TYPE 17 5 7 6
'MAPK1 MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

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

Table S26.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 2 29 7
MAPK1 MUTATED 0 3 0
MAPK1 WILD-TYPE 2 26 7
'MAPK1 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.388 (Fisher's exact test), Q value = 1

Table S27.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 20 6 13
MAPK1 MUTATED 3 0 0
MAPK1 WILD-TYPE 17 6 13
'MAPK1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.792 (Fisher's exact test), Q value = 1

Table S28.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 10 10
MAPK1 MUTATED 2 1 0
MAPK1 WILD-TYPE 17 9 10
'MAPK1 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.698 (Fisher's exact test), Q value = 1

Table S29.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 24 5 10
MAPK1 MUTATED 3 0 0
MAPK1 WILD-TYPE 21 5 10
'MAPK1 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

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

Table S30.  Gene #4: 'MAPK1 MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 19 15 5
MAPK1 MUTATED 2 1 0
MAPK1 WILD-TYPE 17 14 5
Methods & Data
Input

  • Mutation data file = transformed.cor.cli.txt

  • Molecular subtypes file = CESC-TP.transferedmergedcluster.txt

  • Number of patients = 39

  • Number of significantly mutated genes = 4

  • 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

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

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