Correlation between gene methylation status and clinical features

Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

Maintainer Information

Citation Information

Maintained by Juok Cho (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C16M357G

Overview

Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 20141 genes and 9 clinical features across 84 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.

105 genes correlated to 'PATHOLOGY.M.STAGE'.

DUOX2 , DUOXA2 , CHERP , CHRNA7 , DPF3 , ...

1057 genes correlated to 'HISTOLOGICAL.TYPE'.

MAP4K4 , ANO6 , PLEKHA9 , DGCR5 , CIDEA , ...

10 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

CTF1 , NKX3-2 , MAP6 , ZNF221 , HOOK3 , ...

No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'NUMBERPACKYEARSSMOKED', and 'NUMBER.OF.LYMPH.NODES'.

Results

Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature	Statistical test	Significant genes	Associated with		Associated with
Time to Death	Cox regression test	N=0
AGE	Spearman correlation test	N=0
PATHOLOGY T STAGE	Spearman correlation test	N=0
PATHOLOGY N STAGE	t test	N=0
PATHOLOGY M STAGE	ANOVA test	N=105
HISTOLOGICAL TYPE	ANOVA test	N=1057
RADIATIONS RADIATION REGIMENINDICATION	t test	N=10	yes	N=7	no	N=3
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
NUMBER OF LYMPH NODES	Spearman correlation test	N=0

Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1. Basic characteristics of clinical feature: 'Time to Death'


Time to Death	Duration (Months)	0-177 (median=6.9)
	censored	N = 68
	death	N = 14

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

Table S2. Basic characteristics of clinical feature: 'AGE'


AGE	Mean (SD)	48.2 (13)
	Significant markers	N = 0

Clinical variable #3: 'PATHOLOGY.T.STAGE'

No gene related to 'PATHOLOGY.T.STAGE'.

Table S3. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'


PATHOLOGY.T.STAGE	Mean (SD)	1.38 (0.65)
		N
	1	53
	2	22
	3	1
	4	2

	Significant markers	N = 0

Clinical variable #4: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S4. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'


PATHOLOGY.N.STAGE	Labels	N
	class0	52
	class1	24

	Significant markers	N = 0

Clinical variable #5: 'PATHOLOGY.M.STAGE'

105 genes related to 'PATHOLOGY.M.STAGE'.

Table S5. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'


PATHOLOGY.M.STAGE	Labels	N
	M0	51
	M1	2
	MX	26

	Significant markers	N = 105

List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S6. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

	ANOVA_P	Q
DUOX2	1.627e-20	3.28e-16
DUOXA2	1.627e-20	3.28e-16
CHERP	5.527e-15	1.11e-10
CHRNA7	2.745e-14	5.53e-10
DPF3	3.064e-13	6.17e-09
MTUS2	4.214e-12	8.49e-08
PFKM__1	1.12e-11	2.26e-07
SOCS2	6.78e-11	1.37e-06
ATOH8	8.247e-11	1.66e-06
ADAMTS13__1	1.045e-10	2.1e-06

Figure S1. Get High-res Image As an example, this figure shows the association of DUOX2 to 'PATHOLOGY.M.STAGE'. P value = 1.63e-20 with ANOVA analysis.

Clinical variable #6: 'HISTOLOGICAL.TYPE'

1057 genes related to 'HISTOLOGICAL.TYPE'.

Table S7. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	CERVICAL SQUAMOUS CELL CARCINOMA	72
	ENDOCERVICAL ADENOCARCINOMA OF THE USUAL TYPE	1
	ENDOCERVICAL TYPE OF ADENOCARCINOMA	8
	ENDOMETRIOID ADENOCARCINOMA OF ENDOCERVIX	1
	MUCINOUS ADENOCARCINOMA OF ENDOCERVICAL TYPE	2

	Significant markers	N = 1057

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
MAP4K4	2.347e-60	4.73e-56
ANO6	2.889e-55	5.82e-51
PLEKHA9	2.889e-55	5.82e-51
DGCR5	1.668e-53	3.36e-49
CIDEA	1.644e-51	3.31e-47
OSCAR	6.57e-51	1.32e-46
C17ORF86__1	8.266e-45	1.66e-40
SCARNA16__1	8.266e-45	1.66e-40
ABTB2	1.161e-44	2.34e-40
PTGIR	1.132e-42	2.28e-38

Figure S2. Get High-res Image As an example, this figure shows the association of MAP4K4 to 'HISTOLOGICAL.TYPE'. P value = 2.35e-60 with ANOVA analysis.

Clinical variable #7: 'RADIATIONS.RADIATION.REGIMENINDICATION'

10 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S9. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	17
	YES	67

	Significant markers	N = 10
	Higher in YES	7
	Higher in NO	3

List of 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S10. Get Full Table List of 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	T(pos if higher in 'YES')	ttestP	Q	AUC
CTF1	6.85	1.749e-09	3.52e-05	0.8068
NKX3-2	6.46	9.059e-09	0.000182	0.7331
MAP6	5.42	8.299e-07	0.0167	0.6295
ZNF221	5.41	8.719e-07	0.0176	0.8078
HOOK3	-5.65	1.085e-06	0.0218	0.849
RNF170	-5.65	1.085e-06	0.0218	0.849
CDH16	-5.19	1.656e-06	0.0333	0.8174
TMEM160	5.21	1.672e-06	0.0337	0.7612
ANKRD5	5.08	2.338e-06	0.0471	0.8165
GJB2	5.08	2.406e-06	0.0484	0.6874

Figure S3. Get High-res Image As an example, this figure shows the association of CTF1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.75e-09 with T-test analysis.

Clinical variable #8: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S11. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'


NUMBERPACKYEARSSMOKED	Mean (SD)	18 (13)
	Significant markers	N = 0

Clinical variable #9: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S12. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'


NUMBER.OF.LYMPH.NODES	Mean (SD)	0.93 (2.4)
	Significant markers	N = 0

Methods & Data

Input

Expresson data file = CESC-TP.meth.by_min_clin_corr.data.txt
Clinical data file = CESC-TP.merged_data.txt
Number of patients = 84
Number of genes = 20141
Number of clinical features = 9

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' 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] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)

[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)

[3] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)

[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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