Correlation between gene methylation status and clinical features

Glioblastoma Multiforme (Primary solid tumor)

17 October 2014 | analyses__2014_10_17

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/C17D2T02

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 14198 genes and 8 clinical features across 283 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.

146 genes correlated to 'AGE'.

TWIST1 , FBN2 , HOXD8 , SCGN , MACROD2__1 , ...

9 genes correlated to 'GENDER'.

FYTTD1 , KIAA0226 , MIR548H4 , NOX5 , SPESP1 , ...

35 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

GADD45G , HSPB8 , TUBA8 , STXBP6 , BID , ...

3051 genes correlated to 'HISTOLOGICAL.TYPE'.

CNOT4 , PCTP , C11ORF48 , C11ORF83 , CCNK , ...

No genes correlated to 'Time to Death', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'RACE', and 'ETHNICITY'.

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 P value < 0.05 and Q value < 0.3.

Clinical feature	Statistical test	Significant genes	Associated with		Associated with
Time to Death	Cox regression test	N=0
AGE	Spearman correlation test	N=146	older	N=123	younger	N=23
GENDER	Wilcoxon test	N=9	male	N=9	female	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=35	higher score	N=35	lower score	N=0
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=3051
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=0
RACE	Kruskal-Wallis test	N=0
ETHNICITY	Wilcoxon 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)	0.1-127.6 (median=10.6)
	censored	N = 57
	death	N = 226

	Significant markers	N = 0

Clinical variable #2: 'AGE'

146 genes related to 'AGE'.

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


AGE	Mean (SD)	57.81 (15)
	Significant markers	N = 146
	pos. correlated	123
	neg. correlated	23

List of top 10 genes differentially expressed by 'AGE'

Table S3. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
TWIST1	0.4142	3.719e-13	5.28e-09
FBN2	0.4046	1.425e-12	2.02e-08
HOXD8	0.4036	1.645e-12	2.34e-08
SCGN	0.3918	8.059e-12	1.14e-07
MACROD2__1	0.3913	8.607e-12	1.22e-07
SRD5A2	0.3891	1.147e-11	1.63e-07
EFCAB1	0.3701	1.494e-10	2.12e-06
ATP8A2	0.3683	1.607e-10	2.28e-06
MSC	0.3599	4.43e-10	6.29e-06
IRF8	0.3588	5.06e-10	7.18e-06

Clinical variable #3: 'GENDER'

9 genes related to 'GENDER'.

Table S4. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	115
	MALE	168

	Significant markers	N = 9
	Higher in MALE	9
	Higher in FEMALE	0

List of 9 genes differentially expressed by 'GENDER'

Table S5. Get Full Table List of 9 genes differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

	W(pos if higher in 'MALE')	wilcoxontestP	Q	AUC
FYTTD1	5555	1.279e-09	1.82e-05	0.7125
KIAA0226	5555	1.279e-09	1.82e-05	0.7125
MIR548H4	6311	7.347e-07	0.0104	0.6733
NOX5	6311	7.347e-07	0.0104	0.6733
SPESP1	6311	7.347e-07	0.0104	0.6733
DDX43	6324	8.108e-07	0.0115	0.6727
FAM190A	6351	9.94e-07	0.0141	0.6713
TMSL3	6351	9.94e-07	0.0141	0.6713
INTS6	6629	7.405e-06	0.105	0.6569

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

35 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S6. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	75.42 (15)
	Significant markers	N = 35
	pos. correlated	35
	neg. correlated	0

List of top 10 genes differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S7. Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

	SpearmanCorr	corrP	Q
GADD45G	0.3305	7.585e-07	0.0108
HSPB8	0.3301	7.824e-07	0.0111
TUBA8	0.3298	7.983e-07	0.0113
STXBP6	0.3203	1.707e-06	0.0242
BID	0.3192	1.862e-06	0.0264
FAM194A	0.3179	2.069e-06	0.0294
CHPT1	0.317	2.208e-06	0.0313
MAP4K3	0.3155	2.494e-06	0.0354
GPR12	0.31	3.775e-06	0.0536
ITGA11	0.3074	4.612e-06	0.0654

Clinical variable #5: 'HISTOLOGICAL.TYPE'

3051 genes related to 'HISTOLOGICAL.TYPE'.

Table S8. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	GLIOBLASTOMA MULTIFORME (GBM)	3
	TREATED PRIMARY GBM	19
	UNTREATED PRIMARY (DE NOVO) GBM	261

	Significant markers	N = 3051

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

Table S9. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
CNOT4	6.668e-09	9.47e-05
PCTP	6.755e-09	9.59e-05
C11ORF48	7.273e-09	0.000103
C11ORF83	7.273e-09	0.000103
CCNK	7.786e-09	0.000111
SETD3	7.786e-09	0.000111
ZNHIT2	1.098e-08	0.000156
MAFF	1.2e-08	0.00017
MON1A	1.614e-08	0.000229
CNPY4	1.619e-08	0.00023

Clinical variable #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S10. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	210
	YES	73

	Significant markers	N = 0

Clinical variable #7: 'RACE'

No gene related to 'RACE'.

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


RACE	Labels	N
	ASIAN	10
	BLACK OR AFRICAN AMERICAN	16
	WHITE	254

	Significant markers	N = 0

Clinical variable #8: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S12. Basic characteristics of clinical feature: 'ETHNICITY'


ETHNICITY	Labels	N
	HISPANIC OR LATINO	7
	NOT HISPANIC OR LATINO	232

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = GBM-TP.meth.by_min_clin_corr.data.txt
Clinical data file = GBM-TP.merged_data.txt
Number of patients = 283
Number of genes = 14198
Number of clinical features = 8

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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