Correlation between gene methylation status and clinical features

Skin Cutaneous Melanoma (Metastatic)

23 May 2013 | analyses__2013_05_23

Maintainer Information

Citation Information

Maintained by Juok Cho (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1JW8BX8

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 19639 genes and 7 clinical features across 177 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

14 genes correlated to 'AGE'.

PTX3 , VEPH1__1 , ITGA8 , RSPO4 , TRPV4 , ...

213 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

DAZAP1 , TCF3 , IRAK4 , PUS7L , TCF25 , ...

1 gene correlated to 'GENDER'.

DDX43

278 genes correlated to 'DISTANT.METASTASIS'.

SELT , LMF1 , LDHAL6B , MYO1E__1 , FAM186A , ...

59 genes correlated to 'LYMPH.NODE.METASTASIS'.

NGLY1__1 , C6ORF162__1 , GJB7__1 , LIMK2 , AP2S1 , ...

12 genes correlated to 'NEOPLASM.DISEASESTAGE'.

MIR548N__3 , TTN , POLE4 , C4ORF3 , RAD21L1 , ...

No genes correlated to 'Time to Death'

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=14	older	N=14	younger	N=0
PRIMARY SITE OF DISEASE	ANOVA test	N=213
GENDER	t test	N=1	male	N=0	female	N=1
DISTANT METASTASIS	ANOVA test	N=278
LYMPH NODE METASTASIS	ANOVA test	N=59
NEOPLASM DISEASESTAGE	ANOVA test	N=12

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)	0.2-357.4 (median=47.5)
	censored	N = 86
	death	N = 88

	Significant markers	N = 0

Clinical variable #2: 'AGE'

14 genes related to 'AGE'.

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


AGE	Mean (SD)	55.9 (16)
	Significant markers	N = 14
	pos. correlated	14
	neg. correlated	0

List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

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

	SpearmanCorr	corrP	Q
PTX3	0.4169	8.644e-09	0.00017
VEPH1__1	0.4169	8.644e-09	0.00017
ITGA8	0.3897	8.973e-08	0.00176
RSPO4	0.3854	1.279e-07	0.00251
TRPV4	0.381	1.828e-07	0.00359
NIPAL2	0.3657	6.004e-07	0.0118
PLCE1	0.3607	8.737e-07	0.0172
STK38L	0.3594	9.625e-07	0.0189
MCHR1	0.3591	9.875e-07	0.0194
STBD1	0.3548	1.36e-06	0.0267

Figure S1. Get High-res Image As an example, this figure shows the association of PTX3 to 'AGE'. P value = 8.64e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

213 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S4. Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'


PRIMARY.SITE.OF.DISEASE	Labels	N
	DISTANT METASTASIS	27
	PRIMARY TUMOR	1
	REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS)	35
	REGIONAL LYMPH NODE	114

	Significant markers	N = 213

List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S5. Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

	ANOVA_P	Q
DAZAP1	5.236e-112	1.03e-107
TCF3	1.606e-53	3.15e-49
IRAK4	1.627e-51	3.2e-47
PUS7L	1.627e-51	3.2e-47
TCF25	2.008e-47	3.94e-43
AMY2B	1.304e-42	2.56e-38
RNPC3__1	1.304e-42	2.56e-38
TUBGCP6	6.768e-41	1.33e-36
COL18A1__1	7.285e-41	1.43e-36
NCRNA00175	7.285e-41	1.43e-36

Figure S2. Get High-res Image As an example, this figure shows the association of DAZAP1 to 'PRIMARY.SITE.OF.DISEASE'. P value = 5.24e-112 with ANOVA analysis.

Clinical variable #4: 'GENDER'

One gene related to 'GENDER'.

Table S6. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	69
	MALE	108

	Significant markers	N = 1
	Higher in MALE	0
	Higher in FEMALE	1

List of one gene differentially expressed by 'GENDER'

Table S7. Get Full Table List of one gene differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
DDX43	-5.24	4.537e-07	0.00891	0.7348

Figure S3. Get High-res Image As an example, this figure shows the association of DDX43 to 'GENDER'. P value = 4.54e-07 with T-test analysis.

Clinical variable #5: 'DISTANT.METASTASIS'

278 genes related to 'DISTANT.METASTASIS'.

Table S8. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'


DISTANT.METASTASIS	Labels	N
	M0	154
	M1	2
	M1A	2
	M1B	2
	M1C	2

	Significant markers	N = 278

List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S9. Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

	ANOVA_P	Q
SELT	1.964e-22	3.86e-18
LMF1	2.482e-22	4.87e-18
LDHAL6B	3.862e-22	7.58e-18
MYO1E__1	3.862e-22	7.58e-18
FAM186A	7.877e-22	1.55e-17
CCNG1	8.802e-22	1.73e-17
C10ORF88	3.27e-20	6.42e-16
RASA2	3.568e-20	7e-16
ACSS1	1.672e-18	3.28e-14
MDM1	5.005e-18	9.82e-14

Figure S4. Get High-res Image As an example, this figure shows the association of SELT to 'DISTANT.METASTASIS'. P value = 1.96e-22 with ANOVA analysis.

Clinical variable #6: 'LYMPH.NODE.METASTASIS'

59 genes related to 'LYMPH.NODE.METASTASIS'.

Table S10. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'


LYMPH.NODE.METASTASIS	Labels	N
	N0	97
	N1	2
	N1A	8
	N1B	15
	N2	1
	N2A	4
	N2B	12
	N2C	5
	N3	17
	NX	2

	Significant markers	N = 59

List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S11. Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

	ANOVA_P	Q
NGLY1__1	6.023e-66	1.18e-61
C6ORF162__1	7.342e-41	1.44e-36
GJB7__1	7.342e-41	1.44e-36
LIMK2	4.393e-29	8.63e-25
AP2S1	4.368e-28	8.58e-24
NOS1	4.971e-24	9.76e-20
C17ORF63	5.552e-24	1.09e-19
CSRP2BP	3.888e-18	7.63e-14
PET117	3.888e-18	7.63e-14
GPR44	7.785e-18	1.53e-13

Figure S5. Get High-res Image As an example, this figure shows the association of NGLY1__1 to 'LYMPH.NODE.METASTASIS'. P value = 6.02e-66 with ANOVA analysis.

Clinical variable #7: 'NEOPLASM.DISEASESTAGE'

12 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S12. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	I OR II NOS	3
	STAGE I	18
	STAGE IA	10
	STAGE IB	15
	STAGE II	19
	STAGE IIA	9
	STAGE IIB	10
	STAGE IIC	8
	STAGE III	9
	STAGE IIIA	6
	STAGE IIIB	19
	STAGE IIIC	24
	STAGE IV	6

	Significant markers	N = 12

List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S13. Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
MIR548N__3	8.208e-09	0.000161
TTN	8.208e-09	0.000161
POLE4	3.547e-08	0.000697
C4ORF3	1.459e-07	0.00286
RAD21L1	1.483e-07	0.00291
ZNF587	1.554e-07	0.00305
GRAMD1B	2.738e-07	0.00538
C3ORF18__1	9.597e-07	0.0188
HEMK1	9.597e-07	0.0188
UBE2I	9.63e-07	0.0189

Figure S6. Get High-res Image As an example, this figure shows the association of MIR548N__3 to 'NEOPLASM.DISEASESTAGE'. P value = 8.21e-09 with ANOVA analysis.

Methods & Data

Input

Expresson data file = SKCM-TM.meth.by_min_expr_corr.data.txt
Clinical data file = SKCM-TM.clin.merged.picked.txt
Number of patients = 177
Number of genes = 19639
Number of clinical features = 7

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

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

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

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

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

[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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