Stomach Adenocarcinoma: Correlation between gene methylation status and clinical features

Maintained by Juok Cho (Broad Institute)

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 20229 genes and 9 clinical features across 68 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

1 gene correlated to 'GENDER'.

KIF4B

34 genes correlated to 'HISTOLOGICAL.TYPE'.

LOC255025 , VENTXP7 , LRRC7 , NAALADL2 , RBM12B , ...

8 genes correlated to 'PATHOLOGY.T'.

SPINT2 , C17ORF55 , LY75 , DHRS3 , IQGAP3 , ...

66 genes correlated to 'PATHOLOGICSPREAD(M)'.

KDM3A , ZNF846 , C7ORF31 , ZMYM5 , UBE2Q2P2 , ...

No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.N', 'TUMOR.STAGE', and 'NEOADJUVANT.THERAPY'.

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
GENDER	t test	N=1	male	N=0	female	N=1
HISTOLOGICAL TYPE	ANOVA test	N=34
PATHOLOGY T	Spearman correlation test	N=8	higher pT	N=8	lower pT	N=0
PATHOLOGY N	Spearman correlation test	N=0
PATHOLOGICSPREAD(M)	ANOVA test	N=66
TUMOR STAGE	Spearman correlation test	N=0
NEOADJUVANT THERAPY	t 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)	0.1-70.1 (median=2.2)
	censored	N = 56
	death	N = 9

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	66.8 (11)
	Significant markers	N = 0

Clinical variable #3: 'GENDER'

One gene related to 'GENDER'.

Table S3. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	24
	MALE	44

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

List of one gene differentially expressed by 'GENDER'

Table S4. Get Full Table List of one gene differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
KIF4B	-6.8	7.427e-08	0.0015	0.8835

Figure S1. Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 7.43e-08 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

34 genes related to 'HISTOLOGICAL.TYPE'.

Table S5. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	STOMACH ADENOCARCINOMA - DIFFUSE TYPE	11
	STOMACH ADENOCARCINOMA - NOT OTHERWISE SPECIFIED (NOS)	28
	STOMACH INTESTINAL ADENOCARCINOMA - MUCINOUS TYPE	3
	STOMACH INTESTINAL ADENOCARCINOMA - PAPILLARY TYPE	2
	STOMACH INTESTINAL ADENOCARCINOMA - TUBULAR TYPE	9
	STOMACH INTESTINAL ADENOCARCINOMA - TYPE NOT OTHERWISE SPECIFIED (NOS)	15

	Significant markers	N = 34

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

Table S6. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
LOC255025	9.046e-09	0.000183
VENTXP7	9.696e-09	0.000196
LRRC7	1.597e-08	0.000323
NAALADL2	2.638e-08	0.000534
RBM12B	4.66e-08	0.000942
RPL41	7.259e-08	0.00147
PABPC1P2	8.026e-08	0.00162
KRTAP19-7	1.018e-07	0.00206
PDHA2	1.262e-07	0.00255
TMTC1	1.442e-07	0.00292

Figure S2. Get High-res Image As an example, this figure shows the association of LOC255025 to 'HISTOLOGICAL.TYPE'. P value = 9.05e-09 with ANOVA analysis.

Clinical variable #5: 'PATHOLOGY.T'

8 genes related to 'PATHOLOGY.T'.

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T'


PATHOLOGY.T	Mean (SD)	2.57 (0.7)
		N
	T1	2
	T2	31
	T3	29
	T4	6

	Significant markers	N = 8
	pos. correlated	8
	neg. correlated	0

List of 8 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S8. Get Full Table List of 8 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

	SpearmanCorr	corrP	Q
SPINT2	0.5706	3.779e-07	0.00765
C17ORF55	0.566	4.888e-07	0.00989
LY75	0.552	1.062e-06	0.0215
DHRS3	0.5412	1.889e-06	0.0382
IQGAP3	0.5399	2.017e-06	0.0408
TGFBR3	0.5389	2.13e-06	0.0431
C1ORF172	0.5383	2.189e-06	0.0443
KCNE3	0.538	2.227e-06	0.045

Figure S3. Get High-res Image As an example, this figure shows the association of SPINT2 to 'PATHOLOGY.T'. P value = 3.78e-07 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.N'


PATHOLOGY.N	Mean (SD)	1 (1)
		N
	N0	27
	N1	21
	N2	13
	N3	7

	Significant markers	N = 0

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

66 genes related to 'PATHOLOGICSPREAD(M)'.

Table S10. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'


PATHOLOGICSPREAD(M)	Labels	N
	M0	61
	M1	6
	MX	1

	Significant markers	N = 66

List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S11. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

	ANOVA_P	Q
KDM3A	3.54e-56	7.16e-52
ZNF846	8.686e-55	1.76e-50
C7ORF31	8.6e-50	1.74e-45
ZMYM5	2.571e-30	5.2e-26
UBE2Q2P2	2.586e-26	5.23e-22
UBE2Q2P3	2.586e-26	5.23e-22
C6ORF226	1.752e-25	3.54e-21
MIR15A	6.658e-25	1.35e-20
JUN	1.081e-21	2.19e-17
DNAJC18	2.755e-21	5.57e-17

Figure S4. Get High-res Image As an example, this figure shows the association of KDM3A to 'PATHOLOGICSPREAD(M)'. P value = 3.54e-56 with ANOVA analysis.

Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S12. Basic characteristics of clinical feature: 'TUMOR.STAGE'


TUMOR.STAGE	Mean (SD)	2.43 (0.94)
		N
	Stage 1	11
	Stage 2	27
	Stage 3	20
	Stage 4	10

	Significant markers	N = 0

Clinical variable #9: 'NEOADJUVANT.THERAPY'

No gene related to 'NEOADJUVANT.THERAPY'.

Table S13. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'


NEOADJUVANT.THERAPY	Labels	N
	NO	7
	YES	61

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = STAD.meth.for_correlation.filtered_data.txt
Clinical data file = STAD.clin.merged.picked.txt
Number of patients = 68
Number of genes = 20229
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

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] 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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