Prostate 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 20236 genes and 3 clinical features across 124 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

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

NBPF9 , TAAR2 , HLA-DRB1 , LXN , GFM1 , ...

223 genes correlated to 'NEOADJUVANT.THERAPY'.

SMG7 , KIAA1009 , EIF4E2 , ISCA1 , KIAA0753 , ...

No genes correlated to 'AGE'

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
AGE	Spearman correlation test	N=0
RADIATIONS RADIATION REGIMENINDICATION	t test	N=42	yes	N=16	no	N=26
NEOADJUVANT THERAPY	t test	N=223	yes	N=181	no	N=42

Clinical variable #1: 'AGE'

No gene related to 'AGE'.

Table S1. Basic characteristics of clinical feature: 'AGE'


AGE	Mean (SD)	61.19 (6.6)
	Significant markers	N = 0

Clinical variable #2: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S2. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	5
	YES	119

	Significant markers	N = 42
	Higher in YES	16
	Higher in NO	26

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

Table S3. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	T(pos if higher in 'YES')	ttestP	Q	AUC
NBPF9	8.4	8.213e-12	1.66e-07	0.8218
TAAR2	-7.23	5.635e-11	1.14e-06	0.7277
HLA-DRB1	7.22	5.764e-11	1.17e-06	0.6874
LXN	6.91	2.788e-10	5.64e-06	0.8336
GFM1	6.88	3.031e-10	6.13e-06	0.8689
MIR1243	-6.49	3e-09	6.07e-05	0.7294
SNORD113-6	-6.44	3.401e-09	6.88e-05	0.7277
ATP6V1G3	-6.54	4.901e-09	9.91e-05	0.7748
HIST1H3C	6.53	6.164e-09	0.000125	0.6958
MIR376B	-6.38	8.724e-09	0.000176	0.7681

Figure S1. Get High-res Image As an example, this figure shows the association of NBPF9 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 8.21e-12 with T-test analysis.

Clinical variable #3: 'NEOADJUVANT.THERAPY'

223 genes related to 'NEOADJUVANT.THERAPY'.

Table S4. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'


NEOADJUVANT.THERAPY	Labels	N
	NO	4
	YES	120

	Significant markers	N = 223
	Higher in YES	181
	Higher in NO	42

List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S5. Get Full Table List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

	T(pos if higher in 'YES')	ttestP	Q	AUC
SMG7	12.34	4.342e-23	8.79e-19	0.9187
KIAA1009	12.69	5e-23	1.01e-18	0.8646
EIF4E2	11.99	6.064e-21	1.23e-16	0.8792
ISCA1	11.57	1.997e-19	4.04e-15	0.8771
KIAA0753	12.26	2.353e-19	4.76e-15	0.9333
CDKL1	10.54	7.227e-19	1.46e-14	0.9125
KIF15	10.68	2.296e-18	4.65e-14	0.8792
POMT2	10.78	3.012e-18	6.09e-14	0.8771
C21ORF129	-10.76	6.138e-18	1.24e-13	0.8562
NCRNA00112	-10.76	6.138e-18	1.24e-13	0.8562

Figure S2. Get High-res Image As an example, this figure shows the association of SMG7 to 'NEOADJUVANT.THERAPY'. P value = 4.34e-23 with T-test analysis.

Methods & Data

Input

Expresson data file = PRAD.meth.for_correlation.filtered_data.txt
Clinical data file = PRAD.clin.merged.picked.txt
Number of patients = 124
Number of genes = 20236
Number of clinical features = 3

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

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

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

[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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