Correlation between gene methylation status and clinical features
Stomach Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1JS9NJD
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/C1JS9NJD
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 19845 genes and 10 clinical features across 141 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 35 genes correlated to 'AGE'.

    • PRTN3 ,  SLC12A7 ,  CDCA4 ,  SERHL ,  AK7 ,  ...

  • 2 genes correlated to 'GENDER'.

    • KIF4B ,  GPX1

  • 26 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CAT ,  CREB1 ,  TAS1R3 ,  IAPP ,  SLCO1A2__1 ,  ...

  • 502 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • CBWD1 ,  FSCN1 ,  LOC100128191 ,  TMPO ,  HAR1A ,  ...

  • 1 gene correlated to 'LYMPH.NODE.METASTASIS'.

    • COX17

  • 143 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • COPZ1 ,  MIR148B ,  ATP2A2 ,  LOC221122 ,  FBXO24 ,  ...

  • 47 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • ABCC4 ,  ZNF846 ,  EIF4G3 ,  SMYD3 ,  RC3H1 ,  ...

  • No genes correlated to 'Time to Death', 'DISTANT.METASTASIS', 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=35 older N=0 younger N=35
GENDER t test N=2 male N=0 female N=2
HISTOLOGICAL TYPE ANOVA test N=26        
RADIATIONS RADIATION REGIMENINDICATION t test N=502 yes N=463 no N=39
DISTANT METASTASIS ANOVA test   N=0        
LYMPH NODE METASTASIS ANOVA test N=1        
COMPLETENESS OF RESECTION ANOVA test N=143        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE ANOVA test N=47        
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) 0.1-72.2 (median=1)
  censored N = 115
  death N = 14
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

35 genes related to 'AGE'.

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

AGE Mean (SD) 65.38 (11)
  Significant markers N = 35
  pos. correlated 0
  neg. correlated 35
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
PRTN3 -0.4587 3.183e-08 0.000632
SLC12A7 -0.4349 1.883e-07 0.00374
CDCA4 -0.4274 3.205e-07 0.00636
SERHL -0.4216 4.787e-07 0.0095
AK7 -0.4192 5.667e-07 0.0112
CYC1 -0.418 6.14e-07 0.0122
MYCT1 -0.4193 6.199e-07 0.0123
C19ORF52 -0.4169 6.606e-07 0.0131
YIPF2 -0.4169 6.606e-07 0.0131
FBXL6 -0.4159 7.075e-07 0.014

Figure S1.  Get High-res Image As an example, this figure shows the association of PRTN3 to 'AGE'. P value = 3.18e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

2 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 50
  MALE 89
     
  Significant markers N = 2
  Higher in MALE 0
  Higher in FEMALE 2
List of 2 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of 2 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -11.9 4.645e-22 9.22e-18 0.9216
GPX1 -6.34 6.427e-09 0.000128 0.7964

Figure S2.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 4.65e-22 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

26 genes related to 'HISTOLOGICAL.TYPE'.

Table S6.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  STOMACH ADENOCARCINOMA DIFFUSE TYPE 22
  STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 63
  STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 29
  STOMACH INTESTINAL ADENOCARCINOMA TUBULAR TYPE 10
  STOMACH INTESTINAL ADENOCARCINOMA  MUCINOUS TYPE 10
  STOMACH INTESTINAL ADENOCARCINOMA  PAPILLARY TYPE 3
  STOMACH ADENOCARCINOMA SIGNET RING TYPE 2
     
  Significant markers N = 26
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
CAT 1.648e-15 3.27e-11
CREB1 2.606e-09 5.17e-05
TAS1R3 2.579e-08 0.000512
IAPP 3.157e-08 0.000626
SLCO1A2__1 3.157e-08 0.000626
TUBGCP3 4.879e-08 0.000968
ODAM 8.822e-08 0.00175
SLC38A6 1.595e-07 0.00316
TRMT5 1.595e-07 0.00316
SH3PXD2A 3.692e-07 0.00732

Figure S3.  Get High-res Image As an example, this figure shows the association of CAT to 'HISTOLOGICAL.TYPE'. P value = 1.65e-15 with ANOVA analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S8.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 7
  YES 134
     
  Significant markers N = 502
  Higher in YES 463
  Higher in NO 39
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
CBWD1 11.01 1.572e-20 3.12e-16 0.9168
FSCN1 10.93 2.001e-20 3.97e-16 0.8326
LOC100128191 10.69 1.318e-16 2.61e-12 0.8929
TMPO 10.69 1.318e-16 2.61e-12 0.8929
HAR1A 9.45 3.059e-16 6.07e-12 0.8401
HAR1B 9.45 3.059e-16 6.07e-12 0.8401
ARHGAP18 9.07 1.204e-15 2.39e-11 0.9136
MESP2 8.76 2.202e-14 4.37e-10 0.7772
FAM126A 8.17 1.787e-13 3.55e-09 0.7036
CDYL2 8.03 4.188e-13 8.31e-09 0.6557

Figure S4.  Get High-res Image As an example, this figure shows the association of CBWD1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.57e-20 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S10.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 117
  M1 11
  MX 11
     
  Significant markers N = 0
Clinical variable #7: 'LYMPH.NODE.METASTASIS'

One gene related to 'LYMPH.NODE.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 50
  N1 46
  N2 25
  N3 10
  N3A 8
     
  Significant markers N = 1
List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S12.  Get Full Table List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
COX17 1.058e-06 0.021

Figure S5.  Get High-res Image As an example, this figure shows the association of COX17 to 'LYMPH.NODE.METASTASIS'. P value = 1.06e-06 with ANOVA analysis.

Clinical variable #8: 'COMPLETENESS.OF.RESECTION'

143 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S13.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 114
  R1 8
  R2 5
     
  Significant markers N = 143
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
COPZ1 1.848e-12 3.67e-08
MIR148B 1.848e-12 3.67e-08
ATP2A2 1.309e-11 2.6e-07
LOC221122 2.545e-11 5.05e-07
FBXO24 8.179e-11 1.62e-06
LRCH4__1 8.179e-11 1.62e-06
AHI1 1.05e-10 2.08e-06
C6ORF217 1.05e-10 2.08e-06
FAM128A 2.826e-10 5.61e-06
LOC150776 2.826e-10 5.61e-06

Figure S6.  Get High-res Image As an example, this figure shows the association of COPZ1 to 'COMPLETENESS.OF.RESECTION'. P value = 1.85e-12 with ANOVA analysis.

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

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

Table S15.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 4.27 (5.8)
  Significant markers N = 0
Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

47 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S16.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 2
  STAGE IA 4
  STAGE IB 12
  STAGE II 25
  STAGE IIA 9
  STAGE IIB 14
  STAGE III 3
  STAGE IIIA 32
  STAGE IIIB 14
  STAGE IIIC 6
  STAGE IV 18
     
  Significant markers N = 47
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
ABCC4 8.936e-17 1.77e-12
ZNF846 7.135e-14 1.42e-09
EIF4G3 5.942e-13 1.18e-08
SMYD3 8.101e-12 1.61e-07
RC3H1 2.172e-10 4.31e-06
LTBP4 2.454e-10 4.87e-06
LOC152024 3.126e-09 6.2e-05
SRPK2 5.728e-09 0.000114
C7ORF31 5.802e-09 0.000115
ALDH6A1 6.585e-09 0.000131

Figure S7.  Get High-res Image As an example, this figure shows the association of ABCC4 to 'NEOPLASM.DISEASESTAGE'. P value = 8.94e-17 with ANOVA analysis.

Methods & Data
Input

  • Expresson data file = STAD-TP.meth.by_min_expr_corr.data.txt

  • Clinical data file = STAD-TP.clin.merged.picked.txt

  • Number of patients = 141

  • Number of genes = 19845

  • Number of clinical features = 10

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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle