Correlation between gene methylation status and clinical features
Brain Lower Grade Glioma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
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/C1H993XK
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 20110 genes and 8 clinical features across 398 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 1351 genes correlated to 'AGE'.

    • TCHH ,  TRIM58 ,  SHISA2 ,  LOC150786 ,  ADAMTSL3 ,  ...

  • 24 genes correlated to 'GENDER'.

    • ALG11__2 ,  UTP14C ,  POLDIP3 ,  RNU12 ,  KIF4B ,  ...

  • 137 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • PREP ,  ALDH1A1 ,  RCAN1 ,  TMEM165 ,  HS6ST1 ,  ...

  • 3831 genes correlated to 'HISTOLOGICAL.TYPE'.

    • REST ,  MAPKAP1 ,  GLIS3 ,  SLC2A4RG ,  C2ORF67 ,  ...

  • 1356 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • PPP1R8 ,  HSPA13 ,  BIRC6 ,  AMY2B ,  RNPC3 ,  ...

  • 3 genes correlated to 'RACE'.

    • C6ORF52__1 ,  PAK1IP1__1 ,  RNF135

  • No genes correlated to 'Time to Death', 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=1351 older N=440 younger N=911
GENDER Wilcoxon test N=24 male N=24 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=137 higher score N=137 lower score N=0
HISTOLOGICAL TYPE Kruskal-Wallis test N=3831        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test N=1356 yes N=1356 no N=0
RACE Kruskal-Wallis test N=3        
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) 0-211.2 (median=14.9)
  censored N = 326
  death N = 67
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

1351 genes related to 'AGE'.

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

AGE Mean (SD) 43.12 (13)
  Significant markers N = 1351
  pos. correlated 440
  neg. correlated 911
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
TCHH 0.5457 2.941e-32 5.91e-28
TRIM58 0.5398 1.751e-31 3.52e-27
SHISA2 0.5224 3.044e-29 6.12e-25
LOC150786 0.5105 8.588e-28 1.73e-23
ADAMTSL3 0.5006 1.234e-26 2.48e-22
FOXE3 0.497 4.331e-26 8.71e-22
RELN 0.4922 1.134e-25 2.28e-21
GALNT14 0.4901 1.934e-25 3.89e-21
TFAP2B 0.4876 3.651e-25 7.34e-21
SLC22A16 0.4817 1.643e-24 3.3e-20
Clinical variable #3: 'GENDER'

24 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 178
  MALE 220
     
  Significant markers N = 24
  Higher in MALE 24
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of top 10 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
ALG11__2 38337 1.032e-60 2.07e-56 0.979
UTP14C 38337 1.032e-60 2.07e-56 0.979
POLDIP3 2857 1.253e-48 2.52e-44 0.927
RNU12 2857 1.253e-48 2.52e-44 0.927
KIF4B 8574 5.172e-22 1.04e-17 0.7811
WBP11P1 29643 1.161e-18 2.33e-14 0.757
LOC389791__1 28766 8.292e-16 1.67e-11 0.7346
PTGES2__1 28766 8.292e-16 1.67e-11 0.7346
TLE1 10511 1.907e-15 3.83e-11 0.7316
ZNF839 11834 1.138e-11 2.29e-07 0.6978
Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

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

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

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 87.91 (12)
  Significant markers N = 137
  pos. correlated 137
  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
PREP 0.3506 3.575e-08 0.000719
ALDH1A1 0.3332 1.789e-07 0.0036
RCAN1 0.3325 1.903e-07 0.00383
TMEM165 0.3308 2.216e-07 0.00446
HS6ST1 0.3274 3e-07 0.00603
UBC 0.3266 3.221e-07 0.00648
DEGS1 0.3266 3.233e-07 0.0065
BTN2A3 0.3245 3.871e-07 0.00778
KCNN4 0.3226 4.579e-07 0.00921
IGF1 0.3213 5.091e-07 0.0102
Clinical variable #5: 'HISTOLOGICAL.TYPE'

3831 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  ASTROCYTOMA 142
  OLIGOASTROCYTOMA 103
  OLIGODENDROGLIOMA 153
     
  Significant markers N = 3831
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
REST 2.906e-30 5.84e-26
MAPKAP1 2.92e-26 5.87e-22
GLIS3 6.579e-25 1.32e-20
SLC2A4RG 1.075e-24 2.16e-20
C2ORF67 1.316e-24 2.65e-20
BVES 1.683e-24 3.38e-20
EMP1 3.091e-24 6.21e-20
CBX2 3.908e-24 7.86e-20
PLCG1 3.243e-23 6.52e-19
TMC6 5.104e-23 1.03e-18
Clinical variable #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

1356 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 85
  YES 313
     
  Significant markers N = 1356
  Higher in YES 1356
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
PPP1R8 21655 6.686e-19 1.34e-14 0.8139
HSPA13 21593 1.207e-18 2.43e-14 0.8116
BIRC6 21156 6.858e-17 1.38e-12 0.7952
AMY2B 5561 1.866e-16 3.75e-12 0.791
RNPC3 5561 1.866e-16 3.75e-12 0.791
MTX2 5581 2.228e-16 4.48e-12 0.7902
DAZL 20494 5.762e-16 1.16e-11 0.7889
TMEM135 19920 7.418e-16 1.49e-11 0.7908
BMP5 20630 1.112e-15 2.23e-11 0.7846
ASPM 20802 1.548e-15 3.11e-11 0.7819
Clinical variable #7: 'RACE'

3 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 2
  BLACK OR AFRICAN AMERICAN 13
  WHITE 375
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'RACE'

Table S13.  Get Full Table List of 3 genes differentially expressed by 'RACE'

ANOVA_P Q
C6ORF52__1 2.903e-06 0.0584
PAK1IP1__1 2.903e-06 0.0584
RNF135 9.499e-06 0.191
Clinical variable #8: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S14.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 15
  NOT HISPANIC OR LATINO 357
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = LGG-TP.meth.by_min_clin_corr.data.txt

  • Clinical data file = LGG-TP.merged_data.txt

  • Number of patients = 398

  • Number of genes = 20110

  • 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)