Correlation between gene methylation status and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C17S7MNS
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/C17S7MNS
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 20123 genes and 11 clinical features across 307 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 27 genes correlated to 'AGE'.

    • MRPS33 ,  ZYG11A ,  DOK6 ,  RANBP17 ,  C7ORF13 ,  ...

  • 825 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • CLEC2L ,  ACTA1 ,  NEUROD2 ,  OPRK1 ,  SOX8 ,  ...

  • 1180 genes correlated to 'PATHOLOGY.T.STAGE'.

    • CLEC2L ,  ACTA1 ,  OPRK1 ,  NEUROD2 ,  SOX8 ,  ...

  • 651 genes correlated to 'PATHOLOGY.M.STAGE'.

    • ANKRD30B ,  POT1 ,  ARSK__1 ,  TTC37__1 ,  NEDD1 ,  ...

  • 223 genes correlated to 'GENDER'.

    • ALG11__1 ,  UTP14C ,  KIF4B ,  TLE1 ,  COX7C ,  ...

  • 457 genes correlated to 'RACE'.

    • MKRN1 ,  PLAGL2__1 ,  POFUT1__1 ,  HELZ ,  C5ORF28 ,  ...

  • No genes correlated to 'Time to Death', 'PATHOLOGY.N.STAGE', 'KARNOFSKY.PERFORMANCE.SCORE', 'NUMBERPACKYEARSSMOKED', 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=27 older N=21 younger N=6
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=825        
PATHOLOGY T STAGE Spearman correlation test N=1180 higher stage N=556 lower stage N=624
PATHOLOGY N STAGE Wilcoxon test   N=0        
PATHOLOGY M STAGE Kruskal-Wallis test N=651        
GENDER Wilcoxon test N=223 male N=223 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
RACE Kruskal-Wallis test N=457        
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 (Years) 3-3668 (median=1082)
  censored N = 206
  death N = 11
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

27 genes related to 'AGE'.

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

AGE Mean (SD) 61.43 (12)
  Significant markers N = 27
  pos. correlated 21
  neg. correlated 6
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
MRPS33 0.3496 2.963e-10 5.96e-06
ZYG11A 0.3115 2.468e-08 0.000497
DOK6 0.299 9.27e-08 0.00187
RANBP17 0.2977 1.057e-07 0.00213
C7ORF13 0.2976 1.073e-07 0.00216
RNF32 0.2976 1.073e-07 0.00216
TSPYL5 0.292 1.886e-07 0.00379
SLC10A4 0.2917 1.953e-07 0.00393
LYSMD2 -0.2915 1.992e-07 0.00401
ME3 -0.2913 2.041e-07 0.0041
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

825 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 146
  STAGE II 31
  STAGE III 74
  STAGE IV 56
     
  Significant markers N = 825
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
CLEC2L 2.809e-16 5.65e-12
ACTA1 2.625e-15 5.28e-11
NEUROD2 4.316e-15 8.68e-11
OPRK1 5.598e-15 1.13e-10
SOX8 6.913e-15 1.39e-10
FAM38B 1.026e-13 2.06e-09
MYO10 2.573e-13 5.18e-09
MSX2P1 2.702e-13 5.43e-09
SOX17 2.983e-13 6e-09
PSITPTE22 7.281e-13 1.46e-08
Clinical variable #4: 'PATHOLOGY.T.STAGE'

1180 genes related to 'PATHOLOGY.T.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.92 (0.97)
  N
  1 149
  2 41
  3 109
  4 8
     
  Significant markers N = 1180
  pos. correlated 556
  neg. correlated 624
List of top 10 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
CLEC2L 0.4823 2.707e-19 5.45e-15
ACTA1 0.4795 4.709e-19 9.48e-15
OPRK1 0.454 5.135e-17 1.03e-12
NEUROD2 0.4416 4.387e-16 8.83e-12
SOX8 0.433 1.839e-15 3.7e-11
RRM2 -0.4318 2.255e-15 4.54e-11
SLC35F1 0.4308 2.642e-15 5.32e-11
INSM2 0.4285 3.871e-15 7.79e-11
SOX17 0.4176 2.202e-14 4.43e-10
CRHBP 0.4129 4.579e-14 9.21e-10
Clinical variable #5: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 130
  class1 9
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

651 genes related to 'PATHOLOGY.M.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 233
  M1 53
  MX 19
     
  Significant markers N = 651
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
ANKRD30B 4.347e-11 8.75e-07
POT1 7.921e-11 1.59e-06
ARSK__1 1.208e-10 2.43e-06
TTC37__1 1.208e-10 2.43e-06
NEDD1 3.679e-10 7.4e-06
FLJ10213 4.617e-10 9.29e-06
PPP4R2 4.617e-10 9.29e-06
SCFD1 5.007e-10 1.01e-05
ANP32A__1 5.073e-10 1.02e-05
PABPC1P2 6.281e-10 1.26e-05
Clinical variable #7: 'GENDER'

223 genes related to 'GENDER'.

Table S11.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 111
  MALE 196
     
  Significant markers N = 223
  Higher in MALE 223
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S12.  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__1 21375 8.086e-45 1.63e-40 0.9825
UTP14C 21375 8.086e-45 1.63e-40 0.9825
KIF4B 2944 2.491e-26 5.01e-22 0.8647
TLE1 3607 2.257e-22 4.54e-18 0.8342
COX7C 4097 1.15e-19 2.31e-15 0.8117
CAV2 4206 4.342e-19 8.73e-15 0.8067
C5ORF27 4258 8.124e-19 1.63e-14 0.8043
CCDC146__1 4335 2.036e-18 4.1e-14 0.8007
FRG1B 4337 2.085e-18 4.19e-14 0.8007
CHTF8 17323 6.459e-18 1.3e-13 0.7962
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S13.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 92.12 (7.8)
  Score N
  70 1
  80 4
  90 15
  100 13
     
  Significant markers N = 0
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 27.17 (16)
  Significant markers N = 0
Clinical variable #10: 'RACE'

457 genes related to 'RACE'.

Table S15.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 1
  BLACK OR AFRICAN AMERICAN 37
  WHITE 266
     
  Significant markers N = 457
List of top 10 genes differentially expressed by 'RACE'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

ANOVA_P Q
MKRN1 9.979e-12 2.01e-07
PLAGL2__1 6.751e-11 1.36e-06
POFUT1__1 6.751e-11 1.36e-06
HELZ 7.264e-11 1.46e-06
C5ORF28 2.003e-10 4.03e-06
CCT2 3.516e-10 7.07e-06
CEP192 5.188e-10 1.04e-05
ZNF585B 5.984e-10 1.2e-05
ANP32A__1 8.593e-10 1.73e-05
NEDD1 8.857e-10 1.78e-05
Clinical variable #11: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S17.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 10
  NOT HISPANIC OR LATINO 248
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = KIRC-TP.meth.by_min_clin_corr.data.txt

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

  • Number of patients = 307

  • Number of genes = 20123

  • Number of clinical features = 11

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

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] 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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