Correlation between gene methylation status and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1Z036W1
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/C1Z036W1
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 20154 genes and 11 clinical features across 297 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one genes.

  • 16 genes correlated to 'Time to Death'.

    • LUZP2 ,  EBF2 ,  SALL1 ,  OR14I1 ,  CA1 ,  ...

  • 34 genes correlated to 'AGE'.

    • MRPS33 ,  TSPYL5 ,  ZYG11A ,  DOK6 ,  RANBP17 ,  ...

  • 847 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • NOS1 ,  ACTA1 ,  OPRK1 ,  NEUROD2 ,  AVPR1A ,  ...

  • 1196 genes correlated to 'PATHOLOGY.T.STAGE'.

    • ACTA1 ,  NOS1 ,  OPRK1 ,  DBX2 ,  AVPR1A ,  ...

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

    • C20ORF112 ,  HTR6 ,  MYO10 ,  CSDC2 ,  AJAP1 ,  ...

  • 199 genes correlated to 'GENDER'.

    • ALG11__1 ,  UTP14C ,  CCBL2 ,  RBMXL1 ,  KIF4B ,  ...

  • 67 genes correlated to 'RACE'.

    • MKRN1 ,  C5ORF28 ,  LOC253039 ,  PSMD5 ,  ATP5I ,  ...

  • No genes correlated to '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=16 shorter survival N=7 longer survival N=9
AGE Spearman correlation test N=34 older N=27 younger N=7
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=847        
PATHOLOGY T STAGE Spearman correlation test N=1196 higher stage N=546 lower stage N=650
PATHOLOGY N STAGE Wilcoxon test   N=0        
PATHOLOGY M STAGE Kruskal-Wallis test N=109        
GENDER Wilcoxon test N=199 male N=199 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
RACE Kruskal-Wallis test N=67        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

16 genes related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Years) 3-3668 (median=1092)
  censored N = 198
  death N = 13
     
  Significant markers N = 16
  associated with shorter survival 7
  associated with longer survival 9
List of top 10 genes differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
LUZP2 0 1.055e-07 0.0021 0.267
EBF2 850001 2.817e-07 0.0057 0.595
SALL1 64 3.199e-07 0.0064 0.593
OR14I1 0 1.128e-06 0.023 0.168
CA1 0 2.134e-06 0.043 0.257
KCND2 300001 2.217e-06 0.045 0.602
DDI1 0 2.534e-06 0.051 0.321
PDGFD 0 2.534e-06 0.051 0.321
CDH20 0 3.217e-06 0.065 0.432
OPCML 32001 3.297e-06 0.066 0.753
Clinical variable #2: 'AGE'

34 genes related to 'AGE'.

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

AGE Mean (SD) 61.44 (12)
  Significant markers N = 34
  pos. correlated 27
  neg. correlated 7
List of top 10 genes differentially expressed by 'AGE'

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
MRPS33 0.3414 1.524e-09 3.07e-05
TSPYL5 0.3227 1.265e-08 0.000255
ZYG11A 0.3177 2.176e-08 0.000439
DOK6 0.3162 2.555e-08 0.000515
RANBP17 0.3083 5.824e-08 0.00117
PVT1 -0.3025 1.064e-07 0.00214
UNC80 0.2997 1.4e-07 0.00282
ME3 -0.2979 1.681e-07 0.00339
SLC10A4 0.294 2.463e-07 0.00496
DDX25__1 0.2939 2.496e-07 0.00503
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

847 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 138
  STAGE II 30
  STAGE III 74
  STAGE IV 55
     
  Significant markers N = 847
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
NOS1 4.429e-16 8.93e-12
ACTA1 4.987e-15 1.01e-10
OPRK1 5.418e-15 1.09e-10
NEUROD2 1.254e-14 2.53e-10
AVPR1A 3.324e-14 6.7e-10
SYN2 4.413e-14 8.89e-10
MYO10 1.2e-13 2.42e-09
DBX2 2.067e-13 4.16e-09
SOX17 2.929e-13 5.9e-09
CRHBP 7.087e-13 1.43e-08
Clinical variable #4: 'PATHOLOGY.T.STAGE'

1196 genes related to 'PATHOLOGY.T.STAGE'.

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

PATHOLOGY.T.STAGE Mean (SD) 1.94 (0.97)
  N
  1 142
  2 39
  3 108
  4 8
     
  Significant markers N = 1196
  pos. correlated 546
  neg. correlated 650
List of top 10 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
ACTA1 0.4688 1.242e-17 2.5e-13
NOS1 0.4602 5.707e-17 1.15e-12
OPRK1 0.4498 3.355e-16 6.76e-12
DBX2 0.44 1.725e-15 3.48e-11
AVPR1A 0.4386 2.137e-15 4.31e-11
NEUROD2 0.4376 2.53e-15 5.1e-11
SLC35F1 0.436 3.253e-15 6.55e-11
SYN2 0.4343 4.277e-15 8.62e-11
RRM2 -0.4254 1.74e-14 3.5e-10
CECR1 -0.4249 1.887e-14 3.8e-10
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Labels N
  class0 129
  class1 9
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 233
  M1 53
  MX 9
     
  Significant markers N = 109
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
C20ORF112 2.626e-09 5.29e-05
HTR6 2.158e-08 0.000435
MYO10 2.781e-08 0.00056
CSDC2 6.693e-08 0.00135
AJAP1 1.103e-07 0.00222
STK24 1.132e-07 0.00228
WNT2 1.642e-07 0.00331
BEND4 1.76e-07 0.00355
SLC6A11 2.871e-07 0.00578
ASB4 2.943e-07 0.00593
Clinical variable #7: 'GENDER'

199 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 104
  MALE 193
     
  Significant markers N = 199
  Higher in MALE 199
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S13.  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 19703 1.139e-42 2.29e-38 0.9816
UTP14C 19703 1.139e-42 2.29e-38 0.9816
CCBL2 17541 2.175e-26 4.38e-22 0.8739
RBMXL1 17541 2.175e-26 4.38e-22 0.8739
KIF4B 2773 8.096e-25 1.63e-20 0.8618
TLE1 3487 1.771e-20 3.57e-16 0.8263
C5ORF27 3757 5.954e-19 1.2e-14 0.8128
CHTF8 16279 9.41e-19 1.9e-14 0.811
HAS3 16279 9.41e-19 1.9e-14 0.811
COX7C 3865 2.333e-18 4.7e-14 0.8074
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S14.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 92.41 (7.9)
  Score N
  70 1
  80 3
  90 13
  100 12
     
  Significant markers N = 0
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 24.67 (16)
  Significant markers N = 0
Clinical variable #10: 'RACE'

67 genes related to 'RACE'.

Table S16.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 1
  BLACK OR AFRICAN AMERICAN 27
  WHITE 266
     
  Significant markers N = 67
List of top 10 genes differentially expressed by 'RACE'

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

ANOVA_P Q
MKRN1 2.574e-08 0.000519
C5ORF28 2.395e-07 0.00483
LOC253039 4.062e-07 0.00819
PSMD5 4.062e-07 0.00819
ATP5I 8.61e-07 0.0173
CEP192 1.157e-06 0.0233
CROT 1.221e-06 0.0246
TP53TG1 1.221e-06 0.0246
GSTCD__1 1.344e-06 0.0271
INTS12 1.344e-06 0.0271
Clinical variable #11: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S18.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 8
  NOT HISPANIC OR LATINO 240
     
  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 = 297

  • Number of genes = 20154

  • 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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