Correlation between gene methylation status and clinical features
Bladder Urothelial Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1348HRG
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/C1348HRG
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 20063 genes and 11 clinical features across 186 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 78 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • POT1 ,  C6ORF129 ,  ERCC3 ,  C7ORF63 ,  CCDC62 ,  ...

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

    • NR1D1 ,  THRA ,  TRIM10 ,  PLB1

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

    • RBMS3 ,  SLC2A12 ,  NBPF3 ,  TLR4 ,  LRRC45 ,  ...

  • 9 genes correlated to 'GENDER'.

    • ALG11__1 ,  UTP14C ,  HIST1H4K ,  KIF4B ,  DDX55 ,  ...

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

    • C2ORF64 ,  UNC50

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • PHLDB3

  • No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.N.STAGE', 'NUMBERPACKYEARSSMOKED', and 'GLEASON_SCORE'.

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=0        
NEOPLASM DISEASESTAGE ANOVA test N=78        
PATHOLOGY T STAGE Spearman correlation test N=4 higher stage N=2 lower stage N=2
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=23        
GENDER t test N=9 male N=4 female N=5
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=2 higher score N=0 lower score N=2
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=0 lower number.of.lymph.nodes N=1
GLEASON_SCORE Spearman correlation 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) 0.1-140.8 (median=7.6)
  censored N = 123
  death N = 56
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 67.74 (11)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

78 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S3.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 2
  STAGE II 59
  STAGE III 65
  STAGE IV 56
     
  Significant markers N = 78
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S4.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
POT1 4.791e-26 9.61e-22
C6ORF129 1.265e-25 2.54e-21
ERCC3 6.232e-25 1.25e-20
C7ORF63 6.006e-24 1.2e-19
CCDC62 1.645e-22 3.3e-18
DYX1C1 7.37e-18 1.48e-13
LCMT1 2.092e-17 4.2e-13
TBKBP1 4.91e-16 9.85e-12
MINPP1 7.679e-14 1.54e-09
SMOX 9.895e-14 1.98e-09

Figure S1.  Get High-res Image As an example, this figure shows the association of POT1 to 'NEOPLASM.DISEASESTAGE'. P value = 4.79e-26 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.83 (0.72)
  N
  0 1
  1 1
  2 51
  3 88
  4 27
     
  Significant markers N = 4
  pos. correlated 2
  neg. correlated 2
List of 4 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S6.  Get Full Table List of 4 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
NR1D1 -0.3772 4.653e-07 0.00934
THRA -0.3772 4.653e-07 0.00934
TRIM10 0.361 1.535e-06 0.0308
PLB1 0.3553 2.292e-06 0.046

Figure S2.  Get High-res Image As an example, this figure shows the association of NR1D1 to 'PATHOLOGY.T.STAGE'. P value = 4.65e-07 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.59 (0.92)
  N
  0 114
  1 17
  2 33
  3 6
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 100
  M1 5
  MX 80
     
  Significant markers N = 23
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
RBMS3 4.586e-12 9.2e-08
SLC2A12 2.668e-08 0.000535
NBPF3 3.04e-08 0.00061
TLR4 3.254e-08 0.000653
LRRC45 6.064e-08 0.00122
STRA13 6.064e-08 0.00122
SP100 1.86e-07 0.00373
LRIG3 1.907e-07 0.00382
TFCP2 3.185e-07 0.00639
TOR2A 3.573e-07 0.00716

Figure S3.  Get High-res Image As an example, this figure shows the association of RBMS3 to 'PATHOLOGY.M.STAGE'. P value = 4.59e-12 with ANOVA analysis.

Clinical variable #7: 'GENDER'

9 genes related to 'GENDER'.

Table S10.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 47
  MALE 139
     
  Significant markers N = 9
  Higher in MALE 4
  Higher in FEMALE 5
List of 9 genes differentially expressed by 'GENDER'

Table S11.  Get Full Table List of 9 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
ALG11__1 9.49 1.737e-12 3.49e-08 0.9579
UTP14C 9.49 1.737e-12 3.49e-08 0.9579
HIST1H4K 5.58 1.002e-07 0.00201 0.651
KIF4B -5.91 1.089e-07 0.00218 0.7713
DDX55 5.2 5.29e-07 0.0106 0.7021
GRHL1 -5.18 6.324e-07 0.0127 0.5956
TP53INP2 -5.11 8.848e-07 0.0177 0.6877
PSORS1C1__2 -4.94 1.741e-06 0.0349 0.6626
PSORS1C2 -4.94 1.741e-06 0.0349 0.6626

Figure S4.  Get High-res Image As an example, this figure shows the association of ALG11__1 to 'GENDER'. P value = 1.74e-12 with T-test analysis.

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S12.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 77.8 (16)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

Table S13.  Get Full Table List of 2 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
C2ORF64 -0.6161 1.908e-06 0.0383
UNC50 -0.6161 1.908e-06 0.0383

Figure S5.  Get High-res Image As an example, this figure shows the association of C2ORF64 to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 1.91e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 38.19 (26)
  Significant markers N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

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

NUMBER.OF.LYMPH.NODES Mean (SD) 1.58 (3.4)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S16.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
PHLDB3 -0.4226 3.637e-07 0.0073

Figure S6.  Get High-res Image As an example, this figure shows the association of PHLDB3 to 'NUMBER.OF.LYMPH.NODES'. P value = 3.64e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'GLEASON_SCORE'

No gene related to 'GLEASON_SCORE'.

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

GLEASON_SCORE Mean (SD) 6.44 (0.68)
  Score N
  6 25
  7 12
  8 1
  9 1
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 186

  • Number of genes = 20063

  • 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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