Correlation between gene methylation status and clinical features
Bladder Urothelial Carcinoma (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/C1VX0F7N
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 20058 genes and 11 clinical features across 214 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 5 genes correlated to 'AGE'.

    • PLVAP ,  KCNH5 ,  KLHL31 ,  PRDX5__1 ,  TRMT112

  • 11 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • FGF1 ,  NR1D1 ,  THRA ,  C2ORF70 ,  FPGS ,  ...

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

    • NR1D1 ,  THRA ,  C2ORF70 ,  HSH2D ,  TBX4 ,  ...

  • 6 genes correlated to 'PATHOLOGY.N.STAGE'.

    • SPNS2 ,  SVOPL ,  CORO7 ,  VASN ,  EXT1 ,  ...

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

    • RYBP ,  ADORA3 ,  NINJ1 ,  CHERP ,  HERC2P2 ,  ...

  • 34 genes correlated to 'GENDER'.

    • ALG11__1 ,  UTP14C ,  B3GNT1 ,  KIF4B ,  APOC1 ,  ...

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

    • KIAA0319 ,  MITD1__1 ,  MRPL30__1 ,  HTR7 ,  VAPA ,  ...

  • 12 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

    • CDK2 ,  SILV ,  PHLDB3 ,  GDPD3__1 ,  LOC100271831__1 ,  ...

  • 958 genes correlated to 'RACE'.

    • MANBA ,  RBM47 ,  NDRG2 ,  BPGM ,  DNM2 ,  ...

  • No genes correlated to 'Time to Death', and 'NUMBERPACKYEARSSMOKED'.

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=5 older N=4 younger N=1
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=11        
PATHOLOGY T STAGE Spearman correlation test N=70 higher stage N=33 lower stage N=37
PATHOLOGY N STAGE Spearman correlation test N=6 higher stage N=1 lower stage N=5
PATHOLOGY M STAGE Kruskal-Wallis test N=54        
GENDER Wilcoxon test N=34 male N=34 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=10 higher score N=2 lower score N=8
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=12 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=11
RACE Kruskal-Wallis test N=958        
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=8.2)
  censored N = 150
  death N = 58
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

5 genes related to 'AGE'.

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

AGE Mean (SD) 67.63 (11)
  Significant markers N = 5
  pos. correlated 4
  neg. correlated 1
List of 5 genes differentially expressed by 'AGE'

Table S3.  Get Full Table List of 5 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
PLVAP -0.337 4.709e-07 0.00944
KCNH5 0.317 2.481e-06 0.0498
KLHL31 0.3095 4.153e-06 0.0833
PRDX5__1 0.2972 1.026e-05 0.206
TRMT112 0.2972 1.026e-05 0.206
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

11 genes related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE 0A 1
  STAGE I 2
  STAGE II 70
  STAGE III 69
  STAGE IV 68
     
  Significant markers N = 11
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
FGF1 4.451e-07 0.00893
NR1D1 6.914e-07 0.0139
THRA 6.914e-07 0.0139
C2ORF70 1.174e-06 0.0236
FPGS 1.564e-06 0.0314
ZBP1 4.107e-06 0.0824
INPP5F 4.891e-06 0.0981
C8ORF51__1 5.823e-06 0.117
RHPN1__1 5.823e-06 0.117
ABCG2 8.366e-06 0.168
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

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

PATHOLOGY.T.STAGE Mean (SD) 2.83 (0.72)
  N
  0 1
  1 1
  2 61
  3 98
  4 33
     
  Significant markers N = 70
  pos. correlated 33
  neg. correlated 37
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
NR1D1 -0.3883 2.213e-08 0.000444
THRA -0.3883 2.213e-08 0.000444
C2ORF70 0.3754 6.904e-08 0.00138
HSH2D 0.3683 1.265e-07 0.00254
TBX4 -0.3556 3.605e-07 0.00723
PRPF6 0.3538 4.175e-07 0.00837
SAMD10 0.3538 4.175e-07 0.00837
PLB1 0.3495 5.908e-07 0.0118
PCDHGA1__14 -0.348 6.609e-07 0.0133
PCDHGA2__14 -0.348 6.609e-07 0.0133
Clinical variable #5: 'PATHOLOGY.N.STAGE'

6 genes related to 'PATHOLOGY.N.STAGE'.

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

PATHOLOGY.N.STAGE Mean (SD) 0.61 (0.92)
  N
  0 129
  1 22
  2 39
  3 7
     
  Significant markers N = 6
  pos. correlated 1
  neg. correlated 5
List of 6 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S9.  Get Full Table List of 6 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SPNS2 -0.3218 4.017e-06 0.0806
SVOPL -0.3138 7.109e-06 0.143
CORO7 -0.31 9.311e-06 0.187
VASN -0.31 9.311e-06 0.187
EXT1 0.3061 1.214e-05 0.243
CLIC3 -0.3055 1.271e-05 0.255
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 108
  M1 5
  MX 100
     
  Significant markers N = 54
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
RYBP 6.755e-07 0.0135
ADORA3 7.816e-07 0.0157
NINJ1 8.647e-07 0.0173
CHERP 1.294e-06 0.0259
HERC2P2 1.43e-06 0.0287
MFSD6L 1.43e-06 0.0287
PLLP 1.611e-06 0.0323
SLC2A6 1.629e-06 0.0327
ZDHHC14 1.637e-06 0.0328
IL17REL 1.782e-06 0.0357
Clinical variable #7: 'GENDER'

34 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 51
  MALE 163
     
  Significant markers N = 34
  Higher in MALE 34
  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 7975 4.464e-23 8.95e-19 0.9593
UTP14C 7975 4.464e-23 8.95e-19 0.9593
B3GNT1 7017 1.256e-13 2.52e-09 0.8441
KIF4B 1873 3.307e-09 6.63e-05 0.7747
APOC1 2077 7.164e-08 0.00144 0.7502
APITD1__1 2320 1.962e-06 0.0393 0.7209
ACBD5 2361 3.301e-06 0.0662 0.716
ALDH3B2 2367 3.56e-06 0.0714 0.7153
C10ORF57 2370 3.696e-06 0.0741 0.7149
LOC219347 2370 3.696e-06 0.0741 0.7149
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

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

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 79.3 (16)
  Significant markers N = 10
  pos. correlated 2
  neg. correlated 8
List of 10 genes differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S15.  Get Full Table List of 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
KIAA0319 0.59 1.366e-06 0.0274
MITD1__1 -0.5651 4.666e-06 0.0936
MRPL30__1 -0.5651 4.666e-06 0.0936
HTR7 0.5551 7.401e-06 0.148
VAPA -0.5539 7.848e-06 0.157
CD33 -0.5485 1.002e-05 0.201
PLA2G7 -0.5468 1.079e-05 0.216
C2ORF42 -0.5461 1.112e-05 0.223
ISG20 -0.5449 1.173e-05 0.235
GEMIN6 -0.544 1.221e-05 0.245
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 38.89 (28)
  Significant markers N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

12 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S17.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.56 (3.2)
  Significant markers N = 12
  pos. correlated 1
  neg. correlated 11
List of top 10 genes differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S18.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
CDK2 -0.408 8.521e-08 0.00171
SILV -0.408 8.521e-08 0.00171
PHLDB3 -0.396 2.18e-07 0.00437
GDPD3__1 -0.3667 1.851e-06 0.0371
LOC100271831__1 -0.3667 1.851e-06 0.0371
CORO7 -0.3653 2.034e-06 0.0408
VASN -0.3653 2.034e-06 0.0408
BEAN -0.3635 2.302e-06 0.0461
FHL2 -0.362 2.559e-06 0.0513
RNASE13 0.3433 8.838e-06 0.177
Clinical variable #11: 'RACE'

958 genes related to 'RACE'.

Table S19.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 22
  BLACK OR AFRICAN AMERICAN 12
  WHITE 167
     
  Significant markers N = 958
List of top 10 genes differentially expressed by 'RACE'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

ANOVA_P Q
MANBA 4.559e-09 9.14e-05
RBM47 5.44e-09 0.000109
NDRG2 5.573e-09 0.000112
BPGM 5.821e-09 0.000117
DNM2 6.781e-09 0.000136
SNX14 7.447e-09 0.000149
CCDC101 7.823e-09 0.000157
SGPL1 8.083e-09 0.000162
ZNF292 8.605e-09 0.000173
SH3YL1 9.156e-09 0.000184
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 = 214

  • Number of genes = 20058

  • 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)