Correlation between gene methylation status and clinical features
Bladder Urothelial Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1GB22W3
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/C1GB22W3
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 19964 genes and 12 clinical features across 260 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 95 genes correlated to 'AGE'.

    • KLHL31 ,  PLVAP ,  REM2 ,  COL1A1 ,  PRR7 ,  ...

  • 14 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • GATA6 ,  NR1D1 ,  THRA ,  ABCG2 ,  FGF1 ,  ...

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

    • NR1D1 ,  THRA ,  HSH2D ,  LRP1 ,  GATA6 ,  ...

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

    • CORO7 ,  VASN ,  SPNS2 ,  THSD4 ,  MBL1P ,  ...

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

    • IGF2R__1 ,  LOC729603 ,  FSTL5 ,  HERC2P2 ,  CR1L ,  ...

  • 14 genes correlated to 'GENDER'.

    • ALG11__1 ,  UTP14C ,  KIF4B ,  C2ORF7 ,  CCT7 ,  ...

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

    • KIAA0319 ,  RIPK4 ,  IRF2 ,  PCDHB7 ,  VAPA ,  ...

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

    • CORO7 ,  VASN ,  GDPD3 ,  LOC100271831 ,  PHLDB3 ,  ...

  • 922 genes correlated to 'RACE'.

    • LMTK2 ,  SNX14 ,  MANBA ,  SH3YL1 ,  ZNF292 ,  ...

  • No genes correlated to 'Time to Death', '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=95 older N=74 younger N=21
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=14        
PATHOLOGY T STAGE Spearman correlation test N=144 higher stage N=76 lower stage N=68
PATHOLOGY N STAGE Spearman correlation test N=8 higher stage N=1 lower stage N=7
PATHOLOGY M STAGE Kruskal-Wallis test N=93        
GENDER Wilcoxon test N=14 male N=14 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=30 higher score N=25 lower score N=5
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=9 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=8
RACE Kruskal-Wallis test N=922        
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) 0.1-140.8 (median=8.9)
  censored N = 175
  death N = 77
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

95 genes related to 'AGE'.

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

AGE Mean (SD) 67.61 (11)
  Significant markers N = 95
  pos. correlated 74
  neg. correlated 21
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
KLHL31 0.3386 2.295e-08 0.000458
PLVAP -0.3168 1.908e-07 0.00381
REM2 0.3089 3.923e-07 0.00783
COL1A1 -0.3069 4.711e-07 0.0094
PRR7 0.3 8.704e-07 0.0174
C4BPB 0.2993 9.312e-07 0.0186
PRDX5__1 0.2944 1.419e-06 0.0283
TRMT112 0.2944 1.419e-06 0.0283
C14ORF72 0.2924 1.679e-06 0.0335
RFWD2 0.2916 1.81e-06 0.0361
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

14 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 84
  STAGE III 85
  STAGE IV 84
     
  Significant markers N = 14
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
GATA6 3.809e-07 0.0076
NR1D1 7.275e-07 0.0145
THRA 7.275e-07 0.0145
ABCG2 1.713e-06 0.0342
FGF1 2.389e-06 0.0477
ZBP1 2.682e-06 0.0535
OAS1 2.949e-06 0.0589
EPB41L4B 3.771e-06 0.0753
C8ORF51 8.549e-06 0.171
RHPN1 8.549e-06 0.171
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

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

PATHOLOGY.T.STAGE Mean (SD) 2.82 (0.71)
  N
  0 1
  1 1
  2 76
  3 123
  4 37
     
  Significant markers N = 144
  pos. correlated 76
  neg. correlated 68
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 -0.371 3.513e-09 7.01e-05
THRA -0.371 3.513e-09 7.01e-05
HSH2D 0.3546 1.845e-08 0.000368
LRP1 -0.3525 2.273e-08 0.000454
GATA6 -0.3438 5.224e-08 0.00104
OAS1 0.3433 5.518e-08 0.0011
ABCG2 0.3421 6.165e-08 0.00123
PRPF6 0.3416 6.485e-08 0.00129
SAMD10 0.3416 6.485e-08 0.00129
EMR3 0.3393 8.006e-08 0.0016
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.62 (0.91)
  N
  0 156
  1 26
  2 50
  3 7
     
  Significant markers N = 8
  pos. correlated 1
  neg. correlated 7
List of 8 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S9.  Get Full Table List of 8 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
CORO7 -0.3068 1.33e-06 0.0265
VASN -0.3068 1.33e-06 0.0265
SPNS2 -0.3011 2.121e-06 0.0423
THSD4 -0.2901 5.11e-06 0.102
MBL1P 0.2881 5.997e-06 0.12
SVOPL -0.2838 8.312e-06 0.166
CLIC3 -0.2802 1.093e-05 0.218
DAB2 -0.2763 1.467e-05 0.293
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 128
  M1 7
  MX 124
     
  Significant markers N = 93
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
IGF2R__1 4.957e-08 0.00099
LOC729603 4.957e-08 0.00099
FSTL5 2.018e-07 0.00403
HERC2P2 2.349e-07 0.00469
CR1L 3.456e-07 0.0069
ZDHHC14 5.549e-07 0.0111
AGAP5 8.153e-07 0.0163
SLC2A6 8.908e-07 0.0178
MEGF6 1.159e-06 0.0231
NINJ1 1.197e-06 0.0239
Clinical variable #7: 'GENDER'

14 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 66
  MALE 194
     
  Significant markers N = 14
  Higher in MALE 14
  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 12338 2.383e-29 4.76e-25 0.9636
UTP14C 12338 2.383e-29 4.76e-25 0.9636
KIF4B 2624 8.176e-13 1.63e-08 0.7951
C2ORF7 10177 8.522e-13 1.7e-08 0.7948
CCT7 10177 8.522e-13 1.7e-08 0.7948
DDX55 9338 2.657e-08 0.00053 0.7293
FASTKD2__1 3599 1.093e-07 0.00218 0.7189
MDH1B__1 3599 1.093e-07 0.00218 0.7189
SHC3 3895 2.037e-06 0.0407 0.6958
TCF7 4036 7.377e-06 0.147 0.6848
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

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

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 79.62 (16)
  Significant markers N = 30
  pos. correlated 25
  neg. correlated 5
List of top 10 genes differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

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

SpearmanCorr corrP Q
KIAA0319 0.5245 5.916e-07 0.0118
RIPK4 0.5198 7.744e-07 0.0155
IRF2 0.5107 1.3e-06 0.0259
PCDHB7 -0.5078 1.529e-06 0.0305
VAPA -0.5075 1.553e-06 0.031
ENTPD3 0.5044 1.842e-06 0.0368
ZBTB7A 0.5039 1.884e-06 0.0376
TULP4 0.5026 2.025e-06 0.0404
ACBD4 0.4945 3.131e-06 0.0625
PLCD3 0.4945 3.131e-06 0.0625
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 37.92 (27)
  Significant markers N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

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

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

NUMBER.OF.LYMPH.NODES Mean (SD) 2.13 (7.7)
  Significant markers N = 9
  pos. correlated 1
  neg. correlated 8
List of 9 genes differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S18.  Get Full Table List of 9 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
CORO7 -0.3419 7.721e-07 0.0154
VASN -0.3419 7.721e-07 0.0154
GDPD3 -0.3263 2.552e-06 0.0509
LOC100271831 -0.3263 2.552e-06 0.0509
PHLDB3 -0.3138 6.366e-06 0.127
BOK -0.3117 7.419e-06 0.148
SPNS2 -0.3089 9.054e-06 0.181
RNASE13 0.306 1.105e-05 0.221
RER1 -0.3047 1.213e-05 0.242
Clinical variable #11: 'RACE'

922 genes related to 'RACE'.

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

RACE Labels N
  ASIAN 30
  BLACK OR AFRICAN AMERICAN 13
  WHITE 198
     
  Significant markers N = 922
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
LMTK2 9.585e-10 1.91e-05
SNX14 3.453e-09 6.89e-05
MANBA 4.684e-09 9.35e-05
SH3YL1 5.018e-09 1e-04
ZNF292 7.939e-09 0.000158
NDRG2 1.077e-08 0.000215
PHF2 1.134e-08 0.000226
BIN3 1.176e-08 0.000235
FLJ14107 1.176e-08 0.000235
SH2D4A 1.458e-08 0.000291
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S21.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 239
     
  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 = 260

  • Number of genes = 19964

  • Number of clinical features = 12

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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