Correlation between gene methylation status and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1BG2MX9
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/C1BG2MX9
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 19976 genes and 14 clinical features across 345 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one genes.

  • 81 genes correlated to 'AGE'.

    • INA ,  C17ORF104 ,  ZNF835 ,  IRF4 ,  SYPL2 ,  ...

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

    • TACC2 ,  TEPP ,  FAM13C ,  ESRP2 ,  ABCC10 ,  ...

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

    • KIAA0922 ,  DLEU2__2

  • 1 gene correlated to 'HISTOLOGICAL.TYPE'.

    • MAPKAPK2

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

    • KIAA0922 ,  DLEU2__2 ,  KIAA0284

  • 349 genes correlated to 'GLEASON_SCORE_COMBINED'.

    • FAM13C ,  TEPP ,  SATB1 ,  PKD1L3 ,  OR51A7 ,  ...

  • 519 genes correlated to 'GLEASON_SCORE_PRIMARY'.

    • TEPP ,  FAM13C ,  RRM2 ,  CDC42EP5 ,  RECQL4 ,  ...

  • 1 gene correlated to 'GLEASON_SCORE_SECONDARY'.

    • OR51L1

  • 431 genes correlated to 'GLEASON_SCORE'.

    • FAM13C ,  PKD1L3 ,  OR51A7 ,  CYCS ,  LOC93622 ,  ...

  • 131 genes correlated to 'PSA_RESULT_PREOP'.

    • FCRL2 ,  PSG5 ,  SPDYE7P ,  MYCT1 ,  NLRP11__1 ,  ...

  • 3 genes correlated to 'PSA_VALUE'.

    • MIR30E ,  NFYC__1 ,  OVOL1

  • No genes correlated to 'Time to Death', 'COMPLETENESS.OF.RESECTION', and 'RACE'.

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=81 older N=80 younger N=1
PATHOLOGY T STAGE Spearman correlation test N=123 higher stage N=114 lower stage N=9
PATHOLOGY N STAGE Wilcoxon test N=2 class1 N=2 class0 N=0
HISTOLOGICAL TYPE Wilcoxon test N=1 prostate adenocarcinoma acinar type N=1 prostate adenocarcinoma other subtype N=0
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=3 higher number.of.lymph.nodes N=0 lower number.of.lymph.nodes N=3
GLEASON_SCORE_COMBINED Spearman correlation test N=349 higher score N=220 lower score N=129
GLEASON_SCORE_PRIMARY Spearman correlation test N=519 higher score N=320 lower score N=199
GLEASON_SCORE_SECONDARY Spearman correlation test N=1 higher score N=0 lower score N=1
GLEASON_SCORE Spearman correlation test N=431 higher score N=222 lower score N=209
PSA_RESULT_PREOP Spearman correlation test N=131 higher psa_result_preop N=26 lower psa_result_preop N=105
PSA_VALUE Spearman correlation test N=3 higher psa_value N=2 lower psa_value N=1
RACE Kruskal-Wallis 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) 0.3-151.4 (median=23)
  censored N = 338
  death N = 5
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

81 genes related to 'AGE'.

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

AGE Mean (SD) 60.69 (6.9)
  Significant markers N = 81
  pos. correlated 80
  neg. correlated 1
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
INA 0.3146 3.543e-09 7.08e-05
C17ORF104 0.3138 3.896e-09 7.78e-05
ZNF835 0.2964 2.911e-08 0.000581
IRF4 0.2884 7.054e-08 0.00141
SYPL2 0.2836 1.19e-07 0.00238
OXT 0.2755 2.762e-07 0.00552
GPR25 0.2733 3.462e-07 0.00691
ADRA2C 0.2728 3.643e-07 0.00728
NRN1 0.2716 4.122e-07 0.00823
EPO 0.2707 4.545e-07 0.00908
Clinical variable #3: 'PATHOLOGY.T.STAGE'

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

Table S4.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.59 (0.52)
  N
  2 145
  3 193
  4 5
     
  Significant markers N = 123
  pos. correlated 114
  neg. correlated 9
List of top 10 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S5.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TACC2 0.3453 4.834e-11 9.66e-07
TEPP 0.3299 3.756e-10 7.5e-06
FAM13C 0.328 4.798e-10 9.58e-06
ESRP2 0.3129 3.159e-09 6.31e-05
ABCC10 0.3105 4.229e-09 8.45e-05
SYTL1 0.3051 8.015e-09 0.00016
KBTBD11 0.3054 8.156e-09 0.000163
SLC1A5 0.2982 1.792e-08 0.000358
SATB1 0.299 1.892e-08 0.000378
LDLRAD3 0.2961 2.282e-08 0.000456
Clinical variable #4: 'PATHOLOGY.N.STAGE'

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

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 249
  class1 40
     
  Significant markers N = 2
  Higher in class1 2
  Higher in class0 0
List of 2 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S7.  Get Full Table List of 2 genes differentially expressed by 'PATHOLOGY.N.STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
KIAA0922 2722 4.197e-06 0.0838 0.7267
DLEU2__2 2824 1.115e-05 0.223 0.7165
Clinical variable #5: 'HISTOLOGICAL.TYPE'

One gene related to 'HISTOLOGICAL.TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  PROSTATE ADENOCARCINOMA OTHER SUBTYPE 14
  PROSTATE ADENOCARCINOMA ACINAR TYPE 331
     
  Significant markers N = 1
  Higher in PROSTATE ADENOCARCINOMA ACINAR TYPE 1
  Higher in PROSTATE ADENOCARCINOMA OTHER SUBTYPE 0
List of one gene differentially expressed by 'HISTOLOGICAL.TYPE'

Table S9.  Get Full Table List of one gene differentially expressed by 'HISTOLOGICAL.TYPE'

W(pos if higher in 'PROSTATE ADENOCARCINOMA ACINAR TYPE') wilcoxontestP Q AUC
MAPKAPK2 c("4027", "2.915e-06") c("4027", "2.915e-06") 0.0582 0.869
Clinical variable #6: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S10.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 232
  R1 83
  R2 5
  RX 11
     
  Significant markers N = 0
Clinical variable #7: 'NUMBER.OF.LYMPH.NODES'

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

Table S11.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 0.29 (1.1)
  Significant markers N = 3
  pos. correlated 0
  neg. correlated 3
List of 3 genes differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S12.  Get Full Table List of 3 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
KIAA0922 -0.2831 1.185e-06 0.0237
DLEU2__2 -0.2618 7.519e-06 0.15
KIAA0284 -0.2602 8.606e-06 0.172
Clinical variable #8: 'GLEASON_SCORE_COMBINED'

349 genes related to 'GLEASON_SCORE_COMBINED'.

Table S13.  Basic characteristics of clinical feature: 'GLEASON_SCORE_COMBINED'

GLEASON_SCORE_COMBINED Mean (SD) 7.41 (0.9)
  Significant markers N = 349
  pos. correlated 220
  neg. correlated 129
List of top 10 genes differentially expressed by 'GLEASON_SCORE_COMBINED'

Table S14.  Get Full Table List of top 10 genes significantly correlated to 'GLEASON_SCORE_COMBINED' by Spearman correlation test

SpearmanCorr corrP Q
FAM13C 0.4065 3.654e-15 7.3e-11
TEPP 0.3798 2.784e-13 5.56e-09
SATB1 0.3648 3.341e-12 6.67e-08
PKD1L3 0.3594 5.883e-12 1.17e-07
OR51A7 -0.3428 6.007e-11 1.2e-06
LIX1L 0.3404 8.27e-11 1.65e-06
ICK 0.3403 8.475e-11 1.69e-06
EIF2C1 0.3347 1.781e-10 3.56e-06
RRM2 -0.3346 1.798e-10 3.59e-06
ANO9 0.3263 5.291e-10 1.06e-05
Clinical variable #9: 'GLEASON_SCORE_PRIMARY'

519 genes related to 'GLEASON_SCORE_PRIMARY'.

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

GLEASON_SCORE_PRIMARY Mean (SD) 3.56 (0.59)
  Score N
  2 1
  3 166
  4 161
  5 17
     
  Significant markers N = 519
  pos. correlated 320
  neg. correlated 199
List of top 10 genes differentially expressed by 'GLEASON_SCORE_PRIMARY'

Table S16.  Get Full Table List of top 10 genes significantly correlated to 'GLEASON_SCORE_PRIMARY' by Spearman correlation test

SpearmanCorr corrP Q
TEPP 0.4307 5.192e-17 1.04e-12
FAM13C 0.371 1.06e-12 2.12e-08
RRM2 -0.3673 1.863e-12 3.72e-08
CDC42EP5 0.3528 1.512e-11 3.02e-07
RECQL4 -0.3449 4.526e-11 9.04e-07
LYZ 0.3445 4.756e-11 9.5e-07
TTLL5__1 0.3426 6.181e-11 1.23e-06
EIF2C1 0.3397 9.134e-11 1.82e-06
OXT 0.3381 1.14e-10 2.28e-06
FITM1 0.3366 1.378e-10 2.75e-06
Clinical variable #10: 'GLEASON_SCORE_SECONDARY'

One gene related to 'GLEASON_SCORE_SECONDARY'.

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

GLEASON_SCORE_SECONDARY Mean (SD) 3.85 (0.65)
  Score N
  3 103
  4 190
  5 52
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene differentially expressed by 'GLEASON_SCORE_SECONDARY'

Table S18.  Get Full Table List of one gene significantly correlated to 'GLEASON_SCORE_SECONDARY' by Spearman correlation test

SpearmanCorr corrP Q
OR51L1 -0.2337 1.156e-05 0.231
Clinical variable #11: 'GLEASON_SCORE'

431 genes related to 'GLEASON_SCORE'.

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

GLEASON_SCORE Mean (SD) 7.49 (0.94)
  Score N
  6 30
  7 194
  8 45
  9 74
  10 2
     
  Significant markers N = 431
  pos. correlated 222
  neg. correlated 209
List of top 10 genes differentially expressed by 'GLEASON_SCORE'

Table S20.  Get Full Table List of top 10 genes significantly correlated to 'GLEASON_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
FAM13C 0.4234 1.93e-16 3.86e-12
PKD1L3 0.3689 1.465e-12 2.93e-08
OR51A7 -0.3643 2.9e-12 5.79e-08
CYCS -0.3457 4.047e-11 8.08e-07
LOC93622 -0.3453 4.263e-11 8.51e-07
TEPP 0.3405 8.188e-11 1.64e-06
RECQL4 -0.3402 8.589e-11 1.72e-06
SATB1 0.3396 1.113e-10 2.22e-06
RRM2 -0.3374 1.239e-10 2.47e-06
EIF2C1 0.3371 1.294e-10 2.58e-06
Clinical variable #12: 'PSA_RESULT_PREOP'

131 genes related to 'PSA_RESULT_PREOP'.

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

PSA_RESULT_PREOP Mean (SD) 10.75 (12)
  Significant markers N = 131
  pos. correlated 26
  neg. correlated 105
List of top 10 genes differentially expressed by 'PSA_RESULT_PREOP'

Table S22.  Get Full Table List of top 10 genes significantly correlated to 'PSA_RESULT_PREOP' by Spearman correlation test

SpearmanCorr corrP Q
FCRL2 -0.3408 8.972e-11 1.79e-06
PSG5 -0.2889 5.093e-08 0.00102
SPDYE7P -0.2866 6.552e-08 0.00131
MYCT1 -0.284 9.164e-08 0.00183
NLRP11__1 -0.2828 9.907e-08 0.00198
NLRP4__1 -0.2828 9.907e-08 0.00198
SATB1 0.2822 1.201e-07 0.0024
TP53TG3B -0.2761 2.029e-07 0.00405
PKD1L3 0.2735 2.669e-07 0.00533
CENPF -0.2715 3.281e-07 0.00655
Clinical variable #13: 'PSA_VALUE'

3 genes related to 'PSA_VALUE'.

Table S23.  Basic characteristics of clinical feature: 'PSA_VALUE'

PSA_VALUE Mean (SD) 0.97 (3.5)
  Significant markers N = 3
  pos. correlated 2
  neg. correlated 1
List of 3 genes differentially expressed by 'PSA_VALUE'

Table S24.  Get Full Table List of 3 genes significantly correlated to 'PSA_VALUE' by Spearman correlation test

SpearmanCorr corrP Q
MIR30E 0.2981 1.899e-07 0.00379
NFYC__1 0.2981 1.899e-07 0.00379
OVOL1 -0.2511 1.321e-05 0.264
Clinical variable #14: 'RACE'

No gene related to 'RACE'.

Table S25.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 2
  BLACK OR AFRICAN AMERICAN 7
  WHITE 147
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 345

  • Number of genes = 19976

  • Number of clinical features = 14

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

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

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

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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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