Correlation between gene methylation status and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1F18XTD
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1F18XTD
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 19971 genes and 14 clinical features across 488 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • INA ,  FZD9 ,  OXT ,  C17ORF104 ,  SOX11 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • FGD4 ,  TACC2 ,  TEPP ,  ABCC10 ,  KIAA0922 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • C11ORF10 ,  FEN1 ,  MIR611 ,  KIAA0922 ,  EIF4A3 ,  ...

  • 30 genes correlated to 'COMPLETENESS_OF_RESECTION'.

    • RIC3 ,  HNF1B ,  FRYL ,  KIAA1751 ,  ULBP3 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • C11ORF10 ,  FEN1 ,  MIR611 ,  KIAA0922 ,  EIF4A3 ,  ...

  • 30 genes correlated to 'GLEASON_SCORE_COMBINED'.

    • FAM13C ,  PLK1 ,  OR51A7 ,  C11ORF10 ,  FEN1 ,  ...

  • 30 genes correlated to 'GLEASON_SCORE_PRIMARY'.

    • C11ORF10 ,  FEN1 ,  MIR611 ,  PLK1 ,  LOC93622 ,  ...

  • 30 genes correlated to 'GLEASON_SCORE_SECONDARY'.

    • FAM13C ,  OR51L1 ,  ULBP3 ,  FAM63A ,  GREB1 ,  ...

  • 30 genes correlated to 'GLEASON_SCORE'.

    • FAM13C ,  KIAA0922 ,  PLK1 ,  OR51A7 ,  C11ORF10 ,  ...

  • 30 genes correlated to 'PSA_RESULT_PREOP'.

    • SATB1 ,  DEGS1 ,  SPDYE7P ,  ANO9 ,  FAM89A ,  ...

  • 30 genes correlated to 'PSA_VALUE'.

    • OR2A7 ,  SNORD17__1 ,  SNX5__1 ,  COMMD4 ,  OVOL1 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'HISTOLOGICAL_TYPE', 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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=30 younger N=0
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=24 lower stage N=6
PATHOLOGY_N_STAGE Wilcoxon test N=30 n1 N=30 n0 N=0
HISTOLOGICAL_TYPE Wilcoxon test   N=0        
COMPLETENESS_OF_RESECTION Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=0 lower number_of_lymph_nodes N=30
GLEASON_SCORE_COMBINED Spearman correlation test N=30 higher score N=16 lower score N=14
GLEASON_SCORE_PRIMARY Spearman correlation test N=30 higher score N=7 lower score N=23
GLEASON_SCORE_SECONDARY Spearman correlation test N=30 higher score N=24 lower score N=6
GLEASON_SCORE Spearman correlation test N=30 higher score N=11 lower score N=19
PSA_RESULT_PREOP Spearman correlation test N=30 higher psa_result_preop N=9 lower psa_result_preop N=21
PSA_VALUE Spearman correlation test N=30 higher psa_value N=7 lower psa_value N=23
RACE Kruskal-Wallis test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No gene related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.7-165.2 (median=26.5)
  censored N = 479
  death N = 8
     
  Significant markers N = 0
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 60.94 (6.8)
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
INA 0.2855 2.125e-10 4.24e-06
FZD9 0.2787 5.827e-10 5.82e-06
OXT 0.2672 3.071e-09 2.04e-05
C17ORF104 0.2595 8.902e-09 4.44e-05
SOX11 0.2554 1.53e-08 6.11e-05
NKX2-5 0.2481 4.019e-08 0.000134
EPO 0.2464 4.98e-08 0.000142
FBLL1 0.2447 6.228e-08 0.000155
CECR6 0.242 8.789e-08 0.000195
UTF1 0.2394 1.204e-07 0.000206
Clinical variable #3: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S4.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.63 (0.52)
  N
  T2 189
  T3 286
  T4 10
     
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
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
FGD4 0.3585 3.756e-16 3.85e-12
TACC2 0.3583 3.856e-16 3.85e-12
TEPP 0.3336 4.529e-14 3.01e-10
ABCC10 0.3287 1.104e-13 5.47e-10
KIAA0922 -0.3275 1.37e-13 5.47e-10
FAM13C 0.3252 2.077e-13 6.91e-10
INPP5K 0.3226 3.277e-13 9.35e-10
FAM55B 0.3199 5.262e-13 1.31e-09
KBTBD11 0.3187 6.885e-13 1.53e-09
SATB1 0.3067 6.158e-12 1.23e-08
Clinical variable #4: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Labels N
  N0 341
  N1 77
     
  Significant markers N = 30
  Higher in N1 30
  Higher in N0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S7.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

W(pos if higher in 'N1') wilcoxontestP Q AUC
C11ORF10 6139 2.895e-13 1.93e-09 0.7662
FEN1 6139 2.895e-13 1.93e-09 0.7662
MIR611 6139 2.895e-13 1.93e-09 0.7662
KIAA0922 6334 1.288e-12 6.43e-09 0.7588
EIF4A3 7292 1.094e-09 3.79e-06 0.7223
GUCA1B 7298 1.138e-09 3.79e-06 0.7221
ERP29__1 7397 2.159e-09 5.39e-06 0.7183
TMEM116__1 7397 2.159e-09 5.39e-06 0.7183
DHX9 7435 2.753e-09 6.11e-06 0.7168
HN1 7571 6.489e-09 1.3e-05 0.7117
Clinical variable #5: 'HISTOLOGICAL_TYPE'

No gene related to 'HISTOLOGICAL_TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  PROSTATE ADENOCARCINOMA OTHER SUBTYPE 15
  PROSTATE ADENOCARCINOMA ACINAR TYPE 473
     
  Significant markers N = 0
Clinical variable #6: 'COMPLETENESS_OF_RESECTION'

30 genes related to 'COMPLETENESS_OF_RESECTION'.

Table S9.  Basic characteristics of clinical feature: 'COMPLETENESS_OF_RESECTION'

COMPLETENESS_OF_RESECTION Labels N
  R0 313
  R1 141
  R2 5
  RX 15
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'COMPLETENESS_OF_RESECTION'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS_OF_RESECTION'

kruskal_wallis_P Q
RIC3 2.075e-07 0.00414
HNF1B 9.509e-07 0.00949
FRYL 4.07e-06 0.0138
KIAA1751 4.515e-06 0.0138
ULBP3 4.536e-06 0.0138
ARGLU1 6.625e-06 0.0138
LOC93622 6.841e-06 0.0138
SMAP1 7.072e-06 0.0138
ABCC8 8.064e-06 0.0138
PGS1 9.512e-06 0.0138
Clinical variable #7: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

Table S11.  Basic characteristics of clinical feature: 'NUMBER_OF_LYMPH_NODES'

NUMBER_OF_LYMPH_NODES Mean (SD) 0.44 (1.4)
  Significant markers N = 30
  pos. correlated 0
  neg. correlated 30
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S12.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
C11ORF10 -0.3732 1.152e-14 7.67e-11
FEN1 -0.3732 1.152e-14 7.67e-11
MIR611 -0.3732 1.152e-14 7.67e-11
KIAA0922 -0.3702 1.945e-14 9.71e-11
EIF4A3 -0.3258 2.411e-11 9.63e-08
GUCA1B -0.317 8.667e-11 2.88e-07
DHX9 -0.3058 4.203e-10 9.77e-07
HN1 -0.3055 4.327e-10 9.77e-07
ERP29__1 -0.3047 4.894e-10 9.77e-07
TMEM116__1 -0.3047 4.894e-10 9.77e-07
Clinical variable #8: 'GLEASON_SCORE_COMBINED'

30 genes related to 'GLEASON_SCORE_COMBINED'.

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

GLEASON_SCORE_COMBINED Mean (SD) 7.56 (1)
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
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 0.4218 1.779e-22 3.55e-18
PLK1 -0.4043 1.295e-20 6.64e-17
OR51A7 -0.4031 1.705e-20 6.64e-17
C11ORF10 -0.4025 1.995e-20 6.64e-17
FEN1 -0.4025 1.995e-20 6.64e-17
MIR611 -0.4025 1.995e-20 6.64e-17
PTPRN2 0.3882 5.348e-19 1.53e-15
KIAA0922 -0.3813 2.458e-18 6.14e-15
FGD4 0.3591 2.671e-16 5.9e-13
CYP7B1 0.3586 2.954e-16 5.9e-13
Clinical variable #9: 'GLEASON_SCORE_PRIMARY'

30 genes related to 'GLEASON_SCORE_PRIMARY'.

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

GLEASON_SCORE_PRIMARY Mean (SD) 3.69 (0.68)
  Score N
  2 1
  3 206
  4 222
  5 59
     
  Significant markers N = 30
  pos. correlated 7
  neg. correlated 23
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
C11ORF10 -0.4386 2.313e-24 1.54e-20
FEN1 -0.4386 2.313e-24 1.54e-20
MIR611 -0.4386 2.313e-24 1.54e-20
PLK1 -0.4224 1.525e-22 7.61e-19
LOC93622 -0.3897 3.833e-19 1.53e-15
OR51A7 -0.3814 2.41e-18 8.02e-15
LYZ 0.3695 3.089e-17 8.81e-14
ERP29__1 -0.364 9.855e-17 2.15e-13
TMEM116__1 -0.364 9.855e-17 2.15e-13
TEPP 0.3635 1.078e-16 2.15e-13
Clinical variable #10: 'GLEASON_SCORE_SECONDARY'

30 genes related to 'GLEASON_SCORE_SECONDARY'.

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

GLEASON_SCORE_SECONDARY Mean (SD) 3.86 (0.68)
  Score N
  3 151
  4 252
  5 85
     
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
List of top 10 genes differentially expressed by 'GLEASON_SCORE_SECONDARY'

Table S18.  Get Full Table List of top 10 genes significantly correlated to 'GLEASON_SCORE_SECONDARY' by Spearman correlation test

SpearmanCorr corrP Q
FAM13C 0.2608 4.988e-09 9.96e-05
OR51L1 -0.2508 1.962e-08 0.000196
ULBP3 0.2364 1.258e-07 0.000837
FAM63A 0.2294 3.023e-07 0.00135
GREB1 0.2284 3.385e-07 0.00135
CREB3L1 0.2217 7.563e-07 0.002
DNAJC11 0.2212 8.009e-07 0.002
THAP3 0.2212 8.009e-07 0.002
PTPRN2 0.218 1.166e-06 0.00244
OR51A7 -0.2176 1.222e-06 0.00244
Clinical variable #11: 'GLEASON_SCORE'

30 genes related to 'GLEASON_SCORE'.

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

GLEASON_SCORE Mean (SD) 7.59 (1)
  Score N
  6 45
  7 247
  8 62
  9 131
  10 3
     
  Significant markers N = 30
  pos. correlated 11
  neg. correlated 19
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 0.4197 3.067e-22 6.12e-18
KIAA0922 -0.4108 2.742e-21 2.74e-17
PLK1 -0.4055 9.836e-21 6.55e-17
OR51A7 -0.3929 1.822e-19 9.1e-16
C11ORF10 -0.3875 6.224e-19 1.78e-15
FEN1 -0.3875 6.224e-19 1.78e-15
MIR611 -0.3875 6.224e-19 1.78e-15
FGD4 0.3848 1.15e-18 2.87e-15
CTPS -0.3817 2.279e-18 5.06e-15
PTPRN2 0.3774 5.818e-18 1.16e-14
Clinical variable #12: 'PSA_RESULT_PREOP'

30 genes related to 'PSA_RESULT_PREOP'.

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

PSA_RESULT_PREOP Mean (SD) 10.84 (12)
  Significant markers N = 30
  pos. correlated 9
  neg. correlated 21
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
SATB1 0.2535 1.717e-08 0.000318
DEGS1 -0.2478 3.188e-08 0.000318
SPDYE7P -0.2379 1.145e-07 0.00062
ANO9 0.2373 1.242e-07 0.00062
FAM89A 0.2336 1.954e-07 0.00078
CYP2C8 -0.2296 3.197e-07 0.000866
TMEM121 0.2279 3.913e-07 0.000866
PSG5 -0.2276 4.069e-07 0.000866
LOC645166 -0.2276 4.079e-07 0.000866
FLJ12825__1 -0.2253 5.374e-07 0.000866
Clinical variable #13: 'PSA_VALUE'

30 genes related to 'PSA_VALUE'.

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

PSA_VALUE Mean (SD) 1.07 (4.1)
  Significant markers N = 30
  pos. correlated 7
  neg. correlated 23
List of top 10 genes differentially expressed by 'PSA_VALUE'

Table S24.  Get Full Table List of top 10 genes significantly correlated to 'PSA_VALUE' by Spearman correlation test

SpearmanCorr corrP Q
OR2A7 -0.2342 8.513e-07 0.0092
SNORD17__1 -0.2298 1.382e-06 0.0092
SNX5__1 -0.2298 1.382e-06 0.0092
COMMD4 0.2182 4.694e-06 0.0188
OVOL1 -0.2166 5.528e-06 0.0188
BAIAP2__1 0.2118 9.013e-06 0.0188
CST7 -0.2107 1.005e-05 0.0188
C10ORF119 -0.2092 1.168e-05 0.0188
C6ORF41__1 0.2086 1.231e-05 0.0188
LOC100270746__1 0.2086 1.231e-05 0.0188
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 = 488

  • Number of genes = 19971

  • Number of clinical features = 14

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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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