Correlation between gene methylation status and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1RF5TGG
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1RF5TGG
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features. The input file "PRAD-TP.meth.by_min_clin_corr.data.txt" is generated in the pipeline Methylation_Preprocess in stddata run.

Summary

Testing the association between 17007 genes and 11 clinical features across 498 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • INA ,  FZD9 ,  OXT ,  CECR6 ,  EPO ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

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

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • FEN1 ,  KIAA0922 ,  EIF4A3 ,  GUCA1B ,  HN1 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • KIAA0922 ,  LOC595101 ,  RPS6KL1 ,  PLK1 ,  SAMD1 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • RIC3 ,  KIAA1751 ,  FRYL ,  ARGLU1 ,  MAST2 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • KIAA0922 ,  FEN1 ,  EIF4A3 ,  GUCA1B ,  CORO7 ,  ...

  • 30 genes correlated to 'GLEASON_SCORE'.

    • FAM13C ,  KIAA0922 ,  PLK1 ,  OR51A7 ,  FGD4 ,  ...

  • 30 genes correlated to 'PSA_VALUE'.

    • OR2A7 ,  COMMD4 ,  LOC100270746 ,  OVOL1 ,  BAIAP2 ,  ...

  • 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=23 lower stage N=7
PATHOLOGY_N_STAGE Wilcoxon test N=30 n1 N=30 n0 N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Wilcoxon test   N=0        
RESIDUAL_TUMOR 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 Spearman correlation test N=30 higher score N=11 lower score N=19
PSA_VALUE Spearman correlation test N=30 higher psa_value N=10 lower psa_value N=20
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) 0.8-165.2 (median=30.5)
  censored N = 487
  death N = 10
     
  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) 61.02 (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 0.2741 7.641e-10 1.3e-05
FZD9 0.2632 3.704e-09 3.15e-05
OXT 0.2562 9.778e-09 5.54e-05
CECR6 0.2421 6.328e-08 0.000253
EPO 0.2396 8.714e-08 0.000253
SOX11 0.2388 9.663e-08 0.000253
TMEM74 0.2377 1.106e-07 0.000253
C17ORF104 0.2371 1.19e-07 0.000253
NKX2-5 0.2349 1.576e-07 0.00028
RPP25 0.2345 1.645e-07 0.00028
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) 2.64 (0.52)
  N
  T2 188
  T3 293
  T4 10
     
  Significant markers N = 30
  pos. correlated 23
  neg. correlated 7
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 0.3592 2.114e-16 3.18e-12
FGD4 0.3564 3.738e-16 3.18e-12
TEPP 0.332 4.259e-14 1.65e-10
ABCC10 0.3319 4.316e-14 1.65e-10
KIAA0922 -0.3311 4.985e-14 1.65e-10
FAM13C 0.3303 5.818e-14 1.65e-10
INPP5K 0.3223 2.503e-13 6.08e-10
KBTBD11 0.3154 8.867e-13 1.88e-09
FAM55B 0.3142 1.028e-12 1.94e-09
SATB1 0.308 3.703e-12 6.3e-09
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 346
  N1 79
     
  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
FEN1 6536 4.534e-13 5.77e-09 0.7609
KIAA0922 6590 6.781e-13 5.77e-09 0.7589
EIF4A3 7480 3.38e-10 1.92e-06 0.7263
GUCA1B 7583 6.586e-10 2.8e-06 0.7226
HN1 7768 2.125e-09 7.23e-06 0.7158
TMEM116 7800 2.594e-09 7.35e-06 0.7146
DHX9 7941 6.162e-09 1.5e-05 0.7095
LOC93622 8005 9.067e-09 1.93e-05 0.7071
SIN3B 8047 1.166e-08 2.2e-05 0.7056
CORO7 8089 1.496e-08 2.54e-05 0.7041
Clinical variable #5: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 395
  YES 59
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
KIAA0922 6873 3.698e-07 0.00629 0.7051
LOC595101 7125 1.466e-06 0.0125 0.6943
RPS6KL1 7244 2.742e-06 0.0155 0.6892
PLK1 7443 7.551e-06 0.0321 0.6806
SAMD1 7533 1.177e-05 0.04 0.6768
SFXN5 7625 1.836e-05 0.052 0.6728
SNX5 7694 2.548e-05 0.0544 0.6699
DLGAP5 7695 2.56e-05 0.0544 0.6698
ZNF579 7750 3.311e-05 0.0573 0.6675
CHAC1 7814 4.448e-05 0.0573 0.6647
Clinical variable #6: 'HISTOLOGICAL_TYPE'

No gene related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  PROSTATE ADENOCARCINOMA ACINAR TYPE 483
  PROSTATE ADENOCARCINOMA, OTHER SUBTYPE 15
     
  Significant markers N = 0
Clinical variable #7: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 316
  R1 147
  R2 5
  RX 15
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
RIC3 1.783e-07 0.00303
KIAA1751 1.149e-06 0.00388
FRYL 1.218e-06 0.00388
ARGLU1 1.263e-06 0.00388
MAST2 1.697e-06 0.00388
HNF1B 1.804e-06 0.00388
CYP7B1 2.003e-06 0.00388
PGS1 2.011e-06 0.00388
CLDN9 2.053e-06 0.00388
LOC93622 2.5e-06 0.00406
Clinical variable #8: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

Table S13.  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 S14.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
KIAA0922 -0.3783 2.696e-15 4.59e-11
FEN1 -0.3696 1.267e-14 1.08e-10
EIF4A3 -0.335 3.924e-12 2.22e-08
GUCA1B -0.3231 2.428e-11 1.03e-07
CORO7 -0.3096 1.724e-10 5.87e-07
HN1 -0.3076 2.296e-10 6.51e-07
LOC93622 -0.3051 3.228e-10 7.39e-07
TMEM116 -0.3046 3.478e-10 7.39e-07
DHX9 -0.3031 4.299e-10 8.12e-07
ZNRF2 -0.3012 5.572e-10 8.73e-07
Clinical variable #9: 'GLEASON_SCORE'

30 genes related to 'GLEASON_SCORE'.

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

GLEASON_SCORE Mean (SD) 7.61 (1)
  Score N
  6 45
  7 248
  8 64
  9 137
  10 4
     
  Significant markers N = 30
  pos. correlated 11
  neg. correlated 19
List of top 10 genes differentially expressed by 'GLEASON_SCORE'

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

SpearmanCorr corrP Q
FAM13C 0.4328 3.799e-24 6.46e-20
KIAA0922 -0.4229 4.996e-23 4.25e-19
PLK1 -0.4121 7.804e-22 4.42e-18
OR51A7 -0.3948 5.056e-20 2.15e-16
FGD4 0.3884 2.211e-19 7.52e-16
FEN1 -0.3876 2.684e-19 7.61e-16
PTPRN2 0.3842 5.826e-19 1.42e-15
CYP7B1 0.3831 7.356e-19 1.56e-15
CTPS -0.3793 1.721e-18 3.25e-15
EIF2C1 0.3786 2.023e-18 3.44e-15
Clinical variable #10: 'PSA_VALUE'

30 genes related to 'PSA_VALUE'.

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

PSA_VALUE Mean (SD) 1.74 (16)
  Significant markers N = 30
  pos. correlated 10
  neg. correlated 20
List of top 10 genes differentially expressed by 'PSA_VALUE'

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

SpearmanCorr corrP Q
OR2A7 -0.2354 5.741e-07 0.00976
COMMD4 0.2224 2.404e-06 0.0116
LOC100270746 0.2219 2.523e-06 0.0116
OVOL1 -0.2202 3.046e-06 0.0116
BAIAP2 0.2187 3.565e-06 0.0116
SNX5 -0.2162 4.62e-06 0.0116
NUP62 -0.2136 6.035e-06 0.0116
CST7 -0.2128 6.551e-06 0.0116
CDC23 -0.2122 7.463e-06 0.0116
STAG1 -0.2117 7.466e-06 0.0116
Clinical variable #11: 'RACE'

No gene related to 'RACE'.

Table S19.  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 = 498

  • Number of genes = 17007

  • Number of clinical features = 11

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • 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, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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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