Correlation between gene methylation status and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C11834ZG
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/C11834ZG
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 20015 genes and 13 clinical features across 185 samples, statistically thresholded by Q value < 0.05, 10 clinical features related to at least one genes.

  • 3 genes correlated to 'AGE'.

    • LYNX1 ,  NRN1 ,  CAMK4

  • 1 gene correlated to 'PATHOLOGY.T.STAGE'.

    • TACC2

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

    • DYRK2 ,  DLEU2__3 ,  RRM2 ,  KCNJ2 ,  IRF2BP1 ,  ...

  • 6 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • CTNNA3__1 ,  LRRTM3 ,  AKR1B10 ,  CAPN3 ,  SPAG16 ,  ...

  • 5 genes correlated to 'GLEASON_SCORE_COMBINED'.

    • FAM13C ,  LIX1L ,  DLEU2__3 ,  OR51A7 ,  RRM2

  • 26 genes correlated to 'GLEASON_SCORE_PRIMARY'.

    • RRM2 ,  LOC374491 ,  PGLYRP4 ,  TRPA1 ,  C1ORF173 ,  ...

  • 10 genes correlated to 'GLEASON_SCORE'.

    • FAM13C ,  DLEU2__3 ,  SLC5A11 ,  OR51A7 ,  CCNA2 ,  ...

  • 10 genes correlated to 'PSA_RESULT_PREOP'.

    • FCRL2 ,  FCRL4 ,  FCRL3 ,  PGLYRP4 ,  C6 ,  ...

  • 624 genes correlated to 'DAYS_TO_PREOP_PSA'.

    • ZNF800 ,  DEAF1 ,  TMEM80 ,  TRIO ,  C1ORF25__1 ,  ...

  • 6 genes correlated to 'DAYS_TO_PSA'.

    • NKIRAS1__1 ,  RPL15__1 ,  NR1H2 ,  ELOF1 ,  HARS__1 ,  ...

  • No genes correlated to 'NUMBER.OF.LYMPH.NODES', 'GLEASON_SCORE_SECONDARY', and 'PSA_VALUE'.

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 Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
AGE Spearman correlation test N=3 older N=3 younger N=0
PATHOLOGY T STAGE Spearman correlation test N=1 higher stage N=1 lower stage N=0
PATHOLOGY N STAGE t test N=10 class1 N=0 class0 N=10
COMPLETENESS OF RESECTION ANOVA test N=6        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
GLEASON_SCORE_COMBINED Spearman correlation test N=5 higher score N=2 lower score N=3
GLEASON_SCORE_PRIMARY Spearman correlation test N=26 higher score N=7 lower score N=19
GLEASON_SCORE_SECONDARY Spearman correlation test   N=0        
GLEASON_SCORE Spearman correlation test N=10 higher score N=2 lower score N=8
PSA_RESULT_PREOP Spearman correlation test N=10 higher psa_result_preop N=2 lower psa_result_preop N=8
DAYS_TO_PREOP_PSA Spearman correlation test N=624 higher days_to_preop_psa N=235 lower days_to_preop_psa N=389
PSA_VALUE Spearman correlation test   N=0        
DAYS_TO_PSA Spearman correlation test N=6 higher days_to_psa N=6 lower days_to_psa N=0
Clinical variable #1: 'AGE'

3 genes related to 'AGE'.

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

AGE Mean (SD) 60.28 (7)
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

Table S2.  Get Full Table List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
LYNX1 0.3517 1.046e-06 0.0209
NRN1 0.3444 1.801e-06 0.036
CAMK4 0.3408 2.355e-06 0.0471

Figure S1.  Get High-res Image As an example, this figure shows the association of LYNX1 to 'AGE'. P value = 1.05e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #2: 'PATHOLOGY.T.STAGE'

One gene related to 'PATHOLOGY.T.STAGE'.

Table S3.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.59 (0.55)
  N
  2 80
  3 98
  4 5
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S4.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TACC2 0.3476 1.426e-06 0.0286

Figure S2.  Get High-res Image As an example, this figure shows the association of TACC2 to 'PATHOLOGY.T.STAGE'. P value = 1.43e-06 with Spearman correlation analysis.

Clinical variable #3: 'PATHOLOGY.N.STAGE'

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

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 145
  class1 17
     
  Significant markers N = 10
  Higher in class1 0
  Higher in class0 10
List of 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S6.  Get Full Table List of 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

T(pos if higher in 'class1') ttestP Q AUC
DYRK2 -7.16 3.55e-10 7.11e-06 0.7416
DLEU2__3 -6.8 2.203e-09 4.41e-05 0.8292
RRM2 -6.4 3.463e-08 0.000693 0.7826
KCNJ2 -5.7 6.257e-08 0.00125 0.714
IRF2BP1 -5.37 7.509e-07 0.015 0.7266
CCNE2 -5.36 1.102e-06 0.0221 0.7546
PDE3B -5.33 1.467e-06 0.0293 0.7249
IFT74 -4.95 2.012e-06 0.0403 0.703
ARID3A -5.65 2.235e-06 0.0447 0.7542
CCNA2 -5.27 2.379e-06 0.0476 0.7497

Figure S3.  Get High-res Image As an example, this figure shows the association of DYRK2 to 'PATHOLOGY.N.STAGE'. P value = 3.55e-10 with T-test analysis.

Clinical variable #4: 'COMPLETENESS.OF.RESECTION'

6 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S7.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 135
  R1 37
  RX 3
     
  Significant markers N = 6
List of 6 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S8.  Get Full Table List of 6 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
CTNNA3__1 1.728e-14 3.46e-10
LRRTM3 1.728e-14 3.46e-10
AKR1B10 3.168e-10 6.34e-06
CAPN3 1.19e-07 0.00238
SPAG16 1.243e-06 0.0249
PPP1R3B 1.377e-06 0.0276

Figure S4.  Get High-res Image As an example, this figure shows the association of CTNNA3__1 to 'COMPLETENESS.OF.RESECTION'. P value = 1.73e-14 with ANOVA analysis.

Clinical variable #5: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S9.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 0.19 (0.69)
  Significant markers N = 0
Clinical variable #6: 'GLEASON_SCORE_COMBINED'

5 genes related to 'GLEASON_SCORE_COMBINED'.

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

GLEASON_SCORE_COMBINED Mean (SD) 7.26 (0.77)
  Score N
  6 12
  7 135
  8 17
  9 19
  10 2
     
  Significant markers N = 5
  pos. correlated 2
  neg. correlated 3
List of 5 genes significantly correlated to 'GLEASON_SCORE_COMBINED' by Spearman correlation test

Table S11.  Get Full Table List of 5 genes significantly correlated to 'GLEASON_SCORE_COMBINED' by Spearman correlation test

SpearmanCorr corrP Q
FAM13C 0.4047 1.107e-08 0.000222
LIX1L 0.4006 1.598e-08 0.00032
DLEU2__3 -0.3562 6.463e-07 0.0129
OR51A7 -0.3479 1.217e-06 0.0244
RRM2 -0.3417 1.94e-06 0.0388

Figure S5.  Get High-res Image As an example, this figure shows the association of FAM13C to 'GLEASON_SCORE_COMBINED'. P value = 1.11e-08 with Spearman correlation analysis.

Clinical variable #7: 'GLEASON_SCORE_PRIMARY'

26 genes related to 'GLEASON_SCORE_PRIMARY'.

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

GLEASON_SCORE_PRIMARY Mean (SD) 3.48 (0.57)
  Score N
  2 1
  3 101
  4 77
  5 6
     
  Significant markers N = 26
  pos. correlated 7
  neg. correlated 19
List of top 10 genes significantly correlated to 'GLEASON_SCORE_PRIMARY' by Spearman correlation test

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

SpearmanCorr corrP Q
RRM2 -0.4201 2.628e-09 5.26e-05
LOC374491 -0.3805 9.178e-08 0.00184
PGLYRP4 -0.374 1.57e-07 0.00314
TRPA1 -0.3746 1.744e-07 0.00349
C1ORF173 -0.3716 1.907e-07 0.00382
CD38 0.3677 2.614e-07 0.00523
TEPP 0.3661 2.989e-07 0.00598
MEF2D 0.366 2.994e-07 0.00599
C21ORF15 -0.3653 3.172e-07 0.00635
MYO3A -0.361 4.466e-07 0.00894

Figure S6.  Get High-res Image As an example, this figure shows the association of RRM2 to 'GLEASON_SCORE_PRIMARY'. P value = 2.63e-09 with Spearman correlation analysis.

Clinical variable #8: 'GLEASON_SCORE_SECONDARY'

No gene related to 'GLEASON_SCORE_SECONDARY'.

Table S14.  Basic characteristics of clinical feature: 'GLEASON_SCORE_SECONDARY'

GLEASON_SCORE_SECONDARY Mean (SD) 3.79 (0.61)
  Score N
  3 58
  4 108
  5 19
     
  Significant markers N = 0
Clinical variable #9: 'GLEASON_SCORE'

10 genes related to 'GLEASON_SCORE'.

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

GLEASON_SCORE Mean (SD) 7.31 (0.81)
  Score N
  6 12
  7 130
  8 19
  9 22
  10 2
     
  Significant markers N = 10
  pos. correlated 2
  neg. correlated 8
List of 10 genes significantly correlated to 'GLEASON_SCORE' by Spearman correlation test

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

SpearmanCorr corrP Q
FAM13C 0.3951 2.608e-08 0.000522
DLEU2__3 -0.3684 2.471e-07 0.00495
SLC5A11 -0.3596 4.976e-07 0.00996
OR51A7 -0.3569 6.152e-07 0.0123
CCNA2 -0.3549 7.192e-07 0.0144
LIX1L 0.3534 8.064e-07 0.0161
LOC93622 -0.3404 2.131e-06 0.0426
CYP39A1__1 -0.3401 2.169e-06 0.0434
SLC25A27__1 -0.3401 2.169e-06 0.0434
OR7E37P -0.3389 2.379e-06 0.0476

Figure S7.  Get High-res Image As an example, this figure shows the association of FAM13C to 'GLEASON_SCORE'. P value = 2.61e-08 with Spearman correlation analysis.

Clinical variable #10: 'PSA_RESULT_PREOP'

10 genes related to 'PSA_RESULT_PREOP'.

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

PSA_RESULT_PREOP Mean (SD) 10.32 (10)
  Significant markers N = 10
  pos. correlated 2
  neg. correlated 8
List of 10 genes significantly correlated to 'PSA_RESULT_PREOP' by Spearman correlation test

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

SpearmanCorr corrP Q
FCRL2 -0.454 1.079e-10 2.16e-06
FCRL4 -0.3775 1.376e-07 0.00275
FCRL3 -0.3723 2.105e-07 0.00421
PGLYRP4 -0.3532 9.351e-07 0.0187
C6 -0.3512 1.087e-06 0.0218
ATP8B3 0.3481 1.375e-06 0.0275
MDGA2 -0.3468 1.517e-06 0.0303
RGPD1 -0.3444 1.809e-06 0.0362
RGPD2 -0.3444 1.809e-06 0.0362
SHB 0.3423 2.11e-06 0.0422

Figure S8.  Get High-res Image As an example, this figure shows the association of FCRL2 to 'PSA_RESULT_PREOP'. P value = 1.08e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'DAYS_TO_PREOP_PSA'

624 genes related to 'DAYS_TO_PREOP_PSA'.

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

DAYS_TO_PREOP_PSA Mean (SD) -1.53 (100)
  Significant markers N = 624
  pos. correlated 235
  neg. correlated 389
List of top 10 genes significantly correlated to 'DAYS_TO_PREOP_PSA' by Spearman correlation test

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

SpearmanCorr corrP Q
ZNF800 -0.5021 6.915e-13 1.38e-08
DEAF1 0.4917 2.405e-12 4.81e-08
TMEM80 0.4917 2.405e-12 4.81e-08
TRIO -0.4833 6.314e-12 1.26e-07
C1ORF25__1 -0.4775 1.219e-11 2.44e-07
C1ORF26__1 -0.4775 1.219e-11 2.44e-07
UBE3C -0.4749 1.635e-11 3.27e-07
GNAS 0.4729 2.04e-11 4.08e-07
GTF2F1 0.4726 2.102e-11 4.21e-07
FOXO3B -0.4705 2.663e-11 5.33e-07

Figure S9.  Get High-res Image As an example, this figure shows the association of ZNF800 to 'DAYS_TO_PREOP_PSA'. P value = 6.91e-13 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'PSA_VALUE'

No gene related to 'PSA_VALUE'.

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

PSA_VALUE Mean (SD) 1.46 (4.5)
  Significant markers N = 0
Clinical variable #13: 'DAYS_TO_PSA'

6 genes related to 'DAYS_TO_PSA'.

Table S22.  Basic characteristics of clinical feature: 'DAYS_TO_PSA'

DAYS_TO_PSA Mean (SD) 534.61 (500)
  Significant markers N = 6
  pos. correlated 6
  neg. correlated 0
List of 6 genes significantly correlated to 'DAYS_TO_PSA' by Spearman correlation test

Table S23.  Get Full Table List of 6 genes significantly correlated to 'DAYS_TO_PSA' by Spearman correlation test

SpearmanCorr corrP Q
NKIRAS1__1 0.3824 3.122e-07 0.00625
RPL15__1 0.3824 3.122e-07 0.00625
NR1H2 0.3803 3.685e-07 0.00737
ELOF1 0.3669 1.002e-06 0.02
HARS__1 0.3614 1.488e-06 0.0298
HARS2__1 0.3614 1.488e-06 0.0298

Figure S10.  Get High-res Image As an example, this figure shows the association of NKIRAS1__1 to 'DAYS_TO_PSA'. P value = 3.12e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

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 = 185

  • Number of genes = 20015

  • Number of clinical features = 13

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] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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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