Correlation between gene methylation status and clinical features
Colorectal Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1TB1635
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/C1TB1635
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 19838 genes and 14 clinical features across 390 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 12 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • GDNF ,  PENK ,  KLF14 ,  FOXC2 ,  IDO2 ,  ...

  • 30 genes correlated to 'TUMOR_TISSUE_SITE'.

    • PAPLN ,  SMPD1 ,  FAM13C ,  FLJ13197__1 ,  KLF3__1 ,  ...

  • 27 genes correlated to 'PATHOLOGIC_STAGE'.

    • UBE2L6 ,  CASP1__2 ,  SP140L ,  APOL1 ,  C8ORF80 ,  ...

  • 19 genes correlated to 'PATHOLOGY_T_STAGE'.

    • PHYHIP ,  SYN2 ,  TIMP4 ,  EBF1 ,  COPS4 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • CASP1__2 ,  UBE2L6 ,  APOL1 ,  SP140L ,  IL12RB1 ,  ...

  • 30 genes correlated to 'PATHOLOGY_M_STAGE'.

    • UBE2L6 ,  PSORS1C1__2 ,  PSORS1C2__1 ,  PLAT ,  EBF1 ,  ...

  • 30 genes correlated to 'GENDER'.

    • GPX1 ,  KIF4B ,  MIR220B ,  TUBB4 ,  PAFAH1B2 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • KIAA1688 ,  MGC70857 ,  BBS10 ,  FAM60A ,  FLJ13224 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • PAPLN ,  SMPD1 ,  C20ORF43__1 ,  FAM13C ,  CCDC85A ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • BLOC1S3__1 ,  TRAPPC6A ,  WIPF3 ,  FAM55D ,  RIPK2 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • CASP1__2 ,  UBE2L6 ,  IL12RB1 ,  ACTA2__1 ,  FAS ,  ...

  • 30 genes correlated to 'RACE'.

    • GSTCD__1 ,  INTS12__1 ,  IL20 ,  F12 ,  DHRS7 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 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
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
TUMOR_TISSUE_SITE Wilcoxon test N=30 rectum N=30 colon N=0
PATHOLOGIC_STAGE Kruskal-Wallis test N=27        
PATHOLOGY_T_STAGE Spearman correlation test N=19 higher stage N=8 lower stage N=11
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=22 lower stage N=8
PATHOLOGY_M_STAGE Wilcoxon test N=30 class1 N=30 class0 N=0
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=23 lower number_of_lymph_nodes N=7
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon 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) 0.1-148 (median=20)
  censored N = 309
  death N = 80
     
  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) 64.44 (13)
  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
GDNF 0.2932 3.955e-09 7.85e-05
PENK 0.2815 1.681e-08 0.000167
KLF14 0.2777 2.653e-08 0.000175
FOXC2 0.2749 3.702e-08 0.000183
IDO2 0.2705 6.225e-08 0.000183
GPR1 0.2704 6.33e-08 0.000183
ELOVL2 0.2702 6.462e-08 0.000183
EBF4 0.2685 7.851e-08 0.000188
CORO6 0.2678 8.526e-08 0.000188
C1ORF94 0.2655 1.108e-07 2e-04
Clinical variable #3: 'TUMOR_TISSUE_SITE'

30 genes related to 'TUMOR_TISSUE_SITE'.

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

TUMOR_TISSUE_SITE Labels N
  COLON 292
  RECTUM 96
     
  Significant markers N = 30
  Higher in RECTUM 30
  Higher in COLON 0
List of top 10 genes differentially expressed by 'TUMOR_TISSUE_SITE'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'TUMOR_TISSUE_SITE'

W(pos if higher in 'RECTUM') wilcoxontestP Q AUC
PAPLN 3597 8.345e-28 1.66e-23 0.8717
SMPD1 3699 2.698e-27 2.68e-23 0.868
FAM13C 3784 7.111e-27 4.7e-23 0.865
FLJ13197__1 4348 3.614e-24 1.43e-20 0.8449
KLF3__1 4348 3.614e-24 1.43e-20 0.8449
PRKAR2A 4416 7.484e-24 2.47e-20 0.8425
TEF 4462 1.221e-23 3.46e-20 0.8408
METTL3 23324 1.829e-23 3.94e-20 0.8408
SLC44A1 4502 1.865e-23 3.94e-20 0.8394
MED27 4508 1.987e-23 3.94e-20 0.8392
Clinical variable #4: 'PATHOLOGIC_STAGE'

27 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 54
  STAGE IA 1
  STAGE II 20
  STAGE IIA 114
  STAGE IIB 7
  STAGE IIC 3
  STAGE III 11
  STAGE IIIA 15
  STAGE IIIB 61
  STAGE IIIC 35
  STAGE IV 29
  STAGE IVA 25
  STAGE IVB 2
     
  Significant markers N = 27
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
UBE2L6 3.315e-08 0.000658
CASP1__2 3.659e-06 0.0251
SP140L 3.793e-06 0.0251
APOL1 7.058e-06 0.035
C8ORF80 2.144e-05 0.0851
NLRC5 6.055e-05 0.148
CASP5 6.688e-05 0.148
IL12RB1 7.175e-05 0.148
ACTA2__1 7.7e-05 0.148
FAS 7.7e-05 0.148
Clinical variable #5: 'PATHOLOGY_T_STAGE'

19 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.93 (0.62)
  N
  T1 11
  T2 56
  T3 271
  T4 50
     
  Significant markers N = 19
  pos. correlated 8
  neg. correlated 11
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
PHYHIP -0.2447 1.069e-06 0.0212
SYN2 0.2217 1.041e-05 0.0688
TIMP4 0.2217 1.041e-05 0.0688
EBF1 -0.2047 4.85e-05 0.225
COPS4 0.2029 5.677e-05 0.225
TNS4 -0.1999 7.339e-05 0.243
SORBS1 -0.1936 0.0001245 0.252
PGRMC2 0.1931 0.0001316 0.252
EPHA2 -0.1927 0.0001333 0.252
C10ORF10 -0.1912 0.0001506 0.252
Clinical variable #6: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.63 (0.78)
  N
  N0 213
  N1 103
  N2 71
     
  Significant markers N = 30
  pos. correlated 22
  neg. correlated 8
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S11.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
CASP1__2 0.3278 3.803e-11 5.96e-07
UBE2L6 0.3246 6.009e-11 5.96e-07
APOL1 0.2885 7.422e-09 4.47e-05
SP140L 0.287 9.019e-09 4.47e-05
IL12RB1 0.281 1.874e-08 7.44e-05
CASP5 0.2761 3.377e-08 0.000107
ASPHD2 0.2751 3.765e-08 0.000107
ACTA2__1 0.2729 4.885e-08 0.000108
FAS 0.2729 4.885e-08 0.000108
UBA7 0.2692 7.482e-08 0.000148
Clinical variable #7: 'PATHOLOGY_M_STAGE'

30 genes related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 264
  class1 53
     
  Significant markers N = 30
  Higher in class1 30
  Higher in class0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
UBE2L6 9965 1.088e-06 0.0216 0.7122
PSORS1C1__2 4400 2.022e-05 0.084 0.6855
PSORS1C2__1 4400 2.022e-05 0.084 0.6855
PLAT 4404 2.082e-05 0.084 0.6852
EBF1 4433 2.574e-05 0.084 0.6832
SMAD4 9186 3.431e-05 0.084 0.6821
TFAP2C 4474 3.459e-05 0.084 0.6802
CASP1__2 9496 4.047e-05 0.084 0.6787
RGL2 4517 4.695e-05 0.084 0.6772
SP140L 9443 5.876e-05 0.084 0.6749
Clinical variable #8: 'GENDER'

30 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 178
  MALE 212
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S15.  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
GPX1 5894 1.276e-31 2.53e-27 0.8438
KIF4B 6193 2.953e-30 2.93e-26 0.8359
MIR220B 28876 1.796e-19 8.91e-16 0.7652
TUBB4 28876 1.796e-19 8.91e-16 0.7652
PAFAH1B2 11081 2.186e-12 8.67e-09 0.7064
ZNF839 12664 2.213e-08 7.32e-05 0.6644
FASTKD2 12877 6.575e-08 0.000163 0.6588
MDH1B 12877 6.575e-08 0.000163 0.6588
WBP11P1 24776 9.954e-08 0.000219 0.6566
UGDH 13038 1.463e-07 0.000265 0.6545
Clinical variable #9: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 286
  YES 15
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
KIAA1688 787 3.605e-05 0.159 0.8166
MGC70857 787 3.605e-05 0.159 0.8166
BBS10 796 4.06e-05 0.159 0.8145
FAM60A 828 6.159e-05 0.159 0.807
FLJ13224 828 6.159e-05 0.159 0.807
C14ORF109 862 9.495e-05 0.159 0.7991
HS1BP3 862 9.495e-05 0.159 0.7991
MOAP1 862 9.495e-05 0.159 0.7991
MLYCD 866 9.984e-05 0.159 0.7981
RAB3B 871 0.0001063 0.159 0.797
Clinical variable #10: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

Table S18.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  COLON ADENOCARCINOMA 251
  COLON MUCINOUS ADENOCARCINOMA 38
  RECTAL ADENOCARCINOMA 90
  RECTAL MUCINOUS ADENOCARCINOMA 6
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S19.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
PAPLN 2.044e-26 4.05e-22
SMPD1 4.783e-26 4.74e-22
C20ORF43__1 1.082e-25 7.15e-22
FAM13C 3.04e-25 1.51e-21
CCDC85A 4.721e-23 1.87e-19
FOXC1 1.001e-22 3.11e-19
FLJ13197__1 1.254e-22 3.11e-19
KLF3__1 1.254e-22 3.11e-19
TEF 1.712e-22 3.77e-19
CYP19A1 3.407e-22 6.56e-19
Clinical variable #11: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

Table S20.  Basic characteristics of clinical feature: 'RESIDUAL_TUMOR'

RESIDUAL_TUMOR Labels N
  R0 256
  R1 4
  R2 7
  RX 29
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Table S21.  Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
BLOC1S3__1 1.371e-05 0.129
TRAPPC6A 1.371e-05 0.129
WIPF3 2.455e-05 0.129
FAM55D 2.595e-05 0.129
RIPK2 4.035e-05 0.16
KCNK17 8.353e-05 0.194
IFNG 8.75e-05 0.194
ALX3 9.679e-05 0.194
TMEM231 0.0001093 0.194
RPS14 0.0001155 0.194
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.29 (4.8)
  Significant markers N = 30
  pos. correlated 23
  neg. correlated 7
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S23.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
CASP1__2 0.343 3.277e-11 6.5e-07
UBE2L6 0.3326 1.377e-10 1.37e-06
IL12RB1 0.3 8.535e-09 5.64e-05
ACTA2__1 0.2882 3.365e-08 0.000134
FAS 0.2882 3.365e-08 0.000134
APOL1 0.284 5.423e-08 0.000179
SP140L 0.2817 6.976e-08 0.000198
CASP5 0.2768 1.199e-07 0.000297
AMOTL2 -0.2738 1.663e-07 0.000367
KLF10 -0.2607 6.58e-07 0.00131
Clinical variable #13: 'RACE'

30 genes related to 'RACE'.

Table S24.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 12
  BLACK OR AFRICAN AMERICAN 62
  WHITE 282
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S25.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
GSTCD__1 7.114e-15 7.06e-11
INTS12__1 7.114e-15 7.06e-11
IL20 9.624e-14 5.08e-10
F12 1.024e-13 5.08e-10
DHRS7 1.803e-12 7.15e-09
ARL6 3.725e-11 9.1e-08
TRIM73 3.92e-11 9.1e-08
TRIM74 3.92e-11 9.1e-08
FLJ10213 4.587e-11 9.1e-08
PPP4R2 4.587e-11 9.1e-08
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S26.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 5
  NOT HISPANIC OR LATINO 335
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 390

  • Number of genes = 19838

  • Number of clinical features = 14

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, 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle