Correlation between gene methylation status and clinical features
Liver Hepatocellular Carcinoma
14 July 2016  |  awg_lihc__2016_07_14
Maintainer Information
Citation Information
doi:10.7908/C1ST7PCB
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/C1ST7PCB
Overview
Introduction

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

Summary

Testing the association between 16488 genes and 12 clinical features across 377 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • LOC284441 ,  COPB1 ,  LMBRD2 ,  LUC7L2 ,  TOP2B ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • CDCA7 ,  CCNI2 ,  NETO2 ,  SLC7A5P2 ,  BMP8B ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • RPS10 ,  NEK9 ,  LOC647979 ,  YWHAG ,  SLC39A13 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • LOC647979 ,  POLR2D ,  CCDC159 ,  LUC7L2 ,  PMS2L5 ,  ...

  • 30 genes correlated to 'GENDER'.

    • UTP14C ,  FAM35A ,  C17ORF73 ,  CUX2 ,  FAM83A ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • C7ORF53 ,  FASN ,  GALNT10 ,  ENTPD6 ,  RUVBL1 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • CEP97 ,  MYNN ,  OXSR1 ,  DCBLD2 ,  C10ORF68 ,  ...

  • 30 genes correlated to 'RACE'.

    • NUP88 ,  SNX16 ,  MMAA ,  FAM63B ,  IL6 ,  ...

  • 30 genes correlated to 'ETHNICITY'.

    • CRIPAK ,  C1QC ,  ZCWPW1 ,  CYP27A1 ,  HIST1H4C ,  ...

  • No genes correlated to 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', and 'RADIATION_THERAPY'.

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=30   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=28 younger N=2
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=6 lower stage N=24
PATHOLOGY_N_STAGE Wilcoxon test   N=0        
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test N=30 not hispanic or latino N=30 hispanic or latino N=0
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes 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) 0-120.8 (median=19.8)
  censored N = 245
  death N = 131
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
LOC284441 3.61e-09 5.9e-05 0.564
COPB1 1.34e-07 0.0011 0.382
LMBRD2 2.68e-07 0.0012 0.41
LUC7L2 3e-07 0.0012 0.416
TOP2B 4.64e-07 0.0015 0.377
RICTOR 7.6e-07 0.0018 0.385
IMPG2 7.76e-07 0.0018 0.626
C10ORF68 9.4e-07 0.0019 0.628
NIPBL 1.04e-06 0.0019 0.387
PLSCR4 1.38e-06 0.0023 0.374
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

Table S3.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 59.27 (13)
  Significant markers N = 30
  pos. correlated 28
  neg. correlated 2
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
CDCA7 0.388 7.496e-15 1.24e-10
CCNI2 0.3766 5.131e-14 3.03e-10
NETO2 0.3762 5.522e-14 3.03e-10
SLC7A5P2 0.3483 4.429e-12 1.76e-08
BMP8B 0.3471 5.342e-12 1.76e-08
FBLL1 0.3419 1.141e-11 3.14e-08
TRIM40 -0.3271 9.536e-11 2.02e-07
PTK7 0.3268 9.82e-11 2.02e-07
NAT14 0.3252 1.24e-10 2.27e-07
DAB1 0.3226 1.766e-10 2.75e-07
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE Labels N
  STAGE I 175
  STAGE II 87
  STAGE III 3
  STAGE IIIA 65
  STAGE IIIB 9
  STAGE IIIC 9
  STAGE IV 2
  STAGE IVA 1
  STAGE IVB 2
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
RPS10 2.593e-06 0.0276
NEK9 3.35e-06 0.0276
LOC647979 1.358e-05 0.0746
YWHAG 2.959e-05 0.0787
SLC39A13 3.153e-05 0.0787
LUC7L2 3.461e-05 0.0787
PMS2L5 3.483e-05 0.0787
KIAA1279 4.367e-05 0.0787
BAZ2B 4.654e-05 0.0787
SEPT10 4.771e-05 0.0787
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 1.79 (0.9)
  N
  T1 185
  T2 95
  T3 81
  T4 13
     
  Significant markers N = 30
  pos. correlated 6
  neg. correlated 24
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
LOC647979 -0.2984 4.14e-09 6.66e-05
POLR2D -0.2926 8.079e-09 6.66e-05
CCDC159 0.2866 1.671e-08 7.98e-05
LUC7L2 -0.2851 2.185e-08 7.98e-05
PMS2L5 -0.2795 3.872e-08 7.98e-05
LASS6 -0.2785 4.352e-08 7.98e-05
YWHAG -0.2782 4.464e-08 7.98e-05
MED13 -0.2823 4.677e-08 7.98e-05
UBQLN1 -0.2771 5.09e-08 7.98e-05
OSBPL1A -0.2815 5.109e-08 7.98e-05
Clinical variable #5: 'PATHOLOGY_N_STAGE'

No gene related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Labels N
  N0 257
  N1 4
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 272
  class1 4
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

30 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 122
  MALE 255
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S12.  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
UTP14C 29983 4.097e-48 6.75e-44 0.9638
FAM35A 5804 6.877e-23 5.67e-19 0.8134
C17ORF73 7693 1.998e-15 1.1e-11 0.7527
CUX2 7823 5.713e-15 2.35e-11 0.7485
FAM83A 9050 5.009e-11 1.5e-07 0.7091
KIF4B 9063 5.471e-11 1.5e-07 0.7087
ALDH3A1 9205 1.417e-10 3.34e-07 0.7041
ZNF16 9489 8.944e-10 1.84e-06 0.695
ZNF839 9630 2.167e-09 3.97e-06 0.6905
HAS3 21272 7.712e-09 1.27e-05 0.6838
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 345
  YES 9
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  FIBROLAMELLAR CARCINOMA 3
  HEPATOCELLULAR CARCINOMA 367
  HEPATOCHOLANGIOCARCINOMA (MIXED) 7
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
C7ORF53 2.952e-05 0.186
FASN 3.295e-05 0.186
GALNT10 5.416e-05 0.186
ENTPD6 7.565e-05 0.186
RUVBL1 8.968e-05 0.186
C21ORF7 9.721e-05 0.186
IQCK 0.0001287 0.186
PKM2 0.000156 0.186
ANKRD55 0.0001643 0.186
SPRED2 0.0001754 0.186
Clinical variable #10: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 330
  R1 17
  R2 1
  RX 22
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

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

kruskal_wallis_P Q
CEP97 1.665e-07 0.00275
MYNN 3.781e-07 0.00312
OXSR1 8.517e-07 0.00468
DCBLD2 1.601e-06 0.0066
C10ORF68 3.387e-06 0.00913
METAP2 3.421e-06 0.00913
C2ORF69 3.912e-06 0.00913
SCOC 5.294e-06 0.00913
PLSCR4 5.359e-06 0.00913
TMPPE 6.008e-06 0.00913
Clinical variable #11: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 2
  ASIAN 161
  BLACK OR AFRICAN AMERICAN 17
  WHITE 187
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

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

kruskal_wallis_P Q
NUP88 6.038e-36 9.96e-32
SNX16 1.414e-30 1.17e-26
MMAA 3.429e-25 1.88e-21
FAM63B 2.747e-24 1.07e-20
IL6 3.249e-24 1.07e-20
C16ORF87 1.655e-22 4.55e-19
BBS12 2.378e-22 5.6e-19
NFKB1 4.443e-22 9.16e-19
ATMIN 9.199e-22 1.69e-18
SMAD1 1.688e-21 2.72e-18
Clinical variable #12: 'ETHNICITY'

30 genes related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 18
  NOT HISPANIC OR LATINO 340
     
  Significant markers N = 30
  Higher in NOT HISPANIC OR LATINO 30
  Higher in HISPANIC OR LATINO 0
List of top 10 genes differentially expressed by 'ETHNICITY'

Methods & Data
Input

  • Expresson data file = LIHC.meth.by_min_clin_corr.data.txt

  • Clinical data file = LIHC.merged_data.txt

  • Number of patients = 377

  • Number of genes = 16488

  • Number of clinical features = 12

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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