Correlation between gene methylation status and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1Z037B8
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/C1Z037B8
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 20212 genes and 14 clinical features across 528 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'.

    • KLF14 ,  KIAA1143 ,  KIF15 ,  SLC15A3 ,  FIGNL1 ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • PTK2 ,  LOC284688 ,  CCL11 ,  PARL ,  NDUFB9__1 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • IRX2__1 ,  ABL2 ,  SMURF1 ,  HMOX2__1 ,  MAP4K4 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • SLC47A2 ,  C19ORF66__1 ,  DSG1 ,  HCST ,  AVPI1 ,  ...

  • 30 genes correlated to 'GENDER'.

    • KIF4B ,  FRG1B ,  MRPL32 ,  PSMA2__1 ,  NCRNA00116 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • IGSF9 ,  SDHD ,  TIMM8B ,  ALKBH4 ,  LRWD1 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • CALML3 ,  ARHGAP23 ,  KIRREL2 ,  C15ORF56 ,  PAK6__1 ,  ...

  • 30 genes correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • ZMYND8__1 ,  SCN9A ,  THAP2__1 ,  ZFC3H1__1 ,  CAND1 ,  ...

  • 30 genes correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • KLF14 ,  RRP15 ,  ARFIP1 ,  TIGD4 ,  LSM7 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • HSPB3 ,  SLC13A4 ,  C9ORF139 ,  FUT7 ,  NBLA00301__1 ,  ...

  • 30 genes correlated to 'RACE'.

    • SCAMP5 ,  GPBAR1 ,  WBSCR27 ,  TP53 ,  WRAP53 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'PATHOLOGY_M_STAGE', 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=26 younger N=4
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=0 lower stage N=30
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=30 lower stage 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=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=30 higher number_pack_years_smoked N=4 lower number_pack_years_smoked N=26
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=30 higher year_of_tobacco_smoking_onset N=3 lower year_of_tobacco_smoking_onset N=27
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=30 lower number_of_lymph_nodes N=0
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) 0.1-211 (median=21.1)
  censored N = 305
  death N = 222
     
  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) 60.91 (12)
  Significant markers N = 30
  pos. correlated 26
  neg. correlated 4
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
KLF14 0.312 2.3e-13 4.65e-09
KIAA1143 0.2661 5.448e-10 3.67e-06
KIF15 0.2661 5.448e-10 3.67e-06
SLC15A3 0.2284 1.145e-07 0.000494
FIGNL1 0.2279 1.221e-07 0.000494
IFT140__1 0.2125 8.503e-07 0.00286
TRIM45 0.2097 1.194e-06 0.00306
PRR18 0.2089 1.312e-06 0.00306
NAPEPLD 0.2086 1.361e-06 0.00306
GBA -0.2019 2.983e-06 0.00473
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 27
  STAGE II 77
  STAGE III 82
  STAGE IVA 258
  STAGE IVB 12
  STAGE IVC 1
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
PTK2 1.139e-05 0.121
LOC284688 1.195e-05 0.121
CCL11 3.625e-05 0.18
PARL 5.328e-05 0.18
NDUFB9__1 5.462e-05 0.18
UTP3 5.637e-05 0.18
C8ORF44 6.247e-05 0.18
C1ORF104 9.386e-05 0.199
RUSC1 9.386e-05 0.199
CCDC129 0.000101 0.199
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.86 (1)
  N
  T0 1
  T1 49
  T2 140
  T3 101
  T4 175
     
  Significant markers N = 30
  pos. correlated 0
  neg. correlated 30
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
IRX2__1 -0.2603 1.178e-08 0.000205
ABL2 -0.2562 2.029e-08 0.000205
SMURF1 -0.2513 3.835e-08 0.000258
HMOX2__1 -0.2474 6.257e-08 0.000316
MAP4K4 -0.2436 1.008e-07 0.000408
THEM5 -0.2361 2.527e-07 0.000851
CORO1C -0.2311 4.575e-07 0.00132
CCL4 -0.2254 8.876e-07 0.00213
SDCCAG8 -0.2245 9.775e-07 0.00213
OR1J2 -0.2234 1.104e-06 0.00213
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 1.02 (0.95)
  N
  N0 180
  N1 68
  N2 172
  N3 8
     
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
SLC47A2 0.2605 4.574e-08 0.000631
C19ORF66__1 0.2558 8.009e-08 0.000631
DSG1 0.2545 9.368e-08 0.000631
HCST 0.2355 8.557e-07 0.00432
AVPI1 0.2314 1.307e-06 0.00528
EFEMP1 0.2265 2.193e-06 0.00613
C9ORF139 0.2256 2.426e-06 0.00613
FUT7 0.2256 2.426e-06 0.00613
MMP21 0.2233 3.089e-06 0.00655
RAB1A 0.2228 3.241e-06 0.00655
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 190
  class1 1
     
  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 142
  MALE 386
     
  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
KIF4B 8775 4.242e-33 8.57e-29 0.8399
FRG1B 12720 3.473e-21 3.51e-17 0.7679
MRPL32 13946 4.771e-18 2.41e-14 0.7456
PSMA2__1 13946 4.771e-18 2.41e-14 0.7456
NCRNA00116 16299 9e-13 3.64e-09 0.7026
NPDC1 16828 1.013e-11 3.41e-08 0.693
NDUFA13 16936 2.02e-11 5.1e-08 0.6902
TSSK6 16936 2.02e-11 5.1e-08 0.6902
CCDC121__1 17069 2.938e-11 5.94e-08 0.6886
GPN1__1 17069 2.938e-11 5.94e-08 0.6886
Clinical variable #8: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 152
  YES 285
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
IGSF9 14651 2.496e-08 0.000504 0.6618
SDHD 27495 3.485e-06 0.0235 0.6347
TIMM8B 27495 3.485e-06 0.0235 0.6347
ALKBH4 16197 1.398e-05 0.051 0.6261
LRWD1 16197 1.398e-05 0.051 0.6261
NCAPH 16259 1.748e-05 0.051 0.6247
GTPBP3 16262 1.767e-05 0.051 0.6246
OTUD7A 16398 2.861e-05 0.0723 0.6215
APOBEC3C 16495 4.006e-05 0.0815 0.6192
TMEM42 16528 4.487e-05 0.0815 0.6185
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  HEAD AND NECK SQUAMOUS CELL CARCINOMA 517
  HEAD AND NECK SQUAMOUS CELL CARCINOMA SPINDLE CELL VARIANT 1
  HEAD AND NECK SQUAMOUS CELL CARCINOMA BASALOID TYPE 10
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
CALML3 1.605e-05 0.0313
ARHGAP23 1.637e-05 0.0313
KIRREL2 2.064e-05 0.0313
C15ORF56 2.091e-05 0.0313
PAK6__1 2.091e-05 0.0313
ARSG 2.111e-05 0.0313
RALGDS 2.133e-05 0.0313
HAUS8 2.163e-05 0.0313
MYO9B__1 2.163e-05 0.0313
RPP21 2.202e-05 0.0313
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

30 genes related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 45.75 (35)
  Significant markers N = 30
  pos. correlated 4
  neg. correlated 26
List of top 10 genes differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

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

SpearmanCorr corrP Q
ZMYND8__1 -0.3002 1.272e-07 0.00257
SCN9A -0.2835 6.506e-07 0.00622
THAP2__1 -0.2767 1.23e-06 0.00622
ZFC3H1__1 -0.2767 1.23e-06 0.00622
CAND1 -0.2691 2.442e-06 0.00987
ARMC7 -0.2636 3.956e-06 0.0112
KLF6 0.2619 4.582e-06 0.0112
LIN28B -0.2625 4.882e-06 0.0112
LOC100287227__1 -0.2597 5.565e-06 0.0112
TIPARP__1 -0.2597 5.565e-06 0.0112
Clinical variable #11: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

30 genes related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1967.31 (13)
  Significant markers N = 30
  pos. correlated 3
  neg. correlated 27
List of top 10 genes differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

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

SpearmanCorr corrP Q
KLF14 -0.3856 1.97e-11 3.98e-07
RRP15 -0.2811 1.61e-06 0.00822
ARFIP1 -0.2795 1.866e-06 0.00822
TIGD4 -0.2795 1.866e-06 0.00822
LSM7 -0.2764 2.44e-06 0.00822
SPPL2B__1 -0.2764 2.44e-06 0.00822
INSM2 -0.2742 2.962e-06 0.00855
RPS2 -0.27 4.248e-06 0.00859
SNHG9 -0.27 4.248e-06 0.00859
SNORA78 -0.27 4.248e-06 0.00859
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.19 (4.3)
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S22.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSPB3 0.2846 3.912e-09 7.91e-05
SLC13A4 0.267 3.592e-08 0.000286
C9ORF139 0.2628 5.929e-08 0.000286
FUT7 0.2628 5.929e-08 0.000286
NBLA00301__1 0.261 7.387e-08 0.000286
DSG1 0.2598 8.498e-08 0.000286
FAM185A 0.2557 1.373e-07 0.000397
P2RY6 0.2516 2.192e-07 0.000471
NRGN 0.2514 2.252e-07 0.000471
HCST 0.2511 2.331e-07 0.000471
Clinical variable #13: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 2
  ASIAN 11
  BLACK OR AFRICAN AMERICAN 48
  WHITE 452
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S24.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
SCAMP5 3.306e-13 6.68e-09
GPBAR1 3.523e-10 3.56e-06
WBSCR27 1.104e-07 0.000496
TP53 1.227e-07 0.000496
WRAP53 1.227e-07 0.000496
ATAD3A 2.517e-07 0.000848
LOC100133161 4.142e-07 0.00119
EIF3D 4.696e-07 0.00119
CEP290 1.23e-06 0.00249
TMTC3 1.23e-06 0.00249
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S25.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 26
  NOT HISPANIC OR LATINO 465
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 528

  • Number of genes = 20212

  • 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)
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