Correlation between gene methylation status and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C18C9V8P
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/C18C9V8P
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 522 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 'NEOPLASM_DISEASESTAGE'.

    • 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'.

    • C19ORF66__1 ,  SLC47A2 ,  DSG1 ,  EFEMP1 ,  HCST ,  ...

  • 30 genes correlated to 'GENDER'.

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

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • ARHGAP23 ,  CALML3 ,  HAUS8 ,  MYO9B__1 ,  C15ORF56 ,  ...

  • 30 genes correlated to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

    • RUFY3 ,  FAM126B ,  NDUFB3 ,  HSPB1 ,  SNX22 ,  ...

  • 30 genes correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • ZMYND8__1 ,  SCN9A ,  THAP2__1 ,  ZFC3H1__1 ,  LOC401093__1 ,  ...

  • 30 genes correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • HSPB3 ,  SLC13A4 ,  DSG1 ,  FAM185A ,  C9ORF139 ,  ...

  • 30 genes correlated to 'RACE'.

    • SCAMP5 ,  GPBAR1 ,  ATAD3A ,  WBSCR27 ,  TP53 ,  ...

  • 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
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=2 lower stage N=28
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
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RADIATIONS_RADIATION_REGIMENINDICATION Wilcoxon test N=30 yes N=30 no N=0
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=30 higher number_pack_years_smoked N=5 lower number_pack_years_smoked N=25
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=30 higher year_of_tobacco_smoking_onset N=4 lower year_of_tobacco_smoking_onset N=26
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=18.4)
  censored N = 318
  death N = 203
     
  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) 60.89 (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 0.3203 6.745e-14 1.36e-09
KIAA1143 0.2714 3.024e-10 2.04e-06
KIF15 0.2714 3.024e-10 2.04e-06
SLC15A3 0.2359 5.042e-08 0.000255
FIGNL1 0.2218 3.134e-07 0.00127
NAPEPLD 0.2135 8.738e-07 0.00253
PRR18 0.2135 8.767e-07 0.00253
ZNF274 0.2089 1.507e-06 0.00361
IFT140__1 0.2084 1.609e-06 0.00361
TRIM45 0.2064 2.03e-06 0.0041
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

30 genes related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 27
  STAGE II 78
  STAGE III 77
  STAGE IVA 257
  STAGE IVB 12
  STAGE IVC 1
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

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

kruskal_wallis_P Q
PTK2 1.013e-05 0.112
LOC284688 1.107e-05 0.112
CCL11 2.176e-05 0.147
PARL 3.94e-05 0.194
NDUFB9__1 4.791e-05 0.194
IDH3B 6.81e-05 0.197
C8ORF44 7.618e-05 0.197
MYT1 0.0001053 0.197
C1ORF104 0.0001284 0.197
RUSC1 0.0001284 0.197
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 (1.1)
  N
  T0 1
  T1 49
  T2 136
  T3 100
  T4 174
     
  Significant markers N = 30
  pos. correlated 2
  neg. correlated 28
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 -0.2678 5.391e-09 0.000109
ABL2 -0.2585 1.854e-08 0.000187
SMURF1 -0.2538 3.386e-08 0.000228
HMOX2__1 -0.2504 5.236e-08 0.000259
MAP4K4 -0.2488 6.408e-08 0.000259
THEM5 -0.2358 3.115e-07 0.00105
CORO1C -0.2269 8.768e-07 0.0022
CCL4 -0.2258 9.957e-07 0.0022
SDCCAG8 -0.2237 1.251e-06 0.0022
GSTP1 -0.2237 1.257e-06 0.0022
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) 1.01 (0.95)
  N
  N0 179
  N1 66
  N2 169
  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
C19ORF66__1 0.2626 4.405e-08 0.00061
SLC47A2 0.2574 8.182e-08 0.00061
DSG1 0.2566 9.054e-08 0.00061
EFEMP1 0.2371 8.405e-07 0.00425
HCST 0.2346 1.136e-06 0.00459
AVPI1 0.2314 1.55e-06 0.00522
MMP21 0.2243 3.262e-06 0.00758
C9ORF139 0.2205 4.82e-06 0.00758
FUT7 0.2205 4.82e-06 0.00758
NFKBIB__1 0.2201 5.003e-06 0.00758
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 184
  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 141
  MALE 381
     
  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 8265 5.567e-34 1.13e-29 0.8461
FRG1B 12627 1.382e-20 1.4e-16 0.765
MRPL32 13680 7.082e-18 3.58e-14 0.7454
PSMA2__1 13680 7.082e-18 3.58e-14 0.7454
NCRNA00116 16201 3.261e-12 1.32e-08 0.6984
NDUFA13 16494 1.544e-11 3.37e-08 0.6922
TSSK6 16494 1.544e-11 3.37e-08 0.6922
CCDC121__1 16543 1.557e-11 3.37e-08 0.6921
GPN1__1 16543 1.557e-11 3.37e-08 0.6921
NPDC1 16558 1.665e-11 3.37e-08 0.6918
Clinical variable #8: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  HEAD AND NECK SQUAMOUS CELL CARCINOMA 511
  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 S14.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
ARHGAP23 1.669e-05 0.0302
CALML3 1.682e-05 0.0302
HAUS8 2.112e-05 0.0302
MYO9B__1 2.112e-05 0.0302
C15ORF56 2.117e-05 0.0302
PAK6__1 2.117e-05 0.0302
RALGDS 2.142e-05 0.0302
KIRREL2 2.149e-05 0.0302
RPP21 2.173e-05 0.0302
ARSG 2.239e-05 0.0302
Clinical variable #9: 'RADIATIONS_RADIATION_REGIMENINDICATION'

30 genes related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 83
  YES 439
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

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

W(pos if higher in 'YES') wilcoxontestP Q AUC
RUFY3 8321 4.041e-15 5.85e-11 0.7716
FAM126B 8502 1.258e-14 5.85e-11 0.7667
NDUFB3 8502 1.258e-14 5.85e-11 0.7667
HSPB1 8560 1.802e-14 5.85e-11 0.7651
SNX22 8565 1.859e-14 5.85e-11 0.7649
FLJ10213 8579 2.027e-14 5.85e-11 0.7646
PPP4R2 8579 2.027e-14 5.85e-11 0.7646
NFS1 8726 4.986e-14 9.43e-11 0.7605
ROMO1 8726 4.986e-14 9.43e-11 0.7605
SUCLG1 8743 5.529e-14 9.43e-11 0.7601
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) 45.12 (35)
  Significant markers N = 30
  pos. correlated 5
  neg. correlated 25
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 -0.2953 2.766e-07 0.00552
SCN9A -0.288 5.552e-07 0.00552
THAP2__1 -0.2807 1.092e-06 0.00552
ZFC3H1__1 -0.2807 1.092e-06 0.00552
LOC401093__1 -0.2696 2.959e-06 0.0091
MBNL1__2 -0.2696 2.959e-06 0.0091
DYNC1I2 -0.2677 3.478e-06 0.0091
KLF6 0.2661 4.018e-06 0.0091
C12ORF50 -0.266 4.051e-06 0.0091
SUCNR1 -0.2625 5.461e-06 0.00945
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) 1967.15 (13)
  Significant markers N = 30
  pos. correlated 4
  neg. correlated 26
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 -0.3984 4.721e-12 9.54e-08
RRP15 -0.2983 3.86e-07 0.00351
ARFIP1 -0.2919 6.952e-07 0.00351
TIGD4 -0.2919 6.952e-07 0.00351
LSM7 -0.2819 1.714e-06 0.00521
SPPL2B__1 -0.2819 1.714e-06 0.00521
INSM2 -0.2813 1.804e-06 0.00521
RPS27 -0.2737 3.481e-06 0.00714
ZNF193 -0.271 4.362e-06 0.00714
RPS2 -0.2696 4.918e-06 0.00714
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) 2.18 (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 0.282 7.084e-09 0.000143
SLC13A4 0.2677 4.149e-08 0.000368
DSG1 0.2631 7.169e-08 0.000368
FAM185A 0.2597 1.07e-07 0.000368
C9ORF139 0.2583 1.259e-07 0.000368
FUT7 0.2583 1.259e-07 0.000368
P2RY6 0.2582 1.274e-07 0.000368
HCST 0.2509 2.931e-07 0.000729
NBLA00301__1 0.25 3.247e-07 0.000729
C19ORF66__1 0.2488 3.687e-07 0.000745
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 45
  WHITE 447
     
  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 9.272e-13 1.87e-08
GPBAR1 1.329e-10 1.34e-06
ATAD3A 4.803e-08 0.000324
WBSCR27 3.505e-07 0.00177
TP53 7.089e-07 0.00239
WRAP53 7.089e-07 0.00239
MFN2 1.099e-06 0.00296
EIF3D 1.173e-06 0.00296
LOC100133161 1.957e-06 0.0044
EIF2AK4 3.116e-06 0.0063
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 25
  NOT HISPANIC OR LATINO 460
     
  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 = 522

  • Number of genes = 20212

  • Number of clinical features = 14

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • 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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