Correlation between gene methylation status and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1ZG6QVR
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/C1ZG6QVR
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 20185 genes and 12 clinical features across 409 samples, statistically thresholded by Q value < 0.05, 10 clinical features related to at least one genes.

  • 3 genes correlated to 'AGE'.

    • KIAA1143 ,  KIF15 ,  FIGNL1

  • 44 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • ZMIZ2 ,  RIF1 ,  IDH3A ,  HDLBP ,  SEPT2 ,  ...

  • 2 genes correlated to 'PATHOLOGY.T.STAGE'.

    • LOC729121 ,  RGPD4

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

    • EFEMP1 ,  SLC47A2 ,  FAM185A

  • 102 genes correlated to 'PATHOLOGY.M.STAGE'.

    • DDX5 ,  LRRC41 ,  UQCRH ,  ABCB9 ,  OGFOD2__1 ,  ...

  • 46 genes correlated to 'GENDER'.

    • KIF4B ,  FRG1B ,  MRPL32 ,  PSMA2__1 ,  NLRP2 ,  ...

  • 85 genes correlated to 'HISTOLOGICAL.TYPE'.

    • ALG10 ,  CTSK ,  CLCA4 ,  KCNC1 ,  MTA2 ,  ...

  • 185 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • FLJ10213 ,  PPP4R2 ,  C1D ,  AMY2B__1 ,  RNPC3 ,  ...

  • 3 genes correlated to 'NUMBERPACKYEARSSMOKED'.

    • KLF6 ,  ELL ,  DBF4__1

  • 11 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

    • FAM185A ,  WNT1 ,  NBLA00301 ,  ARHGAP27 ,  P2RY6 ,  ...

  • No genes correlated to 'Time to Death', and 'YEAROFTOBACCOSMOKINGONSET'.

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
Time to Death Cox regression test   N=0        
AGE Spearman correlation test N=3 older N=3 younger N=0
NEOPLASM DISEASESTAGE ANOVA test N=44        
PATHOLOGY T STAGE Spearman correlation test N=2 higher stage N=0 lower stage N=2
PATHOLOGY N STAGE Spearman correlation test N=3 higher stage N=3 lower stage N=0
PATHOLOGY M STAGE t test N=102 mx N=12 m0 N=90
GENDER t test N=46 male N=14 female N=32
HISTOLOGICAL TYPE ANOVA test N=85        
RADIATIONS RADIATION REGIMENINDICATION t test N=185 yes N=17 no N=168
NUMBERPACKYEARSSMOKED Spearman correlation test N=3 higher numberpackyearssmoked N=2 lower numberpackyearssmoked N=1
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=11 higher number.of.lymph.nodes N=11 lower number.of.lymph.nodes N=0
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.1-211 (median=16.2)
  censored N = 250
  death N = 154
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

3 genes related to 'AGE'.

Table S2.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 60.84 (12)
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
KIAA1143 0.2855 4.325e-09 8.73e-05
KIF15 0.2855 4.325e-09 8.73e-05
FIGNL1 0.2327 2.014e-06 0.0406

Figure S1.  Get High-res Image As an example, this figure shows the association of KIAA1143 to 'AGE'. P value = 4.33e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

44 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 24
  STAGE II 63
  STAGE III 66
  STAGE IVA 193
  STAGE IVB 8
     
  Significant markers N = 44
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'

ANOVA_P Q
ZMIZ2 1.539e-09 3.11e-05
RIF1 6.217e-09 0.000125
IDH3A 7.315e-09 0.000148
HDLBP 9.116e-09 0.000184
SEPT2 9.116e-09 0.000184
EIF3J 9.456e-09 0.000191
C11ORF45 1.339e-08 0.00027
KCNJ5 1.339e-08 0.00027
C2CD3__1 1.614e-08 0.000326
PPME1__1 1.614e-08 0.000326

Figure S2.  Get High-res Image As an example, this figure shows the association of ZMIZ2 to 'NEOPLASM.DISEASESTAGE'. P value = 1.54e-09 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

2 genes related to 'PATHOLOGY.T.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.85 (1)
  N
  1 39
  2 105
  3 85
  4 130
     
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S7.  Get Full Table List of 2 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
LOC729121 -0.2527 1.231e-06 0.0248
RGPD4 -0.2527 1.231e-06 0.0248

Figure S3.  Get High-res Image As an example, this figure shows the association of LOC729121 to 'PATHOLOGY.T.STAGE'. P value = 1.23e-06 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

3 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
  0 135
  1 52
  2 128
  3 7
     
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S9.  Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
EFEMP1 0.2773 4.288e-07 0.00866
SLC47A2 0.2599 2.276e-06 0.0459
FAM185A 0.2591 2.456e-06 0.0496

Figure S4.  Get High-res Image As an example, this figure shows the association of EFEMP1 to 'PATHOLOGY.N.STAGE'. P value = 4.29e-07 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

102 genes related to 'PATHOLOGY.M.STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 104
  MX 43
     
  Significant markers N = 102
  Higher in MX 12
  Higher in M0 90
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

T(pos if higher in 'MX') ttestP Q AUC
DDX5 -7.16 3.726e-11 7.52e-07 0.7348
LRRC41 -6.81 2.478e-10 5e-06 0.7149
UQCRH -6.81 2.478e-10 5e-06 0.7149
ABCB9 -6.79 2.644e-10 5.34e-06 0.7581
OGFOD2__1 -6.79 2.644e-10 5.34e-06 0.7581
HSPBAP1 -6.69 4.759e-10 9.6e-06 0.7384
WDR54 -6.68 1.092e-09 2.2e-05 0.7929
ATP6V1G2 -6.56 1.116e-09 2.25e-05 0.7625
NFKBIL1 -6.56 1.116e-09 2.25e-05 0.7625
CDKN2D -6.37 2.379e-09 4.8e-05 0.7576

Figure S5.  Get High-res Image As an example, this figure shows the association of DDX5 to 'PATHOLOGY.M.STAGE'. P value = 3.73e-11 with T-test analysis.

Clinical variable #7: 'GENDER'

46 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 118
  MALE 291
     
  Significant markers N = 46
  Higher in MALE 14
  Higher in FEMALE 32
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -13.36 1.502e-29 3.03e-25 0.8543
FRG1B -7.26 1.234e-11 2.49e-07 0.7492
MRPL32 -6.77 1.753e-10 3.54e-06 0.7323
PSMA2__1 -6.77 1.753e-10 3.54e-06 0.7323
NLRP2 5.92 1.129e-08 0.000228 0.6861
CCDC121__1 -5.79 2.697e-08 0.000544 0.6705
GPN1__1 -5.79 2.697e-08 0.000544 0.6705
CEP72 -5.67 2.999e-08 0.000605 0.6389
SLC22A3 5.54 5.308e-08 0.00107 0.5852
TMEM232 -5.63 6.021e-08 0.00121 0.6784

Figure S6.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 1.5e-29 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

85 genes related to 'HISTOLOGICAL.TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  HEAD AND NECK SQUAMOUS CELL CARCINOMA 402
  HEAD AND NECK SQUAMOUS CELL CARCINOMA SPINDLE CELL VARIANT 1
  HEAD AND NECK SQUAMOUS CELL CARCINOMA BASALOID TYPE 6
     
  Significant markers N = 85
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'

ANOVA_P Q
ALG10 1.411e-195 2.85e-191
CTSK 1.003e-24 2.02e-20
CLCA4 2.964e-19 5.98e-15
KCNC1 9.324e-18 1.88e-13
MTA2 4.416e-16 8.91e-12
STRA13__1 4.219e-15 8.51e-11
JRK 6.429e-15 1.3e-10
WDR88 6.959e-15 1.4e-10
CYP2F1 6.983e-15 1.41e-10
LMOD2 1.584e-14 3.2e-10

Figure S7.  Get High-res Image As an example, this figure shows the association of ALG10 to 'HISTOLOGICAL.TYPE'. P value = 1.41e-195 with ANOVA analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

185 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S16.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 81
  YES 328
     
  Significant markers N = 185
  Higher in YES 17
  Higher in NO 168
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
FLJ10213 -8.59 2.548e-16 5.14e-12 0.69
PPP4R2 -8.59 2.548e-16 5.14e-12 0.69
C1D -7.69 1.953e-13 3.94e-09 0.668
AMY2B__1 -7.65 2.038e-13 4.11e-09 0.681
RNPC3 -7.65 2.038e-13 4.11e-09 0.681
HSPB1 -7.08 9.663e-11 1.95e-06 0.7598
RANBP1__1 -6.93 1.314e-10 2.65e-06 0.7215
TRMT2A__1 -6.93 1.314e-10 2.65e-06 0.7215
SNRNP40 -6.9 2.886e-10 5.82e-06 0.7336
ZCCHC17 -6.9 2.886e-10 5.82e-06 0.7336

Figure S8.  Get High-res Image As an example, this figure shows the association of FLJ10213 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.55e-16 with T-test analysis.

Clinical variable #10: 'NUMBERPACKYEARSSMOKED'

3 genes related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 46.7 (38)
  Significant markers N = 3
  pos. correlated 2
  neg. correlated 1
List of 3 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

Table S19.  Get Full Table List of 3 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
KLF6 0.3348 1.991e-07 0.00402
ELL 0.3159 1.009e-06 0.0204
DBF4__1 -0.3136 1.588e-06 0.0321

Figure S9.  Get High-res Image As an example, this figure shows the association of KLF6 to 'NUMBERPACKYEARSSMOKED'. P value = 1.99e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1966.53 (13)
  Significant markers N = 0
Clinical variable #12: 'NUMBER.OF.LYMPH.NODES'

11 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S21.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.32 (4.7)
  Significant markers N = 11
  pos. correlated 11
  neg. correlated 0
List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S22.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
FAM185A 0.3104 2.031e-08 0.00041
WNT1 0.2787 5.42e-07 0.0109
NBLA00301 0.2758 7.193e-07 0.0145
ARHGAP27 0.2757 7.24e-07 0.0146
P2RY6 0.2756 7.294e-07 0.0147
AVPI1 0.2741 8.468e-07 0.0171
HSPB3 0.2717 1.062e-06 0.0214
ISLR2 0.2691 1.353e-06 0.0273
LOC283731 0.2691 1.353e-06 0.0273
PITPNM2 0.2658 1.84e-06 0.0371

Figure S10.  Get High-res Image As an example, this figure shows the association of FAM185A to 'NUMBER.OF.LYMPH.NODES'. P value = 2.03e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

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 = 409

  • Number of genes = 20185

  • Number of clinical features = 12

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

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

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

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] 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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