Correlation between gene methylation status and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1057DCB
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/C1057DCB
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 20108 genes and 12 clinical features across 378 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 3 genes correlated to 'AGE'.

    • SLC35D3 ,  KIAA1143 ,  KIF15

  • 66 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • RB1__1 ,  C11ORF45 ,  KCNJ5 ,  TOB2 ,  HDLBP ,  ...

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

    • FAM185A ,  AVPI1 ,  SLC43A3 ,  RPS25 ,  TRAPPC4

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

    • HSPBAP1 ,  DDX5__1 ,  STX8 ,  WDR16 ,  LRRC41 ,  ...

  • 55 genes correlated to 'GENDER'.

    • KIF4B ,  ZNF770 ,  FRG1B ,  CCDC121__1 ,  GPN1__1 ,  ...

  • 106 genes correlated to 'HISTOLOGICAL.TYPE'.

    • ALG10 ,  STRA13__1 ,  CLCA4 ,  MTA2 ,  FAM103A1 ,  ...

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

    • TOP2B ,  FLJ10213 ,  PPP4R2 ,  BLOC1S2 ,  AMY2B__1 ,  ...

  • 5 genes correlated to 'NUMBERPACKYEARSSMOKED'.

    • KLF6 ,  RAB21 ,  SCN9A ,  ELL ,  SRPK2

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

    • FAM185A ,  ARHGAP27 ,  AVPI1 ,  RPS25 ,  TRAPPC4

  • No genes correlated to 'Time to Death', 'PATHOLOGY.T.STAGE', 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=66        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test N=5 higher stage N=5 lower stage N=0
PATHOLOGY M STAGE t test N=181 mx N=11 m0 N=170
GENDER t test N=55 male N=10 female N=45
HISTOLOGICAL TYPE ANOVA test N=106        
RADIATIONS RADIATION REGIMENINDICATION t test N=81 yes N=3 no N=78
NUMBERPACKYEARSSMOKED Spearman correlation test N=5 higher numberpackyearssmoked N=2 lower numberpackyearssmoked N=3
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=5 higher number.of.lymph.nodes N=5 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) 0.1-210.9 (median=15.8)
  censored N = 233
  death N = 140
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

3 genes related to 'AGE'.

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

AGE Mean (SD) 60.76 (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
SLC35D3 0.2764 4.699e-08 0.000945
KIAA1143 0.2647 1.771e-07 0.00356
KIF15 0.2647 1.771e-07 0.00356

Figure S1.  Get High-res Image As an example, this figure shows the association of SLC35D3 to 'AGE'. P value = 4.7e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

66 genes related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 24
  STAGE II 59
  STAGE III 59
  STAGE IVA 178
  STAGE IVB 6
     
  Significant markers N = 66
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
RB1__1 2.914e-11 5.86e-07
C11ORF45 4.175e-11 8.39e-07
KCNJ5 4.175e-11 8.39e-07
TOB2 4.407e-11 8.86e-07
HDLBP 5.215e-11 1.05e-06
SEPT2 5.215e-11 1.05e-06
C2CD3__1 8.017e-11 1.61e-06
PPME1__1 8.017e-11 1.61e-06
CTR9 8.584e-11 1.73e-06
JARID2 9.861e-11 1.98e-06

Figure S2.  Get High-res Image As an example, this figure shows the association of RB1__1 to 'NEOPLASM.DISEASESTAGE'. P value = 2.91e-11 with ANOVA analysis.

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

No gene 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 37
  2 97
  3 77
  4 120
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

5 genes related to 'PATHOLOGY.N.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 1.01 (0.95)
  N
  0 126
  1 45
  2 120
  3 5
     
  Significant markers N = 5
  pos. correlated 5
  neg. correlated 0
List of 5 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of 5 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
FAM185A 0.2871 5.022e-07 0.0101
AVPI1 0.283 7.411e-07 0.0149
SLC43A3 0.2754 1.494e-06 0.03
RPS25 0.2706 2.316e-06 0.0466
TRAPPC4 0.2706 2.316e-06 0.0466

Figure S3.  Get High-res Image As an example, this figure shows the association of FAM185A to 'PATHOLOGY.N.STAGE'. P value = 5.02e-07 with Spearman correlation analysis.

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

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

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 90
  MX 28
     
  Significant markers N = 181
  Higher in MX 11
  Higher in M0 170
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

T(pos if higher in 'MX') ttestP Q AUC
HSPBAP1 -10.56 3.598e-18 7.23e-14 0.8476
DDX5__1 -10.25 3.925e-17 7.89e-13 0.8393
STX8 -9.61 1.966e-16 3.95e-12 0.8548
WDR16 -9.61 1.966e-16 3.95e-12 0.8548
LRRC41 -9.67 2.329e-16 4.68e-12 0.8214
UQCRH -9.67 2.329e-16 4.68e-12 0.8214
ELMOD3 -9.09 3.237e-15 6.51e-11 0.8488
RETSAT -9.09 3.237e-15 6.51e-11 0.8488
PTRH2__1 -8.88 1.893e-14 3.8e-10 0.8298
TMEM49__1 -8.88 1.893e-14 3.8e-10 0.8298

Figure S4.  Get High-res Image As an example, this figure shows the association of HSPBAP1 to 'PATHOLOGY.M.STAGE'. P value = 3.6e-18 with T-test analysis.

Clinical variable #7: 'GENDER'

55 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 109
  MALE 269
     
  Significant markers N = 55
  Higher in MALE 10
  Higher in FEMALE 45
List of top 10 genes differentially expressed by 'GENDER'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -13.38 3.423e-29 6.88e-25 0.864
ZNF770 -7.22 6.635e-12 1.33e-07 0.7126
FRG1B -7.29 1.279e-11 2.57e-07 0.7588
CCDC121__1 -6.1 5.804e-09 0.000117 0.6858
GPN1__1 -6.1 5.804e-09 0.000117 0.6858
CEP72 -5.95 7.023e-09 0.000141 0.6562
NDUFA13 -5.84 2.228e-08 0.000448 0.6956
TSSK6 -5.84 2.228e-08 0.000448 0.6956
BRCA1__1 -5.78 2.991e-08 0.000601 0.6897
NBR2__1 -5.78 2.991e-08 0.000601 0.6897

Figure S5.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 3.42e-29 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

106 genes related to 'HISTOLOGICAL.TYPE'.

Table S13.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  HEAD AND NECK SQUAMOUS CELL CARCINOMA 373
  HEAD AND NECK SQUAMOUS CELL CARCINOMA SPINDLE CELL VARIANT 1
  HEAD AND NECK SQUAMOUS CELL CARCINOMA BASALOID TYPE 4
     
  Significant markers N = 106
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'

ANOVA_P Q
ALG10 5.382e-188 1.08e-183
STRA13__1 3.225e-21 6.48e-17
CLCA4 4.511e-18 9.07e-14
MTA2 5.058e-18 1.02e-13
FAM103A1 9.664e-17 1.94e-12
ERAP2 2.849e-16 5.73e-12
DPF1 3.525e-16 7.09e-12
WDR88 4.938e-16 9.93e-12
DNAJC11 6.576e-16 1.32e-11
CCDC11 1.44e-14 2.89e-10

Figure S6.  Get High-res Image As an example, this figure shows the association of ALG10 to 'HISTOLOGICAL.TYPE'. P value = 5.38e-188 with ANOVA analysis.

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

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

Table S15.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 76
  YES 302
     
  Significant markers N = 81
  Higher in YES 3
  Higher in NO 78
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'

T(pos if higher in 'YES') ttestP Q AUC
TOP2B 7.23 3.536e-12 7.11e-08 0.6825
FLJ10213 -7.23 3.538e-12 7.11e-08 0.668
PPP4R2 -7.23 3.538e-12 7.11e-08 0.668
BLOC1S2 -6.84 2.027e-10 4.08e-06 0.7206
AMY2B__1 -6.55 2.596e-10 5.22e-06 0.6613
RNPC3 -6.55 2.596e-10 5.22e-06 0.6613
C1D -6.44 4.803e-10 9.66e-06 0.6395
HSPB1 -6.78 5.512e-10 1.11e-05 0.7571
SCARNA2 -6.28 6.869e-09 0.000138 0.7321
RANBP1 -6.1 1.134e-08 0.000228 0.7071

Figure S7.  Get High-res Image As an example, this figure shows the association of TOP2B to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 3.54e-12 with T-test analysis.

Clinical variable #10: 'NUMBERPACKYEARSSMOKED'

5 genes related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 47.12 (39)
  Significant markers N = 5
  pos. correlated 2
  neg. correlated 3
List of 5 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

Table S18.  Get Full Table List of 5 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
KLF6 0.3621 5.328e-08 0.00107
RAB21 -0.3346 5.747e-07 0.0116
SCN9A -0.3341 6.012e-07 0.0121
ELL 0.3285 9.446e-07 0.019
SRPK2 -0.3204 1.795e-06 0.0361

Figure S8.  Get High-res Image As an example, this figure shows the association of KLF6 to 'NUMBERPACKYEARSSMOKED'. P value = 5.33e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1966.42 (13)
  Significant markers N = 0
Clinical variable #12: 'NUMBER.OF.LYMPH.NODES'

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

Table S20.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.47 (4.9)
  Significant markers N = 5
  pos. correlated 5
  neg. correlated 0
List of 5 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S21.  Get Full Table List of 5 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
FAM185A 0.3128 6.918e-08 0.00139
ARHGAP27 0.2875 7.966e-07 0.016
AVPI1 0.2784 1.805e-06 0.0363
RPS25 0.2749 2.469e-06 0.0496
TRAPPC4 0.2749 2.469e-06 0.0496

Figure S9.  Get High-res Image As an example, this figure shows the association of FAM185A to 'NUMBER.OF.LYMPH.NODES'. P value = 6.92e-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 = 378

  • Number of genes = 20108

  • 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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