Correlation between gene methylation status and clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1T43R5C
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1T43R5C
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 19719 genes and 14 clinical features across 421 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

  • 302 genes correlated to 'AGE'.

    • MGA ,  NHLRC1 ,  INA ,  C1ORF59 ,  SYNGR3 ,  ...

  • 26 genes correlated to 'GENDER'.

    • ALG11__2 ,  UTP14C__1 ,  ETF1 ,  KIF4B ,  FAM35A ,  ...

  • 1850 genes correlated to 'HISTOLOGICAL.TYPE'.

    • PON2 ,  LEPR ,  LEPROT ,  XDH ,  EMP1 ,  ...

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

    • SIK1 ,  STX17 ,  SNX31 ,  KIAA1143__1 ,  KIF15__1 ,  ...

  • 49 genes correlated to 'RADIATIONEXPOSURE'.

    • CASP12 ,  CHEK2 ,  HSCB ,  PLOD1 ,  PRMT7 ,  ...

  • 28 genes correlated to 'DISTANT.METASTASIS'.

    • C1ORF91__1 ,  EIF3I__1 ,  LCA5 ,  CAPN5__1 ,  OMP ,  ...

  • 208 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • OTOS ,  TBX19 ,  DEFB131 ,  S100A12 ,  SLC16A3 ,  ...

  • 670 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • CPNE1__1 ,  RBM12__1 ,  PON2 ,  SREBF1 ,  BMP1 ,  ...

  • 10 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • ANKRD34B ,  CAPN5__1 ,  OMP ,  TRPA1 ,  C12ORF54 ,  ...

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

    • FUT2 ,  MET ,  TAGLN2 ,  MACF1__1 ,  DUSP6 ,  ...

  • 174 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • C1ORF91__1 ,  EIF3I__1 ,  OTOS ,  C10ORF137 ,  LCA5 ,  ...

  • 1 gene correlated to 'TUMOR.SIZE'.

    • FOXD4L1

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

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=302 older N=299 younger N=3
GENDER t test N=26 male N=15 female N=11
HISTOLOGICAL TYPE ANOVA test N=1850        
RADIATIONS RADIATION REGIMENINDICATION t test N=39 yes N=21 no N=18
RADIATIONEXPOSURE t test N=49 yes N=24 no N=25
DISTANT METASTASIS ANOVA test N=28        
EXTRATHYROIDAL EXTENSION ANOVA test N=208        
LYMPH NODE METASTASIS ANOVA test N=670        
COMPLETENESS OF RESECTION ANOVA test N=10        
NUMBER OF LYMPH NODES Spearman correlation test N=610 higher number.of.lymph.nodes N=13 lower number.of.lymph.nodes N=597
NEOPLASM DISEASESTAGE ANOVA test N=174        
MULTIFOCALITY t test   N=0        
TUMOR SIZE Spearman correlation test N=1 higher tumor.size N=1 lower tumor.size 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) 0-147.4 (median=9.3)
  censored N = 406
  death N = 10
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

302 genes related to 'AGE'.

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

AGE Mean (SD) 46.55 (16)
  Significant markers N = 302
  pos. correlated 299
  neg. correlated 3
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
MGA 0.5289 1.032e-31 2.04e-27
NHLRC1 0.493 3.6e-27 7.1e-23
INA 0.4852 2.991e-26 5.9e-22
C1ORF59 0.4777 2.201e-25 4.34e-21
SYNGR3 0.4479 3.637e-22 7.17e-18
RANBP17 0.4478 3.717e-22 7.33e-18
ACN9 0.443 1.162e-21 2.29e-17
NTNG2 0.4402 2.239e-21 4.41e-17
ZNF518B 0.4323 1.352e-20 2.66e-16
KL 0.425 6.774e-20 1.34e-15

Figure S1.  Get High-res Image As an example, this figure shows the association of MGA to 'AGE'. P value = 1.03e-31 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

26 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 316
  MALE 105
     
  Significant markers N = 26
  Higher in MALE 15
  Higher in FEMALE 11
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
ALG11__2 39.64 5.734e-141 1.13e-136 0.9945
UTP14C__1 39.64 5.734e-141 1.13e-136 0.9945
ETF1 29.55 1.647e-66 3.25e-62 0.9877
KIF4B -16.3 3.161e-38 6.23e-34 0.904
FAM35A -11.9 4.512e-27 8.9e-23 0.8692
GLUD1__1 -11.9 4.512e-27 8.9e-23 0.8692
CHTF8 10.35 1.667e-20 3.29e-16 0.8134
HAS3__1 10.35 1.667e-20 3.29e-16 0.8134
WBP11P1 8.96 9.636e-16 1.9e-11 0.8066
ANKRD20A4 8.14 2.239e-14 4.41e-10 0.7435

Figure S2.  Get High-res Image As an example, this figure shows the association of ALG11__2 to 'GENDER'. P value = 5.73e-141 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

1850 genes related to 'HISTOLOGICAL.TYPE'.

Table S6.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  OTHER SPECIFY 7
  THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL 294
  THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) 85
  THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) 35
     
  Significant markers N = 1850
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
PON2 1.545e-35 3.05e-31
LEPR 3.713e-33 7.32e-29
LEPROT 3.713e-33 7.32e-29
XDH 7.43e-33 1.46e-28
EMP1 8.247e-33 1.63e-28
SLC6A12 1.1e-32 2.17e-28
LAMP3 1.226e-31 2.42e-27
C8ORF73 1.27e-31 2.5e-27
LOC399959 8.887e-31 1.75e-26
STK17B 3.234e-30 6.37e-26

Figure S3.  Get High-res Image As an example, this figure shows the association of PON2 to 'HISTOLOGICAL.TYPE'. P value = 1.54e-35 with ANOVA analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S8.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 407
     
  Significant markers N = 39
  Higher in YES 21
  Higher in NO 18
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
SIK1 8.85 5.769e-17 1.14e-12 0.6923
STX17 9.26 2.527e-14 4.98e-10 0.6404
SNX31 7.44 9.999e-13 1.97e-08 0.6823
KIAA1143__1 8.38 1.136e-12 2.24e-08 0.742
KIF15__1 8.38 1.136e-12 2.24e-08 0.742
MYOM2 7.62 1.222e-11 2.41e-07 0.5383
TAF7 7.2 1.379e-11 2.72e-07 0.691
HORMAD1 -8.21 4.815e-11 9.49e-07 0.7181
ZNHIT3 6.95 1.278e-10 2.52e-06 0.5674
HSD17B7P2 7.17 3.673e-10 7.24e-06 0.5597

Figure S4.  Get High-res Image As an example, this figure shows the association of SIK1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 5.77e-17 with T-test analysis.

Clinical variable #6: 'RADIATIONEXPOSURE'

49 genes related to 'RADIATIONEXPOSURE'.

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

RADIATIONEXPOSURE Labels N
  NO 363
  YES 16
     
  Significant markers N = 49
  Higher in YES 24
  Higher in NO 25
List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

T(pos if higher in 'YES') ttestP Q AUC
CASP12 -8.38 6.775e-14 1.34e-09 0.6305
CHEK2 -6.85 6.597e-11 1.3e-06 0.5668
HSCB -6.85 6.597e-11 1.3e-06 0.5668
PLOD1 7 7.317e-11 1.44e-06 0.6626
PRMT7 6.64 1.133e-10 2.23e-06 0.5904
HESX1 7.03 2.042e-10 4.03e-06 0.6544
TMEM63C -6.91 1.079e-09 2.13e-05 0.6133
PCNXL3 6.23 1.239e-09 2.44e-05 0.6674
RAD54B 7.66 3.274e-09 6.45e-05 0.7421
PHKB 6.19 4.804e-09 9.47e-05 0.702

Figure S5.  Get High-res Image As an example, this figure shows the association of CASP12 to 'RADIATIONEXPOSURE'. P value = 6.78e-14 with T-test analysis.

Clinical variable #7: 'DISTANT.METASTASIS'

28 genes related to 'DISTANT.METASTASIS'.

Table S12.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 236
  M1 7
  MX 177
     
  Significant markers N = 28
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

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

ANOVA_P Q
C1ORF91__1 6.799e-15 1.34e-10
EIF3I__1 6.799e-15 1.34e-10
LCA5 3.346e-12 6.6e-08
CAPN5__1 4.452e-09 8.78e-05
OMP 4.452e-09 8.78e-05
FOXC1 1.266e-08 0.00025
RPS10 1.958e-08 0.000386
C2ORF34 3.227e-08 0.000636
PREPL 3.227e-08 0.000636
PRPF31 9.171e-08 0.00181

Figure S6.  Get High-res Image As an example, this figure shows the association of C1ORF91__1 to 'DISTANT.METASTASIS'. P value = 6.8e-15 with ANOVA analysis.

Clinical variable #8: 'EXTRATHYROIDAL.EXTENSION'

208 genes related to 'EXTRATHYROIDAL.EXTENSION'.

Table S14.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 113
  MODERATE/ADVANCED (T4A) 13
  NONE 275
  VERY ADVANCED (T4B) 1
     
  Significant markers N = 208
List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

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

ANOVA_P Q
OTOS 1.584e-69 3.12e-65
TBX19 6.084e-32 1.2e-27
DEFB131 1.245e-31 2.45e-27
S100A12 1.531e-24 3.02e-20
SLC16A3 8.529e-23 1.68e-18
PA2G4P4 2.515e-22 4.96e-18
MTUS2 3.718e-22 7.33e-18
BTBD12 1.504e-19 2.97e-15
ISL2 7.19e-19 1.42e-14
C9ORF46 7.688e-18 1.52e-13

Figure S7.  Get High-res Image As an example, this figure shows the association of OTOS to 'EXTRATHYROIDAL.EXTENSION'. P value = 1.58e-69 with ANOVA analysis.

Clinical variable #9: 'LYMPH.NODE.METASTASIS'

670 genes related to 'LYMPH.NODE.METASTASIS'.

Table S16.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 192
  N1 49
  N1A 81
  N1B 60
  NX 39
     
  Significant markers N = 670
List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
CPNE1__1 1.82e-16 3.59e-12
RBM12__1 1.82e-16 3.59e-12
PON2 1.004e-15 1.98e-11
SREBF1 6.902e-15 1.36e-10
BMP1 7.45e-15 1.47e-10
MACF1__1 7.437e-15 1.47e-10
FUT2 9.913e-15 1.95e-10
TMEM173 3.205e-14 6.32e-10
XDH 5.305e-14 1.05e-09
MET 5.362e-14 1.06e-09

Figure S8.  Get High-res Image As an example, this figure shows the association of CPNE1__1 to 'LYMPH.NODE.METASTASIS'. P value = 1.82e-16 with ANOVA analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

10 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S18.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 332
  R1 37
  R2 2
  RX 25
     
  Significant markers N = 10
List of 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S19.  Get Full Table List of 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
ANKRD34B 7.729e-31 1.52e-26
CAPN5__1 4.146e-25 8.18e-21
OMP 4.146e-25 8.18e-21
TRPA1 8.162e-08 0.00161
C12ORF54 9.157e-08 0.00181
HPS3 9.734e-08 0.00192
KCNJ14 1.757e-07 0.00346
CHUK 2.342e-07 0.00462
TMOD4 3.239e-07 0.00638
VPS72 3.239e-07 0.00638

Figure S9.  Get High-res Image As an example, this figure shows the association of ANKRD34B to 'COMPLETENESS.OF.RESECTION'. P value = 7.73e-31 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

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

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

NUMBER.OF.LYMPH.NODES Mean (SD) 3.52 (6.2)
  Significant markers N = 610
  pos. correlated 13
  neg. correlated 597
List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S21.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
FUT2 -0.4275 5.232e-16 1.03e-11
MET -0.4161 3.668e-15 7.23e-11
TAGLN2 -0.4088 1.201e-14 2.37e-10
MACF1__1 -0.4012 4.069e-14 8.02e-10
DUSP6 -0.4005 4.581e-14 9.03e-10
SDC4 -0.4004 4.604e-14 9.08e-10
TMEM173 -0.3999 5.007e-14 9.87e-10
HDAC9 -0.3991 5.696e-14 1.12e-09
CPNE1__1 -0.3975 7.319e-14 1.44e-09
RBM12__1 -0.3975 7.319e-14 1.44e-09

Figure S10.  Get High-res Image As an example, this figure shows the association of FUT2 to 'NUMBER.OF.LYMPH.NODES'. P value = 5.23e-16 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

174 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S22.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 238
  STAGE II 44
  STAGE III 94
  STAGE IV 2
  STAGE IVA 36
  STAGE IVC 4
     
  Significant markers N = 174
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S23.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
C1ORF91__1 1.027e-29 2.03e-25
EIF3I__1 1.027e-29 2.03e-25
OTOS 5.243e-28 1.03e-23
C10ORF137 4.984e-21 9.83e-17
LCA5 2.664e-19 5.25e-15
ACTA1 1.635e-17 3.22e-13
C2ORF34 2.793e-17 5.51e-13
PREPL 2.793e-17 5.51e-13
CHAT__1 2.49e-15 4.91e-11
SLC18A3 2.49e-15 4.91e-11

Figure S11.  Get High-res Image As an example, this figure shows the association of C1ORF91__1 to 'NEOPLASM.DISEASESTAGE'. P value = 1.03e-29 with ANOVA analysis.

Clinical variable #13: 'MULTIFOCALITY'

No gene related to 'MULTIFOCALITY'.

Table S24.  Basic characteristics of clinical feature: 'MULTIFOCALITY'

MULTIFOCALITY Labels N
  MULTIFOCAL 181
  UNIFOCAL 231
     
  Significant markers N = 0
Clinical variable #14: 'TUMOR.SIZE'

One gene related to 'TUMOR.SIZE'.

Table S25.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 2.93 (1.6)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S26.  Get Full Table List of one gene significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
FOXD4L1 0.2618 1.317e-06 0.026

Figure S12.  Get High-res Image As an example, this figure shows the association of FOXD4L1 to 'TUMOR.SIZE'. P value = 1.32e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

  • Expresson data file = THCA-TP.meth.by_min_expr_corr.data.txt

  • Clinical data file = THCA-TP.clin.merged.picked.txt

  • Number of patients = 421

  • Number of genes = 19719

  • Number of clinical features = 14

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

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

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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