Thyroid Adenocarcinoma: Correlation between gene methylation status and clinical features
(primary solid tumor cohort)
Maintained by Juok Cho (Broad Institute)
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 17090 genes and 13 clinical features across 286 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

  • 159 genes correlated to 'AGE'.

    • NHLRC1 ,  C1ORF59 ,  C7ORF13 ,  KIF15 ,  ZNF518B ,  ...

  • 11 genes correlated to 'GENDER'.

    • UTP14C ,  KIF4B ,  FAM35A ,  WBP11P1 ,  ANKRD20A4 ,  ...

  • 1855 genes correlated to 'HISTOLOGICAL.TYPE'.

    • PON2 ,  EMP1 ,  CLCF1 ,  SH3GL1 ,  LY6G6C ,  ...

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

    • KIF15 ,  STX17 ,  MAP3K3 ,  SIK1 ,  SNX31 ,  ...

  • 24 genes correlated to 'RADIATIONEXPOSURE'.

    • ATP5L2 ,  ALKBH2 ,  CASP12 ,  ART3 ,  NKX2-2 ,  ...

  • 33 genes correlated to 'DISTANT.METASTASIS'.

    • GPR153 ,  C12ORF45 ,  DENND1A ,  C1ORF91 ,  C2ORF34 ,  ...

  • 33 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • DYNLRB2 ,  SNORD97 ,  TTC30A ,  ZNF784 ,  C4ORF43 ,  ...

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

    • PON2 ,  CPNE1 ,  RBM12 ,  MVP ,  SNHG3-RCC1 ,  ...

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

    • DENND1A ,  TRRAP ,  ZNF254 ,  C18ORF2 ,  ZNF585A ,  ...

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

    • STARD5 ,  TAGLN2 ,  FUT2 ,  DUSP6 ,  SNHG3-RCC1 ,  ...

  • 92 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • GPR153 ,  C12ORF45 ,  C1ORF91 ,  C2ORF34 ,  C14ORF169 ,  ...

  • 3 genes correlated to 'TUMOR.SIZE'.

    • AP4M1 ,  TXNL4B ,  COMMD3

  • No genes correlated to '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
AGE Spearman correlation test N=159 older N=158 younger N=1
GENDER t test N=11 male N=5 female N=6
HISTOLOGICAL TYPE ANOVA test N=1855        
RADIATIONS RADIATION REGIMENINDICATION t test N=38 yes N=23 no N=15
RADIATIONEXPOSURE t test N=24 yes N=11 no N=13
DISTANT METASTASIS ANOVA test N=33        
EXTRATHYROIDAL EXTENSION ANOVA test N=33        
LYMPH NODE METASTASIS ANOVA test N=396        
COMPLETENESS OF RESECTION ANOVA test N=20        
NUMBER OF LYMPH NODES Spearman correlation test N=618 higher number.of.lymph.nodes N=13 lower number.of.lymph.nodes N=605
NEOPLASM DISEASESTAGE ANOVA test N=92        
MULTIFOCALITY t test   N=0        
TUMOR SIZE Spearman correlation test N=3 higher tumor.size N=3 lower tumor.size N=0
Clinical variable #1: 'AGE'

159 genes related to 'AGE'.

Table S1.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 46.52 (15)
  Significant markers N = 159
  pos. correlated 158
  neg. correlated 1
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S2.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
NHLRC1 0.5174 5.55e-21 9.49e-17
C1ORF59 0.5142 1.057e-20 1.81e-16
C7ORF13 0.5016 1.255e-19 2.14e-15
KIF15 0.4941 5.18e-19 8.85e-15
ZNF518B 0.4854 2.597e-18 4.44e-14
INA 0.4734 2.229e-17 3.81e-13
DLK2 0.4721 2.782e-17 4.75e-13
ZNF274 0.4632 1.282e-16 2.19e-12
ACN9 0.4568 3.745e-16 6.4e-12
GNPNAT1 0.4513 9.403e-16 1.61e-11

Figure S1.  Get High-res Image As an example, this figure shows the association of NHLRC1 to 'AGE'. P value = 5.55e-21 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #2: 'GENDER'

11 genes related to 'GENDER'.

Table S3.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 216
  MALE 70
     
  Significant markers N = 11
  Higher in MALE 5
  Higher in FEMALE 6
List of top 10 genes differentially expressed by 'GENDER'

Table S4.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
UTP14C 34.12 5.144e-96 8.79e-92 0.9968
KIF4B -14.48 6.076e-29 1.04e-24 0.9219
FAM35A -9.33 1.201e-17 2.05e-13 0.8587
WBP11P1 8.41 2e-13 3.42e-09 0.8311
ANKRD20A4 7.47 9.911e-12 1.69e-07 0.762
FRG1B -6.23 2.352e-09 4.02e-05 0.7376
APAF1 -6.2 7.336e-09 0.000125 0.7332
CCDC121 6.05 1.634e-08 0.000279 0.7271
TUBB4 5.98 1.954e-08 0.000334 0.7331
MCOLN1 -5.79 2.697e-08 0.000461 0.6827

Figure S2.  Get High-res Image As an example, this figure shows the association of UTP14C to 'GENDER'. P value = 5.14e-96 with T-test analysis.

Clinical variable #3: 'HISTOLOGICAL.TYPE'

1855 genes related to 'HISTOLOGICAL.TYPE'.

Table S5.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  OTHER 18
  THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL 169
  THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) 70
  THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) 29
     
  Significant markers N = 1855
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
PON2 3.755e-39 6.42e-35
EMP1 8.263e-37 1.41e-32
CLCF1 1.303e-36 2.23e-32
SH3GL1 1.571e-36 2.69e-32
LY6G6C 7.469e-36 1.28e-31
C8ORF73 7.845e-36 1.34e-31
AKNA 8.884e-36 1.52e-31
LOC100126784 1.169e-35 2e-31
SLC35F2 1.34e-35 2.29e-31
JAK1 3.524e-35 6.02e-31

Figure S3.  Get High-res Image As an example, this figure shows the association of PON2 to 'HISTOLOGICAL.TYPE'. P value = 3.75e-39 with ANOVA analysis.

Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S7.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 12
  YES 274
     
  Significant markers N = 38
  Higher in YES 23
  Higher in NO 15
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
KIF15 10.63 9.589e-19 1.64e-14 0.8011
STX17 9.02 3.581e-16 6.12e-12 0.6566
MAP3K3 -11.6 1.285e-13 2.2e-09 0.885
SIK1 7.81 1.465e-13 2.5e-09 0.7226
SNX31 6.45 5.462e-10 9.33e-06 0.7086
POMP -7.41 6.133e-10 1.05e-05 0.8467
ZNHIT3 6.52 8.521e-10 1.46e-05 0.6214
MYOM2 6.7 9.753e-10 1.67e-05 0.5249
GPR120 7.06 1.265e-09 2.16e-05 0.6651
HSD17B7P2 6.46 2.516e-09 4.3e-05 0.5766

Figure S4.  Get High-res Image As an example, this figure shows the association of KIF15 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 9.59e-19 with T-test analysis.

Clinical variable #5: 'RADIATIONEXPOSURE'

24 genes related to 'RADIATIONEXPOSURE'.

Table S9.  Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'

RADIATIONEXPOSURE Labels N
  NO 239
  YES 12
     
  Significant markers N = 24
  Higher in YES 11
  Higher in NO 13
List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

T(pos if higher in 'YES') ttestP Q AUC
ATP5L2 8.38 4.462e-15 7.63e-11 0.7204
ALKBH2 -7.13 1.744e-11 2.98e-07 0.705
CASP12 -6.57 4.109e-09 7.02e-05 0.6269
ART3 6.19 5.478e-09 9.36e-05 0.6625
NKX2-2 -6.27 9.313e-09 0.000159 0.6726
CHEK2 -5.69 5.306e-08 0.000907 0.5868
HSCB -5.69 5.306e-08 0.000907 0.5868
PRMT7 5.6 6.419e-08 0.0011 0.6722
PLOD1 5.47 1.526e-07 0.00261 0.6241
IBTK -6.34 2.28e-07 0.00389 0.7197

Figure S5.  Get High-res Image As an example, this figure shows the association of ATP5L2 to 'RADIATIONEXPOSURE'. P value = 4.46e-15 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

33 genes related to 'DISTANT.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 139
  M1 3
  MX 143
     
  Significant markers N = 33
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

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

ANOVA_P Q
GPR153 1.042e-16 1.78e-12
C12ORF45 1.479e-16 2.53e-12
DENND1A 6.168e-16 1.05e-11
C1ORF91 3.569e-15 6.1e-11
C2ORF34 5.077e-14 8.67e-10
C14ORF169 5.518e-14 9.43e-10
RPS10 5.685e-14 9.71e-10
TMEM161A 2.141e-12 3.66e-08
ADAM9 9.901e-11 1.69e-06
THAP11 2.128e-10 3.64e-06

Figure S6.  Get High-res Image As an example, this figure shows the association of GPR153 to 'DISTANT.METASTASIS'. P value = 1.04e-16 with ANOVA analysis.

Clinical variable #7: 'EXTRATHYROIDAL.EXTENSION'

33 genes related to 'EXTRATHYROIDAL.EXTENSION'.

Table S13.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 67
  MODERATE/ADVANCED (T4A) 5
  NONE 200
     
  Significant markers N = 33
List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

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

ANOVA_P Q
DYNLRB2 2.416e-12 4.13e-08
SNORD97 1.025e-11 1.75e-07
TTC30A 4.033e-10 6.89e-06
ZNF784 1.324e-08 0.000226
C4ORF43 1.434e-08 0.000245
CUX2 1.616e-08 0.000276
ZNF781 1.974e-08 0.000337
ZNF549 2.117e-08 0.000362
FOXO1 2.187e-08 0.000374
MRPL55 3.175e-08 0.000542

Figure S7.  Get High-res Image As an example, this figure shows the association of DYNLRB2 to 'EXTRATHYROIDAL.EXTENSION'. P value = 2.42e-12 with ANOVA analysis.

Clinical variable #8: 'LYMPH.NODE.METASTASIS'

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

Table S15.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 142
  N1 16
  N1A 58
  N1B 42
  NX 28
     
  Significant markers N = 396
List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
PON2 5.882e-13 1.01e-08
CPNE1 2.086e-12 3.57e-08
RBM12 2.086e-12 3.57e-08
MVP 5.507e-12 9.41e-08
SNHG3-RCC1 6.341e-12 1.08e-07
STARD5 1.251e-11 2.14e-07
TAGLN2 1.847e-11 3.16e-07
BMP1 2.088e-11 3.57e-07
ADAMTS17 4.361e-11 7.45e-07
ITGB7 5.647e-11 9.65e-07

Figure S8.  Get High-res Image As an example, this figure shows the association of PON2 to 'LYMPH.NODE.METASTASIS'. P value = 5.88e-13 with ANOVA analysis.

Clinical variable #9: 'COMPLETENESS.OF.RESECTION'

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

Table S17.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 227
  R1 18
  R2 1
  RX 19
     
  Significant markers N = 20
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S18.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
DENND1A 3.243e-64 5.54e-60
TRRAP 3.382e-19 5.78e-15
ZNF254 2.745e-13 4.69e-09
C18ORF2 2.973e-11 5.08e-07
ZNF585A 6.962e-11 1.19e-06
HPS3 2.285e-10 3.9e-06
TYW3 2.497e-10 4.27e-06
LOC728743 3.501e-10 5.98e-06
PCDH18 6.522e-09 0.000111
AVIL 2.108e-08 0.00036

Figure S9.  Get High-res Image As an example, this figure shows the association of DENND1A to 'COMPLETENESS.OF.RESECTION'. P value = 3.24e-64 with ANOVA analysis.

Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

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

Table S19.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.82 (5.2)
  Significant markers N = 618
  pos. correlated 13
  neg. correlated 605
List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S20.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
STARD5 -0.4788 1.81e-14 3.09e-10
TAGLN2 -0.4757 2.824e-14 4.83e-10
FUT2 -0.4606 2.241e-13 3.83e-09
DUSP6 -0.4564 3.915e-13 6.69e-09
SNHG3-RCC1 -0.4542 5.283e-13 9.03e-09
POU2F3 -0.449 1.041e-12 1.78e-08
ARHGEF2 -0.4456 1.6e-12 2.73e-08
GPX4 -0.4443 1.904e-12 3.25e-08
CAPN2 -0.442 2.546e-12 4.35e-08
EPHA4 -0.4419 2.558e-12 4.37e-08

Figure S10.  Get High-res Image As an example, this figure shows the association of STARD5 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.81e-14 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'NEOPLASM.DISEASESTAGE'

92 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S21.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 163
  STAGE II 32
  STAGE III 62
  STAGE IVA 26
  STAGE IVC 2
     
  Significant markers N = 92
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
GPR153 1.337e-26 2.28e-22
C12ORF45 4.757e-25 8.13e-21
C1ORF91 3.026e-24 5.17e-20
C2ORF34 1.445e-23 2.47e-19
C14ORF169 2.057e-21 3.51e-17
RPS10 1.889e-20 3.23e-16
ZP3 5.099e-15 8.71e-11
THAP11 9.156e-15 1.56e-10
ADAM9 8.509e-14 1.45e-09
ZNF202 8.676e-14 1.48e-09

Figure S11.  Get High-res Image As an example, this figure shows the association of GPR153 to 'NEOPLASM.DISEASESTAGE'. P value = 1.34e-26 with ANOVA analysis.

Clinical variable #12: 'MULTIFOCALITY'

No gene related to 'MULTIFOCALITY'.

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

MULTIFOCALITY Labels N
  MULTIFOCAL 142
  UNIFOCAL 135
     
  Significant markers N = 0
Clinical variable #13: 'TUMOR.SIZE'

3 genes related to 'TUMOR.SIZE'.

Table S24.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 2.65 (1.5)
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S25.  Get Full Table List of 3 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
AP4M1 0.3196 1.611e-06 0.0275
TXNL4B 0.3187 1.734e-06 0.0296
COMMD3 0.3152 2.278e-06 0.0389

Figure S12.  Get High-res Image As an example, this figure shows the association of AP4M1 to 'TUMOR.SIZE'. P value = 1.61e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

  • Expresson data file = THCA-TP.meth.for_correlation.filtered_data.txt

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

  • Number of patients = 286

  • Number of genes = 17090

  • Number of clinical features = 13

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] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle