Correlation between gene methylation status and clinical features
PANCANCER cohort with 12 disease types (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1ZK5DN0
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): PANCANCER cohort with 12 disease types (Primary solid tumor cohort) - 21 April 2013: Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1ZK5DN0
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 15521 genes and 16 clinical features across 238 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 21 genes correlated to 'Time to Death'.

    • LGALS4 ,  ALG3 ,  TEX101 ,  VIL1 ,  PPY2 ,  ...

  • 6 genes correlated to 'AGE'.

    • FAM123C ,  C7ORF13 ,  KIF15 ,  TSPYL5 ,  BOC ,  ...

  • 5145 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

    • ZNF416 ,  BBS10 ,  AGK ,  SYNGR1 ,  HERPUD2 ,  ...

  • 332 genes correlated to 'GENDER'.

    • CDKL2 ,  ZNF295 ,  UTP14C ,  GLIPR1L1 ,  TBC1D24 ,  ...

  • 3669 genes correlated to 'HISTOLOGICAL.TYPE'.

    • ZNF419 ,  EPM2AIP1 ,  MED12L ,  BBS10 ,  ZNF416 ,  ...

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

    • DEPDC4 ,  ZFAND6 ,  SLC39A5 ,  SMAD4 ,  PIP4K2C ,  ...

  • 46 genes correlated to 'DISTANT.METASTASIS'.

    • IL10RB ,  JOSD2 ,  ATP2B2 ,  NHEDC1 ,  GOLGA1 ,  ...

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

    • C1ORF91 ,  KIAA1841 ,  TMEM33 ,  RG9MTD1 ,  LDLRAP1 ,  ...

  • 29 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • TCTN2 ,  HIST1H4C ,  UGT2B4 ,  ART4 ,  IL10RB ,  ...

  • No genes correlated to 'PATHOLOGY.T', 'PATHOLOGY.N', 'TUMOR.STAGE', 'NUMBERPACKYEARSSMOKED', 'TOBACCOSMOKINGHISTORYINDICATOR', 'YEAROFTOBACCOSMOKINGONSET', and 'NUMBER.OF.LYMPH.NODES'.

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=21 shorter survival N=0 longer survival N=21
AGE Spearman correlation test N=6 older N=6 younger N=0
PRIMARY SITE OF DISEASE ANOVA test N=5145        
GENDER t test N=332 male N=66 female N=266
HISTOLOGICAL TYPE ANOVA test N=3669        
PATHOLOGY T Spearman correlation test   N=0        
PATHOLOGY N Spearman correlation test   N=0        
TUMOR STAGE Spearman correlation test   N=0        
RADIATIONS RADIATION REGIMENINDICATION t test N=19 yes N=6 no N=13
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
TOBACCOSMOKINGHISTORYINDICATOR ANOVA test   N=0        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
DISTANT METASTASIS ANOVA test N=46        
LYMPH NODE METASTASIS ANOVA test N=51        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE ANOVA test N=29        
Clinical variable #1: 'Time to Death'

21 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0.1-223.4 (median=29.1)
  censored N = 194
  death N = 40
     
  Significant markers N = 21
  associated with shorter survival 0
  associated with longer survival 21
List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
LGALS4 0 1.372e-08 0.00021 0.269
ALG3 0 8.947e-08 0.0014 0.263
TEX101 0 8.948e-08 0.0014 0.32
VIL1 0.01 1.447e-07 0.0022 0.337
PPY2 0 1.611e-07 0.0025 0.342
APOC2 0.01 1.989e-07 0.0031 0.341
TNNT2 0 2.96e-07 0.0046 0.335
PTGDS 0 4.373e-07 0.0068 0.342
ADCK5 0 4.438e-07 0.0069 0.331
PTP4A3 0 4.442e-07 0.0069 0.338

Figure S1.  Get High-res Image As an example, this figure shows the association of LGALS4 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.37e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

6 genes related to 'AGE'.

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

AGE Mean (SD) 56.59 (13)
  Significant markers N = 6
  pos. correlated 6
  neg. correlated 0
List of 6 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 6 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
FAM123C 0.33 2.11e-07 0.00328
C7ORF13 0.3178 6.151e-07 0.00955
KIF15 0.315 7.841e-07 0.0122
TSPYL5 0.3113 1.067e-06 0.0166
BOC 0.3111 1.089e-06 0.0169
HNRNPC 0.3012 2.707e-06 0.042

Figure S2.  Get High-res Image As an example, this figure shows the association of FAM123C to 'AGE'. P value = 2.11e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

5145 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S5.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  BREAST 214
  COLON 1
  KIDNEY 2
  LUNG 20
  RECTUM 1
     
  Significant markers N = 5145
List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

ANOVA_P Q
ZNF416 1.01e-243 1.57e-239
BBS10 1.016e-224 1.58e-220
AGK 1.598e-223 2.48e-219
SYNGR1 1.037e-214 1.61e-210
HERPUD2 3.057e-209 4.74e-205
C20ORF194 1.437e-195 2.23e-191
PARD6G 5.208e-188 8.08e-184
RAB6B 1.442e-165 2.24e-161
MEIS3 5.212e-161 8.09e-157
RDX 8.948e-156 1.39e-151

Figure S3.  Get High-res Image As an example, this figure shows the association of ZNF416 to 'PRIMARY.SITE.OF.DISEASE'. P value = 1.01e-243 with ANOVA analysis.

Clinical variable #4: 'GENDER'

332 genes related to 'GENDER'.

Table S7.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 222
  MALE 16
     
  Significant markers N = 332
  Higher in MALE 66
  Higher in FEMALE 266
List of top 10 genes differentially expressed by 'GENDER'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
CDKL2 -16.25 2.559e-40 3.97e-36 0.8705
ZNF295 -13.25 5.311e-28 8.24e-24 0.8756
UTP14C 18.1 3.502e-26 5.44e-22 0.9428
GLIPR1L1 -10.29 1.166e-20 1.81e-16 0.877
TBC1D24 11.6 5.696e-20 8.84e-16 0.8694
SLC35E2 10.08 7.628e-20 1.18e-15 0.6765
LRIG3 -9.83 2.76e-19 4.28e-15 0.8218
IRF9 11.24 4.911e-19 7.62e-15 0.8156
TMED3 10.44 1.72e-18 2.67e-14 0.7897
BAT2 10.82 2.581e-18 4e-14 0.8528

Figure S4.  Get High-res Image As an example, this figure shows the association of CDKL2 to 'GENDER'. P value = 2.56e-40 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

3669 genes related to 'HISTOLOGICAL.TYPE'.

Table S9.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 1
  INFILTRATING DUCTAL CARCINOMA 35
  INFILTRATING LOBULAR CARCINOMA 5
  KIDNEY CLEAR CELL RENAL CARCINOMA 2
  LUNG BASALOID SQUAMOUS CELL CARCINOMA 2
  LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 18
  MIXED HISTOLOGY (PLEASE SPECIFY) 3
  OTHER SPECIFY 3
  RECTAL ADENOCARCINOMA 1
     
  Significant markers N = 3669
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

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

ANOVA_P Q
ZNF419 2.022e-110 3.14e-106
EPM2AIP1 1.18e-98 1.83e-94
MED12L 3.038e-97 4.71e-93
BBS10 1.237e-93 1.92e-89
ZNF416 2.196e-89 3.41e-85
C2ORF52 5.712e-89 8.86e-85
C6ORF129 2.893e-88 4.49e-84
AGK 5.105e-88 7.92e-84
HERPUD2 3.7e-84 5.74e-80
CRH 3.238e-77 5.02e-73

Figure S5.  Get High-res Image As an example, this figure shows the association of ZNF419 to 'HISTOLOGICAL.TYPE'. P value = 2.02e-110 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 1.96 (0.86)
  N
  T1 7
  T2 13
  T3 2
  T4 2
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S12.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.5 (0.67)
  N
  N0 13
  N1 7
  N2 2
     
  Significant markers N = 0
Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S13.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 1.79 (0.88)
  N
  Stage 1 11
  Stage 2 8
  Stage 3 4
  Stage 4 1
     
  Significant markers N = 0
Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S14.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 79
  YES 159
     
  Significant markers N = 19
  Higher in YES 6
  Higher in NO 13
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
DEPDC4 -5.99 1.358e-08 0.000211 0.7293
ZFAND6 -5.99 1.44e-08 0.000223 0.746
SLC39A5 -5.4 1.79e-07 0.00278 0.6896
SMAD4 -5.4 2.379e-07 0.00369 0.7004
PIP4K2C -5.34 2.914e-07 0.00452 0.7163
BNIP2 -5.32 3.194e-07 0.00496 0.6945
C18ORF8 -5.23 5.995e-07 0.0093 0.7098
SBK1 -5.16 6.828e-07 0.0106 0.6853
CDC27 -5.11 9.06e-07 0.0141 0.6959
LCAT -5 1.247e-06 0.0193 0.6848

Figure S6.  Get High-res Image As an example, this figure shows the association of DEPDC4 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.36e-08 with T-test analysis.

Clinical variable #10: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S16.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 54.79 (42)
  Significant markers N = 0
Clinical variable #11: 'TOBACCOSMOKINGHISTORYINDICATOR'

No gene related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

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

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 7
  CURRENT REFORMED SMOKER FOR > 15 YEARS 6
  CURRENT SMOKER 7
     
  Significant markers N = 0
Clinical variable #12: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1956.38 (6.9)
  Significant markers N = 0
Clinical variable #13: 'DISTANT.METASTASIS'

46 genes related to 'DISTANT.METASTASIS'.

Table S19.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  CM0 (I+) 1
  M0 160
  M1 2
  MX 5
     
  Significant markers N = 46
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
IL10RB 1.533e-20 2.38e-16
JOSD2 5.81e-19 9.02e-15
ATP2B2 3.268e-12 5.07e-08
NHEDC1 1.316e-11 2.04e-07
GOLGA1 1.828e-11 2.84e-07
MRPS12 2.209e-11 3.43e-07
HUNK 2.705e-10 4.2e-06
RBM23 7.483e-10 1.16e-05
TINF2 2.463e-09 3.82e-05
NDEL1 9.759e-09 0.000151

Figure S7.  Get High-res Image As an example, this figure shows the association of IL10RB to 'DISTANT.METASTASIS'. P value = 1.53e-20 with ANOVA analysis.

Clinical variable #14: 'LYMPH.NODE.METASTASIS'

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

Table S21.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 32
  N0 (I+) 5
  N0 (I-) 32
  N1 18
  N1A 28
  N1B 10
  N1C 2
  N1MI 4
  N2 15
  N2A 14
  N3 1
  N3A 5
  NX 2
     
  Significant markers N = 51
List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
C1ORF91 1.987e-23 3.08e-19
KIAA1841 1.077e-19 1.67e-15
TMEM33 1.594e-11 2.47e-07
RG9MTD1 2.155e-11 3.34e-07
LDLRAP1 2.725e-11 4.23e-07
MKRN2 3.855e-11 5.98e-07
TRAPPC2L 1.672e-10 2.59e-06
CLYBL 1.185e-09 1.84e-05
NUP214 1.888e-09 2.93e-05
AP3D1 1.009e-08 0.000157

Figure S8.  Get High-res Image As an example, this figure shows the association of C1ORF91 to 'LYMPH.NODE.METASTASIS'. P value = 1.99e-23 with ANOVA analysis.

Clinical variable #15: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S23.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.09 (3.4)
  Significant markers N = 0
Clinical variable #16: 'NEOPLASM.DISEASESTAGE'

29 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S24.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 15
  STAGE IA 12
  STAGE IB 1
  STAGE IIA 53
  STAGE IIB 36
  STAGE IIIA 38
  STAGE IIIB 3
  STAGE IIIC 5
  STAGE IV 2
  STAGE X 3
     
  Significant markers N = 29
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S25.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
TCTN2 5.469e-31 8.49e-27
HIST1H4C 6.368e-28 9.88e-24
UGT2B4 1.085e-19 1.68e-15
ART4 2.216e-17 3.44e-13
IL10RB 2.508e-16 3.89e-12
JOSD2 8.144e-15 1.26e-10
NR0B2 2.747e-12 4.26e-08
RNF25 4.209e-10 6.53e-06
ZNF619 6.584e-10 1.02e-05
ZNF230 9.591e-10 1.49e-05

Figure S9.  Get High-res Image As an example, this figure shows the association of TCTN2 to 'NEOPLASM.DISEASESTAGE'. P value = 5.47e-31 with ANOVA analysis.

Methods & Data
Input

  • Expresson data file = PANCAN12-TP.meth.for_correlation.filtered_data.txt

  • Clinical data file = PANCAN12-TP.clin.merged.picked.txt

  • Number of patients = 238

  • Number of genes = 15521

  • Number of clinical features = 16

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

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] 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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