Correlation between gene methylation status and clinical features
Colon Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C12V2D4T
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/C12V2D4T
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 19969 genes and 10 clinical features across 255 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 3 genes correlated to 'AGE'.

    • USP35 ,  GDNF ,  TAC1

  • 8 genes correlated to 'GENDER'.

    • GPX1 ,  KIF4B ,  POLDIP3 ,  RNU12 ,  PAFAH1B2 ,  ...

  • 3 genes correlated to 'HISTOLOGICAL.TYPE'.

    • ZNF18 ,  TMEM64 ,  ZNF519

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

    • SUCLG2 ,  SLCO4C1 ,  ZNF665 ,  RRN3P2 ,  OXNAD1 ,  ...

  • 287 genes correlated to 'DISTANT.METASTASIS'.

    • FAM86B2 ,  KCNK4 ,  DMKN ,  MTUS2 ,  PDSS2 ,  ...

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

    • LLPH ,  ATP5G3 ,  PPP2R1A ,  ASTN2 ,  TRIM32 ,  ...

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

    • TMEM115 ,  ZNF140 ,  CAB39L ,  SETDB2 ,  SEC16A ,  ...

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

    • CASP1__1 ,  UBE2L6 ,  IL12RB1 ,  APOL1

  • 968 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • PPDPF ,  USP21 ,  FAM119A ,  ORC3L__1 ,  RARS2__1 ,  ...

  • No genes correlated to 'Time to Death'

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
GENDER t test N=8 male N=1 female N=7
HISTOLOGICAL TYPE t test N=3 colon mucinous adenocarcinoma N=0 colon adenocarcinoma N=3
RADIATIONS RADIATION REGIMENINDICATION t test N=325 yes N=269 no N=56
DISTANT METASTASIS ANOVA test N=287        
LYMPH NODE METASTASIS ANOVA test N=16        
COMPLETENESS OF RESECTION ANOVA test N=98        
NUMBER OF LYMPH NODES Spearman correlation test N=4 higher number.of.lymph.nodes N=4 lower number.of.lymph.nodes N=0
NEOPLASM DISEASESTAGE ANOVA test N=968        
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) 0.1-135.5 (median=7.5)
  censored N = 200
  death N = 36
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

3 genes related to 'AGE'.

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

AGE Mean (SD) 65.29 (13)
  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
USP35 0.3757 7.18e-10 1.43e-05
GDNF 0.326 1.197e-07 0.00239
TAC1 0.3072 6.573e-07 0.0131

Figure S1.  Get High-res Image As an example, this figure shows the association of USP35 to 'AGE'. P value = 7.18e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

8 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 113
  MALE 140
     
  Significant markers N = 8
  Higher in MALE 1
  Higher in FEMALE 7
List of 8 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of 8 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
GPX1 -10.23 1.595e-20 3.19e-16 0.8286
KIF4B -10.15 2.491e-20 4.97e-16 0.8154
POLDIP3 -9.16 3.678e-17 7.34e-13 0.8015
RNU12 -9.16 3.678e-17 7.34e-13 0.8015
PAFAH1B2 -6.64 1.948e-10 3.89e-06 0.7263
UBAP2 -6.19 2.485e-09 4.96e-05 0.7023
RIMBP3 5.46 1.159e-07 0.00231 0.6839
ZNF839 -5.06 8.278e-07 0.0165 0.6761

Figure S2.  Get High-res Image As an example, this figure shows the association of GPX1 to 'GENDER'. P value = 1.6e-20 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

3 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 223
  COLON MUCINOUS ADENOCARCINOMA 30
     
  Significant markers N = 3
  Higher in COLON MUCINOUS ADENOCARCINOMA 0
  Higher in COLON ADENOCARCINOMA 3
List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') ttestP Q AUC
ZNF18 -5.29 1.031e-06 0.0206 0.6702
TMEM64 -5 1.148e-06 0.0229 0.5831
ZNF519 -5.26 1.921e-06 0.0384 0.7143

Figure S3.  Get High-res Image As an example, this figure shows the association of ZNF18 to 'HISTOLOGICAL.TYPE'. P value = 1.03e-06 with T-test analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 3
  YES 252
     
  Significant markers N = 325
  Higher in YES 269
  Higher in NO 56
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
SUCLG2 -19.22 1.067e-49 2.13e-45 0.9048
SLCO4C1 17.73 9.633e-46 1.92e-41 0.7381
ZNF665 15.32 6.166e-38 1.23e-33 0.9048
RRN3P2 15.02 7.254e-37 1.45e-32 0.7632
OXNAD1 -16.26 1.531e-36 3.06e-32 0.8519
CPNE8 14.68 1.338e-35 2.67e-31 0.7304
CYP2U1 14.81 4.503e-35 8.99e-31 0.7884
INHA__1 14.93 1.868e-33 3.73e-29 0.8042
OBSL1__1 14.93 1.868e-33 3.73e-29 0.8042
BASP1 14.06 5.296e-33 1.06e-28 0.7407

Figure S4.  Get High-res Image As an example, this figure shows the association of SUCLG2 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.07e-49 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

287 genes related to 'DISTANT.METASTASIS'.

Table S10.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 179
  M1 26
  M1A 6
  M1B 1
  MX 36
     
  Significant markers N = 287
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

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

ANOVA_P Q
FAM86B2 1.917e-162 3.83e-158
KCNK4 7.213e-70 1.44e-65
DMKN 1.362e-68 2.72e-64
MTUS2 4.456e-59 8.9e-55
PDSS2 5.1e-53 1.02e-48
LYSMD2 6.653e-50 1.33e-45
TMOD2 6.653e-50 1.33e-45
ETV5 1.37e-47 2.74e-43
TSPAN18 1.14e-43 2.28e-39
GBP5 7.066e-42 1.41e-37

Figure S5.  Get High-res Image As an example, this figure shows the association of FAM86B2 to 'DISTANT.METASTASIS'. P value = 1.92e-162 with ANOVA analysis.

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

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

Table S12.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 151
  N1 38
  N1A 13
  N1B 11
  N1C 2
  N2 25
  N2A 3
  N2B 9
  NX 1
     
  Significant markers N = 16
List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

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

ANOVA_P Q
LLPH 2.111e-147 4.21e-143
ATP5G3 6.114e-20 1.22e-15
PPP2R1A 1.192e-16 2.38e-12
ASTN2 1.887e-16 3.77e-12
TRIM32 1.887e-16 3.77e-12
C11ORF51 1.091e-13 2.18e-09
GLCE 3.5e-09 6.99e-05
MIR548H4__3 3.5e-09 6.99e-05
GARNL3 2.074e-08 0.000414
HSP90B1 6.108e-07 0.0122

Figure S6.  Get High-res Image As an example, this figure shows the association of LLPH to 'LYMPH.NODE.METASTASIS'. P value = 2.11e-147 with ANOVA analysis.

Clinical variable #8: 'COMPLETENESS.OF.RESECTION'

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

Table S14.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 155
  R1 2
  R2 4
  RX 21
     
  Significant markers N = 98
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
TMEM115 2.015e-22 4.02e-18
ZNF140 7.028e-17 1.4e-12
CAB39L 1.357e-15 2.71e-11
SETDB2 1.357e-15 2.71e-11
SEC16A 2.245e-13 4.48e-09
CCDC146__1 1.6e-12 3.19e-08
LIG4__1 2.463e-12 4.92e-08
FAM185A 8.167e-12 1.63e-07
C17ORF71 1.611e-11 3.22e-07
HSD17B11 1.886e-11 3.76e-07

Figure S7.  Get High-res Image As an example, this figure shows the association of TMEM115 to 'COMPLETENESS.OF.RESECTION'. P value = 2.01e-22 with ANOVA analysis.

Clinical variable #9: 'NUMBER.OF.LYMPH.NODES'

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

Table S16.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.9 (4.5)
  Significant markers N = 4
  pos. correlated 4
  neg. correlated 0
List of 4 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S17.  Get Full Table List of 4 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
CASP1__1 0.3863 1.33e-09 2.66e-05
UBE2L6 0.3723 5.685e-09 0.000114
IL12RB1 0.321 6.536e-07 0.0131
APOL1 0.3183 8.236e-07 0.0164

Figure S8.  Get High-res Image As an example, this figure shows the association of CASP1__1 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.33e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

968 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S18.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 37
  STAGE IA 1
  STAGE II 19
  STAGE IIA 75
  STAGE IIB 4
  STAGE IIC 1
  STAGE III 8
  STAGE IIIA 10
  STAGE IIIB 35
  STAGE IIIC 18
  STAGE IV 18
  STAGE IVA 15
  STAGE IVB 1
     
  Significant markers N = 968
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S19.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
PPDPF 1.788e-209 3.57e-205
USP21 1.597e-202 3.19e-198
FAM119A 6.537e-200 1.31e-195
ORC3L__1 1.385e-193 2.76e-189
RARS2__1 1.385e-193 2.76e-189
ADNP 9.925e-157 1.98e-152
L3MBTL2 6.285e-153 1.25e-148
FBXW2 1.445e-152 2.88e-148
LOC402377 1.445e-152 2.88e-148
FAM86B2 9.029e-151 1.8e-146

Figure S9.  Get High-res Image As an example, this figure shows the association of PPDPF to 'NEOPLASM.DISEASESTAGE'. P value = 1.79e-209 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 255

  • Number of genes = 19969

  • Number of clinical features = 10

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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