Correlation between gene methylation status and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C10P0XM6
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/C10P0XM6
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 19985 genes and 10 clinical features across 665 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

  • 440 genes correlated to 'AGE'.

    • KIAA1143 ,  KIF15 ,  C1ORF103 ,  LGALS8 ,  MEX3C ,  ...

  • 41 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • WDR74 ,  RHBDL3 ,  FASTKD3 ,  MTRR__1 ,  SIL1 ,  ...

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

    • TCP11L1 ,  ADA

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

    • ABCE1 ,  ANAPC10 ,  RHBDL3 ,  FASTKD3 ,  MTRR__1 ,  ...

  • 191 genes correlated to 'GENDER'.

    • ALDOC ,  CRIP1 ,  NMNAT3 ,  DNAJC15 ,  EML1 ,  ...

  • 1201 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CLUAP1 ,  RNF25 ,  STK36 ,  PRKAR2A ,  FAR1 ,  ...

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

    • PRIM1 ,  METAP2 ,  MAEA ,  HMG20B ,  ZNF639 ,  ...

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • TCP11L1

  • No genes correlated to 'Time to Death', and 'PATHOLOGY.T.STAGE'.

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=440 older N=343 younger N=97
NEOPLASM DISEASESTAGE ANOVA test N=41        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test N=2 higher stage N=2 lower stage N=0
PATHOLOGY M STAGE ANOVA test N=68        
GENDER t test N=191 male N=54 female N=137
HISTOLOGICAL TYPE ANOVA test N=1201        
RADIATIONS RADIATION REGIMENINDICATION t test N=116 yes N=47 no N=69
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=1 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) 0-234.3 (median=21.4)
  censored N = 585
  death N = 74
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

440 genes related to 'AGE'.

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

AGE Mean (SD) 58.06 (13)
  Significant markers N = 440
  pos. correlated 343
  neg. correlated 97
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
KIAA1143 0.3293 5.277e-18 1.05e-13
KIF15 0.3293 5.277e-18 1.05e-13
C1ORF103 0.3106 4.285e-16 8.56e-12
LGALS8 -0.3097 5.259e-16 1.05e-11
MEX3C 0.2998 4.805e-15 9.6e-11
C20ORF199 0.2972 8.42e-15 1.68e-10
SNORD12 0.2972 8.42e-15 1.68e-10
C9ORF69 0.2856 9.625e-14 1.92e-09
DNMT3A 0.2854 1.001e-13 2e-09
CACNA2D1 0.2839 1.362e-13 2.72e-09

Figure S1.  Get High-res Image As an example, this figure shows the association of KIAA1143 to 'AGE'. P value = 5.28e-18 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

41 genes related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 49
  STAGE IA 55
  STAGE IB 5
  STAGE II 8
  STAGE IIA 212
  STAGE IIB 155
  STAGE III 2
  STAGE IIIA 107
  STAGE IIIB 17
  STAGE IIIC 43
  STAGE IV 6
  STAGE X 5
     
  Significant markers N = 41
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
WDR74 1.747e-20 3.49e-16
RHBDL3 2.37e-20 4.74e-16
FASTKD3 7.679e-20 1.53e-15
MTRR__1 7.679e-20 1.53e-15
SIL1 7.436e-19 1.49e-14
MMAB 1.421e-17 2.84e-13
MVK 1.421e-17 2.84e-13
ATP5J 8.599e-17 1.72e-12
GABPA 8.599e-17 1.72e-12
TTC32 4.644e-14 9.28e-10

Figure S2.  Get High-res Image As an example, this figure shows the association of WDR74 to 'NEOPLASM.DISEASESTAGE'. P value = 1.75e-20 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) 1.93 (0.71)
  N
  1 174
  2 383
  3 86
  4 20
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.82 (0.91)
  N
  0 292
  1 235
  2 84
  3 46
     
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of 2 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.2024 1.677e-07 0.00335
ADA 0.1915 7.582e-07 0.0152

Figure S3.  Get High-res Image As an example, this figure shows the association of TCP11L1 to 'PATHOLOGY.N.STAGE'. P value = 1.68e-07 with Spearman correlation analysis.

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

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

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

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 1
  M0 552
  M1 6
  MX 106
     
  Significant markers N = 68
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'

ANOVA_P Q
ABCE1 4.148e-108 8.29e-104
ANAPC10 4.148e-108 8.29e-104
RHBDL3 1.615e-25 3.23e-21
FASTKD3 2.477e-25 4.95e-21
MTRR__1 2.477e-25 4.95e-21
MMAB 1.28e-22 2.56e-18
MVK 1.28e-22 2.56e-18
NHEDC1 1.348e-12 2.69e-08
SAG 2.353e-12 4.7e-08
TSTD1 1.104e-10 2.2e-06

Figure S4.  Get High-res Image As an example, this figure shows the association of ABCE1 to 'PATHOLOGY.M.STAGE'. P value = 4.15e-108 with ANOVA analysis.

Clinical variable #7: 'GENDER'

191 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 658
  MALE 7
     
  Significant markers N = 191
  Higher in MALE 54
  Higher in FEMALE 137
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
ALDOC -30.35 2.529e-72 5.05e-68 0.962
CRIP1 -20.11 1.688e-70 3.37e-66 0.8689
NMNAT3 -14.96 3.999e-43 7.99e-39 0.693
DNAJC15 -14.91 5.895e-42 1.18e-37 0.7093
EML1 -13.13 6.565e-35 1.31e-30 0.6235
ADCY5 14.21 1.343e-31 2.68e-27 0.7312
RND2 -14.18 1.848e-31 3.69e-27 0.7579
SLCO4C1 -12.8 8.868e-30 1.77e-25 0.7178
LOC400043 -13.5 5.202e-29 1.04e-24 0.5597
ACADS -11.73 1.097e-28 2.19e-24 0.612

Figure S5.  Get High-res Image As an example, this figure shows the association of ALDOC to 'GENDER'. P value = 2.53e-72 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

1201 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 456
  INFILTRATING LOBULAR CARCINOMA 134
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 24
  MUCINOUS CARCINOMA 12
  OTHER SPECIFY 32
     
  Significant markers N = 1201
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
CLUAP1 0 0
RNF25 1.962e-271 3.92e-267
STK36 1.962e-271 3.92e-267
PRKAR2A 3.391e-213 6.78e-209
FAR1 5.401e-100 1.08e-95
RNF26 2.007e-85 4.01e-81
AP1M2 3.802e-81 7.6e-77
CYB5D1__1 1.596e-73 3.19e-69
LSMD1__1 1.596e-73 3.19e-69
MPDU1 1.946e-58 3.89e-54

Figure S6.  Get High-res Image As an example, this figure shows the association of CLUAP1 to 'HISTOLOGICAL.TYPE'. P value = 0 with ANOVA analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 215
  YES 450
     
  Significant markers N = 116
  Higher in YES 47
  Higher in NO 69
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
PRIM1 7.8 2.499e-14 4.99e-10 0.6547
METAP2 7.36 6.498e-13 1.3e-08 0.6625
MAEA -7.18 2.192e-12 4.38e-08 0.6474
HMG20B -7.13 3.126e-12 6.25e-08 0.648
ZNF639 6.96 8.941e-12 1.79e-07 0.6478
UHRF1BP1L 6.92 1.261e-11 2.52e-07 0.6578
C16ORF58 -6.9 1.807e-11 3.61e-07 0.6577
TSTD1 -6.52 1.689e-10 3.37e-06 0.6318
USF1 -6.52 1.689e-10 3.37e-06 0.6318
SRRM5 -6.48 2.099e-10 4.19e-06 0.6352

Figure S7.  Get High-res Image As an example, this figure shows the association of PRIM1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.5e-14 with T-test analysis.

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

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S17.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.58 (4.8)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S18.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.2267 1.392e-08 0.000278

Figure S8.  Get High-res Image As an example, this figure shows the association of TCP11L1 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.39e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

  • Expresson data file = BRCA-TP.meth.by_min_clin_corr.data.txt

  • Clinical data file = BRCA-TP.merged_data.txt

  • Number of patients = 665

  • Number of genes = 19985

  • 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

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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