Correlation between gene methylation status and clinical features
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 19941 genes and 10 clinical features across 641 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 4 genes correlated to 'Time to Death'.

    • CDC73 ,  MIR1278 ,  MTHFD1 ,  LOC728323

  • 391 genes correlated to 'AGE'.

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

  • 37 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • RHBDL3 ,  WDR74 ,  IDH3B ,  ATP5J ,  GABPA ,  ...

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

    • TCP11L1 ,  ARHGEF3__1 ,  SPATA12

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

    • RHBDL3 ,  MMAB ,  MVK ,  NHEDC1 ,  SAG ,  ...

  • 192 genes correlated to 'GENDER'.

    • ALDOC ,  CRIP1 ,  DNAJC15 ,  NMNAT3 ,  RAD51AP2 ,  ...

  • 1138 genes correlated to 'HISTOLOGICAL.TYPE'.

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

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

    • AGTPBP1 ,  TMEM194A ,  PRIM1 ,  C16ORF58 ,  TBCA ,  ...

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

    • TCP11L1

  • No genes correlated to '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=4 shorter survival N=2 longer survival N=2
AGE Spearman correlation test N=391 older N=322 younger N=69
NEOPLASM DISEASESTAGE ANOVA test N=37        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test N=3 higher stage N=3 lower stage N=0
PATHOLOGY M STAGE ANOVA test N=69        
GENDER t test N=192 male N=52 female N=140
HISTOLOGICAL TYPE ANOVA test N=1138        
RADIATIONS RADIATION REGIMENINDICATION t test N=144 yes N=74 no N=70
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'

4 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-234.2 (median=20.8)
  censored N = 545
  death N = 70
     
  Significant markers N = 4
  associated with shorter survival 2
  associated with longer survival 2
List of 4 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 4 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
CDC73 0 2.178e-07 0.0043 0.405
MIR1278 0 2.178e-07 0.0043 0.405
MTHFD1 420000001 1.253e-06 0.025 0.648
LOC728323 7401 1.371e-06 0.027 0.561

Figure S1.  Get High-res Image As an example, this figure shows the association of CDC73 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.18e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

391 genes related to 'AGE'.

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

AGE Mean (SD) 57.89 (13)
  Significant markers N = 391
  pos. correlated 322
  neg. correlated 69
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
KIAA1143 0.3285 1.597e-17 3.18e-13
KIF15 0.3285 1.597e-17 3.18e-13
C1ORF103 0.3238 4.875e-17 9.72e-13
LGALS8 -0.3022 6.092e-15 1.21e-10
MEX3C 0.2967 1.961e-14 3.91e-10
C20ORF199 0.293 4.249e-14 8.47e-10
SNORD12 0.293 4.249e-14 8.47e-10
CACNA2D1 0.2811 4.695e-13 9.36e-09
EGR2 0.2789 7.356e-13 1.47e-08
C10ORF35 0.2786 7.783e-13 1.55e-08

Figure S2.  Get High-res Image As an example, this figure shows the association of KIAA1143 to 'AGE'. P value = 1.6e-17 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

37 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 47
  STAGE IA 51
  STAGE IB 6
  STAGE II 8
  STAGE IIA 206
  STAGE IIB 148
  STAGE III 2
  STAGE IIIA 105
  STAGE IIIB 16
  STAGE IIIC 40
  STAGE IV 6
  STAGE X 5
     
  Significant markers N = 37
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
RHBDL3 9.388e-20 1.87e-15
WDR74 9.806e-20 1.96e-15
IDH3B 2.173e-17 4.33e-13
ATP5J 2.406e-17 4.8e-13
GABPA 2.406e-17 4.8e-13
MMAB 6.711e-17 1.34e-12
MVK 6.711e-17 1.34e-12
TMX4 1.614e-14 3.22e-10
TTC32 8.329e-14 1.66e-09
MED6 2.008e-13 4e-09

Figure S3.  Get High-res Image As an example, this figure shows the association of RHBDL3 to 'NEOPLASM.DISEASESTAGE'. P value = 9.39e-20 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

No gene related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.92 (0.72)
  N
  1 170
  2 366
  3 84
  4 19
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.83 (0.9)
  N
  0 280
  1 227
  2 84
  3 43
     
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S9.  Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.2128 6.344e-08 0.00127
ARHGEF3__1 0.1863 2.42e-06 0.0482
SPATA12 0.1863 2.42e-06 0.0482

Figure S4.  Get High-res Image As an example, this figure shows the association of TCP11L1 to 'PATHOLOGY.N.STAGE'. P value = 6.34e-08 with Spearman correlation analysis.

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

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

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 1
  M0 537
  M1 6
  MX 97
     
  Significant markers N = 69
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
RHBDL3 7.337e-25 1.46e-20
MMAB 7.32e-22 1.46e-17
MVK 7.32e-22 1.46e-17
NHEDC1 4.513e-20 9e-16
SAG 2.256e-12 4.5e-08
IP6K1__1 9.702e-12 1.93e-07
TSTD1 9.772e-12 1.95e-07
USF1 9.772e-12 1.95e-07
PACRGL 6.098e-10 1.22e-05
TRIM21 2.405e-09 4.79e-05

Figure S5.  Get High-res Image As an example, this figure shows the association of RHBDL3 to 'PATHOLOGY.M.STAGE'. P value = 7.34e-25 with ANOVA analysis.

Clinical variable #7: 'GENDER'

192 genes related to 'GENDER'.

Table S12.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 634
  MALE 7
     
  Significant markers N = 192
  Higher in MALE 52
  Higher in FEMALE 140
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
ALDOC -28.61 2.773e-114 5.53e-110 0.8598
CRIP1 -19.33 7.723e-66 1.54e-61 0.8689
DNAJC15 -14.76 2.732e-41 5.45e-37 0.7136
NMNAT3 -14.53 5.566e-41 1.11e-36 0.6902
RAD51AP2 -15.31 7.838e-40 1.56e-35 0.6814
EML1 -12.84 1.497e-33 2.98e-29 0.621
ADCY5 14.03 1.366e-31 2.72e-27 0.7323
RND2 -13.78 2.079e-30 4.14e-26 0.7587
RFC5 -16.25 8.358e-30 1.67e-25 0.7213
SLCO4C1 -12.57 3.653e-29 7.28e-25 0.7181

Figure S6.  Get High-res Image As an example, this figure shows the association of ALDOC to 'GENDER'. P value = 2.77e-114 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

1138 genes related to 'HISTOLOGICAL.TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 443
  INFILTRATING LOBULAR CARCINOMA 127
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 22
  MUCINOUS CARCINOMA 12
  OTHER SPECIFY 30
     
  Significant markers N = 1138
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
CLUAP1 0 0
RNF25 4.99e-263 9.95e-259
STK36 4.99e-263 9.95e-259
PRKAR2A 4.07e-206 8.11e-202
FAR1 5.576e-109 1.11e-104
RNF26 3.142e-82 6.26e-78
AP1M2 9.089e-79 1.81e-74
C9ORF45 1.251e-73 2.49e-69
CYB5D1__1 6.746e-71 1.34e-66
LSMD1__1 6.746e-71 1.34e-66

Figure S7.  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'

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

Table S16.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 166
  YES 475
     
  Significant markers N = 144
  Higher in YES 74
  Higher in NO 70
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
AGTPBP1 7.41 1.07e-12 2.13e-08 0.6741
TMEM194A 7.16 4.571e-12 9.12e-08 0.664
PRIM1 6.92 1.669e-11 3.33e-07 0.6613
C16ORF58 -6.75 7.473e-11 1.49e-06 0.6715
TBCA 6.55 1.867e-10 3.72e-06 0.6597
MAEA -6.5 2.596e-10 5.18e-06 0.6475
UMPS 6.32 7.811e-10 1.56e-05 0.6654
KIAA1429 6.24 1.51e-09 3.01e-05 0.6557
ASF1B 6.23 1.645e-09 3.28e-05 0.6574
TOMM34 -6.16 1.877e-09 3.74e-05 0.6388

Figure S8.  Get High-res Image As an example, this figure shows the association of AGTPBP1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.07e-12 with T-test analysis.

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

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

Table S18.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.61 (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 S19.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.2363 5.702e-09 0.000114

Figure S9.  Get High-res Image As an example, this figure shows the association of TCP11L1 to 'NUMBER.OF.LYMPH.NODES'. P value = 5.7e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

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

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

  • Number of patients = 641

  • Number of genes = 19941

  • 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.

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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