Correlation between gene methylation status and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C18G8K2B
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C18G8K2B
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features. The input file "BRCA-TP.meth.by_min_clin_corr.data.txt" is generated in the pipeline Methylation_Preprocess in stddata run.

Summary

Testing the association between 17028 genes and 12 clinical features across 782 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • QPRT ,  PSCA ,  IL17REL ,  ZNF704 ,  TMEM45B ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • KIF15 ,  LGALS8 ,  EGR2 ,  MEX3C ,  CACNA2D1 ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • FAM98C ,  RFFL ,  CLP1 ,  PSPN ,  UBE2Z ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • MYOC ,  PCDHGC4 ,  SLC13A2 ,  C1QL3 ,  ACCN1 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • TCP11L1 ,  ADA ,  KIAA0182 ,  SPATA12 ,  RFFL ,  ...

  • 30 genes correlated to 'PATHOLOGY_M_STAGE'.

    • PRELID1 ,  RFX1 ,  CHD8 ,  DDTL ,  FLJ40292 ,  ...

  • 30 genes correlated to 'GENDER'.

    • WNT7B ,  ARSG ,  STC1 ,  LGALS1 ,  PRRT3 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • SCD ,  PRCD ,  MCAM ,  FADS1 ,  PELO ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • TCP11L1 ,  SEPT8 ,  PARP1 ,  CCDC80 ,  KIAA0182 ,  ...

  • 30 genes correlated to 'RACE'.

    • DHRS7 ,  PPP1R15B ,  ISCA1 ,  INTS12 ,  ZNF639 ,  ...

  • 30 genes correlated to 'ETHNICITY'.

    • LRRC66 ,  WDFY3 ,  SNORD1C ,  SCFD2 ,  ANKRD13C ,  ...

  • No genes correlated to 'RADIATION_THERAPY'

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 P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant genes Associated with                 Associated with
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=27 younger N=3
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=21 lower stage N=9
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_M_STAGE Wilcoxon test N=30 class1 N=30 class0 N=0
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=15 lower number_of_lymph_nodes N=15
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test N=30 not hispanic or latino N=30 hispanic or latino N=0
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

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

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-282.9 (median=27.5)
  censored N = 678
  death N = 103
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
QPRT 1.01e-07 0.0017 0.334
PSCA 5.72e-07 0.0049 0.403
IL17REL 2.26e-06 0.013 0.369
ZNF704 1.94e-05 0.083 0.452
TMEM45B 4.19e-05 0.12 0.401
RSPH3 4.23e-05 0.12 0.418
CHL1 8.97e-05 0.22 0.638
CHST14 0.000103 0.22 0.418
SYT15 0.000127 0.24 0.404
YTHDF3 0.00015 0.25 0.42
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 58.19 (13)
  Significant markers N = 30
  pos. correlated 27
  neg. correlated 3
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

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

SpearmanCorr corrP Q
KIF15 0.331 4.071e-21 6.93e-17
LGALS8 -0.3002 1.757e-17 1.5e-13
EGR2 0.2909 1.816e-16 1.03e-12
MEX3C 0.2824 1.446e-15 6.16e-12
CACNA2D1 0.2793 3.028e-15 1.03e-11
BMPER 0.2721 1.609e-14 4.57e-11
C20ORF199 0.2673 4.791e-14 1.17e-10
TNFSF11 0.2657 6.835e-14 1.32e-10
DNMT3A 0.2656 6.956e-14 1.32e-10
FASN 0.2637 1.073e-13 1.73e-10
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE Labels N
  STAGE I 60
  STAGE IA 61
  STAGE IB 5
  STAGE II 6
  STAGE IIA 244
  STAGE IIB 187
  STAGE III 2
  STAGE IIIA 126
  STAGE IIIB 18
  STAGE IIIC 53
  STAGE IV 11
  STAGE X 5
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
FAM98C 5.681e-06 0.0967
RFFL 2.132e-05 0.157
CLP1 4.176e-05 0.157
PSPN 5.708e-05 0.157
UBE2Z 5.727e-05 0.157
FBXO22OS 7.6e-05 0.157
GLYATL1 8.891e-05 0.157
C15ORF63 9.258e-05 0.157
CYFIP1 0.0001075 0.157
C9ORF30 0.0001097 0.157
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 1.95 (0.72)
  N
  T1 199
  T2 447
  T3 109
  T4 24
     
  Significant markers N = 30
  pos. correlated 21
  neg. correlated 9
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
MYOC -0.1534 1.713e-05 0.0891
PCDHGC4 0.1496 2.754e-05 0.0891
SLC13A2 -0.1489 3.015e-05 0.0891
C1QL3 0.148 3.381e-05 0.0891
ACCN1 0.1465 4.045e-05 0.0891
FAM5C 0.1461 4.235e-05 0.0891
ZNF154 0.1439 5.532e-05 0.0891
STC2 0.1438 5.591e-05 0.0891
SFRS14 -0.1438 5.646e-05 0.0891
ALX3 0.1431 6.133e-05 0.0891
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.82 (0.92)
  N
  N0 349
  N1 269
  N2 95
  N3 57
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.1707 1.895e-06 0.0155
ADA 0.1687 2.492e-06 0.0155
KIAA0182 -0.1681 2.737e-06 0.0155
SPATA12 0.1647 4.474e-06 0.019
RFFL 0.1574 1.141e-05 0.0327
SEPT8 -0.1566 1.266e-05 0.0327
LOC100286844 -0.1562 1.343e-05 0.0327
PDE9A 0.1549 1.583e-05 0.0337
PARP1 0.1539 1.782e-05 0.0337
SCAPER -0.1515 2.442e-05 0.0393
Clinical variable #6: 'PATHOLOGY_M_STAGE'

30 genes related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 609
  class1 13
     
  Significant markers N = 30
  Higher in class1 30
  Higher in class0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

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

W(pos if higher in 'class1') wilcoxontestP Q AUC
PRELID1 1314 3.722e-05 0.295 0.834
RFX1 1408 6.965e-05 0.295 0.8222
CHD8 6444 0.0001062 0.295 0.8139
DDTL 1533 0.0001553 0.295 0.8064
FLJ40292 1560 0.0001837 0.295 0.803
KDM3B 6335 0.0001975 0.295 0.8015
FAM160B1 6331 0.0002157 0.295 0.7997
NUP50 6321 0.0002294 0.295 0.7984
CHRNA10 1654 0.0003259 0.295 0.7911
SNW1 6258 0.0003358 0.295 0.7905
Clinical variable #7: 'GENDER'

30 genes related to 'GENDER'.

Table S13.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 773
  MALE 9
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
WNT7B 525 1.171e-05 0.103 0.9245
ARSG 652 2.736e-05 0.103 0.9063
STC1 691 3.633e-05 0.103 0.9
LGALS1 722 4.304e-05 0.103 0.8962
PRRT3 726 4.416e-05 0.103 0.8956
SLC16A12 741 4.889e-05 0.103 0.8934
C15ORF62 6164 6.744e-05 0.103 0.886
SLC25A10 805 7.268e-05 0.103 0.8843
FLJ90757 813 7.639e-05 0.103 0.8831
BCAS1 822 8.077e-05 0.103 0.8818
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

Table S15.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 316
  YES 412
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 511
  INFILTRATING LOBULAR CARCINOMA 179
  MEDULLARY CARCINOMA 6
  METAPLASTIC CARCINOMA 9
  MIXED HISTOLOGY (PLEASE SPECIFY) 26
  MUCINOUS CARCINOMA 15
  OTHER, SPECIFY 34
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
SCD 2.958e-22 5.04e-18
PRCD 5.689e-21 3.48e-17
MCAM 6.133e-21 3.48e-17
FADS1 9.984e-21 4.25e-17
PELO 7.905e-20 2.69e-16
PABPC4 2.798e-19 7.94e-16
PRPF40A 1.025e-18 2.44e-15
OSGIN2 1.149e-18 2.44e-15
PCGF6 1.301e-18 2.46e-15
ATP2C2 1.531e-18 2.61e-15
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 genes 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 (4.9)
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S19.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
TCP11L1 0.1966 1.12e-07 0.00191
SEPT8 -0.1701 4.652e-06 0.0396
PARP1 0.1634 1.102e-05 0.0396
CCDC80 -0.1615 1.396e-05 0.0396
KIAA0182 -0.1598 1.709e-05 0.0396
ABCC8 0.1596 1.765e-05 0.0396
ADA 0.1581 2.11e-05 0.0396
SCAPER -0.1575 2.27e-05 0.0396
IL21R 0.1565 2.555e-05 0.0396
ZNF521 0.1564 2.586e-05 0.0396
Clinical variable #11: 'RACE'

30 genes related to 'RACE'.

Table S20.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 38
  BLACK OR AFRICAN AMERICAN 160
  WHITE 568
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S21.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
DHRS7 6.257e-37 9.77e-33
PPP1R15B 1.147e-36 9.77e-33
ISCA1 2.208e-33 1.25e-29
INTS12 1.846e-32 7.86e-29
ZNF639 2.755e-31 9.38e-28
EIF2AK4 7.51e-30 2.13e-26
TOMM34 3.702e-28 9.01e-25
SCAMP5 8.581e-28 1.83e-24
KIAA0226 2.901e-27 5.49e-24
RHD 3.449e-27 5.87e-24
Clinical variable #12: 'ETHNICITY'

30 genes related to 'ETHNICITY'.

Table S22.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 38
  NOT HISPANIC OR LATINO 675
     
  Significant markers N = 30
  Higher in NOT HISPANIC OR LATINO 30
  Higher in HISPANIC OR LATINO 0
List of top 10 genes differentially expressed by 'ETHNICITY'

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 = 782

  • Number of genes = 17028

  • Number of clinical features = 12

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

Survival analysis

For survival clinical features, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[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)
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