Colon/Rectal Adenocarcinoma: Correlation between gene methylation status and clinical features
Maintained by Juok Cho (Broad Institute)
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 20228 genes and 11 clinical features across 349 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 1 gene correlated to 'Time to Death'.

    • NR1H2

  • 40 genes correlated to 'AGE'.

    • FAM19A4 ,  DOK5 ,  TBX5 ,  WIT1 ,  PTPRT ,  ...

  • 2070 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

    • ELAVL2 ,  LPHN2 ,  AARS2 ,  MELK ,  L3MBTL2 ,  ...

  • 2 genes correlated to 'GENDER'.

    • KIF4B ,  UTP14C

  • 1150 genes correlated to 'HISTOLOGICAL.TYPE'.

    • SNORD98 ,  THOC7 ,  PMS2L4 ,  DHX33 ,  EXOSC4 ,  ...

  • 3 genes correlated to 'PATHOLOGY.N'.

    • SP140L ,  CD74 ,  ELF5

  • 167 genes correlated to 'PATHOLOGICSPREAD(M)'.

    • CLTCL1 ,  FAHD2B ,  POLR2J4 ,  FAM86B2 ,  UTRN ,  ...

  • 3 genes correlated to 'TUMOR.STAGE'.

    • SP140L ,  MLF1 ,  FGF20

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

    • RTDR1 ,  ZNF586 ,  C1ORF103 ,  VGLL3 ,  GBX1 ,  ...

  • No genes correlated to 'PATHOLOGY.T', and 'NEOADJUVANT.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 Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test N=1 shorter survival N=1 longer survival N=0
AGE Spearman correlation test N=40 older N=40 younger N=0
PRIMARY SITE OF DISEASE t test N=2070 rectum N=32 colon N=2038
GENDER t test N=2 male N=1 female N=1
HISTOLOGICAL TYPE ANOVA test N=1150        
PATHOLOGY T Spearman correlation test   N=0        
PATHOLOGY N Spearman correlation test N=3 higher pN N=2 lower pN N=1
PATHOLOGICSPREAD(M) ANOVA test N=167        
TUMOR STAGE Spearman correlation test N=3 higher stage N=1 lower stage N=2
RADIATIONS RADIATION REGIMENINDICATION t test N=165 yes N=163 no N=2
NEOADJUVANT THERAPY t test   N=0        
Clinical variable #1: 'Time to Death'

One 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)
  censored N = 280
  death N = 44
     
  Significant markers N = 1
  associated with shorter survival 1
  associated with longer survival 0
List of one gene significantly associated with 'Time to Death' by Cox regression test

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

HazardRatio Wald_P Q C_index
NR1H2 500000001 7.561e-08 0.0015 0.69

Figure S1.  Get High-res Image As an example, this figure shows the association of NR1H2 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 7.56e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

40 genes related to 'AGE'.

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

AGE Mean (SD) 64.81 (13)
  Significant markers N = 40
  pos. correlated 40
  neg. correlated 0
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
FAM19A4 0.3094 3.7e-09 7.48e-05
DOK5 0.2959 1.84e-08 0.000372
TBX5 0.2919 2.914e-08 0.000589
WIT1 0.2909 3.239e-08 0.000655
PTPRT 0.2859 5.698e-08 0.00115
FADS2 0.2838 7.215e-08 0.00146
RGS7BP 0.2793 1.175e-07 0.00238
SNAP25 0.2709 2.873e-07 0.00581
UNCX 0.2685 3.672e-07 0.00743
PRDM13 0.2684 3.721e-07 0.00752

Figure S2.  Get High-res Image As an example, this figure shows the association of FAM19A4 to 'AGE'. P value = 3.7e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

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

2070 genes related to 'PRIMARY.SITE.OF.DISEASE'.

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

PRIMARY.SITE.OF.DISEASE Labels N
  COLON 254
  RECTUM 93
     
  Significant markers N = 2070
  Higher in RECTUM 32
  Higher in COLON 2038
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'

T(pos if higher in 'RECTUM') ttestP Q AUC
ELAVL2 -11.06 5.523e-24 1.12e-19 0.7825
LPHN2 -10.81 1.448e-23 2.93e-19 0.7638
AARS2 -11.28 2.095e-23 4.24e-19 0.8231
MELK -10.85 2.764e-23 5.59e-19 0.7823
L3MBTL2 -10.63 3.381e-22 6.84e-18 0.8051
NDFIP1 -10.98 5.194e-22 1.05e-17 0.8238
CCDC85A -10.3 7.936e-22 1.6e-17 0.7394
KLRG2 -10.14 3.124e-21 6.32e-17 0.7503
ZYX -10.28 4.16e-21 8.41e-17 0.8184
PHIP -10.43 1.436e-20 2.9e-16 0.8136

Figure S3.  Get High-res Image As an example, this figure shows the association of ELAVL2 to 'PRIMARY.SITE.OF.DISEASE'. P value = 5.52e-24 with T-test analysis.

Clinical variable #4: 'GENDER'

2 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 156
  MALE 193
     
  Significant markers N = 2
  Higher in MALE 1
  Higher in FEMALE 1
List of 2 genes differentially expressed by 'GENDER'

Table S8.  Get Full Table List of 2 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -8.58 4.156e-16 8.41e-12 0.754
UTP14C 5.41 1.251e-07 0.00253 0.6879

Figure S4.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 4.16e-16 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

1150 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 224
  COLON MUCINOUS ADENOCARCINOMA 30
  RECTAL ADENOCARCINOMA 87
  RECTAL MUCINOUS ADENOCARCINOMA 6
     
  Significant markers N = 1150
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
SNORD98 9.017e-27 1.82e-22
THOC7 3.5e-22 7.08e-18
PMS2L4 1.214e-21 2.46e-17
DHX33 4.559e-21 9.22e-17
EXOSC4 7.863e-21 1.59e-16
ANKRD39 1.041e-20 2.11e-16
NDFIP1 1.055e-20 2.13e-16
SPPL2A 1.086e-20 2.2e-16
AARS2 2.147e-20 4.34e-16
PHIP 7.92e-20 1.6e-15

Figure S5.  Get High-res Image As an example, this figure shows the association of SNORD98 to 'HISTOLOGICAL.TYPE'. P value = 9.02e-27 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) 2.91 (0.63)
  N
  T0 1
  T1 10
  T2 51
  T3 243
  T4 42
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N'

3 genes related to 'PATHOLOGY.N'.

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

PATHOLOGY.N Mean (SD) 0.61 (0.76)
  N
  N0 193
  N1 93
  N2 58
     
  Significant markers N = 3
  pos. correlated 2
  neg. correlated 1
List of 3 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S13.  Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

SpearmanCorr corrP Q
SP140L 0.3003 1.344e-08 0.000272
CD74 0.2666 5.234e-07 0.0106
ELF5 -0.2571 1.344e-06 0.0272

Figure S6.  Get High-res Image As an example, this figure shows the association of SP140L to 'PATHOLOGY.N'. P value = 1.34e-08 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGICSPREAD(M)'

167 genes related to 'PATHOLOGICSPREAD(M)'.

Table S14.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 246
  M1 37
  M1A 8
  M1B 1
  MX 50
     
  Significant markers N = 167
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
CLTCL1 3.983e-54 8.06e-50
FAHD2B 6.363e-34 1.29e-29
POLR2J4 1.102e-33 2.23e-29
FAM86B2 1.04e-32 2.1e-28
UTRN 1.212e-32 2.45e-28
WDR18 1.366e-30 2.76e-26
ZNF136 8.15e-29 1.65e-24
PFN2 1.523e-28 3.08e-24
FAM71E1 2.168e-28 4.38e-24
C13ORF31 3.507e-27 7.09e-23

Figure S7.  Get High-res Image As an example, this figure shows the association of CLTCL1 to 'PATHOLOGICSPREAD(M)'. P value = 3.98e-54 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

3 genes related to 'TUMOR.STAGE'.

Table S16.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.47 (0.92)
  N
  Stage 1 48
  Stage 2 126
  Stage 3 106
  Stage 4 49
     
  Significant markers N = 3
  pos. correlated 1
  neg. correlated 2
List of 3 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S17.  Get Full Table List of 3 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SP140L 0.3115 7.815e-09 0.000158
MLF1 -0.2948 5.092e-08 0.00103
FGF20 -0.2569 2.332e-06 0.0472

Figure S8.  Get High-res Image As an example, this figure shows the association of SP140L to 'TUMOR.STAGE'. P value = 7.82e-09 with Spearman correlation analysis.

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S18.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 8
  YES 341
     
  Significant markers N = 165
  Higher in YES 163
  Higher in NO 2
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S19.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
RTDR1 14.11 1.155e-35 2.34e-31 0.8156
ZNF586 12.21 1.046e-28 2.12e-24 0.8072
C1ORF103 11.78 6.937e-26 1.4e-21 0.6569
VGLL3 12.19 3.512e-22 7.1e-18 0.7463
GBX1 10.25 1.536e-20 3.11e-16 0.8163
LRRTM1 12.14 5.898e-20 1.19e-15 0.7474
ZNF345 9.89 1.691e-19 3.42e-15 0.651
ZNF350 9.93 5.297e-19 1.07e-14 0.7416
LOC285548 9.73 2.628e-18 5.31e-14 0.783
NOG 9.15 1.2e-17 2.43e-13 0.7647

Figure S9.  Get High-res Image As an example, this figure shows the association of RTDR1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.15e-35 with T-test analysis.

Clinical variable #11: 'NEOADJUVANT.THERAPY'

No gene related to 'NEOADJUVANT.THERAPY'.

Table S20.  Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY Labels N
  NO 74
  YES 275
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = COADREAD.meth.for_correlation.filtered_data.txt

  • Clinical data file = COADREAD.clin.merged.picked.txt

  • Number of patients = 349

  • Number of genes = 20228

  • Number of clinical features = 11

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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