Correlation between gene methylation status and clinical features
Rectum Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1FT8JDD
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/C1FT8JDD
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 20132 genes and 11 clinical features across 95 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 268 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • ADRA2A ,  GJB6 ,  ZNF192 ,  GIGYF1 ,  ARNTL ,  ...

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

    • TUBA3D ,  UQCRB ,  DDOST ,  GPR63 ,  TTLL13

  • 63 genes correlated to 'HISTOLOGICAL.TYPE'.

    • LPAR5 ,  E2F4 ,  PLA2G12B ,  KIAA0319L__1 ,  C20ORF56 ,  ...

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

    • RSPO3 ,  ST8SIA2 ,  PAQR7 ,  FFAR2 ,  ZDBF2 ,  ...

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

    • FLJ39582 ,  THAP7 ,  C8ORF47 ,  PABPC1L ,  TNFRSF11B ,  ...

  • No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'GENDER', and 'NUMBER.OF.LYMPH.NODES'.

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=0        
NEOPLASM DISEASESTAGE ANOVA test N=268        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=5        
GENDER t test   N=0        
HISTOLOGICAL TYPE t test N=63 rectal mucinous adenocarcinoma N=36 rectal adenocarcinoma N=27
RADIATIONS RADIATION REGIMENINDICATION t test N=171 yes N=144 no N=27
COMPLETENESS OF RESECTION ANOVA test N=39        
NUMBER OF LYMPH NODES Spearman correlation test   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) 0.2-129.3 (median=11.8)
  censored N = 77
  death N = 9
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 63.26 (12)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

268 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S3.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 11
  STAGE II 6
  STAGE IIA 18
  STAGE IIB 2
  STAGE IIC 2
  STAGE III 4
  STAGE IIIA 9
  STAGE IIIB 13
  STAGE IIIC 8
  STAGE IV 6
  STAGE IVA 9
     
  Significant markers N = 268
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S4.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
ADRA2A 9.851e-33 1.98e-28
GJB6 3.466e-11 6.98e-07
ZNF192 4.753e-11 9.57e-07
GIGYF1 1.993e-10 4.01e-06
ARNTL 2.909e-10 5.85e-06
ACAP2 3.017e-10 6.07e-06
SEC22B 3.242e-10 6.52e-06
SLC23A2 3.619e-10 7.28e-06
SEPT11 4.492e-10 9.04e-06
TXLNA 1.31e-09 2.64e-05

Figure S1.  Get High-res Image As an example, this figure shows the association of ADRA2A to 'NEOPLASM.DISEASESTAGE'. P value = 9.85e-33 with ANOVA analysis.

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

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

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.89 (0.65)
  N
  1 4
  2 13
  3 64
  4 11
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.76 (0.78)
  N
  0 41
  1 30
  2 19
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 65
  M1 10
  M1A 2
  MX 14
     
  Significant markers N = 5
List of 5 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S8.  Get Full Table List of 5 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
TUBA3D 2.928e-12 5.9e-08
UQCRB 6.124e-10 1.23e-05
DDOST 8.742e-10 1.76e-05
GPR63 1.042e-07 0.0021
TTLL13 6.028e-07 0.0121

Figure S2.  Get High-res Image As an example, this figure shows the association of TUBA3D to 'PATHOLOGY.M.STAGE'. P value = 2.93e-12 with ANOVA analysis.

Clinical variable #7: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 41
  MALE 52
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL.TYPE'

63 genes related to 'HISTOLOGICAL.TYPE'.

Table S10.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  RECTAL ADENOCARCINOMA 85
  RECTAL MUCINOUS ADENOCARCINOMA 6
     
  Significant markers N = 63
  Higher in RECTAL MUCINOUS ADENOCARCINOMA 36
  Higher in RECTAL ADENOCARCINOMA 27
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

T(pos if higher in 'RECTAL MUCINOUS ADENOCARCINOMA') ttestP Q AUC
LPAR5 9.21 8.217e-14 1.65e-09 0.8686
E2F4 10.06 3.229e-13 6.5e-09 0.9255
PLA2G12B 9.29 7.375e-13 1.48e-08 0.8255
KIAA0319L__1 -9.58 4.827e-11 9.72e-07 0.8647
C20ORF56 -7.42 6.769e-11 1.36e-06 0.8431
VPS37B -10.28 6.838e-10 1.38e-05 0.9257
ABCB11 6.99 8.181e-10 1.65e-05 0.749
CKMT2 6.94 8.209e-10 1.65e-05 0.7804
RNU5D 6.94 8.209e-10 1.65e-05 0.7804
RNU5E 6.94 8.209e-10 1.65e-05 0.7804

Figure S3.  Get High-res Image As an example, this figure shows the association of LPAR5 to 'HISTOLOGICAL.TYPE'. P value = 8.22e-14 with T-test analysis.

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

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

Table S12.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 4
  YES 91
     
  Significant markers N = 171
  Higher in YES 144
  Higher in NO 27
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
RSPO3 13.41 3.075e-23 6.19e-19 0.9066
ST8SIA2 11.72 7.359e-18 1.48e-13 0.8709
PAQR7 10.44 7.286e-17 1.47e-12 0.8791
FFAR2 10.33 1.32e-16 2.66e-12 0.8874
ZDBF2 9.7 1.525e-15 3.07e-11 0.8956
ZNF543 9.51 2.428e-15 4.89e-11 0.8242
GFI1B 9.54 3.612e-15 7.27e-11 0.8791
ICMT 9.28 8.994e-15 1.81e-10 0.8324
AQP1 9.77 2.115e-14 4.26e-10 0.8407
RET 9.18 4.029e-14 8.11e-10 0.8681

Figure S4.  Get High-res Image As an example, this figure shows the association of RSPO3 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 3.07e-23 with T-test analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

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

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

COMPLETENESS.OF.RESECTION Labels N
  R0 62
  R1 2
  R2 2
  RX 4
     
  Significant markers N = 39
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
FLJ39582 3.302e-18 6.65e-14
THAP7 3.302e-18 6.65e-14
C8ORF47 4.369e-14 8.79e-10
PABPC1L 2.448e-10 4.93e-06
TNFRSF11B 3.682e-10 7.41e-06
ATRNL1 9.675e-10 1.95e-05
MPP2 3.985e-09 8.02e-05
CORO2B 7.168e-09 0.000144
FRMPD1 9.107e-09 0.000183
ABCA11P__1 2.983e-08 6e-04

Figure S5.  Get High-res Image As an example, this figure shows the association of FLJ39582 to 'COMPLETENESS.OF.RESECTION'. P value = 3.3e-18 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

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

NUMBER.OF.LYMPH.NODES Mean (SD) 3.09 (5.8)
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 95

  • Number of genes = 20132

  • 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

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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