Colon Adenocarcinoma: Correlation between mRNA expression and clinical features
(primary solid tumor cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 17814 genes and 10 clinical features across 153 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 1 gene correlated to 'AGE'.

    • ANAPC1

  • 19 genes correlated to 'GENDER'.

    • DDX3Y ,  JARID1D ,  EIF1AY ,  RPS4Y1 ,  CYORF15A ,  ...

  • 147 genes correlated to 'HISTOLOGICAL.TYPE'.

    • C20ORF24 ,  DYNLRB1 ,  AGR2 ,  C20ORF4 ,  C10ORF65 ,  ...

  • 1 gene correlated to 'PATHOLOGICSPREAD(M)'.

    • KCNC2

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

    • CRH ,  CT45-6 ,  COX7B2 ,  CTAG2 ,  RP13-36C9.6 ,  ...

  • No genes correlated to 'Time to Death', 'PATHOLOGY.T', 'PATHOLOGY.N', 'TUMOR.STAGE', 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=1 older N=0 younger N=1
GENDER t test N=19 male N=13 female N=6
HISTOLOGICAL TYPE t test N=147 colon mucinous adenocarcinoma N=46 colon adenocarcinoma N=101
PATHOLOGY T Spearman correlation test   N=0        
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test N=1        
TUMOR STAGE Spearman correlation test   N=0        
COMPLETENESS OF RESECTION ANOVA test N=46        
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) 0.9-52 (median=4.5)
  censored N = 63
  death N = 11
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

One gene related to 'AGE'.

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

AGE Mean (SD) 70.77 (12)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of one gene significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ANAPC1 -0.3783 1.427e-06 0.0254

Figure S1.  Get High-res Image As an example, this figure shows the association of ANAPC1 to 'AGE'. P value = 1.43e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

19 genes related to 'GENDER'.

Table S4.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 75
  MALE 78
     
  Significant markers N = 19
  Higher in MALE 13
  Higher in FEMALE 6
List of top 10 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
DDX3Y 22.4 1.175e-49 2.09e-45 0.974
JARID1D 20.63 9.001e-46 1.6e-41 0.979
EIF1AY 20.53 1.741e-45 3.1e-41 0.9653
RPS4Y1 19.12 5.069e-42 9.03e-38 0.9504
CYORF15A 18.59 1.302e-40 2.32e-36 0.9554
RPS4Y2 18.28 9.619e-40 1.71e-35 0.9622
UTY 17.92 2.456e-38 4.37e-34 0.9568
ZFY 15.63 2.305e-33 4.1e-29 0.9482
CYORF15B 15.59 8.287e-33 1.48e-28 0.9455
USP9Y 10.7 3.609e-20 6.43e-16 0.8937

Figure S2.  Get High-res Image As an example, this figure shows the association of DDX3Y to 'GENDER'. P value = 1.17e-49 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

147 genes related to 'HISTOLOGICAL.TYPE'.

Table S6.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 126
  COLON MUCINOUS ADENOCARCINOMA 24
     
  Significant markers N = 147
  Higher in COLON MUCINOUS ADENOCARCINOMA 46
  Higher in COLON ADENOCARCINOMA 101
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') ttestP Q AUC
C20ORF24 -8.47 1.191e-11 2.12e-07 0.8528
DYNLRB1 -8.09 4.174e-11 7.44e-07 0.835
AGR2 8.11 1.273e-10 2.27e-06 0.8724
C20ORF4 -7.58 5.68e-10 1.01e-05 0.8373
C10ORF65 -7.27 9.327e-10 1.66e-05 0.8099
PLA2G12B -7.46 1.267e-09 2.26e-05 0.828
RDHE2 7.36 1.841e-09 3.28e-05 0.8151
ASXL1 -7.37 2.311e-09 4.12e-05 0.8449
SLC5A6 -7.27 3.045e-09 5.42e-05 0.833
EIF6 -7.32 3.159e-09 5.63e-05 0.834

Figure S3.  Get High-res Image As an example, this figure shows the association of C20ORF24 to 'HISTOLOGICAL.TYPE'. P value = 1.19e-11 with T-test analysis.

Clinical variable #5: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 2.83 (0.61)
  N
  T1 4
  T2 31
  T3 103
  T4 13
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.59 (0.81)
  N
  N0 94
  N1 28
  N2 31
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGICSPREAD(M)'

One gene related to 'PATHOLOGICSPREAD(M)'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 128
  M1 21
  M1A 1
     
  Significant markers N = 1
List of one gene differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S11.  Get Full Table List of one gene differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
KCNC2 3.3e-14 5.88e-10

Figure S4.  Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 3.3e-14 with ANOVA analysis.

Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S12.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.35 (0.94)
  N
  Stage 1 28
  Stage 2 62
  Stage 3 39
  Stage 4 21
     
  Significant markers N = 0
Clinical variable #9: 'COMPLETENESS.OF.RESECTION'

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

Table S13.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 128
  R1 1
  R2 19
     
  Significant markers N = 46
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
CRH 2.812e-24 5.01e-20
CT45-6 5.79e-18 1.03e-13
COX7B2 5.848e-18 1.04e-13
CTAG2 9.785e-17 1.74e-12
RP13-36C9.6 2.305e-15 4.11e-11
HOXC13 3.499e-14 6.23e-10
PAGE4 4.612e-14 8.21e-10
LGALS14 2.336e-13 4.16e-09
RARA 3.586e-13 6.38e-09
PNMT 5.006e-13 8.91e-09

Figure S5.  Get High-res Image As an example, this figure shows the association of CRH to 'COMPLETENESS.OF.RESECTION'. P value = 2.81e-24 with ANOVA analysis.

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

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

Table S15.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.14 (4.5)
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = COAD-TP.medianexp.txt

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

  • Number of patients = 153

  • Number of genes = 17814

  • 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

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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