Colon/Rectal 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 11 clinical features across 222 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

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

    • CEACAM5 ,  PRAC ,  GPX2 ,  LGALS4 ,  ZNF529 ,  ...

  • 30 genes correlated to 'GENDER'.

    • DDX3Y ,  EIF1AY ,  JARID1D ,  RPS4Y1 ,  RPS4Y2 ,  ...

  • 383 genes correlated to 'HISTOLOGICAL.TYPE'.

    • SLC11A1 ,  PLAGL2 ,  C20ORF177 ,  PDGFRL ,  DUSP4 ,  ...

  • 1 gene correlated to 'PATHOLOGY.T'.

    • RBP7

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

    • KCNC2 ,  FLJ44894 ,  MFNG

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

    • CRH ,  DSCR8 ,  LGALS14 ,  FAM69B ,  GRB7 ,  ...

  • No genes correlated to 'Time to Death', 'AGE', '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=0        
PRIMARY SITE OF DISEASE t test N=37 rectum N=25 colon N=12
GENDER t test N=30 male N=14 female N=16
HISTOLOGICAL TYPE ANOVA test N=383        
PATHOLOGY T Spearman correlation test N=1 higher pT N=1 lower pT N=0
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test N=3        
TUMOR STAGE Spearman correlation test   N=0        
COMPLETENESS OF RESECTION ANOVA test N=16        
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=5)
  censored N = 98
  death N = 15
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 69.48 (11)
  Significant markers N = 0
Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

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

Table S3.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  COLON 152
  RECTUM 68
     
  Significant markers N = 37
  Higher in RECTUM 25
  Higher in COLON 12
List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S4.  Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

T(pos if higher in 'RECTUM') ttestP Q AUC
CEACAM5 7.32 5.511e-12 9.82e-08 0.7742
PRAC 7.47 5.752e-12 1.02e-07 0.7802
GPX2 7.25 7.252e-12 1.29e-07 0.7872
LGALS4 7.19 1.683e-11 3e-07 0.7561
ZNF529 6.37 1.113e-09 1.98e-05 0.6865
MLH1 5.96 1.032e-08 0.000184 0.6737
HSP90B3P -5.96 1.406e-08 0.00025 0.7307
CFTR 5.72 4.422e-08 0.000787 0.7652
PPP1R1B 5.69 4.763e-08 0.000848 0.7358
PDZK1IP1 5.76 4.959e-08 0.000883 0.7418

Figure S1.  Get High-res Image As an example, this figure shows the association of CEACAM5 to 'PRIMARY.SITE.OF.DISEASE'. P value = 5.51e-12 with T-test analysis.

Clinical variable #4: 'GENDER'

30 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 106
  MALE 116
     
  Significant markers N = 30
  Higher in MALE 14
  Higher in FEMALE 16
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
DDX3Y 25.23 7.011e-67 1.25e-62 0.9709
EIF1AY 22.77 2.292e-59 4.08e-55 0.9637
JARID1D 22.45 9.333e-59 1.66e-54 0.9702
RPS4Y1 22.26 2.103e-57 3.75e-53 0.9422
RPS4Y2 21.4 1.705e-54 3.04e-50 0.9644
CYORF15A 20.72 9.406e-53 1.68e-48 0.9536
UTY 18.75 3.473e-46 6.18e-42 0.9448
CYORF15B 17.08 1.326e-41 2.36e-37 0.9322
ZFY 16.73 6.339e-41 1.13e-36 0.9297
NLGN4Y 12.15 2.523e-25 4.49e-21 0.8665

Figure S2.  Get High-res Image As an example, this figure shows the association of DDX3Y to 'GENDER'. P value = 7.01e-67 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

383 genes related to 'HISTOLOGICAL.TYPE'.

Table S7.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 126
  COLON MUCINOUS ADENOCARCINOMA 24
  RECTAL ADENOCARCINOMA 58
  RECTAL MUCINOUS ADENOCARCINOMA 7
     
  Significant markers N = 383
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
SLC11A1 2.544e-12 4.53e-08
PLAGL2 3.39e-12 6.04e-08
C20ORF177 1.351e-11 2.41e-07
PDGFRL 1.372e-11 2.44e-07
DUSP4 7.248e-11 1.29e-06
AGR2 7.347e-11 1.31e-06
ZNF529 8.428e-11 1.5e-06
SLC19A3 1.175e-10 2.09e-06
HPSE 1.387e-10 2.47e-06
PRAC 1.581e-10 2.82e-06

Figure S3.  Get High-res Image As an example, this figure shows the association of SLC11A1 to 'HISTOLOGICAL.TYPE'. P value = 2.54e-12 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 2.79 (0.64)
  N
  T1 9
  T2 46
  T3 148
  T4 17
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S10.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
RBP7 0.3138 2.055e-06 0.0366

Figure S4.  Get High-res Image As an example, this figure shows the association of RBP7 to 'PATHOLOGY.T'. P value = 2.05e-06 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.58 (0.8)
  N
  N0 136
  N1 43
  N2 43
     
  Significant markers N = 0
Clinical variable #8: 'PATHOLOGICSPREAD(M)'

3 genes related to 'PATHOLOGICSPREAD(M)'.

Table S12.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 185
  M1 33
  M1A 1
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S13.  Get Full Table List of 3 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
KCNC2 1.205e-10 2.15e-06
FLJ44894 1.792e-06 0.0319
MFNG 2.691e-06 0.0479

Figure S5.  Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 1.2e-10 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S14.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.33 (0.97)
  N
  Stage 1 46
  Stage 2 85
  Stage 3 55
  Stage 4 31
     
  Significant markers N = 0
Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

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

Table S15.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 185
  R1 2
  R2 29
     
  Significant markers N = 16
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
CRH 4.721e-12 8.41e-08
DSCR8 3.183e-11 5.67e-07
LGALS14 1.466e-08 0.000261
FAM69B 2.014e-08 0.000359
GRB7 4.099e-08 0.00073
PAGE4 4.679e-08 0.000833
RARA 7.158e-08 0.00127
FSTL5 7.727e-08 0.00138
TAS2R38 2.729e-07 0.00486
CTAG2 3.697e-07 0.00658

Figure S6.  Get High-res Image As an example, this figure shows the association of CRH to 'COMPLETENESS.OF.RESECTION'. P value = 4.72e-12 with ANOVA analysis.

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

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

Table S17.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.16 (4.7)
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 222

  • Number of genes = 17814

  • 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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