Correlation between mRNA expression and clinical features
Colon/Rectal Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1HQ3WXZ
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1HQ3WXZ
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 222 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

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

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

  • 31 genes correlated to 'GENDER'.

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

  • 381 genes correlated to 'HISTOLOGICAL.TYPE'.

    • SLC11A1 ,  PLAGL2 ,  SRBD1 ,  AGR2 ,  PDGFRL ,  ...

  • 2 genes correlated to 'DISTANT.METASTASIS'.

    • KCNC2 ,  FLJ44894

  • 3 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • KCNC2 ,  LOC253970 ,  HS3ST4

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

    • CRH ,  DSCR8 ,  LGALS14 ,  PAGE4 ,  GRB7 ,  ...

  • 5 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • FLJ44894 ,  KCNC2 ,  ZNF234 ,  TMC7 ,  CALB1

  • No genes correlated to 'Time to Death', 'AGE', 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=38 rectum N=20 colon N=18
GENDER t test N=31 male N=14 female N=17
HISTOLOGICAL TYPE ANOVA test N=381        
DISTANT METASTASIS ANOVA test N=2        
LYMPH NODE METASTASIS ANOVA test N=3        
COMPLETENESS OF RESECTION ANOVA test N=13        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE ANOVA test N=5        
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)
  censored N = 104
  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'

38 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 = 38
  Higher in RECTUM 20
  Higher in COLON 18
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
PRAC 7.42 7.727e-12 1.38e-07 0.7776
GPX2 7.13 1.473e-11 2.62e-07 0.7837
CEACAM5 7.15 1.533e-11 2.73e-07 0.7713
LGALS4 6.97 6.641e-11 1.18e-06 0.7553
ZNF529 6.32 1.459e-09 2.6e-05 0.6806
HSP90B3P -6.35 1.722e-09 3.07e-05 0.7395
SIN3A -5.94 1.58e-08 0.000281 0.7208
MLH1 5.75 2.952e-08 0.000526 0.6613
CORO1C -5.63 7.226e-08 0.00129 0.7218
TUG1 5.59 7.595e-08 0.00135 0.7027

Figure S1.  Get High-res Image As an example, this figure shows the association of PRAC to 'PRIMARY.SITE.OF.DISEASE'. P value = 7.73e-12 with T-test analysis.

Clinical variable #4: 'GENDER'

31 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 106
  MALE 116
     
  Significant markers N = 31
  Higher in MALE 14
  Higher in FEMALE 17
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 25.25 6.169e-67 1.1e-62 0.9703
EIF1AY 22.78 2.202e-59 3.92e-55 0.9635
JARID1D 22.44 1.112e-58 1.98e-54 0.969
RPS4Y1 22.23 2.831e-57 5.04e-53 0.9406
RPS4Y2 21.36 2.393e-54 4.26e-50 0.9634
CYORF15A 20.7 1.244e-52 2.22e-48 0.9527
UTY 18.87 1.811e-46 3.23e-42 0.9453
CYORF15B 17.18 6.979e-42 1.24e-37 0.9329
ZFY 16.5 3.713e-40 6.61e-36 0.9282
NLGN4Y 12.01 4.439e-25 7.9e-21 0.8654

Figure S2.  Get High-res Image As an example, this figure shows the association of DDX3Y to 'GENDER'. P value = 6.17e-67 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

381 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 127
  COLON MUCINOUS ADENOCARCINOMA 24
  RECTAL ADENOCARCINOMA 58
  RECTAL MUCINOUS ADENOCARCINOMA 7
     
  Significant markers N = 381
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 2.494e-12 4.44e-08
PLAGL2 1.102e-11 1.96e-07
SRBD1 1.58e-11 2.81e-07
AGR2 1.774e-11 3.16e-07
PDGFRL 1.817e-11 3.24e-07
C20ORF177 5.477e-11 9.75e-07
HPSE 7.445e-11 1.33e-06
SERF2 7.602e-11 1.35e-06
GPR126 9.206e-11 1.64e-06
DUSP4 9.898e-11 1.76e-06

Figure S3.  Get High-res Image As an example, this figure shows the association of SLC11A1 to 'HISTOLOGICAL.TYPE'. P value = 2.49e-12 with ANOVA analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

2 genes related to 'DISTANT.METASTASIS'.

Table S9.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 186
  M1 33
  M1A 1
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

Table S10.  Get Full Table List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
KCNC2 1.76e-10 3.13e-06
FLJ44894 6.411e-07 0.0114

Figure S4.  Get High-res Image As an example, this figure shows the association of KCNC2 to 'DISTANT.METASTASIS'. P value = 1.76e-10 with ANOVA analysis.

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

3 genes related to 'LYMPH.NODE.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 136
  N1 41
  N1A 1
  N1B 1
  N2 42
  N2A 1
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S12.  Get Full Table List of 3 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
KCNC2 1.329e-08 0.000237
LOC253970 1.675e-07 0.00298
HS3ST4 6.807e-07 0.0121

Figure S5.  Get High-res Image As an example, this figure shows the association of KCNC2 to 'LYMPH.NODE.METASTASIS'. P value = 1.33e-08 with ANOVA analysis.

Clinical variable #8: 'COMPLETENESS.OF.RESECTION'

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

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

COMPLETENESS.OF.RESECTION Labels N
  R0 185
  R1 2
  R2 29
     
  Significant markers N = 13
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 2.584e-12 4.6e-08
DSCR8 3.033e-11 5.4e-07
LGALS14 1.374e-08 0.000245
PAGE4 3.551e-08 0.000633
GRB7 3.602e-08 0.000642
FAM69B 4.643e-08 0.000827
FSTL5 8.955e-08 0.00159
RARA 1.218e-07 0.00217
TAS2R38 2.634e-07 0.00469
CTAG2 4.989e-07 0.00888

Figure S6.  Get High-res Image As an example, this figure shows the association of CRH to 'COMPLETENESS.OF.RESECTION'. P value = 2.58e-12 with ANOVA analysis.

Clinical variable #9: '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) 2.15 (4.7)
  Significant markers N = 0
Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

5 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S16.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 47
  STAGE II 15
  STAGE IIA 65
  STAGE IIB 5
  STAGE III 10
  STAGE IIIA 3
  STAGE IIIB 22
  STAGE IIIC 20
  STAGE IV 32
  STAGE IVA 1
     
  Significant markers N = 5
List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S17.  Get Full Table List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
FLJ44894 3.847e-07 0.00685
KCNC2 5.505e-07 0.00981
ZNF234 1.108e-06 0.0197
TMC7 2.336e-06 0.0416
CALB1 2.595e-06 0.0462

Figure S7.  Get High-res Image As an example, this figure shows the association of FLJ44894 to 'NEOPLASM.DISEASESTAGE'. P value = 3.85e-07 with ANOVA analysis.

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 = 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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