Correlation between mRNA expression and clinical features
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 17814 genes and 10 clinical features across 153 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one genes.

  • 3 genes correlated to 'AGE'.

    • ANAPC1 ,  PRSS12 ,  HSPH1

  • 1 gene correlated to 'PATHOLOGY.T.STAGE'.

    • ALG8

  • 5 genes correlated to 'GENDER'.

    • JARID1D ,  CYORF15A ,  CYORF15B ,  UTX ,  JARID1C

  • 129 genes correlated to 'HISTOLOGICAL.TYPE'.

    • AGR2 ,  SPDEF ,  ALOX5 ,  AQP3 ,  SERF2 ,  ...

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • PDK4

  • No genes correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', and 'COMPLETENESS.OF.RESECTION'.

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 P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test   N=0        
AGE Spearman correlation test N=3 older N=1 younger N=2
NEOPLASM DISEASESTAGE Kruskal-Wallis test   N=0        
PATHOLOGY T STAGE Spearman correlation test N=1 higher stage N=0 lower stage N=1
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE Kruskal-Wallis test   N=0        
GENDER Wilcoxon test N=5 male N=5 female N=0
HISTOLOGICAL TYPE Wilcoxon test N=129 colon mucinous adenocarcinoma N=129 colon adenocarcinoma N=0
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes 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) 0.9-54 (median=23)
  censored N = 115
  death N = 26
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

3 genes related to 'AGE'.

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

AGE Mean (SD) 70.78 (12)
  Significant markers N = 3
  pos. correlated 1
  neg. correlated 2
List of 3 genes differentially expressed by 'AGE'

Table S3.  Get Full Table List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ANAPC1 -0.388 7.19e-07 0.0128
PRSS12 0.3583 5.428e-06 0.0967
HSPH1 -0.3504 8.966e-06 0.16
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 29
  STAGE II 12
  STAGE IIA 45
  STAGE IIB 5
  STAGE III 8
  STAGE IIIA 3
  STAGE IIIB 12
  STAGE IIIC 16
  STAGE IV 21
  STAGE IVA 1
     
  Significant markers N = 0
Clinical variable #4: 'PATHOLOGY.T.STAGE'

One gene related to 'PATHOLOGY.T.STAGE'.

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

PATHOLOGY.T.STAGE Mean (SD) 2.84 (0.62)
  N
  1 4
  2 31
  3 103
  4 15
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene differentially expressed by 'PATHOLOGY.T.STAGE'

Table S6.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
ALG8 -0.3416 1.547e-05 0.276
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.59 (0.81)
  N
  0 94
  1 28
  2 31
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 129
  M1 21
  M1A 1
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

5 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 75
  MALE 78
     
  Significant markers N = 5
  Higher in MALE 5
  Higher in FEMALE 0
List of 5 genes differentially expressed by 'GENDER'

Table S10.  Get Full Table List of 5 genes differentially expressed by 'GENDER'. 22 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
JARID1D 5721 1.93e-24 3.44e-20 0.9779
CYORF15A 5589 2.456e-22 4.37e-18 0.9554
CYORF15B 5535 1.67e-21 2.97e-17 0.9462
UTX 1479 1.323e-07 0.00236 0.7472
JARID1C 1574.5 8.348e-07 0.0149 0.7309
Clinical variable #8: 'HISTOLOGICAL.TYPE'

129 genes related to 'HISTOLOGICAL.TYPE'.

Table S11.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 129
  COLON MUCINOUS ADENOCARCINOMA 22
     
  Significant markers N = 129
  Higher in COLON MUCINOUS ADENOCARCINOMA 129
  Higher in COLON ADENOCARCINOMA 0
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

W(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') wilcoxontestP Q AUC
AGR2 2468 3.201e-08 0.00057 0.8696
SPDEF 2448 5.809e-08 0.00103 0.8626
ALOX5 2411 1.7e-07 0.00303 0.8495
AQP3 2409 1.8e-07 0.00321 0.8488
SERF2 2398 2.458e-07 0.00438 0.845
CREB3L1 2388.5 3.208e-07 0.00571 0.8416
C20ORF177 458 4.064e-07 0.00724 0.8386
SLC19A3 464 4.796e-07 0.00854 0.8365
PTGER2 2370 5.353e-07 0.00953 0.8351
SLC39A9 2361 6.844e-07 0.0122 0.8319
Clinical variable #9: 'COMPLETENESS.OF.RESECTION'

No gene 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 = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S14.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.14 (4.5)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S15.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
PDK4 0.3417 1.648e-05 0.294
Methods & Data
Input

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

  • Clinical data file = COAD-TP.merged_data.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

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.

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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