Colon/Rectal Adenocarcinoma: Correlation between mRNAseq expression and clinical features
Maintained by Juok Cho (Broad Institute)
Overview
Introduction

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

Summary

Testing the association between 18344 genes and 9 clinical features across 83 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

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

    • RFX6|222546 ,  AHSG|197 ,  AFP|174 ,  NXF2B|728343 ,  DPY19L1|23333

  • 17 genes correlated to 'GENDER'.

    • XIST|7503 ,  RPS4Y1|6192 ,  DDX3Y|8653 ,  UTY|7404 ,  ZFY|7544 ,  ...

  • 19 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HBG2|3048 ,  AFP|174 ,  AHSG|197 ,  HSPA2|3306 ,  DPPA4|55211 ,  ...

  • 1 gene correlated to 'PATHOLOGY.N'.

    • CLNK|116449

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

    • PAIP2B|400961 ,  NUCB1|4924 ,  ZDHHC22|283576

  • No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T', and 'TUMOR.STAGE'.

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=5 rectum N=2 colon N=3
GENDER t test N=17 male N=15 female N=2
HISTOLOGICAL TYPE ANOVA test N=19        
PATHOLOGY T Spearman correlation test   N=0        
PATHOLOGY N Spearman correlation test N=1 higher pN N=0 lower pN N=1
PATHOLOGICSPREAD(M) ANOVA test N=3        
TUMOR STAGE 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) 0.9-72.1 (median=8.2)
  censored N = 42
  death N = 4
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 67.58 (11)
  Significant markers N = 0
Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

5 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 11
  RECTUM 71
     
  Significant markers N = 5
  Higher in RECTUM 2
  Higher in COLON 3
List of 5 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S4.  Get Full Table List of 5 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

T(pos if higher in 'RECTUM') ttestP Q AUC
RFX6|222546 7.18 7.096e-09 0.000129 0.8889
AHSG|197 -8.76 2.915e-07 0.00532 0.9642
AFP|174 -8.71 5.621e-07 0.0103 0.9692
NXF2B|728343 6.18 6.281e-07 0.0115 0.8696
DPY19L1|23333 -6.66 1.215e-06 0.0222 0.8988

Figure S1.  Get High-res Image As an example, this figure shows the association of RFX6|222546 to 'PRIMARY.SITE.OF.DISEASE'. P value = 7.1e-09 with T-test analysis.

Clinical variable #4: 'GENDER'

17 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 39
  MALE 44
     
  Significant markers N = 17
  Higher in MALE 15
  Higher in FEMALE 2
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
XIST|7503 -17.52 4.381e-27 8.04e-23 0.9932
RPS4Y1|6192 17.42 3.108e-26 5.7e-22 0.9955
DDX3Y|8653 16.61 7.398e-22 1.36e-17 0.9932
UTY|7404 14.7 1.651e-21 3.03e-17 0.9886
ZFY|7544 11.71 6.462e-19 1.19e-14 0.9679
KDM5D|8284 13.65 1.176e-14 2.16e-10 0.9928
TTTY15|64595 10.33 1.664e-14 3.05e-10 0.9585
PRKY|5616 9.37 1.693e-14 3.1e-10 0.926
TSIX|9383 -9.54 2.535e-14 4.65e-10 0.9108
EIF1AY|9086 11.61 9.986e-14 1.83e-09 0.9795

Figure S2.  Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 4.38e-27 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

19 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 11
  RECTAL ADENOCARCINOMA 60
  RECTAL MUCINOUS ADENOCARCINOMA 8
     
  Significant markers N = 19
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
HBG2|3048 1.369e-10 2.51e-06
AFP|174 5.118e-10 9.39e-06
AHSG|197 3.92e-09 7.19e-05
HSPA2|3306 5.95e-09 0.000109
DPPA4|55211 3.107e-08 0.00057
SILV|6490 7.985e-08 0.00146
PDCL|5082 9.035e-08 0.00166
TOX|9760 1.017e-07 0.00186
TF|7018 2.453e-07 0.0045
B3GNT6|192134 4.009e-07 0.00735

Figure S3.  Get High-res Image As an example, this figure shows the association of HBG2|3048 to 'HISTOLOGICAL.TYPE'. P value = 1.37e-10 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

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

PATHOLOGY.T Mean (SD) 2.71 (0.67)
  N
  T1 5
  T2 19
  T3 54
  T4 5
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.54 (0.77)
  N
  N0 52
  N1 17
  N2 14
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S11.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

SpearmanCorr corrP Q
CLNK|116449 -0.5033 2.271e-06 0.0417

Figure S4.  Get High-res Image As an example, this figure shows the association of CLNK|116449 to 'PATHOLOGY.N'. P value = 2.27e-06 with Spearman correlation analysis.

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 68
  M1 13
  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
PAIP2B|400961 1.063e-06 0.0195
NUCB1|4924 2.379e-06 0.0436
ZDHHC22|283576 2.438e-06 0.0447

Figure S5.  Get High-res Image As an example, this figure shows the association of PAIP2B|400961 to 'PATHOLOGICSPREAD(M)'. P value = 1.06e-06 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) 2.28 (1)
  N
  Stage 1 21
  Stage 2 29
  Stage 3 18
  Stage 4 13
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = COADREAD.mRNAseq_RPKM_log2.txt

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

  • Number of patients = 83

  • Number of genes = 18344

  • Number of clinical features = 9

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)
Copyright © 2012 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle