Correlation between mRNA expression and clinical features
Colorectal Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1W958JM
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features. The input file "COADREAD-TP.medianexp.txt" is generated in the pipeline mRNA_Preprocess_Median in the stddata run.

Summary

Testing the association between 17814 genes and 12 clinical features across 222 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • ANAPC1 ,  SMARCD1 ,  HSPH1 ,  FLJ22222 ,  CEACAM20 ,  ...

  • 30 genes correlated to 'TUMOR_TISSUE_SITE'.

    • GPX2 ,  PRAC ,  CEACAM5 ,  CFTR ,  LGALS4 ,  ...

  • 29 genes correlated to 'PATHOLOGIC_STAGE'.

    • RASGRP1 ,  GLS ,  CDR2 ,  ZNF92 ,  MMP11 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • RBP7 ,  EDG3 ,  SV2B ,  CHRNA3 ,  SCG2 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • LUZP2 ,  NFKBIZ ,  THEX1 ,  SUCLA2 ,  CXCL2 ,  ...

  • 30 genes correlated to 'PATHOLOGY_M_STAGE'.

    • CIITA ,  ZNF273 ,  LAP3 ,  COBLL1 ,  GBP4 ,  ...

  • 7 genes correlated to 'GENDER'.

    • JARID1D ,  CYORF15A ,  CYORF15B ,  UTX ,  HDHD1A ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • AGR2 ,  PRAC ,  GPX2 ,  GFI1 ,  SRBD1 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • CD274 ,  MOCS3 ,  LCK ,  FAM114A1 ,  RASGRP1 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • LUZP2 ,  NFKBIZ ,  CXCL2 ,  THEX1 ,  TMEM46 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', and 'RADIATION_THERAPY'.

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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=22 younger N=8
TUMOR_TISSUE_SITE Wilcoxon test N=30 rectum N=30 colon N=0
PATHOLOGIC_STAGE Kruskal-Wallis test N=29        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=28 lower stage N=2
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_M_STAGE Wilcoxon test N=30 class1 N=30 class0 N=0
GENDER Wilcoxon test N=7 male N=7 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=15 lower number_of_lymph_nodes N=15
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No gene related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-54 (median=21)
  censored N = 182
  death N = 39
     
  Significant markers N = 0
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 69.49 (11)
  Significant markers N = 30
  pos. correlated 22
  neg. correlated 8
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
ANAPC1 -0.3043 3.858e-06 0.0687
SMARCD1 0.2798 2.338e-05 0.0994
HSPH1 -0.2787 2.527e-05 0.0994
FLJ22222 0.2765 2.948e-05 0.0994
CEACAM20 0.2764 2.953e-05 0.0994
SLC7A6 -0.272 3.988e-05 0.0994
BTD 0.2709 4.309e-05 0.0994
SLC25A4 0.2704 4.462e-05 0.0994
RIC8B 0.2659 6.012e-05 0.106
WIF1 -0.2632 7.213e-05 0.106
Clinical variable #3: 'TUMOR_TISSUE_SITE'

30 genes related to 'TUMOR_TISSUE_SITE'.

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

TUMOR_TISSUE_SITE Labels N
  COLON 152
  RECTUM 68
     
  Significant markers N = 30
  Higher in RECTUM 30
  Higher in COLON 0
List of top 10 genes differentially expressed by 'TUMOR_TISSUE_SITE'

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

W(pos if higher in 'RECTUM') wilcoxontestP Q AUC
GPX2 8100.5 1.815e-11 3.23e-07 0.7837
PRAC 8037.5 4.839e-11 4.31e-07 0.7776
CEACAM5 7972 1.313e-10 7.8e-07 0.7713
CFTR 7873 5.691e-10 2.53e-06 0.7617
LGALS4 7807 1.471e-09 5.24e-06 0.7553
C10ORF99 7701 6.454e-09 1.55e-05 0.7451
HOXB13 7699 6.633e-09 1.55e-05 0.7449
FAM3D 7695.5 6.958e-09 1.55e-05 0.7445
HSP90B3P 2693 1.415e-08 2.59e-05 0.7395
PDZK1IP1 7641 1.453e-08 2.59e-05 0.7393
Clinical variable #4: 'PATHOLOGIC_STAGE'

29 genes related to 'PATHOLOGIC_STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE 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 33
  STAGE IVA 1
     
  Significant markers N = 29
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
RASGRP1 5.604e-05 0.217
GLS 5.897e-05 0.217
CDR2 6.457e-05 0.217
ZNF92 7.163e-05 0.217
MMP11 7.377e-05 0.217
ZNF12 0.0001136 0.217
ZNF273 0.0001157 0.217
ZSWIM3 0.0001181 0.217
KIAA1345 0.0001302 0.217
RDH12 0.0001321 0.217
Clinical variable #5: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.8 (0.64)
  N
  T1 9
  T2 46
  T3 148
  T4 19
     
  Significant markers N = 30
  pos. correlated 28
  neg. correlated 2
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
RBP7 0.305 3.667e-06 0.0653
EDG3 0.2907 1.072e-05 0.0955
SV2B 0.2735 3.606e-05 0.144
CHRNA3 0.2724 3.897e-05 0.144
SCG2 0.2718 4.047e-05 0.144
THBS4 0.2622 7.673e-05 0.184
KCNJ8 0.262 7.793e-05 0.184
ZC3H12A -0.2597 9.037e-05 0.184
PRPH 0.2581 1e-04 0.184
MARCO 0.2558 0.0001159 0.184
Clinical variable #6: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Mean (SD) 0.58 (0.8)
  N
  N0 136
  N1 43
  N2 43
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S11.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
LUZP2 0.3103 2.434e-06 0.0434
NFKBIZ -0.289 1.212e-05 0.108
THEX1 -0.2812 2.123e-05 0.126
SUCLA2 0.2764 2.949e-05 0.128
CXCL2 -0.2713 4.192e-05 0.128
TMEM46 0.2709 4.307e-05 0.128
PPP1R14A 0.2643 6.673e-05 0.14
C5ORF23 0.261 8.291e-05 0.14
SLC22A6 -0.2597 9.024e-05 0.14
BIRC3 -0.2596 9.087e-05 0.14
Clinical variable #7: 'PATHOLOGY_M_STAGE'

30 genes related to 'PATHOLOGY_M_STAGE'.

Table S12.  Basic characteristics of clinical feature: 'PATHOLOGY_M_STAGE'

PATHOLOGY_M_STAGE Labels N
  class0 186
  class1 34
     
  Significant markers N = 30
  Higher in class1 30
  Higher in class0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
CIITA 1711 2.135e-05 0.11 0.7294
ZNF273 4598 2.596e-05 0.11 0.7271
LAP3 1730.5 2.751e-05 0.11 0.7264
COBLL1 4573 3.58e-05 0.11 0.7231
GBP4 1762 4.117e-05 0.11 0.7214
INDO 1777 4.973e-05 0.11 0.719
APOL2 1789 5.778e-05 0.11 0.7171
RASGRP1 1789 5.778e-05 0.11 0.7171
APOL1 1796 6.302e-05 0.11 0.716
GBP1 1824 8.886e-05 0.11 0.7116
Clinical variable #8: 'GENDER'

7 genes related to 'GENDER'.

Table S14.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 106
  MALE 116
     
  Significant markers N = 7
  Higher in MALE 7
  Higher in FEMALE 0
List of 7 genes differentially expressed by 'GENDER'

Table S15.  Get Full Table List of 7 genes differentially expressed by 'GENDER'. 23 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
JARID1D 11915 1.649e-33 1.47e-29 0.969
CYORF15A 11715 2.434e-31 8.67e-28 0.9527
CYORF15B 11471.5 8.419e-29 1.87e-25 0.9329
UTX 3089.5 1.582e-10 1.66e-07 0.7487
HDHD1A 3231.5 1.059e-09 1.05e-06 0.7372
JARID1C 3543.5 5.108e-08 3.64e-05 0.7118
ZRSR1 3661.5 1.986e-07 0.000126 0.7022
Clinical variable #9: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

Table S16.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 167
  YES 13
     
  Significant markers N = 0
Clinical variable #10: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

Table S17.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  COLON ADENOCARCINOMA 129
  COLON MUCINOUS ADENOCARCINOMA 22
  RECTAL ADENOCARCINOMA 58
  RECTAL MUCINOUS ADENOCARCINOMA 7
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S18.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
AGR2 1.439e-10 2.56e-06
PRAC 4.171e-10 2.85e-06
GPX2 4.796e-10 2.85e-06
GFI1 6.503e-10 2.9e-06
SRBD1 4.689e-09 1.54e-05
CEACAM5 5.186e-09 1.54e-05
C20ORF177 9.041e-09 2.04e-05
PLAGL2 9.169e-09 2.04e-05
HOXD8 1.076e-08 2.13e-05
HSP90B3P 1.28e-08 2.24e-05
Clinical variable #11: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

Table S19.  Basic characteristics of clinical feature: 'RESIDUAL_TUMOR'

RESIDUAL_TUMOR Labels N
  R0 185
  R1 2
  R2 29
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
CD274 2.17e-05 0.176
MOCS3 3.348e-05 0.176
LCK 4.481e-05 0.176
FAM114A1 4.724e-05 0.176
RASGRP1 6.161e-05 0.176
NCR1 6.646e-05 0.176
MYST3 6.933e-05 0.176
WARS 9.808e-05 0.177
CCDC139 0.0001072 0.177
BST2 0.000118 0.177
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

Table S21.  Basic characteristics of clinical feature: 'NUMBER_OF_LYMPH_NODES'

NUMBER_OF_LYMPH_NODES Mean (SD) 2.15 (4.7)
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S22.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
LUZP2 0.296 7.575e-06 0.0743
NFKBIZ -0.2947 8.339e-06 0.0743
CXCL2 -0.2841 1.798e-05 0.0934
THEX1 -0.2819 2.098e-05 0.0934
TMEM46 0.2763 3.112e-05 0.111
PPP1R14A 0.2703 4.661e-05 0.119
CXCL3 -0.2699 4.794e-05 0.119
SUCLA2 0.266 6.206e-05 0.119
PDK4 0.2654 6.488e-05 0.119
C5ORF23 0.2649 6.698e-05 0.119
Methods & Data
Input
  • Expresson data file = COADREAD-TP.medianexp.txt

  • Clinical data file = COADREAD-TP.merged_data.txt

  • Number of patients = 222

  • Number of genes = 17814

  • Number of clinical features = 12

Selected clinical features
  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

Survival analysis

For survival clinical features, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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)