Correlation between mRNA expression and clinical features
Glioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1J38RX9
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/C1J38RX9
Overview
Introduction

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

Summary

Testing the association between 12042 genes and 8 clinical features across 525 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • RANBP17 ,  NNMT ,  NCOA4 ,  CCDC46 ,  HIST3H2A ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • FBXO17 ,  KIAA0495 ,  RANBP17 ,  NOL3 ,  TUSC3 ,  ...

  • 13 genes correlated to 'GENDER'.

    • JARID1D ,  CYORF15B ,  HDHD1A ,  UTX ,  JARID1C ,  ...

  • 1 gene correlated to 'RADIATION_THERAPY'.

    • HOXD11

  • 30 genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • TM4SF20 ,  ZBP1 ,  CNGA1 ,  COPG ,  FASLG ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • PDIA6 ,  NPM1 ,  HNRPF ,  ALDH18A1 ,  NPM3 ,  ...

  • 3 genes correlated to 'RACE'.

    • CRYBB2 ,  PSPH ,  P2RX5

  • No genes correlated to 'ETHNICITY'

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=30   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=21 younger N=9
GENDER Wilcoxon test N=13 male N=13 female N=0
RADIATION_THERAPY Wilcoxon test N=1 yes N=1 no N=0
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=30 higher score N=20 lower score N=10
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RACE Kruskal-Wallis test N=3        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes 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) 0.1-127.6 (median=12.4)
  censored N = 76
  death N = 448
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
RANBP17 2.19e-09 2.6e-05 0.413
NNMT 6.75e-08 0.00041 0.532
NCOA4 2.3e-07 0.00092 0.437
CCDC46 6.15e-07 0.0015 0.56
HIST3H2A 6.38e-07 0.0015 0.422
FMOD 1.12e-06 0.0023 0.552
ZIC3 1.63e-06 0.0028 0.433
EFEMP2 3.25e-06 0.0047 0.553
MEOX2 3.54e-06 0.0047 0.527
ALCAM 6.02e-06 0.0072 0.481
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

Table S3.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 57.68 (15)
  Significant markers N = 30
  pos. correlated 21
  neg. correlated 9
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
FBXO17 0.3074 5.924e-13 7.13e-09
KIAA0495 0.2949 5.437e-12 3.27e-08
RANBP17 -0.2916 9.501e-12 3.81e-08
NOL3 0.2831 3.903e-11 1.18e-07
TUSC3 -0.2761 1.217e-10 2.93e-07
C14ORF45 0.2726 2.115e-10 4.25e-07
DRG2 0.2617 1.147e-09 1.97e-06
C5ORF21 0.2498 6.579e-09 9.9e-06
CBR1 0.2455 1.203e-08 1.39e-05
H2AFY2 -0.2455 1.206e-08 1.39e-05
Clinical variable #3: 'GENDER'

13 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 205
  MALE 320
     
  Significant markers N = 13
  Higher in MALE 13
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 17 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
JARID1D 62786 5.665e-70 3.41e-66 0.9571
CYORF15B 61883 6.228e-66 1.25e-62 0.9433
HDHD1A 15478 1.702e-24 2.05e-21 0.7641
UTX 20401 2.639e-13 2.44e-10 0.689
JARID1C 20621 6.875e-13 5.91e-10 0.6857
CXORF15 24198 3.927e-07 0.000249 0.6311
GPR88 41229 6.68e-07 0.000402 0.6285
RCAN2 40921 1.678e-06 0.000962 0.6238
ADAM20 25476 1.569e-05 0.00787 0.6116
MKL2 39885 2.943e-05 0.0136 0.608
Clinical variable #4: 'RADIATION_THERAPY'

One gene related to 'RADIATION_THERAPY'.

Table S7.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 70
  YES 435
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one gene differentially expressed by 'RADIATION_THERAPY'

Table S8.  Get Full Table List of one gene differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HOXD11 10359 1.756e-05 0.211 0.6598
Clinical variable #5: 'KARNOFSKY_PERFORMANCE_SCORE'

30 genes related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 77.15 (15)
  Significant markers N = 30
  pos. correlated 20
  neg. correlated 10
List of top 10 genes differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY_PERFORMANCE_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
TM4SF20 0.2672 6.689e-08 0.000805
ZBP1 0.2496 4.897e-07 0.00295
CNGA1 0.2287 4.286e-06 0.0172
COPG -0.2136 1.815e-05 0.0547
FASLG 0.206 3.601e-05 0.0651
CMA1 0.2049 3.992e-05 0.0651
EN2 -0.2007 5.75e-05 0.0651
PPP3R1 -0.2004 5.902e-05 0.0651
ALKBH4 -0.1972 7.814e-05 0.0651
MLN 0.1961 8.523e-05 0.0651
Clinical variable #6: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

Table S11.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  GLIOBLASTOMA MULTIFORME (GBM) 6
  TREATED PRIMARY GBM 20
  UNTREATED PRIMARY (DE NOVO) GBM 499
     
  Significant markers N = 30
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'

kruskal_wallis_P Q
PDIA6 1.192e-07 0.000518
NPM1 1.195e-07 0.000518
HNRPF 1.385e-07 0.000518
ALDH18A1 1.721e-07 0.000518
NPM3 2.897e-07 0.000651
SSR2 3.4e-07 0.000651
TCTN3 5.104e-07 0.000651
ABT1 6.676e-07 0.000651
SLC1A5 6.683e-07 0.000651
MRPS16 6.819e-07 0.000651
Clinical variable #7: 'RACE'

3 genes related to 'RACE'.

Table S13.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 13
  BLACK OR AFRICAN AMERICAN 31
  WHITE 462
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'RACE'

Table S14.  Get Full Table List of 3 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
CRYBB2 5.444e-07 0.00656
PSPH 1.078e-05 0.0649
P2RX5 3.303e-05 0.133
Clinical variable #8: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S15.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 12
  NOT HISPANIC OR LATINO 438
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 525

  • Number of genes = 12042

  • Number of clinical features = 8

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)
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