Correlation between mRNAseq expression and clinical features
Adrenocortical Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1BR8RHM
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features. The input file "ACC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt" is generated in the pipeline mRNAseq_Preprocess in the stddata run.

Summary

Testing the association between 17733 genes and 11 clinical features across 79 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'.

    • GTSE1|51512 ,  PLK1|5347 ,  H2AFX|3014 ,  LMNB2|84823 ,  MKI67|4288 ,  ...

  • 1 gene correlated to 'YEARS_TO_BIRTH'.

    • FAM40B|57464

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • DIAPH3|81624 ,  YJEFN3|374887 ,  C14ORF80|283643 ,  ZWILCH|55055 ,  C8ORFK29|340393 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • SETD8|387893 ,  FANCI|55215 ,  LMNB2|84823 ,  MCM10|55388 ,  DIAPH3|81624 ,  ...

  • 17 genes correlated to 'GENDER'.

    • CLN8|2055 ,  MAFG|4097 ,  DPYSL2|1808 ,  FAM117A|81558 ,  SFRS8|6433 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • GTSE1|51512 ,  CENPF|1063 ,  MKI67|4288 ,  FOXM1|2305 ,  ARHGAP11B|89839 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • ORC5L|5001 ,  LXN|56925 ,  ELAVL2|1993 ,  FAM63A|55793 ,  STAP2|55620 ,  ...

  • No genes correlated to 'PATHOLOGY_N_STAGE', 'RADIATION_THERAPY', 'HISTOLOGICAL_TYPE', and '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=1 older N=1 younger N=0
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=30 lower stage N=0
PATHOLOGY_N_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=17 male N=17 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test   N=0        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=16 lower number_of_lymph_nodes N=14
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) 4.1-153.6 (median=39.3)
  censored N = 50
  death N = 28
     
  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
GTSE1|51512 7.99e-15 1.4e-10 0.828
PLK1|5347 7.54e-14 4.3e-10 0.842
H2AFX|3014 9.48e-14 4.3e-10 0.788
LMNB2|84823 9.7e-14 4.3e-10 0.856
MKI67|4288 2.46e-13 8.1e-10 0.85
TROAP|10024 2.86e-13 8.1e-10 0.856
RACGAP1|29127 3.75e-13 8.1e-10 0.833
MELK|9833 3.79e-13 8.1e-10 0.857
CDCA8|55143 4.13e-13 8.1e-10 0.831
KIF2C|11004 6.15e-13 1.1e-09 0.825
Clinical variable #2: 'YEARS_TO_BIRTH'

One gene related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 46.7 (16)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of one gene significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
FAM40B|57464 0.4662 1.494e-05 0.265
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 9
  STAGE II 37
  STAGE III 16
  STAGE IV 15
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
DIAPH3|81624 4.974e-06 0.0231
YJEFN3|374887 7.87e-06 0.0231
C14ORF80|283643 8.277e-06 0.0231
ZWILCH|55055 8.88e-06 0.0231
C8ORFK29|340393 9.467e-06 0.0231
CENPJ|55835 9.755e-06 0.0231
TRIP13|9319 1.028e-05 0.0231
DCAF15|90379 1.044e-05 0.0231
MCM10|55388 1.566e-05 0.0309
CCT6P1|643253 1.781e-05 0.0316
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.45 (0.98)
  N
  T1 9
  T2 42
  T3 8
  T4 18
     
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SETD8|387893 0.6277 1.001e-09 1.78e-05
FANCI|55215 0.553 1.838e-07 0.00096
LMNB2|84823 0.5518 1.975e-07 0.00096
MCM10|55388 0.5503 2.166e-07 0.00096
DIAPH3|81624 0.5486 2.88e-07 0.00102
TRIP13|9319 0.5404 3.906e-07 0.00112
C8ORFK29|340393 0.5509 4.413e-07 0.00112
YJEFN3|374887 0.5361 6.006e-07 0.0012
CDK1|983 0.532 6.391e-07 0.0012
UHRF1|29128 0.5302 7.06e-07 0.0012
Clinical variable #5: 'PATHOLOGY_N_STAGE'

No gene related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Labels N
  N0 68
  N1 9
     
  Significant markers N = 0
Clinical variable #6: 'GENDER'

17 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 48
  MALE 31
     
  Significant markers N = 17
  Higher in MALE 17
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 13 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
CLN8|2055 276 2.682e-06 0.00476 0.8145
MAFG|4097 296 7.022e-06 0.0113 0.8011
DPYSL2|1808 316 1.769e-05 0.0234 0.7876
FAM117A|81558 317 1.851e-05 0.0234 0.787
SFRS8|6433 1157 3.449e-05 0.0408 0.7776
CYORF15A|246126 217 4.766e-05 0.0497 1
RND2|8153 343 5.792e-05 0.0571 0.7695
KIAA0100|9703 350 7.788e-05 0.0727 0.7648
TEF|7008 352 8.468e-05 0.0751 0.7634
ACLY|47 362 0.000128 0.0947 0.7567
Clinical variable #7: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 59
  YES 17
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL_TYPE'

No gene related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  ADRENOCORTICAL CARCINOMA- MYXOID TYPE 1
  ADRENOCORTICAL CARCINOMA- ONCOCYTIC TYPE 3
  ADRENOCORTICAL CARCINOMA- USUAL TYPE 75
     
  Significant markers N = 0
Clinical variable #9: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 55
  R1 6
  R2 9
  RX 6
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
GTSE1|51512 1.753e-06 0.00771
CENPF|1063 2.053e-06 0.00771
MKI67|4288 2.608e-06 0.00771
FOXM1|2305 2.995e-06 0.00771
ARHGAP11B|89839 3.496e-06 0.00771
KIF4A|24137 3.875e-06 0.00771
CEP55|55165 4.847e-06 0.00771
CENPM|79019 5.504e-06 0.00771
APOBEC3B|9582 5.802e-06 0.00771
CDK1|983 6.334e-06 0.00771
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.85 (10)
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S17.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
ORC5L|5001 0.7406 9.996e-06 0.124
LXN|56925 -0.724 1.968e-05 0.124
ELAVL2|1993 0.7129 3.011e-05 0.124
FAM63A|55793 -0.7101 3.339e-05 0.124
STAP2|55620 -0.7089 3.488e-05 0.124
CRMP1|1400 0.6911 6.578e-05 0.175
ALDH1B1|219 0.6804 9.426e-05 0.175
NTRK2|4915 0.6744 0.0001144 0.175
GRIN3A|116443 0.674 0.0001159 0.175
HLA-A|3105 -0.674 0.0001159 0.175
Clinical variable #11: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S18.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 30
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = ACC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

  • Number of patients = 79

  • Number of genes = 17733

  • Number of clinical features = 11

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)