Correlation between mRNAseq expression and clinical features
Rectum Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1XW4J84
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/C1XW4J84
Overview
Introduction

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

Summary

Testing the association between 18106 genes and 11 clinical features across 166 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • METT10D|79066 ,  RNGTT|8732 ,  FZD3|7976 ,  LOC100128822|100128822 ,  CALB1|793 ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • AP1S2|8905 ,  TYW1B|441250 ,  FAM164A|51101 ,  TRPC1|7220 ,  RGPD5|84220 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • SCG2|7857 ,  PLN|5350 ,  PRELP|5549 ,  ZFHX4|79776 ,  NEXN|91624 ,  ...

  • 3 genes correlated to 'PATHOLOGY_N_STAGE'.

    • SLC26A5|375611 ,  NEDD4L|23327 ,  C19ORF34|255193

  • 6 genes correlated to 'GENDER'.

    • CYORF15B|84663 ,  CYORF15A|246126 ,  HDHD1A|8226 ,  NCRNA00183|554203 ,  CA5BP|340591 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • SERPINA1|5265 ,  RAB26|25837 ,  SPDEF|25803 ,  TMEM61|199964 ,  TPM1|7168 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'PATHOLOGY_M_STAGE', 'RADIATION_THERAPY', 'RESIDUAL_TUMOR', and 'NUMBER_OF_LYMPH_NODES'.

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=11 younger N=19
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=26 lower stage N=4
PATHOLOGY_N_STAGE Spearman correlation test N=3 higher stage N=0 lower stage N=3
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=6 male N=6 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Wilcoxon test N=30 rectal mucinous adenocarcinoma N=30 rectal adenocarcinoma N=0
RESIDUAL_TUMOR Kruskal-Wallis test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test   N=0        
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) 0.4-129.3 (median=21)
  censored N = 139
  death N = 26
     
  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) 64.65 (12)
  Significant markers N = 30
  pos. correlated 11
  neg. correlated 19
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
METT10D|79066 -0.3584 2.123e-06 0.0384
RNGTT|8732 -0.342 6.503e-06 0.0585
FZD3|7976 -0.3359 9.696e-06 0.0585
LOC100128822|100128822 0.3312 1.309e-05 0.0592
CALB1|793 -0.3658 1.875e-05 0.0679
UBXN7|26043 -0.3224 2.268e-05 0.0685
TOR2A|27433 0.318 2.981e-05 0.0693
MRE11A|4361 -0.3158 3.404e-05 0.0693
CPSF4L|642843 0.384 3.445e-05 0.0693
C7ORF43|55262 0.3132 3.971e-05 0.0693
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 30
  STAGE II 8
  STAGE IIA 40
  STAGE IIB 2
  STAGE IIC 1
  STAGE III 5
  STAGE IIIA 7
  STAGE IIIB 25
  STAGE IIIC 14
  STAGE IV 17
  STAGE IVA 7
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
AP1S2|8905 1.118e-05 0.202
TYW1B|441250 5.052e-05 0.209
FAM164A|51101 5.594e-05 0.209
TRPC1|7220 7.811e-05 0.209
RGPD5|84220 9.084e-05 0.209
ARL2BP|23568 0.0001354 0.209
CFL2|1073 0.0001479 0.209
DPP6|1804 0.0001966 0.209
PLN|5350 0.0002116 0.209
CAPRIN2|65981 0.0002229 0.209
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.8 (0.66)
  N
  T1 9
  T2 28
  T3 113
  T4 14
     
  Significant markers N = 30
  pos. correlated 26
  neg. correlated 4
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SCG2|7857 0.411 5.029e-08 0.000911
PLN|5350 0.3792 5.992e-07 0.0023
PRELP|5549 0.3778 6.109e-07 0.0023
ZFHX4|79776 0.3807 6.29e-07 0.0023
NEXN|91624 0.3773 6.339e-07 0.0023
SPP1|6696 0.368 1.25e-06 0.00377
ASPN|54829 0.362 1.912e-06 0.00412
DPYSL3|1809 0.3613 2.008e-06 0.00412
LOC100126784|100126784 0.3777 2.047e-06 0.00412
HAND2|9464 0.3641 2.39e-06 0.00433
Clinical variable #5: 'PATHOLOGY_N_STAGE'

3 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.69 (0.79)
  N
  N0 84
  N1 45
  N2 33
     
  Significant markers N = 3
  pos. correlated 0
  neg. correlated 3
List of 3 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S9.  Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SLC26A5|375611 -0.5043 2.922e-05 0.262
NEDD4L|23327 -0.3196 3.383e-05 0.262
C19ORF34|255193 -0.4086 4.348e-05 0.262
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 126
  class1 23
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

6 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 75
  MALE 91
     
  Significant markers N = 6
  Higher in MALE 6
  Higher in FEMALE 0
List of 6 genes differentially expressed by 'GENDER'

Table S12.  Get Full Table List of 6 genes differentially expressed by 'GENDER'. 24 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
CYORF15B|84663 1783 2.166e-11 4.36e-08 0.9797
CYORF15A|246126 1682 1.045e-10 1.46e-07 0.9728
HDHD1A|8226 1522 8.647e-10 1.04e-06 0.777
NCRNA00183|554203 1577 2.615e-09 2.49e-06 0.7689
CA5BP|340591 1972 2.976e-06 0.00192 0.7111
DDX43|55510 3126 7.472e-06 0.00451 0.7287
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 112
  YES 21
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  RECTAL ADENOCARCINOMA 147
  RECTAL MUCINOUS ADENOCARCINOMA 13
     
  Significant markers N = 30
  Higher in RECTAL MUCINOUS ADENOCARCINOMA 30
  Higher in RECTAL ADENOCARCINOMA 0
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

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

W(pos if higher in 'RECTAL MUCINOUS ADENOCARCINOMA') wilcoxontestP Q AUC
SERPINA1|5265 1808 1.032e-07 0.00102 0.9461
RAB26|25837 1797 1.503e-07 0.00102 0.9403
SPDEF|25803 1785 2.251e-07 0.00102 0.9341
TMEM61|199964 1742 2.887e-07 0.00102 0.9306
TPM1|7168 1773 3.355e-07 0.00102 0.9278
DRP2|1821 1761 3.375e-07 0.00102 0.9278
C20ORF56|140828 1764 4.508e-07 0.00102 0.9231
TOX|9760 1764 4.508e-07 0.00102 0.9231
FAM174B|400451 1759 5.306e-07 0.00104 0.9205
GNA14|9630 1753 6.443e-07 0.00104 0.9173
Clinical variable #10: 'RESIDUAL_TUMOR'

No gene related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 123
  R1 2
  R2 12
  RX 5
     
  Significant markers N = 0
Clinical variable #11: 'NUMBER_OF_LYMPH_NODES'

No gene related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.67 (5.5)
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = READ-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

  • Number of patients = 166

  • Number of genes = 18106

  • 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)
Copyright © 2016 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle