Correlation between mRNAseq expression and clinical features
Bladder Urothelial Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1XD111T
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/C1XD111T
Overview
Introduction

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

Summary

Testing the association between 18215 genes and 13 clinical features across 408 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 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • GSDMB|55876 ,  PMP2|5375 ,  LIPT1|51601 ,  BCL2L14|79370 ,  EHBP1|23301 ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • FAM111A|63901 ,  APLNR|187 ,  PLA2G5|5322 ,  LRRC49|54839 ,  CXCL12|6387 ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • SFRP2|6423 ,  COL10A1|1300 ,  SFRP4|6424 ,  SSC5D|284297 ,  ISLR|3671 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • CCDC80|151887 ,  LRIG1|26018 ,  SFRP4|6424 ,  SSC5D|284297 ,  CTHRC1|115908 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • IL1R1|3554 ,  MESP1|55897 ,  C15ORF48|84419 ,  ISLR|3671 ,  P4HA3|283208 ,  ...

  • 8 genes correlated to 'GENDER'.

    • HDHD1A|8226 ,  CYORF15A|246126 ,  CYORF15B|84663 ,  NCRNA00183|554203 ,  ORC5L|5001 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • ZNF266|10781 ,  PRPF39|55015 ,  WDR27|253769 ,  LOC100131434|100131434 ,  OGT|8473 ,  ...

  • 30 genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • DGKA|1606 ,  S1PR3|1903 ,  ANXA3|306 ,  APBB1IP|54518 ,  ACIN1|22985 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • GDPD3|79153 ,  MAL|4118 ,  MCEE|84693 ,  IL1R1|3554 ,  SLC44A2|57153 ,  ...

  • 30 genes correlated to 'RACE'.

    • CALU|813 ,  XKR9|389668 ,  WFIKKN1|117166 ,  JMJD7-PLA2G4B|8681 ,  TXNRD1|7296 ,  ...

  • No genes correlated to 'PATHOLOGY_M_STAGE', 'NUMBER_PACK_YEARS_SMOKED', 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=30 older N=20 younger N=10
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 Spearman correlation test N=30 higher stage N=26 lower stage N=4
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=8 male N=8 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=30 higher score N=18 lower score N=12
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=29 lower number_of_lymph_nodes N=1
RACE Kruskal-Wallis test N=30        
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) 0.4-166 (median=17.6)
  censored N = 227
  death N = 180
     
  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
GSDMB|55876 1.58e-07 0.0017 0.367
PMP2|5375 1.84e-07 0.0017 0.549
LIPT1|51601 2.86e-07 0.0017 0.379
BCL2L14|79370 1.33e-06 0.0061 0.365
EHBP1|23301 9.28e-06 0.027 0.613
LOC115110|115110 1.2e-05 0.027 0.371
ZSCAN16|80345 1.27e-05 0.027 0.394
LOC91316|91316 1.3e-05 0.027 0.391
NCRNA00185|55410 1.35e-05 0.027 0.427
ZNF524|147807 1.74e-05 0.032 0.4
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) 68.06 (11)
  Significant markers N = 30
  pos. correlated 20
  neg. correlated 10
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
FAM111A|63901 -0.247 4.513e-07 0.00822
APLNR|187 0.2331 1.992e-06 0.00867
PLA2G5|5322 0.2349 2.034e-06 0.00867
LRRC49|54839 -0.2317 2.318e-06 0.00867
CXCL12|6387 0.2311 2.443e-06 0.00867
FGF7|2252 0.2286 3.18e-06 0.00867
ITGA7|3679 0.2281 3.332e-06 0.00867
MED8|112950 0.2254 4.36e-06 0.00886
PLN|5350 0.2273 4.377e-06 0.00886
HAS1|3036 0.2345 5.448e-06 0.00923
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 2
  STAGE II 130
  STAGE III 140
  STAGE IV 134
     
  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
SFRP2|6423 1.732e-14 3.16e-10
COL10A1|1300 5.099e-14 4.64e-10
SFRP4|6424 9.652e-14 5.86e-10
SSC5D|284297 4.248e-13 1.93e-09
ISLR|3671 5.582e-13 2.03e-09
COL6A3|1293 8.672e-13 2.45e-09
FNDC1|84624 1.071e-12 2.45e-09
CTHRC1|115908 1.075e-12 2.45e-09
CCDC80|151887 2.057e-12 4.16e-09
COL1A1|1277 2.517e-12 4.34e-09
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) 2.81 (0.7)
  N
  T0 1
  T1 3
  T2 119
  T3 194
  T4 58
     
  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
CCDC80|151887 0.3256 1.033e-10 1.88e-06
LRIG1|26018 0.3169 3.406e-10 2.44e-06
SFRP4|6424 0.318 5.376e-10 2.44e-06
SSC5D|284297 0.3128 5.928e-10 2.44e-06
CTHRC1|115908 0.3111 7.417e-10 2.44e-06
FNDC1|84624 0.3132 8.051e-10 2.44e-06
LRRN2|10446 0.3098 1.33e-09 2.69e-06
FIBIN|387758 0.3075 1.378e-09 2.69e-06
VCAN|1462 0.3058 1.463e-09 2.69e-06
WISP1|8840 0.3062 1.476e-09 2.69e-06
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.6 (0.88)
  N
  N0 237
  N1 46
  N2 75
  N3 8
     
  Significant markers N = 30
  pos. correlated 26
  neg. correlated 4
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
IL1R1|3554 0.2956 8.18e-09 0.000149
MESP1|55897 0.2769 8.93e-08 0.000464
C15ORF48|84419 0.2723 1.213e-07 0.000464
ISLR|3671 0.2716 1.305e-07 0.000464
P4HA3|283208 0.2714 1.344e-07 0.000464
COPG|22820 0.2696 1.636e-07 0.000464
MCEE|84693 0.2683 1.878e-07 0.000464
CSDC2|27254 0.2708 2.038e-07 0.000464
PTGIS|5740 0.2627 3.434e-07 0.000494
COL8A2|1296 0.2624 3.539e-07 0.000494
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 196
  class1 11
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

8 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 107
  MALE 301
     
  Significant markers N = 8
  Higher in MALE 8
  Higher in FEMALE 0
List of 8 genes differentially expressed by 'GENDER'

Table S13.  Get Full Table List of 8 genes differentially expressed by 'GENDER'. 22 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
HDHD1A|8226 8870 6.317e-12 9.59e-09 0.7237
CYORF15A|246126 4176 4.084e-10 4.96e-07 0.9943
CYORF15B|84663 3856 3.119e-09 3.22e-06 0.9854
NCRNA00183|554203 11216 3.095e-06 0.00219 0.6518
ORC5L|5001 11218 3.124e-06 0.00219 0.6517
CARD10|29775 11401 7.195e-06 0.00485 0.646
LOC100130987|100130987 20592.5 1.835e-05 0.0115 0.6394
PTPN20B|26095 17351.5 2.829e-05 0.0172 0.642
Clinical variable #8: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 362
  YES 20
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

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

W(pos if higher in 'YES') wilcoxontestP Q AUC
ZNF266|10781 6044 4.618e-07 0.00841 0.8348
PRPF39|55015 5867 2.963e-06 0.0144 0.8104
WDR27|253769 5855 3.345e-06 0.0144 0.8087
LOC100131434|100131434 5825 4.519e-06 0.0144 0.8046
OGT|8473 5817 4.893e-06 0.0144 0.8035
LOC619207|619207 5742 6.419e-06 0.0144 0.7997
TUBGCP6|85378 5777 7.253e-06 0.0144 0.7979
ATG16L2|89849 5767 7.995e-06 0.0144 0.7965
NCRNA00201|284702 5760 8.557e-06 0.0144 0.7956
SLC25A27|9481 5725 8.853e-06 0.0144 0.7951
Clinical variable #9: 'KARNOFSKY_PERFORMANCE_SCORE'

30 genes related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 82.99 (14)
  Significant markers N = 30
  pos. correlated 18
  neg. correlated 12
List of top 10 genes differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

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

SpearmanCorr corrP Q
DGKA|1606 -0.4484 5.529e-08 0.000572
S1PR3|1903 0.4467 6.281e-08 0.000572
ANXA3|306 0.4393 1.099e-07 0.000667
APBB1IP|54518 0.4333 1.702e-07 0.000775
ACIN1|22985 -0.4177 5.126e-07 0.00151
MRAS|22808 0.4162 5.703e-07 0.00151
LOC283070|283070 -0.4142 6.5e-07 0.00151
SLC9A1|6548 -0.414 6.628e-07 0.00151
AP1G2|8906 -0.4095 8.967e-07 0.00181
NUCB2|4925 0.4075 1.028e-06 0.00187
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

No gene related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 39.16 (53)
  Significant markers N = 0
Clinical variable #11: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.1 (7)
  Significant markers N = 30
  pos. correlated 29
  neg. correlated 1
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S20.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
GDPD3|79153 0.3056 9.448e-08 0.00138
MAL|4118 0.3008 1.694e-07 0.00138
MCEE|84693 0.2938 3.041e-07 0.00138
IL1R1|3554 0.2931 3.264e-07 0.00138
SLC44A2|57153 0.2915 3.798e-07 0.00138
ANXA9|8416 0.2773 1.424e-06 0.00372
MYH14|79784 0.276 1.608e-06 0.00372
TTYH1|57348 0.2754 1.834e-06 0.00372
PRSS27|83886 0.2745 1.837e-06 0.00372
KCNG1|3755 0.2731 2.077e-06 0.00378
Clinical variable #12: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  ASIAN 44
  BLACK OR AFRICAN AMERICAN 23
  WHITE 324
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
CALU|813 1.749e-11 2.45e-07
XKR9|389668 3.939e-11 2.45e-07
WFIKKN1|117166 5.372e-11 2.45e-07
JMJD7-PLA2G4B|8681 5.382e-11 2.45e-07
TXNRD1|7296 8.847e-11 3.22e-07
ZFPM1|161882 1.206e-10 3.66e-07
CLIC4|25932 1.529e-10 3.98e-07
MMD|23531 1.798e-10 4.09e-07
C15ORF17|57184 2.166e-10 4.12e-07
ARHGEF10L|55160 2.318e-10 4.12e-07
Clinical variable #13: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S23.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 8
  NOT HISPANIC OR LATINO 368
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 408

  • Number of genes = 18215

  • Number of clinical features = 13

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