Correlation between RPPA expression and clinical features
Kidney Chromophobe (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1HQ3Z9Q
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1HQ3Z9Q
Overview
Introduction

This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features. The input file "KICH-TP.rppa.txt" is generated in the pipeline RPPA_AnnotateWithGene in the stddata run.

Summary

Testing the association between 193 genes and 11 clinical features across 63 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one genes.

  • 5 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • SMAD3|SMAD3 ,  PIK3CA |PI3K-P110-ALPHA ,  BCL2L11|BIM ,  ERBB2|HER2_PY1248 ,  EIF4G1|EIF4G

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • YBX1|YB-1 ,  TSC2|TUBERIN_PT1462 ,  YWHAE|14-3-3_EPSILON ,  MAPK14|P38 ,  SFRS1|SF2 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • YBX1|YB-1 ,  TSC2|TUBERIN_PT1462 ,  CHEK1|CHK1_PS345 ,  CAV1|CAVEOLIN-1 ,  MAPK1 MAPK3|MAPK_PT202_Y204 ,  ...

  • 17 genes correlated to 'PATHOLOGY_N_STAGE'.

    • PIK3CA |PI3K-P110-ALPHA ,  ERBB2|HER2_PY1248 ,  SMAD3|SMAD3 ,  CCNB1|CYCLIN_B1 ,  BCL2L11|BIM ,  ...

  • 6 genes correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • SRC|SRC ,  ERBB2|HER2_PY1248 ,  ERBB3|HER3 ,  XBP1|XBP1 ,  TFRC|TFRC ,  ...

  • No genes correlated to 'YEARS_TO_BIRTH', 'PATHOLOGY_M_STAGE', 'GENDER', 'YEAR_OF_TOBACCO_SMOKING_ONSET', 'RACE', 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=5   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test   N=0        
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=16 lower stage N=14
PATHOLOGY_N_STAGE Spearman correlation test N=17 higher stage N=11 lower stage N=6
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=6 higher number_pack_years_smoked N=3 lower number_pack_years_smoked N=3
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test   N=0        
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

5 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) 1-153.7 (median=84.9)
  censored N = 53
  death N = 9
     
  Significant markers N = 5
  associated with shorter survival NA
  associated with longer survival NA
List of 5 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of 5 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
SMAD3|SMAD3 0.000771 0.15 0.178
PIK3CA |PI3K-P110-ALPHA 0.00237 0.15 0.84
BCL2L11|BIM 0.00239 0.15 0.801
ERBB2|HER2_PY1248 0.00615 0.25 0.234
EIF4G1|EIF4G 0.00659 0.25 0.819
Clinical variable #2: 'YEARS_TO_BIRTH'

No gene related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 51.73 (14)
  Significant markers N = 0
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 19
  STAGE II 25
  STAGE III 13
  STAGE IV 6
     
  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
YBX1|YB-1 0.0004048 0.0653
TSC2|TUBERIN_PT1462 0.0008398 0.0653
YWHAE|14-3-3_EPSILON 0.001302 0.0653
MAPK14|P38 0.001743 0.0653
SFRS1|SF2 0.001976 0.0653
EIF4G1|EIF4G 0.00203 0.0653
EIF4EBP1|4E-BP1 0.006025 0.109
MAPK14|P38_PT180_Y182 0.006414 0.109
CAV1|CAVEOLIN-1 0.006771 0.109
IRS1|IRS1 0.007195 0.109
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) 2.03 (0.84)
  N
  T1 19
  T2 25
  T3 17
  T4 2
     
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
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
YBX1|YB-1 0.5159 1.51e-05 0.00291
TSC2|TUBERIN_PT1462 -0.4449 0.0002589 0.025
CHEK1|CHK1_PS345 -0.4278 0.0004708 0.0281
CAV1|CAVEOLIN-1 0.4215 0.0005815 0.0281
MAPK1 MAPK3|MAPK_PT202_Y204 -0.4047 0.001003 0.0387
FRAP1|MTOR_PS2448 -0.3974 0.001261 0.0399
TP53BP1|53BP1 0.3929 0.001446 0.0399
MAPK14|P38_PT180_Y182 -0.3696 0.002874 0.0664
CHEK2|CHK2_PT68 0.365 0.003272 0.0664
IRS1|IRS1 0.3632 0.003441 0.0664
Clinical variable #5: 'PATHOLOGY_N_STAGE'

17 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.16 (0.48)
  N
  N0 39
  N1 3
  N2 2
     
  Significant markers N = 17
  pos. correlated 11
  neg. correlated 6
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
PIK3CA |PI3K-P110-ALPHA 0.4515 0.002095 0.207
ERBB2|HER2_PY1248 -0.4413 0.002714 0.207
SMAD3|SMAD3 -0.4236 0.004165 0.207
CCNB1|CYCLIN_B1 0.4186 0.004682 0.207
BCL2L11|BIM 0.4116 0.005506 0.207
ERBB2|HER2 -0.4047 0.006435 0.207
PIK3R1|PI3K-P85 0.3796 0.01104 0.265
EIF4G1|EIF4G 0.3769 0.01167 0.265
CCNE1|CYCLIN_E1 0.3701 0.01339 0.265
ESR1|ER-ALPHA_PS118 -0.3664 0.01443 0.265
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 33
  class1 2
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 25
  MALE 38
     
  Significant markers N = 0
Clinical variable #8: 'NUMBER_PACK_YEARS_SMOKED'

6 genes related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 25.09 (22)
  Significant markers N = 6
  pos. correlated 3
  neg. correlated 3
List of 6 genes differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

Table S13.  Get Full Table List of 6 genes significantly correlated to 'NUMBER_PACK_YEARS_SMOKED' by Spearman correlation test

SpearmanCorr corrP Q
SRC|SRC -0.8519 0.0008704 0.0956
ERBB2|HER2_PY1248 -0.8474 0.0009907 0.0956
ERBB3|HER3 -0.8246 0.001789 0.115
XBP1|XBP1 0.779 0.004714 0.215
TFRC|TFRC 0.7699 0.005575 0.215
SERPINE1|PAI-1 0.7426 0.00885 0.285
Clinical variable #9: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

No gene related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1973.75 (15)
  Significant markers N = 0
Clinical variable #10: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 2
  BLACK OR AFRICAN AMERICAN 4
  WHITE 55
     
  Significant markers N = 0
Clinical variable #11: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 31
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = KICH-TP.rppa.txt

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

  • Number of patients = 63

  • Number of genes = 193

  • 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)
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