Correlation between RPPA expression and clinical features
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1X63M03
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1X63M03
Overview
Introduction

This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 192 genes and 12 clinical features across 204 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • ASNS|ASNS-R-V ,  MSH6|MSH6-R-C ,  SQSTM1|P62-LCK-LIGAND-M-C ,  CCNB1|CYCLIN_B1-R-V ,  FN1|FIBRONECTIN-R-V ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • RPS6KB1|P70S6K_PT389-R-V ,  NRAS|N-RAS-M-V ,  SCD1|SCD1-M-V ,  PECAM1|CD31-M-V ,  TP53|P53-R-E ,  ...

  • 30 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • CTNNB1|ALPHA-CATENIN-M-V ,  CCNB1|CYCLIN_B1-R-V ,  FN1|FIBRONECTIN-R-V ,  SQSTM1|P62-LCK-LIGAND-M-C ,  YWHAE|14-3-3_EPSILON-M-C ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • CTNNB1|ALPHA-CATENIN-M-V ,  FN1|FIBRONECTIN-R-V ,  CCNB1|CYCLIN_B1-R-V ,  G6PD|G6PD-M-V ,  SQSTM1|P62-LCK-LIGAND-M-C ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • MSH6|MSH6-R-C ,  CTNNB1|ALPHA-CATENIN-M-V ,  FN1|FIBRONECTIN-R-V ,  VHL|VHL-M-C ,  YWHAE|14-3-3_EPSILON-M-C ,  ...

  • 27 genes correlated to 'PATHOLOGY_M_STAGE'.

    • CTNNB1|ALPHA-CATENIN-M-V ,  FASN|FASN-R-V ,  ANXA7 |ANNEXIN_VII-M-V ,  TFRC|TFRC-R-V ,  YWHAE|14-3-3_EPSILON-M-C ,  ...

  • 28 genes correlated to 'GENDER'.

    • YWHAE|14-3-3_EPSILON-M-C ,  PDK1|PDK1-R-V ,  RICTOR|RICTOR-R-C ,  MSH6|MSH6-R-C ,  IGFBP2|IGFBP2-R-V ,  ...

  • 1 gene correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • EGFR|EGFR-R-V

  • No genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE', 'NUMBER_PACK_YEARS_SMOKED', '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=30 shorter survival N=19 longer survival N=11
YEARS_TO_BIRTH Spearman correlation test N=30 older N=21 younger N=9
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=14 lower stage N=16
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=13 lower stage N=17
PATHOLOGY_M_STAGE Wilcoxon test N=27 class1 N=27 class0 N=0
GENDER Wilcoxon test N=28 male N=28 female N=0
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=1 higher year_of_tobacco_smoking_onset N=0 lower year_of_tobacco_smoking_onset N=1
RACE Kruskal-Wallis test   N=0        
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) 0.1-194.8 (median=20.1)
  censored N = 178
  death N = 25
     
  Significant markers N = 30
  associated with shorter survival 19
  associated with longer survival 11
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

HazardRatio Wald_P Q C_index
ASNS|ASNS-R-V 6.1 5.315e-06 0.001 0.771
MSH6|MSH6-R-C 8.3 6.69e-05 0.0057 0.676
SQSTM1|P62-LCK-LIGAND-M-C 2.1 8.912e-05 0.0057 0.639
CCNB1|CYCLIN_B1-R-V 4.8 0.0001929 0.0088 0.706
FN1|FIBRONECTIN-R-V 1.8 0.0002285 0.0088 0.705
RB1|RB_PS807_S811-R-V 3 0.0003147 0.0097 0.623
FASN|FASN-R-V 3.4 0.0004027 0.0097 0.753
YWHAE|14-3-3_EPSILON-M-C 0.05 0.0004056 0.0097 0.295
EIF4EBP1|4E-BP1_PS65-R-V 4.9 0.0005573 0.011 0.684
ANXA7 |ANNEXIN_VII-M-V 0.0600000000000001 0.0005985 0.011 0.282
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) 61.08 (12)
  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
RPS6KB1|P70S6K_PT389-R-V 0.4148 1.017e-09 1.95e-07
NRAS|N-RAS-M-V 0.3643 1.137e-07 7.37e-06
SCD1|SCD1-M-V 0.3642 1.152e-07 7.37e-06
PECAM1|CD31-M-V 0.3599 1.656e-07 7.95e-06
TP53|P53-R-E 0.3527 3.013e-07 1.16e-05
BAK1|BAK-R-E 0.346 5.194e-07 1.48e-05
SMAD4|SMAD4-M-V 0.3444 5.938e-07 1.48e-05
FOXO3|FOXO3A-R-C 0.3439 6.183e-07 1.48e-05
CDC2|CDK1-R-V 0.3288 1.993e-06 4.25e-05
FOXM1|FOXM1-R-V 0.3253 2.593e-06 4.98e-05
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

30 genes related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 126
  STAGE II 15
  STAGE III 43
  STAGE IV 13
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

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

kruskal_wallis_P Q
CTNNB1|ALPHA-CATENIN-M-V 3.626e-09 6.96e-07
CCNB1|CYCLIN_B1-R-V 5.549e-07 5.33e-05
FN1|FIBRONECTIN-R-V 4.147e-06 0.000252
SQSTM1|P62-LCK-LIGAND-M-C 5.256e-06 0.000252
YWHAE|14-3-3_EPSILON-M-C 6.727e-06 0.000258
G6PD|G6PD-M-V 9.556e-06 0.000296
CLDN7|CLAUDIN-7-R-V 1.078e-05 0.000296
FRAP1|MTOR_PS2448-R-C 1.555e-05 0.000373
CCNE1|CYCLIN_E1-M-V 2.031e-05 0.000433
STAT3|STAT3_PY705-R-V 2.487e-05 0.000477
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) 1.6 (0.88)
  N
  T1 131
  T2 22
  T3 47
  T4 2
     
  Significant markers N = 30
  pos. correlated 14
  neg. correlated 16
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
CTNNB1|ALPHA-CATENIN-M-V -0.4416 4.736e-11 9.09e-09
FN1|FIBRONECTIN-R-V 0.3947 6.156e-09 5.91e-07
CCNB1|CYCLIN_B1-R-V 0.3735 4.362e-08 2.79e-06
G6PD|G6PD-M-V 0.3426 5.987e-07 2.87e-05
SQSTM1|P62-LCK-LIGAND-M-C 0.3373 9.198e-07 3.23e-05
CLDN7|CLAUDIN-7-R-V -0.3361 1.008e-06 3.23e-05
VHL|VHL-M-C -0.3275 1.953e-06 5.36e-05
NOTCH1|NOTCH1-R-V 0.3165 4.471e-06 0.000107
CCNE1|CYCLIN_E1-M-V 0.3115 6.419e-06 0.000125
FRAP1|MTOR_PS2448-R-C -0.3113 6.486e-06 0.000125
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) 0.42 (0.61)
  N
  N0 42
  N1 19
  N2 4
     
  Significant markers N = 30
  pos. correlated 13
  neg. correlated 17
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
MSH6|MSH6-R-C 0.5521 1.861e-06 0.000357
CTNNB1|ALPHA-CATENIN-M-V -0.5292 5.847e-06 0.000561
FN1|FIBRONECTIN-R-V 0.5115 1.334e-05 0.000854
VHL|VHL-M-C -0.4834 4.527e-05 0.00217
YWHAE|14-3-3_EPSILON-M-C -0.4504 0.000167 0.00593
IGFBP2|IGFBP2-R-V 0.445 0.0002041 0.00593
CLDN7|CLAUDIN-7-R-V -0.4434 0.0002164 0.00593
FASN|FASN-R-V 0.4311 0.0003376 0.0081
SCD1|SCD1-M-V -0.4042 0.0008395 0.0173
ANXA7 |ANNEXIN_VII-M-V -0.4021 0.0009004 0.0173
Clinical variable #6: 'PATHOLOGY_M_STAGE'

27 genes related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 69
  class1 8
     
  Significant markers N = 27
  Higher in class1 27
  Higher in class0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
CTNNB1|ALPHA-CATENIN-M-V 72 0.0006805 0.131 0.8696
FASN|FASN-R-V 466 0.001558 0.15 0.8442
ANXA7 |ANNEXIN_VII-M-V 105 0.004421 0.183 0.8098
TFRC|TFRC-R-V 447 0.004421 0.183 0.8098
YWHAE|14-3-3_EPSILON-M-C 107 0.004908 0.183 0.8062
FOXO3|FOXO3A_PS318_S321-R-C 110 0.005728 0.183 0.8007
SCD1|SCD1-M-V 115 0.007374 0.185 0.7917
RICTOR|RICTOR-R-C 431 0.0099 0.185 0.7808
CCNE1|CYCLIN_E1-M-V 430 0.01039 0.185 0.779
MSH6|MSH6-R-C 430 0.01039 0.185 0.779
Clinical variable #7: 'GENDER'

28 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 56
  MALE 148
     
  Significant markers N = 28
  Higher in MALE 28
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 2 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
YWHAE|14-3-3_EPSILON-M-C 5807 9.95e-06 0.00122 0.7007
PDK1|PDK1-R-V 5787 1.271e-05 0.00122 0.6982
RICTOR|RICTOR-R-C 2723 0.0001599 0.00965 0.6715
MSH6|MSH6-R-C 2766 0.0002514 0.00965 0.6663
IGFBP2|IGFBP2-R-V 2815 0.0004146 0.0124 0.6604
ANXA7 |ANNEXIN_VII-M-V 5458 0.0004817 0.0124 0.6585
EGFR|EGFR_PY1173-R-V 5451 0.0005163 0.0124 0.6577
CCNE1|CYCLIN_E1-M-V 2923 0.00118 0.0252 0.6473
CLDN7|CLAUDIN-7-R-V 5328 0.001659 0.0319 0.6429
MET|C-MET_PY1235-R-V 5276 0.002638 0.0429 0.6366
Clinical variable #8: 'KARNOFSKY_PERFORMANCE_SCORE'

No gene related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 95.58 (5.5)
  Score N
  80 1
  90 17
  100 25
     
  Significant markers N = 0
Clinical variable #9: 'NUMBER_PACK_YEARS_SMOKED'

No gene related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 31.18 (28)
  Significant markers N = 0
Clinical variable #10: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

One gene related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1970.71 (15)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S18.  Get Full Table List of one gene significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
EGFR|EGFR-R-V -0.4793 0.001322 0.254
Clinical variable #11: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 5
  BLACK OR AFRICAN AMERICAN 44
  WHITE 141
     
  Significant markers N = 0
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S20.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 168
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 204

  • Number of genes = 192

  • Number of clinical features = 12

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • 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, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

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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