Correlation between RPPA expression and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1X63KJV
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1X63KJV
Overview
Introduction

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

Summary

Testing the association between 166 genes and 8 clinical features across 454 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 39 genes correlated to 'Time to Death'.

    • SRC|SRC_PY527-R-V ,  VASP|VASP-R-C ,  CDKN1A|P21-R-C ,  GAB2|GAB2-R-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  ...

  • 1 gene correlated to 'AGE'.

    • IGFBP2|IGFBP2-R-V

  • 36 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • SRC|SRC_PY527-R-V ,  ERBB3|HER3_PY1298-R-C ,  PECAM1|CD31-M-V ,  CCNB1|CYCLIN_B1-R-V ,  CDH3|P-CADHERIN-R-C ,  ...

  • 36 genes correlated to 'PATHOLOGY.T.STAGE'.

    • ERBB3|HER3_PY1298-R-C ,  CDH3|P-CADHERIN-R-C ,  SRC|SRC_PY527-R-V ,  EEF2|EEF2-R-V ,  ACACA|ACC1-R-C ,  ...

  • 1 gene correlated to 'PATHOLOGY.N.STAGE'.

    • EGFR|EGFR_PY1068-R-V

  • 21 genes correlated to 'PATHOLOGY.M.STAGE'.

    • ERBB3|HER3_PY1298-R-C ,  PECAM1|CD31-M-V ,  YBX1|YB-1-R-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  TP53BP1|53BP1-R-C ,  ...

  • 4 genes correlated to 'GENDER'.

    • AR|AR-R-V ,  PTK2|FAK-R-C ,  SRC|SRC-M-V ,  CLDN7|CLAUDIN-7-R-V

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'

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 Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test N=39 shorter survival N=19 longer survival N=20
AGE Spearman correlation test N=1 older N=1 younger N=0
NEOPLASM DISEASESTAGE ANOVA test N=36        
PATHOLOGY T STAGE Spearman correlation test N=36 higher stage N=17 lower stage N=19
PATHOLOGY N STAGE t test N=1 class1 N=0 class0 N=1
PATHOLOGY M STAGE t test N=21 m1 N=8 m0 N=13
GENDER t test N=4 male N=2 female N=2
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
Clinical variable #1: 'Time to Death'

39 genes related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.1-120.6 (median=37)
  censored N = 296
  death N = 158
     
  Significant markers N = 39
  associated with shorter survival 19
  associated with longer survival 20
List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

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
SRC|SRC_PY527-R-V 0.54 5.903e-12 9.8e-10 0.371
VASP|VASP-R-C 4.2 1.001e-11 1.7e-09 0.634
CDKN1A|P21-R-C 6.2 5.491e-11 9e-09 0.625
GAB2|GAB2-R-V 0.5 2.439e-10 4e-08 0.355
MAPK1 MAPK3|MAPK_PT202_Y204-R-V 0.6 9.145e-10 1.5e-07 0.352
PRKAA1|AMPK_PT172-R-V 0.46 9.676e-10 1.6e-07 0.372
CTNNA1|ALPHA-CATENIN-M-V 0.21 1.282e-09 2.1e-07 0.362
AR|AR-R-V 0.33 1.85e-09 2.9e-07 0.352
ACACA|ACC1-R-C 2.5 2.024e-09 3.2e-07 0.623
CCNB1|CYCLIN_B1-R-V 1.76 2.4e-09 3.8e-07 0.58

Figure S1.  Get High-res Image As an example, this figure shows the association of SRC|SRC_PY527-R-V to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 5.9e-12 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

One gene related to 'AGE'.

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

AGE Mean (SD) 60.42 (12)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
IGFBP2|IGFBP2-R-V 0.2272 1.022e-06 0.00017

Figure S2.  Get High-res Image As an example, this figure shows the association of IGFBP2|IGFBP2-R-V to 'AGE'. P value = 1.02e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

36 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 219
  STAGE II 44
  STAGE III 115
  STAGE IV 76
     
  Significant markers N = 36
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'

ANOVA_P Q
SRC|SRC_PY527-R-V 2.708e-11 4.5e-09
ERBB3|HER3_PY1298-R-C 2.833e-11 4.67e-09
PECAM1|CD31-M-V 1.073e-10 1.76e-08
CCNB1|CYCLIN_B1-R-V 5.227e-10 8.52e-08
CDH3|P-CADHERIN-R-C 1.87e-09 3.03e-07
MAPK1 MAPK3|MAPK_PT202_Y204-R-V 1.511e-08 2.43e-06
CTNNA1|ALPHA-CATENIN-M-V 1.597e-08 2.55e-06
YBX1|YB-1_PS102-R-V 9.994e-08 1.59e-05
EEF2|EEF2-R-V 1.17e-07 1.85e-05
RAF1|C-RAF_PS338-R-C 1.537e-07 2.41e-05

Figure S3.  Get High-res Image As an example, this figure shows the association of SRC|SRC_PY527-R-V to 'NEOPLASM.DISEASESTAGE'. P value = 2.71e-11 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

36 genes related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.92 (0.97)
  N
  1 224
  2 54
  3 165
  4 11
     
  Significant markers N = 36
  pos. correlated 17
  neg. correlated 19
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
ERBB3|HER3_PY1298-R-C -0.3199 2.924e-12 4.85e-10
CDH3|P-CADHERIN-R-C 0.3122 1.007e-11 1.66e-09
SRC|SRC_PY527-R-V -0.29 3.005e-10 4.93e-08
EEF2|EEF2-R-V 0.2873 4.478e-10 7.3e-08
ACACA|ACC1-R-C 0.276 2.209e-09 3.58e-07
SHC1|SHC_PY317-R-NA -0.2717 4.011e-09 6.46e-07
CTNNA1|ALPHA-CATENIN-M-V -0.2703 4.814e-09 7.7e-07
PECAM1|CD31-M-V -0.2677 6.88e-09 1.09e-06
ACACA ACACB|ACC_PS79-R-V 0.2667 7.847e-09 1.24e-06
YBX1|YB-1_PS102-R-V 0.2618 1.497e-08 2.35e-06

Figure S4.  Get High-res Image As an example, this figure shows the association of ERBB3|HER3_PY1298-R-C to 'PATHOLOGY.T.STAGE'. P value = 2.92e-12 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

One gene related to 'PATHOLOGY.N.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 208
  class1 16
     
  Significant markers N = 1
  Higher in class1 0
  Higher in class0 1
List of one gene differentially expressed by 'PATHOLOGY.N.STAGE'

Table S10.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY.N.STAGE'

T(pos if higher in 'class1') ttestP Q AUC
EGFR|EGFR_PY1068-R-V -5.09 5.522e-05 0.00917 0.7713

Figure S5.  Get High-res Image As an example, this figure shows the association of EGFR|EGFR_PY1068-R-V to 'PATHOLOGY.N.STAGE'. P value = 5.52e-05 with T-test analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

21 genes related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 379
  M1 75
     
  Significant markers N = 21
  Higher in M1 8
  Higher in M0 13
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'

T(pos if higher in 'M1') ttestP Q AUC
ERBB3|HER3_PY1298-R-C -6.81 2.114e-10 3.51e-08 0.6955
PECAM1|CD31-M-V -5.51 1.939e-07 3.2e-05 0.6715
YBX1|YB-1-R-V 5.13 1.037e-06 0.00017 0.664
MAPK1 MAPK3|MAPK_PT202_Y204-R-V -4.92 3.087e-06 0.000503 0.6609
TP53BP1|53BP1-R-C 4.88 3.333e-06 0.00054 0.6785
PIK3R1|PI3K-P85-R-V 4.91 3.643e-06 0.000586 0.6823
PEA15|PEA-15-R-V 4.68 8.298e-06 0.00133 0.6655
ERRFI1|MIG-6-M-V -4.56 1.126e-05 0.00179 0.6328
RAF1|C-RAF_PS338-R-C -4.32 3.263e-05 0.00516 0.6356
RPS6|S6-R-NA 4.31 3.455e-05 0.00542 0.6285

Figure S6.  Get High-res Image As an example, this figure shows the association of ERBB3|HER3_PY1298-R-C to 'PATHOLOGY.M.STAGE'. P value = 2.11e-10 with T-test analysis.

Clinical variable #7: 'GENDER'

4 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 151
  MALE 303
     
  Significant markers N = 4
  Higher in MALE 2
  Higher in FEMALE 2
List of 4 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of 4 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
AR|AR-R-V 4.46 1.114e-05 0.00185 0.6217
PTK2|FAK-R-C -3.94 0.0001041 0.0172 0.6098
SRC|SRC-M-V -3.87 0.0001383 0.0227 0.6106
CLDN7|CLAUDIN-7-R-V 3.81 0.0001643 0.0268 0.6269

Figure S7.  Get High-res Image As an example, this figure shows the association of AR|AR-R-V to 'GENDER'. P value = 1.11e-05 with T-test analysis.

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) 93.53 (7.7)
  Score N
  70 1
  80 3
  90 13
  100 17
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 454

  • Number of genes = 166

  • Number of clinical features = 8

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

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] 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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