Kidney Renal Clear Cell Carcinoma: Correlation between RPPA expression and clinical features
Maintained by Juok Cho (Broad Institute)
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 9 clinical features across 454 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

- 38 genes correlated to 'Time to Death'.

- VASP|VASP-R-C , SRC|SRC_PY527-R-V , CDKN1A|P21-R-C , GAB2|GAB2-R-V , ACACA|ACC1-R-C , ...

- 1 gene correlated to 'AGE'.

- IGFBP2|IGFBP2-R-V

- 4 genes correlated to 'GENDER'.

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

- 36 genes correlated to 'PATHOLOGY.T'.

- 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'.

- EGFR|EGFR_PY1068-R-V

- 23 genes correlated to 'PATHOLOGICSPREAD(M)'.

- 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 , ...

- 42 genes correlated to 'TUMOR.STAGE'.

- ERBB3|HER3_PY1298-R-C , CDH3|P-CADHERIN-R-C , SRC|SRC_PY527-R-V , SHC1|SHC_PY317-R-NA , PECAM1|CD31-M-V , ...

- No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', and 'NEOADJUVANT.THERAPY'.

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=38 | shorter survival | N=18 | longer survival | N=20
AGE | Spearman correlation test | N=1 | older | N=1 | younger | N=0
GENDER | t test | N=4 | male | N=2 | female | N=2
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 |  |  |  |
PATHOLOGY T | Spearman correlation test | N=36 | higher pT | N=17 | lower pT | N=19
PATHOLOGY N | t test | N=1 | n1 | N=0 | n0 | N=1
PATHOLOGICSPREAD(M) | t test | N=23 | m1 | N=8 | m0 | N=15
TUMOR STAGE | Spearman correlation test | N=42 | higher stage | N=19 | lower stage | N=23
NEOADJUVANT THERAPY | t test | N=0 |  |  |  |

Clinical variable #1: 'Time to Death'

38 genes related to 'Time to Death'.

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

Time to Death | Duration (Months) | 0.1-111 (median=34.3)
| censored | N = 301
| death | N = 150
| Significant markers | N = 38
| associated with shorter survival | 18
| 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
--- | --- | --- | --- | ---
VASP|VASP-R-C | 4.3 | 2.018e-11 | 3.3e-09 | 0.637
SRC|SRC_PY527-R-V | 0.54 | 3.171e-11 | 5.2e-09 | 0.37
CDKN1A|P21-R-C | 6.4 | 4.922e-11 | 8.1e-09 | 0.631
GAB2|GAB2-R-V | 0.5 | 8.237e-10 | 1.3e-07 | 0.354
ACACA|ACC1-R-C | 2.6 | 1.397e-09 | 2.3e-07 | 0.626
CTNNA1|ALPHA-CATENIN-M-V | 0.2 | 1.707e-09 | 2.7e-07 | 0.352
MAPK1 MAPK3|MAPK_PT202_Y204-R-V | 0.61 | 2.621e-09 | 4.2e-07 | 0.349
RAD51|RAD51-M-C | 4.1 | 2.664e-09 | 4.2e-07 | 0.633
AR|AR-R-V | 0.32 | 4.642e-09 | 7.3e-07 | 0.346
PRKAA1|AMPK_PT172-R-V | 0.47 | 5.98e-09 | 9.4e-07 | 0.376

Figure S1. Get High-res Image As an example, this figure shows the association of VASP|VASP-R-C to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.02e-11 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 | 0.2273 | 1.014e-06 | 0.000168

Figure S2. Get High-res Image As an example, this figure shows the association of IGFBP2|IGFBP2-R-V to 'AGE'. P value = 1.01e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

4 genes related to 'GENDER'.

Table S5. 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 S6. Get Full Table List of 4 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
AR|AR-R-V | 4.57 | 6.794e-06 | 0.00113 | 0.6251
SRC|SRC-M-V | -3.84 | 0.0001525 | 0.0252 | 0.6096
PTK2|FAK-R-C | -3.78 | 0.0001971 | 0.0323 | 0.6063
CLDN7|CLAUDIN-7-R-V | 3.74 | 0.0002208 | 0.036 | 0.6239

Figure S3. Get High-res Image As an example, this figure shows the association of AR|AR-R-V to 'GENDER'. P value = 6.79e-06 with T-test analysis.

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S7. 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

Clinical variable #5: 'PATHOLOGY.T'

36 genes related to 'PATHOLOGY.T'.

Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T | Mean (SD) | 1.92 (0.97)
|  | N
| T1 | 224
| T2 | 54
| T3 | 165
| T4 | 11
| Significant markers | N = 36
| pos. correlated | 17
| neg. correlated | 19

List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S9. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T' 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'. P value = 2.92e-12 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S10. Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N | Labels | N
| N0 | 208
| N1 | 16
| Significant markers | N = 1
| Higher in N1 | 0
| Higher in N0 | 1

List of one gene differentially expressed by 'PATHOLOGY.N'

Table S11. Get Full Table List of one gene differentially expressed by 'PATHOLOGY.N'

| T(pos if higher in 'N1') | 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'. P value = 5.52e-05 with T-test analysis.

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

23 genes related to 'PATHOLOGICSPREAD(M)'.

Table S12. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 380
| M1 | 74
| Significant markers | N = 23
| Higher in M1 | 8
| Higher in M0 | 15

List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S13. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

| T(pos if higher in 'M1') | ttestP | Q | AUC
--- | --- | --- | --- | ---
ERBB3|HER3_PY1298-R-C | -7.13 | 3.866e-11 | 6.42e-09 | 0.7025
PECAM1|CD31-M-V | -5.32 | 4.663e-07 | 7.69e-05 | 0.6658
YBX1|YB-1-R-V | 5.04 | 1.591e-06 | 0.000261 | 0.6618
MAPK1 MAPK3|MAPK_PT202_Y204-R-V | -5.04 | 1.935e-06 | 0.000315 | 0.6656
TP53BP1|53BP1-R-C | 4.73 | 6.443e-06 | 0.00104 | 0.6734
PIK3R1|PI3K-P85-R-V | 4.72 | 7.989e-06 | 0.00129 | 0.6766
ERRFI1|MIG-6-M-V | -4.62 | 9.093e-06 | 0.00145 | 0.6369
PEA15|PEA-15-R-V | 4.63 | 1.046e-05 | 0.00166 | 0.6642
AKT1 AKT2 AKT3|AKT_PS473-R-V | -4.39 | 2.42e-05 | 0.00382 | 0.6352
EEF2|EEF2-R-V | 4.4 | 2.65e-05 | 0.00416 | 0.6615

Figure S6. Get High-res Image As an example, this figure shows the association of ERBB3|HER3_PY1298-R-C to 'PATHOLOGICSPREAD(M)'. P value = 3.87e-11 with T-test analysis.

Clinical variable #8: 'TUMOR.STAGE'

42 genes related to 'TUMOR.STAGE'.

Table S14. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 2.11 (1.2)
|  | N
| Stage 1 | 219
| Stage 2 | 43
| Stage 3 | 114
| Stage 4 | 78
| Significant markers | N = 42
| pos. correlated | 19
| neg. correlated | 23

List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S15. Get Full Table List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
ERBB3|HER3_PY1298-R-C | -0.3545 | 6.916e-15 | 1.15e-12
CDH3|P-CADHERIN-R-C | 0.3324 | 3.591e-13 | 5.92e-11
SRC|SRC_PY527-R-V | -0.3104 | 1.343e-11 | 2.2e-09
SHC1|SHC_PY317-R-NA | -0.3068 | 2.381e-11 | 3.88e-09
PECAM1|CD31-M-V | -0.2965 | 1.149e-10 | 1.86e-08
CTNNA1|ALPHA-CATENIN-M-V | -0.2914 | 2.467e-10 | 3.97e-08
MAPK1 MAPK3|MAPK_PT202_Y204-R-V | -0.2831 | 8.191e-10 | 1.31e-07
EEF2|EEF2-R-V | 0.2819 | 9.758e-10 | 1.55e-07
RAF1|C-RAF_PS338-R-C | -0.274 | 2.922e-09 | 4.62e-07
ACACA ACACB|ACC_PS79-R-V | 0.2715 | 4.12e-09 | 6.47e-07

Figure S7. Get High-res Image As an example, this figure shows the association of ERBB3|HER3_PY1298-R-C to 'TUMOR.STAGE'. P value = 6.92e-15 with Spearman correlation analysis.

Clinical variable #9: 'NEOADJUVANT.THERAPY'

No gene related to 'NEOADJUVANT.THERAPY'.

Table S16. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY | Labels | N
| NO | 4
| YES | 450
| Significant markers | N = 0

Methods & Data
Input

- Expresson data file = KIRC.rppa.txt

- Clinical data file = KIRC.clin.merged.picked.txt

- Number of patients = 454

- Number of genes = 166

- Number of clinical features = 9

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[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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