Correlation between RPPA expression and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
15 January 2014 | analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1RV0M56
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/C1RV0M56
Overview
Introduction

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

Summary

Testing the association between 189 genes and 13 clinical features across 143 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

- 3 genes correlated to 'PATHOLOGY.T.STAGE'.

- EIF4G1|EIF4G-R-C , DVL3|DVL3-R-V , EEF2K|EEF2K-R-V

- 2 genes correlated to 'GLEASON_SCORE_COMBINED'.

- BCL2L11|BIM-R-V , SHC1|SHC_PY317-R-E

- 5 genes correlated to 'GLEASON_SCORE_PRIMARY'.

- ESR1|ER-ALPHA_PS118-R-V , CCNB1|CYCLIN_B1-R-V , EIF4G1|EIF4G-R-C , MAPK14|P38_PT180_Y182-R-V , ERRFI1|MIG-6-M-V

- 4 genes correlated to 'GLEASON_SCORE'.

- BCL2L11|BIM-R-V , EIF4G1|EIF4G-R-C , GAB2|GAB2-R-V , CCNB1|CYCLIN_B1-R-V

- 2 genes correlated to 'PSA_RESULT_PREOP'.

- EEF2|EEF2-R-C , RAF1|C-RAF-R-V

- 20 genes correlated to 'DAYS_TO_PREOP_PSA'.

- EGFR|EGFR_PY1173-R-V , RPS6|S6_PS235_S236-R-V , TSC2|TUBERIN_PT1462-R-V , RPS6|S6_PS240_S244-R-V , SRC|SRC_PY527-R-V , ...

- No genes correlated to 'AGE', 'PATHOLOGY.N.STAGE', 'COMPLETENESS.OF.RESECTION', 'NUMBER.OF.LYMPH.NODES', 'GLEASON_SCORE_SECONDARY', 'PSA_VALUE', and 'DAYS_TO_PSA'.

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 |
--- | --- | --- | --- | --- | --- | ---
AGE | Spearman correlation test | N=0 |  |  |  |
PATHOLOGY T STAGE | Spearman correlation test | N=3 | higher stage | N=3 | lower stage | N=0
PATHOLOGY N STAGE | t test | N=0 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=0 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |  |  |  |
GLEASON_SCORE_COMBINED | Spearman correlation test | N=2 | higher score | N=1 | lower score | N=1
GLEASON_SCORE_PRIMARY | Spearman correlation test | N=5 | higher score | N=4 | lower score | N=1
GLEASON_SCORE_SECONDARY | Spearman correlation test | N=0 |  |  |  |
GLEASON_SCORE | Spearman correlation test | N=4 | higher score | N=4 | lower score | N=0
PSA_RESULT_PREOP | Spearman correlation test | N=2 | higher psa_result_preop | N=2 | lower psa_result_preop | N=0
DAYS_TO_PREOP_PSA | Spearman correlation test | N=20 | higher days_to_preop_psa | N=14 | lower days_to_preop_psa | N=6
PSA_VALUE | Spearman correlation test | N=0 |  |  |  |
DAYS_TO_PSA | Spearman correlation test | N=0 |  |  |  |

Clinical variable #1: 'AGE'

No gene related to 'AGE'.

Table S1. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 60.14 (7.1)
| Significant markers | N = 0

Clinical variable #2: 'PATHOLOGY.T.STAGE'

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

Table S2. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE | Mean (SD) | 2.65 (0.55)
|  | N
| 2 | 55
| 3 | 82
| 4 | 5
| Significant markers | N = 3
| pos. correlated | 3
| neg. correlated | 0

List of 3 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S3. Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
EIF4G1|EIF4G-R-C | 0.3602 | 1.067e-05 | 0.00202
DVL3|DVL3-R-V | 0.3391 | 3.656e-05 | 0.00687
EEF2K|EEF2K-R-V | 0.32 | 0.0001035 | 0.0194

Figure S1. Get High-res Image As an example, this figure shows the association of EIF4G1|EIF4G-R-C to 'PATHOLOGY.T.STAGE'. P value = 1.07e-05 with Spearman correlation analysis.

Clinical variable #3: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S4. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE | Labels | N
| class0 | 114
| class1 | 14
| Significant markers | N = 0

Clinical variable #4: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S5. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 102
| R1 | 30
| RX | 3
| Significant markers | N = 0

Clinical variable #5: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S6. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 0.2 (0.75)
| Significant markers | N = 0

Clinical variable #6: 'GLEASON_SCORE_COMBINED'

2 genes related to 'GLEASON_SCORE_COMBINED'.

Table S7. Basic characteristics of clinical feature: 'GLEASON_SCORE_COMBINED'

GLEASON_SCORE_COMBINED | Mean (SD) | 7.31 (0.83)
| Score | N
| 6 | 9
| 7 | 102
| 8 | 12
| 9 | 18
| 10 | 2
| Significant markers | N = 2
| pos. correlated | 1
| neg. correlated | 1

List of 2 genes significantly correlated to 'GLEASON_SCORE_COMBINED' by Spearman correlation test

Table S8. Get Full Table List of 2 genes significantly correlated to 'GLEASON_SCORE_COMBINED' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
BCL2L11|BIM-R-V | 0.3723 | 4.674e-06 | 0.000883
SHC1|SHC_PY317-R-E | -0.3108 | 0.0001579 | 0.0297

Figure S2. Get High-res Image As an example, this figure shows the association of BCL2L11|BIM-R-V to 'GLEASON_SCORE_COMBINED'. P value = 4.67e-06 with Spearman correlation analysis.

Clinical variable #7: 'GLEASON_SCORE_PRIMARY'

5 genes related to 'GLEASON_SCORE_PRIMARY'.

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

GLEASON_SCORE_PRIMARY | Mean (SD) | 3.51 (0.58)
| Score | N
| 2 | 1
| 3 | 73
| 4 | 64
| 5 | 5
| Significant markers | N = 5
| pos. correlated | 4
| neg. correlated | 1

List of 5 genes significantly correlated to 'GLEASON_SCORE_PRIMARY' by Spearman correlation test

Table S10. Get Full Table List of 5 genes significantly correlated to 'GLEASON_SCORE_PRIMARY' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
ESR1|ER-ALPHA_PS118-R-V | 0.3493 | 1.902e-05 | 0.0036
CCNB1|CYCLIN_B1-R-V | 0.325 | 7.5e-05 | 0.0141
EIF4G1|EIF4G-R-C | 0.316 | 0.000121 | 0.0226
MAPK14|P38_PT180_Y182-R-V | -0.3131 | 0.0001407 | 0.0262
ERRFI1|MIG-6-M-V | 0.3077 | 0.000185 | 0.0342

Figure S3. Get High-res Image As an example, this figure shows the association of ESR1|ER-ALPHA_PS118-R-V to 'GLEASON_SCORE_PRIMARY'. P value = 1.9e-05 with Spearman correlation analysis.

Clinical variable #8: 'GLEASON_SCORE_SECONDARY'

No gene related to 'GLEASON_SCORE_SECONDARY'.

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

GLEASON_SCORE_SECONDARY | Mean (SD) | 3.8 (0.64)
| Score | N
| 3 | 46
| 4 | 79
| 5 | 18
| Significant markers | N = 0

Clinical variable #9: 'GLEASON_SCORE'

4 genes related to 'GLEASON_SCORE'.

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

GLEASON_SCORE | Mean (SD) | 7.37 (0.86)
| Score | N
| 6 | 9
| 7 | 97
| 8 | 14
| 9 | 21
| 10 | 2
| Significant markers | N = 4
| pos. correlated | 4
| neg. correlated | 0

List of 4 genes significantly correlated to 'GLEASON_SCORE' by Spearman correlation test

Table S13. Get Full Table List of 4 genes significantly correlated to 'GLEASON_SCORE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
BCL2L11|BIM-R-V | 0.4167 | 2.266e-07 | 4.28e-05
EIF4G1|EIF4G-R-C | 0.3272 | 6.639e-05 | 0.0125
GAB2|GAB2-R-V | 0.3078 | 0.0001844 | 0.0345
CCNB1|CYCLIN_B1-R-V | 0.3058 | 0.0002039 | 0.0379

Figure S4. Get High-res Image As an example, this figure shows the association of BCL2L11|BIM-R-V to 'GLEASON_SCORE'. P value = 2.27e-07 with Spearman correlation analysis.

Clinical variable #10: 'PSA_RESULT_PREOP'

2 genes related to 'PSA_RESULT_PREOP'.

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

PSA_RESULT_PREOP | Mean (SD) | 10.47 (9.9)
| Significant markers | N = 2
| pos. correlated | 2
| neg. correlated | 0

List of 2 genes significantly correlated to 'PSA_RESULT_PREOP' by Spearman correlation test

Table S15. Get Full Table List of 2 genes significantly correlated to 'PSA_RESULT_PREOP' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
EEF2|EEF2-R-C | 0.3556 | 1.512e-05 | 0.00286
RAF1|C-RAF-R-V | 0.3356 | 4.75e-05 | 0.00893

Figure S5. Get High-res Image As an example, this figure shows the association of EEF2|EEF2-R-C to 'PSA_RESULT_PREOP'. P value = 1.51e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'DAYS_TO_PREOP_PSA'

20 genes related to 'DAYS_TO_PREOP_PSA'.

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

DAYS_TO_PREOP_PSA | Mean (SD) | -3.02 (56)
| Significant markers | N = 20
| pos. correlated | 14
| neg. correlated | 6

List of top 10 genes significantly correlated to 'DAYS_TO_PREOP_PSA' by Spearman correlation test

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

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
EGFR|EGFR_PY1173-R-V | -0.4407 | 6.315e-08 | 1.19e-05
RPS6|S6_PS235_S236-R-V | 0.4086 | 6.532e-07 | 0.000123
TSC2|TUBERIN_PT1462-R-V | 0.3924 | 1.934e-06 | 0.000362
RPS6|S6_PS240_S244-R-V | 0.3889 | 2.43e-06 | 0.000452
SRC|SRC_PY527-R-V | 0.3873 | 2.696e-06 | 0.000499
MAPK1 MAPK3|MAPK_PT202_Y204-R-V | 0.3779 | 4.894e-06 | 9e-04
EIF4EBP1|4E-BP1_PT37_T46-R-V | 0.3668 | 9.667e-06 | 0.00177
RB1|RB_PS807_S811-R-V | 0.3645 | 1.11e-05 | 0.00202
MAPK1|ERK2-R-E | -0.3558 | 1.842e-05 | 0.00333
SRC|SRC_PY416-R-C | 0.3424 | 3.953e-05 | 0.00712

Figure S6. Get High-res Image As an example, this figure shows the association of EGFR|EGFR_PY1173-R-V to 'DAYS_TO_PREOP_PSA'. P value = 6.32e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'PSA_VALUE'

No gene related to 'PSA_VALUE'.

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

PSA_VALUE | Mean (SD) | 1.52 (4.6)
| Significant markers | N = 0

Clinical variable #13: 'DAYS_TO_PSA'

No gene related to 'DAYS_TO_PSA'.

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

DAYS_TO_PSA | Mean (SD) | 547.4 (470)
| Significant markers | N = 0

Methods & Data
Input

- Expresson data file = PRAD-TP.rppa.txt

- Clinical data file = PRAD-TP.merged_data.txt

- Number of patients = 143

- Number of genes = 189

- Number of clinical features = 13

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

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

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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 © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle