Correlation between RPPA expression and clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
21 April 2013 | analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1R78C6K
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Thyroid Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1R78C6K
Overview
Introduction

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

Summary

Testing the association between 175 genes and 14 clinical features across 198 samples, statistically thresholded by Q value < 0.05, 10 clinical features related to at least one genes.

- 16 genes correlated to 'AGE'.

- SNAI2|SNAIL-M-C , EGFR|EGFR_PY1068-R-V , MAPK8|JNK_PT183_PT185-R-V , EEF2|EEF2-R-V , AKT1 AKT2 AKT3|AKT_PT308-R-V , ...

- 17 genes correlated to 'HISTOLOGICAL.TYPE'.

- ANXA1|ANNEXIN_I-R-V , FN1|FIBRONECTIN-R-C , PIK3R1|PI3K-P85-R-V , NEK7|NEK7-R-NA , CHEK2|CHK2-M-C , ...

- 7 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- ERBB2|HER2_PY1248-R-V , ARID1A|ARID1A-M-V , WWTR1|TAZ_PS89-R-C , DVL3|DVL3-R-V , MET|C-MET-M-C , ...

- 1 gene correlated to 'DISTANT.METASTASIS'.

- BCL2L1|BCL-XL-R-V

- 4 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.

- EIF4EBP1|4E-BP1-R-V , PIK3CA |PI3K-P110-ALPHA-R-C , EGFR|EGFR_PY1173-R-C , BCL2|BCL-2-R-C

- 9 genes correlated to 'LYMPH.NODE.METASTASIS'.

- ANXA1|ANNEXIN_I-R-V , SRC|SRC_PY527-R-V , CASP9|CASPASE-9_CLEAVEDD330-R-C , DVL3|DVL3-R-V , PIK3CA |PI3K-P110-ALPHA-R-C , ...

- 1 gene correlated to 'COMPLETENESS.OF.RESECTION'.

- LCK|LCK-R-V

- 8 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

- MAPK14|P38_MAPK-R-C , ANXA1|ANNEXIN_I-R-V , DVL3|DVL3-R-V , PTCH1|PTCH-R-C , SRC|SRC_PY527-R-V , ...

- 5 genes correlated to 'NEOPLASM.DISEASESTAGE'.

- BECN1|BECLIN-G-V , PECAM1|CD31-M-V , AKT1 AKT2 AKT3|AKT_PS473-R-V , CASP3|CASPASE-3_ACTIVE-R-C , ANXA1|ANNEXIN_I-R-V

- 1 gene correlated to 'MULTIFOCALITY'.

- YAP1|YAP-R-V

- No genes correlated to 'Time to Death', 'GENDER', 'RADIATIONEXPOSURE', and 'TUMOR.SIZE'.

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=0 |  |  |  |
AGE | Spearman correlation test | N=16 | older | N=8 | younger | N=8
GENDER | t test | N=0 |  |  |  |
HISTOLOGICAL TYPE | ANOVA test | N=17 |  |  |  |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=7 | yes | N=6 | no | N=1
RADIATIONEXPOSURE | t test | N=0 |  |  |  |
DISTANT METASTASIS | ANOVA test | N=1 |  |  |  |
EXTRATHYROIDAL EXTENSION | ANOVA test | N=4 |  |  |  |
LYMPH NODE METASTASIS | ANOVA test | N=9 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=1 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=8 | higher number.of.lymph.nodes | N=6 | lower number.of.lymph.nodes | N=2
NEOPLASM DISEASESTAGE | ANOVA test | N=5 |  |  |  |
MULTIFOCALITY | t test | N=1 | unifocal | N=0 | multifocal | N=1
TUMOR SIZE | Spearman correlation test | N=0 |  |  |  |

Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

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

Time to Death | Duration (Months) | 0.1-147.4 (median=9.7)
| censored | N = 187
| death | N = 9
| Significant markers | N = 0

Clinical variable #2: 'AGE'

16 genes related to 'AGE'.

Table S2. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 47.53 (16)
| Significant markers | N = 16
| pos. correlated | 8
| neg. correlated | 8

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

Table S3. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
SNAI2|SNAIL-M-C | 0.3233 | 3.396e-06 | 0.000594
EGFR|EGFR_PY1068-R-V | 0.3161 | 5.733e-06 | 0.000998
MAPK8|JNK_PT183_PT185-R-V | 0.307 | 1.089e-05 | 0.00188
EEF2|EEF2-R-V | -0.306 | 1.162e-05 | 0.002
AKT1 AKT2 AKT3|AKT_PT308-R-V | 0.3012 | 1.62e-05 | 0.00277
ATM|ATM-R-C | -0.286 | 4.413e-05 | 0.0075
PRKCA |PKC-ALPHA-M-V | 0.2855 | 4.563e-05 | 0.00771
AKT1 AKT2 AKT3|AKT_PS473-R-V | 0.2849 | 4.74e-05 | 0.00796
DVL3|DVL3-R-V | -0.2836 | 5.152e-05 | 0.0086
YAP1|YAP_PS127-R-C | -0.2799 | 6.489e-05 | 0.0108

Figure S1. Get High-res Image As an example, this figure shows the association of SNAI2|SNAIL-M-C to 'AGE'. P value = 3.4e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

Table S4. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 138
| MALE | 60
| Significant markers | N = 0

Clinical variable #4: 'HISTOLOGICAL.TYPE'

17 genes related to 'HISTOLOGICAL.TYPE'.

Table S5. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| OTHER SPECIFY | 4
| THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | 133
| THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | 50
| THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) | 11
| Significant markers | N = 17

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

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

| ANOVA_P | Q
--- | --- | ---
ANXA1|ANNEXIN_I-R-V | 3.759e-13 | 6.58e-11
FN1|FIBRONECTIN-R-C | 3.757e-10 | 6.54e-08
PIK3R1|PI3K-P85-R-V | 3.175e-08 | 5.49e-06
NEK7|NEK7-R-NA | 4.041e-07 | 6.95e-05
CHEK2|CHK2-M-C | 1.335e-06 | 0.000228
RPS6KA1|P90RSK_PT359_S363-R-C | 3.985e-06 | 0.000677
RAF1|C-RAF_PS338-R-C | 2.043e-05 | 0.00345
IRS1|IRS1-R-V | 2.355e-05 | 0.00396
PXN|PAXILLIN-R-V | 2.735e-05 | 0.00457
COL6A1|COLLAGEN_VI-R-V | 2.987e-05 | 0.00496

Figure S2. Get High-res Image As an example, this figure shows the association of ANXA1|ANNEXIN_I-R-V to 'HISTOLOGICAL.TYPE'. P value = 3.76e-13 with ANOVA analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

7 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S7. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 13
| YES | 185
| Significant markers | N = 7
| Higher in YES | 6
| Higher in NO | 1

List of 7 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8. Get Full Table List of 7 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
ERBB2|HER2_PY1248-R-V | 4.86 | 4.719e-05 | 0.00826 | 0.716
ARID1A|ARID1A-M-V | 4.69 | 9.794e-05 | 0.017 | 0.7143
WWTR1|TAZ_PS89-R-C | 4.92 | 0.0001253 | 0.0217 | 0.7842
DVL3|DVL3-R-V | -4.88 | 0.0001325 | 0.0228 | 0.7844
MET|C-MET-M-C | 4.45 | 0.0001575 | 0.0269 | 0.6848
IRS1|IRS1-R-V | 4.45 | 0.0002495 | 0.0424 | 0.7098
CDKN1B|P27_PT157-R-C | 4.48 | 0.0002712 | 0.0458 | 0.7451

Figure S3. Get High-res Image As an example, this figure shows the association of ERBB2|HER2_PY1248-R-V to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.72e-05 with T-test analysis.

Clinical variable #6: 'RADIATIONEXPOSURE'

No gene related to 'RADIATIONEXPOSURE'.

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

RADIATIONEXPOSURE | Labels | N
| NO | 167
| YES | 9
| Significant markers | N = 0

Clinical variable #7: 'DISTANT.METASTASIS'

One gene related to 'DISTANT.METASTASIS'.

Table S10. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS | Labels | N
| M0 | 100
| M1 | 4
| MX | 93
| Significant markers | N = 1

List of one gene differentially expressed by 'DISTANT.METASTASIS'

Table S11. Get Full Table List of one gene differentially expressed by 'DISTANT.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
BCL2L1|BCL-XL-R-V | 2.522e-05 | 0.00441

Figure S4. Get High-res Image As an example, this figure shows the association of BCL2L1|BCL-XL-R-V to 'DISTANT.METASTASIS'. P value = 2.52e-05 with ANOVA analysis.

Clinical variable #8: 'EXTRATHYROIDAL.EXTENSION'

4 genes related to 'EXTRATHYROIDAL.EXTENSION'.

Table S12. Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION | Labels | N
| MINIMAL (T3) | 48
| MODERATE/ADVANCED (T4A) | 8
| NONE | 134
| Significant markers | N = 4

List of 4 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

Table S13. Get Full Table List of 4 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

| ANOVA_P | Q
--- | --- | ---
EIF4EBP1|4E-BP1-R-V | 3.502e-05 | 0.00613
PIK3CA |PI3K-P110-ALPHA-R-C | 0.0001771 | 0.0308
EGFR|EGFR_PY1173-R-C | 0.0001933 | 0.0334
BCL2|BCL-2-R-C | 0.000234 | 0.0403

Figure S5. Get High-res Image As an example, this figure shows the association of EIF4EBP1|4E-BP1-R-V to 'EXTRATHYROIDAL.EXTENSION'. P value = 3.5e-05 with ANOVA analysis.

Clinical variable #9: 'LYMPH.NODE.METASTASIS'

9 genes related to 'LYMPH.NODE.METASTASIS'.

Table S14. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS | Labels | N
| N0 | 87
| N1 | 21
| N1A | 37
| N1B | 26
| NX | 27
| Significant markers | N = 9

List of 9 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S15. Get Full Table List of 9 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
ANXA1|ANNEXIN_I-R-V | 1.057e-07 | 1.85e-05
SRC|SRC_PY527-R-V | 5.396e-06 | 0.000939
CASP9|CASPASE-9_CLEAVEDD330-R-C | 6.714e-06 | 0.00116
DVL3|DVL3-R-V | 1.581e-05 | 0.00272
PIK3CA |PI3K-P110-ALPHA-R-C | 6.007e-05 | 0.0103
MAPK14|P38_MAPK-R-C | 7.288e-05 | 0.0124
FN1|FIBRONECTIN-R-C | 9.107e-05 | 0.0154
BCL2|BCL-2-R-C | 0.0001221 | 0.0205
PAI-1|PAL-1-M-C | 0.0001705 | 0.0285

Figure S6. Get High-res Image As an example, this figure shows the association of ANXA1|ANNEXIN_I-R-V to 'LYMPH.NODE.METASTASIS'. P value = 1.06e-07 with ANOVA analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

One gene related to 'COMPLETENESS.OF.RESECTION'.

Table S16. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 152
| R1 | 17
| R2 | 1
| RX | 13
| Significant markers | N = 1

List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S17. Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

| ANOVA_P | Q
--- | --- | ---
LCK|LCK-R-V | 2.186e-05 | 0.00383

Figure S7. Get High-res Image As an example, this figure shows the association of LCK|LCK-R-V to 'COMPLETENESS.OF.RESECTION'. P value = 2.19e-05 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

8 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S18. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 3.23 (5.5)
| Significant markers | N = 8
| pos. correlated | 6
| neg. correlated | 2

List of 8 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S19. Get Full Table List of 8 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
MAPK14|P38_MAPK-R-C | 0.4144 | 1.349e-07 | 2.36e-05
ANXA1|ANNEXIN_I-R-V | 0.3739 | 2.433e-06 | 0.000423
DVL3|DVL3-R-V | 0.3587 | 6.551e-06 | 0.00113
PTCH1|PTCH-R-C | 0.3369 | 2.486e-05 | 0.00428
SRC|SRC_PY527-R-V | -0.3268 | 4.463e-05 | 0.00763
PXN|PAXILLIN-R-V | 0.318 | 7.339e-05 | 0.0125
ERBB2|HER2_PY1248-R-V | -0.2955 | 0.0002415 | 0.0408
EEF2|EEF2-R-V | 0.2916 | 0.0002942 | 0.0494

Figure S8. Get High-res Image As an example, this figure shows the association of MAPK14|P38_MAPK-R-C to 'NUMBER.OF.LYMPH.NODES'. P value = 1.35e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

5 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S20. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE I | 101
| STAGE II | 32
| STAGE III | 44
| STAGE IVA | 16
| STAGE IVC | 3
| Significant markers | N = 5

List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S21. Get Full Table List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

| ANOVA_P | Q
--- | --- | ---
BECN1|BECLIN-G-V | 3.323e-07 | 5.81e-05
PECAM1|CD31-M-V | 3.71e-05 | 0.00646
AKT1 AKT2 AKT3|AKT_PS473-R-V | 4.829e-05 | 0.00835
CASP3|CASPASE-3_ACTIVE-R-C | 6.966e-05 | 0.012
ANXA1|ANNEXIN_I-R-V | 0.0002824 | 0.0483

Figure S9. Get High-res Image As an example, this figure shows the association of BECN1|BECLIN-G-V to 'NEOPLASM.DISEASESTAGE'. P value = 3.32e-07 with ANOVA analysis.

Clinical variable #13: 'MULTIFOCALITY'

One gene related to 'MULTIFOCALITY'.

Table S22. Basic characteristics of clinical feature: 'MULTIFOCALITY'

MULTIFOCALITY | Labels | N
| MULTIFOCAL | 87
| UNIFOCAL | 103
| Significant markers | N = 1
| Higher in UNIFOCAL | 0
| Higher in MULTIFOCAL | 1

List of one gene differentially expressed by 'MULTIFOCALITY'

Table S23. Get Full Table List of one gene differentially expressed by 'MULTIFOCALITY'

| T(pos if higher in 'UNIFOCAL') | ttestP | Q | AUC
--- | --- | --- | --- | ---
YAP1|YAP-R-V | -3.72 | 0.0002643 | 0.0463 | 0.6462

Figure S10. Get High-res Image As an example, this figure shows the association of YAP1|YAP-R-V to 'MULTIFOCALITY'. P value = 0.000264 with T-test analysis.

Clinical variable #14: 'TUMOR.SIZE'

No gene related to 'TUMOR.SIZE'.

Table S24. Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE | Mean (SD) | 3.22 (1.6)
| Significant markers | N = 0

Methods & Data
Input

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

- Clinical data file = THCA-TP.clin.merged.picked.txt

- Number of patients = 198

- Number of genes = 175

- Number of clinical features = 14

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

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

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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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