Correlation between RPPA expression and clinical features

Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)

17 October 2014 | analyses__2014_10_17

Maintainer Information

Citation Information

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/C1C24VCZ

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 7 clinical features across 200 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.

1 gene correlated to 'Time to Death'.

PTGS2|COX-2-R-C

23 genes correlated to 'HISTOLOGICAL.TYPE'.

TP53|P53-R-V , AKT1 AKT2 AKT3|AKT_PS473-R-V , ESR1|ER-ALPHA_PS118-R-V , CHEK2|CHK2_PT68-R-C , PTEN|PTEN-R-V , ...

2 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

MYC|C-MYC-R-C , CHEK1|CHK1_PS345-R-C

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

SRC|SRC_PY416-R-C

No genes correlated to 'AGE', '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
Time to Death	Cox regression test	N=1	shorter survival	N=1	longer survival	N=0
AGE	Spearman correlation test	N=0
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=23
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=2	yes	N=2	no	N=0
COMPLETENESS OF RESECTION	Kruskal-Wallis test	N=1
RACE	Kruskal-Wallis test	N=0
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'Time to Death'

One gene related to 'Time to Death'.

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


Time to Death	Duration (Months)	0.6-185.8 (median=29.2)
	censored	N = 180
	death	N = 20

	Significant markers	N = 1
	associated with shorter survival	1
	associated with longer survival	0

List of one gene differentially expressed by 'Time to Death'

Table S2. Get Full Table List of one gene significantly associated with 'Time to Death' by Cox regression test

	HazardRatio	Wald_P	Q	C_index
PTGS2\|COX-2-R-C	2.2	0.000526	0.087	0.642

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	62.73 (11)
	Significant markers	N = 0

Clinical variable #3: 'HISTOLOGICAL.TYPE'

23 genes related to 'HISTOLOGICAL.TYPE'.

Table S4. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA	174
	MIXED SEROUS AND ENDOMETRIOID	3
	SEROUS ENDOMETRIAL ADENOCARCINOMA	23

	Significant markers	N = 23

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

Table S5. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
TP53\|P53-R-V	1.642e-08	2.73e-06
AKT1 AKT2 AKT3\|AKT_PS473-R-V	1.38e-07	2.28e-05
ESR1\|ER-ALPHA_PS118-R-V	8.033e-07	0.000132
CHEK2\|CHK2_PT68-R-C	1.953e-06	0.000318
PTEN\|PTEN-R-V	2.566e-06	0.000416
PGR\|PR-R-V	2.878e-06	0.000463
CDH1\|E-CADHERIN-R-V	4.378e-06	7e-04
ESR1\|ER-ALPHA-R-V	5.4e-06	0.000859
AKT1 AKT2 AKT3\|AKT_PT308-R-V	6.272e-06	0.000991
CTNNA1\|ALPHA-CATENIN-M-V	6.334e-05	0.00994

Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S6. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	80
	YES	120

	Significant markers	N = 2
	Higher in YES	2
	Higher in NO	0

List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S7. Get Full Table List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	W(pos if higher in 'YES')	wilcoxontestP	Q	AUC
MYC\|C-MYC-R-C	3494	0.001131	0.188	0.636
CHEK1\|CHK1_PS345-R-C	6058	0.001713	0.283	0.631

Clinical variable #5: 'COMPLETENESS.OF.RESECTION'

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

Table S8. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	143
	R1	7
	R2	5
	RX	16

	Significant markers	N = 1

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

Table S9. Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

	ANOVA_P	Q
SRC\|SRC_PY416-R-C	0.001405	0.233

Clinical variable #6: 'RACE'

No gene related to 'RACE'.

Table S10. Basic characteristics of clinical feature: 'RACE'


RACE	Labels	N
	AMERICAN INDIAN OR ALASKA NATIVE	2
	ASIAN	9
	BLACK OR AFRICAN AMERICAN	18
	NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER	4
	WHITE	162

	Significant markers	N = 0

Clinical variable #7: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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


ETHNICITY	Labels	N
	HISPANIC OR LATINO	5
	NOT HISPANIC OR LATINO	135

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = UCEC-TP.rppa.txt
Clinical data file = UCEC-TP.merged_data.txt
Number of patients = 200
Number of genes = 166
Number of clinical features = 7

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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