Correlation between RPPA expression and clinical features

Lung Adenocarcinoma (Primary solid tumor)

23 May 2013 | analyses__2013_05_23

Maintainer Information

Citation Information

Maintained by Juok Cho (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1DF6P9V

Overview

Introduction

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

Summary

Testing the association between 174 genes and 12 clinical features across 237 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

2 genes correlated to 'AGE'.

PTGS2|COX-2-R-C , ARID1A|ARID1A-M-V

1 gene correlated to 'GENDER'.

CLDN7|CLAUDIN-7-R-V

9 genes correlated to 'HISTOLOGICAL.TYPE'.

PARP1|PARP_CLEAVED-M-C , ERCC1|ERCC1-M-C , CASP8|CASPASE-8-M-C , MET|C-MET-M-C , RB1|RB-M-V , ...

2 genes correlated to 'DISTANT.METASTASIS'.

EGFR|EGFR_PY1173-R-C , CD20|CD20-R-C

No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'YEAROFTOBACCOSMOKINGONSET', 'LYMPH.NODE.METASTASIS', 'COMPLETENESS.OF.RESECTION', and 'NEOPLASM.DISEASESTAGE'.

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=2	older	N=0	younger	N=2
GENDER	t test	N=1	male	N=1	female	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=0
HISTOLOGICAL TYPE	ANOVA test	N=9
RADIATIONS RADIATION REGIMENINDICATION	t test	N=0
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
YEAROFTOBACCOSMOKINGONSET	Spearman correlation test	N=0
DISTANT METASTASIS	ANOVA test	N=2
LYMPH NODE METASTASIS	ANOVA test	N=0
COMPLETENESS OF RESECTION	ANOVA test	N=0
NEOPLASM DISEASESTAGE	ANOVA 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)	0-224 (median=12.3)
	censored	N = 147
	death	N = 68

	Significant markers	N = 0

Clinical variable #2: 'AGE'

2 genes related to 'AGE'.

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


AGE	Mean (SD)	64.81 (9.8)
	Significant markers	N = 2
	pos. correlated	0
	neg. correlated	2

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

Table S3. Get Full Table List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
PTGS2\|COX-2-R-C	-0.2924	1.251e-05	0.00218
ARID1A\|ARID1A-M-V	-0.2464	0.0002553	0.0442

Figure S1. Get High-res Image As an example, this figure shows the association of PTGS2|COX-2-R-C to 'AGE'. P value = 1.25e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

One gene related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	131
	MALE	106

	Significant markers	N = 1
	Higher in MALE	1
	Higher in FEMALE	0

List of one gene differentially expressed by 'GENDER'

Table S5. Get Full Table List of one gene differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
CLDN7\|CLAUDIN-7-R-V	3.86	0.0001598	0.0278	0.6072

Figure S2. Get High-res Image As an example, this figure shows the association of CLDN7|CLAUDIN-7-R-V to 'GENDER'. P value = 0.00016 with T-test analysis.

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

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

Table S6. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	69.05 (35)
	Significant markers	N = 0

Clinical variable #5: 'HISTOLOGICAL.TYPE'

9 genes related to 'HISTOLOGICAL.TYPE'.

Table S7. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	LUNG ACINAR ADENOCARCINOMA	6
	LUNG ADENOCARCINOMA MIXED SUBTYPE	52
	LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS)	151
	LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS	3
	LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS	10
	LUNG CLEAR CELL ADENOCARCINOMA	1
	LUNG MICROPAPILLARY ADENOCARCINOMA	2
	LUNG MUCINOUS ADENOCARCINOMA	2
	LUNG PAPILLARY ADENOCARCINOMA	6
	LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA	1
	MUCINOUS (COLLOID) CARCINOMA	3

	Significant markers	N = 9

List of 9 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S8. Get Full Table List of 9 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
PARP1\|PARP_CLEAVED-M-C	1.357e-07	2.36e-05
ERCC1\|ERCC1-M-C	1.598e-07	2.77e-05
CASP8\|CASPASE-8-M-C	2.088e-07	3.59e-05
MET\|C-MET-M-C	6.775e-07	0.000116
RB1\|RB-M-V	1.155e-06	0.000196
SNAI2\|SNAIL-M-C	3.752e-06	0.000634
C12ORF5\|TIGAR-R-V	4.014e-05	0.00674
DIABLO\|SMAC-M-V	8.65e-05	0.0144
FOXO3\|FOXO3A-R-C	0.0001199	0.0199

Figure S3. Get High-res Image As an example, this figure shows the association of PARP1|PARP_CLEAVED-M-C to 'HISTOLOGICAL.TYPE'. P value = 1.36e-07 with ANOVA analysis.

Clinical variable #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S9. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	13
	YES	224

	Significant markers	N = 0

Clinical variable #7: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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


NUMBERPACKYEARSSMOKED	Mean (SD)	40.85 (27)
	Significant markers	N = 0

Clinical variable #8: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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


YEAROFTOBACCOSMOKINGONSET	Mean (SD)	1964.47 (14)
	Significant markers	N = 0

Clinical variable #9: 'DISTANT.METASTASIS'

2 genes related to 'DISTANT.METASTASIS'.

Table S12. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'


DISTANT.METASTASIS	Labels	N
	M0	166
	M1	12
	MX	56

	Significant markers	N = 2

List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

Table S13. Get Full Table List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

	ANOVA_P	Q
EGFR\|EGFR_PY1173-R-C	0.0001675	0.0291
CD20\|CD20-R-C	0.0002157	0.0373

Figure S4. Get High-res Image As an example, this figure shows the association of EGFR|EGFR_PY1173-R-C to 'DISTANT.METASTASIS'. P value = 0.000168 with ANOVA analysis.

Clinical variable #10: 'LYMPH.NODE.METASTASIS'

No gene related to 'LYMPH.NODE.METASTASIS'.

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


LYMPH.NODE.METASTASIS	Labels	N
	N0	141
	N1	46
	N2	43
	N3	1
	NX	5

	Significant markers	N = 0

Clinical variable #11: 'COMPLETENESS.OF.RESECTION'

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

Table S15. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	131
	R1	6
	R2	3
	RX	12

	Significant markers	N = 0

Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S16. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	1
	STAGE IA	54
	STAGE IB	68
	STAGE IIA	19
	STAGE IIB	32
	STAGE IIIA	42
	STAGE IIIB	7
	STAGE IV	13

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = LUAD-TP.rppa.txt
Clinical data file = LUAD-TP.clin.merged.picked.txt
Number of patients = 237
Number of genes = 174
Number of clinical features = 12

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.

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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