Correlation between mRNA expression and clinical features

Lung Squamous Cell Carcinoma (Primary solid tumor)

23 May 2013 | analyses__2013_05_23

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C17H1GN3

Overview

Introduction

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

Summary

Testing the association between 17814 genes and 11 clinical features across 154 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

13 genes correlated to 'GENDER'.

RPS4Y1 , RPS4Y2 , DDX3Y , EIF1AY , CYORF15A , ...

13 genes correlated to 'HISTOLOGICAL.TYPE'.

FAM5B , NUT , A2BP1 , SPINK7 , CAPZA3 , ...

20 genes correlated to 'DISTANT.METASTASIS'.

P2RY6 , OPRL1 , BIRC8 , MAGEH1 , ACTR3 , ...

2 genes correlated to 'COMPLETENESS.OF.RESECTION'.

ANKRD33 , TINAG

No genes correlated to 'Time to Death', 'AGE', 'KARNOFSKY.PERFORMANCE.SCORE', 'NUMBERPACKYEARSSMOKED', 'YEAROFTOBACCOSMOKINGONSET', 'LYMPH.NODE.METASTASIS', 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=0
GENDER	t test	N=13	male	N=13	female	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=0
HISTOLOGICAL TYPE	ANOVA test	N=13
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
YEAROFTOBACCOSMOKINGONSET	Spearman correlation test	N=0
DISTANT METASTASIS	t test	N=20	m1	N=4	m0	N=16
LYMPH NODE METASTASIS	ANOVA test	N=0
COMPLETENESS OF RESECTION	ANOVA test	N=2
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)	0.4-173.8 (median=17.5)
	censored	N = 86
	death	N = 62

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	66.53 (8.6)
	Significant markers	N = 0

Clinical variable #3: 'GENDER'

13 genes related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	44
	MALE	110

	Significant markers	N = 13
	Higher in MALE	13
	Higher in FEMALE	0

List of top 10 genes differentially expressed by 'GENDER'

Table S4. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
RPS4Y1	41.46	2.767e-80	4.93e-76	1
RPS4Y2	33.72	2.902e-70	5.17e-66	1
DDX3Y	27.62	5.344e-58	9.52e-54	0.9998
EIF1AY	25.39	2.236e-53	3.98e-49	0.9977
CYORF15A	19.08	5.911e-37	1.05e-32	0.9909
UTY	16.63	3.88e-35	6.91e-31	0.9684
JARID1D	17.26	1.435e-31	2.55e-27	0.9824
ZFY	13.63	9.37e-27	1.67e-22	0.937
TTTY14	12.54	5.239e-25	9.33e-21	0.9529
CYORF15B	13.66	5.684e-24	1.01e-19	0.9467

Figure S1. Get High-res Image As an example, this figure shows the association of RPS4Y1 to 'GENDER'. P value = 2.77e-80 with T-test analysis.

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

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

Table S5. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	24.23 (38)
	Score	N
	0	18
	50	2
	70	1
	90	4
	100	1

	Significant markers	N = 0

Clinical variable #5: 'HISTOLOGICAL.TYPE'

13 genes related to 'HISTOLOGICAL.TYPE'.

Table S6. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	LUNG BASALOID SQUAMOUS CELL CARCINOMA	5
	LUNG PAPILLARY SQUAMOUS CELL CARICNOMA	1
	LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS)	148

	Significant markers	N = 13

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

Table S7. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
FAM5B	1.9e-10	3.38e-06
NUT	2.209e-10	3.93e-06
A2BP1	6.605e-09	0.000118
SPINK7	1.946e-07	0.00347
CAPZA3	2.047e-07	0.00365
UGT2B10	2.803e-07	0.00499
GABRA4	4.203e-07	0.00748
DCD	4.586e-07	0.00817
PDS5B	6.666e-07	0.0119
MGC21881	8.832e-07	0.0157

Figure S2. Get High-res Image As an example, this figure shows the association of FAM5B to 'HISTOLOGICAL.TYPE'. P value = 1.9e-10 with ANOVA analysis.

Clinical variable #6: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S8. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'


NUMBERPACKYEARSSMOKED	Mean (SD)	54.83 (36)
	Significant markers	N = 0

Clinical variable #7: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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


YEAROFTOBACCOSMOKINGONSET	Mean (SD)	1958.02 (11)
	Significant markers	N = 0

Clinical variable #8: 'DISTANT.METASTASIS'

20 genes related to 'DISTANT.METASTASIS'.

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


DISTANT.METASTASIS	Labels	N
	M0	146
	M1	4

	Significant markers	N = 20
	Higher in M1	4
	Higher in M0	16

List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S11. Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

	T(pos if higher in 'M1')	ttestP	Q	AUC
P2RY6	-8.15	1.779e-10	3.17e-06	0.8099
OPRL1	8.8	1.345e-09	2.4e-05	0.8305
BIRC8	-7.19	4.357e-09	7.76e-05	0.851
MAGEH1	6.26	8.788e-09	0.000157	0.714
ACTR3	-8.5	2.431e-08	0.000433	0.8271
NSD1	-9.3	2.835e-08	0.000505	0.8408
RGPD5	-10.94	3.638e-08	0.000648	0.8973
PTPRD	-6.32	5.655e-08	0.00101	0.6661
KRT24	-6.03	6.075e-08	0.00108	0.6045
LCE3E	-6.94	1.357e-07	0.00242	0.7217

Figure S3. Get High-res Image As an example, this figure shows the association of P2RY6 to 'DISTANT.METASTASIS'. P value = 1.78e-10 with T-test analysis.

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

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

Table S12. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'


LYMPH.NODE.METASTASIS	Labels	N
	N0	96
	N1	40
	N2	13
	N3	5

	Significant markers	N = 0

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

2 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S13. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	139
	R1	3
	R2	2
	RX	5

	Significant markers	N = 2

List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S14. Get Full Table List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

	ANOVA_P	Q
ANKRD33	1.353e-06	0.0241
TINAG	2.046e-06	0.0364

Figure S4. Get High-res Image As an example, this figure shows the association of ANKRD33 to 'COMPLETENESS.OF.RESECTION'. P value = 1.35e-06 with ANOVA analysis.

Clinical variable #11: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S15. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE IA	20
	STAGE IB	61
	STAGE IIA	7
	STAGE IIB	27
	STAGE IIIA	19
	STAGE IIIB	15
	STAGE IV	4

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = LUSC-TP.medianexp.txt
Clinical data file = LUSC-TP.clin.merged.picked.txt
Number of patients = 154
Number of genes = 17814
Number of clinical features = 11

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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