Correlation between mRNAseq expression and clinical features

Breast Invasive Carcinoma (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 mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1PV6HC9

Overview

Introduction

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

Summary

Testing the association between 18279 genes and 9 clinical features across 877 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

6 genes correlated to 'Time to Death'.

DIP2B|57609 , CAND1|55832 , NFKBIA|4792 , PGK1|5230 , LRP11|84918 , ...

774 genes correlated to 'AGE'.

ESR1|2099 , LRFN5|145581 , TFPI2|7980 , TMEFF1|8577 , DZIP1|22873 , ...

19 genes correlated to 'GENDER'.

NLGN4Y|22829 , ZFY|7544 , PRKY|5616 , C7ORF10|79783 , SYT9|143425 , ...

3599 genes correlated to 'HISTOLOGICAL.TYPE'.

CDH1|999 , RAPGEF3|10411 , LRRC70|100130733 , MUC2|4583 , PSMD14|10213 , ...

44 genes correlated to 'LYMPH.NODE.METASTASIS'.

PIK3CA|5290 , BTBD10|84280 , RPL35|11224 , HSPA8|3312 , C19ORF21|126353 , ...

1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

HMSD|284293

3 genes correlated to 'NEOPLASM.DISEASESTAGE'.

C20ORF43|51507 , CSTF1|1477 , PGGT1B|5229

No genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION', and 'DISTANT.METASTASIS'.

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=6	shorter survival	N=4	longer survival	N=2
AGE	Spearman correlation test	N=774	older	N=201	younger	N=573
GENDER	t test	N=19	male	N=8	female	N=11
HISTOLOGICAL TYPE	ANOVA test	N=3599
RADIATIONS RADIATION REGIMENINDICATION	t test	N=0
DISTANT METASTASIS	ANOVA test	N=0
LYMPH NODE METASTASIS	ANOVA test	N=44
NUMBER OF LYMPH NODES	Spearman correlation test	N=1	higher number.of.lymph.nodes	N=0	lower number.of.lymph.nodes	N=1
NEOPLASM DISEASESTAGE	ANOVA test	N=3

Clinical variable #1: 'Time to Death'

6 genes related to 'Time to Death'.

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


Time to Death	Duration (Months)	0-223.4 (median=18.2)
	censored	N = 723
	death	N = 96

	Significant markers	N = 6
	associated with shorter survival	4
	associated with longer survival	2

List of 6 genes significantly associated with 'Time to Death' by Cox regression test

Table S2. Get Full Table List of 6 genes significantly associated with 'Time to Death' by Cox regression test

	HazardRatio	Wald_P	Q	C_index
DIP2B\|57609	3	6.028e-08	0.0011	0.634
CAND1\|55832	2	1.3e-06	0.024	0.623
NFKBIA\|4792	0.42	1.493e-06	0.027	0.362
PGK1\|5230	2	1.595e-06	0.029	0.679
LRP11\|84918	1.9	1.624e-06	0.03	0.633
IRF2\|3660	0.29	1.805e-06	0.033	0.332

Figure S1. Get High-res Image As an example, this figure shows the association of DIP2B|57609 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 6.03e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

774 genes related to 'AGE'.

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


AGE	Mean (SD)	58.42 (13)
	Significant markers	N = 774
	pos. correlated	201
	neg. correlated	573

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

Table S4. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
ESR1\|2099	0.3563	1.298e-27	2.37e-23
LRFN5\|145581	-0.2627	5.621e-15	1.03e-10
TFPI2\|7980	-0.2608	5.748e-15	1.05e-10
TMEFF1\|8577	-0.2583	8.144e-15	1.49e-10
DZIP1\|22873	-0.2502	5.694e-14	1.04e-09
DSC2\|1824	-0.2472	1.15e-13	2.1e-09
DBX2\|440097	-0.2644	1.992e-13	3.64e-09
FMO1\|2326	-0.2437	2.665e-13	4.87e-09
DIO2\|1734	-0.2428	3.183e-13	5.82e-09
PCDH18\|54510	-0.2401	5.898e-13	1.08e-08

Figure S2. Get High-res Image As an example, this figure shows the association of ESR1|2099 to 'AGE'. P value = 1.3e-27 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

19 genes related to 'GENDER'.

Table S5. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	868
	MALE	9

	Significant markers	N = 19
	Higher in MALE	8
	Higher in FEMALE	11

List of top 10 genes differentially expressed by 'GENDER'

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

	T(pos if higher in 'MALE')	ttestP	Q	AUC
NLGN4Y\|22829	41.35	2.846e-12	5.12e-08	1
ZFY\|7544	42.09	1.917e-11	3.45e-07	1
PRKY\|5616	27.64	6.778e-10	1.22e-05	1
C7ORF10\|79783	8.94	2.705e-09	4.86e-05	0.6669
SYT9\|143425	12.49	8.247e-09	0.000148	0.7952
GSTA1\|2938	-16.33	1.16e-08	0.000208	0.8872
MMP11\|4320	11.37	1.403e-08	0.000252	0.7526
RND2\|8153	12.09	4.105e-08	0.000738	0.829
HTR4\|3360	-12.33	1.31e-07	0.00235	0.7979
SNORA74B\|677841	-12	1.568e-07	0.00282	0.8387

Figure S3. Get High-res Image As an example, this figure shows the association of NLGN4Y|22829 to 'GENDER'. P value = 2.85e-12 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

3599 genes related to 'HISTOLOGICAL.TYPE'.

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


HISTOLOGICAL.TYPE	Labels	N
	INFILTRATING DUCTAL CARCINOMA	682
	INFILTRATING LOBULAR CARCINOMA	116
	MEDULLARY CARCINOMA	4
	MIXED HISTOLOGY (PLEASE SPECIFY)	25
	MUCINOUS CARCINOMA	10
	OTHER SPECIFY	40

	Significant markers	N = 3599

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

Table S8. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
CDH1\|999	4.248e-80	7.77e-76
RAPGEF3\|10411	7.163e-30	1.31e-25
LRRC70\|100130733	3.467e-29	6.34e-25
MUC2\|4583	7.76e-29	1.42e-24
PSMD14\|10213	1.558e-28	2.85e-24
BTG2\|7832	3.389e-28	6.19e-24
AVPR2\|554	4.544e-28	8.3e-24
SDPR\|8436	5.083e-28	9.29e-24
USHBP1\|83878	6.156e-28	1.12e-23
GPIHBP1\|338328	1.741e-27	3.18e-23

Figure S4. Get High-res Image As an example, this figure shows the association of CDH1|999 to 'HISTOLOGICAL.TYPE'. P value = 4.25e-80 with ANOVA analysis.

Clinical variable #5: '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	213
	YES	664

	Significant markers	N = 0

Clinical variable #6: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

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


DISTANT.METASTASIS	Labels	N
	CM0 (I+)	2
	M0	778
	M1	15
	MX	82

	Significant markers	N = 0

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

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

Table S11. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'


LYMPH.NODE.METASTASIS	Labels	N
	N0	256
	N0 (I+)	22
	N0 (I-)	135
	N0 (MOL+)	1
	N1	104
	N1A	130
	N1B	32
	N1C	2
	N1MI	24
	N2	50
	N2A	54
	N3	19
	N3A	31
	N3B	1
	N3C	1
	NX	15

	Significant markers	N = 44

List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S12. Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

	ANOVA_P	Q
PIK3CA\|5290	3.444e-13	6.3e-09
BTBD10\|84280	7.398e-13	1.35e-08
RPL35\|11224	1.982e-09	3.62e-05
HSPA8\|3312	3.46e-09	6.32e-05
C19ORF21\|126353	5.023e-09	9.18e-05
SERINC3\|10955	1.61e-08	0.000294
UBR1\|197131	6.044e-08	0.0011
RPL12\|6136	6.892e-08	0.00126
RPL34\|6164	1.223e-07	0.00223
SPPL3\|121665	1.389e-07	0.00254

Figure S5. Get High-res Image As an example, this figure shows the association of PIK3CA|5290 to 'LYMPH.NODE.METASTASIS'. P value = 3.44e-13 with ANOVA analysis.

Clinical variable #8: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S13. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'


NUMBER.OF.LYMPH.NODES	Mean (SD)	2.2 (4.4)
	Significant markers	N = 1
	pos. correlated	0
	neg. correlated	1

List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S14. Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

	SpearmanCorr	corrP	Q
HMSD\|284293	-0.2644	1.921e-08	0.000351

Figure S6. Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.92e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #9: 'NEOPLASM.DISEASESTAGE'

3 genes related to 'NEOPLASM.DISEASESTAGE'.

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


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	72
	STAGE IA	69
	STAGE IB	7
	STAGE II	8
	STAGE IIA	296
	STAGE IIB	198
	STAGE III	2
	STAGE IIIA	125
	STAGE IIIB	25
	STAGE IIIC	41
	STAGE IV	15
	STAGE TIS	1
	STAGE X	17

	Significant markers	N = 3

List of 3 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S16. Get Full Table List of 3 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
C20ORF43\|51507	1.021e-10	1.87e-06
CSTF1\|1477	1.901e-08	0.000348
PGGT1B\|5229	2.103e-07	0.00384

Figure S7. Get High-res Image As an example, this figure shows the association of C20ORF43|51507 to 'NEOPLASM.DISEASESTAGE'. P value = 1.02e-10 with ANOVA analysis.

Methods & Data

Input

Expresson data file = BRCA-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
Clinical data file = BRCA-TP.clin.merged.picked.txt
Number of patients = 877
Number of genes = 18279
Number of clinical features = 9

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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