Correlation between miRseq expression and clinical features

Brain Lower Grade Glioma (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 miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1GQ6WPN

Overview

Introduction

This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 548 miRs and 8 clinical features across 430 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one miRs.

101 miRs correlated to 'Time to Death'.

HSA-MIR-155 , HSA-MIR-10A , HSA-MIR-15B , HSA-MIR-148A , HSA-MIR-196B , ...

41 miRs correlated to 'AGE'.

HSA-MIR-34A , HSA-MIR-155 , HSA-MIR-10B , HSA-MIR-25 , HSA-MIR-146A , ...

19 miRs correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

HSA-MIR-222 , HSA-MIR-148A , HSA-MIR-181A-2 , HSA-MIR-432 , HSA-MIR-135B , ...

107 miRs correlated to 'HISTOLOGICAL.TYPE'.

HSA-MIR-1262 , HSA-MIR-186 , HSA-MIR-219-1 , HSA-MIR-592 , HSA-MIR-576 , ...

56 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

HSA-MIR-1274B , HSA-MIR-628 , HSA-MIR-3130-1 , HSA-MIR-9-3 , HSA-MIR-30E , ...

1 miR correlated to 'RACE'.

HSA-MIR-1304

No miRs correlated to 'GENDER', 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 miRs that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature	Statistical test	Significant miRs	Associated with		Associated with
Time to Death	Cox regression test	N=101	shorter survival	N=96	longer survival	N=5
AGE	Spearman correlation test	N=41	older	N=32	younger	N=9
GENDER	Wilcoxon test	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=19	higher score	N=1	lower score	N=18
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=107
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=56	yes	N=56	no	N=0
RACE	Kruskal-Wallis test	N=1
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'Time to Death'

101 miRs related to 'Time to Death'.

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


Time to Death	Duration (Months)	0-211.2 (median=15.8)
	censored	N = 354
	death	N = 74

	Significant markers	N = 101
	associated with shorter survival	96
	associated with longer survival	5

List of top 10 miRs differentially expressed by 'Time to Death'

Table S2. Get Full Table List of top 10 miRs significantly associated with 'Time to Death' by Cox regression test

	HazardRatio	Wald_P	Q	C_index
HSA-MIR-155	1.96	0	0	0.805
HSA-MIR-10A	1.34	2.802e-12	1.5e-09	0.729
HSA-MIR-15B	2	4.946e-12	2.7e-09	0.797
HSA-MIR-148A	1.65	8.413e-11	4.6e-08	0.767
HSA-MIR-196B	1.24	1.876e-10	1e-07	0.732
HSA-MIR-9-1	0.39	3.472e-09	1.9e-06	0.231
HSA-MIR-9-2	0.39	3.511e-09	1.9e-06	0.231
HSA-MIR-346	0.62	1.534e-08	8.3e-06	0.37
HSA-MIR-23A	1.96	1.585e-08	8.6e-06	0.733
HSA-MIR-142	1.67	2.849e-08	1.5e-05	0.727

Clinical variable #2: 'AGE'

41 miRs related to 'AGE'.

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


AGE	Mean (SD)	42.94 (13)
	Significant markers	N = 41
	pos. correlated	32
	neg. correlated	9

List of top 10 miRs differentially expressed by 'AGE'

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

	SpearmanCorr	corrP	Q
HSA-MIR-34A	0.2988	2.677e-10	1.47e-07
HSA-MIR-155	0.2637	2.956e-08	1.62e-05
HSA-MIR-10B	0.2575	6.342e-08	3.46e-05
HSA-MIR-25	0.2575	6.349e-08	3.46e-05
HSA-MIR-146A	0.255	8.534e-08	4.64e-05
HSA-MIR-10A	0.2492	1.698e-07	9.22e-05
HSA-MIR-126	0.244	3.112e-07	0.000169
HSA-MIR-2115	0.2447	8.293e-07	0.000449
HSA-MIR-320B-2	0.2333	1.033e-06	0.000558
HSA-MIR-16-1	0.2189	4.746e-06	0.00256

Clinical variable #3: 'GENDER'

No miR related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	192
	MALE	238

	Significant markers	N = 0

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

19 miRs related to 'KARNOFSKY.PERFORMANCE.SCORE'.

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


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	87.74 (12)
	Significant markers	N = 19
	pos. correlated	1
	neg. correlated	18

List of top 10 miRs differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S7. Get Full Table List of top 10 miRs significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

	SpearmanCorr	corrP	Q
HSA-MIR-222	-0.255	4.838e-05	0.0265
HSA-MIR-148A	-0.2524	5.828e-05	0.0319
HSA-MIR-181A-2	0.2499	6.924e-05	0.0378
HSA-MIR-432	-0.2466	8.694e-05	0.0474
HSA-MIR-135B	-0.2634	0.0001036	0.0564
HSA-MIR-493	-0.2455	0.0001178	0.064
HSA-MIR-187	-0.2377	0.0002279	0.124
HSA-MIR-103-2	-0.2318	0.0002312	0.125
HSA-MIR-134	-0.2294	0.0002691	0.145
HSA-MIR-337	-0.2287	0.0002819	0.152

Clinical variable #5: 'HISTOLOGICAL.TYPE'

107 miRs related to 'HISTOLOGICAL.TYPE'.

Table S8. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	ASTROCYTOMA	158
	OLIGOASTROCYTOMA	106
	OLIGODENDROGLIOMA	166

	Significant markers	N = 107

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

Table S9. Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
HSA-MIR-1262	1.592e-17	8.72e-15
HSA-MIR-186	4.075e-16	2.23e-13
HSA-MIR-219-1	1.346e-15	7.35e-13
HSA-MIR-592	3.202e-15	1.75e-12
HSA-MIR-576	6.813e-15	3.71e-12
HSA-MIR-3065	1.183e-14	6.42e-12
HSA-MIR-3074	3.451e-13	1.87e-10
HSA-MIR-505	3.619e-13	1.96e-10
HSA-MIR-301A	1.691e-12	9.13e-10
HSA-MIR-21	3.645e-12	1.96e-09

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

56 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S10. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	88
	YES	342

	Significant markers	N = 56
	Higher in YES	56
	Higher in NO	0

List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S11. Get Full Table List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	W(pos if higher in 'YES')	wilcoxontestP	Q	AUC
HSA-MIR-1274B	7213	2.004e-12	1.1e-09	0.7447
HSA-MIR-628	8403	1.649e-10	9.02e-08	0.7208
HSA-MIR-3130-1	7170	3.865e-10	2.11e-07	0.7242
HSA-MIR-9-3	21069	7.01e-09	3.82e-06	0.7001
HSA-MIR-30E	9290	3.064e-08	1.67e-05	0.6913
HSA-MIR-331	9333	3.877e-08	2.11e-05	0.6899
HSA-MIR-3677	9602	1.626e-07	8.82e-05	0.681
HSA-MIR-424	9640	1.981e-07	0.000107	0.6797
HSA-MIR-296	9868	6.3e-07	0.00034	0.6721
HSA-MIR-500A	20228	6.3e-07	0.00034	0.6721

Clinical variable #7: 'RACE'

One miR related to 'RACE'.

Table S12. Basic characteristics of clinical feature: 'RACE'


RACE	Labels	N
	AMERICAN INDIAN OR ALASKA NATIVE	1
	ASIAN	6
	BLACK OR AFRICAN AMERICAN	14
	WHITE	400

	Significant markers	N = 1

List of one miR differentially expressed by 'RACE'

Table S13. Get Full Table List of one miR differentially expressed by 'RACE'

	ANOVA_P	Q
HSA-MIR-1304	6.547e-05	0.0359

Clinical variable #8: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S14. Basic characteristics of clinical feature: 'ETHNICITY'


ETHNICITY	Labels	N
	HISPANIC OR LATINO	16
	NOT HISPANIC OR LATINO	387

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = LGG-TP.miRseq_RPKM_log2.txt
Clinical data file = LGG-TP.merged_data.txt
Number of patients = 430
Number of miRs = 548
Number of clinical features = 8

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

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] 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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