Correlation between miRseq expression and clinical features

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 545 miRs and 14 clinical features across 396 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

7 miRs correlated to 'Time to Death'.

HSA-MIR-628 , HSA-MIR-3605 , HSA-MIR-185 , HSA-MIR-99B , HSA-MIR-128-2 , ...

5 miRs correlated to 'AGE'.

HSA-MIR-99A , HSA-LET-7C , HSA-MIR-10A , HSA-MIR-125B-2 , HSA-MIR-100

2 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

HSA-MIR-23C , HSA-MIR-126

13 miRs correlated to 'PATHOLOGY.M.STAGE'.

HSA-MIR-26A-1 , HSA-MIR-140 , HSA-MIR-16-1 , HSA-MIR-361 , HSA-MIR-1277 , ...

2 miRs correlated to 'GENDER'.

HSA-MIR-375 , HSA-MIR-516A-1

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

HSA-MIR-26A-1 , HSA-MIR-628 , HSA-MIR-3653 , HSA-MIR-3647 , HSA-MIR-140 , ...

2 miRs correlated to 'HISTOLOGICAL.TYPE'.

HSA-MIR-29A , HSA-MIR-17

2 miRs correlated to 'RACE'.

HSA-MIR-1269 , HSA-MIR-412

No miRs correlated to 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'COMPLETENESS.OF.RESECTION', 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=7	shorter survival	N=4	longer survival	N=3
AGE	Spearman correlation test	N=5	older	N=5	younger	N=0
NEOPLASM DISEASESTAGE	Kruskal-Wallis test	N=2
PATHOLOGY T STAGE	Spearman correlation test	N=0
PATHOLOGY N STAGE	Spearman correlation test	N=0
PATHOLOGY M STAGE	Kruskal-Wallis test	N=13
GENDER	Wilcoxon test	N=2	male	N=2	female	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=50	higher score	N=6	lower score	N=44
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=2
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=0
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
COMPLETENESS OF RESECTION	Kruskal-Wallis test	N=0
RACE	Kruskal-Wallis test	N=2
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'Time to Death'

7 miRs related to 'Time to Death'.

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


Time to Death	Duration (Years)	1-5287 (median=639)
	censored	N = 254
	death	N = 109

	Significant markers	N = 7
	associated with shorter survival	4
	associated with longer survival	3

List of 7 miRs differentially expressed by 'Time to Death'

Table S2. Get Full Table List of 7 miRs significantly associated with 'Time to Death' by Cox regression test

	HazardRatio	Wald_P	Q	C_index
HSA-MIR-628	1.26	6.406e-05	0.035	0.686
HSA-MIR-3605	1.41	8.086e-05	0.044	0.659
HSA-MIR-185	0.56	9.808e-05	0.053	0.374
HSA-MIR-99B	1.59	0.0001119	0.061	0.605
HSA-MIR-128-2	0.63	0.0001977	0.11	0.373
HSA-MIR-128-1	0.61	0.0002192	0.12	0.375
HSA-MIR-3607	1.25	0.0004998	0.27	0.65

Clinical variable #2: 'AGE'

5 miRs related to 'AGE'.

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


AGE	Mean (SD)	67.37 (8.7)
	Significant markers	N = 5
	pos. correlated	5
	neg. correlated	0

List of 5 miRs differentially expressed by 'AGE'

Table S4. Get Full Table List of 5 miRs significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
HSA-MIR-99A	0.2107	2.804e-05	0.0153
HSA-LET-7C	0.2086	3.385e-05	0.0184
HSA-MIR-10A	0.1958	0.0001011	0.0549
HSA-MIR-125B-2	0.1784	0.000414	0.224
HSA-MIR-100	0.1757	0.0005003	0.271

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

2 miRs related to 'NEOPLASM.DISEASESTAGE'.

Table S5. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	2
	STAGE IA	68
	STAGE IB	128
	STAGE II	1
	STAGE IIA	49
	STAGE IIB	69
	STAGE IIIA	55
	STAGE IIIB	17
	STAGE IV	5

	Significant markers	N = 2

List of 2 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6. Get Full Table List of 2 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
HSA-MIR-23C	0.0003019	0.165
HSA-MIR-126	0.0004467	0.243

Clinical variable #4: 'PATHOLOGY.T.STAGE'

No miR related to 'PATHOLOGY.T.STAGE'.

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'


PATHOLOGY.T.STAGE	Mean (SD)	1.97 (0.73)
		N
	1	92
	2	240
	3	46
	4	18

	Significant markers	N = 0

Clinical variable #5: 'PATHOLOGY.N.STAGE'

No miR related to 'PATHOLOGY.N.STAGE'.

Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'


PATHOLOGY.N.STAGE	Mean (SD)	0.48 (0.7)
		N
	0	244
	1	107
	2	35
	3	4

	Significant markers	N = 0

Clinical variable #6: 'PATHOLOGY.M.STAGE'

13 miRs related to 'PATHOLOGY.M.STAGE'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'


PATHOLOGY.M.STAGE	Labels	N
	M0	336
	M1	4
	M1A	1
	MX	49

	Significant markers	N = 13

List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10. Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

	ANOVA_P	Q
HSA-MIR-26A-1	9.82e-07	0.000535
HSA-MIR-140	8.379e-06	0.00456
HSA-MIR-16-1	1.6e-05	0.00869
HSA-MIR-361	3.884e-05	0.021
HSA-MIR-1277	3.96e-05	0.0214
HSA-MIR-3615	0.0001735	0.0937
HSA-MIR-627	0.0001985	0.107
HSA-MIR-106A	0.000204	0.11
HSA-MIR-181A-1	0.0002776	0.149
HSA-MIR-628	0.0003647	0.196

Clinical variable #7: 'GENDER'

2 miRs related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	101
	MALE	295

	Significant markers	N = 2
	Higher in MALE	2
	Higher in FEMALE	0

List of 2 miRs differentially expressed by 'GENDER'

Table S12. Get Full Table List of 2 miRs differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

	W(pos if higher in 'MALE')	wilcoxontestP	Q	AUC
HSA-MIR-375	11040	0.0001024	0.0558	0.6295
HSA-MIR-516A-1	6355	0.0003593	0.195	0.6568

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S13. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	53.14 (42)
	Significant markers	N = 50
	pos. correlated	6
	neg. correlated	44

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

Table S14. Get Full Table List of top 10 miRs significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

	SpearmanCorr	corrP	Q
HSA-MIR-26A-1	-0.6367	5.763e-11	3.14e-08
HSA-MIR-628	-0.596	1.413e-09	7.68e-07
HSA-MIR-3653	-0.568	1.172e-08	6.36e-06
HSA-MIR-3647	-0.5555	2.829e-08	1.53e-05
HSA-MIR-140	0.5551	2.903e-08	1.57e-05
HSA-MIR-3607	-0.547	5.052e-08	2.73e-05
HSA-MIR-30E	-0.5446	5.957e-08	3.21e-05
HSA-MIR-186	-0.508	5.96e-07	0.000321
HSA-LET-7G	-0.497	1.132e-06	0.000608
HSA-MIR-3605	-0.4862	2.077e-06	0.00111

Clinical variable #9: 'HISTOLOGICAL.TYPE'

2 miRs related to 'HISTOLOGICAL.TYPE'.

Table S15. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	LUNG BASALOID SQUAMOUS CELL CARCINOMA	10
	LUNG PAPILLARY SQUAMOUS CELL CARICNOMA	6
	LUNG SMALL CELL SQUAMOUS CELL CARCINOMA	1
	LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS)	379

	Significant markers	N = 2

List of 2 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

Table S16. Get Full Table List of 2 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
HSA-MIR-29A	0.0001771	0.0965
HSA-MIR-17	0.0004371	0.238

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S17. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	12
	YES	384

	Significant markers	N = 0

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No miR related to 'NUMBERPACKYEARSSMOKED'.

Table S18. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'


NUMBERPACKYEARSSMOKED	Mean (SD)	53.57 (32)
	Significant markers	N = 0

Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

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

Table S19. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	322
	R1	7
	R2	3
	RX	16

	Significant markers	N = 0

Clinical variable #13: 'RACE'

2 miRs related to 'RACE'.

Table S20. Basic characteristics of clinical feature: 'RACE'


RACE	Labels	N
	ASIAN	9
	BLACK OR AFRICAN AMERICAN	16
	WHITE	282

	Significant markers	N = 2

List of 2 miRs differentially expressed by 'RACE'

Table S21. Get Full Table List of 2 miRs differentially expressed by 'RACE'

	ANOVA_P	Q
HSA-MIR-1269	8.238e-05	0.0449
HSA-MIR-412	0.000251	0.137

Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S22. Basic characteristics of clinical feature: 'ETHNICITY'


ETHNICITY	Labels	N
	HISPANIC OR LATINO	7
	NOT HISPANIC OR LATINO	252

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = LUSC-TP.miRseq_RPKM_log2.txt
Clinical data file = LUSC-TP.merged_data.txt
Number of patients = 396
Number of miRs = 545
Number of clinical features = 14

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.

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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