Correlation between mutation rate and clinical features

Thyroid Adenocarcinoma (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 mutation rate and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1KW5F11

Overview

Introduction

This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.

Summary

Testing the association between 2 variables and 18 clinical features across 398 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one variables.

2 variables correlated to 'Time to Death'.

MUTATIONRATE_SILENT , MUTATIONRATE_NONSYNONYMOUS

2 variables correlated to 'AGE'.

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

2 variables correlated to 'AGE_mutation.rate'.

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

2 variables correlated to 'NEOPLASM.DISEASESTAGE'.

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

2 variables correlated to 'PATHOLOGY.T.STAGE'.

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

1 variable correlated to 'HISTOLOGICAL.TYPE'.

MUTATIONRATE_SILENT

2 variables correlated to 'EXTRATHYROIDAL.EXTENSION'.

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

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

MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT

1 variable correlated to 'TUMOR.SIZE'.

MUTATIONRATE_NONSYNONYMOUS

1 variable correlated to 'RACE'.

MUTATIONRATE_NONSYNONYMOUS

No variables correlated to 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'GENDER', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'RADIATIONEXPOSURE', 'NUMBER.OF.LYMPH.NODES', 'MULTIFOCALITY', 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 variables that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature	Statistical test	Significant variables	Associated with		Associated with
Time to Death	Cox regression test	N=2	shorter survival	N=2	longer survival	N=0
AGE	Spearman correlation test	N=2	older	N=2	younger	N=0
AGE	Linear Regression Analysis	N=2
NEOPLASM DISEASESTAGE	Kruskal-Wallis test	N=2
PATHOLOGY T STAGE	Spearman correlation test	N=2	higher stage	N=2	lower stage	N=0
PATHOLOGY N STAGE	Wilcoxon test	N=0
PATHOLOGY M STAGE	Kruskal-Wallis test	N=0
GENDER	Wilcoxon test	N=0
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=1
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=0
RADIATIONEXPOSURE	Wilcoxon test	N=0
EXTRATHYROIDAL EXTENSION	Kruskal-Wallis test	N=2
COMPLETENESS OF RESECTION	Kruskal-Wallis test	N=2
NUMBER OF LYMPH NODES	Spearman correlation test	N=0
MULTIFOCALITY	Wilcoxon test	N=0
TUMOR SIZE	Spearman correlation test	N=1	higher tumor.size	N=1	lower tumor.size	N=0
RACE	Kruskal-Wallis test	N=1
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'Time to Death'

2 variables related to 'Time to Death'.

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


Time to Death	Duration (Months)	0-158.8 (median=17)
	censored	N = 383
	death	N = 13

	Significant variables	N = 2
	associated with shorter survival	2
	associated with longer survival	0

List of 2 variables associated with 'Time to Death'

Table S2. Get Full Table List of 2 variables significantly associated with 'Time to Death' by Cox regression test

	HazardRatio	Wald_P	Q	C_index
MUTATIONRATE_SILENT	Inf	0.001069	0.0021	0.714
MUTATIONRATE_NONSYNONYMOUS	Inf	0.002274	0.0023	0.758

Clinical variable #2: 'AGE'

2 variables related to 'AGE'.

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


AGE	Mean (SD)	47.07 (16)
	Significant variables	N = 2
	pos. correlated	2
	neg. correlated	0

List of 2 variables associated with 'AGE'

Table S4. Get Full Table List of 2 variables significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
MUTATIONRATE_NONSYNONYMOUS	0.4607	2.615e-22	5.23e-22
MUTATIONRATE_SILENT	0.4219	1.315e-18	1.31e-18

Clinical variable #3: 'AGE'

2 variables related to 'AGE'.

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


AGE	Mean (SD)	47.07 (16)
	Significant variables	N = 2

List of 2 variables associated with 'AGE'

Table S6. Get Full Table List of 2 variables significantly correlated to 'AGE' by Linear regression analysis [lm (mutation rate ~ age)]. Compared to a correlation analysis testing for interdependence of the variables, a regression model attempts to describe the dependence of a variable on one (or more) explanatory variables assuming that there is a one-way causal effect from the explanatory variable(s) to the response variable. If 'Residuals vs Fitted' plot (a standard residual plot) shows a random pattern indicating a good fit for a linear model, it explains linear regression relationship between Mutation rate and age factor. Adj.R-squared (= Explained variation / Total variation) indicates regression model's explanatory power.

	Adj.R.squared	F	P	Residual.std.err	DF	coef(intercept)	coef.p(intercept)
MUTATIONRATE_NONSYNONYMOUS	0.183	89.8	2.49e-19	2.43e-07	396	7.44e-09 ( 3.7e-08 )	2.49e-19 ( 0.343 )
MUTATIONRATE_SILENT	0.141	66.3	5.06e-15	1.05e-07	396	2.76e-09 ( 2.46e-09 )	5.06e-15 ( 0.884 )

Clinical variable #4: 'NEOPLASM.DISEASESTAGE'

2 variables related to 'NEOPLASM.DISEASESTAGE'.

Table S7. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	228
	STAGE II	44
	STAGE III	83
	STAGE IV	2
	STAGE IVA	33
	STAGE IVC	6

	Significant variables	N = 2

List of 2 variables associated with 'NEOPLASM.DISEASESTAGE'

Table S8. Get Full Table List of 2 variables differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
MUTATIONRATE_NONSYNONYMOUS	5.089e-14	1.02e-13
MUTATIONRATE_SILENT	8.782e-10	8.78e-10

Clinical variable #5: 'PATHOLOGY.T.STAGE'

2 variables related to 'PATHOLOGY.T.STAGE'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'


PATHOLOGY.T.STAGE	Mean (SD)	2.1 (0.87)
		N
	1	116
	2	137
	3	127
	4	15

	Significant variables	N = 2
	pos. correlated	2
	neg. correlated	0

List of 2 variables associated with 'PATHOLOGY.T.STAGE'

Table S10. Get Full Table List of 2 variables significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
MUTATIONRATE_NONSYNONYMOUS	0.2021	5.212e-05	0.000104
MUTATIONRATE_SILENT	0.1224	0.01497	0.015

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

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

Table S11. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'


PATHOLOGY.N.STAGE	Labels	N
	class0	188
	class1	169

	Significant variables	N = 0

Clinical variable #7: 'PATHOLOGY.M.STAGE'

No variable related to 'PATHOLOGY.M.STAGE'.

Table S12. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'


PATHOLOGY.M.STAGE	Labels	N
	M0	219
	M1	7
	MX	171

	Significant variables	N = 0

Clinical variable #8: 'GENDER'

No variable related to 'GENDER'.

Table S13. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	297
	MALE	101

	Significant variables	N = 0

Clinical variable #9: 'HISTOLOGICAL.TYPE'

One variable related to 'HISTOLOGICAL.TYPE'.

Table S14. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	OTHER SPECIFY	6
	THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL	280
	THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED)	83
	THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)	29

	Significant variables	N = 1

List of one variable associated with 'HISTOLOGICAL.TYPE'

Table S15. Get Full Table List of one variable differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
MUTATIONRATE_SILENT	0.04024	0.0805

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

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

Table S16. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	12
	YES	386

	Significant variables	N = 0

Clinical variable #11: 'RADIATIONEXPOSURE'

No variable related to 'RADIATIONEXPOSURE'.

Table S17. Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'


RADIATIONEXPOSURE	Labels	N
	NO	334
	YES	15

	Significant variables	N = 0

Clinical variable #12: 'EXTRATHYROIDAL.EXTENSION'

2 variables related to 'EXTRATHYROIDAL.EXTENSION'.

Table S18. Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'


EXTRATHYROIDAL.EXTENSION	Labels	N
	MINIMAL (T3)	102
	MODERATE/ADVANCED (T4A)	11
	NONE	270
	VERY ADVANCED (T4B)	1

	Significant variables	N = 2

List of 2 variables associated with 'EXTRATHYROIDAL.EXTENSION'

Table S19. Get Full Table List of 2 variables differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

	ANOVA_P	Q
MUTATIONRATE_NONSYNONYMOUS	4.575e-05	9.15e-05
MUTATIONRATE_SILENT	0.0002119	0.000212

Clinical variable #13: 'COMPLETENESS.OF.RESECTION'

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

Table S20. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	311
	R1	37
	R2	3
	RX	22

	Significant variables	N = 2

List of 2 variables associated with 'COMPLETENESS.OF.RESECTION'

Table S21. Get Full Table List of 2 variables differentially expressed by 'COMPLETENESS.OF.RESECTION'

	ANOVA_P	Q
MUTATIONRATE_NONSYNONYMOUS	0.03689	0.0738
MUTATIONRATE_SILENT	0.04421	0.0738

Clinical variable #14: 'NUMBER.OF.LYMPH.NODES'

No variable related to 'NUMBER.OF.LYMPH.NODES'.

Table S22. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'


NUMBER.OF.LYMPH.NODES	Mean (SD)	3.3 (6)
	Significant variables	N = 0

Clinical variable #15: 'MULTIFOCALITY'

No variable related to 'MULTIFOCALITY'.

Table S23. Basic characteristics of clinical feature: 'MULTIFOCALITY'


MULTIFOCALITY	Labels	N
	MULTIFOCAL	180
	UNIFOCAL	209

	Significant variables	N = 0

Clinical variable #16: 'TUMOR.SIZE'

One variable related to 'TUMOR.SIZE'.

Table S24. Basic characteristics of clinical feature: 'TUMOR.SIZE'


TUMOR.SIZE	Mean (SD)	2.97 (1.6)
	Significant variables	N = 1
	pos. correlated	1
	neg. correlated	0

List of one variable associated with 'TUMOR.SIZE'

Table S25. Get Full Table List of one variable significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

	SpearmanCorr	corrP	Q
MUTATIONRATE_NONSYNONYMOUS	0.134	0.01577	0.0315

Clinical variable #17: 'RACE'

One variable related to 'RACE'.

Table S26. Basic characteristics of clinical feature: 'RACE'


RACE	Labels	N
	ASIAN	35
	BLACK OR AFRICAN AMERICAN	18
	WHITE	258

	Significant variables	N = 1

List of one variable associated with 'RACE'

Table S27. Get Full Table List of one variable differentially expressed by 'RACE'

	ANOVA_P	Q
MUTATIONRATE_NONSYNONYMOUS	0.04774	0.0955

Clinical variable #18: 'ETHNICITY'

No variable related to 'ETHNICITY'.

Table S28. Basic characteristics of clinical feature: 'ETHNICITY'


ETHNICITY	Labels	N
	HISPANIC OR LATINO	31
	NOT HISPANIC OR LATINO	283

	Significant variables	N = 0

Methods & Data

Input

Expresson data file = THCA-TP.patients.counts_and_rates.txt
Clinical data file = THCA-TP.merged_data.txt
Number of patients = 398
Number of variables = 2
Number of clinical features = 18

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.

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] 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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