Correlation between APOBEC signature variables and clinical features

Lung Adenocarcinoma (Primary solid tumor)

02 April 2015 | analyses__2015_04_02

Maintainer Information

Citation Information

Maintained by Juok Cho (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between APOBEC signature variables and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1057F0T

Overview

Introduction

This pipeline uses various statistical tests to identify selected clinical features related to APOBEC signature variables.

Summary

Testing the association between 3 variables and 15 clinical features across 480 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one variables.

1 variable correlated to 'YEARS_TO_BIRTH'.

[TCW_TO_G+TCW_TO_T]_PER_MUT

2 variables correlated to 'HISTOLOGICAL_TYPE'.

TCW_TO_G+TCW_TO_T , [TCW_TO_G+TCW_TO_T]_PER_MUT

2 variables correlated to 'NUMBER_PACK_YEARS_SMOKED'.

TCW_TO_G+TCW_TO_T , APOBEC_MUTLOAD_MINESTIMATE

1 variable correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

[TCW_TO_G+TCW_TO_T]_PER_MUT

1 variable correlated to 'RACE'.

[TCW_TO_G+TCW_TO_T]_PER_MUT

No variables correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'NEOPLASM_DISEASESTAGE', 'PATHOLOGY_T_STAGE', 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', 'GENDER', 'KARNOFSKY_PERFORMANCE_SCORE', 'RADIATIONS_RADIATION_REGIMENINDICATION', '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 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
DAYS_TO_DEATH_OR_LAST_FUP	Cox regression test	N=0
YEARS_TO_BIRTH	Spearman correlation test	N=1	older	N=1	younger	N=0
NEOPLASM_DISEASESTAGE	Kruskal-Wallis test	N=0
PATHOLOGY_T_STAGE	Spearman correlation test	N=0
PATHOLOGY_N_STAGE	Spearman correlation test	N=0
PATHOLOGY_M_STAGE	Wilcoxon test	N=0
GENDER	Wilcoxon test	N=0
KARNOFSKY_PERFORMANCE_SCORE	Spearman correlation test	N=0
HISTOLOGICAL_TYPE	Kruskal-Wallis test	N=2
RADIATIONS_RADIATION_REGIMENINDICATION	Wilcoxon test	N=0
NUMBER_PACK_YEARS_SMOKED	Spearman correlation test	N=2	higher number_pack_years_smoked	N=2	lower number_pack_years_smoked	N=0
YEAR_OF_TOBACCO_SMOKING_ONSET	Spearman correlation test	N=1	higher year_of_tobacco_smoking_onset	N=0	lower year_of_tobacco_smoking_onset	N=1
COMPLETENESS_OF_RESECTION	Kruskal-Wallis test	N=0
RACE	Kruskal-Wallis test	N=1
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No variable related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1. Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'


DAYS_TO_DEATH_OR_LAST_FUP	Duration (Months)	0-224 (median=18)
	censored	N = 334
	death	N = 145

	Significant markers	N = 0

Clinical variable #2: 'YEARS_TO_BIRTH'

One variable related to 'YEARS_TO_BIRTH'.

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


YEARS_TO_BIRTH	Mean (SD)	65.74 (9.7)
	Significant variables	N = 1
	pos. correlated	1
	neg. correlated	0

List of one variable associated with 'YEARS_TO_BIRTH'

Table S3. Get Full Table List of one variable significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

	SpearmanCorr	corrP	Q
[TCW_TO_G+TCW_TO_T]_PER_MUT	0.1436	0.002294	0.00688

Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

No variable related to 'NEOPLASM_DISEASESTAGE'.

Table S4. Basic characteristics of clinical feature: 'NEOPLASM_DISEASESTAGE'


NEOPLASM_DISEASESTAGE	Labels	N
	STAGE I	4
	STAGE IA	123
	STAGE IB	133
	STAGE IIA	46
	STAGE IIB	67
	STAGE IIIA	70
	STAGE IIIB	11
	STAGE IV	25

	Significant variables	N = 0

Clinical variable #4: 'PATHOLOGY_T_STAGE'

No variable related to 'PATHOLOGY_T_STAGE'.

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


PATHOLOGY_T_STAGE	Mean (SD)	1.84 (0.74)
		N
	T1	155
	T2	261
	T3	43
	T4	18

	Significant variables	N = 0

Clinical variable #5: 'PATHOLOGY_N_STAGE'

No variable related to 'PATHOLOGY_N_STAGE'.

Table S6. Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'


PATHOLOGY_N_STAGE	Mean (SD)	0.5 (0.76)
		N
	N0	307
	N1	89
	N2	70
	N3	2

	Significant variables	N = 0

Clinical variable #6: 'PATHOLOGY_M_STAGE'

No variable related to 'PATHOLOGY_M_STAGE'.

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY_M_STAGE'


PATHOLOGY_M_STAGE	Labels	N
	class0	327
	class1	23

	Significant variables	N = 0

Clinical variable #7: 'GENDER'

No variable related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	259
	MALE	221

	Significant variables	N = 0

Clinical variable #8: 'KARNOFSKY_PERFORMANCE_SCORE'

No variable related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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


KARNOFSKY_PERFORMANCE_SCORE	Mean (SD)	83.93 (23)
	Significant variables	N = 0

Clinical variable #9: 'HISTOLOGICAL_TYPE'

2 variables related to 'HISTOLOGICAL_TYPE'.

Table S10. Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'


HISTOLOGICAL_TYPE	Labels	N
	LUNG ACINAR ADENOCARCINOMA	18
	LUNG ADENOCARCINOMA MIXED SUBTYPE	102
	LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS)	294
	LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS	4
	LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS	19
	LUNG CLEAR CELL ADENOCARCINOMA	2
	LUNG MICROPAPILLARY ADENOCARCINOMA	3
	LUNG MUCINOUS ADENOCARCINOMA	2
	LUNG PAPILLARY ADENOCARCINOMA	22
	LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA	5
	MUCINOUS (COLLOID) CARCINOMA	9

	Significant variables	N = 2

List of 2 variables associated with 'HISTOLOGICAL_TYPE'

Table S11. Get Full Table List of 2 variables differentially expressed by 'HISTOLOGICAL_TYPE'

	kruskal_wallis_P	Q
TCW_TO_G+TCW_TO_T	0.001263	0.00379
[TCW_TO_G+TCW_TO_T]_PER_MUT	0.01671	0.0251

Clinical variable #10: 'RADIATIONS_RADIATION_REGIMENINDICATION'

No variable related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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


RADIATIONS_RADIATION_REGIMENINDICATION	Labels	N
	NO	20
	YES	460

	Significant variables	N = 0

Clinical variable #11: 'NUMBER_PACK_YEARS_SMOKED'

2 variables related to 'NUMBER_PACK_YEARS_SMOKED'.

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


NUMBER_PACK_YEARS_SMOKED	Mean (SD)	41.72 (28)
	Significant variables	N = 2
	pos. correlated	2
	neg. correlated	0

List of 2 variables associated with 'NUMBER_PACK_YEARS_SMOKED'

Table S14. Get Full Table List of 2 variables significantly correlated to 'NUMBER_PACK_YEARS_SMOKED' by Spearman correlation test

	SpearmanCorr	corrP	Q
TCW_TO_G+TCW_TO_T	0.2065	0.0001479	0.000444
APOBEC_MUTLOAD_MINESTIMATE	0.1612	0.003187	0.00478

Clinical variable #12: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

One variable related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

Table S15. Basic characteristics of clinical feature: 'YEAR_OF_TOBACCO_SMOKING_ONSET'


YEAR_OF_TOBACCO_SMOKING_ONSET	Mean (SD)	1964.39 (12)
	Significant variables	N = 1
	pos. correlated	0
	neg. correlated	1

List of one variable associated with 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S16. Get Full Table List of one variable significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

	SpearmanCorr	corrP	Q
[TCW_TO_G+TCW_TO_T]_PER_MUT	-0.1395	0.02537	0.0761

Clinical variable #13: 'COMPLETENESS_OF_RESECTION'

No variable related to 'COMPLETENESS_OF_RESECTION'.

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


COMPLETENESS_OF_RESECTION	Labels	N
	R0	310
	R1	11
	R2	4
	RX	25

	Significant variables	N = 0

Clinical variable #14: 'RACE'

One variable related to 'RACE'.

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


RACE	Labels	N
	AMERICAN INDIAN OR ALASKA NATIVE	1
	ASIAN	7
	BLACK OR AFRICAN AMERICAN	29
	WHITE	377

	Significant variables	N = 1

List of one variable associated with 'RACE'

Table S19. Get Full Table List of one variable differentially expressed by 'RACE'

	kruskal_wallis_P	Q
[TCW_TO_G+TCW_TO_T]_PER_MUT	0.0373	0.112

Clinical variable #15: 'ETHNICITY'

No variable related to 'ETHNICITY'.

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


ETHNICITY	Labels	N
	HISPANIC OR LATINO	6
	NOT HISPANIC OR LATINO	349

	Significant variables	N = 0

Methods & Data

Input

Expresson data file = APOBEC_for_clinical.correlaion.input.continuous.txt
Clinical data file = LUAD-TP.merged_data.txt
Number of patients = 480
Number of variables = 3
Number of clinical features = 15

Selected clinical features

For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .
Survival time data

Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

if 'vital_status'==0(alive),

if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

if 'vital_status'==NA,excludes this case in survival analysis and report the case.

cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)

[4] 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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