Correlation between gene mutation status and selected clinical features

Overview

Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 55 genes and 5 clinical features across 507 patients, 2 significant findings detected with Q value < 0.25.

MAP3K1 mutation correlated to 'AGE'.
FGFR2 mutation correlated to 'Time to Death'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 55 genes and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	RADIATIONS RADIATION REGIMENINDICATION	NEOADJUVANT THERAPY
	nMutated (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test
MAP3K1	38 (7%)	469	0.916 (1.00)	0.000845 (0.231)	1 (1.00)	0.346 (1.00)	1 (1.00)
FGFR2	4 (1%)	503	2.21e-05 (0.00604)	0.219 (1.00)	1 (1.00)	1 (1.00)	0.645 (1.00)
GATA3	54 (11%)	453	0.812 (1.00)	0.00918 (1.00)	0.493 (1.00)	0.147 (1.00)	0.381 (1.00)
RUNX1	18 (4%)	489	0.236 (1.00)	0.481 (1.00)	1 (1.00)	0.422 (1.00)	1 (1.00)
AKT1	12 (2%)	495	0.223 (1.00)	0.548 (1.00)	1 (1.00)	0.194 (1.00)	0.769 (1.00)
PIK3CA	178 (35%)	329	0.455 (1.00)	0.0485 (1.00)	1 (1.00)	1 (1.00)	0.85 (1.00)
TP53	184 (36%)	323	0.966 (1.00)	0.186 (1.00)	0.0914 (1.00)	0.47 (1.00)	0.64 (1.00)
MAP2K4	20 (4%)	487	0.0878 (1.00)	0.134 (1.00)	1 (1.00)	0.611 (1.00)	0.166 (1.00)
CDH1	33 (7%)	474	0.909 (1.00)	0.0619 (1.00)	1 (1.00)	0.84 (1.00)	0.588 (1.00)
PTEN	17 (3%)	490	0.896 (1.00)	0.579 (1.00)	1 (1.00)	1 (1.00)	0.453 (1.00)
PIK3R1	14 (3%)	493	0.213 (1.00)	0.88 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
MLL3	37 (7%)	470	0.301 (1.00)	0.0094 (1.00)	1 (1.00)	0.566 (1.00)	0.166 (1.00)
TBX3	13 (3%)	494	0.235 (1.00)	0.0275 (1.00)	1 (1.00)	1 (1.00)	0.572 (1.00)
CBFB	8 (2%)	499	0.632 (1.00)	0.367 (1.00)	1 (1.00)	1 (1.00)	0.479 (1.00)
CTCF	13 (3%)	494	0.149 (1.00)	0.365 (1.00)	1 (1.00)	1 (1.00)	0.78 (1.00)
SF3B1	10 (2%)	497	0.386 (1.00)	0.378 (1.00)	1 (1.00)	1 (1.00)	0.534 (1.00)
FOXA1	8 (2%)	499	0.0014 (0.381)	0.0133 (1.00)	1 (1.00)	1 (1.00)	0.479 (1.00)
C9ORF102	5 (1%)	502	0.468 (1.00)	0.382 (1.00)	1 (1.00)	0.618 (1.00)	0.409 (1.00)
TBL1XR1	8 (2%)	499	0.811 (1.00)	0.0425 (1.00)	1 (1.00)	0.69 (1.00)	1 (1.00)
KLRG2	3 (1%)	504		0.307 (1.00)	1 (1.00)	0.184 (1.00)	0.572 (1.00)
GPS2	6 (1%)	501	0.242 (1.00)	0.986 (1.00)	1 (1.00)	0.668 (1.00)	1 (1.00)
VASN	6 (1%)	501	0.13 (1.00)	0.858 (1.00)	1 (1.00)	0.668 (1.00)	1 (1.00)
NCOR1	17 (3%)	490	0.624 (1.00)	0.53 (1.00)	1 (1.00)	0.58 (1.00)	0.142 (1.00)
ZFP36L1	7 (1%)	500	0.951 (1.00)	0.0859 (1.00)	1 (1.00)	0.198 (1.00)	0.248 (1.00)
AFF2	13 (3%)	494	0.887 (1.00)	0.0186 (1.00)	1 (1.00)	0.357 (1.00)	1 (1.00)
ERBB2	7 (1%)	500	0.298 (1.00)	0.208 (1.00)	1 (1.00)	0.68 (1.00)	0.045 (1.00)
C1ORF65	7 (1%)	500	0.254 (1.00)	0.656 (1.00)	1 (1.00)	0.0935 (1.00)	0.456 (1.00)
RPGR	10 (2%)	497	0.783 (1.00)	0.81 (1.00)	1 (1.00)	0.735 (1.00)	0.748 (1.00)
DALRD3	6 (1%)	501	0.613 (1.00)	0.0641 (1.00)	1 (1.00)	0.353 (1.00)	0.696 (1.00)
MYB	8 (2%)	499	0.219 (1.00)	0.255 (1.00)	1 (1.00)	0.224 (1.00)	0.285 (1.00)
RB1	9 (2%)	498	0.69 (1.00)	0.305 (1.00)	1 (1.00)	0.455 (1.00)	0.318 (1.00)
CCDC146	6 (1%)	501	0.609 (1.00)	0.772 (1.00)	1 (1.00)	0.353 (1.00)	0.238 (1.00)
CDKN1B	5 (1%)	502	0.469 (1.00)	0.982 (1.00)	1 (1.00)	1 (1.00)	0.409 (1.00)
LYSMD3	4 (1%)	503	0.736 (1.00)	0.58 (1.00)	1 (1.00)	1 (1.00)	0.645 (1.00)
ZNF268	4 (1%)	503	0.638 (1.00)	0.726 (1.00)	1 (1.00)	0.303 (1.00)	1 (1.00)
UBC	7 (1%)	500	0.292 (1.00)	0.548 (1.00)	1 (1.00)	1 (1.00)	0.132 (1.00)
NEK5	8 (2%)	499	0.672 (1.00)	0.106 (1.00)	1 (1.00)	0.456 (1.00)	0.479 (1.00)
PRRX1	5 (1%)	502	0.505 (1.00)	0.785 (1.00)	1 (1.00)	0.13 (1.00)	0.653 (1.00)
GPR32	5 (1%)	502	0.733 (1.00)	0.155 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
KCNT2	9 (2%)	498	0.717 (1.00)	0.251 (1.00)	1 (1.00)	0.455 (1.00)	0.742 (1.00)
KRT38	3 (1%)	504	0.518 (1.00)	0.359 (1.00)	1 (1.00)	1 (1.00)	0.572 (1.00)
KRAS	4 (1%)	503	0.532 (1.00)	0.209 (1.00)	1 (1.00)	0.579 (1.00)	0.146 (1.00)
SAAL1	4 (1%)	503	0.0658 (1.00)	0.957 (1.00)	1 (1.00)	1 (1.00)	0.645 (1.00)
AVPI1	4 (1%)	503	0.672 (1.00)	0.5 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
SRGAP1	8 (2%)	499	0.959 (1.00)	0.584 (1.00)	1 (1.00)	1 (1.00)	0.479 (1.00)
CHGB	7 (1%)	500	0.0351 (1.00)	0.23 (1.00)	1 (1.00)	1 (1.00)	0.248 (1.00)
ATN1	8 (2%)	499	0.235 (1.00)	0.72 (1.00)	1 (1.00)	0.456 (1.00)	0.479 (1.00)
HIST1H2BC	4 (1%)	503	0.556 (1.00)	0.657 (1.00)	1 (1.00)	1 (1.00)	0.312 (1.00)
PPEF1	7 (1%)	500	0.7 (1.00)	0.533 (1.00)	1 (1.00)	0.68 (1.00)	0.705 (1.00)
DCAF4L2	7 (1%)	500	0.595 (1.00)	0.625 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
CBLB	9 (2%)	498	0.367 (1.00)	0.556 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
HIST1H1C	4 (1%)	503	0.766 (1.00)	0.979 (1.00)	0.0466 (1.00)	0.579 (1.00)	1 (1.00)
HLA-DRB1	4 (1%)	503	0.551 (1.00)	0.616 (1.00)	1 (1.00)	0.579 (1.00)	0.312 (1.00)
TRIM6-TRIM34	4 (1%)	503	0.803 (1.00)	0.853 (1.00)	1 (1.00)	0.0647 (1.00)	0.312 (1.00)
SLC22A20	7 (1%)	500	0.776 (1.00)	0.84 (1.00)	1 (1.00)	0.399 (1.00)	0.456 (1.00)

'MAP3K1 MUTATION STATUS' versus 'AGE'

P value = 0.000845 (t-test), Q value = 0.23

Table S1. Gene #9: 'MAP3K1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	507	57.8 (13.1)
MAP3K1 MUTATED	38	64.7 (12.3)
MAP3K1 WILD-TYPE	469	57.2 (13.1)

Figure S1. Get High-res Image Gene #9: 'MAP3K1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'FGFR2 MUTATION STATUS' versus 'Time to Death'

P value = 2.21e-05 (logrank test), Q value = 0.006

Table S2. Gene #55: 'FGFR2 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	476	64	0.1 - 223.4 (24.4)
FGFR2 MUTATED	4	1	1.1 - 15.1 (10.8)
FGFR2 WILD-TYPE	472	63	0.1 - 223.4 (24.5)

Figure S2. Get High-res Image Gene #55: 'FGFR2 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

Methods & Data

Input

Mutation data file = BRCA.mutsig.cluster.txt
Clinical data file = BRCA.clin.merged.picked.txt
Number of patients = 507
Number of significantly mutated genes = 55
Number of selected clinical features = 5
Exclude genes that fewer than K tumors have mutations, K = 3

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' function in R

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)

[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[3] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)

[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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