Breast Invasive Carcinoma: Correlation between gene mutation status and selected clinical features

Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)

Overview

Introduction

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

Summary

Testing the association between mutation status of 57 genes and 5 clinical features across 507 patients, one significant finding detected with Q value < 0.25.

FAM169A mutation correlated to 'Time to Death'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 57 genes and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding 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
FAM169A	4 (1%)	503	0.000797 (0.221)	0.556 (1.00)	1 (1.00)	1 (1.00)	0.644 (1.00)
ERBB3	9 (2%)	498	0.00314 (0.866)	0.403 (1.00)	1 (1.00)	0.455 (1.00)	0.317 (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)
SHD	6 (1%)	501	0.334 (1.00)	0.603 (1.00)	1 (1.00)	1 (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)
TLN1	9 (2%)	498	0.186 (1.00)	0.269 (1.00)	1 (1.00)	1 (1.00)	0.317 (1.00)
ERBB2	7 (1%)	500	0.298 (1.00)	0.208 (1.00)	1 (1.00)	0.68 (1.00)	0.248 (1.00)
ZCWPW1	4 (1%)	503	0.295 (1.00)	0.842 (1.00)	1 (1.00)	1 (1.00)	0.644 (1.00)
PDCD11	6 (1%)	501	0.647 (1.00)	0.819 (1.00)	1 (1.00)	1 (1.00)	0.408 (1.00)
PRPF38B	4 (1%)	503	0.646 (1.00)	0.662 (1.00)	0.0466 (1.00)	1 (1.00)	0.644 (1.00)
FAM58A	3 (1%)	504	0.803 (1.00)	0.537 (1.00)	1 (1.00)	1 (1.00)	0.573 (1.00)
AQP7	3 (1%)	504	0.737 (1.00)	0.651 (1.00)	1 (1.00)	1 (1.00)	0.573 (1.00)
HLA-C	3 (1%)	504	0.599 (1.00)	0.786 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
KIFC1	5 (1%)	502	0.611 (1.00)	0.906 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
CAD	7 (1%)	500	0.74 (1.00)	0.634 (1.00)	1 (1.00)	0.68 (1.00)	1 (1.00)
HIST1H3B	4 (1%)	503	0.577 (1.00)	0.399 (1.00)	1 (1.00)	0.303 (1.00)	0.313 (1.00)
DHRS2	3 (1%)	504	0.00519 (1.00)	0.452 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
FCRL1	3 (1%)	504		0.599 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
KLC4	4 (1%)	503	0.612 (1.00)	0.422 (1.00)	1 (1.00)	0.303 (1.00)	0.313 (1.00)
KRT28	3 (1%)	504	0.267 (1.00)	0.393 (1.00)	1 (1.00)	0.565 (1.00)	1 (1.00)
DLGAP4	6 (1%)	501	0.822 (1.00)	0.274 (1.00)	1 (1.00)	0.668 (1.00)	1 (1.00)
ACADSB	3 (1%)	504		0.612 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
NKTR	3 (1%)	504	0.693 (1.00)	0.784 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
ZNF473	3 (1%)	504	0.544 (1.00)	0.821 (1.00)	1 (1.00)	1 (1.00)	0.573 (1.00)
C17ORF68	3 (1%)	504	0.888 (1.00)	0.1 (1.00)	1 (1.00)	0.565 (1.00)	1 (1.00)
CA9	3 (1%)	504	0.639 (1.00)	0.665 (1.00)	1 (1.00)	1 (1.00)	0.0715 (1.00)
GLYR1	3 (1%)	504		0.838 (1.00)	1 (1.00)	0.184 (1.00)	0.573 (1.00)
MYH4	6 (1%)	501	0.778 (1.00)	0.869 (1.00)	1 (1.00)	0.668 (1.00)	1 (1.00)
ZNF296	3 (1%)	504	0.285 (1.00)	0.486 (1.00)	1 (1.00)	0.565 (1.00)	1 (1.00)
PCDHGA9	3 (1%)	504		0.198 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
DNAH2	10 (2%)	497	0.612 (1.00)	0.684 (1.00)	1 (1.00)	1 (1.00)	0.206 (1.00)
CDHR1	5 (1%)	502	0.205 (1.00)	0.676 (1.00)	1 (1.00)	1 (1.00)	0.407 (1.00)
RBPJL	4 (1%)	503	0.164 (1.00)	0.377 (1.00)	1 (1.00)	0.303 (1.00)	1 (1.00)
TRIM46	3 (1%)	504	0.779 (1.00)	0.886 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
LRRC8A	3 (1%)	504	0.558 (1.00)	0.669 (1.00)	1 (1.00)	0.184 (1.00)	0.0715 (1.00)
VSIG1	3 (1%)	504		0.646 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
SEC31B	4 (1%)	503	0.508 (1.00)	0.523 (1.00)	1 (1.00)	0.303 (1.00)	0.313 (1.00)
ZNF544	3 (1%)	504	0.65 (1.00)	0.496 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
GBF1	4 (1%)	503	0.684 (1.00)	0.739 (1.00)	1 (1.00)	0.303 (1.00)	1 (1.00)
MUC12	9 (2%)	498	0.0782 (1.00)	0.849 (1.00)	1 (1.00)	0.266 (1.00)	0.0379 (1.00)
PPP3CB	3 (1%)	504	0.753 (1.00)	0.715 (1.00)	1 (1.00)	0.565 (1.00)	1 (1.00)
SUOX	3 (1%)	504	0.653 (1.00)	0.268 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
TRIM5	3 (1%)	504	0.537 (1.00)	0.67 (1.00)	1 (1.00)	0.565 (1.00)	0.573 (1.00)
SERTAD3	3 (1%)	504	0.00174 (0.482)	0.252 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
BACH2	5 (1%)	502	0.538 (1.00)	0.393 (1.00)	0.058 (1.00)	0.33 (1.00)	0.407 (1.00)
GPR162	4 (1%)	503	0.0987 (1.00)	0.23 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
ATG4D	3 (1%)	504		0.0713 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
PCDHB7	6 (1%)	501	0.597 (1.00)	0.473 (1.00)	1 (1.00)	0.353 (1.00)	0.697 (1.00)
C17ORF81	3 (1%)	504	0.285 (1.00)	0.926 (1.00)	1 (1.00)	0.184 (1.00)	1 (1.00)
PLXDC1	3 (1%)	504	0.54 (1.00)	0.618 (1.00)	1 (1.00)	1 (1.00)	0.573 (1.00)
RORC	3 (1%)	504	0.668 (1.00)	0.212 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)
SLC35B2	4 (1%)	503	0.0423 (1.00)	0.252 (1.00)	1 (1.00)	0.303 (1.00)	0.313 (1.00)
HOXA1	3 (1%)	504	0.742 (1.00)	0.151 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
SLC22A11	3 (1%)	504	0.895 (1.00)	0.327 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
LRIT2	3 (1%)	504	0.387 (1.00)	0.812 (1.00)	1 (1.00)	1 (1.00)	0.573 (1.00)
HRNR	9 (2%)	498	0.41 (1.00)	0.339 (1.00)	1 (1.00)	0.455 (1.00)	0.741 (1.00)
SLCO2A1	3 (1%)	504		0.659 (1.00)	1 (1.00)	0.565 (1.00)	0.27 (1.00)

'FAM169A MUTATION STATUS' versus 'Time to Death'

P value = 0.000797 (logrank test), Q value = 0.22

Table S1. Gene #8: 'FAM169A MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	476	64	0.1 - 223.4 (24.4)
FAM169A MUTATED	4	1	1.0 - 26.7 (7.7)
FAM169A WILD-TYPE	472	63	0.1 - 223.4 (24.5)

Figure S1. Get High-res Image Gene #8: 'FAM169A 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 = 57
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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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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