Correlation between gene mutation status and selected clinical features

Sarcoma (Primary solid tumor)

21 August 2015 | analyses__2015_08_21

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1N58KN8

Overview

Introduction

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

Summary

Testing the association between mutation status of 23 genes and 9 clinical features across 244 patients, one significant finding detected with Q value < 0.25.

TP53 mutation correlated to 'HISTOLOGICAL_TYPE'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 23 genes and 9 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	YEARS TO BIRTH	TUMOR TISSUE SITE	GENDER	RADIATION THERAPY	HISTOLOGICAL TYPE	RESIDUAL TUMOR	RACE	ETHNICITY
	nMutated (%)	nWild-Type	logrank test	Wilcoxon-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
TP53	84 (34%)	160	0.648 (1.00)	0.333 (1.00)	0.168 (1.00)	0.685 (1.00)	1 (1.00)	1e-05 (0.00207)	0.772 (1.00)	0.746 (1.00)	0.177 (1.00)
ATRX	37 (15%)	207	0.224 (1.00)	0.0129 (0.737)	0.791 (1.00)	0.479 (1.00)	0.315 (1.00)	0.225 (1.00)	0.77 (1.00)	0.585 (1.00)	1 (1.00)
RB1	24 (10%)	220	0.962 (1.00)	0.922 (1.00)	0.907 (1.00)	0.202 (1.00)	0.0557 (1.00)	0.0328 (0.969)	0.602 (1.00)	1 (1.00)	1 (1.00)
NUMBL	9 (4%)	235	0.694 (1.00)	0.177 (1.00)	0.991 (1.00)	0.737 (1.00)	0.452 (1.00)	0.434 (1.00)	0.18 (1.00)	1 (1.00)	1 (1.00)
MSH3	7 (3%)	237	0.94 (1.00)	0.616 (1.00)	0.646 (1.00)	0.127 (1.00)	1 (1.00)	0.723 (1.00)	0.882 (1.00)	1 (1.00)	0.133 (1.00)
EOMES	6 (2%)	238	0.495 (1.00)	0.906 (1.00)	0.0701 (1.00)	0.42 (1.00)	0.0552 (1.00)	0.138 (1.00)	0.862 (1.00)	0.46 (1.00)	1 (1.00)
PKD2	6 (2%)	238	0.422 (1.00)	0.566 (1.00)	0.769 (1.00)	0.689 (1.00)	1 (1.00)	0.34 (1.00)	1 (1.00)	1 (1.00)	0.111 (1.00)
LTBP3	5 (2%)	239	0.591 (1.00)	0.692 (1.00)	0.373 (1.00)	0.665 (1.00)	0.325 (1.00)	0.66 (1.00)	0.479 (1.00)	0.401 (1.00)	1 (1.00)
SHROOM4	8 (3%)	236	0.372 (1.00)	0.728 (1.00)	0.771 (1.00)	0.292 (1.00)	1 (1.00)	0.816 (1.00)	0.813 (1.00)	0.174 (1.00)	1 (1.00)
WNK1	6 (2%)	238	0.633 (1.00)	0.444 (1.00)	0.174 (1.00)	0.42 (1.00)	0.188 (1.00)	0.284 (1.00)	0.731 (1.00)	1 (1.00)	1 (1.00)
ANP32E	4 (2%)	240	0.599 (1.00)	0.608 (1.00)	0.0944 (1.00)	0.626 (1.00)	1 (1.00)	0.573 (1.00)	0.369 (1.00)	0.111 (1.00)	1 (1.00)
PTEN	7 (3%)	237	0.712 (1.00)	0.277 (1.00)	0.0221 (0.916)	1 (1.00)	0.355 (1.00)	0.805 (1.00)	0.523 (1.00)	1 (1.00)	1 (1.00)
KRTAP5-5	7 (3%)	237	0.702 (1.00)	0.138 (1.00)	0.706 (1.00)	0.455 (1.00)	0.407 (1.00)	0.383 (1.00)	0.0993 (1.00)	1 (1.00)	0.153 (1.00)
TRAF7	4 (2%)	240	0.907 (1.00)	0.869 (1.00)	0.427 (1.00)	0.339 (1.00)	1 (1.00)	0.343 (1.00)	0.613 (1.00)	1 (1.00)	1 (1.00)
MEGF9	3 (1%)	241	0.258 (1.00)	0.299 (1.00)	0.0142 (0.737)	0.598 (1.00)	1 (1.00)	0.472 (1.00)	0.365 (1.00)	1 (1.00)	1 (1.00)
LOR	6 (2%)	238	0.94 (1.00)	0.869 (1.00)	0.3 (1.00)	0.42 (1.00)	1 (1.00)	0.202 (1.00)	0.413 (1.00)	1 (1.00)	1 (1.00)
CABLES1	3 (1%)	241	0.495 (1.00)	0.833 (1.00)	0.404 (1.00)	0.598 (1.00)	1 (1.00)	1 (1.00)	0.709 (1.00)	1 (1.00)	1 (1.00)
COL18A1	7 (3%)	237	0.99 (1.00)	0.374 (1.00)	0.074 (1.00)	0.254 (1.00)	0.407 (1.00)	0.213 (1.00)	0.33 (1.00)	0.513 (1.00)	1 (1.00)
LHCGR	6 (2%)	238	0.357 (1.00)	0.295 (1.00)	0.0789 (1.00)	1 (1.00)	0.355 (1.00)	0.0584 (1.00)	0.732 (1.00)	1 (1.00)	1 (1.00)
NF1	10 (4%)	234	0.584 (1.00)	0.156 (1.00)	0.167 (1.00)	1 (1.00)	0.475 (1.00)	0.0285 (0.969)	0.163 (1.00)	1 (1.00)	1 (1.00)
FOXD2	3 (1%)	241	0.266 (1.00)	0.704 (1.00)	0.759 (1.00)	1 (1.00)	1 (1.00)	0.173 (1.00)	1 (1.00)		1 (1.00)
MMP17	3 (1%)	241	0.24 (1.00)	0.329 (1.00)	0.19 (1.00)	0.598 (1.00)	0.561 (1.00)	0.00489 (0.506)	0.71 (1.00)	1 (1.00)	0.0459 (1.00)
ASTE1	3 (1%)	241	0.26 (1.00)	0.795 (1.00)	0.758 (1.00)	0.0979 (1.00)	1 (1.00)	0.0912 (1.00)	1 (1.00)	1 (1.00)	0.0682 (1.00)

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL_TYPE'

P value = 1e-05 (Fisher's exact test), Q value = 0.0021

Table S1. Gene #1: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'HISTOLOGICAL_TYPE'

nPatients	DEDIFFERENTIATED LIPOSARCOMA	DESMOID TUMOR	GIANT CELL 'MFH' / UNDIFFERENTIATED PLEOMORPHIC SARCOMA WITH GIANT CELLS	LEIOMYOSARCOMA (LMS)	MALIGNANT PERIPHERAL NERVE SHEATH TUMORS (MPNST)	MYXOFIBROSARCOMA	PLEOMORPHIC 'MFH'/ UNDIFFERENTIATED PLEOMORPHIC SARCOMA	SARCOMA; SYNOVIAL; POORLY DIFFERENTIATED	SYNOVIAL SARCOMA - BIPHASIC	SYNOVIAL SARCOMA - MONOPHASIC	UNDIFFERENTIATED PLEOMORPHIC SARCOMA (UPS)
ALL	56	2	1	97	8	21	29	2	2	6	20
TP53 MUTATED	5	0	0	49	1	9	12	0	0	0	8
TP53 WILD-TYPE	51	2	1	48	7	12	17	2	2	6	12

Figure S1. Get High-res Image Gene #1: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'HISTOLOGICAL_TYPE'

Methods & Data

Input

Mutation data file = sample_sig_gene_table.txt from Mutsig_2CV pipeline
Processed Mutation data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/SARC-TP/19898602/transformed.cor.cli.txt
Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/SARC-TP/19775498/SARC-TP.merged_data.txt
Number of patients = 244
Number of significantly mutated genes = 23
Number of selected clinical features = 9
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

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

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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)

[2] 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)

[3] 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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