Correlation between gene mutation status and selected clinical features

Brain Lower Grade Glioma (Primary solid tumor)

23 May 2013 | analyses__2013_05_23

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 (2013): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C11G0J9V

Overview

Introduction

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

Summary

Testing the association between mutation status of 16 genes and 6 clinical features across 204 patients, 10 significant findings detected with Q value < 0.25.

IDH1 mutation correlated to 'Time to Death'.
TP53 mutation correlated to 'AGE', 'HISTOLOGICAL.TYPE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
ATRX mutation correlated to 'AGE' and 'HISTOLOGICAL.TYPE'.
CIC mutation correlated to 'HISTOLOGICAL.TYPE'.
FUBP1 mutation correlated to 'HISTOLOGICAL.TYPE'.
NOTCH1 mutation correlated to 'HISTOLOGICAL.TYPE'.
PTEN mutation correlated to 'HISTOLOGICAL.TYPE'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 16 genes and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 10 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	KARNOFSKY PERFORMANCE SCORE	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION
	nMutated (%)	nWild-Type	logrank test	t-test	Fisher's exact test	t-test	Fisher's exact test	Fisher's exact test
TP53	105 (51%)	99	0.17 (1.00)	1.1e-06 (9.83e-05)	0.157 (1.00)	0.45 (1.00)	4.95e-07 (4.46e-05)	0.000926 (0.0768)
ATRX	87 (43%)	117	0.106 (1.00)	1.65e-05 (0.00145)	0.476 (1.00)	0.522 (1.00)	5.21e-05 (0.00453)	0.0294 (1.00)
IDH1	157 (77%)	47	0.000178 (0.0153)	0.0292 (1.00)	0.0186 (1.00)	0.842 (1.00)	0.00713 (0.571)	0.173 (1.00)
CIC	40 (20%)	164	0.0807 (1.00)	0.587 (1.00)	0.723 (1.00)	0.718 (1.00)	1.25e-09 (1.13e-07)	0.106 (1.00)
FUBP1	22 (11%)	182	0.743 (1.00)	0.00634 (0.514)	1 (1.00)	0.711 (1.00)	0.000973 (0.0798)	0.822 (1.00)
NOTCH1	18 (9%)	186	0.777 (1.00)	0.0158 (1.00)	0.318 (1.00)	0.119 (1.00)	0.000211 (0.0179)	0.801 (1.00)
PTEN	11 (5%)	193	0.279 (1.00)	0.0305 (1.00)	0.532 (1.00)		0.000493 (0.0414)	0.754 (1.00)
IL32	5 (2%)	199	0.00837 (0.662)	0.285 (1.00)	1 (1.00)	0.14 (1.00)	1 (1.00)	0.159 (1.00)
IDH2	8 (4%)	196	0.532 (1.00)	0.148 (1.00)	1 (1.00)		0.0399 (1.00)	1 (1.00)
PIK3R1	14 (7%)	190	0.196 (1.00)	0.0624 (1.00)	0.403 (1.00)	0.674 (1.00)	0.603 (1.00)	0.783 (1.00)
PIK3CA	19 (9%)	185	0.778 (1.00)	0.47 (1.00)	0.808 (1.00)	0.351 (1.00)	0.148 (1.00)	1 (1.00)
CREBZF	4 (2%)	200	0.648 (1.00)	0.22 (1.00)	0.312 (1.00)	0.291 (1.00)	0.477 (1.00)	1 (1.00)
TIMD4	5 (2%)	199	0.103 (1.00)	0.175 (1.00)	0.652 (1.00)	0.14 (1.00)	1 (1.00)	0.65 (1.00)
EMG1	4 (2%)	200	0.53 (1.00)	0.583 (1.00)	0.64 (1.00)		0.581 (1.00)	0.302 (1.00)
NOX4	5 (2%)	199	0.475 (1.00)	0.494 (1.00)	1 (1.00)		0.727 (1.00)	0.382 (1.00)
ZNF57	6 (3%)	198	0.249 (1.00)	0.759 (1.00)	0.242 (1.00)		0.149 (1.00)	1 (1.00)

'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 0.000178 (logrank test), Q value = 0.015

Table S1. Gene #3: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	203	49	0.0 - 211.2 (13.4)
IDH1 MUTATED	156	32	0.0 - 182.3 (15.2)
IDH1 WILD-TYPE	47	17	0.1 - 211.2 (8.4)

Figure S1. Get High-res Image Gene #3: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'TP53 MUTATION STATUS' versus 'AGE'

P value = 1.1e-06 (t-test), Q value = 9.8e-05

Table S2. Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	204	43.0 (13.3)
TP53 MUTATED	105	38.7 (11.8)
TP53 WILD-TYPE	99	47.6 (13.3)

Figure S2. Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 4.95e-07 (Fisher's exact test), Q value = 4.5e-05

Table S3. Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
TP53 MUTATED	39	38	27
TP53 WILD-TYPE	22	15	62

Figure S3. Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'TP53 MUTATION STATUS' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000926 (Fisher's exact test), Q value = 0.077

Table S4. Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients	NO	YES
ALL	80	124
TP53 MUTATED	53	52
TP53 WILD-TYPE	27	72

Figure S4. Get High-res Image Gene #4: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'ATRX MUTATION STATUS' versus 'AGE'

P value = 1.65e-05 (t-test), Q value = 0.0014

Table S5. Gene #5: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	204	43.0 (13.3)
ATRX MUTATED	87	38.5 (12.1)
ATRX WILD-TYPE	117	46.4 (13.2)

Figure S5. Get High-res Image Gene #5: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'ATRX MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 5.21e-05 (Fisher's exact test), Q value = 0.0045

Table S6. Gene #5: 'ATRX MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
ATRX MUTATED	29	34	24
ATRX WILD-TYPE	32	19	65

Figure S6. Get High-res Image Gene #5: 'ATRX MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'CIC MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.25e-09 (Fisher's exact test), Q value = 1.1e-07

Table S7. Gene #6: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
CIC MUTATED	2	3	35
CIC WILD-TYPE	59	50	54

Figure S7. Get High-res Image Gene #6: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'FUBP1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000973 (Fisher's exact test), Q value = 0.08

Table S8. Gene #7: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
FUBP1 MUTATED	2	2	18
FUBP1 WILD-TYPE	59	51	71

Figure S8. Get High-res Image Gene #7: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'NOTCH1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000211 (Fisher's exact test), Q value = 0.018

Table S9. Gene #8: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
NOTCH1 MUTATED	1	1	16
NOTCH1 WILD-TYPE	60	52	73

Figure S9. Get High-res Image Gene #8: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'PTEN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000493 (Fisher's exact test), Q value = 0.041

Table S10. Gene #12: 'PTEN MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	61	53	89
PTEN MUTATED	9	0	2
PTEN WILD-TYPE	52	53	87

Figure S10. Get High-res Image Gene #12: 'PTEN MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

Methods & Data

Input

Mutation data file = LGG-TP.mutsig.cluster.txt
Clinical data file = LGG-TP.clin.merged.picked.txt
Number of patients = 204
Number of significantly mutated genes = 16
Number of selected clinical features = 6
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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