Correlation between gene mutation status and selected clinical features

Brain Lower Grade Glioma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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 (2014): Correlation between gene mutation status and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C13J3BFM

Overview

Introduction

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

Summary

Testing the association between mutation status of 22 genes and 6 clinical features across 261 patients, 14 significant findings detected with Q value < 0.25.

NOTCH1 mutation correlated to 'HISTOLOGICAL.TYPE'.
IDH1 mutation correlated to 'Time to Death' and 'AGE'.
TP53 mutation correlated to 'AGE' and 'HISTOLOGICAL.TYPE'.
CIC mutation correlated to 'HISTOLOGICAL.TYPE'.
ATRX mutation correlated to 'AGE' and 'HISTOLOGICAL.TYPE'.
FUBP1 mutation correlated to 'HISTOLOGICAL.TYPE'.
EGFR mutation correlated to 'Time to Death' and 'AGE'.
PTEN mutation correlated to 'Time to Death' and 'AGE'.
NF1 mutation correlated to 'Time to Death'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 22 genes and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 14 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
IDH1	198 (76%)	63	9.52e-08 (1.18e-05)	0.00112 (0.13)	0.11 (1.00)	0.147 (1.00)	0.0237 (1.00)	0.758 (1.00)
TP53	132 (51%)	129	0.519 (1.00)	2.69e-07 (3.31e-05)	0.0822 (1.00)	0.329 (1.00)	1.47e-08 (1.85e-06)	0.0181 (1.00)
ATRX	104 (40%)	157	0.142 (1.00)	8.75e-08 (1.09e-05)	0.0312 (1.00)	0.318 (1.00)	6.25e-05 (0.0075)	0.0599 (1.00)
EGFR	15 (6%)	246	2.57e-11 (3.29e-09)	1.03e-08 (1.31e-06)	1 (1.00)	0.0759 (1.00)	0.375 (1.00)	0.154 (1.00)
PTEN	13 (5%)	248	5.75e-06 (0.000701)	0.000729 (0.0853)	0.574 (1.00)	0.146 (1.00)	0.00237 (0.272)	0.762 (1.00)
NOTCH1	24 (9%)	237	0.85 (1.00)	0.0157 (1.00)	0.669 (1.00)	0.715 (1.00)	0.000359 (0.0427)	0.497 (1.00)
CIC	52 (20%)	209	0.0629 (1.00)	0.304 (1.00)	0.277 (1.00)	0.515 (1.00)	8.19e-12 (1.06e-09)	0.068 (1.00)
FUBP1	26 (10%)	235	1 (1.00)	0.00247 (0.281)	0.838 (1.00)	0.87 (1.00)	6.62e-06 (0.000801)	1 (1.00)
NF1	19 (7%)	242	0.00038 (0.0449)	0.231 (1.00)	0.816 (1.00)	0.291 (1.00)	0.0377 (1.00)	0.202 (1.00)
PIK3CA	24 (9%)	237	0.0427 (1.00)	0.0936 (1.00)	0.831 (1.00)	0.481 (1.00)	0.0878 (1.00)	0.497 (1.00)
IDH2	12 (5%)	249	0.256 (1.00)	0.0382 (1.00)	0.772 (1.00)	0.919 (1.00)	0.00983 (1.00)	1 (1.00)
STK19	5 (2%)	256	0.688 (1.00)	0.691 (1.00)	0.659 (1.00)		0.523 (1.00)	0.177 (1.00)
PIK3R1	12 (5%)	249	0.575 (1.00)	0.0582 (1.00)	0.235 (1.00)	0.861 (1.00)	0.272 (1.00)	0.213 (1.00)
PCDHAC2	13 (5%)	248	0.699 (1.00)	0.185 (1.00)	0.574 (1.00)	0.456 (1.00)	0.204 (1.00)	0.127 (1.00)
CREBZF	4 (2%)	257	0.73 (1.00)	0.215 (1.00)	0.328 (1.00)	0.349 (1.00)	0.471 (1.00)	1 (1.00)
EIF1AX	4 (2%)	257	0.384 (1.00)	0.99 (1.00)	0.13 (1.00)	0.919 (1.00)	0.185 (1.00)	0.598 (1.00)
HTRA2	4 (2%)	257	0.852 (1.00)	0.136 (1.00)	0.63 (1.00)		0.566 (1.00)	0.307 (1.00)
VAV3	6 (2%)	255	0.39 (1.00)	0.918 (1.00)	0.413 (1.00)	0.0439 (1.00)	0.882 (1.00)	0.395 (1.00)
SPANXE	4 (2%)	257	0.39 (1.00)	0.987 (1.00)	1 (1.00)		0.388 (1.00)	1 (1.00)
TCF12	8 (3%)	253	0.3 (1.00)	0.0906 (1.00)	1 (1.00)	0.422 (1.00)	0.179 (1.00)	0.281 (1.00)
SMARCA4	12 (5%)	249	0.124 (1.00)	0.162 (1.00)	1 (1.00)	0.0156 (1.00)	0.702 (1.00)	0.0626 (1.00)
BCOR	8 (3%)	253	0.915 (1.00)	0.473 (1.00)	0.0242 (1.00)	0.0583 (1.00)	0.349 (1.00)	0.718 (1.00)

'NOTCH1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000359 (Fisher's exact test), Q value = 0.043

Table S1. Gene #1: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	81	74	106
NOTCH1 MUTATED	2	3	19
NOTCH1 WILD-TYPE	79	71	87

Figure S1. Get High-res Image Gene #1: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 9.52e-08 (logrank test), Q value = 1.2e-05

Table S2. Gene #4: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	261	55	0.0 - 182.3 (15.1)
IDH1 MUTATED	198	32	0.0 - 182.3 (16.0)
IDH1 WILD-TYPE	63	23	0.1 - 133.7 (11.9)

Figure S2. Get High-res Image Gene #4: 'IDH1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'IDH1 MUTATION STATUS' versus 'AGE'

P value = 0.00112 (t-test), Q value = 0.13

Table S3. Gene #4: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	261	42.9 (13.4)
IDH1 MUTATED	198	41.3 (12.8)
IDH1 WILD-TYPE	63	48.0 (14.3)

Figure S3. Get High-res Image Gene #4: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TP53 MUTATION STATUS' versus 'AGE'

P value = 2.69e-07 (t-test), Q value = 3.3e-05

Table S4. Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	261	42.9 (13.4)
TP53 MUTATED	132	38.8 (12.0)
TP53 WILD-TYPE	129	47.1 (13.5)

Figure S4. Get High-res Image Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.47e-08 (Fisher's exact test), Q value = 1.8e-06

Table S5. Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	81	74	106
TP53 MUTATED	54	48	30
TP53 WILD-TYPE	27	26	76

Figure S5. Get High-res Image Gene #5: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'CIC MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 8.19e-12 (Fisher's exact test), Q value = 1.1e-09

Table S6. Gene #7: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	81	74	106
CIC MUTATED	1	9	42
CIC WILD-TYPE	80	65	64

Figure S6. Get High-res Image Gene #7: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'ATRX MUTATION STATUS' versus 'AGE'

P value = 8.75e-08 (t-test), Q value = 1.1e-05

Table S7. Gene #8: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	261	42.9 (13.4)
ATRX MUTATED	104	37.7 (11.7)
ATRX WILD-TYPE	157	46.4 (13.4)

Figure S7. Get High-res Image Gene #8: 'ATRX MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'ATRX MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.25e-05 (Fisher's exact test), Q value = 0.0075

Table S8. Gene #8: 'ATRX MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	81	74	106
ATRX MUTATED	37	41	26
ATRX WILD-TYPE	44	33	80

Figure S8. Get High-res Image Gene #8: 'ATRX MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'FUBP1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.62e-06 (Fisher's exact test), Q value = 8e-04

Table S9. Gene #9: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	81	74	106
FUBP1 MUTATED	1	3	22
FUBP1 WILD-TYPE	80	71	84

Figure S9. Get High-res Image Gene #9: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'EGFR MUTATION STATUS' versus 'Time to Death'

P value = 2.57e-11 (logrank test), Q value = 3.3e-09

Table S10. Gene #10: 'EGFR MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	261	55	0.0 - 182.3 (15.1)
EGFR MUTATED	15	6	0.5 - 13.6 (6.5)
EGFR WILD-TYPE	246	49	0.0 - 182.3 (16.0)

Figure S10. Get High-res Image Gene #10: 'EGFR MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'EGFR MUTATION STATUS' versus 'AGE'

P value = 1.03e-08 (t-test), Q value = 1.3e-06

Table S11. Gene #10: 'EGFR MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	261	42.9 (13.4)
EGFR MUTATED	15	60.5 (7.1)
EGFR WILD-TYPE	246	41.8 (13.0)

Figure S11. Get High-res Image Gene #10: 'EGFR MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'PTEN MUTATION STATUS' versus 'Time to Death'

P value = 5.75e-06 (logrank test), Q value = 7e-04

Table S12. Gene #13: 'PTEN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	261	55	0.0 - 182.3 (15.1)
PTEN MUTATED	13	5	0.5 - 21.0 (10.4)
PTEN WILD-TYPE	248	50	0.0 - 182.3 (15.5)

Figure S12. Get High-res Image Gene #13: 'PTEN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'PTEN MUTATION STATUS' versus 'AGE'

P value = 0.000729 (t-test), Q value = 0.085

Table S13. Gene #13: 'PTEN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	261	42.9 (13.4)
PTEN MUTATED	13	55.3 (10.5)
PTEN WILD-TYPE	248	42.2 (13.3)

Figure S13. Get High-res Image Gene #13: 'PTEN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'NF1 MUTATION STATUS' versus 'Time to Death'

P value = 0.00038 (logrank test), Q value = 0.045

Table S14. Gene #21: 'NF1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	261	55	0.0 - 182.3 (15.1)
NF1 MUTATED	19	8	0.2 - 73.0 (18.0)
NF1 WILD-TYPE	242	47	0.0 - 182.3 (15.1)

Figure S14. Get High-res Image Gene #21: 'NF1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

Methods & Data

Input

Mutation data file = transformed.cor.cli.txt
Clinical data file = LGG-TP.merged_data.txt
Number of patients = 261
Number of significantly mutated genes = 22
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

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] 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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