Brain Lower Grade Glioma: Correlation between copy number variations of arm-level result and selected clinical features<BR>(primary solid tumor cohort)

Brain Lower Grade Glioma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor cohort)

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

Overview

Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 49 arm-level results and 6 clinical features across 178 patients, 14 significant findings detected with Q value < 0.25.

12q gain cnv correlated to 'AGE'.
19q gain cnv correlated to 'Time to Death'.
20p gain cnv correlated to 'Time to Death'.
20q gain cnv correlated to 'Time to Death'.
1p loss cnv correlated to 'HISTOLOGICAL.TYPE' and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
3p loss cnv correlated to 'AGE'.
6p loss cnv correlated to 'Time to Death'.
10p loss cnv correlated to 'Time to Death' and 'AGE'.
10q loss cnv correlated to 'Time to Death' and 'AGE'.
19q loss cnv correlated to 'HISTOLOGICAL.TYPE'.
22q loss cnv correlated to 'Time to Death'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 49 arm-level results 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
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	t-test	Fisher's exact test	Fisher's exact test
1p loss	55 (31%)	123	0.132 (1.00)	0.019 (1.00)	1 (1.00)	0.78 (1.00)	3.64e-15 (1.03e-12)	0.000625 (0.168)
10p loss	26 (15%)	152	9.19e-11 (2.57e-08)	1.95e-06 (0.00054)	0.0522 (1.00)	0.838 (1.00)	0.023 (1.00)	0.832 (1.00)
10q loss	27 (15%)	151	2.08e-10 (5.81e-08)	1.03e-06 (0.000287)	0.0332 (1.00)	0.883 (1.00)	0.0115 (1.00)	0.676 (1.00)
12q gain	4 (2%)	174	0.195 (1.00)	2.67e-05 (0.00731)	0.137 (1.00)		0.819 (1.00)	1 (1.00)
19q gain	6 (3%)	172	0.000486 (0.131)	0.0584 (1.00)	0.241 (1.00)	0.267 (1.00)	0.496 (1.00)	0.22 (1.00)
20p gain	15 (8%)	163	0.000193 (0.0524)	0.0246 (1.00)	0.18 (1.00)	0.937 (1.00)	0.406 (1.00)	0.419 (1.00)
20q gain	13 (7%)	165	0.000463 (0.126)	0.0479 (1.00)	0.243 (1.00)	0.847 (1.00)	0.503 (1.00)	0.774 (1.00)
3p loss	4 (2%)	174	0.89 (1.00)	5.59e-06 (0.00154)	0.637 (1.00)		0.686 (1.00)	0.336 (1.00)
6p loss	5 (3%)	173	0.000146 (0.0398)	0.801 (1.00)	1 (1.00)	0.847 (1.00)	0.449 (1.00)	1 (1.00)
19q loss	64 (36%)	114	0.175 (1.00)	0.0498 (1.00)	0.753 (1.00)	0.911 (1.00)	2.56e-11 (7.19e-09)	0.00824 (1.00)
22q loss	13 (7%)	165	1.61e-05 (0.00443)	0.692 (1.00)	0.562 (1.00)	0.181 (1.00)	0.00786 (1.00)	0.264 (1.00)
1p gain	6 (3%)	172	0.00803 (1.00)	0.171 (1.00)	0.085 (1.00)	0.167 (1.00)	0.0221 (1.00)	1 (1.00)
1q gain	8 (4%)	170	0.289 (1.00)	0.00482 (1.00)	0.289 (1.00)	0.558 (1.00)	0.486 (1.00)	0.727 (1.00)
7p gain	31 (17%)	147	0.0119 (1.00)	0.0904 (1.00)	0.0722 (1.00)	0.992 (1.00)	0.184 (1.00)	0.113 (1.00)
7q gain	43 (24%)	135	0.0189 (1.00)	0.00311 (0.82)	0.218 (1.00)	0.665 (1.00)	0.273 (1.00)	0.22 (1.00)
8p gain	12 (7%)	166	0.702 (1.00)	0.859 (1.00)	0.56 (1.00)	0.652 (1.00)	0.281 (1.00)	0.0391 (1.00)
8q gain	15 (8%)	163	0.932 (1.00)	0.434 (1.00)	1 (1.00)	0.599 (1.00)	0.097 (1.00)	0.175 (1.00)
9p gain	4 (2%)	174	0.17 (1.00)	0.00546 (1.00)	0.314 (1.00)		0.819 (1.00)	1 (1.00)
9q gain	4 (2%)	174	0.0627 (1.00)	0.0911 (1.00)	0.314 (1.00)	0.167 (1.00)	0.219 (1.00)	0.625 (1.00)
10p gain	18 (10%)	160	0.454 (1.00)	0.026 (1.00)	0.215 (1.00)	0.109 (1.00)	0.395 (1.00)	0.135 (1.00)
11p gain	9 (5%)	169	0.606 (1.00)	0.278 (1.00)	1 (1.00)	0.737 (1.00)	0.467 (1.00)	1 (1.00)
11q gain	13 (7%)	165	0.765 (1.00)	0.186 (1.00)	0.562 (1.00)	0.59 (1.00)	0.817 (1.00)	0.774 (1.00)
12p gain	9 (5%)	169	0.761 (1.00)	0.00201 (0.533)	0.0108 (1.00)		0.686 (1.00)	1 (1.00)
18p gain	4 (2%)	174	0.555 (1.00)	0.753 (1.00)	0.314 (1.00)		0.219 (1.00)	0.336 (1.00)
19p gain	8 (4%)	170	0.182 (1.00)	0.0121 (1.00)	0.469 (1.00)	0.0611 (1.00)	0.332 (1.00)	0.0709 (1.00)
21q gain	4 (2%)	174	0.291 (1.00)	0.964 (1.00)	0.637 (1.00)		0.469 (1.00)	0.625 (1.00)
1q loss	7 (4%)	171	0.497 (1.00)	0.0369 (1.00)	0.462 (1.00)	0.114 (1.00)	0.00523 (1.00)	1 (1.00)
2p loss	4 (2%)	174	0.0729 (1.00)	0.67 (1.00)	0.637 (1.00)		0.686 (1.00)	0.625 (1.00)
2q loss	3 (2%)	175	0.521 (1.00)	0.186 (1.00)	0.262 (1.00)		0.112 (1.00)	0.595 (1.00)
3q loss	9 (5%)	169	0.619 (1.00)	0.863 (1.00)	0.734 (1.00)	0.223 (1.00)	0.427 (1.00)	1 (1.00)
4p loss	15 (8%)	163	0.121 (1.00)	0.255 (1.00)	0.276 (1.00)	0.554 (1.00)	0.061 (1.00)	0.289 (1.00)
4q loss	24 (13%)	154	0.0928 (1.00)	0.864 (1.00)	0.661 (1.00)	0.383 (1.00)	0.273 (1.00)	0.271 (1.00)
5p loss	10 (6%)	168	0.242 (1.00)	0.99 (1.00)	0.52 (1.00)	0.209 (1.00)	0.00573 (1.00)	0.345 (1.00)
5q loss	7 (4%)	171	0.0138 (1.00)	0.82 (1.00)	0.462 (1.00)	0.167 (1.00)	0.374 (1.00)	0.126 (1.00)
6q loss	19 (11%)	159	0.00578 (1.00)	0.134 (1.00)	0.463 (1.00)	0.185 (1.00)	0.0305 (1.00)	0.00633 (1.00)
9p loss	34 (19%)	144	0.00826 (1.00)	0.0866 (1.00)	1 (1.00)	0.57 (1.00)	0.087 (1.00)	0.0039 (1.00)
9q loss	6 (3%)	172	0.918 (1.00)	0.116 (1.00)	0.404 (1.00)	0.609 (1.00)	0.576 (1.00)	0.416 (1.00)
11p loss	17 (10%)	161	0.13 (1.00)	0.167 (1.00)	0.798 (1.00)	0.826 (1.00)	0.00156 (0.415)	0.202 (1.00)
11q loss	4 (2%)	174	0.00128 (0.343)	0.0652 (1.00)	0.314 (1.00)		0.219 (1.00)	0.625 (1.00)
12q loss	8 (4%)	170	0.428 (1.00)	0.887 (1.00)	0.725 (1.00)	0.852 (1.00)	0.238 (1.00)	0.727 (1.00)
13q loss	27 (15%)	151	0.229 (1.00)	0.4 (1.00)	0.836 (1.00)	0.86 (1.00)	1 (1.00)	0.402 (1.00)
14q loss	21 (12%)	157	0.00187 (0.498)	0.0189 (1.00)	0.0324 (1.00)	0.481 (1.00)	0.148 (1.00)	0.353 (1.00)
15q loss	11 (6%)	167	0.266 (1.00)	0.575 (1.00)	0.357 (1.00)	0.807 (1.00)	0.0536 (1.00)	0.115 (1.00)
16q loss	6 (3%)	172	0.998 (1.00)	0.178 (1.00)	0.701 (1.00)		0.88 (1.00)	0.22 (1.00)
18p loss	13 (7%)	165	0.611 (1.00)	0.245 (1.00)	0.781 (1.00)	0.491 (1.00)	0.353 (1.00)	1 (1.00)
18q loss	15 (8%)	163	0.749 (1.00)	0.37 (1.00)	0.423 (1.00)	0.713 (1.00)	0.13 (1.00)	0.788 (1.00)
19p loss	6 (3%)	172	0.902 (1.00)	0.625 (1.00)	0.701 (1.00)	0.114 (1.00)	0.287 (1.00)	1 (1.00)
21q loss	5 (3%)	173	0.958 (1.00)	0.79 (1.00)	1 (1.00)		0.449 (1.00)	1 (1.00)
Xq loss	4 (2%)	174	0.333 (1.00)	0.608 (1.00)	1 (1.00)		0.787 (1.00)	0.125 (1.00)

'12q gain mutation analysis' versus 'AGE'

P value = 2.67e-05 (t-test), Q value = 0.0073

Table S1. Gene #13: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	178	43.1 (13.4)
12Q GAIN MUTATED	4	31.2 (2.4)
12Q GAIN WILD-TYPE	174	43.4 (13.4)

Figure S1. Get High-res Image Gene #13: '12q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'19q gain mutation analysis' versus 'Time to Death'

P value = 0.000486 (logrank test), Q value = 0.13

Table S2. Gene #16: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
19Q GAIN MUTATED	6	4	4.1 - 26.3 (17.2)
19Q GAIN WILD-TYPE	171	46	0.0 - 211.2 (14.5)

Figure S2. Get High-res Image Gene #16: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20p gain mutation analysis' versus 'Time to Death'

P value = 0.000193 (logrank test), Q value = 0.052

Table S3. Gene #17: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
20P GAIN MUTATED	15	7	3.8 - 41.1 (16.8)
20P GAIN WILD-TYPE	162	43	0.0 - 211.2 (14.5)

Figure S3. Get High-res Image Gene #17: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20q gain mutation analysis' versus 'Time to Death'

P value = 0.000463 (logrank test), Q value = 0.13

Table S4. Gene #18: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
20Q GAIN MUTATED	13	6	4.7 - 41.1 (15.3)
20Q GAIN WILD-TYPE	164	44	0.0 - 211.2 (14.6)

Figure S4. Get High-res Image Gene #18: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'1p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.64e-15 (Fisher's exact test), Q value = 1e-12

Table S5. Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	55	47	75
1P LOSS MUTATED	2	6	47
1P LOSS WILD-TYPE	53	41	28

Figure S5. Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'1p loss mutation analysis' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 0.000625 (Fisher's exact test), Q value = 0.17

Table S6. Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients	NO	YES
ALL	96	82
1P LOSS MUTATED	19	36
1P LOSS WILD-TYPE	77	46

Figure S6. Get High-res Image Gene #20: '1p loss mutation analysis' versus Clinical Feature #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'3p loss mutation analysis' versus 'AGE'

P value = 5.59e-06 (t-test), Q value = 0.0015

Table S7. Gene #24: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	178	43.1 (13.4)
3P LOSS MUTATED	4	31.0 (2.2)
3P LOSS WILD-TYPE	174	43.4 (13.4)

Figure S7. Get High-res Image Gene #24: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'6p loss mutation analysis' versus 'Time to Death'

P value = 0.000146 (logrank test), Q value = 0.04

Table S8. Gene #30: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
6P LOSS MUTATED	5	2	3.0 - 13.4 (6.4)
6P LOSS WILD-TYPE	172	48	0.0 - 211.2 (15.2)

Figure S8. Get High-res Image Gene #30: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'Time to Death'

P value = 9.19e-11 (logrank test), Q value = 2.6e-08

Table S9. Gene #34: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
10P LOSS MUTATED	26	17	0.1 - 134.3 (8.6)
10P LOSS WILD-TYPE	151	33	0.0 - 211.2 (15.8)

Figure S9. Get High-res Image Gene #34: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'AGE'

P value = 1.95e-06 (t-test), Q value = 0.00054

Table S10. Gene #34: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	178	43.1 (13.4)
10P LOSS MUTATED	26	54.8 (11.1)
10P LOSS WILD-TYPE	152	41.2 (12.8)

Figure S10. Get High-res Image Gene #34: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'10q loss mutation analysis' versus 'Time to Death'

P value = 2.08e-10 (logrank test), Q value = 5.8e-08

Table S11. Gene #35: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
10Q LOSS MUTATED	27	17	0.1 - 134.3 (8.8)
10Q LOSS WILD-TYPE	150	33	0.0 - 211.2 (16.0)

Figure S11. Get High-res Image Gene #35: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10q loss mutation analysis' versus 'AGE'

P value = 1.03e-06 (t-test), Q value = 0.00029

Table S12. Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	178	43.1 (13.4)
10Q LOSS MUTATED	27	54.6 (10.9)
10Q LOSS WILD-TYPE	151	41.1 (12.8)

Figure S12. Get High-res Image Gene #35: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'19q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.56e-11 (Fisher's exact test), Q value = 7.2e-09

Table S13. Gene #46: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	55	47	75
19Q LOSS MUTATED	8	7	49
19Q LOSS WILD-TYPE	47	40	26

Figure S13. Get High-res Image Gene #46: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'22q loss mutation analysis' versus 'Time to Death'

P value = 1.61e-05 (logrank test), Q value = 0.0044

Table S14. Gene #48: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	177	50	0.0 - 211.2 (14.7)
22Q LOSS MUTATED	13	7	0.1 - 46.6 (13.4)
22Q LOSS WILD-TYPE	164	43	0.0 - 211.2 (14.8)

Figure S14. Get High-res Image Gene #48: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = LGG-TP.clin.merged.picked.txt
Number of patients = 178
Number of significantly arm-level cnvs = 49
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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