Brain Lower Grade Glioma: Correlation between gene mutation status 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 significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 33 genes and 7 clinical features across 168 patients, 9 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'.

- CIC mutation correlated to 'HISTOLOGICAL.TYPE'.

- FUBP1 mutation correlated to 'HISTOLOGICAL.TYPE'.

- NOTCH1 mutation correlated to 'HISTOLOGICAL.TYPE'.

- EGFR mutation correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 33 genes and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 9 significant findings detected.

|  | Clinical Features | Time to Death | AGE | GENDER | KARNOFSKY PERFORMANCE SCORE | HISTOLOGICAL TYPE | HISTOLOGICCLASSIFICATION | RADIATIONS RADIATION REGIMENINDICATION
| nMutated (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test
TP53 | 88 (52%) | 80 | 0.101 (1.00) | 6.07e-06 (0.00129) | 0.276 (1.00) | 0.592 (1.00) | 3.08e-05 (0.00651) | 1 (1.00) | 0.000344 (0.0721)
IDH1 | 131 (78%) | 37 | 2.4e-05 (0.00509) | 0.113 (1.00) | 0.0246 (1.00) | 0.892 (1.00) | 0.0133 (1.00) | 0.00487 (0.988) | 1 (1.00)
ATRX | 73 (43%) | 95 | 0.124 (1.00) | 0.000623 (0.129) | 0.53 (1.00) | 0.69 (1.00) | 0.00168 (0.345) | 0.349 (1.00) | 0.019 (1.00)
CIC | 35 (21%) | 133 | 0.0537 (1.00) | 0.437 (1.00) | 0.706 (1.00) | 0.535 (1.00) | 1.43e-09 (3.07e-07) | 0.703 (1.00) | 0.087 (1.00)
FUBP1 | 19 (11%) | 149 | 0.775 (1.00) | 0.00573 (1.00) | 0.806 (1.00) | 0.694 (1.00) | 0.000607 (0.126) | 0.625 (1.00) | 0.334 (1.00)
NOTCH1 | 16 (10%) | 152 | 0.859 (1.00) | 0.0196 (1.00) | 0.115 (1.00) | 0.111 (1.00) | 0.000574 (0.12) | 0.116 (1.00) | 0.44 (1.00)
EGFR | 8 (5%) | 160 | 0.0261 (1.00) | 0.00243 (0.495) | 0.29 (1.00) | 6.32e-11 (1.36e-08) | 0.0689 (1.00) | 0.00869 (1.00) | 1 (1.00)
IDH2 | 6 (4%) | 162 | 0.684 (1.00) | 0.13 (1.00) | 0.701 (1.00) |  | 0.175 (1.00) | 0.41 (1.00) | 1 (1.00)
PIK3CA | 15 (9%) | 153 | 0.915 (1.00) | 0.558 (1.00) | 1 (1.00) | 0.36 (1.00) | 0.337 (1.00) | 1 (1.00) | 0.292 (1.00)
PIK3R1 | 12 (7%) | 156 | 0.239 (1.00) | 0.0323 (1.00) | 0.559 (1.00) | 0.696 (1.00) | 0.745 (1.00) | 1 (1.00) | 0.773 (1.00)
ZNF844 | 4 (2%) | 164 | 0.35 (1.00) | 0.997 (1.00) | 1 (1.00) |  | 0.693 (1.00) | 0.628 (1.00) | 1 (1.00)
IL32 | 4 (2%) | 164 | 0.015 (1.00) | 0.254 (1.00) | 1 (1.00) | 0.132 (1.00) | 1 (1.00) | 0.628 (1.00) | 0.0445 (1.00)
PTEN | 7 (4%) | 161 | 0.194 (1.00) | 0.365 (1.00) | 0.463 (1.00) |  | 0.0355 (1.00) | 0.131 (1.00) | 0.452 (1.00)
TIMD4 | 5 (3%) | 163 | 0.1 (1.00) | 0.173 (1.00) | 0.652 (1.00) | 0.132 (1.00) | 1 (1.00) | 1 (1.00) | 0.184 (1.00)
CREBZF | 4 (2%) | 164 | 0.722 (1.00) | 0.22 (1.00) | 0.315 (1.00) | 0.297 (1.00) | 0.482 (1.00) | 0.128 (1.00) | 1 (1.00)
ZNF57 | 6 (4%) | 162 | 0.247 (1.00) | 0.756 (1.00) | 0.404 (1.00) |  | 0.151 (1.00) | 0.692 (1.00) | 1 (1.00)
ARID1A | 11 (7%) | 157 | 0.058 (1.00) | 0.794 (1.00) | 0.118 (1.00) | 0.353 (1.00) | 0.622 (1.00) | 0.756 (1.00) | 0.547 (1.00)
NF1 | 11 (7%) | 157 | 0.0464 (1.00) | 0.725 (1.00) | 1 (1.00) | 0.776 (1.00) | 0.0514 (1.00) | 0.0238 (1.00) | 0.0641 (1.00)
TCF12 | 6 (4%) | 162 | 0.972 (1.00) | 0.554 (1.00) | 0.085 (1.00) | 0.671 (1.00) | 1 (1.00) | 0.692 (1.00) | 0.418 (1.00)
NOX4 | 5 (3%) | 163 | 0.483 (1.00) | 0.493 (1.00) | 1 (1.00) |  | 0.735 (1.00) | 0.381 (1.00) | 1 (1.00)
ZBTB20 | 7 (4%) | 161 | 0.163 (1.00) | 0.64 (1.00) | 0.7 (1.00) |  | 0.488 (1.00) | 0.245 (1.00) | 0.0503 (1.00)
MUC7 | 4 (2%) | 164 | 0.147 (1.00) | 0.46 (1.00) | 1 (1.00) |  | 0.816 (1.00) | 0.628 (1.00) | 1 (1.00)
ZNF845 | 6 (4%) | 162 | 0.347 (1.00) | 0.796 (1.00) | 1 (1.00) |  | 0.885 (1.00) | 0.692 (1.00) | 0.218 (1.00)
ANKRD30A | 7 (4%) | 161 | 0.274 (1.00) | 0.0454 (1.00) | 0.241 (1.00) |  | 0.0647 (1.00) | 0.702 (1.00) | 1 (1.00)
SPDYE5 | 3 (2%) | 165 | 0.00205 (0.419) | 0.226 (1.00) | 0.577 (1.00) | 0.671 (1.00) | 0.362 (1.00) | 1 (1.00) | 0.098 (1.00)
SCAF1 | 4 (2%) | 164 | 0.134 (1.00) | 0.477 (1.00) | 0.0321 (1.00) |  | 0.816 (1.00) | 0.628 (1.00) | 0.624 (1.00)
PRDM9 | 5 (3%) | 163 | 0.259 (1.00) | 0.0461 (1.00) | 0.652 (1.00) |  | 0.389 (1.00) | 1 (1.00) | 0.374 (1.00)
PRAMEF11 | 5 (3%) | 163 | 0.129 (1.00) | 0.981 (1.00) | 1 (1.00) |  | 1 (1.00) | 0.381 (1.00) | 1 (1.00)
ZCCHC12 | 3 (2%) | 165 | 0.539 (1.00) | 0.758 (1.00) | 0.577 (1.00) |  | 0.26 (1.00) | 1 (1.00) | 1 (1.00)
ZNF91 | 5 (3%) | 163 | 0.968 (1.00) | 0.793 (1.00) | 0.652 (1.00) |  | 0.519 (1.00) | 0.658 (1.00) | 0.184 (1.00)
C3ORF35 | 3 (2%) | 165 | 0.495 (1.00) | 0.724 (1.00) | 1 (1.00) |  | 1 (1.00) | 0.253 (1.00) | 0.249 (1.00)
RPTN | 5 (3%) | 163 | 0.169 (1.00) | 0.969 (1.00) | 1 (1.00) |  | 0.735 (1.00) | 0.658 (1.00) | 1 (1.00)
DDX5 | 5 (3%) | 163 | 0.157 (1.00) | 0.965 (1.00) | 1 (1.00) | 0.398 (1.00) | 0.605 (1.00) | 0.381 (1.00) | 0.664 (1.00)

'IDH1 MUTATION STATUS' versus 'Time to Death'

P value = 2.4e-05 (logrank test), Q value = 0.0051

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

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 167 | 46 | 0.0 - 211.2 (15.1)
IDH1 MUTATED | 130 | 29 | 0.0 - 182.3 (17.4)
IDH1 WILD-TYPE | 37 | 17 | 0.1 - 211.2 (8.4)

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

'TP53 MUTATION STATUS' versus 'AGE'

P value = 6.07e-06 (t-test), Q value = 0.0013

Table S2. Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 168 | 43.0 (13.4)
TP53 MUTATED | 88 | 38.7 (12.2)
TP53 WILD-TYPE | 80 | 47.8 (13.1)

Figure S2. Get High-res Image Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'TP53 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 3.08e-05 (Fisher's exact test), Q value = 0.0065

Table S3. Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 48 | 47 | 72
TP53 MUTATED | 32 | 32 | 23
TP53 WILD-TYPE | 16 | 15 | 49

Figure S3. Get High-res Image Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

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

P value = 0.000344 (Fisher's exact test), Q value = 0.072

Table S4. Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #7: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients | NO | YES
--- | --- | ---
ALL | 90 | 78
TP53 MUTATED | 59 | 29
TP53 WILD-TYPE | 31 | 49

Figure S4. Get High-res Image Gene #3: 'TP53 MUTATION STATUS' versus Clinical Feature #7: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'ATRX MUTATION STATUS' versus 'AGE'

P value = 0.000623 (t-test), Q value = 0.13

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

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 168 | 43.0 (13.4)
ATRX MUTATED | 73 | 39.1 (12.6)
ATRX WILD-TYPE | 95 | 46.1 (13.3)

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

'CIC MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.43e-09 (Fisher's exact test), Q value = 3.1e-07

Table S6. Gene #6: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 48 | 47 | 72
CIC MUTATED | 1 | 3 | 31
CIC WILD-TYPE | 47 | 44 | 41

Figure S6. Get High-res Image Gene #6: 'CIC MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'FUBP1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000607 (Fisher's exact test), Q value = 0.13

Table S7. Gene #7: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 48 | 47 | 72
FUBP1 MUTATED | 1 | 2 | 16
FUBP1 WILD-TYPE | 47 | 45 | 56

Figure S7. Get High-res Image Gene #7: 'FUBP1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'NOTCH1 MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000574 (Fisher's exact test), Q value = 0.12

Table S8. Gene #9: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 48 | 47 | 72
NOTCH1 MUTATED | 1 | 1 | 14
NOTCH1 WILD-TYPE | 47 | 46 | 58

Figure S8. Get High-res Image Gene #9: 'NOTCH1 MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'EGFR MUTATION STATUS' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 6.32e-11 (t-test), Q value = 1.4e-08

Table S9. Gene #20: 'EGFR MUTATION STATUS' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 88 | 88.3 (10.5)
EGFR MUTATED | 4 | 80.0 (0.0)
EGFR WILD-TYPE | 84 | 88.7 (10.6)

Figure S9. Get High-res Image Gene #20: 'EGFR MUTATION STATUS' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

Methods & Data
Input

- Mutation data file = LGG-TP.mutsig.cluster.txt

- Clinical data file = LGG-TP.clin.merged.picked.txt

- Number of patients = 168

- Number of significantly mutated genes = 33

- Number of selected clinical features = 7

- 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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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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