This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.
Testing the association between mutation status of 26 genes and 12 clinical features across 282 patients, 2 significant findings detected with Q value < 0.25.
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PBRM1 mutation correlated to 'Time to Death'.
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CALCR mutation correlated to 'Time to Death'.
Table 1. Get Full Table Overview of the association between mutation status of 26 genes and 12 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.
Clinical Features |
Time to Death |
YEARS TO BIRTH |
PATHOLOGIC STAGE |
PATHOLOGY T STAGE |
PATHOLOGY N STAGE |
PATHOLOGY M STAGE |
GENDER |
KARNOFSKY PERFORMANCE SCORE |
NUMBER PACK YEARS SMOKED |
YEAR OF TOBACCO SMOKING ONSET |
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 | Wilcoxon-test | Wilcoxon-test | Wilcoxon-test | Fisher's exact test | Fisher's exact test | |
PBRM1 | 11 (4%) | 271 |
0.000244 (0.0381) |
0.0077 (0.382) |
0.201 (1.00) |
0.113 (1.00) |
0.657 (1.00) |
1 (1.00) |
0.299 (1.00) |
0.512 (1.00) |
0.797 (1.00) |
1 (1.00) |
||
CALCR | 3 (1%) | 279 |
4.15e-06 (0.0013) |
0.166 (1.00) |
0.119 (1.00) |
0.15 (1.00) |
1 (1.00) |
0.0874 (1.00) |
1 (1.00) |
1 (1.00) |
0.129 (1.00) |
|||
SETD2 | 16 (6%) | 266 |
0.0129 (0.382) |
0.0793 (1.00) |
0.00252 (0.262) |
0.00431 (0.269) |
0.431 (1.00) |
0.144 (1.00) |
0.57 (1.00) |
0.499 (1.00) |
0.834 (1.00) |
0.412 (1.00) |
1 (1.00) |
|
NF2 | 10 (4%) | 272 |
0.244 (1.00) |
0.398 (1.00) |
0.00384 (0.269) |
0.00917 (0.382) |
0.0355 (0.651) |
0.31 (1.00) |
0.467 (1.00) |
0.977 (1.00) |
0.454 (1.00) |
0.882 (1.00) |
0.565 (1.00) |
1 (1.00) |
ZNF814 | 9 (3%) | 273 |
0.49 (1.00) |
0.339 (1.00) |
0.739 (1.00) |
1 (1.00) |
1 (1.00) |
0.173 (1.00) |
1 (1.00) |
1 (1.00) |
||||
MET | 21 (7%) | 261 |
0.898 (1.00) |
0.724 (1.00) |
0.971 (1.00) |
1 (1.00) |
0.411 (1.00) |
1 (1.00) |
1 (1.00) |
0.122 (1.00) |
0.339 (1.00) |
0.229 (1.00) |
0.634 (1.00) |
0.553 (1.00) |
NEFH | 6 (2%) | 276 |
0.317 (1.00) |
0.93 (1.00) |
0.488 (1.00) |
0.531 (1.00) |
1 (1.00) |
0.196 (1.00) |
1 (1.00) |
1 (1.00) |
||||
KRAS | 5 (2%) | 277 |
0.476 (1.00) |
0.772 (1.00) |
0.809 (1.00) |
0.629 (1.00) |
1 (1.00) |
0.0197 (0.448) |
0.0274 (0.535) |
1 (1.00) |
||||
CUL3 | 10 (4%) | 272 |
0.621 (1.00) |
0.647 (1.00) |
0.176 (1.00) |
1 (1.00) |
1 (1.00) |
0.242 (1.00) |
1 (1.00) |
0.0135 (0.382) |
0.256 (1.00) |
1 (1.00) |
1 (1.00) |
|
PCF11 | 11 (4%) | 271 |
0.985 (1.00) |
0.332 (1.00) |
1 (1.00) |
0.698 (1.00) |
1 (1.00) |
1 (1.00) |
0.621 (1.00) |
0.619 (1.00) |
0.342 (1.00) |
|||
BCLAF1 | 6 (2%) | 276 |
0.842 (1.00) |
0.562 (1.00) |
0.137 (1.00) |
0.0979 (1.00) |
0.262 (1.00) |
0.242 (1.00) |
1 (1.00) |
0.451 (1.00) |
1 (1.00) |
|||
PAM | 3 (1%) | 279 |
0.423 (1.00) |
0.562 (1.00) |
0.257 (1.00) |
0.694 (1.00) |
1 (1.00) |
0.566 (1.00) |
0.481 (1.00) |
1 (1.00) |
||||
SMARCB1 | 6 (2%) | 276 |
0.26 (1.00) |
0.295 (1.00) |
0.0408 (0.67) |
0.0459 (0.717) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
|||
KDM6A | 10 (4%) | 272 |
0.711 (1.00) |
0.0122 (0.382) |
0.74 (1.00) |
1 (1.00) |
0.546 (1.00) |
1 (1.00) |
1 (1.00) |
0.698 (1.00) |
0.181 (1.00) |
0.181 (1.00) |
1 (1.00) |
|
AR | 13 (5%) | 269 |
0.969 (1.00) |
0.43 (1.00) |
0.438 (1.00) |
0.426 (1.00) |
1 (1.00) |
1 (1.00) |
0.346 (1.00) |
0.397 (1.00) |
0.944 (1.00) |
0.977 (1.00) |
0.54 (1.00) |
1 (1.00) |
TP53 | 7 (2%) | 275 |
0.0119 (0.382) |
0.134 (1.00) |
0.0215 (0.448) |
0.0619 (0.877) |
1 (1.00) |
0.0595 (0.877) |
0.679 (1.00) |
0.479 (1.00) |
1 (1.00) |
|||
KRTAP4-5 | 5 (2%) | 277 |
0.325 (1.00) |
0.453 (1.00) |
0.379 (1.00) |
0.0207 (0.448) |
1 (1.00) |
0.328 (1.00) |
0.209 (1.00) |
1 (1.00) |
||||
BRAF | 4 (1%) | 278 |
0.296 (1.00) |
0.983 (1.00) |
0.706 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.626 (1.00) |
1 (1.00) |
||||
KIAA0922 | 5 (2%) | 277 |
0.841 (1.00) |
0.253 (1.00) |
0.809 (1.00) |
0.633 (1.00) |
1 (1.00) |
0.328 (1.00) |
0.627 (1.00) |
1 (1.00) |
||||
KRT2 | 5 (2%) | 277 |
0.362 (1.00) |
0.0903 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.592 (1.00) |
0.299 (1.00) |
0.148 (1.00) |
1 (1.00) |
||
ALMS1 | 8 (3%) | 274 |
0.618 (1.00) |
0.37 (1.00) |
0.738 (1.00) |
1 (1.00) |
1 (1.00) |
0.113 (1.00) |
0.231 (1.00) |
0.277 (1.00) |
||||
GXYLT1 | 4 (1%) | 278 |
0.574 (1.00) |
0.258 (1.00) |
0.769 (1.00) |
0.739 (1.00) |
1 (1.00) |
0.626 (1.00) |
1 (1.00) |
|||||
ATP1B1 | 7 (2%) | 275 |
0.989 (1.00) |
0.583 (1.00) |
0.69 (1.00) |
0.584 (1.00) |
1 (1.00) |
0.0873 (1.00) |
0.354 (1.00) |
0.242 (1.00) |
||||
PTEN | 7 (2%) | 275 |
0.271 (1.00) |
0.04 (0.67) |
0.509 (1.00) |
0.47 (1.00) |
0.546 (1.00) |
1 (1.00) |
0.0168 (0.436) |
0.481 (1.00) |
1 (1.00) |
|||
SAV1 | 6 (2%) | 276 |
0.869 (1.00) |
0.682 (1.00) |
0.325 (1.00) |
1 (1.00) |
1 (1.00) |
0.348 (1.00) |
0.228 (1.00) |
0.109 (1.00) |
1 (1.00) |
|||
IGSF3 | 4 (1%) | 278 |
0.455 (1.00) |
0.245 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.577 (1.00) |
0.311 (1.00) |
1 (1.00) |
P value = 0.000244 (logrank test), Q value = 0.038
Table S1. Gene #22: 'PBRM1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 279 | 41 | 0.1 - 194.8 (25.2) |
PBRM1 MUTATED | 11 | 4 | 0.1 - 67.2 (12.3) |
PBRM1 WILD-TYPE | 268 | 37 | 0.1 - 194.8 (25.5) |
Figure S1. Get High-res Image Gene #22: 'PBRM1 MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'
![](D22V1.png)
P value = 4.15e-06 (logrank test), Q value = 0.0013
Table S2. Gene #25: 'CALCR MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 279 | 41 | 0.1 - 194.8 (25.2) |
CALCR MUTATED | 3 | 2 | 10.8 - 16.0 (12.9) |
CALCR WILD-TYPE | 276 | 39 | 0.1 - 194.8 (25.3) |
Figure S2. Get High-res Image Gene #25: 'CALCR MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'
![](D25V1.png)
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Mutation data file = sample_sig_gene_table.txt from Mutsig_2CV pipeline
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Processed Mutation data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/KIRP-TP/22574643/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/KIRP-TP/22507257/KIRP-TP.merged_data.txt
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Number of patients = 282
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Number of significantly mutated genes = 26
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Number of selected clinical features = 12
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Exclude genes that fewer than K tumors have mutations, K = 3
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
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
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.
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.