This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 19971 genes and 11 clinical features across 497 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.
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11 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.
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GAS2L3 , LIPA , ADH6 , SLC9A9 , CHRNB2 , ...
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30 genes correlated to 'YEARS_TO_BIRTH'.
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INA , FZD9 , OXT , CECR6 , EPO , ...
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30 genes correlated to 'PATHOLOGY_T_STAGE'.
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TACC2 , FGD4 , TEPP , ABCC10 , FAM13C , ...
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30 genes correlated to 'PATHOLOGY_N_STAGE'.
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C11ORF10 , FEN1 , MIR611 , KIAA0922 , EIF4A3 , ...
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30 genes correlated to 'RADIATION_THERAPY'.
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KIAA0922 , LOC595101 , DLGAP5 , RPS6KL1 , MME , ...
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30 genes correlated to 'RESIDUAL_TUMOR'.
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RIC3 , HNF1B , KIAA1751 , FRYL , ARGLU1 , ...
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30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.
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KIAA0922 , C11ORF10 , FEN1 , MIR611 , EIF4A3 , ...
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30 genes correlated to 'GLEASON_SCORE'.
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FAM13C , KIAA0922 , PLK1 , OR51A7 , C11ORF10 , ...
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30 genes correlated to 'PSA_VALUE'.
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OR2A7 , OVOL1 , C6ORF41__1 , LOC100270746__1 , COMMD4 , ...
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No genes correlated to 'HISTOLOGICAL_TYPE', and 'RACE'.
Complete statistical result table is provided in Supplement Table 1
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
DAYS_TO_DEATH_OR_LAST_FUP | Cox regression test | N=11 | shorter survival | N=10 | longer survival | N=1 |
YEARS_TO_BIRTH | Spearman correlation test | N=30 | older | N=30 | younger | N=0 |
PATHOLOGY_T_STAGE | Spearman correlation test | N=30 | higher stage | N=23 | lower stage | N=7 |
PATHOLOGY_N_STAGE | Wilcoxon test | N=30 | n1 | N=30 | n0 | N=0 |
RADIATION_THERAPY | Wilcoxon test | N=30 | yes | N=30 | no | N=0 |
HISTOLOGICAL_TYPE | Wilcoxon test | N=0 | ||||
RESIDUAL_TUMOR | Kruskal-Wallis test | N=30 | ||||
NUMBER_OF_LYMPH_NODES | Spearman correlation test | N=30 | higher number_of_lymph_nodes | N=0 | lower number_of_lymph_nodes | N=30 |
GLEASON_SCORE | Spearman correlation test | N=30 | higher score | N=12 | lower score | N=18 |
PSA_VALUE | Spearman correlation test | N=30 | higher psa_value | N=7 | lower psa_value | N=23 |
RACE | Kruskal-Wallis test | N=0 |
Table S1. Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'
DAYS_TO_DEATH_OR_LAST_FUP | Duration (Months) | 0.7-165.2 (median=28.8) |
censored | N = 486 | |
death | N = 10 | |
Significant markers | N = 11 | |
associated with shorter survival | 10 | |
associated with longer survival | 1 |
Table S2. Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
GAS2L3 | 1.6e+22 | 6.006e-06 | 0.12 | 0.795 |
LIPA | 86000001 | 1.874e-05 | 0.17 | 0.657 |
ADH6 | 0 | 3.127e-05 | 0.17 | 0.184 |
SLC9A9 | 201 | 4.168e-05 | 0.17 | 0.707 |
CHRNB2 | 40000000001 | 4.601e-05 | 0.17 | 0.747 |
IPO9 | 5.2e+15 | 5.023e-05 | 0.17 | 0.724 |
ZMYND10 | 14001 | 7.035e-05 | 0.2 | 0.607 |
RNH1 | 1.7e+16 | 0.0001055 | 0.25 | 0.624 |
IGSF9B | 4101 | 0.0001109 | 0.25 | 0.729 |
KCNG1 | 10001 | 0.000152 | 0.28 | 0.714 |
Table S3. Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'
YEARS_TO_BIRTH | Mean (SD) | 61.02 (6.8) |
Significant markers | N = 30 | |
pos. correlated | 30 | |
neg. correlated | 0 |
Table S4. Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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INA | 0.2767 | 5.415e-10 | 1.08e-05 |
FZD9 | 0.2649 | 3.016e-09 | 3.01e-05 |
OXT | 0.2557 | 1.076e-08 | 7.17e-05 |
CECR6 | 0.2415 | 7.078e-08 | 0.000257 |
EPO | 0.2409 | 7.596e-08 | 0.000257 |
SOX11 | 0.2408 | 7.723e-08 | 0.000257 |
TMEM74 | 0.2378 | 1.133e-07 | 0.000319 |
C17ORF104 | 0.2368 | 1.277e-07 | 0.000319 |
NKX2-5 | 0.235 | 1.6e-07 | 0.000344 |
RPP25 | 0.2344 | 1.723e-07 | 0.000344 |
Table S5. Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'
PATHOLOGY_T_STAGE | Mean (SD) | 2.64 (0.52) |
N | ||
T2 | 189 | |
T3 | 292 | |
T4 | 10 | |
Significant markers | N = 30 | |
pos. correlated | 23 | |
neg. correlated | 7 |
Table S6. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
TACC2 | 0.3584 | 2.527e-16 | 3.22e-12 |
FGD4 | 0.3572 | 3.22e-16 | 3.22e-12 |
TEPP | 0.3345 | 2.653e-14 | 1.77e-10 |
ABCC10 | 0.3324 | 3.959e-14 | 1.86e-10 |
FAM13C | 0.3315 | 4.647e-14 | 1.86e-10 |
KIAA0922 | -0.3301 | 6.012e-14 | 2e-10 |
INPP5K | 0.3219 | 2.665e-13 | 7.6e-10 |
KBTBD11 | 0.3164 | 7.499e-13 | 1.83e-09 |
FAM55B | 0.3155 | 8.239e-13 | 1.83e-09 |
SATB1 | 0.3104 | 2.463e-12 | 4.92e-09 |
Table S7. Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'
PATHOLOGY_N_STAGE | Labels | N |
N0 | 345 | |
N1 | 79 | |
Significant markers | N = 30 | |
Higher in N1 | 30 | |
Higher in N0 | 0 |
Table S8. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'
W(pos if higher in 'N1') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
C11ORF10 | 6508 | 4.296e-13 | 2.24e-09 | 0.7612 |
FEN1 | 6508 | 4.296e-13 | 2.24e-09 | 0.7612 |
MIR611 | 6508 | 4.296e-13 | 2.24e-09 | 0.7612 |
KIAA0922 | 6514 | 4.494e-13 | 2.24e-09 | 0.761 |
EIF4A3 | 7443 | 3.089e-10 | 1.23e-06 | 0.7269 |
GUCA1B | 7525 | 5.273e-10 | 1.76e-06 | 0.7239 |
HN1 | 7755 | 2.277e-09 | 5.18e-06 | 0.7155 |
ERP29__1 | 7759 | 2.335e-09 | 5.18e-06 | 0.7153 |
TMEM116__1 | 7759 | 2.335e-09 | 5.18e-06 | 0.7153 |
DHX9 | 7890 | 5.243e-09 | 1.05e-05 | 0.7105 |
Table S9. Basic characteristics of clinical feature: 'RADIATION_THERAPY'
RADIATION_THERAPY | Labels | N |
NO | 383 | |
YES | 57 | |
Significant markers | N = 30 | |
Higher in YES | 30 | |
Higher in NO | 0 |
Table S10. Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
KIAA0922 | 5917 | 2.406e-08 | 0.00048 | 0.729 |
LOC595101 | 6396 | 4.531e-07 | 0.00452 | 0.707 |
DLGAP5 | 6726 | 2.914e-06 | 0.0194 | 0.6919 |
RPS6KL1 | 6806 | 4.487e-06 | 0.0224 | 0.6882 |
MME | 7026 | 1.413e-05 | 0.0564 | 0.6782 |
MAPKAPK2 | 7099 | 2.041e-05 | 0.0591 | 0.6748 |
PLK1 | 7102 | 2.072e-05 | 0.0591 | 0.6747 |
SFXN5 | 7175 | 2.974e-05 | 0.0664 | 0.6713 |
SAMD1 | 7184 | 3.108e-05 | 0.0664 | 0.6709 |
SNORD17__1 | 7237 | 4.021e-05 | 0.0664 | 0.6685 |
Table S11. Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'
HISTOLOGICAL_TYPE | Labels | N |
PROSTATE ADENOCARCINOMA OTHER SUBTYPE | 15 | |
PROSTATE ADENOCARCINOMA ACINAR TYPE | 482 | |
Significant markers | N = 0 |
Table S12. Basic characteristics of clinical feature: 'RESIDUAL_TUMOR'
RESIDUAL_TUMOR | Labels | N |
R0 | 315 | |
R1 | 146 | |
R2 | 5 | |
RX | 15 | |
Significant markers | N = 30 |
Table S13. Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'
kruskal_wallis_P | Q | |
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RIC3 | 2.077e-07 | 0.00415 |
HNF1B | 8.108e-07 | 0.00707 |
KIAA1751 | 1.823e-06 | 0.00707 |
FRYL | 1.852e-06 | 0.00707 |
ARGLU1 | 2.078e-06 | 0.00707 |
CYP7B1 | 2.247e-06 | 0.00707 |
MAST2 | 2.81e-06 | 0.00707 |
LOC93622 | 3.121e-06 | 0.00707 |
PGS1 | 3.335e-06 | 0.00707 |
CLDN9 | 3.677e-06 | 0.00707 |
Table S14. Basic characteristics of clinical feature: 'NUMBER_OF_LYMPH_NODES'
NUMBER_OF_LYMPH_NODES | Mean (SD) | 0.44 (1.4) |
Significant markers | N = 30 | |
pos. correlated | 0 | |
neg. correlated | 30 |
Table S15. Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
KIAA0922 | -0.3735 | 6.94e-15 | 8.95e-11 |
C11ORF10 | -0.3681 | 1.793e-14 | 8.95e-11 |
FEN1 | -0.3681 | 1.793e-14 | 8.95e-11 |
MIR611 | -0.3681 | 1.793e-14 | 8.95e-11 |
EIF4A3 | -0.332 | 6.678e-12 | 2.67e-08 |
GUCA1B | -0.319 | 4.663e-11 | 1.55e-07 |
HN1 | -0.3103 | 1.634e-10 | 4.66e-07 |
CORO7 | -0.3046 | 3.669e-10 | 8.5e-07 |
LOC93622 | -0.3026 | 4.842e-10 | 8.5e-07 |
SIN3B | -0.3024 | 4.953e-10 | 8.5e-07 |
Table S16. Basic characteristics of clinical feature: 'GLEASON_SCORE'
GLEASON_SCORE | Mean (SD) | 7.61 (1) |
Score | N | |
6 | 45 | |
7 | 248 | |
8 | 64 | |
9 | 136 | |
10 | 4 | |
Significant markers | N = 30 | |
pos. correlated | 12 | |
neg. correlated | 18 |
Table S17. Get Full Table List of top 10 genes significantly correlated to 'GLEASON_SCORE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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FAM13C | 0.4307 | 7.347e-24 | 1.47e-19 |
KIAA0922 | -0.4203 | 1.092e-22 | 1.09e-18 |
PLK1 | -0.4096 | 1.568e-21 | 1.04e-17 |
OR51A7 | -0.3922 | 1.003e-19 | 5.01e-16 |
C11ORF10 | -0.3864 | 3.818e-19 | 1.09e-15 |
FEN1 | -0.3864 | 3.818e-19 | 1.09e-15 |
MIR611 | -0.3864 | 3.818e-19 | 1.09e-15 |
FGD4 | 0.3857 | 4.477e-19 | 1.12e-15 |
PTPRN2 | 0.3829 | 8.352e-19 | 1.85e-15 |
CYP7B1 | 0.3808 | 1.354e-18 | 2.7e-15 |
Table S18. Basic characteristics of clinical feature: 'PSA_VALUE'
PSA_VALUE | Mean (SD) | 1.79 (16) |
Significant markers | N = 30 | |
pos. correlated | 7 | |
neg. correlated | 23 |
Table S19. Get Full Table List of top 10 genes significantly correlated to 'PSA_VALUE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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OR2A7 | -0.2279 | 1.361e-06 | 0.0118 |
OVOL1 | -0.2239 | 2.1e-06 | 0.0118 |
C6ORF41__1 | 0.2184 | 3.748e-06 | 0.0118 |
LOC100270746__1 | 0.2184 | 3.748e-06 | 0.0118 |
COMMD4 | 0.2164 | 4.623e-06 | 0.0118 |
BAIAP2__1 | 0.2147 | 5.518e-06 | 0.0118 |
SNORD17__1 | -0.2139 | 5.982e-06 | 0.0118 |
SNX5__1 | -0.2139 | 5.982e-06 | 0.0118 |
ATF5__1 | -0.2131 | 6.482e-06 | 0.0118 |
IL4I1__1 | -0.2131 | 6.482e-06 | 0.0118 |
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Expresson data file = PRAD-TP.meth.by_min_clin_corr.data.txt
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Clinical data file = PRAD-TP.merged_data.txt
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Number of patients = 497
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Number of genes = 19971
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Number of clinical features = 11
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Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.
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There are also useful links about clinical features.
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Survival time data
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Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.
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if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'
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if 'vital_status'==0(alive),
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if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'
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if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.
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if 'vital_status'==NA,excludes this case in survival analysis and report the case.
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cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .
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This analysis excluded clinical variables that has only NA values.
For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels
For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R
For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.
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.