(primary solid tumor cohort)
This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 564 genes and 5 clinical features across 442 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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4 genes correlated to 'Time to Death'.
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HSA-LET-7G , HSA-LET-7B , HSA-MIR-628 , HSA-MIR-30E
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54 genes correlated to 'AGE'.
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HSA-MIR-424 , HSA-MIR-1247 , HSA-MIR-337 , HSA-MIR-199A-1 , HSA-MIR-214 , ...
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88 genes correlated to 'HISTOLOGICAL.TYPE'.
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HSA-MIR-9-1 , HSA-MIR-9-2 , HSA-MIR-34A , HSA-MIR-934 , HSA-MIR-375 , ...
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6 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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HSA-MIR-128-2 , HSA-MIR-3613 , HSA-MIR-128-1 , HSA-MIR-628 , HSA-MIR-181D , ...
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No genes correlated to 'COMPLETENESS.OF.RESECTION'
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=4 | shorter survival | N=0 | longer survival | N=4 |
AGE | Spearman correlation test | N=54 | older | N=7 | younger | N=47 |
HISTOLOGICAL TYPE | ANOVA test | N=88 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=6 | yes | N=4 | no | N=2 |
COMPLETENESS OF RESECTION | ANOVA test | N=0 |
Time to Death | Duration (Months) | 0-187.1 (median=15.8) |
censored | N = 398 | |
death | N = 39 | |
Significant markers | N = 4 | |
associated with shorter survival | 0 | |
associated with longer survival | 4 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-LET-7G | 0.45 | 1.31e-05 | 0.0074 | 0.292 |
HSA-LET-7B | 0.53 | 2.625e-05 | 0.015 | 0.255 |
HSA-MIR-628 | 0.64 | 4.273e-05 | 0.024 | 0.293 |
HSA-MIR-30E | 0.34 | 6.315e-05 | 0.035 | 0.309 |
AGE | Mean (SD) | 63.48 (11) |
Significant markers | N = 54 | |
pos. correlated | 7 | |
neg. correlated | 47 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-424 | -0.3188 | 7.082e-12 | 3.99e-09 |
HSA-MIR-1247 | -0.2843 | 1.374e-09 | 7.74e-07 |
HSA-MIR-337 | -0.2722 | 6.254e-09 | 3.51e-06 |
HSA-MIR-199A-1 | -0.2647 | 1.657e-08 | 9.3e-06 |
HSA-MIR-214 | -0.2622 | 2.368e-08 | 1.33e-05 |
HSA-MIR-199A-2 | -0.2617 | 2.435e-08 | 1.36e-05 |
HSA-MIR-409 | -0.2616 | 2.484e-08 | 1.39e-05 |
HSA-MIR-34A | -0.2605 | 2.842e-08 | 1.58e-05 |
HSA-MIR-493 | -0.2591 | 3.922e-08 | 2.18e-05 |
HSA-MIR-199B | -0.2552 | 5.498e-08 | 3.05e-05 |
HISTOLOGICAL.TYPE | Labels | N |
ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 349 | |
MIXED SEROUS AND ENDOMETRIOID | 18 | |
SEROUS ENDOMETRIAL ADENOCARCINOMA | 75 | |
Significant markers | N = 88 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-9-1 | 3.585e-26 | 2.02e-23 |
HSA-MIR-9-2 | 4.153e-26 | 2.34e-23 |
HSA-MIR-34A | 4.13e-24 | 2.32e-21 |
HSA-MIR-934 | 1.191e-21 | 6.68e-19 |
HSA-MIR-375 | 5.966e-19 | 3.34e-16 |
HSA-MIR-195 | 1.927e-18 | 1.08e-15 |
HSA-MIR-497 | 3.165e-18 | 1.77e-15 |
HSA-MIR-548V | 6.869e-17 | 3.83e-14 |
HSA-MIR-452 | 3.477e-16 | 1.93e-13 |
HSA-MIR-190B | 2.88e-15 | 1.6e-12 |
6 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 127 | |
YES | 315 | |
Significant markers | N = 6 | |
Higher in YES | 4 | |
Higher in NO | 2 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-128-2 | 5.28 | 2.37e-07 | 0.000134 | 0.6446 |
HSA-MIR-3613 | -5.22 | 3.512e-07 | 0.000198 | 0.6572 |
HSA-MIR-128-1 | 5.03 | 8.438e-07 | 0.000474 | 0.6431 |
HSA-MIR-628 | -4.51 | 9.551e-06 | 0.00536 | 0.6223 |
HSA-MIR-181D | 4.21 | 3.455e-05 | 0.0193 | 0.6243 |
HSA-MIR-660 | 4.07 | 6.251e-05 | 0.0349 | 0.6145 |
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Expresson data file = UCEC-TP.miRseq_RPKM_log2.txt
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Clinical data file = UCEC-TP.clin.merged.picked.txt
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Number of patients = 442
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Number of genes = 564
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Number of clinical features = 5
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 multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R
For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.