(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 471 genes and 8 clinical features across 481 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.
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61 genes correlated to 'Time to Death'.
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HSA-MIR-130B , HSA-MIR-223 , HSA-MIR-21 , HSA-MIR-34C , HSA-MIR-138-1 , ...
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2 genes correlated to 'AGE'.
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HSA-MIR-148A , HSA-MIR-590
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11 genes correlated to 'GENDER'.
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HSA-MIR-100 , HSA-MIR-455 , HSA-MIR-708 , HSA-MIR-599 , HSA-MIR-30A , ...
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34 genes correlated to 'PATHOLOGY.T'.
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HSA-MIR-139 , HSA-MIR-625 , HSA-MIR-21 , HSA-MIR-486 , HSA-MIR-130B , ...
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17 genes correlated to 'PATHOLOGICSPREAD(M)'.
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HSA-MIR-193A , HSA-MIR-625 , HSA-MIR-155 , HSA-MIR-130B , HSA-MIR-28 , ...
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41 genes correlated to 'TUMOR.STAGE'.
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HSA-MIR-139 , HSA-MIR-21 , HSA-MIR-155 , HSA-MIR-625 , HSA-MIR-144 , ...
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No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', and 'PATHOLOGY.N'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=61 | shorter survival | N=55 | longer survival | N=6 |
AGE | Spearman correlation test | N=2 | older | N=2 | younger | N=0 |
GENDER | t test | N=11 | male | N=4 | female | N=7 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=34 | higher pT | N=26 | lower pT | N=8 |
PATHOLOGY N | t test | N=0 | ||||
PATHOLOGICSPREAD(M) | t test | N=17 | m1 | N=13 | m0 | N=4 |
TUMOR STAGE | Spearman correlation test | N=41 | higher stage | N=32 | lower stage | N=9 |
Time to Death | Duration (Months) | 0.1-111 (median=35.2) |
censored | N = 323 | |
death | N = 155 | |
Significant markers | N = 61 | |
associated with shorter survival | 55 | |
associated with longer survival | 6 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-MIR-130B | 2.1 | 3.075e-14 | 1.4e-11 | 0.669 |
HSA-MIR-223 | 1.65 | 8.46e-14 | 4e-11 | 0.654 |
HSA-MIR-21 | 2.1 | 4.472e-10 | 2.1e-07 | 0.66 |
HSA-MIR-34C | 1.28 | 6.215e-10 | 2.9e-07 | 0.639 |
HSA-MIR-138-1 | 1.4 | 6.303e-09 | 2.9e-06 | 0.651 |
HSA-MIR-10B | 0.56 | 2.534e-08 | 1.2e-05 | 0.37 |
HSA-MIR-18A | 1.54 | 6.379e-08 | 3e-05 | 0.619 |
HSA-MIR-1248 | 1.39 | 6.748e-08 | 3.1e-05 | 0.614 |
HSA-MIR-101-1 | 0.55 | 9.998e-08 | 4.6e-05 | 0.395 |
HSA-MIR-365-2 | 1.62 | 1.371e-07 | 6.3e-05 | 0.621 |
AGE | Mean (SD) | 60.58 (12) |
Significant markers | N = 2 | |
pos. correlated | 2 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-148A | 0.1836 | 5.117e-05 | 0.0241 |
HSA-MIR-590 | 0.1811 | 6.484e-05 | 0.0305 |
GENDER | Labels | N |
FEMALE | 163 | |
MALE | 318 | |
Significant markers | N = 11 | |
Higher in MALE | 4 | |
Higher in FEMALE | 7 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-100 | 8.52 | 7.686e-16 | 3.62e-13 | 0.7408 |
HSA-MIR-455 | -5.21 | 3.138e-07 | 0.000147 | 0.6516 |
HSA-MIR-708 | 5.23 | 3.139e-07 | 0.000147 | 0.6531 |
HSA-MIR-599 | -5.09 | 6.767e-07 | 0.000317 | 0.6722 |
HSA-MIR-30A | -4.35 | 1.742e-05 | 0.00813 | 0.6136 |
HSA-MIR-30C-2 | -4.33 | 2.037e-05 | 0.00949 | 0.6143 |
HSA-MIR-500B | -4.3 | 2.236e-05 | 0.0104 | 0.6197 |
HSA-MIR-31 | 4.08 | 5.754e-05 | 0.0267 | 0.621 |
HSA-MIR-3934 | 4.07 | 6.518e-05 | 0.0302 | 0.6302 |
HSA-MIR-204 | -4.04 | 6.707e-05 | 0.031 | 0.6355 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 88.33 (23) |
Score | N | |
0 | 2 | |
70 | 1 | |
80 | 3 | |
90 | 13 | |
100 | 17 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 1.93 (0.97) |
N | ||
T1 | 233 | |
T2 | 62 | |
T3 | 175 | |
T4 | 11 | |
Significant markers | N = 34 | |
pos. correlated | 26 | |
neg. correlated | 8 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-139 | -0.3349 | 4.563e-14 | 2.15e-11 |
HSA-MIR-625 | 0.2826 | 2.768e-10 | 1.3e-07 |
HSA-MIR-21 | 0.2786 | 5.071e-10 | 2.38e-07 |
HSA-MIR-486 | -0.2608 | 6.415e-09 | 3e-06 |
HSA-MIR-130B | 0.2606 | 6.563e-09 | 3.06e-06 |
HSA-MIR-155 | 0.2551 | 1.398e-08 | 6.51e-06 |
HSA-MIR-144 | -0.2488 | 3.23e-08 | 1.5e-05 |
HSA-MIR-9-2 | 0.2312 | 2.959e-07 | 0.000137 |
HSA-MIR-451 | -0.2277 | 4.478e-07 | 0.000207 |
HSA-MIR-9-1 | 0.227 | 4.868e-07 | 0.000225 |
PATHOLOGY.N | Labels | N |
N0 | 222 | |
N1 | 18 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 405 | |
M1 | 76 | |
Significant markers | N = 17 | |
Higher in M1 | 13 | |
Higher in M0 | 4 |
T(pos if higher in 'M1') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-193A | 5.84 | 2.409e-08 | 1.13e-05 | 0.6498 |
HSA-MIR-625 | 5.47 | 3.19e-07 | 0.00015 | 0.6889 |
HSA-MIR-155 | 5.35 | 4.693e-07 | 0.00022 | 0.686 |
HSA-MIR-130B | 5.29 | 5.697e-07 | 0.000267 | 0.6714 |
HSA-MIR-28 | 5.17 | 1.011e-06 | 0.000472 | 0.6609 |
HSA-MIR-27A | 5.06 | 1.363e-06 | 0.000635 | 0.6356 |
HSA-MIR-144 | -5.13 | 1.365e-06 | 0.000635 | 0.6829 |
HSA-MIR-106B | 4.98 | 1.792e-06 | 0.000831 | 0.6551 |
HSA-MIR-139 | -4.73 | 7.165e-06 | 0.00332 | 0.668 |
HSA-MIR-21 | 4.66 | 8.186e-06 | 0.00378 | 0.6443 |
TUMOR.STAGE | Mean (SD) | 2.11 (1.2) |
N | ||
Stage 1 | 229 | |
Stage 2 | 50 | |
Stage 3 | 122 | |
Stage 4 | 80 | |
Significant markers | N = 41 | |
pos. correlated | 32 | |
neg. correlated | 9 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-139 | -0.3487 | 3.374e-15 | 1.59e-12 |
HSA-MIR-21 | 0.283 | 2.604e-10 | 1.22e-07 |
HSA-MIR-155 | 0.2814 | 3.341e-10 | 1.57e-07 |
HSA-MIR-625 | 0.2807 | 3.697e-10 | 1.73e-07 |
HSA-MIR-144 | -0.2756 | 7.829e-10 | 3.66e-07 |
HSA-MIR-486 | -0.275 | 8.559e-10 | 3.99e-07 |
HSA-MIR-451 | -0.2538 | 1.652e-08 | 7.68e-06 |
HSA-MIR-130B | 0.2496 | 2.872e-08 | 1.33e-05 |
HSA-MIR-9-2 | 0.2379 | 1.299e-07 | 6.01e-05 |
HSA-MIR-142 | 0.2345 | 1.977e-07 | 9.13e-05 |
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Expresson data file = KIRC-TP.miRseq_RPKM_log2.txt
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Clinical data file = KIRC-TP.clin.merged.picked.txt
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Number of patients = 481
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Number of genes = 471
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Number of clinical features = 8
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-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.