This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 514 miRs and 15 clinical features across 483 samples, statistically thresholded by Q value < 0.05, 14 clinical features related to at least one miRs.
-
5 miRs correlated to 'Time to Death'.
-
HSA-MIR-376A-1 , HSA-MIR-181A-2 , HSA-MIR-487A , HSA-MIR-425 , HSA-MIR-30D
-
4 miRs correlated to 'AGE'.
-
HSA-MIR-625 , HSA-MIR-376A-1 , HSA-MIR-181A-2 , HSA-MIR-1229
-
38 miRs correlated to 'NEOPLASM.DISEASESTAGE'.
-
HSA-MIR-139 , HSA-MIR-210 , HSA-MIR-146B , HSA-MIR-425 , HSA-MIR-31 , ...
-
15 miRs correlated to 'PATHOLOGY.T.STAGE'.
-
HSA-MIR-139 , HSA-MIR-126 , HSA-MIR-363 , HSA-MIR-3074 , HSA-MIR-30C-2 , ...
-
65 miRs correlated to 'PATHOLOGY.N.STAGE'.
-
HSA-MIR-146B , HSA-MIR-21 , HSA-MIR-204 , HSA-MIR-7-2 , HSA-MIR-1179 , ...
-
3 miRs correlated to 'PATHOLOGY.M.STAGE'.
-
HSA-MIR-3677 , HSA-MIR-589 , HSA-MIR-655
-
2 miRs correlated to 'GENDER'.
-
HSA-MIR-651 , HSA-MIR-361
-
170 miRs correlated to 'HISTOLOGICAL.TYPE'.
-
HSA-MIR-21 , HSA-MIR-146B , HSA-MIR-7-2 , HSA-MIR-204 , HSA-MIR-375 , ...
-
11 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
-
HSA-MIR-888 , HSA-MIR-374A , HSA-MIR-660 , HSA-MIR-324 , HSA-MIR-20B , ...
-
71 miRs correlated to 'EXTRATHYROIDAL.EXTENSION'.
-
HSA-MIR-30A , HSA-MIR-363 , HSA-MIR-148B , HSA-MIR-126 , HSA-MIR-21 , ...
-
1 miR correlated to 'COMPLETENESS.OF.RESECTION'.
-
HSA-MIR-139
-
60 miRs correlated to 'NUMBER.OF.LYMPH.NODES'.
-
HSA-MIR-7-2 , HSA-MIR-1179 , HSA-MIR-21 , HSA-MIR-511-2 , HSA-MIR-382 , ...
-
1 miR correlated to 'MULTIFOCALITY'.
-
HSA-MIR-132
-
3 miRs correlated to 'TUMOR.SIZE'.
-
HSA-MIR-9-2 , HSA-MIR-9-1 , HSA-MIR-183
-
No miRs correlated to 'RADIATIONEXPOSURE'
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 miRs that are significantly associated with each clinical feature at Q value < 0.05.
Clinical feature | Statistical test | Significant miRs | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=5 | shorter survival | N=3 | longer survival | N=2 |
AGE | Spearman correlation test | N=4 | older | N=2 | younger | N=2 |
NEOPLASM DISEASESTAGE | ANOVA test | N=38 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=15 | higher stage | N=3 | lower stage | N=12 |
PATHOLOGY N STAGE | t test | N=65 | class1 | N=32 | class0 | N=33 |
PATHOLOGY M STAGE | ANOVA test | N=3 | ||||
GENDER | t test | N=2 | male | N=0 | female | N=2 |
HISTOLOGICAL TYPE | ANOVA test | N=170 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=11 | yes | N=8 | no | N=3 |
RADIATIONEXPOSURE | t test | N=0 | ||||
EXTRATHYROIDAL EXTENSION | ANOVA test | N=71 | ||||
COMPLETENESS OF RESECTION | ANOVA test | N=1 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=60 | higher number.of.lymph.nodes | N=36 | lower number.of.lymph.nodes | N=24 |
MULTIFOCALITY | t test | N=1 | unifocal | N=0 | multifocal | N=1 |
TUMOR SIZE | Spearman correlation test | N=3 | higher tumor.size | N=1 | lower tumor.size | N=2 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0-158.8 (median=14.9) |
censored | N = 464 | |
death | N = 14 | |
Significant markers | N = 5 | |
associated with shorter survival | 3 | |
associated with longer survival | 2 |
Table S2. Get Full Table List of 5 miRs significantly associated with 'Time to Death' by Cox regression test
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-MIR-376A-1 | 4.2 | 2.175e-05 | 0.011 | 0.885 |
HSA-MIR-181A-2 | 0.33 | 3.884e-05 | 0.02 | 0.176 |
HSA-MIR-487A | 2.6 | 4.319e-05 | 0.022 | 0.843 |
HSA-MIR-425 | 5.6 | 7.624e-05 | 0.039 | 0.79 |
HSA-MIR-30D | 0.14 | 8.088e-05 | 0.041 | 0.16 |
Figure S1. Get High-res Image As an example, this figure shows the association of HSA-MIR-376A-1 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.17e-05 with univariate Cox regression analysis using continuous log-2 expression values.
![](V1ex.png)
Table S3. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 47.22 (16) |
Significant markers | N = 4 | |
pos. correlated | 2 | |
neg. correlated | 2 |
Table S4. Get Full Table List of 4 miRs significantly correlated to 'AGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-625 | -0.197 | 1.296e-05 | 0.00666 |
HSA-MIR-376A-1 | 0.2586 | 1.408e-05 | 0.00722 |
HSA-MIR-181A-2 | -0.1925 | 2.057e-05 | 0.0105 |
HSA-MIR-1229 | 0.1996 | 6.359e-05 | 0.0325 |
Figure S2. Get High-res Image As an example, this figure shows the association of HSA-MIR-625 to 'AGE'. P value = 1.3e-05 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V2ex.png)
Table S5. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 273 | |
STAGE II | 51 | |
STAGE III | 106 | |
STAGE IV | 2 | |
STAGE IVA | 43 | |
STAGE IVC | 6 | |
Significant markers | N = 38 |
Table S6. Get Full Table List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'
ANOVA_P | Q | |
---|---|---|
HSA-MIR-139 | 7.912e-13 | 4.07e-10 |
HSA-MIR-210 | 1.394e-10 | 7.15e-08 |
HSA-MIR-146B | 1.887e-07 | 9.66e-05 |
HSA-MIR-425 | 2.491e-07 | 0.000127 |
HSA-MIR-31 | 4.179e-07 | 0.000213 |
HSA-MIR-126 | 5.388e-07 | 0.000274 |
HSA-MIR-154 | 7.694e-07 | 0.000391 |
HSA-MIR-376C | 1.078e-06 | 0.000547 |
HSA-MIR-369 | 1.739e-06 | 0.00088 |
HSA-MIR-655 | 1.906e-06 | 0.000963 |
Figure S3. Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'NEOPLASM.DISEASESTAGE'. P value = 7.91e-13 with ANOVA analysis.
![](V3ex.png)
Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'
PATHOLOGY.T.STAGE | Mean (SD) | 2.13 (0.88) |
N | ||
1 | 140 | |
2 | 161 | |
3 | 159 | |
4 | 21 | |
Significant markers | N = 15 | |
pos. correlated | 3 | |
neg. correlated | 12 |
Table S8. Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-139 | -0.2822 | 2.962e-10 | 1.52e-07 |
HSA-MIR-126 | -0.2693 | 1.952e-09 | 1e-06 |
HSA-MIR-363 | -0.2412 | 8.753e-08 | 4.48e-05 |
HSA-MIR-3074 | -0.2045 | 6.133e-06 | 0.00313 |
HSA-MIR-30C-2 | -0.2036 | 6.754e-06 | 0.00344 |
HSA-MIR-92B | 0.2008 | 9.116e-06 | 0.00464 |
HSA-MIR-145 | -0.1992 | 1.076e-05 | 0.00547 |
HSA-MIR-7-2 | -0.2008 | 1.179e-05 | 0.00598 |
HSA-MIR-20B | -0.1973 | 1.337e-05 | 0.00677 |
HSA-MIR-433 | 0.2412 | 2.274e-05 | 0.0115 |
Figure S4. Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'PATHOLOGY.T.STAGE'. P value = 2.96e-10 with Spearman correlation analysis.
![](V4ex.png)
Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'
PATHOLOGY.N.STAGE | Labels | N |
class0 | 220 | |
class1 | 216 | |
Significant markers | N = 65 | |
Higher in class1 | 32 | |
Higher in class0 | 33 |
Table S10. Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.N.STAGE'
T(pos if higher in 'class1') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-146B | 7.72 | 1.25e-13 | 6.42e-11 | 0.6736 |
HSA-MIR-21 | 7.52 | 3.688e-13 | 1.89e-10 | 0.6811 |
HSA-MIR-204 | -7.02 | 9.13e-12 | 4.67e-09 | 0.6756 |
HSA-MIR-7-2 | -6.98 | 1.174e-11 | 6e-09 | 0.6834 |
HSA-MIR-1179 | -6.85 | 2.786e-11 | 1.42e-08 | 0.6825 |
HSA-MIR-222 | 6.74 | 6.751e-11 | 3.44e-08 | 0.6556 |
HSA-MIR-511-2 | 6.35 | 5.319e-10 | 2.7e-07 | 0.6681 |
HSA-MIR-221 | 6.23 | 1.371e-09 | 6.95e-07 | 0.6343 |
HSA-MIR-375 | 6.08 | 2.993e-09 | 1.51e-06 | 0.637 |
HSA-MIR-3074 | -6.03 | 3.669e-09 | 1.85e-06 | 0.6615 |
Figure S5. Get High-res Image As an example, this figure shows the association of HSA-MIR-146B to 'PATHOLOGY.N.STAGE'. P value = 1.25e-13 with T-test analysis.
![](V5ex.png)
Table S11. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'
PATHOLOGY.M.STAGE | Labels | N |
M0 | 264 | |
M1 | 9 | |
MX | 209 | |
Significant markers | N = 3 |
Table S12. Get Full Table List of 3 miRs differentially expressed by 'PATHOLOGY.M.STAGE'
ANOVA_P | Q | |
---|---|---|
HSA-MIR-3677 | 4.996e-06 | 0.00257 |
HSA-MIR-589 | 3.046e-05 | 0.0156 |
HSA-MIR-655 | 6.792e-05 | 0.0348 |
Figure S6. Get High-res Image As an example, this figure shows the association of HSA-MIR-3677 to 'PATHOLOGY.M.STAGE'. P value = 5e-06 with ANOVA analysis.
![](V6ex.png)
Table S13. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 354 | |
MALE | 129 | |
Significant markers | N = 2 | |
Higher in MALE | 0 | |
Higher in FEMALE | 2 |
Table S14. Get Full Table List of 2 miRs differentially expressed by 'GENDER'
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-651 | -5.2 | 4.795e-07 | 0.000246 | 0.6551 |
HSA-MIR-361 | -4.42 | 1.406e-05 | 0.00721 | 0.617 |
Figure S7. Get High-res Image As an example, this figure shows the association of HSA-MIR-651 to 'GENDER'. P value = 4.79e-07 with T-test analysis.
![](V7ex.png)
Table S15. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
HISTOLOGICAL.TYPE | Labels | N |
OTHER SPECIFY | 9 | |
THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | 340 | |
THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | 99 | |
THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) | 35 | |
Significant markers | N = 170 |
Table S16. Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'
ANOVA_P | Q | |
---|---|---|
HSA-MIR-21 | 8.373e-41 | 4.3e-38 |
HSA-MIR-146B | 7.771e-33 | 3.99e-30 |
HSA-MIR-7-2 | 1.34e-24 | 6.86e-22 |
HSA-MIR-204 | 9.277e-22 | 4.74e-19 |
HSA-MIR-375 | 3.517e-21 | 1.79e-18 |
HSA-MIR-1179 | 4.212e-21 | 2.14e-18 |
HSA-MIR-345 | 6.079e-21 | 3.09e-18 |
HSA-MIR-31 | 1.343e-20 | 6.81e-18 |
HSA-MIR-511-2 | 1.418e-20 | 7.17e-18 |
HSA-MIR-511-1 | 6.591e-20 | 3.33e-17 |
Figure S8. Get High-res Image As an example, this figure shows the association of HSA-MIR-21 to 'HISTOLOGICAL.TYPE'. P value = 8.37e-41 with ANOVA analysis.
![](V8ex.png)
11 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S17. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 14 | |
YES | 469 | |
Significant markers | N = 11 | |
Higher in YES | 8 | |
Higher in NO | 3 |
Table S18. Get Full Table List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-888 | 9.75 | 1.006e-10 | 5.03e-08 | 0.885 |
HSA-MIR-374A | -8.75 | 2.656e-07 | 0.000133 | 0.9175 |
HSA-MIR-660 | 7.95 | 9.216e-07 | 0.000459 | 0.8862 |
HSA-MIR-324 | 6.56 | 8.752e-06 | 0.00435 | 0.8451 |
HSA-MIR-20B | 6.36 | 1.377e-05 | 0.00683 | 0.8393 |
HSA-MIR-3130-1 | -5.51 | 3.7e-05 | 0.0183 | 0.7428 |
HSA-MIR-1976 | 5.69 | 3.895e-05 | 0.0192 | 0.7968 |
HSA-MIR-338 | 5.36 | 8.605e-05 | 0.0424 | 0.7979 |
HSA-MIR-3909 | -5.21 | 9.124e-05 | 0.0449 | 0.7457 |
HSA-MIR-532 | 5.36 | 9.213e-05 | 0.0452 | 0.8293 |
Figure S9. Get High-res Image As an example, this figure shows the association of HSA-MIR-888 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.01e-10 with T-test analysis.
![](V9ex.png)
Table S19. Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'
RADIATIONEXPOSURE | Labels | N |
NO | 407 | |
YES | 17 | |
Significant markers | N = 0 |
Table S20. Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'
EXTRATHYROIDAL.EXTENSION | Labels | N |
MINIMAL (T3) | 125 | |
MODERATE/ADVANCED (T4A) | 16 | |
NONE | 324 | |
VERY ADVANCED (T4B) | 1 | |
Significant markers | N = 71 |
Table S21. Get Full Table List of top 10 miRs differentially expressed by 'EXTRATHYROIDAL.EXTENSION'
ANOVA_P | Q | |
---|---|---|
HSA-MIR-30A | 3.319e-09 | 1.71e-06 |
HSA-MIR-363 | 3.35e-09 | 1.72e-06 |
HSA-MIR-148B | 8.793e-09 | 4.5e-06 |
HSA-MIR-126 | 1.312e-08 | 6.7e-06 |
HSA-MIR-21 | 1.313e-08 | 6.7e-06 |
HSA-MIR-758 | 1.7e-08 | 8.65e-06 |
HSA-MIR-411 | 1.921e-08 | 9.76e-06 |
HSA-MIR-376C | 2.017e-08 | 1.02e-05 |
HSA-MIR-1180 | 2.032e-08 | 1.03e-05 |
HSA-MIR-493 | 2.456e-08 | 1.24e-05 |
Figure S10. Get High-res Image As an example, this figure shows the association of HSA-MIR-30A to 'EXTRATHYROIDAL.EXTENSION'. P value = 3.32e-09 with ANOVA analysis.
![](V11ex.png)
Table S22. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 372 | |
R1 | 47 | |
R2 | 4 | |
RX | 29 | |
Significant markers | N = 1 |
Table S23. Get Full Table List of one miR differentially expressed by 'COMPLETENESS.OF.RESECTION'
ANOVA_P | Q | |
---|---|---|
HSA-MIR-139 | 1.471e-05 | 0.00756 |
Figure S11. Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'COMPLETENESS.OF.RESECTION'. P value = 1.47e-05 with ANOVA analysis.
![](V12ex.png)
Table S24. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'
NUMBER.OF.LYMPH.NODES | Mean (SD) | 3.54 (6.2) |
Significant markers | N = 60 | |
pos. correlated | 36 | |
neg. correlated | 24 |
Table S25. Get Full Table List of top 10 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-7-2 | -0.3175 | 3.888e-10 | 2e-07 |
HSA-MIR-1179 | -0.2956 | 1.431e-08 | 7.34e-06 |
HSA-MIR-21 | 0.2833 | 1.687e-08 | 8.64e-06 |
HSA-MIR-511-2 | 0.2778 | 3.362e-08 | 1.72e-05 |
HSA-MIR-382 | 0.2768 | 8.688e-08 | 4.43e-05 |
HSA-MIR-30E | -0.2685 | 9.506e-08 | 4.84e-05 |
HSA-MIR-199A-1 | 0.2674 | 1.083e-07 | 5.5e-05 |
HSA-MIR-874 | -0.2665 | 1.198e-07 | 6.07e-05 |
HSA-MIR-31 | 0.2662 | 1.329e-07 | 6.72e-05 |
HSA-MIR-134 | 0.2649 | 1.539e-07 | 7.77e-05 |
Figure S12. Get High-res Image As an example, this figure shows the association of HSA-MIR-7-2 to 'NUMBER.OF.LYMPH.NODES'. P value = 3.89e-10 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V13ex.png)
Table S26. Basic characteristics of clinical feature: 'MULTIFOCALITY'
MULTIFOCALITY | Labels | N |
MULTIFOCAL | 218 | |
UNIFOCAL | 255 | |
Significant markers | N = 1 | |
Higher in UNIFOCAL | 0 | |
Higher in MULTIFOCAL | 1 |
Table S27. Get Full Table List of one miR differentially expressed by 'MULTIFOCALITY'
T(pos if higher in 'UNIFOCAL') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-132 | -3.94 | 9.575e-05 | 0.0492 | 0.6054 |
Figure S13. Get High-res Image As an example, this figure shows the association of HSA-MIR-132 to 'MULTIFOCALITY'. P value = 9.58e-05 with T-test analysis.
![](V14ex.png)
Table S28. Basic characteristics of clinical feature: 'TUMOR.SIZE'
TUMOR.SIZE | Mean (SD) | 2.95 (1.6) |
Significant markers | N = 3 | |
pos. correlated | 1 | |
neg. correlated | 2 |
Table S29. Get Full Table List of 3 miRs significantly correlated to 'TUMOR.SIZE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-9-2 | -0.2071 | 4.34e-05 | 0.0223 |
HSA-MIR-9-1 | -0.2035 | 5.891e-05 | 0.0302 |
HSA-MIR-183 | 0.1976 | 9.702e-05 | 0.0497 |
Figure S14. Get High-res Image As an example, this figure shows the association of HSA-MIR-9-2 to 'TUMOR.SIZE'. P value = 4.34e-05 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V15ex.png)
-
Expresson data file = THCA-TP.miRseq_RPKM_log2.txt
-
Clinical data file = THCA-TP.merged_data.txt
-
Number of patients = 483
-
Number of miRs = 514
-
Number of clinical features = 15
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.
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.