Correlation between miRseq expression and clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
21 April 2013 | analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1GT5K69
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Thyroid Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1GT5K69
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 517 genes and 14 clinical features across 373 samples, statistically thresholded by Q value < 0.05, 13 clinical features related to at least one genes.

- 1 gene correlated to 'Time to Death'.

- HSA-MIR-181A-2

- 5 genes correlated to 'AGE'.

- HSA-MIR-362 , HSA-MIR-376A-1 , HSA-MIR-1229 , HSA-MIR-660 , HSA-MIR-181A-2

- 2 genes correlated to 'GENDER'.

- HSA-MIR-651 , HSA-MIR-3920

- 142 genes correlated to 'HISTOLOGICAL.TYPE'.

- HSA-MIR-21 , HSA-MIR-146B , HSA-MIR-7-2 , HSA-MIR-511-2 , HSA-MIR-31 , ...

- 8 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- HSA-MIR-888 , HSA-MIR-374A , HSA-MIR-660 , HSA-MIR-324 , HSA-MIR-20B , ...

- 1 gene correlated to 'DISTANT.METASTASIS'.

- HSA-MIR-3677

- 57 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.

- HSA-MIR-30A , HSA-MIR-21 , HSA-MIR-425 , HSA-MIR-7-2 , HSA-MIR-148B , ...

- 30 genes correlated to 'LYMPH.NODE.METASTASIS'.

- HSA-MIR-146B , HSA-MIR-21 , HSA-MIR-7-2 , HSA-MIR-511-2 , HSA-MIR-1179 , ...

- 2 genes correlated to 'COMPLETENESS.OF.RESECTION'.

- HSA-MIR-196A-1 , HSA-MIR-139

- 37 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

- HSA-MIR-7-2 , HSA-MIR-1179 , HSA-MIR-31 , HSA-MIR-511-2 , HSA-MIR-21 , ...

- 19 genes correlated to 'NEOPLASM.DISEASESTAGE'.

- HSA-MIR-425 , HSA-MIR-139 , HSA-MIR-30A , HSA-MIR-181A-2 , HSA-MIR-376A-1 , ...

- 1 gene correlated to 'MULTIFOCALITY'.

- HSA-MIR-132

- 2 genes correlated to 'TUMOR.SIZE'.

- HSA-MIR-182 , HSA-MIR-183

- No genes correlated to 'RADIATIONEXPOSURE'

Results
Overview of the results

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 Q value < 0.05.

Clinical feature | Statistical test | Significant genes | Associated with |  | Associated with |
--- | --- | --- | --- | --- | --- | ---
Time to Death | Cox regression test | N=1 | shorter survival | N=0 | longer survival | N=1
AGE | Spearman correlation test | N=5 | older | N=4 | younger | N=1
GENDER | t test | N=2 | male | N=0 | female | N=2
HISTOLOGICAL TYPE | ANOVA test | N=142 |  |  |  |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=8 | yes | N=6 | no | N=2
RADIATIONEXPOSURE | t test | N=0 |  |  |  |
DISTANT METASTASIS | ANOVA test | N=1 |  |  |  |
EXTRATHYROIDAL EXTENSION | ANOVA test | N=57 |  |  |  |
LYMPH NODE METASTASIS | ANOVA test | N=30 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=2 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=37 | higher number.of.lymph.nodes | N=24 | lower number.of.lymph.nodes | N=13
NEOPLASM DISEASESTAGE | ANOVA test | N=19 |  |  |  |
MULTIFOCALITY | t test | N=1 | unifocal | N=0 | multifocal | N=1
TUMOR SIZE | Spearman correlation test | N=2 | higher tumor.size | N=2 | lower tumor.size | N=0

Clinical variable #1: 'Time to Death'

One gene related to 'Time to Death'.

Table S1. Basic characteristics of clinical feature: 'Time to Death'

Time to Death | Duration (Months) | 0-147.4 (median=9)
| censored | N = 358
| death | N = 10
| Significant markers | N = 1
| associated with shorter survival | 0
| associated with longer survival | 1

List of one gene significantly associated with 'Time to Death' by Cox regression test

Table S2. Get Full Table List of one gene significantly associated with 'Time to Death' by Cox regression test

| HazardRatio | Wald_P | Q | C_index
--- | --- | --- | --- | ---
HSA-MIR-181A-2 | 0.28 | 6.597e-05 | 0.034 | 0.137

Figure S1. Get High-res Image As an example, this figure shows the association of HSA-MIR-181A-2 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 6.6e-05 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

5 genes related to 'AGE'.

Table S3. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 46.45 (16)
| Significant markers | N = 5
| pos. correlated | 4
| neg. correlated | 1

List of 5 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4. Get Full Table List of 5 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-362 | 0.2216 | 1.571e-05 | 0.00812
HSA-MIR-376A-1 | 0.2899 | 2.156e-05 | 0.0111
HSA-MIR-1229 | 0.2416 | 2.334e-05 | 0.012
HSA-MIR-660 | 0.2131 | 3.335e-05 | 0.0171
HSA-MIR-181A-2 | -0.2052 | 6.526e-05 | 0.0335

Figure S2. Get High-res Image As an example, this figure shows the association of HSA-MIR-362 to 'AGE'. P value = 1.57e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

2 genes related to 'GENDER'.

Table S5. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 279
| MALE | 94
| Significant markers | N = 2
| Higher in MALE | 0
| Higher in FEMALE | 2

List of 2 genes differentially expressed by 'GENDER'

Table S6. Get Full Table List of 2 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
HSA-MIR-651 | -5.19 | 6.475e-07 | 0.000335 | 0.6797
HSA-MIR-3920 | -4.09 | 7.101e-05 | 0.0366 | 0.6371

Figure S3. Get High-res Image As an example, this figure shows the association of HSA-MIR-651 to 'GENDER'. P value = 6.47e-07 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

142 genes related to 'HISTOLOGICAL.TYPE'.

Table S7. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| OTHER SPECIFY | 6
| THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | 254
| THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | 82
| THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) | 31
| Significant markers | N = 142

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-21 | 3.804e-33 | 1.97e-30
HSA-MIR-146B | 2.041e-21 | 1.05e-18
HSA-MIR-7-2 | 4.061e-18 | 2.09e-15
HSA-MIR-511-2 | 3.812e-17 | 1.96e-14
HSA-MIR-31 | 2.021e-16 | 1.04e-13
HSA-MIR-345 | 2.218e-16 | 1.14e-13
HSA-MIR-204 | 4.177e-16 | 2.13e-13
HSA-MIR-511-1 | 4.295e-16 | 2.19e-13
HSA-MIR-30C-2 | 1.766e-15 | 8.99e-13
HSA-MIR-1179 | 1.164e-14 | 5.91e-12

Figure S4. Get High-res Image As an example, this figure shows the association of HSA-MIR-21 to 'HISTOLOGICAL.TYPE'. P value = 3.8e-33 with ANOVA analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

8 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S9. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 14
| YES | 359
| Significant markers | N = 8
| Higher in YES | 6
| Higher in NO | 2

List of 8 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S10. Get Full Table List of 8 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
HSA-MIR-888 | 8.52 | 4.139e-10 | 2.08e-07 | 0.8649
HSA-MIR-374A | -8.27 | 3.421e-07 | 0.000171 | 0.8999
HSA-MIR-660 | 6.61 | 7.333e-06 | 0.00367 | 0.8603
HSA-MIR-324 | 6.27 | 1.176e-05 | 0.00587 | 0.8337
HSA-MIR-20B | 5.85 | 2.794e-05 | 0.0139 | 0.8212
HSA-MIR-1976 | 5.68 | 3.049e-05 | 0.0152 | 0.7921
HSA-MIR-3130-1 | -5.06 | 7.038e-05 | 0.0349 | 0.7198
HSA-MIR-99A | 5.29 | 0.000101 | 0.05 | 0.839

Figure S5. Get High-res Image As an example, this figure shows the association of HSA-MIR-888 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.14e-10 with T-test analysis.

Clinical variable #6: 'RADIATIONEXPOSURE'

No gene related to 'RADIATIONEXPOSURE'.

Table S11. Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'

RADIATIONEXPOSURE | Labels | N
| NO | 318
| YES | 16
| Significant markers | N = 0

Clinical variable #7: 'DISTANT.METASTASIS'

One gene related to 'DISTANT.METASTASIS'.

Table S12. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS | Labels | N
| M0 | 195
| M1 | 6
| MX | 171
| Significant markers | N = 1

List of one gene differentially expressed by 'DISTANT.METASTASIS'

Table S13. Get Full Table List of one gene differentially expressed by 'DISTANT.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-3677 | 7.774e-05 | 0.0402

Figure S6. Get High-res Image As an example, this figure shows the association of HSA-MIR-3677 to 'DISTANT.METASTASIS'. P value = 7.77e-05 with ANOVA analysis.

Clinical variable #8: 'EXTRATHYROIDAL.EXTENSION'

57 genes related to 'EXTRATHYROIDAL.EXTENSION'.

Table S14. Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION | Labels | N
| MINIMAL (T3) | 96
| MODERATE/ADVANCED (T4A) | 12
| NONE | 248
| VERY ADVANCED (T4B) | 1
| Significant markers | N = 57

List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

Table S15. Get Full Table List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-30A | 1.451e-08 | 7.5e-06
HSA-MIR-21 | 1.855e-08 | 9.57e-06
HSA-MIR-425 | 6.198e-08 | 3.19e-05
HSA-MIR-7-2 | 6.769e-08 | 3.48e-05
HSA-MIR-148B | 1.439e-07 | 7.38e-05
HSA-MIR-411 | 1.501e-07 | 7.68e-05
HSA-MIR-1180 | 1.839e-07 | 9.4e-05
HSA-MIR-204 | 3.181e-07 | 0.000162
HSA-MIR-539 | 3.789e-07 | 0.000193
HSA-MIR-127 | 4.035e-07 | 0.000205

Figure S7. Get High-res Image As an example, this figure shows the association of HSA-MIR-30A to 'EXTRATHYROIDAL.EXTENSION'. P value = 1.45e-08 with ANOVA analysis.

Clinical variable #9: 'LYMPH.NODE.METASTASIS'

30 genes related to 'LYMPH.NODE.METASTASIS'.

Table S16. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS | Labels | N
| N0 | 176
| N1 | 38
| N1A | 75
| N1B | 49
| NX | 35
| Significant markers | N = 30

List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S17. Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-146B | 2.059e-10 | 1.06e-07
HSA-MIR-21 | 4.228e-09 | 2.18e-06
HSA-MIR-7-2 | 8.5e-09 | 4.38e-06
HSA-MIR-511-2 | 4.002e-08 | 2.06e-05
HSA-MIR-1179 | 6.631e-08 | 3.4e-05
HSA-MIR-222 | 8.355e-08 | 4.28e-05
HSA-MIR-31 | 1.182e-07 | 6.04e-05
HSA-MIR-204 | 1.879e-07 | 9.58e-05
HSA-MIR-142 | 3.31e-07 | 0.000169
HSA-MIR-152 | 4.291e-07 | 0.000218

Figure S8. Get High-res Image As an example, this figure shows the association of HSA-MIR-146B to 'LYMPH.NODE.METASTASIS'. P value = 2.06e-10 with ANOVA analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

2 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S18. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 293
| R1 | 30
| R2 | 2
| RX | 24
| Significant markers | N = 2

List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S19. Get Full Table List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-196A-1 | 7.168e-05 | 0.0371
HSA-MIR-139 | 9.63e-05 | 0.0497

Figure S9. Get High-res Image As an example, this figure shows the association of HSA-MIR-196A-1 to 'COMPLETENESS.OF.RESECTION'. P value = 7.17e-05 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

37 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S20. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 3.19 (5.6)
| Significant markers | N = 37
| pos. correlated | 24
| neg. correlated | 13

List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S21. Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-7-2 | -0.3792 | 4.469e-11 | 2.31e-08
HSA-MIR-1179 | -0.3219 | 7.93e-08 | 4.09e-05
HSA-MIR-31 | 0.3083 | 9.798e-08 | 5.05e-05
HSA-MIR-511-2 | 0.2923 | 4.641e-07 | 0.000239
HSA-MIR-21 | 0.2889 | 6.111e-07 | 0.000314
HSA-MIR-19B-1 | 0.2787 | 1.548e-06 | 0.000793
HSA-MIR-152 | -0.2728 | 2.622e-06 | 0.00134
HSA-MIR-511-1 | 0.2722 | 2.882e-06 | 0.00147
HSA-MIR-222 | 0.2693 | 3.541e-06 | 0.0018
HSA-MIR-7-3 | -0.2982 | 3.606e-06 | 0.00183

Figure S10. Get High-res Image As an example, this figure shows the association of HSA-MIR-7-2 to 'NUMBER.OF.LYMPH.NODES'. P value = 4.47e-11 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

19 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S22. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE I | 210
| STAGE II | 43
| STAGE III | 83
| STAGE IV | 1
| STAGE IVA | 29
| STAGE IVC | 4
| Significant markers | N = 19

List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S23. Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-425 | 1.145e-07 | 5.92e-05
HSA-MIR-139 | 2.938e-07 | 0.000152
HSA-MIR-30A | 3.237e-06 | 0.00167
HSA-MIR-181A-2 | 3.79e-06 | 0.00195
HSA-MIR-376A-1 | 4.619e-06 | 0.00237
HSA-MIR-31 | 5.113e-06 | 0.00262
HSA-MIR-514B | 6.182e-06 | 0.00316
HSA-MIR-210 | 7.864e-06 | 0.00401
HSA-MIR-146B | 9.068e-06 | 0.00462
HSA-MIR-206 | 1.808e-05 | 0.00918

Figure S11. Get High-res Image As an example, this figure shows the association of HSA-MIR-425 to 'NEOPLASM.DISEASESTAGE'. P value = 1.14e-07 with ANOVA analysis.

Clinical variable #13: 'MULTIFOCALITY'

One gene related to 'MULTIFOCALITY'.

Table S24. Basic characteristics of clinical feature: 'MULTIFOCALITY'

MULTIFOCALITY | Labels | N
| MULTIFOCAL | 165
| UNIFOCAL | 199
| Significant markers | N = 1
| Higher in UNIFOCAL | 0
| Higher in MULTIFOCAL | 1

List of one gene differentially expressed by 'MULTIFOCALITY'

Table S25. Get Full Table List of one gene differentially expressed by 'MULTIFOCALITY'

| T(pos if higher in 'UNIFOCAL') | ttestP | Q | AUC
--- | --- | --- | --- | ---
HSA-MIR-132 | -4.47 | 1.077e-05 | 0.00557 | 0.6345

Figure S12. Get High-res Image As an example, this figure shows the association of HSA-MIR-132 to 'MULTIFOCALITY'. P value = 1.08e-05 with T-test analysis.

Clinical variable #14: 'TUMOR.SIZE'

2 genes related to 'TUMOR.SIZE'.

Table S26. Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE | Mean (SD) | 2.87 (1.6)
| Significant markers | N = 2
| pos. correlated | 2
| neg. correlated | 0

List of 2 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S27. Get Full Table List of 2 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-182 | 0.2391 | 3.895e-05 | 0.0201
HSA-MIR-183 | 0.2385 | 4.073e-05 | 0.021

Figure S13. Get High-res Image As an example, this figure shows the association of HSA-MIR-182 to 'TUMOR.SIZE'. P value = 3.89e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

- Expresson data file = THCA-TP.miRseq_RPKM_log2.txt

- Clinical data file = THCA-TP.clin.merged.picked.txt

- Number of patients = 373

- Number of genes = 517

- Number of clinical features = 14

Survival analysis

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

Correlation analysis

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

Student's t-test analysis

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

ANOVA analysis

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

Q value calculation

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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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