Correlation between miRseq expression and clinical features
Adrenocortical Carcinoma (Primary solid tumor)
15 July 2014 | analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1C24V4T
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1C24V4T
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 518 miRs and 7 clinical features across 78 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one miRs.

- 33 miRs correlated to 'Time to Death'.

- HSA-MIR-106B , HSA-MIR-29C , HSA-MIR-130B , HSA-MIR-664 , HSA-MIR-3170 , ...

- 3 miRs correlated to 'AGE'.

- HSA-MIR-505 , HSA-MIR-580 , HSA-MIR-361

- 1 miR correlated to 'NEOPLASM.DISEASESTAGE'.

- HSA-MIR-130B

- 9 miRs correlated to 'PATHOLOGY.T.STAGE'.

- HSA-MIR-615 , HSA-MIR-130B , HSA-MIR-489 , HSA-MIR-130A , HSA-MIR-550A-2 , ...

- 2 miRs correlated to 'GENDER'.

- HSA-MIR-139 , HSA-MIR-3074

- No miRs correlated to 'PATHOLOGY.N.STAGE', and 'ETHNICITY'.

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 miRs that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature | Statistical test | Significant miRs | Associated with |  | Associated with |
--- | --- | --- | --- | --- | --- | ---
Time to Death | Cox regression test | N=33 | shorter survival | N=21 | longer survival | N=12
AGE | Spearman correlation test | N=3 | older | N=3 | younger | N=0
NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=1 |  |  |  |
PATHOLOGY T STAGE | Spearman correlation test | N=9 | higher stage | N=8 | lower stage | N=1
PATHOLOGY N STAGE | Wilcoxon test | N=0 |  |  |  |
GENDER | Wilcoxon test | N=2 | male | N=2 | female | N=0
ETHNICITY | Wilcoxon test | N=0 |  |  |  |

Clinical variable #1: 'Time to Death'

33 miRs related to 'Time to Death'.

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

Time to Death | Duration (Months) | 4.1-153.6 (median=32)
| censored | N = 52
| death | N = 26
| Significant markers | N = 33
| associated with shorter survival | 21
| associated with longer survival | 12

List of top 10 miRs differentially expressed by 'Time to Death'

Table S2. Get Full Table List of top 10 miRs significantly associated with 'Time to Death' by Cox regression test

| HazardRatio | Wald_P | Q | C_index
--- | --- | --- | --- | ---
HSA-MIR-106B | 3.6 | 4.712e-07 | 0.00024 | 0.793
HSA-MIR-29C | 0.58 | 5.101e-07 | 0.00026 | 0.198
HSA-MIR-130B | 2.3 | 7.514e-07 | 0.00039 | 0.798
HSA-MIR-664 | 0.38 | 4.508e-06 | 0.0023 | 0.228
HSA-MIR-3170 | 1.97 | 1.447e-05 | 0.0074 | 0.778
HSA-MIR-18A | 1.97 | 1.659e-05 | 0.0085 | 0.712
HSA-MIR-301B | 1.76 | 1.76e-05 | 0.009 | 0.755
HSA-MIR-1255A | 2.7 | 1.774e-05 | 0.0091 | 0.781
HSA-MIR-197 | 2.1 | 3.473e-05 | 0.018 | 0.758
HSA-MIR-3940 | 1.97 | 5.068e-05 | 0.026 | 0.788

Clinical variable #2: 'AGE'

3 miRs related to 'AGE'.

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

AGE | Mean (SD) | 46.44 (16)
| Significant markers | N = 3
| pos. correlated | 3
| neg. correlated | 0

List of 3 miRs differentially expressed by 'AGE'

Table S4. Get Full Table List of 3 miRs significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-505 | 0.4496 | 3.637e-05 | 0.0188
HSA-MIR-580 | 0.4959 | 4.151e-05 | 0.0215
HSA-MIR-361 | 0.4308 | 8.253e-05 | 0.0426

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

One miR related to 'NEOPLASM.DISEASESTAGE'.

Table S5. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE I | 8
| STAGE II | 33
| STAGE III | 16
| STAGE IV | 16
| Significant markers | N = 1

List of one miR differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6. Get Full Table List of one miR differentially expressed by 'NEOPLASM.DISEASESTAGE'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-130B | 0.0005459 | 0.283

Clinical variable #4: 'PATHOLOGY.T.STAGE'

9 miRs related to 'PATHOLOGY.T.STAGE'.

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE | Mean (SD) | 2.51 (0.99)
|  | N
| 1 | 8
| 2 | 38
| 3 | 9
| 4 | 18
| Significant markers | N = 9
| pos. correlated | 8
| neg. correlated | 1

List of 9 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

Table S8. Get Full Table List of 9 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-615 | 0.5074 | 8.59e-06 | 0.00445
HSA-MIR-130B | 0.4656 | 3.319e-05 | 0.0172
HSA-MIR-489 | -0.6525 | 3.877e-05 | 0.02
HSA-MIR-130A | 0.4484 | 6.948e-05 | 0.0358
HSA-MIR-550A-2 | 0.4375 | 0.000191 | 0.0982
HSA-MIR-196A-1 | 0.4182 | 0.0002314 | 0.119
HSA-MIR-16-2 | 0.4107 | 0.0003075 | 0.157
HSA-MIR-3074 | 0.4041 | 0.000392 | 0.2
HSA-MIR-769 | 0.3933 | 0.0005779 | 0.295

Clinical variable #5: 'PATHOLOGY.N.STAGE'

No miR related to 'PATHOLOGY.N.STAGE'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE | Labels | N
| class0 | 64
| class1 | 10
| Significant markers | N = 0

Clinical variable #6: 'GENDER'

2 miRs related to 'GENDER'.

Table S10. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 49
| MALE | 29
| Significant markers | N = 2
| Higher in MALE | 2
| Higher in FEMALE | 0

List of 2 miRs differentially expressed by 'GENDER'

Table S11. Get Full Table List of 2 miRs differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

| W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC
--- | --- | --- | --- | ---
HSA-MIR-139 | 333 | 9.706e-05 | 0.0503 | 0.7657
HSA-MIR-3074 | 1062 | 0.0002845 | 0.147 | 0.7474

Clinical variable #7: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S12. Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY | Labels | N
| HISPANIC OR LATINO | 8
| NOT HISPANIC OR LATINO | 28
| Significant markers | N = 0

Methods & Data
Input

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

- Clinical data file = ACC-TP.merged_data.txt

- Number of patients = 78

- Number of miRs = 518

- Number of clinical features = 7

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

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

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

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

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.

- 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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle