Correlation between miRseq expression and clinical features
Colon Adenocarcinoma (Primary solid tumor)
21 April 2013 | analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1Q81B0V
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Colon Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1Q81B0V
Overview
Introduction

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

Summary

Testing the association between 417 genes and 11 clinical features across 407 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

- 8 genes correlated to 'AGE'.

- HSA-MIR-141 , HSA-MIR-26A-1 , HSA-MIR-153-2 , HSA-MIR-34A , HSA-MIR-432 , ...

- 13 genes correlated to 'HISTOLOGICAL.TYPE'.

- HSA-MIR-592 , HSA-MIR-31 , HSA-MIR-92A-1 , HSA-MIR-92A-2 , HSA-MIR-374B , ...

- 1 gene correlated to 'PATHOLOGY.T'.

- HSA-MIR-501

- 16 genes correlated to 'PATHOLOGICSPREAD(M)'.

- HSA-MIR-628 , HSA-MIR-1180 , HSA-MIR-140 , HSA-MIR-106A , HSA-LET-7F-2 , ...

- 1 gene correlated to 'TUMOR.STAGE'.

- HSA-MIR-625

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

- HSA-LET-7A-1 , HSA-LET-7A-2 , HSA-LET-7A-3 , HSA-MIR-497 , HSA-LET-7F-2 , ...

- No genes correlated to 'Time to Death', 'GENDER', 'PATHOLOGY.N', 'RADIATIONS.RADIATION.REGIMENINDICATION', and 'NUMBER.OF.LYMPH.NODES'.

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=0 |  |  |  |
AGE | Spearman correlation test | N=8 | older | N=7 | younger | N=1
GENDER | t test | N=0 |  |  |  |
HISTOLOGICAL TYPE | t test | N=13 | colon mucinous adenocarcinoma | N=2 | colon adenocarcinoma | N=11
PATHOLOGY T | Spearman correlation test | N=1 | higher pT | N=0 | lower pT | N=1
PATHOLOGY N | Spearman correlation test | N=0 |  |  |  |
PATHOLOGICSPREAD(M) | ANOVA test | N=16 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=1 | higher stage | N=0 | lower stage | N=1
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=36 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |  |  |  |

Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

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

Time to Death | Duration (Months) | 0.1-135.5 (median=7.5)
| censored | N = 260
| death | N = 49
| Significant markers | N = 0

Clinical variable #2: 'AGE'

8 genes related to 'AGE'.

Table S2. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 67.29 (13)
| Significant markers | N = 8
| pos. correlated | 7
| neg. correlated | 1

List of 8 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3. Get Full Table List of 8 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-141 | 0.2362 | 1.484e-06 | 0.000619
HSA-MIR-26A-1 | 0.2238 | 5.295e-06 | 0.0022
HSA-MIR-153-2 | 0.2191 | 8.38e-06 | 0.00348
HSA-MIR-34A | 0.2147 | 1.283e-05 | 0.00531
HSA-MIR-432 | -0.2118 | 1.94e-05 | 0.00801
HSA-MIR-33B | 0.1961 | 7.079e-05 | 0.0292
HSA-MIR-616 | 0.1945 | 9.184e-05 | 0.0377
HSA-MIR-653 | 0.1932 | 0.0001073 | 0.044

Figure S1. Get High-res Image As an example, this figure shows the association of HSA-MIR-141 to 'AGE'. P value = 1.48e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

Table S4. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 192
| MALE | 215
| Significant markers | N = 0

Clinical variable #4: 'HISTOLOGICAL.TYPE'

13 genes related to 'HISTOLOGICAL.TYPE'.

Table S5. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 349
| COLON MUCINOUS ADENOCARCINOMA | 55
| Significant markers | N = 13
| Higher in COLON MUCINOUS ADENOCARCINOMA | 2
| Higher in COLON ADENOCARCINOMA | 11

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

Table S6. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') | ttestP | Q | AUC
--- | --- | --- | --- | ---
HSA-MIR-592 | -6.31 | 1.886e-08 | 7.87e-06 | 0.746
HSA-MIR-31 | 5.81 | 1.242e-07 | 5.17e-05 | 0.7159
HSA-MIR-92A-1 | -5.59 | 3.277e-07 | 0.000136 | 0.714
HSA-MIR-92A-2 | -4.83 | 7.505e-06 | 0.00311 | 0.6961
HSA-MIR-374B | -4.78 | 7.745e-06 | 0.0032 | 0.6792
HSA-MIR-196B | -4.77 | 9.22e-06 | 0.0038 | 0.686
HSA-MIR-574 | 4.64 | 1.48e-05 | 0.00608 | 0.6868
HSA-MIR-29A | -4.63 | 1.666e-05 | 0.00683 | 0.6971
HSA-MIR-1247 | -4.61 | 1.728e-05 | 0.00707 | 0.6913
HSA-MIR-98 | -4.53 | 2.086e-05 | 0.00851 | 0.6802

Figure S2. Get High-res Image As an example, this figure shows the association of HSA-MIR-592 to 'HISTOLOGICAL.TYPE'. P value = 1.89e-08 with T-test analysis.

Clinical variable #5: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

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

PATHOLOGY.T | Mean (SD) | 2.88 (0.63)
|  | N
| T0 | 1
| T1 | 10
| T2 | 69
| T3 | 279
| T4 | 45
| Significant markers | N = 1
| pos. correlated | 0
| neg. correlated | 1

List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S8. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-501 | -0.1908 | 0.0001139 | 0.0475

Figure S3. Get High-res Image As an example, this figure shows the association of HSA-MIR-501 to 'PATHOLOGY.T'. P value = 0.000114 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

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

PATHOLOGY.N | Mean (SD) | 0.58 (0.77)
|  | N
| N0 | 241
| N1 | 94
| N2 | 70
| Significant markers | N = 0

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

16 genes related to 'PATHOLOGICSPREAD(M)'.

Table S10. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 305
| M1 | 50
| M1A | 7
| M1B | 1
| MX | 36
| Significant markers | N = 16

List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S11. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

| ANOVA_P | Q
--- | --- | ---
HSA-MIR-628 | 1.496e-06 | 0.000624
HSA-MIR-1180 | 1.503e-06 | 0.000625
HSA-MIR-140 | 1.926e-06 | 0.000799
HSA-MIR-106A | 4.51e-06 | 0.00187
HSA-LET-7F-2 | 5.673e-06 | 0.00234
HSA-MIR-142 | 7.536e-06 | 0.0031
HSA-MIR-301A | 1.422e-05 | 0.00585
HSA-LET-7A-1 | 2.684e-05 | 0.011
HSA-MIR-126 | 2.76e-05 | 0.0113
HSA-MIR-1277 | 2.984e-05 | 0.0122

Figure S4. Get High-res Image As an example, this figure shows the association of HSA-MIR-628 to 'PATHOLOGICSPREAD(M)'. P value = 1.5e-06 with ANOVA analysis.

Clinical variable #8: 'TUMOR.STAGE'

One gene related to 'TUMOR.STAGE'.

Table S12. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 2.42 (0.93)
|  | N
| Stage 1 | 65
| Stage 2 | 155
| Stage 3 | 113
| Stage 4 | 57
| Significant markers | N = 1
| pos. correlated | 0
| neg. correlated | 1

List of one gene significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S13. Get Full Table List of one gene significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
HSA-MIR-625 | -0.2101 | 2.892e-05 | 0.0121

Figure S5. Get High-res Image As an example, this figure shows the association of HSA-MIR-625 to 'TUMOR.STAGE'. P value = 2.89e-05 with Spearman correlation analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S14. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 3
| YES | 404
| Significant markers | N = 0

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

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

Table S15. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 281
| R1 | 1
| R2 | 25
| RX | 22
| Significant markers | N = 36

List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S16. Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

| ANOVA_P | Q
--- | --- | ---
HSA-LET-7A-1 | 1.64e-09 | 6.84e-07
HSA-LET-7A-2 | 1.823e-09 | 7.59e-07
HSA-LET-7A-3 | 1.922e-09 | 7.98e-07
HSA-MIR-497 | 9.129e-09 | 3.78e-06
HSA-LET-7F-2 | 1.883e-08 | 7.77e-06
HSA-MIR-16-1 | 2.024e-07 | 8.34e-05
HSA-MIR-126 | 2.129e-07 | 8.75e-05
HSA-MIR-1180 | 2.818e-07 | 0.000116
HSA-MIR-106A | 3.022e-07 | 0.000124
HSA-MIR-136 | 4.192e-07 | 0.000171

Figure S6. Get High-res Image As an example, this figure shows the association of HSA-LET-7A-1 to 'COMPLETENESS.OF.RESECTION'. P value = 1.64e-09 with ANOVA analysis.

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

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S17. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 2.04 (4.5)
| Significant markers | N = 0

Methods & Data
Input

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

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

- Number of patients = 407

- Number of genes = 417

- Number of clinical features = 11

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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