Correlation between miRseq expression and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C11R6P83
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/C11R6P83
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 461 miRs and 11 clinical features across 492 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one miRs.

  • 10 miRs correlated to 'Time to Death'.

    • HSA-MIR-34B ,  HSA-MIR-34C ,  HSA-MIR-627 ,  HSA-MIR-450A-2 ,  HSA-MIR-130B ,  ...

  • 3 miRs correlated to 'AGE'.

    • HSA-MIR-590 ,  HSA-MIR-148A ,  HSA-MIR-29B-2

  • 54 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-139 ,  HSA-MIR-625 ,  HSA-MIR-486 ,  HSA-MIR-21 ,  HSA-MIR-155 ,  ...

  • 57 miRs correlated to 'PATHOLOGY.T.STAGE'.

    • HSA-MIR-139 ,  HSA-MIR-486 ,  HSA-MIR-625 ,  HSA-MIR-21 ,  HSA-MIR-155 ,  ...

  • 3 miRs correlated to 'PATHOLOGY.N.STAGE'.

    • HSA-MIR-193A ,  HSA-MIR-99B ,  HSA-MIR-34C

  • 55 miRs correlated to 'PATHOLOGY.M.STAGE'.

    • HSA-MIR-144 ,  HSA-MIR-625 ,  HSA-MIR-130B ,  HSA-MIR-106B ,  HSA-MIR-155 ,  ...

  • 20 miRs correlated to 'GENDER'.

    • HSA-MIR-100 ,  HSA-MIR-708 ,  HSA-MIR-455 ,  HSA-MIR-599 ,  HSA-MIR-204 ,  ...

  • 23 miRs correlated to 'RACE'.

    • HSA-MIR-26B ,  HSA-MIR-497 ,  HSA-MIR-3605 ,  HSA-MIR-195 ,  HSA-MIR-590 ,  ...

  • 1 miR correlated to 'ETHNICITY'.

    • HSA-MIR-219-2

  • No miRs correlated to 'KARNOFSKY.PERFORMANCE.SCORE', and 'NUMBERPACKYEARSSMOKED'.

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=10 shorter survival N=10 longer survival N=0
AGE Spearman correlation test N=3 older N=3 younger N=0
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=54        
PATHOLOGY T STAGE Spearman correlation test N=57 higher stage N=43 lower stage N=14
PATHOLOGY N STAGE Wilcoxon test N=3 class1 N=3 class0 N=0
PATHOLOGY M STAGE Kruskal-Wallis test N=55        
GENDER Wilcoxon test N=20 male N=20 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
RACE Kruskal-Wallis test N=23        
ETHNICITY Wilcoxon test N=1 not hispanic or latino N=1 hispanic or latino N=0
Clinical variable #1: 'Time to Death'

10 miRs related to 'Time to Death'.

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

Time to Death Duration (Years) 7-3668 (median=1321.5)
  censored N = 327
  death N = 25
     
  Significant markers N = 10
  associated with shorter survival 10
  associated with longer survival 0
List of 10 miRs differentially expressed by 'Time to Death'

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

HazardRatio Wald_P Q C_index
HSA-MIR-34B 1.5 1.244e-06 0.00057 0.754
HSA-MIR-34C 1.43 7.22e-06 0.0033 0.673
HSA-MIR-627 2.1 0.0001124 0.052 0.732
HSA-MIR-450A-2 1.99 0.0001193 0.055 0.697
HSA-MIR-130B 2.9 0.000125 0.057 0.666
HSA-MIR-149 1.75 0.0001289 0.059 0.736
HSA-MIR-450A-1 1.92 0.0002392 0.11 0.693
HSA-MIR-9-1 1.29 0.0002585 0.12 0.663
HSA-MIR-9-2 1.28 0.0003541 0.16 0.65
HSA-MIR-296 1.86 0.0004447 0.2 0.7
Clinical variable #2: 'AGE'

3 miRs related to 'AGE'.

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

AGE Mean (SD) 60.56 (12)
  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-590 0.1807 5.558e-05 0.0256
HSA-MIR-148A 0.1599 0.0003709 0.171
HSA-MIR-29B-2 0.1585 0.0004185 0.192
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

54 miRs related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 234
  STAGE II 54
  STAGE III 125
  STAGE IV 79
     
  Significant markers N = 54
List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-139 9.203e-13 4.24e-10
HSA-MIR-625 1.412e-09 6.5e-07
HSA-MIR-486 4.915e-09 2.26e-06
HSA-MIR-21 1.929e-08 8.83e-06
HSA-MIR-155 2.05e-08 9.37e-06
HSA-LET-7I 3.104e-08 1.42e-05
HSA-MIR-144 4.244e-08 1.93e-05
HSA-MIR-130B 7.412e-08 3.37e-05
HSA-MIR-106B 2.519e-07 0.000114
HSA-MIR-451 5.557e-07 0.000251
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

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

PATHOLOGY.T.STAGE Mean (SD) 1.91 (0.96)
  N
  1 240
  2 65
  3 176
  4 11
     
  Significant markers N = 57
  pos. correlated 43
  neg. correlated 14
List of top 10 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

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 -0.3304 5.431e-14 2.5e-11
HSA-MIR-486 -0.273 7.437e-10 3.42e-07
HSA-MIR-625 0.2686 1.406e-09 6.45e-07
HSA-MIR-21 0.2615 3.884e-09 1.78e-06
HSA-MIR-155 0.2493 2.097e-08 9.58e-06
HSA-MIR-144 -0.2424 5.221e-08 2.38e-05
HSA-MIR-9-1 0.2343 1.456e-07 6.62e-05
HSA-MIR-130B 0.2339 1.537e-07 6.98e-05
HSA-MIR-451 -0.2319 1.98e-07 8.97e-05
HSA-MIR-9-2 0.2251 4.55e-07 0.000206
Clinical variable #5: 'PATHOLOGY.N.STAGE'

3 miRs related to 'PATHOLOGY.N.STAGE'.

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

PATHOLOGY.N.STAGE Labels N
  class0 224
  class1 18
     
  Significant markers N = 3
  Higher in class1 3
  Higher in class0 0
List of 3 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S10.  Get Full Table List of 3 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
HSA-MIR-193A 3020 0.0004449 0.205 0.749
HSA-MIR-99B 1030 0.0005628 0.258 0.7445
HSA-MIR-34C 2613 0.0006293 0.288 0.7498
Clinical variable #6: 'PATHOLOGY.M.STAGE'

55 miRs related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 405
  M1 78
  MX 8
     
  Significant markers N = 55
List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-144 7.905e-07 0.000364
HSA-MIR-625 8.534e-07 0.000393
HSA-MIR-130B 1.648e-06 0.000756
HSA-MIR-106B 3.533e-06 0.00162
HSA-MIR-155 4.052e-06 0.00185
HSA-MIR-1277 5.3e-06 0.00242
HSA-MIR-10B 5.558e-06 0.00253
HSA-MIR-186 6.204e-06 0.00282
HSA-LET-7I 9.752e-06 0.00442
HSA-MIR-1269 1.424e-05 0.00644
Clinical variable #7: 'GENDER'

20 miRs related to 'GENDER'.

Table S13.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 169
  MALE 323
     
  Significant markers N = 20
  Higher in MALE 20
  Higher in FEMALE 0
List of top 10 miRs differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 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-100 39354 8.064e-16 3.72e-13 0.7209
HSA-MIR-708 36180 2.961e-09 1.36e-06 0.6628
HSA-MIR-455 19155 5.502e-08 2.53e-05 0.6491
HSA-MIR-599 6842 1.053e-07 4.82e-05 0.6805
HSA-MIR-204 19906 1.014e-06 0.000463 0.6342
HSA-MIR-31 28290 6.125e-06 0.00279 0.6308
HSA-MIR-155 33793 1.426e-05 0.00649 0.6191
HSA-MIR-30A 21385 7.975e-05 0.0362 0.6082
HSA-MIR-500B 21569 0.0001597 0.0723 0.6036
HSA-MIR-500A 21824 0.0002602 0.118 0.6002
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

No miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S15.  Basic characteristics of clinical feature: '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
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No miR related to 'NUMBERPACKYEARSSMOKED'.

Table S16.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 29 (15)
  Value N
  7 1
  10 1
  30 2
  40 2
  46 1
     
  Significant markers N = 0
Clinical variable #10: 'RACE'

23 miRs related to 'RACE'.

Table S17.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 8
  BLACK OR AFRICAN AMERICAN 32
  WHITE 445
     
  Significant markers N = 23
List of top 10 miRs differentially expressed by 'RACE'

Table S18.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-26B 1.923e-06 0.000887
HSA-MIR-497 3.561e-06 0.00164
HSA-MIR-3605 3.687e-06 0.00169
HSA-MIR-195 3.84e-06 0.00176
HSA-MIR-590 1.168e-05 0.00534
HSA-MIR-1271 2.021e-05 0.00921
HSA-MIR-186 2.244e-05 0.0102
HSA-MIR-574 2.772e-05 0.0126
HSA-MIR-3613 3.815e-05 0.0173
HSA-MIR-424 4.663e-05 0.0211
Clinical variable #11: 'ETHNICITY'

One miR related to 'ETHNICITY'.

Table S19.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 22
  NOT HISPANIC OR LATINO 324
     
  Significant markers N = 1
  Higher in NOT HISPANIC OR LATINO 1
  Higher in HISPANIC OR LATINO 0
List of one miR differentially expressed by 'ETHNICITY'

Table S20.  Get Full Table List of one miR differentially expressed by 'ETHNICITY'

W(pos if higher in 'NOT HISPANIC OR LATINO') wilcoxontestP Q AUC
HSA-MIR-219-2 c("117", "0.0002285") c("117", "0.0002285") 0.105 0.8892
Methods & Data
Input

  • Expresson data file = KIRC-TP.miRseq_RPKM_log2.txt

  • Clinical data file = KIRC-TP.merged_data.txt

  • Number of patients = 492

  • Number of miRs = 461

  • 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

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.

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)
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