Correlation between miRseq expression and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1BK1B67
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/C1BK1B67
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 462 miRs and 11 clinical features across 504 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one miRs.

  • 8 miRs correlated to 'Time to Death'.

    • HSA-MIR-34B ,  HSA-MIR-34C ,  HSA-MIR-627 ,  HSA-MIR-450A-2 ,  HSA-MIR-9-1 ,  ...

  • 3 miRs correlated to 'AGE'.

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

  • 61 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

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

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

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

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

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

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

    • HSA-MIR-140 ,  HSA-MIR-3607 ,  HSA-MIR-628 ,  HSA-MIR-361 ,  HSA-MIR-142 ,  ...

  • 18 miRs correlated to 'GENDER'.

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

  • 1 miR correlated to 'NUMBERPACKYEARSSMOKED'.

    • HSA-MIR-124-1

  • 70 miRs correlated to 'RACE'.

    • HSA-MIR-3605 ,  HSA-MIR-3607 ,  HSA-MIR-628 ,  HSA-MIR-215 ,  HSA-MIR-424 ,  ...

  • 1 miR correlated to 'ETHNICITY'.

    • HSA-MIR-219-2

  • No miRs correlated to 'KARNOFSKY.PERFORMANCE.SCORE'

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=8 shorter survival N=8 longer survival N=0
AGE Spearman correlation test N=3 older N=3 younger N=0
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=61        
PATHOLOGY T STAGE Spearman correlation test N=62 higher stage N=48 lower stage N=14
PATHOLOGY N STAGE Wilcoxon test N=3 class1 N=3 class0 N=0
PATHOLOGY M STAGE Kruskal-Wallis test N=108        
GENDER Wilcoxon test N=18 male N=18 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test N=1 higher numberpackyearssmoked N=1 lower numberpackyearssmoked N=0
RACE Kruskal-Wallis test N=70        
ETHNICITY Wilcoxon test N=1 not hispanic or latino N=1 hispanic or latino N=0
Clinical variable #1: 'Time to Death'

8 miRs related to 'Time to Death'.

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

Time to Death Duration (Years) 3-3668 (median=1307.5)
  censored N = 337
  death N = 23
     
  Significant markers N = 8
  associated with shorter survival 8
  associated with longer survival 0
List of 8 miRs differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of 8 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-34B 1.53 7.637e-07 0.00035 0.775
HSA-MIR-34C 1.45 2.942e-06 0.0014 0.688
HSA-MIR-627 2.2 7.657e-05 0.035 0.75
HSA-MIR-450A-2 2 0.0001405 0.064 0.699
HSA-MIR-9-1 1.28 0.0003089 0.14 0.669
HSA-MIR-450A-1 1.92 0.0004192 0.19 0.69
HSA-MIR-130B 2.3 0.0004361 0.2 0.65
HSA-MIR-9-2 1.28 0.0004434 0.2 0.655
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 0.1878 2.205e-05 0.0102
HSA-MIR-148A 0.1601 0.0003085 0.142
HSA-MIR-29B-2 0.1529 0.0005714 0.263
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

61 miRs related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 244
  STAGE II 55
  STAGE III 125
  STAGE IV 80
     
  Significant markers N = 61
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 2.048e-13 9.46e-11
HSA-MIR-486 3.193e-09 1.47e-06
HSA-MIR-625 5.28e-09 2.43e-06
HSA-MIR-155 6.924e-09 3.18e-06
HSA-MIR-21 1.95e-08 8.93e-06
HSA-LET-7I 2.794e-08 1.28e-05
HSA-MIR-130B 5e-08 2.28e-05
HSA-MIR-144 6.041e-08 2.75e-05
HSA-MIR-106B 1.865e-07 8.47e-05
HSA-MIR-142 3.519e-07 0.000159
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

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

PATHOLOGY.T.STAGE Mean (SD) 1.9 (0.96)
  N
  1 249
  2 67
  3 177
  4 11
     
  Significant markers N = 62
  pos. correlated 48
  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 -0.337 7.528e-15 3.48e-12
HSA-MIR-486 -0.276 2.925e-10 1.35e-07
HSA-MIR-155 0.2607 2.812e-09 1.29e-06
HSA-MIR-21 0.2595 3.383e-09 1.55e-06
HSA-MIR-625 0.2563 5.336e-09 2.44e-06
HSA-MIR-144 -0.2429 3.339e-08 1.53e-05
HSA-MIR-130B 0.2394 5.318e-08 2.43e-05
HSA-MIR-142 0.2342 1.044e-07 4.75e-05
HSA-MIR-9-1 0.2339 1.089e-07 4.94e-05
HSA-MIR-451 -0.2308 1.603e-07 7.26e-05
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 225
  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 0.0005291 0.244 0.7457
HSA-MIR-34C 2630 0.0005904 0.272 0.751
HSA-MIR-99B 1041 0.0006098 0.28 0.743
Clinical variable #6: 'PATHOLOGY.M.STAGE'

108 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 19
     
  Significant markers N = 108
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-140 1.959e-11 9.05e-09
HSA-MIR-3607 1.578e-10 7.28e-08
HSA-MIR-628 2.466e-10 1.13e-07
HSA-MIR-361 3.051e-10 1.4e-07
HSA-MIR-142 4.574e-10 2.09e-07
HSA-MIR-3647 7.342e-10 3.36e-07
HSA-MIR-26A-1 1.157e-09 5.28e-07
HSA-MIR-181A-1 4.054e-09 1.84e-06
HSA-MIR-3605 1.512e-08 6.86e-06
HSA-MIR-181B-1 2.214e-08 1e-05
Clinical variable #7: 'GENDER'

18 miRs related to 'GENDER'.

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

GENDER Labels N
  FEMALE 178
  MALE 326
     
  Significant markers N = 18
  Higher in MALE 18
  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 41336 3.151e-15 1.46e-12 0.7123
HSA-MIR-708 38913 2.385e-10 1.1e-07 0.6706
HSA-MIR-455 20972 2.662e-07 0.000122 0.6386
HSA-MIR-599 7689 5.713e-07 0.000262 0.6664
HSA-MIR-204 21171 6.552e-07 3e-04 0.634
HSA-MIR-155 36528 1.524e-06 0.000697 0.6295
HSA-MIR-31 30345 1.66e-06 0.000757 0.636
HSA-MIR-500B 22627 5.343e-05 0.0243 0.6089
HSA-MIR-500A 22838 7.756e-05 0.0352 0.6064
HSA-MIR-532 23192 0.0001951 0.0884 0.6003
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) 88.54 (22)
  Score N
  0 2
  70 1
  80 4
  90 16
  100 18
     
  Significant markers N = 0
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

One miR related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 27.17 (16)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one miR differentially expressed by 'NUMBERPACKYEARSSMOKED'

Table S17.  Get Full Table List of one miR significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-124-1 0.9856 0.0003091 0.141
Clinical variable #10: 'RACE'

70 miRs related to 'RACE'.

Table S18.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 8
  BLACK OR AFRICAN AMERICAN 44
  WHITE 445
     
  Significant markers N = 70
List of top 10 miRs differentially expressed by 'RACE'

Table S19.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-3605 8.808e-10 4.07e-07
HSA-MIR-3607 1.989e-09 9.17e-07
HSA-MIR-628 5.266e-08 2.42e-05
HSA-MIR-215 8.201e-08 3.76e-05
HSA-MIR-424 1.44e-07 6.6e-05
HSA-MIR-186 2.847e-07 0.00013
HSA-MIR-3648 2.84e-07 0.00013
HSA-MIR-142 3.176e-07 0.000144
HSA-MIR-26B 6.776e-07 0.000308
HSA-MIR-16-1 7.118e-07 0.000322
Clinical variable #11: 'ETHNICITY'

One miR related to 'ETHNICITY'.

Table S20.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 24
  NOT HISPANIC OR LATINO 333
     
  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 S21.  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", "0.0002062") c("117", "0.0002062") 0.0953 0.8917
Methods & Data
Input

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

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

  • Number of patients = 504

  • Number of miRs = 462

  • 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle