Correlation between miRseq expression and clinical features
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
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/C10P0XSF
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 482 miRs and 11 clinical features across 202 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

  • 18 miRs correlated to 'AGE'.

    • HSA-MIR-34A ,  HSA-MIR-486 ,  HSA-MIR-451 ,  HSA-MIR-1468 ,  HSA-MIR-1976 ,  ...

  • 51 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-224 ,  HSA-MIR-452 ,  HSA-MIR-217 ,  HSA-MIR-200B ,  HSA-MIR-200A ,  ...

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

    • HSA-MIR-452 ,  HSA-MIR-200B ,  HSA-MIR-224 ,  HSA-MIR-217 ,  HSA-MIR-216A ,  ...

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

    • HSA-MIR-224 ,  HSA-MIR-34A ,  HSA-MIR-589 ,  HSA-MIR-660 ,  HSA-MIR-141

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

    • HSA-LET-7E ,  HSA-LET-7F-2 ,  HSA-MIR-143 ,  HSA-MIR-452 ,  HSA-MIR-151 ,  ...

  • 3 miRs correlated to 'GENDER'.

    • HSA-MIR-625 ,  HSA-MIR-1276 ,  HSA-MIR-196A-2

  • 2 miRs correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • HSA-MIR-875 ,  HSA-MIR-508

  • 1 miR correlated to 'RACE'.

    • HSA-MIR-1304

  • No miRs correlated to 'Time to Death', 'NUMBERPACKYEARSSMOKED', 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=0        
AGE Spearman correlation test N=18 older N=18 younger N=0
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=51        
PATHOLOGY T STAGE Spearman correlation test N=37 higher stage N=33 lower stage N=4
PATHOLOGY N STAGE Spearman correlation test N=5 higher stage N=2 lower stage N=3
PATHOLOGY M STAGE Kruskal-Wallis test N=12        
GENDER Wilcoxon test N=3 male N=3 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=2 higher score N=1 lower score N=1
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
RACE Kruskal-Wallis test N=1        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

No miR related to 'Time to Death'.

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

Time to Death Duration (Years) 2-5925 (median=494)
  censored N = 170
  death N = 7
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

18 miRs related to 'AGE'.

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

AGE Mean (SD) 60.12 (12)
  Significant markers N = 18
  pos. correlated 18
  neg. correlated 0
List of top 10 miRs differentially expressed by 'AGE'

Table S3.  Get Full Table List of top 10 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-34A 0.3365 1.178e-06 0.000568
HSA-MIR-486 0.325 2.829e-06 0.00136
HSA-MIR-451 0.3204 4.699e-06 0.00226
HSA-MIR-1468 0.3126 6.941e-06 0.00332
HSA-MIR-1976 0.2909 3.076e-05 0.0147
HSA-MIR-144 0.2903 3.187e-05 0.0152
HSA-MIR-204 0.2881 3.68e-05 0.0175
HSA-MIR-362 0.2657 0.000149 0.0708
HSA-MIR-30E 0.2607 0.0001995 0.0946
HSA-MIR-197 0.2528 0.0003147 0.149
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

51 miRs related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 124
  STAGE II 12
  STAGE III 43
  STAGE IV 12
     
  Significant markers N = 51
List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S5.  Get Full Table List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-224 4.518e-10 2.18e-07
HSA-MIR-452 5.773e-10 2.78e-07
HSA-MIR-217 4.351e-08 2.09e-05
HSA-MIR-200B 5.231e-08 2.51e-05
HSA-MIR-200A 9.553e-07 0.000457
HSA-MIR-126 2.949e-06 0.00141
HSA-MIR-216A 3.763e-06 0.00179
HSA-MIR-429 4.135e-06 0.00196
HSA-MIR-143 4.777e-06 0.00226
HSA-MIR-320B-2 5.524e-06 0.00261
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.61 (0.89)
  N
  1 132
  2 19
  3 49
  4 2
     
  Significant markers N = 37
  pos. correlated 33
  neg. correlated 4
List of top 10 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

Table S7.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-452 0.3976 4.657e-09 2.24e-06
HSA-MIR-200B -0.3864 1.344e-08 6.46e-06
HSA-MIR-224 0.385 1.666e-08 8e-06
HSA-MIR-217 0.3791 3.371e-08 1.61e-05
HSA-MIR-216A 0.5063 7.707e-08 3.68e-05
HSA-MIR-200A -0.3577 1.723e-07 8.22e-05
HSA-MIR-429 -0.3445 5.141e-07 0.000245
HSA-MIR-153-2 0.3198 3.915e-06 0.00186
HSA-MIR-143 0.3163 4.536e-06 0.00215
HSA-MIR-320D-1 0.4272 5.502e-06 0.0026
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.48 (0.63)
  N
  0 34
  1 20
  2 4
     
  Significant markers N = 5
  pos. correlated 2
  neg. correlated 3
List of 5 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S9.  Get Full Table List of 5 miRs significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-224 0.5073 4.828e-05 0.0233
HSA-MIR-34A -0.4926 8.556e-05 0.0412
HSA-MIR-589 -0.4803 0.0001357 0.0651
HSA-MIR-660 -0.4585 0.0002953 0.141
HSA-MIR-141 0.4394 0.0005588 0.267
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 84
  M1 8
  MX 97
     
  Significant markers N = 12
List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-LET-7E 1.13e-05 0.00545
HSA-LET-7F-2 1.372e-05 0.0066
HSA-MIR-143 2.086e-05 0.01
HSA-MIR-452 8.3e-05 0.0398
HSA-MIR-151 9.645e-05 0.0461
HSA-MIR-100 0.0001241 0.0592
HSA-MIR-33A 0.0001327 0.0632
HSA-MIR-424 0.0001871 0.0889
HSA-MIR-200C 0.0003314 0.157
HSA-MIR-224 0.0004407 0.208
Clinical variable #7: 'GENDER'

3 miRs related to 'GENDER'.

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

GENDER Labels N
  FEMALE 59
  MALE 143
     
  Significant markers N = 3
  Higher in MALE 3
  Higher in FEMALE 0
List of 3 miRs differentially expressed by 'GENDER'

Table S13.  Get Full Table List of 3 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-625 6015 1.995e-06 0.000961 0.7129
HSA-MIR-1276 762 0.0003744 0.18 0.772
HSA-MIR-196A-2 5562 0.0003782 0.182 0.6592
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

2 miRs related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S14.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 91.48 (16)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 miRs differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S15.  Get Full Table List of 2 miRs significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-875 0.6478 0.0004636 0.223
HSA-MIR-508 -0.4533 0.0005774 0.278
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No miR related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 28.86 (34)
  Significant markers N = 0
Clinical variable #10: 'RACE'

One miR related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 2
  ASIAN 5
  BLACK OR AFRICAN AMERICAN 49
  WHITE 132
     
  Significant markers N = 1
List of one miR differentially expressed by 'RACE'

Table S18.  Get Full Table List of one miR differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-1304 9.207e-05 0.0444
Clinical variable #11: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 9
  NOT HISPANIC OR LATINO 157
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = KIRP-TP.miRseq_RPKM_log2.txt

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

  • Number of patients = 202

  • Number of miRs = 482

  • 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)