Correlation between miRseq expression and clinical features
Bladder Urothelial 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/C13F4NBB
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 571 miRs and 11 clinical features across 216 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

  • 14 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-99A ,  HSA-MIR-125B-2 ,  HSA-LET-7C ,  HSA-MIR-874 ,  HSA-MIR-100 ,  ...

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

    • HSA-MIR-99A ,  HSA-MIR-199B ,  HSA-MIR-199A-2 ,  HSA-MIR-199A-1 ,  HSA-MIR-1307 ,  ...

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

    • HSA-MIR-581 ,  HSA-MIR-100 ,  HSA-MIR-582 ,  HSA-MIR-545

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

    • HSA-MIR-151 ,  HSA-MIR-223 ,  HSA-MIR-21 ,  HSA-MIR-142 ,  HSA-MIR-199A-1 ,  ...

  • 6 miRs correlated to 'GENDER'.

    • HSA-MIR-152 ,  HSA-MIR-376C ,  HSA-MIR-134 ,  HSA-MIR-758 ,  HSA-MIR-487B ,  ...

  • 1 miR correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • HSA-MIR-1248

  • 2 miRs correlated to 'NUMBER.OF.LYMPH.NODES'.

    • HSA-MIR-545 ,  HSA-MIR-934

  • 57 miRs correlated to 'RACE'.

    • HSA-MIR-212 ,  HSA-MIR-30D ,  HSA-MIR-659 ,  HSA-MIR-134 ,  HSA-MIR-99A ,  ...

  • No miRs correlated to 'Time to Death', 'AGE', 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=0        
AGE Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=14        
PATHOLOGY T STAGE Spearman correlation test N=42 higher stage N=25 lower stage N=17
PATHOLOGY N STAGE Spearman correlation test N=4 higher stage N=1 lower stage N=3
PATHOLOGY M STAGE Kruskal-Wallis test N=13        
GENDER Wilcoxon test N=6 male N=6 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=1 higher score N=1 lower score N=0
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=2 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=1
RACE Kruskal-Wallis test N=57        
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 (Months) 0.1-140.8 (median=8.3)
  censored N = 151
  death N = 59
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No miR related to 'AGE'.

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

AGE Mean (SD) 67.57 (11)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

14 miRs related to 'NEOPLASM.DISEASESTAGE'.

Table S3.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE 0A 1
  STAGE I 2
  STAGE II 69
  STAGE III 72
  STAGE IV 68
     
  Significant markers N = 14
List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S4.  Get Full Table List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-99A 7.733e-06 0.00442
HSA-MIR-125B-2 1.111e-05 0.00633
HSA-LET-7C 2.394e-05 0.0136
HSA-MIR-874 8.566e-05 0.0487
HSA-MIR-100 0.0001143 0.0648
HSA-MIR-199A-2 0.000129 0.073
HSA-MIR-199B 0.0001635 0.0924
HSA-MIR-199A-1 0.0002059 0.116
HSA-MIR-1976 0.00027 0.152
HSA-MIR-125B-1 0.0003287 0.185
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.83 (0.71)
  N
  0 1
  1 1
  2 60
  3 102
  4 32
     
  Significant markers N = 42
  pos. correlated 25
  neg. correlated 17
List of top 10 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

Table S6.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-99A 0.3587 2.432e-07 0.000139
HSA-MIR-199B 0.3472 6.169e-07 0.000352
HSA-MIR-199A-2 0.3433 8.381e-07 0.000477
HSA-MIR-199A-1 0.3322 1.97e-06 0.00112
HSA-MIR-1307 -0.3279 2.706e-06 0.00153
HSA-MIR-125B-1 0.3252 3.318e-06 0.00188
HSA-MIR-200C -0.3212 4.438e-06 0.00251
HSA-MIR-381 0.3169 6.04e-06 0.00341
HSA-MIR-125B-2 0.318 7.78e-06 0.00438
HSA-MIR-100 0.3115 8.797e-06 0.00494
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.61 (0.92)
  N
  0 131
  1 22
  2 39
  3 7
     
  Significant markers N = 4
  pos. correlated 1
  neg. correlated 3
List of 4 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S8.  Get Full Table List of 4 miRs significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-581 -0.3191 0.0002711 0.155
HSA-MIR-100 0.2509 0.0003505 0.2
HSA-MIR-582 -0.2507 0.0003543 0.202
HSA-MIR-545 -0.2658 0.0004094 0.233
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 109
  M1 5
  MX 101
     
  Significant markers N = 13
List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-151 2.109e-05 0.012
HSA-MIR-223 3.312e-05 0.0189
HSA-MIR-21 3.84e-05 0.0218
HSA-MIR-142 8.128e-05 0.0462
HSA-MIR-199A-1 0.0001109 0.0629
HSA-MIR-199A-2 0.0001251 0.0708
HSA-MIR-330 0.0001512 0.0854
HSA-MIR-200C 0.0001555 0.0877
HSA-MIR-338 0.000159 0.0895
HSA-MIR-98 0.0001598 0.0898
Clinical variable #7: 'GENDER'

6 miRs related to 'GENDER'.

Table S11.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 50
  MALE 166
     
  Significant markers N = 6
  Higher in MALE 6
  Higher in FEMALE 0
List of 6 miRs differentially expressed by 'GENDER'

Table S12.  Get Full Table List of 6 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-152 2633 9.063e-05 0.0518 0.6828
HSA-MIR-376C 2764 0.0003486 0.199 0.667
HSA-MIR-134 2780 0.0004078 0.232 0.6651
HSA-MIR-758 2782 0.0004159 0.236 0.6648
HSA-MIR-487B 2709 0.0004861 0.276 0.6635
HSA-MIR-369 2784 0.0005041 0.285 0.6625
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

One miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S13.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 79.84 (15)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one miR differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S14.  Get Full Table List of one miR significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1248 0.4578 0.000302 0.172
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No miR related to 'NUMBERPACKYEARSSMOKED'.

Table S15.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 38.19 (28)
  Significant markers N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

2 miRs related to 'NUMBER.OF.LYMPH.NODES'.

Table S16.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.53 (3.2)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 miRs differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S17.  Get Full Table List of 2 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-545 -0.3225 0.0001079 0.0616
HSA-MIR-934 0.2863 0.0002652 0.151
Clinical variable #11: 'RACE'

57 miRs related to 'RACE'.

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

RACE Labels N
  ASIAN 22
  BLACK OR AFRICAN AMERICAN 12
  WHITE 169
     
  Significant markers N = 57
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-212 5.619e-09 3.21e-06
HSA-MIR-30D 3.13e-07 0.000178
HSA-MIR-659 1.521e-06 0.000865
HSA-MIR-134 1.887e-06 0.00107
HSA-MIR-99A 2.543e-06 0.00144
HSA-MIR-214 3.505e-06 0.00198
HSA-MIR-758 4.124e-06 0.00233
HSA-MIR-152 4.314e-06 0.00243
HSA-LET-7C 4.581e-06 0.00258
HSA-MIR-125B-2 4.975e-06 0.0028
Methods & Data
Input
  • Expresson data file = BLCA-TP.miRseq_RPKM_log2.txt

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

  • Number of patients = 216

  • Number of miRs = 571

  • 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)