Correlation between miRseq expression and clinical features
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1DZ073P
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/C1DZ073P
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 554 miRs and 7 clinical features across 486 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one miRs.

  • 9 miRs correlated to 'Time to Death'.

    • HSA-MIR-34A ,  HSA-MIR-628 ,  HSA-LET-7G ,  HSA-MIR-497 ,  HSA-MIR-195 ,  ...

  • 72 miRs correlated to 'AGE'.

    • HSA-MIR-424 ,  HSA-MIR-1247 ,  HSA-MIR-34A ,  HSA-MIR-199A-1 ,  HSA-MIR-214 ,  ...

  • 127 miRs correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-9-3 ,  HSA-MIR-9-2 ,  HSA-MIR-9-1 ,  HSA-MIR-934 ,  HSA-MIR-34A ,  ...

  • 17 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • HSA-MIR-3613 ,  HSA-MIR-128-1 ,  HSA-MIR-628 ,  HSA-MIR-103-1 ,  HSA-MIR-181D ,  ...

  • 10 miRs correlated to 'RACE'.

    • HSA-MIR-1304 ,  HSA-MIR-3170 ,  HSA-MIR-23B ,  HSA-MIR-92A-1 ,  HSA-MIR-199B ,  ...

  • No miRs correlated to 'COMPLETENESS.OF.RESECTION', 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=9 shorter survival N=0 longer survival N=9
AGE Spearman correlation test N=72 older N=10 younger N=62
HISTOLOGICAL TYPE Kruskal-Wallis test N=127        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test N=17 yes N=17 no N=0
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test N=10        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

9 miRs related to 'Time to Death'.

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

Time to Death Duration (Months) 0-191.8 (median=22.8)
  censored N = 427
  death N = 57
     
  Significant markers N = 9
  associated with shorter survival 0
  associated with longer survival 9
List of 9 miRs differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of 9 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-34A 0.72 5.927e-05 0.033 0.364
HSA-MIR-628 0.69 6.711e-05 0.037 0.364
HSA-LET-7G 0.54 7.87e-05 0.043 0.348
HSA-MIR-497 0.71 0.0001358 0.075 0.357
HSA-MIR-195 0.74 0.00032 0.18 0.36
HSA-MIR-455 0.69 0.0003218 0.18 0.377
HSA-MIR-576 0.62 0.0003687 0.2 0.364
HSA-LET-7B 0.64 0.0004356 0.24 0.324
HSA-MIR-23C 0.68 0.0005251 0.29 0.356
Clinical variable #2: 'AGE'

72 miRs related to 'AGE'.

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

AGE Mean (SD) 63.64 (11)
  Significant markers N = 72
  pos. correlated 10
  neg. correlated 62
List of top 10 miRs differentially expressed by 'AGE'

Table S4.  Get Full Table List of top 10 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-424 -0.3186 6.691e-13 3.71e-10
HSA-MIR-1247 -0.2659 3.137e-09 1.73e-06
HSA-MIR-34A -0.2453 4.423e-08 2.44e-05
HSA-MIR-199A-1 -0.2359 1.479e-07 8.15e-05
HSA-MIR-214 -0.2359 1.512e-07 8.32e-05
HSA-MIR-935 0.2568 1.599e-07 8.78e-05
HSA-MIR-337 -0.2338 1.914e-07 0.000105
HSA-MIR-199A-2 -0.2307 2.799e-07 0.000153
HSA-MIR-516A-1 0.291 3.792e-07 0.000207
HSA-MIR-199B -0.2255 5.215e-07 0.000284
Clinical variable #3: 'HISTOLOGICAL.TYPE'

127 miRs related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA 372
  MIXED SEROUS AND ENDOMETRIOID 20
  SEROUS ENDOMETRIAL ADENOCARCINOMA 94
     
  Significant markers N = 127
List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

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

ANOVA_P Q
HSA-MIR-9-3 5.167e-29 2.86e-26
HSA-MIR-9-2 6.333e-27 3.5e-24
HSA-MIR-9-1 6.83e-27 3.77e-24
HSA-MIR-934 4.91e-22 2.71e-19
HSA-MIR-34A 8.198e-21 4.51e-18
HSA-MIR-375 1.427e-18 7.83e-16
HSA-MIR-221 7.168e-18 3.93e-15
HSA-MIR-452 2.883e-17 1.58e-14
HSA-MIR-548V 4.093e-17 2.23e-14
HSA-MIR-195 4.129e-17 2.25e-14
Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

17 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S7.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 134
  YES 352
     
  Significant markers N = 17
  Higher in YES 17
  Higher in NO 0
List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8.  Get Full Table List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-3613 16193 9.21e-08 5.1e-05 0.6567
HSA-MIR-128-1 29767 7.875e-06 0.00435 0.6311
HSA-MIR-628 17539 1.484e-05 0.00819 0.6271
HSA-MIR-103-1 29545 1.647e-05 0.00907 0.6264
HSA-MIR-181D 29518 1.798e-05 0.00989 0.6258
HSA-MIR-210 17882 3.774e-05 0.0207 0.6209
HSA-MIR-128-2 29217 4.681e-05 0.0257 0.6194
HSA-MIR-146A 18006 5.548e-05 0.0303 0.6183
HSA-MIR-361 29162 5.548e-05 0.0303 0.6183
HSA-MIR-3170 17342 5.807e-05 0.0316 0.6187
Clinical variable #5: 'COMPLETENESS.OF.RESECTION'

No miR related to 'COMPLETENESS.OF.RESECTION'.

Table S9.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 336
  R1 22
  R2 16
  RX 29
     
  Significant markers N = 0
Clinical variable #6: 'RACE'

10 miRs related to 'RACE'.

Table S10.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 4
  ASIAN 19
  BLACK OR AFRICAN AMERICAN 76
  NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 9
  WHITE 353
     
  Significant markers N = 10
List of 10 miRs differentially expressed by 'RACE'

Table S11.  Get Full Table List of 10 miRs differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-1304 1.154e-06 0.000639
HSA-MIR-3170 3.152e-05 0.0174
HSA-MIR-23B 5.408e-05 0.0298
HSA-MIR-92A-1 6.053e-05 0.0334
HSA-MIR-199B 0.0001018 0.056
HSA-MIR-361 0.0002137 0.117
HSA-MIR-145 0.0002472 0.135
HSA-MIR-455 0.0003077 0.168
HSA-MIR-199A-2 0.0003914 0.214
HSA-MIR-20A 0.0004043 0.22
Clinical variable #7: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 13
  NOT HISPANIC OR LATINO 339
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 486

  • Number of miRs = 554

  • Number of clinical features = 7

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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