Correlation between miRseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1SF2V0S
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/C1SF2V0S
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 500 miRs and 12 clinical features across 1023 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one miRs.

  • 4 miRs correlated to 'Time to Death'.

    • HSA-MIR-874 ,  HSA-MIR-30A ,  HSA-MIR-101-1 ,  HSA-MIR-1307

  • 58 miRs correlated to 'AGE'.

    • HSA-MIR-31 ,  HSA-MIR-424 ,  HSA-MIR-99A ,  HSA-MIR-381 ,  HSA-MIR-598 ,  ...

  • 22 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-210 ,  HSA-MIR-374C ,  HSA-MIR-1247 ,  HSA-MIR-196B ,  HSA-MIR-455 ,  ...

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

    • HSA-MIR-758 ,  HSA-MIR-127 ,  HSA-MIR-409 ,  HSA-MIR-382 ,  HSA-MIR-150 ,  ...

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

    • HSA-MIR-10A ,  HSA-MIR-92A-2 ,  HSA-MIR-3613 ,  HSA-MIR-455 ,  HSA-MIR-577 ,  ...

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

    • HSA-MIR-16-1 ,  HSA-MIR-628 ,  HSA-MIR-3607 ,  HSA-MIR-26A-1 ,  HSA-MIR-424 ,  ...

  • 408 miRs correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-210 ,  HSA-MIR-1306 ,  HSA-MIR-301A ,  HSA-MIR-130B ,  HSA-MIR-197 ,  ...

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

    • HSA-MIR-3605 ,  HSA-MIR-3607 ,  HSA-MIR-1271 ,  HSA-MIR-3647 ,  HSA-MIR-628 ,  ...

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

    • HSA-MIR-577 ,  HSA-MIR-10A ,  HSA-MIR-221 ,  HSA-MIR-222 ,  HSA-MIR-3613 ,  ...

  • 122 miRs correlated to 'RACE'.

    • HSA-MIR-660 ,  HSA-MIR-20A ,  HSA-MIR-93 ,  HSA-MIR-1304 ,  HSA-MIR-103-1 ,  ...

  • No miRs correlated to 'GENDER', 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=4 shorter survival N=2 longer survival N=2
AGE Spearman correlation test N=58 older N=9 younger N=49
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=22        
PATHOLOGY T STAGE Spearman correlation test N=7 higher stage N=1 lower stage N=6
PATHOLOGY N STAGE Spearman correlation test N=10 higher stage N=1 lower stage N=9
PATHOLOGY M STAGE Kruskal-Wallis test N=146        
GENDER Wilcoxon test   N=0        
HISTOLOGICAL TYPE Kruskal-Wallis test N=408        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test N=59 yes N=59 no N=0
NUMBER OF LYMPH NODES Spearman correlation test N=16 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=15
RACE Kruskal-Wallis test N=122        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

4 miRs related to 'Time to Death'.

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

Time to Death Duration (Months) 0-234.3 (median=22.3)
  censored N = 884
  death N = 119
     
  Significant markers N = 4
  associated with shorter survival 2
  associated with longer survival 2
List of 4 miRs differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of 4 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-874 1.48 2.02e-05 0.01 0.585
HSA-MIR-30A 0.79 0.0002385 0.12 0.379
HSA-MIR-101-1 0.68 0.0003963 0.2 0.349
HSA-MIR-1307 1.32 0.0004248 0.21 0.614
Clinical variable #2: 'AGE'

58 miRs related to 'AGE'.

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

AGE Mean (SD) 58.62 (13)
  Significant markers N = 58
  pos. correlated 9
  neg. correlated 49
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-31 -0.2182 6.48e-12 3.24e-09
HSA-MIR-424 -0.2102 1.516e-11 7.57e-09
HSA-MIR-99A -0.2077 2.661e-11 1.33e-08
HSA-MIR-381 -0.2041 6.05e-11 3.01e-08
HSA-MIR-598 -0.1944 4.653e-10 2.31e-07
HSA-LET-7C -0.1827 4.951e-09 2.45e-06
HSA-MIR-652 -0.1823 5.503e-09 2.72e-06
HSA-MIR-542 -0.1735 2.893e-08 1.43e-05
HSA-MIR-125B-1 -0.1626 2.032e-07 1e-04
HSA-MIR-375 0.1594 3.557e-07 0.000175
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

22 miRs related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 83
  STAGE IA 82
  STAGE IB 10
  STAGE II 5
  STAGE IIA 342
  STAGE IIB 233
  STAGE III 2
  STAGE IIIA 140
  STAGE IIIB 28
  STAGE IIIC 62
  STAGE IV 17
  STAGE TIS 1
  STAGE X 17
     
  Significant markers N = 22
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-210 1.515e-06 0.000758
HSA-MIR-374C 8.077e-06 0.00403
HSA-MIR-1247 2.616e-05 0.013
HSA-MIR-196B 2.94e-05 0.0146
HSA-MIR-455 3.077e-05 0.0153
HSA-MIR-222 3.962e-05 0.0196
HSA-MIR-301A 9.774e-05 0.0483
HSA-MIR-130B 9.983e-05 0.0492
HSA-MIR-874 0.0001858 0.0914
HSA-MIR-1271 0.0001867 0.0917
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

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

PATHOLOGY.T.STAGE Mean (SD) 1.93 (0.73)
  N
  1 270
  2 589
  3 122
  4 39
     
  Significant markers N = 7
  pos. correlated 1
  neg. correlated 6
List of 7 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

Table S8.  Get Full Table List of 7 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-758 -0.1435 4.35e-06 0.00217
HSA-MIR-127 -0.1204 0.0001153 0.0575
HSA-MIR-409 -0.1153 0.0002247 0.112
HSA-MIR-382 -0.1118 0.0003509 0.174
HSA-MIR-150 -0.1105 0.0004086 0.203
HSA-MIR-9-2 0.1085 0.0005169 0.256
HSA-MIR-431 -0.1077 0.0005953 0.294
Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.77 (0.91)
  N
  0 483
  1 338
  2 111
  3 72
     
  Significant markers N = 10
  pos. correlated 1
  neg. correlated 9
List of 10 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S10.  Get Full Table List of 10 miRs significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-10A 0.1523 1.241e-06 0.000621
HSA-MIR-92A-2 -0.1247 7.478e-05 0.0373
HSA-MIR-3613 -0.1246 7.521e-05 0.0375
HSA-MIR-455 -0.1237 8.455e-05 0.042
HSA-MIR-577 -0.1392 8.748e-05 0.0434
HSA-MIR-17 -0.1118 0.0003864 0.191
HSA-MIR-30E -0.1096 0.0005056 0.25
HSA-MIR-92A-1 -0.1094 0.0005152 0.254
HSA-MIR-19B-2 -0.1089 0.000546 0.269
HSA-MIR-19B-1 -0.1087 0.0005887 0.289
Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 5
  M0 852
  M1 18
  MX 148
     
  Significant markers N = 146
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-16-1 1.847e-14 9.24e-12
HSA-MIR-628 2.564e-13 1.28e-10
HSA-MIR-3607 2.686e-10 1.34e-07
HSA-MIR-26A-1 6.488e-10 3.22e-07
HSA-MIR-424 7.043e-10 3.49e-07
HSA-MIR-550A-2 1.127e-09 5.58e-07
HSA-MIR-23B 2.795e-09 1.38e-06
HSA-MIR-3647 3.724e-09 1.84e-06
HSA-MIR-3170 5.767e-09 2.84e-06
HSA-MIR-345 8.684e-09 4.26e-06
Clinical variable #7: 'GENDER'

No miR related to 'GENDER'.

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

GENDER Labels N
  FEMALE 1012
  MALE 11
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL.TYPE'

408 miRs related to 'HISTOLOGICAL.TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 754
  INFILTRATING LOBULAR CARCINOMA 174
  MEDULLARY CARCINOMA 6
  MIXED HISTOLOGY (PLEASE SPECIFY) 28
  MUCINOUS CARCINOMA 15
  OTHER SPECIFY 44
     
  Significant markers N = 408
List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

Table S15.  Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-210 4.509e-42 2.25e-39
HSA-MIR-1306 1.905e-35 9.51e-33
HSA-MIR-301A 1.904e-34 9.48e-32
HSA-MIR-130B 7.836e-34 3.89e-31
HSA-MIR-197 1.318e-33 6.54e-31
HSA-MIR-328 2.453e-33 1.21e-30
HSA-MIR-616 2.499e-33 1.23e-30
HSA-MIR-186 1.628e-32 8.02e-30
HSA-MIR-301B 1.626e-32 8.02e-30
HSA-MIR-505 3.296e-32 1.62e-29
Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S16.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 278
  YES 745
     
  Significant markers N = 59
  Higher in YES 59
  Higher in NO 0
List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  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-3605 71211 1.56e-11 7.8e-09 0.6387
HSA-MIR-3607 75614 3.007e-11 1.5e-08 0.6349
HSA-MIR-1271 76272 7.047e-08 3.51e-05 0.6111
HSA-MIR-3647 81762 2.174e-07 0.000108 0.6052
HSA-MIR-628 81948 2.754e-07 0.000137 0.6043
HSA-MIR-940 75897 2.779e-07 0.000138 0.6063
HSA-MIR-101-2 124917 3.749e-07 0.000185 0.6031
HSA-MIR-551B 59691 7.109e-07 0.00035 0.6082
HSA-MIR-3677 82551 1.18e-06 0.000581 0.5987
HSA-MIR-545 51080.5 1.472e-06 0.000723 0.6086
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

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

Table S18.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.39 (4.7)
  Significant markers N = 16
  pos. correlated 1
  neg. correlated 15
List of top 10 miRs differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S19.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-577 -0.1639 1.633e-05 0.00817
HSA-MIR-10A 0.1389 4.103e-05 0.0205
HSA-MIR-221 -0.1333 8.286e-05 0.0413
HSA-MIR-222 -0.1316 0.0001029 0.0511
HSA-MIR-3613 -0.1292 0.0001374 0.0681
HSA-LET-7G -0.125 0.0002258 0.112
HSA-MIR-92A-2 -0.1248 0.0002327 0.115
HSA-MIR-197 -0.1245 0.0002407 0.119
HSA-MIR-505 -0.1222 0.000314 0.154
HSA-MIR-455 -0.122 0.0003197 0.157
Clinical variable #11: 'RACE'

122 miRs related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 57
  BLACK OR AFRICAN AMERICAN 159
  WHITE 718
     
  Significant markers N = 122
List of top 10 miRs differentially expressed by 'RACE'

Table S21.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-660 1.843e-21 9.21e-19
HSA-MIR-20A 1.971e-17 9.83e-15
HSA-MIR-93 4.437e-16 2.21e-13
HSA-MIR-1304 6.026e-15 3e-12
HSA-MIR-103-1 2.127e-14 1.06e-11
HSA-MIR-17 7.697e-14 3.81e-11
HSA-MIR-361 1.958e-13 9.67e-11
HSA-MIR-185 6.617e-13 3.26e-10
HSA-MIR-500B 3.308e-12 1.63e-09
HSA-MIR-26A-1 6.174e-12 3.03e-09
Clinical variable #12: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S22.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 36
  NOT HISPANIC OR LATINO 825
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 1023

  • Number of miRs = 500

  • Number of clinical features = 12

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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