Correlation between miRseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1765CXV
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/C1765CXV
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 498 miRs and 10 clinical features across 968 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one miRs.

  • 2 miRs correlated to 'Time to Death'.

    • HSA-MIR-874 ,  HSA-MIR-328

  • 34 miRs correlated to 'AGE'.

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

  • 31 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-210 ,  HSA-MIR-143 ,  HSA-LET-7F-2 ,  HSA-MIR-301A ,  HSA-MIR-3607 ,  ...

  • 1 miR correlated to 'PATHOLOGY.T.STAGE'.

    • HSA-MIR-758

  • 1 miR correlated to 'PATHOLOGY.N.STAGE'.

    • HSA-MIR-10A

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

    • HSA-MIR-16-1 ,  HSA-MIR-628 ,  HSA-MIR-2276 ,  HSA-MIR-550A-2 ,  HSA-MIR-361 ,  ...

  • 368 miRs correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-210 ,  HSA-MIR-616 ,  HSA-MIR-1306 ,  HSA-MIR-301B ,  HSA-MIR-301A ,  ...

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

    • HSA-MIR-3605 ,  HSA-MIR-3607 ,  HSA-MIR-1271 ,  HSA-MIR-3620 ,  HSA-MIR-3647 ,  ...

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

    • HSA-MIR-10A ,  HSA-MIR-577

  • No miRs correlated to 'GENDER'

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 Q value < 0.05.

Clinical feature Statistical test Significant miRs Associated with                 Associated with
Time to Death Cox regression test N=2 shorter survival N=2 longer survival N=0
AGE Spearman correlation test N=34 older N=6 younger N=28
NEOPLASM DISEASESTAGE ANOVA test N=31        
PATHOLOGY T STAGE Spearman correlation test N=1 higher stage N=0 lower stage N=1
PATHOLOGY N STAGE Spearman correlation test N=1 higher stage N=1 lower stage N=0
PATHOLOGY M STAGE ANOVA test N=47        
GENDER t test   N=0        
HISTOLOGICAL TYPE ANOVA test N=368        
RADIATIONS RADIATION REGIMENINDICATION t test N=21 yes N=1 no N=20
NUMBER OF LYMPH NODES Spearman correlation test N=2 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=1
Clinical variable #1: 'Time to Death'

2 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=21.5)
  censored N = 835
  death N = 112
     
  Significant markers N = 2
  associated with shorter survival 2
  associated with longer survival 0
List of 2 miRs significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 2 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-874 1.48 3.266e-05 0.016 0.583
HSA-MIR-328 1.37 8.455e-05 0.042 0.594

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-874 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 3.27e-05 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

34 miRs related to 'AGE'.

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

AGE Mean (SD) 58.64 (13)
  Significant markers N = 34
  pos. correlated 6
  neg. correlated 28
List of top 10 miRs significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-424 -0.2139 2.411e-11 1.2e-08
HSA-MIR-31 -0.2095 1.532e-10 7.61e-08
HSA-MIR-99A -0.2032 2.344e-10 1.16e-07
HSA-MIR-381 -0.1899 3.477e-09 1.72e-06
HSA-MIR-598 -0.186 6.992e-09 3.45e-06
HSA-MIR-652 -0.1791 2.543e-08 1.25e-05
HSA-LET-7C -0.1762 4.217e-08 2.07e-05
HSA-MIR-542 -0.172 8.93e-08 4.38e-05
HSA-MIR-125B-1 -0.1592 7.585e-07 0.000372
HSA-MIR-202 -0.1966 8.214e-07 0.000402

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-424 to 'AGE'. P value = 2.41e-11 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

31 miRs related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 77
  STAGE IA 76
  STAGE IB 10
  STAGE II 9
  STAGE IIA 327
  STAGE IIB 220
  STAGE III 2
  STAGE IIIA 133
  STAGE IIIB 26
  STAGE IIIC 55
  STAGE IV 14
  STAGE TIS 1
  STAGE X 17
     
  Significant markers N = 31
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 8.099e-13 4.03e-10
HSA-MIR-143 1.272e-08 6.32e-06
HSA-LET-7F-2 1.127e-07 5.59e-05
HSA-MIR-301A 2.502e-07 0.000124
HSA-MIR-3607 5.616e-07 0.000277
HSA-MIR-374C 6.567e-07 0.000324
HSA-MIR-592 1.807e-06 0.000889
HSA-MIR-130B 2.638e-06 0.0013
HSA-MIR-484 3.189e-06 0.00156
HSA-MIR-3653 3.326e-06 0.00163

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-210 to 'NEOPLASM.DISEASESTAGE'. P value = 8.1e-13 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

One miR related to 'PATHOLOGY.T.STAGE'.

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

PATHOLOGY.T.STAGE Mean (SD) 1.93 (0.72)
  N
  1 254
  2 562
  3 113
  4 36
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one miR significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-758 -0.1396 1.395e-05 0.00695

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-758 to 'PATHOLOGY.T.STAGE'. P value = 1.39e-05 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

One miR related to 'PATHOLOGY.N.STAGE'.

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

PATHOLOGY.N.STAGE Mean (SD) 0.77 (0.9)
  N
  0 457
  1 324
  2 106
  3 65
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one miR significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-10A 0.1525 2.277e-06 0.00113

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-10A to 'PATHOLOGY.N.STAGE'. P value = 2.28e-06 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 2
  M0 833
  M1 14
  MX 119
     
  Significant markers N = 47
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 1.618e-10 8.06e-08
HSA-MIR-628 1.835e-09 9.12e-07
HSA-MIR-2276 3.5e-08 1.74e-05
HSA-MIR-550A-2 6.437e-08 3.19e-05
HSA-MIR-361 9.76e-08 4.82e-05
HSA-MIR-345 2.53e-07 0.000125
HSA-MIR-374C 2.765e-07 0.000136
HSA-MIR-424 4.152e-07 0.000204
HSA-MIR-23B 5.958e-07 0.000292
HSA-MIR-3170 7.168e-07 0.000351

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-16-1 to 'PATHOLOGY.M.STAGE'. P value = 1.62e-10 with ANOVA analysis.

Clinical variable #7: 'GENDER'

No miR related to 'GENDER'.

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

GENDER Labels N
  FEMALE 958
  MALE 10
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL.TYPE'

368 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 718
  INFILTRATING LOBULAR CARCINOMA 157
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 28
  MUCINOUS CARCINOMA 14
  OTHER SPECIFY 44
     
  Significant markers N = 368
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 3.859e-54 1.92e-51
HSA-MIR-616 5.166e-38 2.57e-35
HSA-MIR-1306 1.061e-36 5.26e-34
HSA-MIR-301B 7.57e-35 3.75e-32
HSA-MIR-301A 1.952e-34 9.64e-32
HSA-MIR-324 2.029e-34 1e-31
HSA-MIR-328 5.034e-34 2.48e-31
HSA-LET-7D 2.44e-33 1.2e-30
HSA-MIR-345 2.828e-33 1.39e-30
HSA-MIR-197 2.313e-32 1.13e-29

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-210 to 'HISTOLOGICAL.TYPE'. P value = 3.86e-54 with ANOVA analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 278
  YES 690
     
  Significant markers N = 21
  Higher in YES 1
  Higher in NO 20
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'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-3605 -6.54 1.401e-10 6.98e-08 0.6175
HSA-MIR-3607 -5.98 3.861e-09 1.92e-06 0.6157
HSA-MIR-1271 -5.18 3.004e-07 0.000149 0.5963
HSA-MIR-3620 -4.88 2e-06 0.00099 0.6477
HSA-MIR-3647 -4.8 2.054e-06 0.00101 0.5859
HSA-MIR-940 -4.72 3.169e-06 0.00156 0.5964
HSA-MIR-3677 -4.61 5.001e-06 0.00246 0.586
HSA-MIR-628 -4.52 7.332e-06 0.0036 0.5788
HSA-MIR-551B -4.52 7.816e-06 0.00383 0.5943
HSA-MIR-545 -4.35 1.654e-05 0.00809 0.5899

Figure S8.  Get High-res Image As an example, this figure shows the association of HSA-MIR-3605 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.4e-10 with T-test analysis.

Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

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

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

NUMBER.OF.LYMPH.NODES Mean (SD) 2.32 (4.5)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S19.  Get Full Table List of 2 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-10A 0.1374 8.296e-05 0.0413
HSA-MIR-577 -0.1525 9.401e-05 0.0467

Figure S9.  Get High-res Image As an example, this figure shows the association of HSA-MIR-10A to 'NUMBER.OF.LYMPH.NODES'. P value = 8.3e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

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

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

  • Number of patients = 968

  • Number of miRs = 498

  • Number of clinical features = 10

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 © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle