Correlation between miRseq expression and clinical features
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 genes and 10 clinical features across 946 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

  • 2 genes correlated to 'Time to Death'.

    • HSA-MIR-874 ,  HSA-MIR-328

  • 34 genes correlated to 'AGE'.

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

  • 22 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-210 ,  HSA-MIR-143 ,  HSA-LET-7F-2 ,  HSA-MIR-374C ,  HSA-MIR-3607 ,  ...

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

    • HSA-MIR-758

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

    • HSA-MIR-10A

  • 33 genes correlated to 'PATHOLOGY.M.STAGE'.

    • HSA-MIR-16-1 ,  HSA-MIR-2276 ,  HSA-MIR-628 ,  HSA-MIR-550A-2 ,  HSA-MIR-424 ,  ...

  • 359 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-210 ,  HSA-MIR-616 ,  HSA-MIR-1306 ,  HSA-MIR-301B ,  HSA-MIR-328 ,  ...

  • 2 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • HSA-MIR-3607 ,  HSA-MIR-3605

  • No genes correlated to 'GENDER', and 'NUMBER.OF.LYMPH.NODES'.

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 genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature Statistical test Significant genes 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=22        
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=33        
GENDER t test   N=0        
HISTOLOGICAL TYPE ANOVA test N=359        
RADIATIONS RADIATION REGIMENINDICATION t test N=2 yes N=0 no N=2
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
Clinical variable #1: 'Time to Death'

2 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-234.2 (median=21.6)
  censored N = 784
  death N = 108
     
  Significant markers N = 2
  associated with shorter survival 2
  associated with longer survival 0
List of 2 genes significantly associated with 'Time to Death' by Cox regression test

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

HazardRatio Wald_P Q C_index
HSA-MIR-874 1.52 1.558e-05 0.0078 0.594
HSA-MIR-328 1.42 2.587e-05 0.013 0.604

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 = 1.56e-05 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

34 genes related to 'AGE'.

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

AGE Mean (SD) 58.51 (13)
  Significant markers N = 34
  pos. correlated 6
  neg. correlated 28
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-424 -0.2187 1.125e-11 5.6e-09
HSA-MIR-31 -0.2022 8.316e-10 4.13e-07
HSA-MIR-99A -0.1964 1.172e-09 5.81e-07
HSA-MIR-598 -0.191 3.409e-09 1.69e-06
HSA-MIR-381 -0.1906 3.755e-09 1.86e-06
HSA-MIR-652 -0.1857 9.388e-09 4.63e-06
HSA-MIR-542 -0.172 1.068e-07 5.25e-05
HSA-LET-7C -0.1672 2.419e-07 0.000119
HSA-MIR-125B-1 -0.1564 1.387e-06 0.00068
HSA-MIR-202 -0.1923 1.746e-06 0.000854

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-424 to 'AGE'. P value = 1.12e-11 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

22 genes related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 77
  STAGE IA 72
  STAGE IB 11
  STAGE II 9
  STAGE IIA 321
  STAGE IIB 213
  STAGE III 2
  STAGE IIIA 131
  STAGE IIIB 25
  STAGE IIIC 52
  STAGE IV 14
  STAGE TIS 1
  STAGE X 17
     
  Significant markers N = 22
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-210 4.713e-12 2.35e-09
HSA-MIR-143 7.138e-09 3.55e-06
HSA-LET-7F-2 1.221e-07 6.05e-05
HSA-MIR-374C 5.134e-07 0.000254
HSA-MIR-3607 9.87e-07 0.000488
HSA-MIR-301A 1.003e-06 0.000494
HSA-MIR-3653 2.92e-06 0.00144
HSA-MIR-592 1.109e-05 0.00545
HSA-MIR-130B 1.213e-05 0.00594
HSA-MIR-200A 1.233e-05 0.00603

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-210 to 'NEOPLASM.DISEASESTAGE'. P value = 4.71e-12 with ANOVA analysis.

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

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

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

PATHOLOGY.T.STAGE Mean (SD) 1.92 (0.73)
  N
  1 252
  2 545
  3 111
  4 35
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-758 -0.1414 1.355e-05 0.00675

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-758 to 'PATHOLOGY.T.STAGE'. P value = 1.36e-05 with Spearman correlation analysis.

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

One gene 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
  0 447
  1 316
  2 106
  3 62
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-10A 0.1543 2.243e-06 0.00112

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-10A to 'PATHOLOGY.N.STAGE'. P value = 2.24e-06 with Spearman correlation analysis.

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

33 genes related to 'PATHOLOGY.M.STAGE'.

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

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 2
  M0 820
  M1 14
  MX 110
     
  Significant markers N = 33
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-16-1 2.268e-09 1.13e-06
HSA-MIR-2276 6.554e-09 3.26e-06
HSA-MIR-628 7.745e-08 3.84e-05
HSA-MIR-550A-2 1.257e-07 6.22e-05
HSA-MIR-424 9.656e-07 0.000477
HSA-MIR-374C 1.538e-06 0.000758
HSA-MIR-361 2e-06 0.000984
HSA-MIR-3174 2.641e-06 0.0013
HSA-MIR-345 2.847e-06 0.0014
HSA-MIR-23B 3.558e-06 0.00174

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 = 2.27e-09 with ANOVA analysis.

Clinical variable #7: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 936
  MALE 10
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL.TYPE'

359 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 705
  INFILTRATING LOBULAR CARCINOMA 150
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 27
  MUCINOUS CARCINOMA 14
  OTHER SPECIFY 43
     
  Significant markers N = 359
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

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

ANOVA_P Q
HSA-MIR-210 9.477e-52 4.72e-49
HSA-MIR-616 2.065e-37 1.03e-34
HSA-MIR-1306 2.411e-35 1.2e-32
HSA-MIR-301B 6.172e-35 3.05e-32
HSA-MIR-328 7.508e-33 3.71e-30
HSA-MIR-345 1.224e-32 6.03e-30
HSA-MIR-301A 1.593e-32 7.84e-30
HSA-MIR-324 3.686e-32 1.81e-29
HSA-MIR-130B 1.012e-31 4.96e-29
HSA-LET-7D 1.756e-31 8.59e-29

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-210 to 'HISTOLOGICAL.TYPE'. P value = 9.48e-52 with ANOVA analysis.

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

2 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 229
  YES 717
     
  Significant markers N = 2
  Higher in YES 0
  Higher in NO 2
List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  Get Full Table List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-3607 -5.29 1.961e-07 9.76e-05 0.6007
HSA-MIR-3605 -4.64 4.671e-06 0.00232 0.5836

Figure S8.  Get High-res Image As an example, this figure shows the association of HSA-MIR-3607 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.96e-07 with T-test analysis.

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

No gene related to 'NUMBER.OF.LYMPH.NODES'.

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

NUMBER.OF.LYMPH.NODES Mean (SD) 2.33 (4.6)
  Significant markers N = 0
Methods & Data
Input

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

  • Clinical data file = BRCA-TP.clin.merged.picked.txt

  • Number of patients = 946

  • Number of genes = 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.

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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