Correlation between miRseq expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1445K9N
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/C1445K9N
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 593 miRs and 14 clinical features across 285 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one miRs.

  • 1 miR correlated to 'Time to Death'.

    • HSA-MIR-607

  • 2 miRs correlated to 'AGE'.

    • HSA-MIR-3200 ,  HSA-MIR-204

  • 41 miRs correlated to 'PRIMARY.SITE.OF.DISEASE'.

    • HSA-MIR-342 ,  HSA-MIR-150 ,  HSA-MIR-379 ,  HSA-MIR-217 ,  HSA-MIR-136 ,  ...

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

    • HSA-MIR-1537 ,  HSA-MIR-582

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

    • HSA-MIR-29A ,  HSA-MIR-135B

  • 1 miR correlated to 'MELANOMA.ULCERATION'.

    • HSA-MIR-2277

  • 2 miRs correlated to 'MELANOMA.PRIMARY.KNOWN'.

    • HSA-MIR-582 ,  HSA-MIR-181A-2

  • 4 miRs correlated to 'BRESLOW.THICKNESS'.

    • HSA-MIR-1537 ,  HSA-MIR-125B-1 ,  HSA-MIR-1243 ,  HSA-MIR-100

  • 1 miR correlated to 'GENDER'.

    • HSA-MIR-361

  • No miRs correlated to 'Time from Specimen Diagnosis to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.M.STAGE', 'RACE', 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 from Specimen Diagnosis to Death Cox regression test   N=0        
Time to Death Cox regression test N=1 shorter survival N=1 longer survival N=0
AGE Spearman correlation test N=2 older N=0 younger N=2
PRIMARY SITE OF DISEASE Kruskal-Wallis test N=41        
NEOPLASM DISEASESTAGE Kruskal-Wallis test   N=0        
PATHOLOGY T STAGE Spearman correlation test N=2 higher stage N=2 lower stage N=0
PATHOLOGY N STAGE Spearman correlation test N=2 higher stage N=2 lower stage N=0
PATHOLOGY M STAGE Kruskal-Wallis test   N=0        
MELANOMA ULCERATION Wilcoxon test N=1 yes N=1 no N=0
MELANOMA PRIMARY KNOWN Wilcoxon test N=2 yes N=2 no N=0
BRESLOW THICKNESS Spearman correlation test N=4 higher breslow.thickness N=2 lower breslow.thickness N=2
GENDER Wilcoxon test N=1 male N=1 female N=0
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time from Specimen Diagnosis to Death'

No miR related to 'Time from Specimen Diagnosis to Death'.

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

Time from Specimen Diagnosis to Death Duration (Months) 0-142.4 (median=14.6)
  censored N = 136
  death N = 136
     
  Significant markers N = 0
Clinical variable #2: 'Time to Death'

One miR related to 'Time to Death'.

Table S2.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.2-357.4 (median=47.5)
  censored N = 142
  death N = 137
     
  Significant markers N = 1
  associated with shorter survival 1
  associated with longer survival 0
List of one miR differentially expressed by 'Time to Death'

Table S3.  Get Full Table List of one miR significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-607 1.37 0.0003476 0.21 0.585
Clinical variable #3: 'AGE'

2 miRs related to 'AGE'.

Table S4.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 55.65 (15)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 miRs differentially expressed by 'AGE'

Table S5.  Get Full Table List of 2 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-3200 -0.2508 2.498e-05 0.0148
HSA-MIR-204 -0.224 0.0001617 0.0957
Clinical variable #4: 'PRIMARY.SITE.OF.DISEASE'

41 miRs related to 'PRIMARY.SITE.OF.DISEASE'.

Table S6.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  DISTANT METASTASIS 41
  PRIMARY TUMOR 4
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE 60
  REGIONAL LYMPH NODE 179
     
  Significant markers N = 41
List of top 10 miRs differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S7.  Get Full Table List of top 10 miRs differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

ANOVA_P Q
HSA-MIR-342 7.301e-09 4.33e-06
HSA-MIR-150 1.018e-07 6.02e-05
HSA-MIR-379 1.88e-07 0.000111
HSA-MIR-217 4.272e-07 0.000252
HSA-MIR-136 1.559e-06 0.000918
HSA-MIR-410 1.741e-06 0.00102
HSA-MIR-654 2.119e-06 0.00124
HSA-MIR-134 2.35e-06 0.00138
HSA-MIR-382 3.423e-06 0.002
HSA-MIR-127 3.585e-06 0.00209
Clinical variable #5: 'NEOPLASM.DISEASESTAGE'

No miR related to 'NEOPLASM.DISEASESTAGE'.

Table S8.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 10
  STAGE 0 6
  STAGE I 22
  STAGE IA 11
  STAGE IB 25
  STAGE II 16
  STAGE IIA 9
  STAGE IIB 15
  STAGE IIC 10
  STAGE III 30
  STAGE IIIA 13
  STAGE IIIB 26
  STAGE IIIC 50
  STAGE IV 13
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.T.STAGE'

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

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.42 (1.3)
  N
  0 22
  1 30
  2 61
  3 57
  4 56
     
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 miRs differentially expressed by 'PATHOLOGY.T.STAGE'

Table S10.  Get Full Table List of 2 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1537 0.3013 3.582e-05 0.0212
HSA-MIR-582 0.2536 0.0001158 0.0686
Clinical variable #7: 'PATHOLOGY.N.STAGE'

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.88 (1.1)
  N
  0 142
  1 51
  2 34
  3 38
     
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S12.  Get Full Table List of 2 miRs significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-29A 0.2226 0.0002594 0.154
HSA-MIR-135B 0.2186 0.0004255 0.252
Clinical variable #8: 'PATHOLOGY.M.STAGE'

No miR related to 'PATHOLOGY.M.STAGE'.

Table S13.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 254
  M1 4
  M1A 2
  M1B 3
  M1C 5
     
  Significant markers N = 0
Clinical variable #9: 'MELANOMA.ULCERATION'

One miR related to 'MELANOMA.ULCERATION'.

Table S14.  Basic characteristics of clinical feature: 'MELANOMA.ULCERATION'

MELANOMA.ULCERATION Labels N
  NO 104
  YES 74
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one miR differentially expressed by 'MELANOMA.ULCERATION'

Table S15.  Get Full Table List of one miR differentially expressed by 'MELANOMA.ULCERATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-2277 4639 0.0003124 0.185 0.6627
Clinical variable #10: 'MELANOMA.PRIMARY.KNOWN'

2 miRs related to 'MELANOMA.PRIMARY.KNOWN'.

Table S16.  Basic characteristics of clinical feature: 'MELANOMA.PRIMARY.KNOWN'

MELANOMA.PRIMARY.KNOWN Labels N
  NO 36
  YES 249
     
  Significant markers N = 2
  Higher in YES 2
  Higher in NO 0
List of 2 miRs differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

Table S17.  Get Full Table List of 2 miRs differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-582 6186 0.0002282 0.135 0.6901
HSA-MIR-181A-2 6126 0.000377 0.223 0.6834
Clinical variable #11: 'BRESLOW.THICKNESS'

4 miRs related to 'BRESLOW.THICKNESS'.

Table S18.  Basic characteristics of clinical feature: 'BRESLOW.THICKNESS'

BRESLOW.THICKNESS Mean (SD) 3.61 (5.1)
  Significant markers N = 4
  pos. correlated 2
  neg. correlated 2
List of 4 miRs differentially expressed by 'BRESLOW.THICKNESS'

Table S19.  Get Full Table List of 4 miRs significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1537 0.3781 4.003e-07 0.000237
HSA-MIR-125B-1 -0.252 0.000249 0.147
HSA-MIR-1243 0.2845 0.000254 0.15
HSA-MIR-100 -0.2432 0.0004138 0.244
Clinical variable #12: 'GENDER'

One miR related to 'GENDER'.

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

GENDER Labels N
  FEMALE 105
  MALE 180
     
  Significant markers N = 1
  Higher in MALE 1
  Higher in FEMALE 0
List of one miR differentially expressed by 'GENDER'

Table S21.  Get Full Table List of one miR 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-361 6520 1.272e-05 0.00754 0.655
Clinical variable #13: 'RACE'

No miR related to 'RACE'.

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

RACE Labels N
  ASIAN 5
  BLACK OR AFRICAN AMERICAN 1
  WHITE 277
     
  Significant markers N = 0
Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S23.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 275
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = SKCM-TM.miRseq_RPKM_log2.txt

  • Clinical data file = SKCM-TM.merged_data.txt

  • Number of patients = 285

  • Number of miRs = 593

  • Number of clinical features = 14

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