Correlation between miRseq expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1PV6JN9
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1PV6JN9
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 590 miRs and 14 clinical features across 352 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

  • 22 miRs correlated to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-1976 ,  HSA-MIR-625 ,  HSA-MIR-100 ,  HSA-MIR-155 ,  HSA-MIR-125B-1 ,  ...

  • 30 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-551A ,  HSA-MIR-3680 ,  HSA-MIR-181A-2 ,  HSA-MIR-625 ,  HSA-MIR-3150B ,  ...

  • 6 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-3200 ,  HSA-MIR-204 ,  HSA-MIR-375 ,  HSA-MIR-497 ,  HSA-MIR-125B-1 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-1537 ,  HSA-MIR-582 ,  HSA-MIR-29B-2 ,  HSA-MIR-1262 ,  HSA-MIR-656 ,  ...

  • 6 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-338 ,  HSA-MIR-10A ,  HSA-MIR-3909 ,  HSA-MIR-29A ,  HSA-MIR-29B-1 ,  ...

  • 13 miRs correlated to 'MELANOMA_ULCERATION'.

    • HSA-MIR-2277 ,  HSA-MIR-191 ,  HSA-MIR-34A ,  HSA-LET-7E ,  HSA-MIR-301A ,  ...

  • 30 miRs correlated to 'BRESLOW_THICKNESS'.

    • HSA-MIR-1537 ,  HSA-MIR-1243 ,  HSA-MIR-100 ,  HSA-MIR-125B-1 ,  HSA-MIR-211 ,  ...

  • 11 miRs correlated to 'GENDER'.

    • HSA-MIR-361 ,  HSA-LET-7A-1 ,  HSA-LET-7A-2 ,  HSA-LET-7A-3 ,  HSA-MIR-10B ,  ...

  • No miRs correlated to 'PATHOLOGIC_STAGE', 'PATHOLOGY_M_STAGE', 'MELANOMA_PRIMARY_KNOWN', 'RADIATION_THERAPY', '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_DX_TO_DEATH_OR_LAST_FUP Cox regression test N=22 shorter survival N=5 longer survival N=17
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=20 longer survival N=10
YEARS_TO_BIRTH Spearman correlation test N=6 older N=1 younger N=5
PATHOLOGIC_STAGE Kruskal-Wallis test   N=0        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=20 lower stage N=10
PATHOLOGY_N_STAGE Spearman correlation test N=6 higher stage N=5 lower stage N=1
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
MELANOMA_ULCERATION Wilcoxon test N=13 yes N=13 no N=0
MELANOMA_PRIMARY_KNOWN Wilcoxon test   N=0        
BRESLOW_THICKNESS Spearman correlation test N=30 higher breslow_thickness N=24 lower breslow_thickness N=6
GENDER Wilcoxon test N=11 male N=11 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

22 miRs related to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP Duration (Months) 0-346.5 (median=47.1)
  censored N = 115
  death N = 123
     
  Significant markers N = 22
  associated with shorter survival 5
  associated with longer survival 17
List of top 10 miRs differentially expressed by 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 miRs significantly associated with 'Time from Specimen Diagnosis to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-1976 0.74 0.0003088 0.13 0.406
HSA-MIR-625 0.74 0.0004779 0.13 0.409
HSA-MIR-100 0.84 0.000644 0.13 0.397
HSA-MIR-155 0.86 0.001431 0.2 0.403
HSA-MIR-125B-1 0.82 0.001729 0.2 0.411
HSA-MIR-3131 1.35 0.002123 0.21 0.588
HSA-MIR-3200 0.86 0.002847 0.23 0.44
HSA-MIR-505 0.76 0.003112 0.23 0.423
HSA-MIR-3605 0.78 0.00376 0.25 0.445
HSA-MIR-374A 1.26 0.004255 0.25 0.557
Clinical variable #2: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 miRs related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

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

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.2-369.9 (median=52.3)
  censored N = 167
  death N = 184
     
  Significant markers N = 30
  associated with shorter survival 20
  associated with longer survival 10
List of top 10 miRs differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S4.  Get Full Table List of top 10 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-551A 1.23 2.99e-05 0.018 0.619
HSA-MIR-3680 1.26 0.0001279 0.037 0.59
HSA-MIR-181A-2 1.28 0.0001886 0.037 0.581
HSA-MIR-625 0.79 0.0003751 0.039 0.413
HSA-MIR-3150B 1.19 0.0004004 0.039 0.577
HSA-MIR-100 0.86 0.0004342 0.039 0.411
HSA-MIR-29C 0.84 0.0005591 0.039 0.418
HSA-MIR-3170 1.2 0.0005679 0.039 0.577
HSA-MIR-144 1.13 0.0005894 0.039 0.585
HSA-MIR-607 1.3 0.0006825 0.04 0.581
Clinical variable #3: 'YEARS_TO_BIRTH'

6 miRs related to 'YEARS_TO_BIRTH'.

Table S5.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 56.39 (16)
  Significant markers N = 6
  pos. correlated 1
  neg. correlated 5
List of 6 miRs differentially expressed by 'YEARS_TO_BIRTH'

Table S6.  Get Full Table List of 6 miRs significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-3200 -0.2405 7.542e-06 0.00445
HSA-MIR-204 -0.2226 3.281e-05 0.00968
HSA-MIR-375 0.1788 0.0008813 0.146
HSA-MIR-497 -0.1775 0.0009931 0.146
HSA-MIR-125B-1 -0.1714 0.001415 0.167
HSA-MIR-335 -0.1608 0.002788 0.274
Clinical variable #4: 'PATHOLOGIC_STAGE'

No miR related to 'PATHOLOGIC_STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE Labels N
  I OR II NOS 13
  STAGE 0 7
  STAGE I 28
  STAGE IA 16
  STAGE IB 28
  STAGE II 24
  STAGE IIA 12
  STAGE IIB 18
  STAGE IIC 14
  STAGE III 38
  STAGE IIIA 14
  STAGE IIIB 31
  STAGE IIIC 55
  STAGE IV 20
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY_T_STAGE'

30 miRs related to 'PATHOLOGY_T_STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.45 (1.2)
  N
  T0 23
  T1 37
  T2 73
  T3 74
  T4 66
     
  Significant markers N = 30
  pos. correlated 20
  neg. correlated 10
List of top 10 miRs differentially expressed by 'PATHOLOGY_T_STAGE'

Table S9.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1537 0.2649 8.442e-05 0.0498
HSA-MIR-582 0.2163 0.0003182 0.0834
HSA-MIR-29B-2 -0.204 0.0006952 0.0834
HSA-MIR-1262 0.207 0.0006961 0.0834
HSA-MIR-656 0.2974 0.0007568 0.0834
HSA-MIR-155 -0.2008 0.0008485 0.0834
HSA-MIR-1243 0.2178 0.001274 0.0851
HSA-MIR-29C -0.1938 0.00129 0.0851
HSA-MIR-29B-1 -0.1937 0.001298 0.0851
HSA-MIR-380 0.2361 0.00182 0.0967
Clinical variable #6: 'PATHOLOGY_N_STAGE'

6 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.86 (1.1)
  N
  N0 170
  N1 62
  N2 39
  N3 43
     
  Significant markers N = 6
  pos. correlated 5
  neg. correlated 1
List of 6 miRs differentially expressed by 'PATHOLOGY_N_STAGE'

Table S11.  Get Full Table List of 6 miRs significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-338 0.2086 0.0001965 0.116
HSA-MIR-10A -0.1976 0.0004267 0.126
HSA-MIR-3909 0.183 0.001718 0.294
HSA-MIR-29A 0.1738 0.001992 0.294
HSA-MIR-29B-1 0.1689 0.002669 0.294
HSA-MIR-365-1 0.167 0.00299 0.294
Clinical variable #7: 'PATHOLOGY_M_STAGE'

No miR related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 307
  class1 21
     
  Significant markers N = 0
Clinical variable #8: 'MELANOMA_ULCERATION'

13 miRs related to 'MELANOMA_ULCERATION'.

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

MELANOMA_ULCERATION Labels N
  NO 127
  YES 87
     
  Significant markers N = 13
  Higher in YES 13
  Higher in NO 0
List of top 10 miRs differentially expressed by 'MELANOMA_ULCERATION'

Table S14.  Get Full Table List of top 10 miRs differentially expressed by 'MELANOMA_ULCERATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-2277 6464 0.0006406 0.178 0.6409
HSA-MIR-191 6993 0.0009689 0.178 0.6329
HSA-MIR-34A 6924 0.001665 0.178 0.6267
HSA-LET-7E 4127 0.00169 0.178 0.6265
HSA-MIR-301A 6708 0.001875 0.178 0.6263
HSA-MIR-2276 3575 0.002459 0.178 0.6448
HSA-MIR-449A 1523 0.002491 0.178 0.6811
HSA-MIR-590 6712 0.002684 0.178 0.6218
HSA-MIR-3170 6536 0.00271 0.178 0.6225
HSA-LET-7A-2 4273 0.004928 0.269 0.6133
Clinical variable #9: 'MELANOMA_PRIMARY_KNOWN'

No miR related to 'MELANOMA_PRIMARY_KNOWN'.

Table S15.  Basic characteristics of clinical feature: 'MELANOMA_PRIMARY_KNOWN'

MELANOMA_PRIMARY_KNOWN Labels N
  NO 45
  YES 307
     
  Significant markers N = 0
Clinical variable #10: 'BRESLOW_THICKNESS'

30 miRs related to 'BRESLOW_THICKNESS'.

Table S16.  Basic characteristics of clinical feature: 'BRESLOW_THICKNESS'

BRESLOW_THICKNESS Mean (SD) 3.44 (4.7)
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
List of top 10 miRs differentially expressed by 'BRESLOW_THICKNESS'

Table S17.  Get Full Table List of top 10 miRs significantly correlated to 'BRESLOW_THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1537 0.3267 2.079e-06 0.00123
HSA-MIR-1243 0.2739 9.053e-05 0.0267
HSA-MIR-100 -0.2333 0.0001754 0.0345
HSA-MIR-125B-1 -0.2262 0.0002786 0.0411
HSA-MIR-211 0.2146 0.0005745 0.0603
HSA-MIR-873 0.2292 0.0006134 0.0603
HSA-MIR-508 0.2062 0.0009479 0.0799
HSA-MIR-509-1 0.2027 0.001159 0.0855
HSA-MIR-510 0.2258 0.001462 0.0861
HSA-MIR-509-2 0.1981 0.001542 0.0861
Clinical variable #11: 'GENDER'

11 miRs related to 'GENDER'.

Table S18.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 131
  MALE 221
     
  Significant markers N = 11
  Higher in MALE 11
  Higher in FEMALE 0
List of top 10 miRs differentially expressed by 'GENDER'

Table S19.  Get Full Table List of top 10 miRs 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 10422 1.124e-05 0.00663 0.64
HSA-LET-7A-1 17775 0.0003505 0.0559 0.614
HSA-LET-7A-2 17762 0.0003698 0.0559 0.6135
HSA-LET-7A-3 17756 0.0003791 0.0559 0.6133
HSA-MIR-10B 11253 0.0004805 0.0567 0.6113
HSA-LET-7E 17260 0.002555 0.251 0.5962
HSA-LET-7F-2 17171 0.003497 0.266 0.5931
HSA-MIR-891A 11230 0.003627 0.266 0.5938
HSA-MIR-590 11645 0.004487 0.266 0.591
HSA-MIR-766 11758 0.004521 0.266 0.5907
Clinical variable #12: 'RADIATION_THERAPY'

No miR related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 307
  YES 43
     
  Significant markers N = 0
Clinical variable #13: 'RACE'

No miR related to 'RACE'.

Table S21.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 5
  BLACK OR AFRICAN AMERICAN 1
  WHITE 338
     
  Significant markers N = 0
Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 337
     
  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 = 352

  • Number of miRs = 590

  • Number of clinical features = 14

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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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