Correlation between miRseq expression and clinical features
Liver Hepatocellular Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1PZ5821
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/C1PZ5821
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 544 miRs and 12 clinical features across 363 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one miRs.

  • 30 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-149 ,  HSA-MIR-632 ,  HSA-MIR-3677 ,  HSA-MIR-106A ,  HSA-MIR-210 ,  ...

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-1269 ,  HSA-MIR-412 ,  HSA-MIR-181D ,  HSA-MIR-200C ,  HSA-MIR-483 ,  ...

  • 19 miRs correlated to 'PATHOLOGIC_STAGE'.

    • HSA-MIR-23C ,  HSA-MIR-550A-1 ,  HSA-MIR-139 ,  HSA-MIR-7-2 ,  HSA-MIR-642A ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-23C ,  HSA-MIR-139 ,  HSA-MIR-550A-1 ,  HSA-MIR-122 ,  HSA-MIR-149 ,  ...

  • 30 miRs correlated to 'GENDER'.

    • HSA-MIR-331 ,  HSA-MIR-375 ,  HSA-MIR-26A-2 ,  HSA-MIR-1301 ,  HSA-MIR-106A ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-194-1 ,  HSA-MIR-194-2 ,  HSA-MIR-192 ,  HSA-MIR-10A ,  HSA-MIR-122 ,  ...

  • 30 miRs correlated to 'RACE'.

    • HSA-MIR-23C ,  HSA-MIR-3130-1 ,  HSA-MIR-532 ,  HSA-MIR-30D ,  HSA-MIR-1304 ,  ...

  • No miRs correlated to 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', 'RADIATION_THERAPY', 'RESIDUAL_TUMOR', 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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=27 longer survival N=3
YEARS_TO_BIRTH Spearman correlation test N=30 older N=5 younger N=25
PATHOLOGIC_STAGE Kruskal-Wallis test N=19        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=22 lower stage N=8
PATHOLOGY_N_STAGE Wilcoxon test   N=0        
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 miRs related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

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

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-120.8 (median=19.7)
  censored N = 235
  death N = 127
     
  Significant markers N = 30
  associated with shorter survival 27
  associated with longer survival 3
List of top 10 miRs differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  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-149 1.39 6.251e-08 3.4e-05 0.641
HSA-MIR-632 1.88 2.517e-07 6.8e-05 0.643
HSA-MIR-3677 1.44 5.77e-07 1e-04 0.655
HSA-MIR-106A 1.38 2.041e-06 0.00024 0.606
HSA-MIR-210 1.26 2.231e-06 0.00024 0.64
HSA-MIR-3680 1.54 3.724e-06 0.00034 0.624
HSA-MIR-489 1.51 5.331e-06 0.00041 0.65
HSA-MIR-23C 0.74 7.261e-06 0.00049 0.396
HSA-MIR-3682 1.42 1.41e-05 0.00079 0.634
HSA-MIR-9-1 1.17 1.586e-05 0.00079 0.62
Clinical variable #2: 'YEARS_TO_BIRTH'

30 miRs related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 59.54 (13)
  Significant markers N = 30
  pos. correlated 5
  neg. correlated 25
List of top 10 miRs differentially expressed by 'YEARS_TO_BIRTH'

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

SpearmanCorr corrP Q
HSA-MIR-1269 0.2601 6.465e-07 0.000352
HSA-MIR-412 -0.2239 2.492e-05 0.00346
HSA-MIR-181D -0.2195 2.654e-05 0.00346
HSA-MIR-200C -0.2185 2.896e-05 0.00346
HSA-MIR-483 -0.2186 3.184e-05 0.00346
HSA-MIR-181B-1 -0.2106 5.656e-05 0.00464
HSA-MIR-296 -0.2165 5.971e-05 0.00464
HSA-LET-7E -0.2055 8.579e-05 0.00583
HSA-MIR-181A-2 -0.2011 0.0001221 0.00738
HSA-MIR-98 -0.1965 0.000175 0.00891
Clinical variable #3: 'PATHOLOGIC_STAGE'

19 miRs related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 169
  STAGE II 84
  STAGE III 3
  STAGE IIIA 62
  STAGE IIIB 8
  STAGE IIIC 9
  STAGE IV 3
  STAGE IVA 1
  STAGE IVB 2
     
  Significant markers N = 19
List of top 10 miRs differentially expressed by 'PATHOLOGIC_STAGE'

Table S6.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
HSA-MIR-23C 8.559e-05 0.0466
HSA-MIR-550A-1 0.0002981 0.0552
HSA-MIR-139 0.0003629 0.0552
HSA-MIR-7-2 0.0004533 0.0552
HSA-MIR-642A 0.0005071 0.0552
HSA-MIR-194-1 0.001542 0.133
HSA-MIR-194-2 0.001714 0.133
HSA-MIR-550A-2 0.003886 0.237
HSA-MIR-346 0.003921 0.237
HSA-MIR-561 0.005393 0.26
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 miRs related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 1.78 (0.91)
  N
  T0 1
  T1 179
  T2 91
  T3 77
  T4 13
     
  Significant markers N = 30
  pos. correlated 22
  neg. correlated 8
List of top 10 miRs differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-23C -0.286 1.856e-07 5.15e-05
HSA-MIR-139 -0.27 1.895e-07 5.15e-05
HSA-MIR-550A-1 0.254 1.041e-06 0.000189
HSA-MIR-122 -0.226 1.451e-05 0.00197
HSA-MIR-149 0.2236 1.906e-05 0.00207
HSA-MIR-194-1 -0.2174 3.102e-05 0.00245
HSA-MIR-194-2 -0.2172 3.159e-05 0.00245
HSA-MIR-22 -0.2135 4.31e-05 0.00266
HSA-MIR-550A-2 0.2136 4.404e-05 0.00266
HSA-MIR-7-3 0.2879 7.746e-05 0.00421
Clinical variable #5: 'PATHOLOGY_N_STAGE'

No miR related to 'PATHOLOGY_N_STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Labels N
  N0 250
  N1 4
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No miR related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 264
  class1 4
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

30 miRs related to 'GENDER'.

Table S11.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 115
  MALE 248
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 miRs differentially expressed by 'GENDER'

Table S12.  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-331 10317 2.248e-05 0.00491 0.6383
HSA-MIR-375 10318 2.259e-05 0.00491 0.6382
HSA-MIR-26A-2 10356 2.707e-05 0.00491 0.6369
HSA-MIR-1301 10500 5.3e-05 0.00664 0.6318
HSA-MIR-106A 10531 6.106e-05 0.00664 0.6308
HSA-MIR-363 10756 0.0001654 0.0104 0.6229
HSA-MIR-1266 10711 0.0001658 0.0104 0.6229
HSA-MIR-26A-1 10502 0.0001803 0.0104 0.6226
HSA-MIR-190 10721 0.0002107 0.0104 0.621
HSA-MIR-3065 10818 0.0002155 0.0104 0.6207
Clinical variable #8: 'RADIATION_THERAPY'

No miR related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 337
  YES 7
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  FIBROLAMELLAR CARCINOMA 2
  HEPATOCELLULAR CARCINOMA 354
  HEPATOCHOLANGIOCARCINOMA (MIXED) 7
     
  Significant markers N = 30
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'

kruskal_wallis_P Q
HSA-MIR-194-1 0.00029 0.0768
HSA-MIR-194-2 0.0003836 0.0768
HSA-MIR-192 0.0004236 0.0768
HSA-MIR-10A 0.0009286 0.11
HSA-MIR-122 0.00101 0.11
HSA-MIR-200B 0.001611 0.143
HSA-MIR-101-1 0.002087 0.143
HSA-MIR-200A 0.002103 0.143
HSA-MIR-375 0.002522 0.152
HSA-MIR-214 0.003371 0.179
Clinical variable #10: 'RESIDUAL_TUMOR'

No miR related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 318
  R1 15
  R2 1
  RX 22
     
  Significant markers N = 0
Clinical variable #11: 'RACE'

30 miRs related to 'RACE'.

Table S17.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 160
  BLACK OR AFRICAN AMERICAN 17
  WHITE 175
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RACE'

Table S18.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-23C 3.004e-15 1.63e-12
HSA-MIR-3130-1 1.845e-11 5.02e-09
HSA-MIR-532 3.589e-07 6.51e-05
HSA-MIR-30D 8.614e-07 0.000117
HSA-MIR-1304 1.122e-05 0.00122
HSA-MIR-511-1 2.226e-05 0.00202
HSA-MIR-511-2 2.79e-05 0.00217
HSA-MIR-338 3.957e-05 0.00245
HSA-MIR-627 4.047e-05 0.00245
HSA-MIR-26B 5.646e-05 0.00307
Clinical variable #12: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S19.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 14
  NOT HISPANIC OR LATINO 332
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 363

  • Number of miRs = 544

  • Number of clinical features = 12

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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