Correlation between miRseq expression and clinical features
Esophageal Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C11G0K8T
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/C11G0K8T
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 523 miRs and 10 clinical features across 173 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one miRs.

  • 27 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-1291 ,  HSA-MIR-612 ,  HSA-MIR-3687 ,  HSA-MIR-3648 ,  HSA-MIR-103-2 ,  ...

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-375 ,  HSA-MIR-944 ,  HSA-MIR-3619 ,  HSA-MIR-149 ,  HSA-MIR-193B ,  ...

  • 30 miRs correlated to 'NEOPLASM_DISEASESTAGE'.

    • HSA-MIR-205 ,  HSA-MIR-192 ,  HSA-MIR-708 ,  HSA-MIR-194-1 ,  HSA-MIR-194-2 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-199A-1 ,  HSA-MIR-34B ,  HSA-MIR-556 ,  HSA-MIR-199A-2 ,  HSA-MIR-708 ,  ...

  • 10 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-23A ,  HSA-MIR-192 ,  HSA-MIR-27A ,  HSA-LET-7B ,  HSA-MIR-7-3 ,  ...

  • 30 miRs correlated to 'RACE'.

    • HSA-MIR-205 ,  HSA-MIR-149 ,  HSA-MIR-944 ,  HSA-MIR-224 ,  HSA-MIR-194-1 ,  ...

  • No miRs correlated to 'PATHOLOGY_M_STAGE', 'GENDER', 'NUMBER_PACK_YEARS_SMOKED', 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=27 shorter survival N=27 longer survival N=0
YEARS_TO_BIRTH Spearman correlation test N=30 older N=13 younger N=17
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_N_STAGE Spearman correlation test N=10 higher stage N=5 lower stage N=5
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

27 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) 0.1-122.1 (median=12.6)
  censored N = 101
  death N = 71
     
  Significant markers N = 27
  associated with shorter survival 27
  associated with longer survival 0
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-1291 1.45 0.0005787 0.12 0.631
HSA-MIR-612 1.44 0.0009357 0.12 0.667
HSA-MIR-3687 1.2 0.001022 0.12 0.647
HSA-MIR-3648 1.18 0.00103 0.12 0.647
HSA-MIR-103-2 1.75 0.001137 0.12 0.653
HSA-MIR-663 1.25 0.002452 0.19 0.619
HSA-MIR-550A-2 1.38 0.002998 0.19 0.624
HSA-MIR-1294 1.6 0.003062 0.19 0.684
HSA-MIR-517B 1.27 0.003667 0.19 0.669
HSA-MIR-517A 1.27 0.003693 0.19 0.669
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) 62.7 (12)
  Significant markers N = 30
  pos. correlated 13
  neg. correlated 17
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-375 0.3695 5.643e-07 0.000195
HSA-MIR-944 -0.372 7.446e-07 0.000195
HSA-MIR-3619 -0.4146 2.667e-05 0.0032
HSA-MIR-149 -0.3126 2.823e-05 0.0032
HSA-MIR-193B -0.3113 3.061e-05 0.0032
HSA-MIR-708 -0.3024 5.264e-05 0.00459
HSA-MIR-29B-2 0.2976 6.994e-05 0.00483
HSA-MIR-29B-1 0.2967 7.385e-05 0.00483
HSA-MIR-205 -0.2931 9.527e-05 0.00554
HSA-MIR-147B 0.302 0.0001148 0.00584
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

30 miRs related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 8
  STAGE IA 5
  STAGE IB 7
  STAGE II 1
  STAGE IIA 38
  STAGE IIB 29
  STAGE III 26
  STAGE IIIA 12
  STAGE IIIB 10
  STAGE IIIC 7
  STAGE IV 5
  STAGE IVA 4
     
  Significant markers N = 30
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'

kruskal_wallis_P Q
HSA-MIR-205 0.000107 0.0214
HSA-MIR-192 0.0001186 0.0214
HSA-MIR-708 0.0001228 0.0214
HSA-MIR-194-1 0.0002983 0.0336
HSA-MIR-194-2 0.0003216 0.0336
HSA-MIR-944 0.001468 0.0996
HSA-MIR-200B 0.001507 0.0996
HSA-MIR-215 0.001535 0.0996
HSA-MIR-592 0.001866 0.0996
HSA-MIR-190 0.001936 0.0996
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) 2.4 (0.85)
  N
  T0 1
  T1 30
  T2 36
  T3 85
  T4 5
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
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-199A-1 0.3172 5.163e-05 0.0196
HSA-MIR-34B 0.312 0.0001135 0.0196
HSA-MIR-556 -0.3474 0.0001427 0.0196
HSA-MIR-199A-2 0.298 0.0001501 0.0196
HSA-MIR-708 0.2914 0.0002138 0.0207
HSA-MIR-215 -0.2893 0.000238 0.0207
HSA-MIR-34C 0.2831 0.0003417 0.0255
HSA-MIR-206 -0.3268 0.0004367 0.0285
HSA-MIR-125B-1 0.2723 0.0005598 0.0325
HSA-LET-7I 0.2654 0.0007813 0.0366
Clinical variable #5: 'PATHOLOGY_N_STAGE'

10 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.73 (0.82)
  N
  N0 70
  N1 65
  N2 12
  N3 8
     
  Significant markers N = 10
  pos. correlated 5
  neg. correlated 5
List of 10 miRs differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of 10 miRs significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-23A -0.2709 0.0006498 0.273
HSA-MIR-192 0.2528 0.001509 0.273
HSA-MIR-27A -0.2425 0.00236 0.273
HSA-LET-7B -0.2367 0.00303 0.273
HSA-MIR-7-3 0.2491 0.003213 0.273
HSA-MIR-194-1 0.2333 0.003479 0.273
HSA-MIR-194-2 0.2313 0.003777 0.273
HSA-MIR-205 -0.2285 0.004235 0.273
HSA-MIR-365-2 -0.226 0.004694 0.273
HSA-MIR-1911 0.3331 0.005513 0.288
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No miR related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 126
  class1 9
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

No miR related to 'GENDER'.

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

GENDER Labels N
  FEMALE 24
  MALE 149
     
  Significant markers N = 0
Clinical variable #8: 'NUMBER_PACK_YEARS_SMOKED'

No miR related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 35.37 (22)
  Significant markers N = 0
Clinical variable #9: 'RACE'

30 miRs related to 'RACE'.

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

RACE Labels N
  ASIAN 40
  BLACK OR AFRICAN AMERICAN 2
  WHITE 111
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RACE'

Table S15.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-205 8.703e-10 3.74e-07
HSA-MIR-149 1.432e-09 3.74e-07
HSA-MIR-944 1.754e-08 2.81e-06
HSA-MIR-224 2.15e-08 2.81e-06
HSA-MIR-194-1 3.542e-08 3.7e-06
HSA-MIR-193B 8.634e-08 6.85e-06
HSA-MIR-194-2 9.17e-08 6.85e-06
HSA-MIR-192 1.471e-07 9.62e-06
HSA-MIR-708 1.67e-07 9.71e-06
HSA-MIR-23A 2.695e-07 1.41e-05
Clinical variable #10: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 3
  NOT HISPANIC OR LATINO 80
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 173

  • Number of miRs = 523

  • Number of clinical features = 10

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • 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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