Correlation between miRseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1HT2NGW
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/C1HT2NGW
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 501 miRs and 12 clinical features across 1078 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one miRs.

  • 2 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-874 ,  HSA-MIR-30A

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

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

  • 30 miRs correlated to 'PATHOLOGIC_STAGE'.

    • HSA-MIR-210 ,  HSA-MIR-499 ,  HSA-MIR-99A ,  HSA-MIR-222 ,  HSA-MIR-374C ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-758 ,  HSA-MIR-9-2 ,  HSA-MIR-374A ,  HSA-MIR-9-1 ,  HSA-MIR-127 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-10A ,  HSA-MIR-577 ,  HSA-MIR-3613 ,  HSA-MIR-92A-2 ,  HSA-MIR-141 ,  ...

  • 1 miR correlated to 'PATHOLOGY_M_STAGE'.

    • HSA-MIR-374C

  • 8 miRs correlated to 'GENDER'.

    • HSA-MIR-29A ,  HSA-MIR-223 ,  HSA-MIR-454 ,  HSA-MIR-194-1 ,  HSA-MIR-3199-2 ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-210 ,  HSA-MIR-1306 ,  HSA-MIR-301A ,  HSA-MIR-301B ,  HSA-MIR-130B ,  ...

  • 30 miRs correlated to 'NUMBER_OF_LYMPH_NODES'.

    • HSA-MIR-577 ,  HSA-MIR-10A ,  HSA-MIR-3613 ,  HSA-MIR-141 ,  HSA-MIR-221 ,  ...

  • 30 miRs correlated to 'RACE'.

    • HSA-MIR-660 ,  HSA-MIR-20A ,  HSA-MIR-93 ,  HSA-MIR-1304 ,  HSA-MIR-103-1 ,  ...

  • 5 miRs correlated to 'ETHNICITY'.

    • HSA-MIR-23B ,  HSA-MIR-3934 ,  HSA-MIR-2110 ,  HSA-MIR-27B ,  HSA-MIR-23A

  • No miRs correlated to 'RADIATION_THERAPY'

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=2 shorter survival N=1 longer survival N=1
YEARS_TO_BIRTH Spearman correlation test N=30 older N=7 younger N=23
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=5 lower stage N=25
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=2 lower stage N=28
PATHOLOGY_M_STAGE Wilcoxon test N=1 class1 N=1 class0 N=0
GENDER Wilcoxon test N=8 male N=8 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=3 lower number_of_lymph_nodes N=27
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test N=5 not hispanic or latino N=5 hispanic or latino N=0
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

2 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) 0-282.9 (median=27.6)
  censored N = 930
  death N = 147
     
  Significant markers N = 2
  associated with shorter survival 1
  associated with longer survival 1
List of 2 miRs differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

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

HazardRatio Wald_P Q C_index
HSA-MIR-874 1.34 0.0004269 0.19 0.573
HSA-MIR-30A 0.82 0.0007465 0.19 0.387
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) 58.62 (13)
  Significant markers N = 30
  pos. correlated 7
  neg. correlated 23
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-31 -0.2113 9.217e-12 4.62e-09
HSA-MIR-424 -0.2039 1.915e-11 4.8e-09
HSA-MIR-381 -0.1948 1.574e-10 2.63e-08
HSA-MIR-99A -0.1918 2.894e-10 3.1e-08
HSA-MIR-598 -0.1915 3.093e-10 3.1e-08
HSA-MIR-652 -0.1837 1.619e-09 1.35e-07
HSA-LET-7C -0.17 2.443e-08 1.75e-06
HSA-MIR-542 -0.1679 3.657e-08 2.29e-06
HSA-MIR-375 0.1613 1.235e-07 6.88e-06
HSA-MIR-202 -0.1975 1.492e-07 7.47e-06
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 miRs related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 89
  STAGE IA 87
  STAGE IB 7
  STAGE II 6
  STAGE IIA 354
  STAGE IIB 249
  STAGE III 2
  STAGE IIIA 152
  STAGE IIIB 28
  STAGE IIIC 64
  STAGE IV 20
  STAGE TIS 1
  STAGE X 14
     
  Significant markers N = 30
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-210 1.979e-05 0.00991
HSA-MIR-499 4.067e-05 0.0102
HSA-MIR-99A 9.404e-05 0.0157
HSA-MIR-222 0.0001269 0.0157
HSA-MIR-374C 0.0001689 0.0157
HSA-LET-7F-2 0.0001878 0.0157
HSA-MIR-1247 0.0002373 0.017
HSA-MIR-130B 0.0003099 0.0186
HSA-MIR-125B-2 0.000355 0.0186
HSA-MIR-301A 0.0003713 0.0186
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) 1.94 (0.73)
  N
  T1 281
  T2 619
  T3 134
  T4 40
     
  Significant markers N = 30
  pos. correlated 5
  neg. correlated 25
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-758 -0.1267 3.229e-05 0.0162
HSA-MIR-9-2 0.108 0.0003901 0.0631
HSA-MIR-374A -0.1072 0.0004351 0.0631
HSA-MIR-9-1 0.1057 0.0005232 0.0631
HSA-MIR-127 -0.1037 0.0006635 0.0631
HSA-MIR-409 -0.1027 0.0007563 0.0631
HSA-MIR-1287 -0.0985 0.001224 0.0857
HSA-MIR-1976 -0.0974 0.001403 0.0857
HSA-MIR-382 -0.096 0.001651 0.0857
HSA-MIR-1247 -0.095 0.001928 0.0857
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.77 (0.91)
  N
  N0 509
  N1 356
  N2 118
  N3 75
     
  Significant markers N = 30
  pos. correlated 2
  neg. correlated 28
List of top 10 miRs differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
HSA-MIR-10A 0.1438 2.667e-06 0.00134
HSA-MIR-577 -0.1394 5.926e-05 0.0148
HSA-MIR-3613 -0.1175 0.0001273 0.0213
HSA-MIR-92A-2 -0.1122 0.0002564 0.025
HSA-MIR-141 -0.1121 0.000258 0.025
HSA-MIR-30A -0.111 0.0002994 0.025
HSA-MIR-455 -0.1085 0.0004055 0.029
HSA-MIR-548B -0.1219 0.0005133 0.0321
HSA-MIR-19B-2 -0.1044 0.0006707 0.0373
HSA-MIR-17 -0.1023 0.000858 0.0388
Clinical variable #6: 'PATHOLOGY_M_STAGE'

One miR related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 887
  class1 21
     
  Significant markers N = 1
  Higher in class1 1
  Higher in class0 0
List of one miR differentially expressed by 'PATHOLOGY_M_STAGE'

Table S12.  Get Full Table List of one miR differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
HSA-MIR-374C 3587 0.0001415 0.0709 0.852
Clinical variable #7: 'GENDER'

8 miRs related to 'GENDER'.

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

GENDER Labels N
  FEMALE 1066
  MALE 12
     
  Significant markers N = 8
  Higher in MALE 8
  Higher in FEMALE 0
List of 8 miRs differentially expressed by 'GENDER'

Table S14.  Get Full Table List of 8 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-29A 2455 0.0002386 0.12 0.8081
HSA-MIR-223 2775 0.000736 0.184 0.7831
HSA-MIR-454 9749 0.001772 0.192 0.7621
HSA-MIR-194-1 3062 0.001882 0.192 0.7606
HSA-MIR-3199-2 144 0.001921 0.192 0.9495
HSA-MIR-378C 3107 0.002536 0.207 0.7532
HSA-MIR-21 9555 0.003229 0.207 0.747
HSA-MIR-194-2 3245 0.003308 0.207 0.7463
Clinical variable #8: 'RADIATION_THERAPY'

No miR related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 431
  YES 513
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 770
  INFILTRATING LOBULAR CARCINOMA 199
  MEDULLARY CARCINOMA 6
  METAPLASTIC CARCINOMA 9
  MIXED HISTOLOGY (PLEASE SPECIFY) 28
  MUCINOUS CARCINOMA 17
  OTHER SPECIFY 47
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

Table S17.  Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
HSA-MIR-210 1.118e-45 5.6e-43
HSA-MIR-1306 6.4e-38 1.6e-35
HSA-MIR-301A 1.325e-37 2.21e-35
HSA-MIR-301B 1.831e-36 2.29e-34
HSA-MIR-130B 5.089e-36 5.1e-34
HSA-MIR-328 1.509e-35 1.26e-33
HSA-MIR-197 2.394e-35 1.71e-33
HSA-MIR-505 2.828e-35 1.77e-33
HSA-MIR-345 3.82e-35 2.13e-33
HSA-MIR-616 6.585e-35 3.3e-33
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 miRs related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.37 (4.6)
  Significant markers N = 30
  pos. correlated 3
  neg. correlated 27
List of top 10 miRs differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S19.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-577 -0.1626 1.171e-05 0.00587
HSA-MIR-10A 0.1359 3.704e-05 0.00928
HSA-MIR-3613 -0.1285 9.644e-05 0.0161
HSA-MIR-141 -0.1232 0.0001854 0.0196
HSA-MIR-221 -0.1228 0.0001959 0.0196
HSA-LET-7G -0.1208 0.0002479 0.0206
HSA-MIR-19B-2 -0.1193 0.0002973 0.0206
HSA-MIR-2114 -0.1481 0.0003282 0.0206
HSA-MIR-222 -0.1167 0.0004007 0.0223
HSA-MIR-148A -0.1134 0.0005854 0.0253
Clinical variable #11: 'RACE'

30 miRs related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 61
  BLACK OR AFRICAN AMERICAN 182
  WHITE 746
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RACE'

Table S21.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-660 5.108e-23 2.56e-20
HSA-MIR-20A 4.647e-20 1.16e-17
HSA-MIR-93 3.778e-19 6.31e-17
HSA-MIR-1304 8.866e-18 1.11e-15
HSA-MIR-103-1 7.375e-17 7.39e-15
HSA-MIR-17 1.826e-15 1.52e-13
HSA-MIR-361 3.222e-15 2.31e-13
HSA-MIR-26A-1 3.813e-15 2.39e-13
HSA-MIR-185 6.487e-14 3.61e-12
HSA-MIR-3615 4.979e-13 2.33e-11
Clinical variable #12: 'ETHNICITY'

5 miRs related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 39
  NOT HISPANIC OR LATINO 874
     
  Significant markers N = 5
  Higher in NOT HISPANIC OR LATINO 5
  Higher in HISPANIC OR LATINO 0
List of 5 miRs differentially expressed by 'ETHNICITY'

Table S23.  Get Full Table List of 5 miRs differentially expressed by 'ETHNICITY'

W(pos if higher in 'NOT HISPANIC OR LATINO') wilcoxontestP Q AUC
HSA-MIR-23B c("22172", "0.001458") c("22172", "0.001458") 0.238 0.6505
HSA-MIR-3934 c("19242", "0.001816") c("19242", "0.001816") 0.238 0.6534
HSA-MIR-2110 c("20952", "0.00191") c("20952", "0.00191") 0.238 0.6487
HSA-MIR-27B c("21970", "0.002232") c("21970", "0.002232") 0.238 0.6445
HSA-MIR-23A c("21940", "0.002374") c("21940", "0.002374") 0.238 0.6437
Methods & Data
Input

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

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

  • Number of patients = 1078

  • Number of miRs = 501

  • 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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