Correlation between miRseq expression and clinical features
Stomach and Esophageal carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C16D5S48
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/C16D5S48
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 513 miRs and 14 clinical features across 610 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one miRs.

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-194-1 ,  HSA-MIR-194-2 ,  HSA-MIR-192 ,  HSA-MIR-29B-1 ,  HSA-MIR-215 ,  ...

  • 30 miRs correlated to 'NEOPLASM_DISEASESTAGE'.

    • HSA-MIR-199B ,  HSA-MIR-199A-2 ,  HSA-MIR-199A-1 ,  HSA-MIR-127 ,  HSA-MIR-134 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-217 ,  HSA-MIR-199A-1 ,  HSA-MIR-132 ,  HSA-MIR-199A-2 ,  HSA-MIR-100 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-217 ,  HSA-MIR-203 ,  HSA-MIR-205 ,  HSA-MIR-944 ,  HSA-MIR-27A ,  ...

  • 30 miRs correlated to 'GENDER'.

    • HSA-MIR-326 ,  HSA-MIR-132 ,  HSA-MIR-3176 ,  HSA-MIR-142 ,  HSA-MIR-216A ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-100 ,  HSA-MIR-105-1 ,  HSA-MIR-577 ,  HSA-MIR-93 ,  HSA-MIR-188 ,  ...

  • 30 miRs correlated to 'COMPLETENESS_OF_RESECTION'.

    • HSA-LET-7F-2 ,  HSA-MIR-628 ,  HSA-LET-7A-2 ,  HSA-MIR-26A-1 ,  HSA-LET-7A-1 ,  ...

  • 14 miRs correlated to 'NUMBER_OF_LYMPH_NODES'.

    • HSA-MIR-3679 ,  HSA-MIR-556 ,  HSA-MIR-130A ,  HSA-MIR-151 ,  HSA-MIR-3680 ,  ...

  • 30 miRs correlated to 'RACE'.

    • HSA-MIR-3130-1 ,  HSA-MIR-412 ,  HSA-MIR-4326 ,  HSA-MIR-34B ,  HSA-MIR-423 ,  ...

  • 1 miR correlated to 'ETHNICITY'.

    • HSA-MIR-3690

  • No miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'PATHOLOGY_M_STAGE', 'RADIATIONS_RADIATION_REGIMENINDICATION', and 'NUMBER_PACK_YEARS_SMOKED'.

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=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=24 younger N=6
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=16 lower stage N=14
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=6 lower stage N=24
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RADIATIONS_RADIATION_REGIMENINDICATION Wilcoxon test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
COMPLETENESS_OF_RESECTION Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=14 higher number_of_lymph_nodes N=6 lower number_of_lymph_nodes N=8
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test N=1 not hispanic or latino N=1 hispanic or latino N=0
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No miR 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) 0-122.3 (median=12.8)
  censored N = 387
  death N = 222
     
  Significant markers N = 0
Clinical variable #2: 'YEARS_TO_BIRTH'

30 miRs related to 'YEARS_TO_BIRTH'.

Table S2.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 64.83 (11)
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
List of top 10 miRs differentially expressed by 'YEARS_TO_BIRTH'

Table S3.  Get Full Table List of top 10 miRs significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-194-1 0.2203 4.582e-08 1.27e-05
HSA-MIR-194-2 0.2198 4.953e-08 1.27e-05
HSA-MIR-192 0.2164 8.052e-08 1.28e-05
HSA-MIR-29B-1 0.2143 1.078e-07 1.28e-05
HSA-MIR-215 0.2132 1.248e-07 1.28e-05
HSA-MIR-29B-2 0.2111 1.667e-07 1.43e-05
HSA-MIR-153-2 0.202 5.797e-07 4.25e-05
HSA-MIR-592 0.2018 1.025e-06 6.58e-05
HSA-MIR-326 0.1928 1.989e-06 0.000113
HSA-MIR-375 0.1881 3.319e-06 0.00017
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

30 miRs related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 11
  STAGE IA 19
  STAGE IB 48
  STAGE II 33
  STAGE IIA 77
  STAGE IIB 84
  STAGE III 30
  STAGE IIIA 97
  STAGE IIIB 72
  STAGE IIIC 48
  STAGE IV 50
  STAGE IVA 4
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'NEOPLASM_DISEASESTAGE'

Table S5.  Get Full Table List of top 10 miRs differentially expressed by 'NEOPLASM_DISEASESTAGE'

kruskal_wallis_P Q
HSA-MIR-199B 6.09e-12 1.63e-09
HSA-MIR-199A-2 9.476e-12 1.63e-09
HSA-MIR-199A-1 9.505e-12 1.63e-09
HSA-MIR-127 3.711e-11 4.76e-09
HSA-MIR-134 5.619e-11 5.77e-09
HSA-MIR-654 2.421e-10 2.07e-08
HSA-MIR-152 1.047e-09 7.67e-08
HSA-MIR-337 2.795e-09 1.79e-07
HSA-MIR-409 3.43e-09 1.95e-07
HSA-MIR-708 4.537e-09 2.33e-07
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 miRs related to 'PATHOLOGY_T_STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.81 (0.88)
  N
  T0 1
  T1 52
  T2 126
  T3 281
  T4 124
     
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
List of top 10 miRs differentially expressed by 'PATHOLOGY_T_STAGE'

Table S7.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-217 0.2694 3.761e-11 1.93e-08
HSA-MIR-199A-1 0.2546 4.293e-10 9.47e-08
HSA-MIR-132 0.2516 6.998e-10 9.47e-08
HSA-MIR-199A-2 0.2512 7.381e-10 9.47e-08
HSA-MIR-100 0.2412 3.557e-09 3.65e-07
HSA-MIR-199B 0.2399 4.332e-09 3.7e-07
HSA-MIR-205 -0.2569 2.058e-08 1.51e-06
HSA-MIR-490 0.2481 1.15e-07 7.37e-06
HSA-MIR-125B-1 0.2089 3.527e-07 2.01e-05
HSA-MIR-556 -0.2252 5.559e-07 2.85e-05
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 1.15 (1.1)
  N
  N0 201
  N1 183
  N2 96
  N3 96
     
  Significant markers N = 30
  pos. correlated 6
  neg. correlated 24
List of top 10 miRs differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
HSA-MIR-217 0.1979 1.731e-06 0.000573
HSA-MIR-203 -0.1956 2.233e-06 0.000573
HSA-MIR-205 -0.1887 4.941e-05 0.0067
HSA-MIR-944 -0.1862 5.227e-05 0.0067
HSA-MIR-27A -0.165 6.947e-05 0.00713
HSA-MIR-137 -0.2313 0.0001333 0.0113
HSA-MIR-193B -0.157 0.0001545 0.0113
HSA-MIR-23A -0.1493 0.0003225 0.0192
HSA-MIR-24-2 -0.1489 0.0003373 0.0192
HSA-MIR-365-2 -0.1446 0.0004979 0.0255
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 514
  class1 39
     
  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 182
  MALE 428
     
  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-326 30177 3.405e-05 0.0065 0.6065
HSA-MIR-132 30831 4.591e-05 0.0065 0.6042
HSA-MIR-3176 9511 6.94e-05 0.0065 0.635
HSA-MIR-142 31036 7.11e-05 0.0065 0.6016
HSA-MIR-216A 19282 7.255e-05 0.0065 0.6128
HSA-MIR-330 31068 7.606e-05 0.0065 0.6012
HSA-MIR-1274B 28856 0.0002069 0.0152 0.5968
HSA-MIR-935 27551 0.0003671 0.0235 0.5942
HSA-MIR-766 31922 0.0004192 0.0239 0.5902
HSA-MIR-323B 29372 0.0008669 0.0408 0.5869
Clinical variable #8: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  STOMACH ADENOCARCINOMA DIFFUSE TYPE 71
  STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 163
  STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 80
  STOMACH INTESTINAL ADENOCARCINOMA TUBULAR TYPE 78
  STOMACH INTESTINAL ADENOCARCINOMA  MUCINOUS TYPE 22
  STOMACH INTESTINAL ADENOCARCINOMA  PAPILLARY TYPE 8
  STOMACH ADENOCARCINOMA SIGNET RING TYPE 13
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

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

kruskal_wallis_P Q
HSA-MIR-100 3.107e-09 1.07e-06
HSA-MIR-105-1 4.171e-09 1.07e-06
HSA-MIR-577 3.606e-08 6.17e-06
HSA-MIR-93 1.749e-07 1.58e-05
HSA-MIR-188 2.025e-07 1.58e-05
HSA-MIR-3615 2.147e-07 1.58e-05
HSA-MIR-20A 2.151e-07 1.58e-05
HSA-MIR-99A 2.66e-07 1.71e-05
HSA-MIR-532 3.62e-07 2.06e-05
HSA-MIR-92A-1 4.324e-07 2.22e-05
Clinical variable #9: 'RADIATIONS_RADIATION_REGIMENINDICATION'

No miR related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 6
  YES 604
     
  Significant markers N = 0
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

No miR related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 35.37 (22)
  Significant markers N = 0
Clinical variable #11: 'COMPLETENESS_OF_RESECTION'

30 miRs related to 'COMPLETENESS_OF_RESECTION'.

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

COMPLETENESS_OF_RESECTION Labels N
  R0 348
  R1 18
  R2 18
  RX 25
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'COMPLETENESS_OF_RESECTION'

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

kruskal_wallis_P Q
HSA-LET-7F-2 1.162e-15 5.96e-13
HSA-MIR-628 5.573e-15 1.43e-12
HSA-LET-7A-2 4.444e-14 5.43e-12
HSA-MIR-26A-1 4.591e-14 5.43e-12
HSA-LET-7A-1 5.347e-14 5.43e-12
HSA-LET-7A-3 6.348e-14 5.43e-12
HSA-MIR-361 3.557e-13 2.61e-11
HSA-MIR-3607 7.15e-10 4.4e-08
HSA-MIR-106A 7.712e-10 4.4e-08
HSA-MIR-3605 1.97e-09 1.01e-07
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

14 miRs related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 5.53 (8.1)
  Significant markers N = 14
  pos. correlated 6
  neg. correlated 8
List of top 10 miRs differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S20.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-3679 -0.2988 5.342e-05 0.0274
HSA-MIR-556 -0.1971 0.000261 0.0514
HSA-MIR-130A 0.1828 0.0003005 0.0514
HSA-MIR-151 -0.1705 0.0007546 0.0825
HSA-MIR-3680 -0.207 0.0008041 0.0825
HSA-MIR-653 0.1647 0.001221 0.104
HSA-MIR-1254 -0.1711 0.001997 0.142
HSA-MIR-1-2 0.1551 0.002211 0.142
HSA-MIR-33B -0.1549 0.002777 0.144
HSA-MIR-100 0.1512 0.002856 0.144
Clinical variable #13: 'RACE'

30 miRs related to 'RACE'.

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

RACE Labels N
  ASIAN 129
  BLACK OR AFRICAN AMERICAN 14
  WHITE 385
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RACE'

Table S22.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-3130-1 3.249e-18 1.67e-15
HSA-MIR-412 2.712e-11 6.96e-09
HSA-MIR-4326 1.19e-10 2.03e-08
HSA-MIR-34B 8.026e-07 0.000103
HSA-MIR-423 2.635e-06 0.00027
HSA-MIR-2355 3.628e-06 0.00031
HSA-MIR-9-3 5.512e-06 0.000404
HSA-MIR-93 2.782e-05 0.00156
HSA-MIR-671 3.036e-05 0.00156
HSA-MIR-365-1 3.045e-05 0.00156
Clinical variable #14: 'ETHNICITY'

One miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 394
     
  Significant markers N = 1
  Higher in NOT HISPANIC OR LATINO 1
  Higher in HISPANIC OR LATINO 0
List of one miR differentially expressed by 'ETHNICITY'

Table S24.  Get Full Table List of one miR differentially expressed by 'ETHNICITY'

W(pos if higher in 'NOT HISPANIC OR LATINO') wilcoxontestP Q AUC
HSA-MIR-3690 c("173", "0.0001455") c("173", "0.0001455") 0.0747 0.92
Methods & Data
Input

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

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

  • Number of patients = 610

  • Number of miRs = 513

  • Number of clinical features = 14

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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