Correlation between miRseq expression and clinical features
Stomach Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1D799W0
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features. The input file " STAD-TP.miRseq_RPKM_log2.txt " is generated in the pipeline miRseq_Preprocess in the stddata run.

Summary

Testing the association between 506 miRs and 13 clinical features across 436 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 12 clinical features related to at least one miRs.

  • 1 miR correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-541

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-182 ,  HSA-MIR-183 ,  HSA-LET-7C ,  HSA-MIR-96 ,  HSA-MIR-616 ,  ...

  • 30 miRs correlated to 'PATHOLOGIC_STAGE'.

    • HSA-MIR-152 ,  HSA-MIR-101-2 ,  HSA-MIR-199A-1 ,  HSA-MIR-217 ,  HSA-MIR-199A-2 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-217 ,  HSA-MIR-320B-2 ,  HSA-MIR-132 ,  HSA-MIR-556 ,  HSA-MIR-16-1 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-556 ,  HSA-MIR-33B ,  HSA-MIR-320D-1 ,  HSA-MIR-151 ,  HSA-MIR-2277 ,  ...

  • 19 miRs correlated to 'PATHOLOGY_M_STAGE'.

    • HSA-MIR-181A-2 ,  HSA-MIR-654 ,  HSA-MIR-152 ,  HSA-MIR-1274B ,  HSA-MIR-337 ,  ...

  • 1 miR correlated to 'GENDER'.

    • HSA-MIR-3176

  • 30 miRs correlated to 'RADIATION_THERAPY'.

    • HSA-LET-7F-2 ,  HSA-MIR-490 ,  HSA-LET-7A-3 ,  HSA-LET-7A-1 ,  HSA-LET-7A-2 ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-105-1 ,  HSA-MIR-100 ,  HSA-MIR-577 ,  HSA-MIR-99A ,  HSA-MIR-20A ,  ...

  • 30 miRs correlated to 'RESIDUAL_TUMOR'.

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

  • 30 miRs correlated to 'NUMBER_OF_LYMPH_NODES'.

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

  • 30 miRs correlated to 'RACE'.

    • HSA-MIR-3130-1 ,  HSA-MIR-412 ,  HSA-MIR-4326 ,  HSA-MIR-423 ,  HSA-MIR-361 ,  ...

  • No miRs correlated to '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=1   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=24 younger N=6
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=9 lower stage N=21
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=3 lower stage N=27
PATHOLOGY_M_STAGE Wilcoxon test N=19 class1 N=19 class0 N=0
GENDER Wilcoxon test N=1 male N=1 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=10 lower number_of_lymph_nodes N=20
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

One 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=14.7)
  censored N = 263
  death N = 172
     
  Significant markers N = 1
  associated with shorter survival NA
  associated with longer survival NA
List of one miR differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of one miR significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
HSA-MIR-541 7.56e-05 0.038 0.586
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) 65.73 (11)
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
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-182 0.2135 8.566e-06 0.00377
HSA-MIR-183 0.2079 1.492e-05 0.00377
HSA-LET-7C -0.1991 3.422e-05 0.00577
HSA-MIR-96 0.1957 4.651e-05 0.00588
HSA-MIR-616 0.189 0.0001013 0.0102
HSA-MIR-125B-2 -0.1867 0.0001207 0.0102
HSA-MIR-125B-1 -0.1819 0.0001571 0.0105
HSA-MIR-215 0.1813 0.000166 0.0105
HSA-MIR-195 -0.1764 0.0002499 0.0123
HSA-MIR-592 0.179 0.0002745 0.0123
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 2
  STAGE IA 16
  STAGE IB 40
  STAGE II 32
  STAGE IIA 41
  STAGE IIB 55
  STAGE III 3
  STAGE IIIA 80
  STAGE IIIB 61
  STAGE IIIC 39
  STAGE IV 43
     
  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-152 4.689e-07 0.000153
HSA-MIR-101-2 6.064e-07 0.000153
HSA-MIR-199A-1 1.821e-06 0.000307
HSA-MIR-217 3.794e-06 0.000402
HSA-MIR-199A-2 3.971e-06 0.000402
HSA-MIR-134 5.483e-06 0.000462
HSA-MIR-199B 7.23e-06 0.000489
HSA-MIR-130A 7.903e-06 0.000489
HSA-MIR-214 8.69e-06 0.000489
HSA-MIR-654 1.617e-05 0.000818
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) 2.95 (0.84)
  N
  T1 23
  T2 92
  T3 193
  T4 118
     
  Significant markers N = 30
  pos. correlated 9
  neg. correlated 21
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-217 0.2611 4.71e-08 2.38e-05
HSA-MIR-320B-2 -0.2284 1.902e-06 0.000481
HSA-MIR-132 0.2218 3.81e-06 0.000643
HSA-MIR-556 -0.2323 6.337e-06 0.000802
HSA-MIR-16-1 -0.2135 8.755e-06 0.000886
HSA-MIR-320A -0.2061 1.813e-05 0.00153
HSA-MIR-191 -0.2 3.21e-05 0.00209
HSA-MIR-32 -0.198 3.86e-05 0.00209
HSA-MIR-7-1 -0.1977 3.966e-05 0.00209
HSA-MIR-100 0.1973 4.137e-05 0.00209
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) 1.31 (1.1)
  N
  N0 129
  N1 117
  N2 85
  N3 87
     
  Significant markers N = 30
  pos. correlated 3
  neg. correlated 27
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-556 -0.2107 5.329e-05 0.027
HSA-MIR-33B -0.1841 0.0002101 0.0532
HSA-MIR-320D-1 -0.2027 0.0006026 0.0742
HSA-MIR-151 -0.1667 0.0006226 0.0742
HSA-MIR-2277 -0.1741 0.0007722 0.0742
HSA-MIR-550A-2 -0.1625 0.0008799 0.0742
HSA-MIR-217 0.1588 0.001137 0.075
HSA-MIR-580 -0.1719 0.001187 0.075
HSA-MIR-3679 -0.2299 0.001334 0.075
HSA-MIR-1274B -0.152 0.002242 0.0963
Clinical variable #6: 'PATHOLOGY_M_STAGE'

19 miRs related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 384
  class1 30
     
  Significant markers N = 19
  Higher in class1 19
  Higher in class0 0
List of top 10 miRs differentially expressed by 'PATHOLOGY_M_STAGE'

Table S12.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
HSA-MIR-181A-2 7972 0.0004588 0.192 0.692
HSA-MIR-654 7850 0.0009316 0.192 0.6814
HSA-MIR-152 7808 0.001179 0.192 0.6778
HSA-MIR-1274B 7414 0.001587 0.192 0.6734
HSA-MIR-337 7682 0.002333 0.192 0.6668
HSA-MIR-495 7664 0.002564 0.192 0.6653
HSA-MIR-379 7641 0.002889 0.192 0.6633
HSA-MIR-99B 7623 0.00317 0.192 0.6617
HSA-MIR-873 1341 0.003696 0.192 0.7368
HSA-MIR-24-2 7588 0.003788 0.192 0.6587
Clinical variable #7: 'GENDER'

One miR related to 'GENDER'.

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

GENDER Labels N
  FEMALE 155
  MALE 281
     
  Significant markers N = 1
  Higher in MALE 1
  Higher in FEMALE 0
List of one miR differentially expressed by 'GENDER'

Table S14.  Get Full Table List of one miR 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-3176 5071 0.000266 0.135 0.6405
Clinical variable #8: 'RADIATION_THERAPY'

30 miRs related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 319
  YES 74
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 miRs differentially expressed by 'RADIATION_THERAPY'

Table S16.  Get Full Table List of top 10 miRs differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-LET-7F-2 15041 0.0002356 0.0885 0.6372
HSA-MIR-490 5365 0.0005348 0.0885 0.6462
HSA-LET-7A-3 14672 0.001121 0.0885 0.6215
HSA-LET-7A-1 14669 0.001135 0.0885 0.6214
HSA-LET-7A-2 14651 0.001219 0.0885 0.6206
HSA-MIR-185 14650 0.001224 0.0885 0.6206
HSA-MIR-1295 8340 0.001225 0.0885 0.6392
HSA-MIR-320C-1 10658 0.001688 0.107 0.6258
HSA-MIR-486 14486 0.002311 0.13 0.6137
HSA-MIR-1245 8128 0.002905 0.132 0.6142
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  STOMACH ADENOCARCINOMA, SIGNET RING TYPE 11
  STOMACH, ADENOCARCINOMA, DIFFUSE TYPE 72
  STOMACH, ADENOCARCINOMA, NOT OTHERWISE SPECIFIED (NOS) 164
  STOMACH, INTESTINAL ADENOCARCINOMA, MUCINOUS TYPE 22
  STOMACH, INTESTINAL ADENOCARCINOMA, NOT OTHERWISE SPECIFIED (NOS) 79
  STOMACH, INTESTINAL ADENOCARCINOMA, PAPILLARY TYPE 8
  STOMACH, INTESTINAL ADENOCARCINOMA, TUBULAR TYPE 77
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

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

kruskal_wallis_P Q
HSA-MIR-105-1 3.319e-09 1.04e-06
HSA-MIR-100 4.108e-09 1.04e-06
HSA-MIR-577 4.118e-08 6.95e-06
HSA-MIR-99A 1.449e-07 1.83e-05
HSA-MIR-20A 1.951e-07 1.97e-05
HSA-MIR-93 3.861e-07 2.71e-05
HSA-MIR-188 4.099e-07 2.71e-05
HSA-MIR-135B 4.278e-07 2.71e-05
HSA-MIR-92A-1 5.534e-07 3.11e-05
HSA-MIR-3200 6.424e-07 3.25e-05
Clinical variable #10: 'RESIDUAL_TUMOR'

30 miRs related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 344
  R1 18
  R2 18
  RX 25
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RESIDUAL_TUMOR'

Table S20.  Get Full Table List of top 10 miRs differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
HSA-LET-7F-2 1.348e-15 6.82e-13
HSA-MIR-628 6.958e-15 1.76e-12
HSA-MIR-26A-1 4.766e-14 6.12e-12
HSA-LET-7A-2 5.075e-14 6.12e-12
HSA-LET-7A-1 6.138e-14 6.12e-12
HSA-LET-7A-3 7.258e-14 6.12e-12
HSA-MIR-361 3.859e-13 2.79e-11
HSA-MIR-3607 7.748e-10 4.9e-08
HSA-MIR-106A 9.994e-10 5.62e-08
HSA-MIR-3605 1.788e-09 9.05e-08
Clinical variable #11: 'NUMBER_OF_LYMPH_NODES'

30 miRs related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 5.56 (8.1)
  Significant markers N = 30
  pos. correlated 10
  neg. correlated 20
List of top 10 miRs differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S22.  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 -0.3114 2.89e-05 0.0146
HSA-MIR-130A 0.189 0.0001907 0.0483
HSA-MIR-556 -0.1939 0.0003305 0.0558
HSA-MIR-151 -0.172 0.0007006 0.0886
HSA-MIR-3680 -0.2002 0.00117 0.0986
HSA-MIR-100 0.1638 0.001256 0.0986
HSA-MIR-653 0.1635 0.001365 0.0986
HSA-MIR-1254 -0.1714 0.001996 0.126
HSA-MIR-497 0.1539 0.002457 0.138
HSA-MIR-33B -0.1554 0.002767 0.14
Clinical variable #12: 'RACE'

30 miRs related to 'RACE'.

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

RACE Labels N
  ASIAN 88
  BLACK OR AFRICAN AMERICAN 13
  WHITE 273
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'RACE'

Table S24.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-3130-1 6.252e-14 3.16e-11
HSA-MIR-412 2.062e-09 5.22e-07
HSA-MIR-4326 5.337e-08 9e-06
HSA-MIR-423 1.733e-06 0.000219
HSA-MIR-361 2.597e-06 0.000263
HSA-MIR-103-1 3.364e-06 0.000284
HSA-MIR-660 2.773e-05 0.00189
HSA-MIR-1304 2.985e-05 0.00189
HSA-MIR-500B 3.91e-05 0.0022
HSA-MIR-93 5.017e-05 0.00254
Clinical variable #13: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S25.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 5
  NOT HISPANIC OR LATINO 317
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = STAD-TP.miRseq_RPKM_log2.txt

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

  • Number of patients = 436

  • Number of miRs = 506

  • Number of clinical features = 13

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, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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)