Correlation between miRseq expression and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1F18Z3D
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/C1F18Z3D
Overview
Introduction

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

Summary

Testing the association between 550 miRs and 14 clinical features across 523 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 12 clinical features related to at least one miRs.

  • 30 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-337 ,  HSA-MIR-485 ,  HSA-MIR-758 ,  HSA-MIR-495 ,  HSA-MIR-377 ,  ...

  • 3 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-548B ,  HSA-MIR-128-1 ,  HSA-MIR-3177

  • 1 miR correlated to 'PATHOLOGIC_STAGE'.

    • HSA-MIR-139

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-150 ,  HSA-MIR-146A ,  HSA-MIR-206 ,  HSA-MIR-128-1 ,  HSA-MIR-363 ,  ...

  • 23 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-1293 ,  HSA-MIR-203 ,  HSA-MIR-3620 ,  HSA-MIR-548K ,  HSA-MIR-542 ,  ...

  • 30 miRs correlated to 'GENDER'.

    • HSA-MIR-1293 ,  HSA-MIR-25 ,  HSA-MIR-187 ,  HSA-MIR-9-1 ,  HSA-MIR-9-2 ,  ...

  • 30 miRs correlated to 'RADIATION_THERAPY'.

    • HSA-MIR-206 ,  HSA-MIR-133A-1 ,  HSA-MIR-133A-2 ,  HSA-MIR-93 ,  HSA-MIR-1-2 ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-9-1 ,  HSA-MIR-9-2 ,  HSA-MIR-92A-1 ,  HSA-MIR-141 ,  HSA-MIR-181C ,  ...

  • 30 miRs correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • HSA-MIR-152 ,  HSA-MIR-1180 ,  HSA-MIR-151 ,  HSA-MIR-1266 ,  HSA-MIR-3677 ,  ...

  • 30 miRs correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • HSA-MIR-548B ,  HSA-MIR-450A-2 ,  HSA-MIR-18A ,  HSA-MIR-3177 ,  HSA-MIR-451 ,  ...

  • 30 miRs correlated to 'NUMBER_OF_LYMPH_NODES'.

    • HSA-MIR-151 ,  HSA-MIR-1293 ,  HSA-LET-7F-2 ,  HSA-MIR-421 ,  HSA-MIR-411 ,  ...

  • 16 miRs correlated to 'RACE'.

    • HSA-MIR-1304 ,  HSA-MIR-508 ,  HSA-MIR-130B ,  HSA-MIR-3129 ,  HSA-MIR-509-3 ,  ...

  • No miRs correlated to 'PATHOLOGY_M_STAGE', 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   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=3 older N=0 younger N=3
PATHOLOGIC_STAGE Kruskal-Wallis test N=1        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=4 lower stage N=26
PATHOLOGY_N_STAGE Spearman correlation test N=23 higher stage N=13 lower stage N=10
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=30 higher number_pack_years_smoked N=27 lower number_pack_years_smoked N=3
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=30 higher year_of_tobacco_smoking_onset N=21 lower year_of_tobacco_smoking_onset N=9
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=25 lower number_of_lymph_nodes N=5
RACE Kruskal-Wallis test N=16        
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) 0.1-211 (median=21.2)
  censored N = 301
  death N = 221
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
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. 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-337 0.000461 0.11 0.583
HSA-MIR-485 0.000997 0.11 0.572
HSA-MIR-758 0.0011 0.11 0.578
HSA-MIR-495 0.00115 0.11 0.57
HSA-MIR-377 0.00148 0.11 0.581
HSA-MIR-411 0.00152 0.11 0.579
HSA-MIR-99A 0.00177 0.11 0.401
HSA-MIR-125B-2 0.0019 0.11 0.407
HSA-MIR-382 0.00216 0.11 0.571
HSA-MIR-410 0.00218 0.11 0.574
Clinical variable #2: 'YEARS_TO_BIRTH'

3 miRs related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 60.94 (12)
  Significant markers N = 3
  pos. correlated 0
  neg. correlated 3
List of 3 miRs differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of 3 miRs significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-548B -0.1623 0.001421 0.288
HSA-MIR-128-1 -0.1385 0.001516 0.288
HSA-MIR-3177 -0.22 0.001569 0.288
Clinical variable #3: 'PATHOLOGIC_STAGE'

One miR related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 27
  STAGE II 76
  STAGE III 79
  STAGE IVA 257
  STAGE IVB 12
  STAGE IVC 1
     
  Significant markers N = 1
List of one miR differentially expressed by 'PATHOLOGIC_STAGE'

Table S6.  Get Full Table List of one miR differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
HSA-MIR-139 8.783e-05 0.0483
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) 2.87 (1)
  N
  T0 1
  T1 48
  T2 138
  T3 99
  T4 175
     
  Significant markers N = 30
  pos. correlated 4
  neg. correlated 26
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-150 -0.2229 1.332e-06 0.000733
HSA-MIR-146A -0.2001 1.501e-05 0.00413
HSA-MIR-206 -0.1944 2.702e-05 0.00495
HSA-MIR-128-1 -0.1792 0.0001094 0.012
HSA-MIR-363 -0.1792 0.0001095 0.012
HSA-MIR-133A-1 -0.1722 0.0002132 0.0179
HSA-MIR-137 0.2022 0.0002281 0.0179
HSA-MIR-3065 0.1676 0.0003014 0.0185
HSA-MIR-660 -0.1676 0.000302 0.0185
HSA-MIR-181C -0.1657 0.0003524 0.0193
Clinical variable #5: 'PATHOLOGY_N_STAGE'

23 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 1.03 (0.95)
  N
  N0 176
  N1 68
  N2 171
  N3 8
     
  Significant markers N = 23
  pos. correlated 13
  neg. correlated 10
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-1293 -0.1953 6.086e-05 0.0335
HSA-MIR-203 -0.1776 0.0002409 0.0663
HSA-MIR-3620 -0.232 0.0005225 0.0823
HSA-MIR-548K 0.2064 0.0005986 0.0823
HSA-MIR-542 0.1602 0.0009451 0.104
HSA-LET-7F-2 0.1542 0.001465 0.131
HSA-MIR-151 0.1505 0.001905 0.131
HSA-MIR-421 0.1508 0.001948 0.131
HSA-MIR-223 -0.1488 0.002148 0.131
HSA-MIR-106B 0.1405 0.003777 0.208
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 189
  class1 1
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

30 miRs related to 'GENDER'.

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

GENDER Labels N
  FEMALE 141
  MALE 382
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 miRs differentially expressed by 'GENDER'

Table S13.  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-1293 19220 3.44e-06 0.00189 0.6329
HSA-MIR-25 33205 4.301e-05 0.00647 0.6165
HSA-MIR-187 20531 4.855e-05 0.00647 0.6158
HSA-MIR-9-1 33083 6.043e-05 0.00647 0.6142
HSA-MIR-9-2 33057 6.492e-05 0.00647 0.6137
HSA-MIR-584 20866 7.673e-05 0.00647 0.6126
HSA-MIR-130B 32865 0.0001093 0.00647 0.6102
HSA-MIR-561 8662 0.0001098 0.00647 0.6602
HSA-MIR-222 21018 0.0001156 0.00647 0.6098
HSA-MIR-1180 32810 0.0001265 0.00647 0.6091
Clinical variable #8: 'RADIATION_THERAPY'

30 miRs related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 161
  YES 300
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 miRs differentially expressed by 'RADIATION_THERAPY'

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

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-206 18679 8.926e-05 0.0491 0.6109
HSA-MIR-133A-1 18843 0.0002157 0.0521 0.6048
HSA-MIR-133A-2 9660 0.0002844 0.0521 0.6193
HSA-MIR-93 28957 0.0004239 0.0533 0.5995
HSA-MIR-1-2 19324 0.0004844 0.0533 0.5986
HSA-MIR-139 19501 0.0006524 0.0598 0.5963
HSA-MIR-25 28678 0.0008998 0.0707 0.5937
HSA-MIR-194-1 28497 0.001436 0.0884 0.59
HSA-MIR-1304 16719 0.001453 0.0884 0.5936
HSA-MIR-499 8155 0.001607 0.0884 0.6092
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  HEAD & NECK SQUAMOUS CELL CARCINOMA 512
  HEAD & NECK SQUAMOUS CELL CARCINOMA BASALOID TYPE 10
  HEAD & NECK SQUAMOUS CELL CARCINOMA, SPINDLE CELL VARIANT 1
     
  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-9-1 0.0001447 0.041
HSA-MIR-9-2 0.0001491 0.041
HSA-MIR-92A-1 0.0002729 0.05
HSA-MIR-141 0.0005387 0.0741
HSA-MIR-181C 0.0007547 0.076
HSA-MIR-548B 0.0008953 0.076
HSA-MIR-92A-2 0.0009676 0.076
HSA-MIR-25 0.001518 0.094
HSA-MIR-362 0.001609 0.094
HSA-MIR-187 0.00171 0.094
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

30 miRs related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 45.69 (35)
  Significant markers N = 30
  pos. correlated 27
  neg. correlated 3
List of top 10 miRs differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

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

SpearmanCorr corrP Q
HSA-MIR-152 0.2863 5.666e-07 0.000312
HSA-MIR-1180 0.2341 4.883e-05 0.00918
HSA-MIR-151 0.2338 5.007e-05 0.00918
HSA-MIR-1266 0.2274 0.00012 0.0165
HSA-MIR-3677 0.2183 0.0001574 0.0173
HSA-MIR-1224 0.2849 0.0004697 0.0327
HSA-MIR-744 0.2021 0.0004778 0.0327
HSA-MIR-1249 0.2015 0.0004973 0.0327
HSA-MIR-940 0.2007 0.0005348 0.0327
HSA-MIR-29B-2 -0.1945 0.0007815 0.0418
Clinical variable #11: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

30 miRs related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1967.2 (13)
  Significant markers N = 30
  pos. correlated 21
  neg. correlated 9
List of top 10 miRs differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S21.  Get Full Table List of top 10 miRs significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-548B 0.2497 0.0002578 0.0901
HSA-MIR-450A-2 0.2117 0.0003875 0.0901
HSA-MIR-18A 0.2073 0.0004914 0.0901
HSA-MIR-3177 0.307 0.0008914 0.123
HSA-MIR-451 0.1883 0.001582 0.155
HSA-LET-7C -0.1868 0.001729 0.155
HSA-MIR-1295 -0.1931 0.002508 0.155
HSA-MIR-125B-2 -0.1794 0.002631 0.155
HSA-MIR-2355 0.1792 0.002666 0.155
HSA-MIR-19B-2 0.1782 0.00281 0.155
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

30 miRs related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.2 (4.3)
  Significant markers N = 30
  pos. correlated 25
  neg. correlated 5
List of top 10 miRs differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S23.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-151 0.217 9.288e-06 0.00277
HSA-MIR-1293 -0.2177 1.009e-05 0.00277
HSA-LET-7F-2 0.1975 5.653e-05 0.0104
HSA-MIR-421 0.1928 9.025e-05 0.0124
HSA-MIR-411 0.1888 0.00012 0.0132
HSA-MIR-203 -0.1859 0.0001533 0.014
HSA-MIR-143 0.1807 0.0002346 0.0179
HSA-MIR-542 0.1792 0.000266 0.0179
HSA-MIR-654 0.178 0.0002922 0.0179
HSA-MIR-379 0.1743 0.000393 0.0202
Clinical variable #13: 'RACE'

16 miRs related to 'RACE'.

Table S24.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 2
  ASIAN 11
  BLACK OR AFRICAN AMERICAN 47
  WHITE 448
     
  Significant markers N = 16
List of top 10 miRs differentially expressed by 'RACE'

Table S25.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-1304 3.227e-06 0.00177
HSA-MIR-508 0.0005851 0.124
HSA-MIR-130B 0.0006739 0.124
HSA-MIR-3129 0.001325 0.156
HSA-MIR-509-3 0.00149 0.156
HSA-MIR-511-2 0.001697 0.156
HSA-MIR-509-1 0.002807 0.221
HSA-MIR-511-1 0.003417 0.229
HSA-MIR-514-2 0.003885 0.229
HSA-MIR-514-1 0.004895 0.229
Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S26.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 25
  NOT HISPANIC OR LATINO 461
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 523

  • Number of miRs = 550

  • Number of clinical features = 14

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)
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