Correlation between miRseq expression and clinical features
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 550 miRs and 14 clinical features across 518 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one miRs.

  • 30 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-412 ,  HSA-MIR-543 ,  HSA-MIR-377 ,  HSA-MIR-493 ,  HSA-MIR-99A ,  ...

  • 4 miRs correlated to 'NEOPLASM_DISEASESTAGE'.

    • HSA-MIR-139 ,  HSA-MIR-140 ,  HSA-MIR-206 ,  HSA-MIR-361

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

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

  • 16 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-187 ,  HSA-MIR-25 ,  HSA-MIR-584 ,  HSA-MIR-9-1 ,  ...

  • 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 'RADIATIONS_RADIATION_REGIMENINDICATION'.

    • HSA-MIR-660 ,  HSA-MIR-362 ,  HSA-LET-7F-2 ,  HSA-LET-7A-3 ,  HSA-LET-7A-2 ,  ...

  • 30 miRs correlated to 'NUMBER_PACK_YEARS_SMOKED'.

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

  • 30 miRs correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • HSA-MIR-548B ,  HSA-MIR-18A ,  HSA-MIR-450A-2 ,  HSA-MIR-451 ,  HSA-LET-7C ,  ...

  • 30 miRs correlated to 'NUMBER_OF_LYMPH_NODES'.

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

  • 13 miRs correlated to 'RACE'.

    • HSA-MIR-1304 ,  HSA-MIR-130B ,  HSA-MIR-508 ,  HSA-MIR-509-1 ,  HSA-MIR-509-3 ,  ...

  • No miRs correlated to 'YEARS_TO_BIRTH', '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 shorter survival N=25 longer survival N=5
YEARS_TO_BIRTH Spearman correlation test   N=0        
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=4        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=5 lower stage N=25
PATHOLOGY_N_STAGE Spearman correlation test N=16 higher stage N=9 lower stage N=7
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=30 yes N=30 no N=0
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=24 lower number_of_lymph_nodes N=6
RACE Kruskal-Wallis test N=13        
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=18.4)
  censored N = 316
  death N = 201
     
  Significant markers N = 30
  associated with shorter survival 25
  associated with longer survival 5
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-412 1.2 2.774e-05 0.012 0.583
HSA-MIR-543 1.27 5.337e-05 0.012 0.584
HSA-MIR-377 1.26 7.747e-05 0.012 0.578
HSA-MIR-493 1.28 8.386e-05 0.012 0.583
HSA-MIR-99A 0.83 0.0001115 0.012 0.402
HSA-MIR-758 1.25 0.0001597 0.012 0.575
HSA-MIR-410 1.23 0.0001802 0.012 0.572
HSA-MIR-337 1.23 0.0002343 0.012 0.582
HSA-MIR-379 1.27 0.0002365 0.012 0.575
HSA-MIR-654 1.22 0.0002402 0.012 0.578
Clinical variable #2: 'YEARS_TO_BIRTH'

No miR related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 60.92 (12)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

4 miRs related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 27
  STAGE II 77
  STAGE III 75
  STAGE IVA 257
  STAGE IVB 12
  STAGE IVC 1
     
  Significant markers N = 4
List of 4 miRs differentially expressed by 'NEOPLASM_DISEASESTAGE'

Table S5.  Get Full Table List of 4 miRs differentially expressed by 'NEOPLASM_DISEASESTAGE'

kruskal_wallis_P Q
HSA-MIR-139 8.173e-05 0.045
HSA-MIR-140 0.0009675 0.266
HSA-MIR-206 0.00149 0.271
HSA-MIR-361 0.001971 0.271
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) 2.87 (1)
  N
  T0 1
  T1 48
  T2 134
  T3 99
  T4 174
     
  Significant markers N = 30
  pos. correlated 5
  neg. correlated 25
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-150 -0.2258 1.107e-06 0.000609
HSA-MIR-146A -0.2027 1.283e-05 0.00353
HSA-MIR-206 -0.1969 2.33e-05 0.00427
HSA-MIR-128-1 -0.1821 9.183e-05 0.0126
HSA-MIR-363 -0.1783 0.0001291 0.0142
HSA-MIR-133A-1 -0.1728 0.0002186 0.0182
HSA-MIR-137 0.2032 0.0002314 0.0182
HSA-MIR-3065 0.1679 0.0003175 0.0196
HSA-MIR-181C -0.1677 0.0003212 0.0196
HSA-MIR-660 -0.1656 0.000384 0.0211
Clinical variable #5: 'PATHOLOGY_N_STAGE'

16 miRs related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 1.02 (0.95)
  N
  N0 176
  N1 66
  N2 168
  N3 8
     
  Significant markers N = 16
  pos. correlated 9
  neg. correlated 7
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-1293 -0.1916 9.285e-05 0.0511
HSA-MIR-203 -0.171 0.0004442 0.0802
HSA-MIR-3620 -0.233 0.000555 0.0802
HSA-MIR-548K 0.208 0.0005835 0.0802
HSA-MIR-542 0.1611 0.0009493 0.0962
HSA-MIR-421 0.1603 0.00105 0.0962
HSA-LET-7F-2 0.1509 0.001981 0.156
HSA-MIR-151 0.1478 0.002443 0.168
HSA-MIR-223 -0.1456 0.002856 0.175
HSA-MIR-195 0.1385 0.004556 0.227
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 183
  class1 1
     
  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 141
  MALE 377
     
  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-1293 18908 2.994e-06 0.00165 0.634
HSA-MIR-187 20200 4.221e-05 0.00721 0.6169
HSA-MIR-25 32747 4.744e-05 0.00721 0.616
HSA-MIR-584 20459 5.446e-05 0.00721 0.6151
HSA-MIR-9-1 32573 7.713e-05 0.00721 0.6128
HSA-MIR-9-2 32547 8.285e-05 0.00721 0.6123
HSA-MIR-130B 32468 0.0001028 0.00721 0.6108
HSA-MIR-561 8627 0.0001049 0.00721 0.6608
HSA-MIR-222 20783 0.0001324 0.00723 0.609
HSA-MIR-1180 32292 0.0001647 0.00723 0.6075
Clinical variable #8: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  HEAD AND NECK SQUAMOUS CELL CARCINOMA 507
  HEAD AND NECK SQUAMOUS CELL CARCINOMA SPINDLE CELL VARIANT 1
  HEAD AND NECK SQUAMOUS CELL CARCINOMA BASALOID TYPE 10
     
  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-9-1 0.0001458 0.0413
HSA-MIR-9-2 0.0001503 0.0413
HSA-MIR-92A-1 0.0002469 0.0453
HSA-MIR-141 0.0005081 0.0699
HSA-MIR-181C 0.0007006 0.0714
HSA-MIR-548B 0.0008865 0.0714
HSA-MIR-92A-2 0.0009089 0.0714
HSA-MIR-25 0.001442 0.0985
HSA-MIR-362 0.001661 0.0985
HSA-MIR-187 0.00179 0.0985
Clinical variable #9: 'RADIATIONS_RADIATION_REGIMENINDICATION'

30 miRs related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 82
  YES 436
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 miRs differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

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

W(pos if higher in 'YES') wilcoxontestP Q AUC
HSA-MIR-660 26973 2.568e-13 1.41e-10 0.7544
HSA-MIR-362 25578 5.886e-10 1.62e-07 0.7154
HSA-LET-7F-2 11127 5.729e-08 7.73e-06 0.6888
HSA-LET-7A-3 11205 8.125e-08 7.73e-06 0.6866
HSA-LET-7A-2 11223 8.803e-08 7.73e-06 0.6861
HSA-LET-7A-1 11235 9.284e-08 7.73e-06 0.6858
HSA-MIR-34A 24504 9.835e-08 7.73e-06 0.6854
HSA-MIR-143 11301 1.243e-07 8.54e-06 0.6839
HSA-MIR-19B-2 24326 2.142e-07 1.31e-05 0.6804
HSA-MIR-19A 24251 2.955e-07 1.63e-05 0.6783
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

30 miRs related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 45.05 (35)
  Significant markers N = 30
  pos. correlated 27
  neg. correlated 3
List of top 10 miRs differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

Table S18.  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 0.2896 5.462e-07 3e-04
HSA-MIR-1180 0.2402 3.696e-05 0.00914
HSA-MIR-3677 0.2324 6.64e-05 0.00914
HSA-MIR-1266 0.2377 6.647e-05 0.00914
HSA-MIR-151 0.2287 8.756e-05 0.00963
HSA-MIR-744 0.2234 0.0001278 0.0115
HSA-MIR-940 0.222 0.0001459 0.0115
HSA-MIR-1224 0.2921 0.0003823 0.0263
HSA-MIR-1249 0.193 0.0009752 0.0493
HSA-MIR-3130-1 0.1917 0.001171 0.0493
Clinical variable #11: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

30 miRs related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1967.03 (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 S20.  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 0.2726 6.798e-05 0.0374
HSA-MIR-18A 0.2104 0.0004343 0.0916
HSA-MIR-450A-2 0.2089 0.0004996 0.0916
HSA-MIR-451 0.1936 0.001231 0.118
HSA-LET-7C -0.1904 0.001483 0.118
HSA-MIR-19B-2 0.1875 0.001753 0.118
HSA-MIR-125B-2 -0.1858 0.001935 0.118
HSA-MIR-152 -0.1798 0.002722 0.118
HSA-MIR-3177 0.2796 0.00283 0.118
HSA-MIR-1295 -0.1899 0.003086 0.118
Clinical variable #12: '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) 2.2 (4.3)
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
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-1293 -0.2168 1.251e-05 0.00397
HSA-MIR-151 0.2137 1.445e-05 0.00397
HSA-MIR-421 0.2032 4.039e-05 0.00741
HSA-LET-7F-2 0.1938 8.637e-05 0.0117
HSA-MIR-411 0.1913 0.0001068 0.0117
HSA-MIR-143 0.1875 0.0001468 0.0135
HSA-MIR-542 0.1818 0.0002356 0.0163
HSA-MIR-654 0.1799 0.0002736 0.0163
HSA-MIR-203 -0.1799 0.0002744 0.0163
HSA-MIR-379 0.1789 0.0002964 0.0163
Clinical variable #13: 'RACE'

13 miRs related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 2
  ASIAN 11
  BLACK OR AFRICAN AMERICAN 44
  WHITE 444
     
  Significant markers N = 13
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-1304 5.756e-06 0.00317
HSA-MIR-130B 0.0002284 0.0628
HSA-MIR-508 0.0008724 0.16
HSA-MIR-509-1 0.001572 0.216
HSA-MIR-509-3 0.002251 0.227
HSA-MIR-98 0.00281 0.227
HSA-MIR-152 0.003279 0.227
HSA-MIR-514-1 0.003307 0.227
HSA-MIR-511-2 0.004024 0.246
HSA-MIR-511-1 0.004924 0.249
Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 25
  NOT HISPANIC OR LATINO 456
     
  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 = 518

  • Number of miRs = 550

  • 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.

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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