Correlation between miRseq expression and clinical features
Lung Squamous Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1W094QM
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 543 miRs and 14 clinical features across 396 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

  • 7 miRs correlated to 'Time to Death'.

    • HSA-MIR-628 ,  HSA-MIR-3605 ,  HSA-MIR-185 ,  HSA-MIR-99B ,  HSA-MIR-128-2 ,  ...

  • 5 miRs correlated to 'AGE'.

    • HSA-MIR-99A ,  HSA-LET-7C ,  HSA-MIR-10A ,  HSA-MIR-125B-2 ,  HSA-MIR-100

  • 2 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-23C ,  HSA-MIR-126

  • 13 miRs correlated to 'PATHOLOGY.M.STAGE'.

    • HSA-MIR-26A-1 ,  HSA-MIR-140 ,  HSA-MIR-16-1 ,  HSA-MIR-361 ,  HSA-MIR-1277 ,  ...

  • 2 miRs correlated to 'GENDER'.

    • HSA-MIR-375 ,  HSA-MIR-516A-1

  • 50 miRs correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • HSA-MIR-26A-1 ,  HSA-MIR-628 ,  HSA-MIR-3653 ,  HSA-MIR-3647 ,  HSA-MIR-140 ,  ...

  • 2 miRs correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-29A ,  HSA-MIR-17

  • 2 miRs correlated to 'RACE'.

    • HSA-MIR-1269 ,  HSA-MIR-412

  • No miRs correlated to 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'COMPLETENESS.OF.RESECTION', 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
Time to Death Cox regression test N=7 shorter survival N=4 longer survival N=3
AGE Spearman correlation test N=5 older N=5 younger N=0
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=2        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE Kruskal-Wallis test N=13        
GENDER Wilcoxon test N=2 male N=2 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=50 higher score N=6 lower score N=44
HISTOLOGICAL TYPE Kruskal-Wallis test N=2        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test N=2        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

7 miRs related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Years) 1-5287 (median=639)
  censored N = 254
  death N = 109
     
  Significant markers N = 7
  associated with shorter survival 4
  associated with longer survival 3
List of 7 miRs differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of 7 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-628 1.26 6.406e-05 0.035 0.686
HSA-MIR-3605 1.41 8.086e-05 0.044 0.659
HSA-MIR-185 0.56 9.808e-05 0.053 0.374
HSA-MIR-99B 1.59 0.0001119 0.06 0.605
HSA-MIR-128-2 0.63 0.0001977 0.11 0.373
HSA-MIR-128-1 0.61 0.0002192 0.12 0.375
HSA-MIR-3607 1.25 0.0004998 0.27 0.65
Clinical variable #2: 'AGE'

5 miRs related to 'AGE'.

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

AGE Mean (SD) 67.37 (8.7)
  Significant markers N = 5
  pos. correlated 5
  neg. correlated 0
List of 5 miRs differentially expressed by 'AGE'

Table S4.  Get Full Table List of 5 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-99A 0.2107 2.804e-05 0.0152
HSA-LET-7C 0.2086 3.385e-05 0.0183
HSA-MIR-10A 0.1958 0.0001011 0.0547
HSA-MIR-125B-2 0.1784 0.000414 0.224
HSA-MIR-100 0.1757 0.0005003 0.27
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

2 miRs related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 2
  STAGE IA 68
  STAGE IB 128
  STAGE II 1
  STAGE IIA 49
  STAGE IIB 69
  STAGE IIIA 55
  STAGE IIIB 17
  STAGE IV 5
     
  Significant markers N = 2
List of 2 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of 2 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-23C 0.0003019 0.164
HSA-MIR-126 0.0004467 0.242
Clinical variable #4: 'PATHOLOGY.T.STAGE'

No miR related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.97 (0.73)
  N
  1 92
  2 240
  3 46
  4 18
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

No miR related to 'PATHOLOGY.N.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.48 (0.7)
  N
  0 244
  1 107
  2 35
  3 4
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

13 miRs related to 'PATHOLOGY.M.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 336
  M1 4
  M1A 1
  MX 49
     
  Significant markers N = 13
List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-26A-1 9.82e-07 0.000533
HSA-MIR-140 8.379e-06 0.00454
HSA-MIR-16-1 1.6e-05 0.00866
HSA-MIR-361 3.884e-05 0.021
HSA-MIR-1277 3.96e-05 0.0213
HSA-MIR-3615 0.0001735 0.0933
HSA-MIR-627 0.0001985 0.107
HSA-MIR-106A 0.000204 0.109
HSA-MIR-181A-1 0.0002776 0.149
HSA-MIR-628 0.0003647 0.195
Clinical variable #7: 'GENDER'

2 miRs related to 'GENDER'.

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

GENDER Labels N
  FEMALE 101
  MALE 295
     
  Significant markers N = 2
  Higher in MALE 2
  Higher in FEMALE 0
List of 2 miRs differentially expressed by 'GENDER'

Table S12.  Get Full Table List of 2 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-375 11040 0.0001024 0.0556 0.6295
HSA-MIR-516A-1 6355 0.0003593 0.195 0.6568
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

50 miRs related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S13.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 53.14 (42)
  Significant markers N = 50
  pos. correlated 6
  neg. correlated 44
List of top 10 miRs differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S14.  Get Full Table List of top 10 miRs significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-26A-1 -0.6367 5.763e-11 3.13e-08
HSA-MIR-628 -0.596 1.413e-09 7.66e-07
HSA-MIR-3653 -0.568 1.172e-08 6.34e-06
HSA-MIR-3647 -0.5555 2.829e-08 1.53e-05
HSA-MIR-140 0.5551 2.903e-08 1.56e-05
HSA-MIR-3607 -0.547 5.052e-08 2.72e-05
HSA-MIR-30E -0.5446 5.957e-08 3.2e-05
HSA-MIR-186 -0.508 5.96e-07 0.000319
HSA-LET-7G -0.497 1.132e-06 0.000605
HSA-MIR-3605 -0.4862 2.077e-06 0.00111
Clinical variable #9: 'HISTOLOGICAL.TYPE'

2 miRs related to 'HISTOLOGICAL.TYPE'.

Table S15.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG BASALOID SQUAMOUS CELL CARCINOMA 10
  LUNG PAPILLARY SQUAMOUS CELL CARICNOMA 6
  LUNG SMALL CELL SQUAMOUS CELL CARCINOMA 1
  LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 379
     
  Significant markers N = 2
List of 2 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

Table S16.  Get Full Table List of 2 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-29A 0.0001771 0.0962
HSA-MIR-17 0.0004371 0.237
Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No miR related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S17.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 12
  YES 384
     
  Significant markers N = 0
Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No miR related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 53.57 (32)
  Significant markers N = 0
Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

No miR related to 'COMPLETENESS.OF.RESECTION'.

Table S19.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 322
  R1 7
  R2 3
  RX 16
     
  Significant markers N = 0
Clinical variable #13: 'RACE'

2 miRs related to 'RACE'.

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

RACE Labels N
  ASIAN 9
  BLACK OR AFRICAN AMERICAN 16
  WHITE 282
     
  Significant markers N = 2
List of 2 miRs differentially expressed by 'RACE'

Table S21.  Get Full Table List of 2 miRs differentially expressed by 'RACE'

ANOVA_P Q
HSA-MIR-1269 8.238e-05 0.0447
HSA-MIR-412 0.000251 0.136
Clinical variable #14: 'ETHNICITY'

No miR related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 252
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = LUSC-TP.miRseq_RPKM_log2.txt

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

  • Number of patients = 396

  • Number of miRs = 543

  • Number of clinical features = 14

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

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] 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)