Correlation between miRseq expression and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C11834J3
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C11834J3
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 551 genes and 10 clinical features across 327 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 8 genes correlated to 'Time to Death'.

    • HSA-MIR-377 ,  HSA-MIR-337 ,  HSA-MIR-493 ,  HSA-MIR-154 ,  HSA-MIR-654 ,  ...

  • 3 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • HSA-MIR-1274B ,  HSA-MIR-374A ,  HSA-MIR-660

  • 2 genes correlated to 'NUMBERPACKYEARSSMOKED'.

    • HSA-MIR-1180 ,  HSA-MIR-183

  • 1 gene correlated to 'DISTANT.METASTASIS'.

    • HSA-MIR-184

  • 1 gene correlated to 'LYMPH.NODE.METASTASIS'.

    • HSA-MIR-195

  • 2 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

    • HSA-MIR-411 ,  HSA-MIR-195

  • No genes correlated to 'AGE', 'GENDER', 'YEAROFTOBACCOSMOKINGONSET', and 'NEOPLASM.DISEASESTAGE'.

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 genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test N=8 shorter survival N=8 longer survival N=0
AGE Spearman correlation test   N=0        
GENDER t test   N=0        
RADIATIONS RADIATION REGIMENINDICATION t test N=3 yes N=2 no N=1
NUMBERPACKYEARSSMOKED Spearman correlation test N=2 higher numberpackyearssmoked N=2 lower numberpackyearssmoked N=0
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
DISTANT METASTASIS t test N=1 mx N=0 m0 N=1
LYMPH NODE METASTASIS ANOVA test N=1        
NUMBER OF LYMPH NODES Spearman correlation test N=2 higher number.of.lymph.nodes N=2 lower number.of.lymph.nodes N=0
NEOPLASM DISEASESTAGE ANOVA test   N=0        
Clinical variable #1: 'Time to Death'

8 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0.1-210.9 (median=14.3)
  censored N = 200
  death N = 123
     
  Significant markers N = 8
  associated with shorter survival 8
  associated with longer survival 0
List of 8 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 8 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-377 1.46 1.515e-06 0.00083 0.635
HSA-MIR-337 1.4 1.008e-05 0.0055 0.634
HSA-MIR-493 1.45 1.44e-05 0.0079 0.631
HSA-MIR-154 1.43 1.833e-05 0.01 0.629
HSA-MIR-654 1.38 1.855e-05 0.01 0.626
HSA-MIR-382 1.47 4.738e-05 0.026 0.623
HSA-MIR-758 1.39 4.973e-05 0.027 0.614
HSA-MIR-127 1.47 6.521e-05 0.035 0.621

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-377 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.51e-06 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 61.13 (12)
  Significant markers N = 0
Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 92
  MALE 235
     
  Significant markers N = 0
Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S5.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 79
  YES 248
     
  Significant markers N = 3
  Higher in YES 2
  Higher in NO 1
List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S6.  Get Full Table List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-1274B 5.11 1.144e-06 0.000631 0.6809
HSA-MIR-374A -4.86 3.28e-06 0.0018 0.6632
HSA-MIR-660 4.52 1.309e-05 0.00718 0.6677

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-1274B to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.14e-06 with T-test analysis.

Clinical variable #5: 'NUMBERPACKYEARSSMOKED'

2 genes related to 'NUMBERPACKYEARSSMOKED'.

Table S7.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 50.28 (41)
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

Table S8.  Get Full Table List of 2 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1180 0.3032 3.017e-05 0.0166
HSA-MIR-183 0.2994 3.823e-05 0.021

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-1180 to 'NUMBERPACKYEARSSMOKED'. P value = 3.02e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #6: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1965.07 (12)
  Significant markers N = 0
Clinical variable #7: 'DISTANT.METASTASIS'

One gene related to 'DISTANT.METASTASIS'.

Table S10.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 63
  MX 6
     
  Significant markers N = 1
  Higher in MX 0
  Higher in M0 1
List of one gene differentially expressed by 'DISTANT.METASTASIS'

Table S11.  Get Full Table List of one gene differentially expressed by 'DISTANT.METASTASIS'

T(pos if higher in 'MX') ttestP Q AUC
HSA-MIR-184 -7.91 7.547e-08 3.83e-05 0.937

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-184 to 'DISTANT.METASTASIS'. P value = 7.55e-08 with T-test analysis.

Clinical variable #8: 'LYMPH.NODE.METASTASIS'

One gene related to 'LYMPH.NODE.METASTASIS'.

Table S12.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 106
  N1 38
  N2 7
  N2A 4
  N2B 59
  N2C 34
  N3 5
  NX 64
     
  Significant markers N = 1
List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S13.  Get Full Table List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
HSA-MIR-195 7.163e-05 0.0395

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-195 to 'LYMPH.NODE.METASTASIS'. P value = 7.16e-05 with ANOVA analysis.

Clinical variable #9: 'NUMBER.OF.LYMPH.NODES'

2 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S14.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.61 (5.2)
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S15.  Get Full Table List of 2 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-411 0.2512 7.27e-05 0.0401
HSA-MIR-195 0.2495 8.175e-05 0.045

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-411 to 'NUMBER.OF.LYMPH.NODES'. P value = 7.27e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S16.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 20
  STAGE II 51
  STAGE III 47
  STAGE IVA 156
  STAGE IVB 6
     
  Significant markers N = 0
Methods & Data
Input

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

  • Clinical data file = HNSC-TP.clin.merged.picked.txt

  • Number of patients = 327

  • Number of genes = 551

  • Number of clinical features = 10

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

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

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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