Correlation between miRseq expression and clinical features
Thyroid Adenocarcinoma (Mut_BRAF)
01 July 2013  |  awg_thca__2013_07_01
Maintainer Information
Citation Information
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/C1J964HS
Overview
Introduction

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

Summary

Testing the association between 513 genes and 14 clinical features across 228 samples, statistically thresholded by Q value < 0.05, 11 clinical features related to at least one genes.

  • 7 genes correlated to 'AGE'.

    • HSA-MIR-653 ,  HSA-MIR-1229 ,  HSA-MIR-376A-1 ,  HSA-MIR-181A-2 ,  HSA-MIR-154 ,  ...

  • 1 gene correlated to 'GENDER'.

    • HSA-MIR-651

  • 3 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-21 ,  HSA-MIR-1224 ,  HSA-MIR-598

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

    • HSA-MIR-374A ,  HSA-MIR-1251 ,  HSA-MIR-2355 ,  HSA-MIR-19A ,  HSA-MIR-1266 ,  ...

  • 1 gene correlated to 'RADIATIONEXPOSURE'.

    • HSA-MIR-548J

  • 1 gene correlated to 'DISTANT.METASTASIS'.

    • HSA-MIR-151

  • 1 gene correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • HSA-MIR-411

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • HSA-MIR-1179

  • 4 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-376C ,  HSA-MIR-539 ,  HSA-MIR-487B ,  HSA-MIR-494

  • 1 gene correlated to 'MULTIFOCALITY'.

    • HSA-MIR-132

  • 2 genes correlated to 'TUMOR.SIZE'.

    • HSA-MIR-126 ,  HSA-MIR-145

  • No genes correlated to 'Time to Death', 'LYMPH.NODE.METASTASIS', and 'COMPLETENESS.OF.RESECTION'.

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=0        
AGE Spearman correlation test N=7 older N=6 younger N=1
GENDER t test N=1 male N=0 female N=1
HISTOLOGICAL TYPE ANOVA test N=3        
RADIATIONS RADIATION REGIMENINDICATION t test N=6 yes N=4 no N=2
RADIATIONEXPOSURE t test N=1 yes N=1 no N=0
DISTANT METASTASIS ANOVA test N=1        
EXTRATHYROIDAL EXTENSION ANOVA test N=1        
LYMPH NODE METASTASIS ANOVA test   N=0        
COMPLETENESS OF RESECTION ANOVA test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=0 lower number.of.lymph.nodes N=1
NEOPLASM DISEASESTAGE ANOVA test N=4        
MULTIFOCALITY t test N=1 unifocal N=0 multifocal N=1
TUMOR SIZE Spearman correlation test N=2 higher tumor.size N=0 lower tumor.size N=2
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

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

Time to Death Duration (Months) 0-158.8 (median=15.1)
  censored N = 221
  death N = 5
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

7 genes related to 'AGE'.

Table S2.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 46.9 (15)
  Significant markers N = 7
  pos. correlated 6
  neg. correlated 1
List of 7 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of 7 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-653 0.3363 1.965e-07 0.000101
HSA-MIR-1229 0.3393 2.025e-06 0.00104
HSA-MIR-376A-1 0.3823 2.666e-06 0.00136
HSA-MIR-181A-2 -0.3049 2.732e-06 0.00139
HSA-MIR-154 0.3116 4.379e-06 0.00223
HSA-MIR-425 0.2738 2.767e-05 0.0141
HSA-MIR-514B 0.3295 5.843e-05 0.0296

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-653 to 'AGE'. P value = 1.96e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

One gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 168
  MALE 60
     
  Significant markers N = 1
  Higher in MALE 0
  Higher in FEMALE 1
List of one gene differentially expressed by 'GENDER'

Table S5.  Get Full Table List of one gene differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
HSA-MIR-651 -5.01 2.961e-06 0.00152 0.7307

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-651 to 'GENDER'. P value = 2.96e-06 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

3 genes related to 'HISTOLOGICAL.TYPE'.

Table S6.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  OTHER SPECIFY 3
  THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL 183
  THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) 16
  THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) 26
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-21 1.117e-06 0.000573
HSA-MIR-1224 2.199e-05 0.0113
HSA-MIR-598 2.447e-05 0.0125

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-21 to 'HISTOLOGICAL.TYPE'. P value = 1.12e-06 with ANOVA analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S8.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 11
  YES 217
     
  Significant markers N = 6
  Higher in YES 4
  Higher in NO 2
List of 6 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S9.  Get Full Table List of 6 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-374A -9.85 6.91e-08 3.44e-05 0.9376
HSA-MIR-1251 6.93 4.783e-06 0.00238 0.8467
HSA-MIR-2355 7.05 5.03e-06 0.00249 0.8626
HSA-MIR-19A 6.16 6.343e-06 0.00314 0.7537
HSA-MIR-1266 -6.03 6.959e-05 0.0344 0.8898
HSA-MIR-135A-2 5.36 9.888e-05 0.0487 0.7918

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-374A to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 6.91e-08 with T-test analysis.

Clinical variable #6: 'RADIATIONEXPOSURE'

One gene related to 'RADIATIONEXPOSURE'.

Table S10.  Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'

RADIATIONEXPOSURE Labels N
  NO 196
  YES 8
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one gene differentially expressed by 'RADIATIONEXPOSURE'

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

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-548J 7.69 1.863e-10 9.13e-08 0.734

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-548J to 'RADIATIONEXPOSURE'. P value = 1.86e-10 with T-test analysis.

Clinical variable #7: 'DISTANT.METASTASIS'

One gene related to 'DISTANT.METASTASIS'.

Table S12.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 131
  M1 4
  MX 93
     
  Significant markers N = 1
List of one gene differentially expressed by 'DISTANT.METASTASIS'

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

ANOVA_P Q
HSA-MIR-151 3.179e-06 0.00163

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-151 to 'DISTANT.METASTASIS'. P value = 3.18e-06 with ANOVA analysis.

Clinical variable #8: 'EXTRATHYROIDAL.EXTENSION'

One gene related to 'EXTRATHYROIDAL.EXTENSION'.

Table S14.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 75
  MODERATE/ADVANCED (T4A) 9
  NONE 139
     
  Significant markers N = 1
List of one gene differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

Table S15.  Get Full Table List of one gene differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

ANOVA_P Q
HSA-MIR-411 2.406e-05 0.0123

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-411 to 'EXTRATHYROIDAL.EXTENSION'. P value = 2.41e-05 with ANOVA analysis.

Clinical variable #9: 'LYMPH.NODE.METASTASIS'

No gene related to 'LYMPH.NODE.METASTASIS'.

Table S16.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 92
  N1 27
  N1A 55
  N1B 33
  NX 21
     
  Significant markers N = 0
Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

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

Table S17.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 181
  R1 22
  R2 1
  RX 13
     
  Significant markers N = 0
Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S18.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 3.52 (5.6)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S19.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-1179 -0.309 5.393e-05 0.0277

Figure S8.  Get High-res Image As an example, this figure shows the association of HSA-MIR-1179 to 'NUMBER.OF.LYMPH.NODES'. P value = 5.39e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

4 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S20.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 131
  STAGE II 16
  STAGE III 55
  STAGE IVA 22
  STAGE IVC 3
     
  Significant markers N = 4
List of 4 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S21.  Get Full Table List of 4 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-376C 2.974e-05 0.0153
HSA-MIR-539 3.724e-05 0.0191
HSA-MIR-487B 4.543e-05 0.0232
HSA-MIR-494 5.722e-05 0.0292

Figure S9.  Get High-res Image As an example, this figure shows the association of HSA-MIR-376C to 'NEOPLASM.DISEASESTAGE'. P value = 2.97e-05 with ANOVA analysis.

Clinical variable #13: 'MULTIFOCALITY'

One gene related to 'MULTIFOCALITY'.

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

MULTIFOCALITY Labels N
  MULTIFOCAL 104
  UNIFOCAL 121
     
  Significant markers N = 1
  Higher in UNIFOCAL 0
  Higher in MULTIFOCAL 1
List of one gene differentially expressed by 'MULTIFOCALITY'

Table S23.  Get Full Table List of one gene differentially expressed by 'MULTIFOCALITY'

T(pos if higher in 'UNIFOCAL') ttestP Q AUC
HSA-MIR-132 -3.99 8.934e-05 0.0458 0.6546

Figure S10.  Get High-res Image As an example, this figure shows the association of HSA-MIR-132 to 'MULTIFOCALITY'. P value = 8.93e-05 with T-test analysis.

Clinical variable #14: 'TUMOR.SIZE'

2 genes related to 'TUMOR.SIZE'.

Table S24.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 2.83 (1.6)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S25.  Get Full Table List of 2 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-126 -0.2976 3.88e-05 0.0199
HSA-MIR-145 -0.2866 7.636e-05 0.0391

Figure S11.  Get High-res Image As an example, this figure shows the association of HSA-MIR-126 to 'TUMOR.SIZE'. P value = 3.88e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input
  • Expresson data file = THCA-Mut_BRAF.miRseq_RPKM_log2.txt

  • Clinical data file = THCA-Mut_BRAF.clin.merged.picked.txt

  • Number of patients = 228

  • Number of genes = 513

  • 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

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)