Correlation between miRseq expression and clinical features
Stomach Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C11R6NKQ
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/C11R6NKQ
Overview
Introduction

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

Summary

Testing the association between 510 genes and 10 clinical features across 184 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 9 genes correlated to 'AGE'.

    • HSA-MIR-183 ,  HSA-MIR-100 ,  HSA-MIR-182 ,  HSA-LET-7C ,  HSA-MIR-96 ,  ...

  • 15 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-577 ,  HSA-MIR-33A ,  HSA-MIR-188 ,  HSA-MIR-937 ,  HSA-MIR-3127 ,  ...

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

    • HSA-MIR-548F-1 ,  HSA-MIR-7-3 ,  HSA-MIR-320A ,  HSA-MIR-3920

  • 3 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • HSA-LET-7F-2 ,  HSA-MIR-134 ,  HSA-MIR-26A-1

  • 13 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • HSA-LET-7F-2 ,  HSA-LET-7A-2 ,  HSA-LET-7A-1 ,  HSA-LET-7A-3 ,  HSA-MIR-628 ,  ...

  • 5 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-217 ,  HSA-MIR-125B-1 ,  HSA-MIR-516A-1 ,  HSA-MIR-199A-1 ,  HSA-MIR-24-2

  • No genes correlated to 'Time to Death', 'GENDER', 'DISTANT.METASTASIS', and 'NUMBER.OF.LYMPH.NODES'.

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=9 older N=3 younger N=6
GENDER t test   N=0        
HISTOLOGICAL TYPE ANOVA test N=15        
RADIATIONS RADIATION REGIMENINDICATION t test N=4 yes N=1 no N=3
DISTANT METASTASIS ANOVA test   N=0        
LYMPH NODE METASTASIS ANOVA test N=3        
COMPLETENESS OF RESECTION ANOVA test N=13        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE ANOVA test N=5        
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) 0.1-72.2 (median=1.3)
  censored N = 124
  death N = 20
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

9 genes related to 'AGE'.

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

AGE Mean (SD) 66.62 (11)
  Significant markers N = 9
  pos. correlated 3
  neg. correlated 6
List of 9 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of 9 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-183 0.3361 4.8e-06 0.00245
HSA-MIR-100 -0.323 1.162e-05 0.00591
HSA-MIR-182 0.3172 1.693e-05 0.0086
HSA-LET-7C -0.316 1.825e-05 0.00925
HSA-MIR-96 0.3066 3.315e-05 0.0168
HSA-MIR-99A -0.3057 3.517e-05 0.0178
HSA-MIR-195 -0.3013 4.588e-05 0.0231
HSA-MIR-218-2 -0.2952 6.639e-05 0.0334
HSA-MIR-125B-1 -0.2914 8.293e-05 0.0416

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-183 to 'AGE'. P value = 4.8e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 72
  MALE 112
     
  Significant markers N = 0
Clinical variable #4: 'HISTOLOGICAL.TYPE'

15 genes related to 'HISTOLOGICAL.TYPE'.

Table S5.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  STOMACH ADENOCARCINOMA DIFFUSE TYPE 28
  STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 89
  STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 38
  STOMACH INTESTINAL ADENOCARCINOMA TUBULAR TYPE 11
  STOMACH INTESTINAL ADENOCARCINOMA  MUCINOUS TYPE 11
  STOMACH INTESTINAL ADENOCARCINOMA  PAPILLARY TYPE 3
  STOMACH ADENOCARCINOMA SIGNET RING TYPE 2
     
  Significant markers N = 15
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-577 8.853e-07 0.000451
HSA-MIR-33A 1.402e-06 0.000713
HSA-MIR-188 6.547e-06 0.00333
HSA-MIR-937 8.041e-06 0.00408
HSA-MIR-3127 1.519e-05 0.00769
HSA-MIR-105-1 2.091e-05 0.0106
HSA-MIR-579 2.118e-05 0.0107
HSA-MIR-96 2.303e-05 0.0116
HSA-MIR-3651 2.899e-05 0.0146
HSA-MIR-100 3.729e-05 0.0187

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-577 to 'HISTOLOGICAL.TYPE'. P value = 8.85e-07 with ANOVA analysis.

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

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

Table S7.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 7
  YES 177
     
  Significant markers N = 4
  Higher in YES 1
  Higher in NO 3
List of 4 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8.  Get Full Table List of 4 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-548F-1 7.64 4.512e-06 0.00222 0.8889
HSA-MIR-7-3 -6.4 1.617e-05 0.00794 0.7884
HSA-MIR-320A -6.25 2.213e-05 0.0108 0.7732
HSA-MIR-3920 -6.33 8.998e-05 0.044 0.8112

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-548F-1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.51e-06 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S9.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 152
  M1 18
  MX 14
     
  Significant markers N = 0
Clinical variable #7: 'LYMPH.NODE.METASTASIS'

3 genes related to 'LYMPH.NODE.METASTASIS'.

Table S10.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 58
  N1 63
  N2 29
  N3 14
  N3A 9
  NX 11
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S11.  Get Full Table List of 3 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
HSA-LET-7F-2 2.21e-05 0.0113
HSA-MIR-134 6.325e-05 0.0322
HSA-MIR-26A-1 9.19e-05 0.0467

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-LET-7F-2 to 'LYMPH.NODE.METASTASIS'. P value = 2.21e-05 with ANOVA analysis.

Clinical variable #8: 'COMPLETENESS.OF.RESECTION'

13 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S12.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 126
  R1 9
  R2 12
  RX 25
     
  Significant markers N = 13
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
HSA-LET-7F-2 2.411e-16 1.23e-13
HSA-LET-7A-2 2.605e-13 1.33e-10
HSA-LET-7A-1 2.911e-13 1.48e-10
HSA-LET-7A-3 5.634e-13 2.86e-10
HSA-MIR-628 6.252e-13 3.16e-10
HSA-MIR-26A-1 3.513e-12 1.77e-09
HSA-MIR-361 2.674e-11 1.35e-08
HSA-MIR-106A 4.701e-10 2.36e-07
HSA-MIR-3605 7.049e-06 0.00354
HSA-LET-7E 4.588e-05 0.023

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-LET-7F-2 to 'COMPLETENESS.OF.RESECTION'. P value = 2.41e-16 with ANOVA analysis.

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

No gene related to 'NUMBER.OF.LYMPH.NODES'.

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

NUMBER.OF.LYMPH.NODES Mean (SD) 4.71 (6.6)
  Significant markers N = 0
Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

5 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S15.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 2
  STAGE IA 5
  STAGE IB 19
  STAGE II 29
  STAGE IIA 8
  STAGE IIB 14
  STAGE III 4
  STAGE IIIA 38
  STAGE IIIB 13
  STAGE IIIC 7
  STAGE IV 29
     
  Significant markers N = 5
List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S16.  Get Full Table List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
HSA-MIR-217 1.224e-05 0.00624
HSA-MIR-125B-1 2.845e-05 0.0145
HSA-MIR-516A-1 5.015e-05 0.0255
HSA-MIR-199A-1 7.145e-05 0.0362
HSA-MIR-24-2 9.166e-05 0.0464

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-217 to 'NEOPLASM.DISEASESTAGE'. P value = 1.22e-05 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 184

  • Number of genes = 510

  • 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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