Correlation between miRseq expression and clinical features
Stomach Adenocarcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C100003D
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Stomach Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C100003D
Overview
Introduction

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

Summary

Testing the association between 515 genes and 11 clinical features across 167 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 2 genes correlated to 'AGE'.

    • HSA-MIR-100 ,  HSA-MIR-183

  • 74 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-16-1 ,  HSA-MIR-424 ,  HSA-MIR-191 ,  HSA-MIR-320A ,  HSA-MIR-26B ,  ...

  • 2 genes correlated to 'PATHOLOGY.T'.

    • HSA-MIR-200B ,  HSA-MIR-200C

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

    • HSA-MIR-23A ,  HSA-MIR-3150 ,  HSA-MIR-559 ,  HSA-MIR-548F-1 ,  HSA-MIR-361

  • 10 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 ,  ...

  • No genes correlated to 'Time to Death', 'GENDER', 'PATHOLOGY.N', 'PATHOLOGICSPREAD(M)', 'TUMOR.STAGE', 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=2 older N=1 younger N=1
GENDER t test   N=0        
HISTOLOGICAL TYPE ANOVA test N=74        
PATHOLOGY T Spearman correlation test N=2 higher pT N=0 lower pT N=2
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test   N=0        
TUMOR STAGE Spearman correlation test   N=0        
RADIATIONS RADIATION REGIMENINDICATION t test N=5 yes N=4 no N=1
COMPLETENESS OF RESECTION ANOVA test N=10        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
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=1.5)
  censored N = 112
  death N = 18
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

2 genes related to 'AGE'.

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

AGE Mean (SD) 67.47 (11)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-100 -0.3227 3.162e-05 0.0163
HSA-MIR-183 0.3216 3.363e-05 0.0173

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-100 to 'AGE'. P value = 3.16e-05 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 66
  MALE 101
     
  Significant markers N = 0
Clinical variable #4: 'HISTOLOGICAL.TYPE'

74 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  STOMACH ADENOCARCINOMA DIFFUSE TYPE 6
  STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 7
  STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 8
  STOMACH INTESTINAL ADENOCARCINOMA  MUCINOUS TYPE 2
  STOMACH ADENOCARCINOMA SIGNET RING TYPE 1
  STOMACH ADENOCARCINOMA - DIFFUSE TYPE 16
  STOMACH ADENOCARCINOMA - NOT OTHERWISE SPECIFIED (NOS) 73
  STOMACH INTESTINAL ADENOCARCINOMA - MUCINOUS TYPE 8
  STOMACH INTESTINAL ADENOCARCINOMA - PAPILLARY TYPE 3
  STOMACH INTESTINAL ADENOCARCINOMA - TUBULAR TYPE 10
  STOMACH INTESTINAL ADENOCARCINOMA - TYPE NOT OTHERWISE SPECIFIED (NOS) 28
     
  Significant markers N = 74
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-16-1 2.17e-09 1.12e-06
HSA-MIR-424 3.566e-09 1.83e-06
HSA-MIR-191 7.255e-09 3.72e-06
HSA-MIR-320A 8.608e-09 4.41e-06
HSA-MIR-26B 1.225e-08 6.26e-06
HSA-MIR-7-1 2.568e-08 1.31e-05
HSA-MIR-425 2.926e-08 1.49e-05
HSA-MIR-3647 3.382e-08 1.72e-05
HSA-MIR-103-2 8.034e-08 4.07e-05
HSA-MIR-590 1.45e-07 7.34e-05

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-16-1 to 'HISTOLOGICAL.TYPE'. P value = 2.17e-09 with ANOVA analysis.

Clinical variable #5: 'PATHOLOGY.T'

2 genes related to 'PATHOLOGY.T'.

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

PATHOLOGY.T Mean (SD) 2.65 (0.77)
  N
  T1 6
  T2 52
  T3 57
  T4 18
     
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S8.  Get Full Table List of 2 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-200B -0.3574 2.414e-05 0.0124
HSA-MIR-200C -0.3458 4.569e-05 0.0235

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-200B to 'PATHOLOGY.T'. P value = 2.41e-05 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 1.06 (0.99)
  N
  N0 45
  N1 49
  N2 23
  N3 15
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGICSPREAD(M)'

No gene related to 'PATHOLOGICSPREAD(M)'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 119
  M1 16
  MX 8
     
  Significant markers N = 0
Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.53 (1)
  N
  Stage 1 24
  Stage 2 38
  Stage 3 39
  Stage 4 26
     
  Significant markers N = 0
Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S12.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 5
  YES 162
     
  Significant markers N = 5
  Higher in YES 4
  Higher in NO 1
List of 5 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S13.  Get Full Table List of 5 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-23A 11.6 1.161e-17 5.38e-15 0.8691
HSA-MIR-3150 6.27 2.34e-07 0.000108 0.8129
HSA-MIR-559 6.69 7.299e-05 0.0336 0.8441
HSA-MIR-548F-1 7.29 7.998e-05 0.0368 0.8943
HSA-MIR-361 -5.37 9.291e-05 0.0426 0.7395

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-23A to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.16e-17 with T-test analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

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

Table S14.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 111
  R1 7
  R2 12
  RX 25
     
  Significant markers N = 10
List of 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S15.  Get Full Table List of 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
HSA-LET-7F-2 2.313e-15 1.19e-12
HSA-LET-7A-2 5.889e-13 3.03e-10
HSA-LET-7A-1 6.495e-13 3.33e-10
HSA-LET-7A-3 1.251e-12 6.41e-10
HSA-MIR-628 4.247e-11 2.17e-08
HSA-MIR-26A-1 9.944e-11 5.07e-08
HSA-MIR-361 4.319e-10 2.2e-07
HSA-MIR-106A 3.251e-09 1.65e-06
HSA-MIR-3605 3.712e-05 0.0188
HSA-LET-7E 4.953e-05 0.0251

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 = 2.31e-15 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

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

Table S16.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 4.17 (5.8)
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 167

  • Number of genes = 515

  • Number of clinical features = 11

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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