Correlation between miRseq expression and clinical features
Lung Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1VX0DV9
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/C1VX0DV9
Overview
Introduction

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

Summary

Testing the association between 530 genes and 13 clinical features across 447 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 1 gene correlated to 'AGE'.

    • HSA-MIR-29C

  • 9 genes correlated to 'PATHOLOGY.T.STAGE'.

    • HSA-MIR-30C-2 ,  HSA-MIR-451 ,  HSA-MIR-150 ,  HSA-MIR-146A ,  HSA-MIR-101-2 ,  ...

  • 6 genes correlated to 'PATHOLOGY.M.STAGE'.

    • HSA-MIR-628 ,  HSA-MIR-21 ,  HSA-MIR-660 ,  HSA-MIR-532 ,  HSA-MIR-374A ,  ...

  • 2 genes correlated to 'GENDER'.

    • HSA-MIR-105-2 ,  HSA-MIR-105-1

  • 1 gene correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • HSA-MIR-940

  • 9 genes correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-194-1 ,  HSA-MIR-194-2 ,  HSA-MIR-21 ,  HSA-MIR-192 ,  HSA-MIR-215 ,  ...

  • 5 genes correlated to 'NUMBERPACKYEARSSMOKED'.

    • HSA-MIR-210 ,  HSA-MIR-345 ,  HSA-MIR-296 ,  HSA-MIR-339 ,  HSA-MIR-31

  • No genes correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.N.STAGE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'YEAROFTOBACCOSMOKINGONSET', 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=1 older N=1 younger N=0
NEOPLASM DISEASESTAGE ANOVA test   N=0        
PATHOLOGY T STAGE Spearman correlation test N=9 higher stage N=0 lower stage N=9
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=6        
GENDER t test N=2 male N=2 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=1 higher score N=0 lower score N=1
HISTOLOGICAL TYPE ANOVA test N=9        
RADIATIONS RADIATION REGIMENINDICATION t test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test N=5 higher numberpackyearssmoked N=5 lower numberpackyearssmoked N=0
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
COMPLETENESS OF RESECTION ANOVA 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) 0-224 (median=12.2)
  censored N = 298
  death N = 116
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

One gene related to 'AGE'.

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

AGE Mean (SD) 65.46 (9.8)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
HSA-MIR-29C 0.1912 8.564e-05 0.0454

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-29C to 'AGE'. P value = 8.56e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 3
  STAGE IA 110
  STAGE IB 130
  STAGE IIA 43
  STAGE IIB 62
  STAGE IIIA 66
  STAGE IIIB 11
  STAGE IV 21
     
  Significant markers N = 0
Clinical variable #4: 'PATHOLOGY.T.STAGE'

9 genes related to 'PATHOLOGY.T.STAGE'.

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.86 (0.74)
  N
  1 138
  2 249
  3 39
  4 18
     
  Significant markers N = 9
  pos. correlated 0
  neg. correlated 9
List of 9 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S6.  Get Full Table List of 9 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-30C-2 -0.2174 3.78e-06 0.002
HSA-MIR-451 -0.2021 1.787e-05 0.00945
HSA-MIR-150 -0.2004 2.105e-05 0.0111
HSA-MIR-146A -0.1982 2.585e-05 0.0136
HSA-MIR-101-2 -0.1972 2.866e-05 0.0151
HSA-MIR-342 -0.1875 7.037e-05 0.0369
HSA-MIR-598 -0.1867 7.741e-05 0.0406
HSA-MIR-374B -0.1862 7.895e-05 0.0413
HSA-MIR-486 -0.1843 9.413e-05 0.0491

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-30C-2 to 'PATHOLOGY.T.STAGE'. P value = 3.78e-06 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

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

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.52 (0.77)
  N
  0 283
  1 83
  2 68
  3 2
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

6 genes related to 'PATHOLOGY.M.STAGE'.

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

PATHOLOGY.M.STAGE Labels N
  M0 308
  M1 16
  M1A 1
  M1B 3
  MX 115
     
  Significant markers N = 6
List of 6 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S9.  Get Full Table List of 6 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-628 1.29e-06 0.000684
HSA-MIR-21 4.823e-06 0.00255
HSA-MIR-660 1.817e-05 0.00959
HSA-MIR-532 2.563e-05 0.0135
HSA-MIR-374A 2.754e-05 0.0145
HSA-MIR-340 3.909e-05 0.0205

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-628 to 'PATHOLOGY.M.STAGE'. P value = 1.29e-06 with ANOVA analysis.

Clinical variable #7: 'GENDER'

2 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 240
  MALE 207
     
  Significant markers N = 2
  Higher in MALE 2
  Higher in FEMALE 0
List of 2 genes differentially expressed by 'GENDER'

Table S11.  Get Full Table List of 2 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
HSA-MIR-105-2 4.99 1.154e-06 0.000612 0.6675
HSA-MIR-105-1 4.13 4.783e-05 0.0253 0.6476

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-105-2 to 'GENDER'. P value = 1.15e-06 with T-test analysis.

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

One gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S12.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 83.7 (23)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

Table S13.  Get Full Table List of one gene significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-940 -0.4727 2.752e-05 0.0146

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-940 to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 2.75e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #9: 'HISTOLOGICAL.TYPE'

9 genes related to 'HISTOLOGICAL.TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 13
  LUNG ADENOCARCINOMA MIXED SUBTYPE 89
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 287
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 4
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 18
  LUNG CLEAR CELL ADENOCARCINOMA 2
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 18
  LUNG SIGNET RING ADENOCARCINOMA 1
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 4
  MUCINOUS (COLLOID) CARCINOMA 7
     
  Significant markers N = 9
List of 9 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S15.  Get Full Table List of 9 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-194-1 1.071e-08 5.68e-06
HSA-MIR-194-2 1.401e-08 7.41e-06
HSA-MIR-21 8.182e-08 4.32e-05
HSA-MIR-192 4.323e-06 0.00228
HSA-MIR-215 1.921e-05 0.0101
HSA-MIR-200B 2.388e-05 0.0125
HSA-MIR-377 3.05e-05 0.016
HSA-LET-7B 5.128e-05 0.0268
HSA-MIR-656 5.276e-05 0.0275

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-194-1 to 'HISTOLOGICAL.TYPE'. P value = 1.07e-08 with ANOVA analysis.

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S16.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 19
  YES 428
     
  Significant markers N = 0
Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

5 genes related to 'NUMBERPACKYEARSSMOKED'.

Table S17.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 42.1 (27)
  Significant markers N = 5
  pos. correlated 5
  neg. correlated 0
List of 5 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

Table S18.  Get Full Table List of 5 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-210 0.2701 1.451e-06 0.000769
HSA-MIR-345 0.2621 2.992e-06 0.00158
HSA-MIR-296 0.2573 4.776e-06 0.00252
HSA-MIR-339 0.2548 5.753e-06 0.00303
HSA-MIR-31 0.2262 9.151e-05 0.0481

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-210 to 'NUMBERPACKYEARSSMOKED'. P value = 1.45e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S19.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1964.71 (12)
  Significant markers N = 0
Clinical variable #13: 'COMPLETENESS.OF.RESECTION'

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

Table S20.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 303
  R1 10
  R2 4
  RX 18
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 447

  • Number of genes = 530

  • Number of clinical features = 13

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)
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