Prostate Adenocarcinoma: Correlation between mRNAseq expression and clinical features
Maintained by Juok Cho (Broad Institute)
Overview
Introduction

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

Summary

Testing the association between 18266 genes and 3 clinical features across 102 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.

  • 1 gene correlated to 'AGE'.

    • ADAP2|55803

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

    • SFRS2|6427 ,  ABHD11|83451 ,  C14ORF126|112487 ,  CEBPZ|10153 ,  ZNF596|169270 ,  ...

  • 49 genes correlated to 'NEOADJUVANT.THERAPY'.

    • SLC16A2|6567 ,  FYCO1|79443 ,  PIK3R1|5295 ,  BEND6|221336 ,  PTN|5764 ,  ...

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
AGE Spearman correlation test N=1 older N=1 younger N=0
RADIATIONS RADIATION REGIMENINDICATION t test N=20 yes N=3 no N=17
NEOADJUVANT THERAPY t test N=49 yes N=35 no N=14
Clinical variable #1: 'AGE'

One gene related to 'AGE'.

Table S1.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 61.34 (6.8)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'AGE' by Spearman correlation test

Table S2.  Get Full Table List of one gene significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ADAP2|55803 0.4835 2.636e-07 0.00481

Figure S1.  Get High-res Image As an example, this figure shows the association of ADAP2|55803 to 'AGE'. P value = 2.64e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #2: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S3.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 5
  YES 97
     
  Significant markers N = 20
  Higher in YES 3
  Higher in NO 17
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S4.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
SFRS2|6427 -8.86 2.5e-11 4.38e-07 0.8454
ABHD11|83451 9.49 1.204e-10 2.11e-06 0.8866
C14ORF126|112487 -7.27 2.121e-10 3.71e-06 0.8062
CEBPZ|10153 -7.27 3.222e-10 5.64e-06 0.8
ZNF596|169270 -9.26 2.072e-08 0.000363 0.901
CLK4|57396 -8.55 2.571e-08 0.00045 0.8742
CDC40|51362 -6.93 3.386e-08 0.000592 0.7959
VN1R1|57191 -7.2 5.162e-08 0.000903 0.8206
SFRS13A|10772 -7.71 5.721e-08 0.001 0.8412
TMEM161B|153396 -7.3 2.174e-07 0.0038 0.8371

Figure S2.  Get High-res Image As an example, this figure shows the association of SFRS2|6427 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.5e-11 with T-test analysis.

Clinical variable #3: 'NEOADJUVANT.THERAPY'

49 genes related to 'NEOADJUVANT.THERAPY'.

Table S5.  Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY Labels N
  NO 4
  YES 98
     
  Significant markers N = 49
  Higher in YES 35
  Higher in NO 14
List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

T(pos if higher in 'YES') ttestP Q AUC
SLC16A2|6567 13.43 8.527e-24 1.45e-19 0.9107
FYCO1|79443 11.64 1.205e-19 2.04e-15 0.8852
PIK3R1|5295 12.02 1.295e-18 2.2e-14 0.875
BEND6|221336 10.34 5.722e-17 9.71e-13 0.8622
PTN|5764 16.04 1.068e-13 1.81e-09 0.9898
LTBP3|4054 8.54 2.211e-13 3.75e-09 0.8036
CLCNKB|1188 8.48 2.26e-13 3.84e-09 0.8129
RRP9|9136 -8.83 2.051e-12 3.48e-08 0.8393
TIMELESS|8914 -13.15 2.276e-12 3.86e-08 0.9694
TBX4|9496 8.93 3.44e-12 5.84e-08 0.8144

Figure S3.  Get High-res Image As an example, this figure shows the association of SLC16A2|6567 to 'NEOADJUVANT.THERAPY'. P value = 8.53e-24 with T-test analysis.

Methods & Data
Input
  • Expresson data file = PRAD.uncv2.mRNAseq_RSEM_normalized_log2.txt

  • Clinical data file = PRAD.clin.merged.picked.txt

  • Number of patients = 102

  • Number of genes = 18266

  • Number of clinical features = 3

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

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] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] 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)