Prostate Adenocarcinoma: Correlation between gene mutation status and selected clinical features<BR>(primary solid tumor cohort)

Prostate Adenocarcinoma: Correlation between gene mutation status and selected clinical features
(primary solid tumor cohort)

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Overview

Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 12 genes and 2 clinical features across 83 patients, one significant finding detected with Q value < 0.25.

PRR21 mutation correlated to 'AGE'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 12 genes and 2 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding detected.


		Clinical Features	AGE	RADIATIONS RADIATION REGIMENINDICATION
	nMutated (%)	nWild-Type	t-test	Fisher's exact test
PRR21	4 (5%)	79	0.00302 (0.0725)	0.224 (1.00)
NKX3-1	5 (6%)	78	0.463 (1.00)	1 (1.00)
FRG1	4 (5%)	79	0.0586 (1.00)	0.224 (1.00)
TP53	5 (6%)	78	0.64 (1.00)	1 (1.00)
SPOP	4 (5%)	79	0.481 (1.00)	1 (1.00)
OR4D5	3 (4%)	80	0.092 (1.00)	1 (1.00)
OR6N1	3 (4%)	80	0.367 (1.00)	0.172 (1.00)
CNTNAP5	5 (6%)	78	0.488 (1.00)	1 (1.00)
AIM2	3 (4%)	80	0.361 (1.00)	0.172 (1.00)
MLL3	7 (8%)	76	0.618 (1.00)	0.364 (1.00)
OR5L2	3 (4%)	80	0.0989 (1.00)	1 (1.00)
YBX1	3 (4%)	80	0.784 (1.00)	1 (1.00)

'PRR21 MUTATION STATUS' versus 'AGE'

P value = 0.00302 (t-test), Q value = 0.072

Table S1. Gene #4: 'PRR21 MUTATION STATUS' versus Clinical Feature #1: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	83	61.1 (6.8)
PRR21 MUTATED	4	66.5 (2.1)
PRR21 WILD-TYPE	79	60.8 (6.8)

Figure S1. Get High-res Image Gene #4: 'PRR21 MUTATION STATUS' versus Clinical Feature #1: 'AGE'

Methods & Data

Input

Mutation data file = PRAD-TP.mutsig.cluster.txt
Clinical data file = PRAD-TP.clin.merged.picked.txt
Number of patients = 83
Number of significantly mutated genes = 12
Number of selected clinical features = 2
Exclude genes that fewer than K tumors have mutations, K = 3

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' function in R

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[2] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)

[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)

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