Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular network

Lei Yang,Xiaowen Chen,Shiyuan Wang,Meng Zhou,Yongchun Zuo,Wei Jiang,Yingli Lv

doi:10.1038/s41598-017-00872-8

Lei Yang, Xiaowen Chen + Show 5 more

Open Access

https://doi.org/10.1038/s41598-017-00872-8

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Abstract

Prostate cancer is one of the most common cancers in men and a leading cause of cancer death worldwide, displaying a broad range of heterogeneity in terms of clinical and molecular behavior. Increasing evidence suggests that classifying prostate cancers into distinct molecular subtypes is critical to exploring the potential molecular variation underlying this heterogeneity and to better treat this cancer. In this study, the somatic mutation profiles of prostate cancer were downloaded from the TCGA database and used as the source nodes of the random walk with restart algorithm (RWRA) for generating smoothed mutation profiles in the STRING network. The smoothed mutation profiles were selected as the input matrix of the Graph-regularized Nonnegative Matrix Factorization (GNMF) for classifying patients into distinct molecular subtypes. The results were associated with most of the clinical and pathological outcomes. In addition, some bioinformatics analyses were performed for the robust subtyping, and good results were obtained. These results indicated that prostate cancers can be usefully classified according to their mutation profiles, and we hope that these subtypes will help improve the treatment stratification of this cancer in the future.

Highlights

Prostate cancer is the most non-cutaneous common cancer in males and one of the leading causes of cancer-related deaths worldwide
The analysis of the prostate adenocarcinoma revealed that the somatic mutation frequencies vary more than three orders of magnitude (from 0.2 per megabase (Mb) to 214.8 per Mb) across patients within a cancer type (Fig. 1A), consistent with the study of the mutational heterogeneity of approximately 3000 samples[32]
We identified some genes previously known to be associated with prostate adenocarcinoma, including SPOP, a substrate-binding subunit of a cullin-based E3 ubiquitin ligase complex, to be mutated in 11.65% of samples, and FOXA1, known as hepatocyte nuclear factor 3-alpha (HNF-3A), to be mutated in 6.22% of samples

Summary

Introduction

Prostate cancer is the most non-cutaneous common cancer in males and one of the leading causes of cancer-related deaths worldwide. With the emergence and application of new genomic technologies, such as next-generation sequencing and microarray analyses, more molecular and genetic profiles of prostate adenocarcinomas have been generated in recent years Based on these profiles, we found that prostate adenocarcinomas exhibit a remarkable biological heterogeneity, including alterations of somatic copy number, point mutations, and structural rearrangements, and these genetic heterogeneities may underlie the high variability of clinical outcomes in prostate adenocarcinomas[5,6,7,8,9,10]. Markert et al, analyzed a microarray dataset of 281 prostate cancers, and five distinct molecular subtypes were identified by unsupervised clustering They found that the first subtype was characterized by poor survival outcome, the second subtype was characterized by intermediate survival outcome, and three subtypes were characterized by benign outcome. We are to describe how to deal with these steps one-by-one

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