The mitochondrial and autosomal mutation landscapes of prostate cancer

BACKGROUND: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression.

OBJECTIVE: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected.

DESIGN, SETTING, AND PARTICIPANTS: Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature.

RESULTS AND LIMITATIONS: Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for.

CONCLUSIONS: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology.

Exome sequencing of prostate cancer supports the hypothesis of independent tumour origins

BACKGROUND: Prostate cancer (PCa) is a clinically and pathologically heterogeneous disease. The rapid development of sequencing technology has the potential to deliver new biomarkers with emphasis on aggressive disease and to revolutionise personalised cancer treatment. However, a prostate harbouring cancer commonly contains multiple separate tumour foci, with the potential to aggravate tumour sampling. The level of intraprostatic tumour heterogeneity remains to be determined.

OBJECTIVE: To determine the level of intraprostatic tumour heterogeneity through genome-wide, high-resolution profiling of multiple tumour samples from the same individual.

DESIGN, SETTINGS, AND PARTICIPANTS: Multiple tumour samples were obtained from four individuals following radical prostatectomy. One individual (SWE-1) contained >70% cancer cells in all tumour samples, whereas the other three (SWE-2 to SWE-4) required the use of laser capture microdissection for tumour cell enrichment. Subsequently, DNA was extracted from all tissue samples, and exome sequencing was performed. All tumour foci of SWE-1 were also profiled using a high-resolution array for the identification of copy number alterations (CNA).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Shared somatic high-frequency single nucleotide variants (SNV) and CNAs were used to infer the level of intraprostatic tumour heterogeneity.

RESULTS AND LIMITATIONS: No high-frequency mutations, common for the three tumour samples of SWE-1, were identified. Ten randomly chosen positions were validated with Sanger sequencing in all foci, which verified the exome data. The high level of intraprostatic heterogeneity was consistent in all individuals. In total, three out of four individuals harboured tumours without an apparent common somatic denominator. Although we cannot exclude the presence of common structural rearrangements, a high-density array was used for the detection of deletions and amplifications in SWE-1, which agreed with the exome data.

CONCLUSIONS: We present evidence for the presence of somatically independent tumours within the same prostate. This finding will have implications for personalised cancer treatment and biomarker discovery.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.