Evaluation of exome sequencing to estimate tumor burden in plasma.

Accurate estimation of systemic tumor load from the blood of cancer patients has enormous potential. One avenue is to measure the presence of cell-free circulating tumor DNA in plasma. Various approaches have been investigated, predominantly covering hotspot mutations or customized, patient-specific assays. Therefore, we investigated the utility of using exome sequencing to monitor circulating tumor DNA levels through the detection of single nucleotide variants in plasma. Two technologies, claiming to offer efficient library preparation from nanogram levels of DNA, were evaluated. This allowed us to estimate the proportion of starting molecules measurable by sequence capture (<5%). As cell-free DNA is highly fragmented, we designed and provide software for efficient identification of PCR duplicates in single-end libraries with a varying size distribution. On average, this improved sequence coverage by 38% in comparison to standard tools. By exploiting the redundant information in PCR-duplicates the background noise was reduced to ∼1/35,000. By applying our optimized analysis pipeline to a simulation analysis, we determined the current sensitivity limit to ∼1/2400, starting with 30 ng of cell-free DNA. Subsequently, circulating tumor DNA levels were assessed in seven breast- and one prostate cancer patient. One patient carried detectable levels of circulating tumor DNA, as verified by break-point specific PCR. These results demonstrate exome sequencing on cell-free DNA to be a powerful tool for disease monitoring of metastatic cancers. To enable a broad implementation in the diagnostic settings, the efficiency limitations of sequence capture and the inherent noise levels of the Illumina sequencing technology must be further improved.

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.

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.