Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods
Authors
Murphy, R. G.Roddy, A. C.
Srivastava, S.
Baena, Esther
Waugh, D. J.
J, M. O. S.
McArt, D. G.
Jain, S.
LaBonte, M. J.
Affiliation
Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast BT9 7AE, UK.Issue Date
2020
Metadata
Show full item recordAbstract
Combining alignment-free methods for phylogenetic analysis with multi-regional sampling using next-generation sequencing can provide an assessment of intra-patient tumour heterogeneity. From multi-regional sampling divergent branching, we validated two different lesions within a patient's prostate. Where multi-regional sampling has not been used, a single sample from one of these areas could misguide as to which drugs or therapies would best benefit this patient, due to the fact these tumours appear to be genetically different. This application has the power to render, in a fraction of the time used by other approaches, intra-patient heterogeneity and decipher aberrant biomarkers. Another alignment-free method for calling single-nucleotide variants from raw next-generation sequencing samples has determined possible variants and genomic locations that may be able to characterize the differences between the two main branching patterns. Alignment-free approaches have been applied to relevant clinical multi-regional samples and may be considered as a valuable option for comparing and determining heterogeneity to help deliver personalized medicine through more robust efforts in identifying targetable pathways and therapeutic strategies. Our study highlights the application these tools could have on patient-aligned treatment indications.Citation
Murphy RG, Roddy AC, Srivastava S, Baena E, Waugh David�J, M.�O�Sullivan J, et al. Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods. NAR Genomics and Bioinformatics. 2020;2(3):lqaa062.Journal
NAR Genomics and BioinformaticsDOI
10.1093/nargab/lqaa062PubMed ID
32856020Additional Links
https://dx.doi.org/10.1093/nargab/lqaa062Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1093/nargab/lqaa062
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