title: Application of single-cell genomics in cancer: promise and challenges.
abstract: Recent advances in single-cell genomics are opening up unprecedented opportunities to transform cancer genomics. While bulk tissue genomic analysis across large populations of tumour cells has provided key insights into cancer biology, this approach does not provide the resolution that is critical for understanding the interaction between different genetic events within the cellular hierarchy of the tumour during disease initiation, evolution, relapse and metastasis. Single-cell genomic approaches are uniquely placed to definitively unravel complex clonal structures and tissue hierarchies, account for spatiotemporal cell interactions and discover rare cells that drive metastatic disease, drug resistance and disease progression. Here we present five challenges that need to be met for single-cell genomics to fulfil its potential as a routine tool alongside bulk sequencing. These might be thought of as being challenges related to samples (processing and scale for analysis), sensitivity and specificity of mutation detection, sources of heterogeneity (biological and technical), synergies (from data integration) and systems modelling. We discuss these in the context of recent advances in technologies and data modelling, concluding with implications for moving cancer research into the clinic.
authors.affiliation: Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, UK, Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK and.
authors.forename: Quin F
authors.initials: QF
authors.lastname: Wills
authors.affiliation: Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, UK, NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LE, UK adam.mead@imm.ox.ac.uk.
authors.forename: Adam J
authors.initials: AJ
authors.lastname: Mead
mesh_terms: D000818:Animals; D023281:Genomics; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D012680:Sensitivity and Specificity; D059010:Single-Cell Analysis / Q000379:methods*