| Literature DB >> 29180472 |
Joan Alexander1, Jude Kendall1, Jean McIndoo1, Linda Rodgers1, Robert Aboukhalil1, Dan Levy1, Asya Stepansky1, Guoli Sun1, Lubomir Chobardjiev2, Michael Riggs1, Hilary Cox1, Inessa Hakker1, Dawid G Nowak1, Juliana Laze3, Elton Llukani3, Abhishek Srivastava4, Siobhan Gruschow4, Shalini S Yadav4, Brian Robinson5, Gurinder Atwal1, Lloyd C Trotman1, Herbert Lepor3, James Hicks1, Michael Wigler1, Alexander Krasnitz6.
Abstract
A distinction between indolent and aggressive disease is a major challenge in diagnostics of prostate cancer. As genetic heterogeneity and complexity may influence clinical outcome, we have initiated studies on single tumor cell genomics. In this study, we demonstrate that sparse DNA sequencing of single-cell nuclei from prostate core biopsies is a rich source of quantitative parameters for evaluating neoplastic growth and aggressiveness. These include the presence of clonal populations, the phylogenetic structure of those populations, the degree of the complexity of copy-number changes in those populations, and measures of the proportion of cells with clonal copy-number signatures. The parameters all showed good correlation to the measure of prostatic malignancy, the Gleason score, derived from individual prostate biopsy tissue cores. Remarkably, a more accurate histopathologic measure of malignancy, the surgical Gleason score, agrees better with these genomic parameters of diagnostic biopsy than it does with the diagnostic Gleason score and related measures of diagnostic histopathology. This is highly relevant because primary treatment decisions are dependent upon the biopsy and not the surgical specimen. Thus, single-cell analysis has the potential to augment traditional core histopathology, improving both the objectivity and accuracy of risk assessment and inform treatment decisions.Significance: Genomic analysis of multiple individual cells harvested from prostate biopsies provides an indepth view of cell populations comprising a prostate neoplasm, yielding novel genomic measures with the potential to improve the accuracy of diagnosis and prognosis in prostate cancer. Cancer Res; 78(2); 348-58. ©2017 AACR. ©2017 American Association for Cancer Research.Entities:
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Year: 2017 PMID: 29180472 PMCID: PMC5771881 DOI: 10.1158/0008-5472.CAN-17-1138
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701