Mutational patterns in chemotherapy resistant muscle-invasive bladder cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

David Liu, Philip Abbosh, Daniel Keliher, Brendan Reardon, Diana Miao, Kent Mouw, Amaro Weiner-Taylor, Stephanie Wankowicz, Garam Han, Min Yuen Teo, Catharine Cipolla, Jaegil Kim, Gopa Iyer, Hikmat Al-Ahmadie, Essel Dulaimi, David Y. T. Chen, R. Katherine Alpaugh, Jean Hoffman-Censits, Levi A. Garraway, Gad Getz, Scott L. Carter, Joaquim Bellmunt, Elizabeth R. Plimack, Jonathan E. Rosenberg, Eliezer M. Van Allen

ABSTRACT

Despite continued widespread use, the genomic effects of cisplatin-based chemotherapy and implications for subsequent treatment are incompletely characterized. Here, we analyze whole exome sequencing of matched pre- and post-neoadjuvant cisplatin-based chemotherapy primary bladder tumor samples from 30 muscle-invasive bladder cancer patients. We observe no overall increase in tumor mutational burden post-chemotherapy, though a significant proportion of subclonal mutations are unique to the matched pre- or post-treatment tumor, suggesting chemotherapy-induced and/or spatial heterogeneity. We subsequently identify and validate a novel mutational signature in post-treatment tumors consistent with known characteristics of cisplatin damage and repair. We find that post-treatment tumor heterogeneity predicts worse overall survival, and further observe alterations in cell-cycle and immune checkpoint regulation genes in post-treatment tumors. These results provide insight into the clinical and genomic dynamics of tumor evolution with cisplatin-based chemotherapy, suggest mechanisms of clinical resistance, and inform development of clinically relevant biomarkers and trials of combination therapies. More... »

PAGES

2193

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-017-02320-7

    DOI

    http://dx.doi.org/10.1038/s41467-017-02320-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1099706980

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29259186


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