AI Article Synopsis

  • Patient responses to cancer therapy differ greatly due to genetic and molecular diversity, underscoring the importance of understanding tumor variations.
  • To improve personalized treatment, researchers have created a detailed database of 462 patient-derived tumor cell lines (PDCs) and their characteristics across 14 cancer types, showing they better represent actual disease biology compared to traditional cancer cell lines.
  • The study reveals insights into how specific genetic factors can lead to resistance against EGFR inhibitors and suggests the potential for using ibrutinib, typically for blood cancers, in EGFR-targeted treatment for gliomas, alongside retroactive clinical response predictions based on drug sensitivities.

Article Abstract

Outcomes of anticancer therapy vary dramatically among patients due to diverse genetic and molecular backgrounds, highlighting extensive intertumoral heterogeneity. The fundamental tenet of precision oncology defines molecular characterization of tumors to guide optimal patient-tailored therapy. Towards this goal, we have established a compilation of pharmacological landscapes of 462 patient-derived tumor cells (PDCs) across 14 cancer types, together with genomic and transcriptomic profiling in 385 of these tumors. Compared with the traditional long-term cultured cancer cell line models, PDCs recapitulate the molecular properties and biology of the diseases more precisely. Here, we provide insights into dynamic pharmacogenomic associations, including molecular determinants that elicit therapeutic resistance to EGFR inhibitors, and the potential repurposing of ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, we present a potential implementation of PDC-derived drug sensitivities for the prediction of clinical response to targeted therapeutics using retrospective clinical studies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514738PMC
http://dx.doi.org/10.1038/s41588-018-0209-6DOI Listing

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