| Literature DB >> 31570899 |
Nike Beaubier1, Martin Bontrager1, Robert Huether1, Catherine Igartua1, Denise Lau1, Robert Tell1, Alexandria M Bobe1, Stephen Bush1, Alan L Chang1, Derick C Hoskinson1, Aly A Khan1, Emily Kudalkar1, Benjamin D Leibowitz1, Ariane Lozachmeur1, Jackson Michuda1, Jerod Parsons1, Jason F Perera1, Ameen Salahudeen1, Kaanan P Shah1, Timothy Taxter1, Wei Zhu1, Kevin P White2.
Abstract
Genomic analysis of paired tumor-normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor-normal plus transcriptome sequencing outperforms tumor-only DNA panel testing.Entities:
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Year: 2019 PMID: 31570899 DOI: 10.1038/s41587-019-0259-z
Source DB: PubMed Journal: Nat Biotechnol ISSN: 1087-0156 Impact factor: 68.164