Abstract 98: Personalized therapy choice integrating genome and expression data in advanced cancers

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Abstract Sequencing technology is increasingly essential in clinical cancer management. The majority of clinical cancer sequencing has focused on panel approaches, but recent trials have begun to report the use of transcriptome expression profiling to match patients to therapy. The Personalized OncoGenomics (POG) program at BC Cancer has sequenced over 500 patient tumors, integrating both whole genome and transcriptome data to inform treatment options for patients with advanced or metastatic disease. Here we present 570 patients who were sequenced from 2012 to 2017 and reviewed at the POG multidisciplinary molecular tumor board. Genome and transcriptome information identified clinically actionable targets in 83% (475/570) of sequenced cases, with 37% (209/570) receiving POG-informed therapy. Overall, 248 whole genome and transcriptome sequencing analysis (WGTA)-informed treatments were administered, with some patients receiving multiple treatment courses. Of the treated cases, 46% (114/248) were reported to have physician-assessed clinical benefit. Clinical benefit was assessed as per standard of care rather than strict timing as per RECIST criteria. Mutation, copy number, structural variant, expression, and genome signature data were all used individually or in combination to inform treatments. Treatments based in whole or in part from RNA expression data were the largest subgroup (66.9%, 166/248), and patients in this group had similar proportion of clinical benefit compared to those receiving treatments informed by DNA-based data. Importantly, the use of RNA data resulted in 14.5% (36/248) additional patients receiving WGTA-informed treatments with clinical benefit. Patients were directed to clinical trials, treated with therapeutics in off-label indications, or positioned to genomically-informed standard of care options. For a subset of 42 cases where the planned next line of therapy was documented prior to WGTA analysis, 76.2% (32/42) of genomically-informed standard therapies were different from those which would otherwise have been considered the next line of therapy by the treating clinician, or aided in a decision between multiple different therapy options under consideration. These results emphasize the importance of multiple data types, including expression information, to personalize treatment. We also observe that, in addition to positioning for trials or identifying cases for off-label treatment, choice of standard of care therapies is an important use of genomic data. Overall, our data supports the integration of whole genome and RNA sequencing data in the clinic, with implications both for cancer research and treatment, and ultimately the potential to improve cancer outcomes. Citation Format: Alexandra K. Bohm, Erin Pleasance, Emma Tittmus, Kathleen Wee, Gregory Taylor, Melika Bonakdar, Yaoqing Shen, Laura Williamson, Veronika Csizmok, Martin Jones, Jessica Nelson, Balvir Deol, Caralyn Reisle, Karen Mungall, Eric Chuah, Andrew Mungall, Richard Moore, Sophie Sun, Howard Lim, Daniel Renouf, Steven Jones, Marco Marra, Janessa Laskin. Personalized therapy choice integrating genome and expression data in advanced cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 98.