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Integrated genomic profiling expands clinical options for patients with cancer

Nature Biotechnology volume 37, pages 1351–1360 (2019)Cite this article

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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.

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Fig. 1: Mutational spectrum of the xT 500 cohort.
Fig. 2: Predicted TCGA cancer types for samples within each xT 500 cohort cancer type.
Fig. 3: Immunogenomic landscape of solid tumors in the xT 500 cohort.
Fig. 4: Evidence-based therapy and clinical trial matching.
Fig. 5: Tumor-only versus tumor–normal analyses.

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Data availability

VCF files, RNA count files and associated deidentified clinical data that support these findings will be available through Vivli (ID T19.01).

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Acknowledgements

We are thankful to the operations, product, engineering and clinical data teams at Tempus Labs, including but not limited to U. Pipic, C. Schwalbach, S. Hynes, K. Stenglein, L. Sachse, A. Hoyer, S. Carsanaro, H, Lefkofsky, R. Chang, M. Barber, R. Pe Benito, R. Star, H. Whipple and D. King. We thank the pathology and lab teams for sample processing and data collection. We are grateful to M. Salazar for managing the work required for this manuscript. We thank G. Palmer and A. Schwarzbach for review of the manuscript, M. Kase and A. Hoffman-Peterson for proofreading, and A. Sheals and B. Santacaterina for help with figure aesthetics and assembly. We thank E. Lefkofsky for his support and discussions.

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  1. These authors contributed equally: Nike Beaubier, Martin Bontrager, Robert Huether, Catherine Igartua, Denise Lau, Robert Tell.

Authors and Affiliations

  1. Tempus Labs, Inc., Chicago, IL, USA

    Nike Beaubier, Martin Bontrager, Robert Huether, Catherine Igartua, Denise Lau, Robert Tell, Alexandria M. Bobe, Stephen Bush, Alan L. Chang, Derick C. Hoskinson, Aly A. Khan, Emily Kudalkar, Benjamin D. Leibowitz, Ariane Lozachmeur, Jackson Michuda, Jerod Parsons, Jason F. Perera, Ameen Salahudeen, Kaanan P. Shah, Timothy Taxter, Wei Zhu & Kevin P. White

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Contributions

N.B., M.B., R.H., C.I., R.T. and D.L. led data analysis and interpretation, and wrote sections of the manuscript. N.B. and T.T. performed the pathologic review of the cohort and wrote sections of the manuscript. C.I., J.M., B.D.L., K.P.S., T.T. and N.B. contributed to gene expression and cancer type predictor analyses and figures. D.L., A.L.C., J.F.P., A.L. and A.A.K. contributed to immune analyses and figures. R.T., S.B., J.P. and W.Z. contributed to mutational and genomic rearrangement analyses and figures. R.H., R.T., D.C.H., N.B., A.S. and M.B. contributed to tumor-only and tumor–normal analyses and figures. R.H., N.B., E.K. and M.B. contributed to therapeutic evidence and clinical trial matching analyses. A.M.B. provided critical review of drafts and figures, wrote sections of the manuscript and reviewed the final manuscript. K.P.W. oversaw manuscript preparation, provided scientific direction, wrote sections of the manuscript and reviewed the final manuscript.

Corresponding author

Correspondence to Kevin P. White.

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Authors are employees of Tempus Labs, Inc.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–7 and Supplementary Tables 1–3

Reporting Summary

Supplementary Table 4

Identification of clinical trial options. Examples of the clinical data fields used to identify pertinent clinical trials for the cohort (n = 481 patients). Multiple clinical trial options may have been reported, but only one is shown per patient in the table.

Supplementary Table 5

Tumor-only analysis of somatic false positives. List of variants classified as somatic and verified as germline. Each variant contains the hg19 coordinates followed by symbol, variant, allele frequency (AF) in the tumor and germline sample, and mutation classification (TVUS, tumor-only variant of unknown significance; TMUT, tumor-only mutation).

Supplementary Table 6

Comparison between full Tempus xT test and tumor-only tests. Comparison of test results and relevant therapies for 50 patients from a full Tempus xT test, a tumor-only DNA sequencing xT test, and an analysis of treatment options based on tumor-only variants from My Cancer Genome.

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Beaubier, N., Bontrager, M., Huether, R. et al. Integrated genomic profiling expands clinical options for patients with cancer. Nat Biotechnol 37, 1351–1360 (2019). https://doi.org/10.1038/s41587-019-0259-z

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