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Reply to ‘H-STS, L-STS and KRJ-I are not authentic GEPNET cell lines’

Nature Genetics volume 51, pages 1427–1428 (2019)Cite this article

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Alvarez et al. reply — Quantitative, objective metrics to assess the fidelity of cancer models— such as cell lines, organoids or patient-derived xenografts—remain elusive, and histological criteria or the presence of specific mutations is often used as a surrogate. Hofving et al.1 have reported that two cell lines (H-STS and KRJ-1) recently used as a model to prioritize treatment for gastro-enteropancreatic neuroendocrine tumors (GEP-NETs)2 are not appropriate models for this disease because, as also previously reported3, they are derived from Epstein–Barr virus–immortalized lymphoblastoid cells. Yet, what constitutes an appropriate model to study a specific tumor remains a matter of considerable debate. Indeed, histology and mutational status may negatively bias model selection. For instance, we have recently assessed the suitability of 16 neuroblastoma cell lines bearing MYCN amplifications as high-fidelity models for the study of the MYCN-dependent subtype of this tumor4. Unexpectedly, only four of these cell lines effectively recapitulated key tumor dependencies and associated mechanisms that have been shown to be highly conserved across virtually all MYCN-subtype patients in two independent cohorts.

The results of that study motivated us to seek more quantitative, molecular-level criteria to assess the fidelity of a given model to a tumor of interest, by integrating two independent measurements: (i) the conservation of regulatory networks inferred exclusively from patient-derived samples in the tumor-model and (ii) the overlap of patient-specific master-regulator proteins—that is, proteins representing mechanistic regulatory determinants of tumor state and tumor dependencies5—with model-specific master regulators. Master-regulator proteins are identified on the basis of the enrichment of their positively regulated and repressed targets in a phenotype-specific signature, by using the VIPER algorithm, which has been extensively validated6. Such unbiased criteria may be especially valuable for tumors that, like GEP-NETs, lack effective in vitro or in vivo models.

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References

  1. Hofving, T., Karlsson, J., Nilsson, O. & Nilsson, J. A. Nat Genet. https://doi.org/10.1038/s41588-019-0490-z (2019).

    Article  PubMed  Google Scholar 

  2. Alvarez, M. J. et al. Nat. Genet. 50, 979–989 (2018).

    Article  CAS  Google Scholar 

  3. Hofving, T. et al. Endocr. Relat. Cancer 25, X1–X2 (2018).

    Article  Google Scholar 

  4. Rajbhandari, P. et al. Cancer Discov. 8, 582–599 (2018).

    Article  CAS  Google Scholar 

  5. Califano, A. & Alvarez, M. J. Nat. Rev. Cancer 17, 116–130 (2017).

    Article  CAS  Google Scholar 

  6. Alvarez, M. J. et al. Nat. Genet. 48, 838–847 (2016).

    Article  CAS  Google Scholar 

  7. Barretina, J. et al. Nature 483, 603–607 (2012).

    Article  CAS  Google Scholar 

  8. Pfragner, R. et al. Anticancer Res. 29, 1951–1961 (2009).

    CAS  PubMed  Google Scholar 

  9. Rinner, B. et al. BMC Genomics 13, 594 (2012).

    Article  CAS  Google Scholar 

  10. Alvarez, M.J. et al. Preprint at bioRxiv https://doi.org/10.1101/677435 (2019).

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Acknowledgements

The results in this manuscript were produced by using generous support from the NET Research Foundation to A.C., D.L.R.-L. and M.H.K. for the GEP-NET explant component of the study. We would also like to acknowledge the National Institutes of Health 1R35CA197745 (Outstanding Investigator Award) and U01CA217858 (Cancer Target Discovery and Development network) to A.C., and the NCI instrumentation grants S10OD012351 and S10OD021764 to A.C., which were instrumental for the data analysis. All RNA-seq libraries and sequencing were performed in the JP Sulzberger Columbia Genome Center, with support from a P30 Cancer Center Support Grant (P30CA013696).

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Authors and Affiliations

  1. Department of Systems Biology, Columbia University Irvin Medical Center, New York, NY, USA

    Mariano J. Alvarez, Charles Karan, Ronald B. Realubit, Prabhjot S. Mundi, Adina Grunn & Andrea Califano

  2. DarwinHealth Inc., New York, NY, USA

    Mariano J. Alvarez

  3. Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Pengrong Yan, Mary L. Alpaugh & Gabriela Chiosis

  4. Department of Molecular and Cellular Biosciences, Rowan University, Glassboro, NJ, USA

    Mary L. Alpaugh

  5. Department of Translational Medicine, Bristol-Meyers Squibb, Boston, MA, USA

    Michaela Bowden

  6. Department of Oncologic Pathology, Dana Farber Cancer Institute, Boston, MA, USA

    Ewa Sicinska & Chensheng W. Zhou

  7. James J. Peters Virginia Medical Center, Bronx, NY, USA

    Prabhjot S. Mundi

  8. Medical Oncology, National Center for Tumor Diseases Heidelberg, University Medical Center Heidelberg, Heidelberg, Germany

    Dirk Jäger

  9. Department of Surgery, Columbia University Irvin Medical Center, New York, NY, USA

    John A. Chabot

  10. Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA

    John A. Chabot, Antonio T. Fojo, Hanina Hibshoosh & Andrea Califano

  11. Department of Medicine, Columbia University Irvin Medical Center, New York, NY, USA

    Antonio T. Fojo

  12. Department of Medical Oncology, Perlmutter Cancer Center, New York, NY, USA

    Paul E. Oberstein

  13. Department of Pathology, Columbia University Irvin Medical Center, New York, NY, USA

    Hanina Hibshoosh

  14. Colon and Rectal Surgery, Weill Cornell Medicine, New York, NY, USA

    Jeffrey W. Milsom

  15. Department of Hematology and Medical Oncology, Boston University Cancer Center, Boston, MA, USA

    Matthew H. Kulke

  16. Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA

    Massimo Loda

  17. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    Diane L. Reidy-Lagunes

  18. JP Sulzberger Columbia Genome Center, Columbia University, New York, NY, USA

    Andrea Califano

  19. Department of Biomedical Informatics, Columbia University, New York, NY, USA

    Andrea Califano

  20. Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA

    Andrea Califano

Authors
  1. Mariano J. Alvarez
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Contributions

A.C. conceived the study and was involved in all aspects of study organization, sample collection, data analysis and manuscript writing. M.J.A. was responsible for all aspects of data analysis, and P.S.M. assisted. P.Y., M.L.A., M.B., E.S., C.W.Z. and H.H. were responsible for explant generation, culturing and treatment. A.G. was responsible for GEP-NET sample preparation, storage and RNA isolation. C.K. and R.B.R. were responsible for the P0NETCL dissociation, culturing and treatment to generate drug-perturbation profiles. J.A.C., A.T.F., P.E.O., J.W.M., M.H.K. and D.L.R.-L. were responsible for patient enrollment into the study. M.L., M.L.A. and G.C. were responsible for the optimization and supervision of the explant generation protocol at the three institutions. D.J. was involved in the study conception and design. Finally, M.J.A. and A.C. were responsible for all aspects of manuscript writing and revision.

Corresponding author

Correspondence to Andrea Califano.

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Competing interests

M.J.A. is Chief Scientific Officer and an equity holder at DarwinHealth, Inc., a company that has licensed some of the algorithms used in this manuscript from Columbia University. A.C. is a founder, equity holder, consultant and director of DarwinHealth, Inc. Columbia University is also an equity holder in DarwinHealth, Inc.

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Alvarez, M.J., Yan, P., Alpaugh, M.L. et al. Reply to ‘H-STS, L-STS and KRJ-I are not authentic GEPNET cell lines’. Nat Genet 51, 1427–1428 (2019). https://doi.org/10.1038/s41588-019-0509-5

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