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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Data availability

All sequenced data have been deposited in the European Genome-phenome Archive (EGA) under accession EGAS00001002515. Processed data and basic association analysis are publicly available through an interactive web portal (the Cancer-Drug eXplorer (cDx); see URLs).

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

This research was supported by a grant of the Korea Health Technology Research and Development project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (HI14C3418). This work has been funded by NIH grants (R01 CA185486, R01 CA179044, U54 CA193313 and U54 209997) and NSF/SU2C/V Foundation Ideas Lab Multidisciplinary Team (PHY-1545805) and Hong Kong RGC grants (N_HKUST601/17 and C6002-17G). The biospecimens for this study were provided by the Samsung Medical Center BioBank.

Author information

Author notes

  1. These authors contributed equally: Jin-Ku Lee, Zhaoqi Liu, Jason K. Sa, Sang Shin, Jiguang Wang.

Affiliations

  1. Institute for Refractory Cancer Research, Samsung Medical Center, Seoul, Republic of Korea

    • Jin-Ku Lee
    • , Jason K. Sa
    • , Sang Shin
    • , Hee Jin Cho
    • , Seung Won Choi
    • , In-Hee Lee
    • , Yong Jae Shin
    • , Hyun Ju Kang
    • , Donggeon Kim
    • , Yun Jee Seo
    • , Hyemi Shin
    • , Mijeong Lee
    • , Sung Heon Kim
    • , Yong-Jun Kwon
    • , Jeong-Woo Oh
    • , Minsuk Song
    • , Misuk Kim
    •  & Do-Hyun Nam
  2. Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Jin-Ku Lee
    • , Yong Jae Shin
    • , Sung Heon Kim
    • , Doo-Sik Kong
    • , Jung Won Choi
    • , Ho Jun Seol
    • , Jung-Il Lee
    •  & Do-Hyun Nam
  3. Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea

    • Jin-Ku Lee
    • , Jason K. Sa
    • , Hee Jin Cho
    • , In-Hee Lee
    • , Yong Jae Shin
    • , Hyun Ju Kang
    • , Donggeon Kim
    • , Yun Jee Seo
    • , Misuk Kim
    • , Yeup Yoon
    • , Gyu Ha Ryu
    • , Nayoung K. D. Kim
    • , Joon Seol Bae
    •  & Woong-Yang Park
  4. Department of Systems Biology, Columbia University, New York, NY, USA

    • Zhaoqi Liu
    • , Mykola Bordyuh
    • , Oliver Elliott
    • , Timothy Chu
    • , Daniel I. S. Rosenbloom
    •  & Raul Rabadan
  5. Department of Biomedical Informatics, Columbia University, New York, NY, USA

    • Zhaoqi Liu
    • , Mykola Bordyuh
    • , Oliver Elliott
    • , Timothy Chu
    • , Daniel I. S. Rosenbloom
    •  & Raul Rabadan
  6. Department of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul, Republic of Korea

    • Sang Shin
    • , Seung Won Choi
    • , Hyemi Shin
    • , Mijeong Lee
    • , Jeong-Woo Oh
    • , Joon Oh Park
    • , Yeup Yoon
    • , Woong-Yang Park
    • , Jeeyun Lee
    •  & Do-Hyun Nam
  7. Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China

    • Jiguang Wang
  8. Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Hong Kong, China

    • Jiguang Wang
  9. Center of Systems Biology and Human Health, Hong Kong University of Science and Technology, Hong Kong, China

    • Jiguang Wang
  10. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Sun Young Kim
    • , Moon-Hee Sim
    • , Jusun Kim
    • , Taehyang Lee
    • , Seung Tae Kim
    • , Joon Oh Park
    •  & Jeeyun Lee
  11. Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Kyoung-Mee Kim
    •  & Sang-Yong Song
  12. Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Jeong-Won Lee
  13. Deparment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Hee-Cheol Kim
    • , Jeong Eon Lee
    •  & Min Gew Choi
  14. Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Sung Wook Seo
  15. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Young Mog Shim
    •  & Jae Ill Zo
  16. Deparment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    • Byong Chang Jeong
  17. Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea

    • Nayoung K. D. Kim
    • , Joon Seol Bae
    •  & Woong-Yang Park
  18. Department of Stem Cell Biology and Regenerative Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA

    • Jeongwu Lee
  19. The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA

    • Roel G. W. Verhaak
  20. Institute for Cancer Genetics, Columbia University, New York, NY, USA

    • Antonio Iavarone
  21. Department of Neurology, Columbia University, New York, NY, USA

    • Antonio Iavarone
  22. Department of Pathology, Columbia University, New York, NY, USA

    • Antonio Iavarone

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Contributions

J.-K.L., Z.L., J.K.S., S.S. and J.W. are co-first authors. J.-K.L., Z.L., J.K.S., S.S. and J.W. performed the majority of the experiments and analyses. Z.L. and M.B. analyzed the therapeutic landscape of PDCs and pharmacogenomic interactions. D.I.S.R., O.E. and T.C. designed and constructed the cDx interactive webportal. S.W.C., D.-S.K., D.-H.N., S.T.K. and J.L. interpreted the clinical data. J.-K.L., S.S., J.-W.O., M.S., H.J.K., S.H.K., G.H.R. and Y.-J.K. organized and analyzed the drug-screening experiments. Y.J.Shin, H.J.K., Y.J.Seo, M.L., S.Y.K., M.-H.S., J.K., T.L., S.-Y.S., K.-M.K., M.K., J.O.P. and Y.Y. organized and processed the specimens for patient-derived cultures and genome analysis. D.K. and M.L. conducted the animal experiments. J.K.S., H.J.C., I.-H.L., H.S., N.K.D.K., J.S.B. and W.-Y.P. analyzed the genomic profiling. D.-S.K., J.W.C., H.J.S., J.-I.L., J.-W.L., H.-C.K., J.E.L., M.G.C., S.W.S., Y.M.S., J.I.Z. and B.C.J. provided surgical specimens. J.-K.L., Z.L., J.K.S., S.S. and J.W. wrote the manuscript with the feedback from J.L., R.G.W.V., A.I., J.L., R.R. and D.-H.N. J.L., R.R. and D.-H.N. designed and supervised the entire project.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Jeeyun Lee or Raul Rabadan or Do-Hyun Nam.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–15

  2. Reporting Summary

  3. Supplementary Table 1

    Clinical information of the pan-cancer patients included in this study

  4. Supplementary Table 2

    CancerSCAN (targeted exome sequencing) gene list

  5. Supplementary Table 3

    GliomaSCAN (targeted exome sequencing) gene list

  6. Supplementary Table 4

    List of detected genomic alterations (mutation, fusion, copy number variation)

  7. Supplementary Table 5

    List of the 60-drug panel

  8. Supplementary Table 6

    Sixty-drug library quality control

  9. Supplementary Table 7

    Area under the curve (AUC) for the dose–response curve (DRC)

  10. Supplementary Table 8

    Half-maximal inhibitory concentration of drug sensitivity

  11. Supplementary Table 9

    Cancer-type-specific drug associations

  12. Supplementary Table 10

    Topolgoical data analysis of cancer-type-specific drug associations

  13. Supplementary Table 11

    Single genomic alteration–drug associations

  14. Supplementary Table 12

    Genetic features associated with panobinostat response using dNetFS

  15. Supplementary Table 13

    Genetic features associated with EGFR inhibitor response using dNetFS

  16. Supplementary Table 14

    Clinical responses in retrospective cases

About this article

Publication history

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DOI

https://doi.org/10.1038/s41588-018-0209-6

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