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Integrated genomics and functional validation identifies malignant cell specific dependencies in triple negative breast cancer

Author

Listed:
  • Nirmesh Patel

    (King’s College London
    King’s College London)

  • Daniel Weekes

    (King’s College London
    King’s College London)

  • Konstantinos Drosopoulos

    (The Institute of Cancer Research)

  • Patrycja Gazinska

    (King’s College London
    King’s College London)

  • Elodie Noel

    (King’s College London
    King’s College London)

  • Mamun Rashid

    (King’s College London
    King’s College London)

  • Hasan Mirza

    (King’s College London
    King’s College London
    King’s College London)

  • Jelmar Quist

    (King’s College London
    King’s College London
    King’s College London)

  • Fara Brasó-Maristany

    (King’s College London
    King’s College London)

  • Sumi Mathew

    (King’s College London
    King’s College London)

  • Riccardo Ferro

    (King’s College London
    King’s College London)

  • Ana Mendes Pereira

    (King’s College London
    King’s College London)

  • Cynthia Prince

    (King’s College London
    King’s College London)

  • Farzana Noor

    (King’s College London
    King’s College London)

  • Erika Francesch-Domenech

    (King’s College London
    King’s College London)

  • Rebecca Marlow

    (King’s College London
    King’s College London)

  • Emanuele de Rinaldis

    (King’s College London
    King’s College London
    Sanofi)

  • Anita Grigoriadis

    (King’s College London
    King’s College London
    King’s College London)

  • Spiros Linardopoulos

    (The Institute of Cancer Research
    The Institute of Cancer Research)

  • Pierfrancesco Marra

    (King’s College London
    King’s College London)

  • Andrew N. J. Tutt

    (King’s College London
    King’s College London
    The Institute of Cancer Research)

Abstract

Triple negative breast cancers (TNBCs) lack recurrent targetable driver mutations but demonstrate frequent copy number aberrations (CNAs). Here, we describe an integrative genomic and RNAi-based approach that identifies and validates gene addictions in TNBCs. CNAs and gene expression alterations are integrated and genes scored for pre-specified target features revealing 130 candidate genes. We test functional dependence on each of these genes using RNAi in breast cancer and non-malignant cells, validating malignant cell selective dependence upon 37 of 130 genes. Further analysis reveals a cluster of 13 TNBC addiction genes frequently co-upregulated that includes genes regulating cell cycle checkpoints, DNA damage response, and malignant cell selective mitotic genes. We validate the mechanism of addiction to a potential drug target: the mitotic kinesin family member C1 (KIFC1/HSET), essential for successful bipolar division of centrosome-amplified malignant cells and develop a potential selection biomarker to identify patients with tumors exhibiting centrosome amplification.

Suggested Citation

  • Nirmesh Patel & Daniel Weekes & Konstantinos Drosopoulos & Patrycja Gazinska & Elodie Noel & Mamun Rashid & Hasan Mirza & Jelmar Quist & Fara Brasó-Maristany & Sumi Mathew & Riccardo Ferro & Ana Mende, 2018. "Integrated genomics and functional validation identifies malignant cell specific dependencies in triple negative breast cancer," Nature Communications, Nature, vol. 9(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03283-z
    DOI: 10.1038/s41467-018-03283-z
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