2. Academic Validation
  3. A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

  • Commun Biol. 2022 Nov 26;5(1):1295. doi: 10.1038/s42003-022-04270-3.
Robert J Kimmerling # 1,  Mark M Stevens # 2,  Selim Olcum # 2,  Anthony Minnah # 2,  Madeleine Vacha # 2,  Rachel LaBella # 2,  Matthew Ferri 2,  Steven C Wasserman 2,  Juanita Fujii 3,  Zayna Shaheen 3,  Srividya Sundaresan 3,  Drew Ribadeneyra 4,  David S Jayabalan 4,  Sarita Agte 5 6,  Adolfo Aleman 5 6 7,  Joseph A Criscitiello 8,  Ruben Niesvizky 4,  Marlise R Luskin 8,  Samir Parekh 5 6 9 10,  Cara A Rosenbaum 4,  Anobel Tamrazi 11,  Clifford A Reid 12
Affiliations

Affiliations

  • 1 Travera, Medford, MA, USA. rkimmerling@travera.com.
  • 2 Travera, Medford, MA, USA.
  • 3 Department of Clinical Research, Dignity Health, Sequoia Hospital, Redwood City, CA, USA.
  • 4 Weill Cornell Medicine, New York, NY, USA.
  • 5 Department of Medicine, Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • 6 Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • 7 Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • 8 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • 9 Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • 10 Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • 11 Division of Vascular and Interventional Radiology, Palo Alto Medical Foundation, Redwood City, CA, USA.
  • 12 Travera, Medford, MA, USA. creid@travera.com.
  • # Contributed equally.
PMID: 36435843 DOI: 10.1038/s42003-022-04270-3
Abstract

Functional precision medicine offers a promising complement to genomics-based Cancer therapy guidance by testing drug efficacy directly on a patient's tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for Cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of Cancer drug response.

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