Anti-myeloma activity and molecular logic operation by Natural Killer cells in microfluidic droplets.

agent-based model dynamic imaging microfluidics nanoliter droplets single cell analysis

Journal

Sensors and actuators. B, Chemical
ISSN: 0925-4005
Titre abrégé: Sens Actuators B Chem
Pays: Switzerland
ID NLM: 101149755

Informations de publication

Date de publication:
01 Mar 2019
Historique:
entrez: 21 9 2019
pubmed: 21 9 2019
medline: 21 9 2019
Statut: ppublish

Résumé

Immune-targeted therapies that activate effector lymphocytes such as Natural Killer (NK) cells are currently being investigated for the treatment of Multiple myeloma (MM), the second most common form of hematological cancer. However, individual NK cells are highly heterogeneous in their cytolytic potential, making it difficult to detect, quantify and correlate the outcome of dynamic effector-target cell interactions at single cell resolution. Here, we present a microfluidic bioassay platform capable of activity-based screening of cellular and molecular immunotherapies. We identified distinct functional signatures associated with NK-MM cell interaction. The addition of immunomodulatory drug lenalidomide altered responses of NK-susceptible MM cells but not that of NK-tolerant MM cells. Antitumor cytotoxicity was significantly increased by the blockade of PD1/PDL1 axis as well as the clinically relevant cell line NK92, which were used to construct molecular logic functions (AND and NOT gates). A predictive agent-based mathematical model was developed to simulate progressive disease states and drug efficacy. The findings of the current study validate the applicability of this microfluidic cytotoxicity assay for immunotherapy screening, biocomputation and for future employment in detection of patient-specific cell response for precision medicine.

Identifiants

pubmed: 31537955
doi: 10.1016/j.snb.2018.11.068
pmc: PMC6752214
mid: NIHMS1514479
doi:

Types de publication

Journal Article

Langues

eng

Pagination

580-589

Subventions

Organisme : NCI NIH HHS
ID : R21 CA174401
Pays : United States

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Auteurs

Saheli Sarkar (S)

Department of Pharmaceutical Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115.

Seamus McKenney (S)

Department of Pharmaceutical Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115.

Pooja Sabhachandani (P)

Department of Pharmaceutical Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115.

James Adler (J)

Department of Mathematics, School of Arts and Sciences, Tufts University, Medford, MA 02155.

Xiaozhe Hu (X)

Department of Mathematics, School of Arts and Sciences, Tufts University, Medford, MA 02155.

Dina Stroopinksy (D)

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115.

Jacalyn Rosenblatt (J)

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115.

David Avigan (D)

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115.

Tania Konry (T)

Department of Pharmaceutical Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115.

Classifications MeSH