journal article·2016-06-28

Rationally Designed 2-in-1 Nanoparticles Can Overcome Adaptive Resistance in Cancer

Aaron Goldman, Ashish Kulkarni, Mohammad Kohandel, Prithvi Pandey, Poornima Rao, Siva Kumar Natarajan, Venkata Sabbisetti, Shiladitya Sengupta

ACS Nano· Volume 10· Issue 6
Publisher page

Abstract

The development of resistance is the major cause of mortality in cancer. Combination chemotherapy is used clinically to reduce the probability of evolution of resistance. A similar trend toward the use of combinations of drugs is also emerging in the application of cancer nanomedicine. However, should a combination of two drugs be delivered from a single nanoparticle or should they be delivered in two different nanoparticles for maximal efficacy? We explored these questions in the context of adaptive resistance, which emerges as a phenotypic response of cancer cells to chemotherapy. We studied the phenotypic dynamics of breast cancer cells under cytotoxic chemotherapeutic stress and analyzed the data using a phenomenological mathematical model. We demonstrate that cancer cells can develop adaptive resistance by entering into a predetermined transitional trajectory that leads to phenocopies of inherently chemoresistant cancer cells. Disrupting this deterministic program requires a unique combination of inhibitors and cytotoxic agents. Using two such combinations, we demonstrate that a 2-in-1 nanomedicine can induce greater antitumor efficacy by ensuring that the origins of adaptive resistance are terminated by deterministic spatially constrained delivery of both drugs to the target cells. In contrast, a combination of free-form drugs or two nanoparticles, each carrying a single payload, is less effective, arising from a stochastic distribution to cells. These findings suggest that 2-in-1 nanomedicines could emerge as an important strategy for targeting adaptive resistance, resulting in increased antitumor efficacy.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Mathematical Biology Tumor Growth · Cancer Cells and Metastasis · Microtubule and mitosis dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States

Harvard−MIT Division of Health Sciences and Technology, Cambridge, Massachusetts 02139, United States

Division of Biomedical Engineering, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts 02115, United States

Harvard Digestive Diseases Center, Boston, Massachusetts 02115, United States

Department of Applied Mathematics, University of Waterloo, Waterloo, ON N2L 3G1, Canada

India Innovation Research Center, Invictus Oncology, New Delhi 92, India

Dana Farber Cancer Institute, Boston, Massachusetts 02115, United States

Funding

National Cancer Institute · Indo-US Science and Technology Forum · Congressionally Directed Medical Research Programs · American Lung Association · American Cancer Society

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