Multidrug Analyses in Patients Distinguish Efficacious Cancer Agents Based on Both Tumor Cell Killing and Immunomodulation.

Multidrug Analyses in Patients Distinguish Efficacious Cancer Agents Based on Both Tumor Cell Killing and Immunomodulation.
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DOI:
10.1158/0008-5472.can-17-0084
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发表时间:
2017-06-01
期刊:
影响因子:
11.2
通讯作者:
Klinghoffer RA
Klinghoffer RA
中科院分区:
医学1区
文献类型:
--
作者:
Frazier JP;Bertout JA;Kerwin WS;Moreno-Gonzalez A;Casalini JR;Grenley MO;Beirne E;Watts KL;Keener A;Thirstrup DJ;Tretyak I;Ditzler SH;Tripp CD;Choy K;Gillings S;Breit MN;Meleo KA;Rizzo V;Herrera CL;Perry JA;Amaravadi RK;Olson JM;Klinghoffer RA

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The vision of a precision medicine–guided approach to novel cancer drug development is challenged by high intratumor heterogeneity and interpatient diversity. This complexity is rarely modeled accurately during preclinical drug development, hampering predictions of clinical drug efficacy. To address this issue, we developed Comparative In Vivo Oncology (CIVO) arrayed microinjection technology to test tumor responsiveness to simultaneous microdoses of multiple drugs directly in a patient’s tumor. Here, in a study of 18 canine patients with soft tissue sarcoma (STS), CIVO captured complex, patient-specific tumor responses encompassing both cancer cells and multiple immune infiltrates following localized exposure to different chemotherapy agents. CIVO also classified patient-specific tumor resistance to the most effective agent, doxorubicin, and further enabled assessment of a preclinical autophagy inhibitor, PS-1001, to reverse doxorubicin resistance. In a CIVO-identified subset of doxorubicin-resistant tumors, PS-1001 resulted in enhanced antitumor activity, increased infiltration of macrophages, and skewed this infiltrate toward M1 polarization. The ability to evaluate and cross-compare multiple drugs and drug combinations simultaneously in living tumors and across a diverse immunocompetent patient population may provide a foundation from which to make informed drug development decisions. This method also represents a viable functional approach to complement current precision oncology strategies.