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High-throughput dynamic BH3 profiling may quickly and accurately predict effective therapies in solid tumors
Author(s) -
Patrick Bhola,
Eman Y. Ahmed,
Jennifer L. Guerriero,
Ewa Sicińska,
Emily Chia Yu Su,
Elizaveta Lavrova,
Jing Ni,
Otari Chipashvili,
Timothy Hagan,
Marissa S. Pioso,
Kelley E. McQueeney,
Kimmie Ng,
Andrew J. Aguirre,
James M. Cleary,
David Cocozziello,
Alaba Sotayo,
Jeremy Ryan,
Jean J. Zhao,
Anthony Letaï
Publication year - 2020
Publication title -
science signaling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.659
H-Index - 154
eISSN - 1937-9145
pISSN - 1945-0877
DOI - 10.1126/scisignal.aay1451
Subject(s) - ex vivo , in vivo , cancer research , cancer cell , computational biology , cancer , biology , bioinformatics , medicine , microbiology and biotechnology
Despite decades of effort, the sensitivity of patient tumors to individual drugs is often not predictable on the basis of molecular markers alone. Therefore, unbiased, high-throughput approaches to match patient tumors to effective drugs, without requiring a priori molecular hypotheses, are critically needed. Here, we improved upon a method that we previously reported and developed called high-throughput dynamic BH3 profiling (HT-DBP). HT-DBP is a microscopy-based, single-cell resolution assay that enables chemical screens of hundreds to thousands of candidate drugs on freshly isolated tumor cells. The method identifies chemical inducers of mitochondrial apoptotic signaling, a mechanism of cell death. HT-DBP requires only 24 hours of ex vivo culture, which enables a more immediate study of fresh primary tumor cells and minimizes adaptive changes that occur with prolonged ex vivo culture. Effective compounds identified by HT-DBP induced tumor regression in genetically engineered and patient-derived xenograft (PDX) models of breast cancer. We additionally found that chemical vulnerabilities changed as cancer cells expanded ex vivo. Furthermore, using PDX models of colon cancer and resected tumors from colon cancer patients, our data demonstrated that HT-DBP could be used to generate personalized pharmacotypes. Thus, HT-DBP appears to be an ex vivo functional method with sufficient scale to simultaneously function as a companion diagnostic, therapeutic personalization, and discovery tool.

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