Patient-derived Models of Resistant Cancers

Patient-derived Models of Resistant Cancers

Download the Summer 2015 issue of Advances PDF

Can cultured strains from patients promote individualized cancer therapy?

Medicines are increasingly tailored to the genetic and molecular signatures of individual cancers. But most tumors quickly develop resistance to drug T-Cell lines derived from patient biopsy therapies designed to inhibit target oncogenes, either through secondary resistance mutations in the oncogene or through the development of a “bypass track” that reactivates downstream proliferation and survival signals, which keeps the cell line alive even after the oncogene has turned off.1 To identify personalized combinations of drugs that can overcome this resistance, a team of researchers from Massachusetts General Hospital Cancer Center helped to develop an innovative pharmacogenomic strategy, described in research published in the December 2014 issue of Science.

The study was a coordinated multi-disciplinary effort spearheaded by researchers from Mass General Cancer Center. The team was led by Mass General medical oncologist Adam S. Crystal, MD, PhD; Jeffrey A. Engelman, MD, PhD, director of the Center for Thoracic Cancers at Mass General Cancer Center; Cyril Benes, PhD, director of the Center for Molecular Therapeutics at Mass General; and Alice T. Shaw, MD, PhD, thoracic oncologist at the Mass General Cancer Center, among others.

Culturing Resistant Cell Lines From Patient Biopsies

Using irradiated feeder cells, the team was able to grow lab cultures of 60 resistant cancer cell lines directly from biopsies of cancer patients. This offered an advance on previous efforts to study resistance, which focused on two more problematic approaches: growing cell lines until drug resistance emerged, and analyzing biopsies of resistant cells to identify genetic anomalies.

Using these lab-grown cell lines, 201 different combinations of drugs were found to serve as effective therapies, or about 3.4 “hits” per cell line. The researchers genetically sequenced the cells and compared this against their pharmacological results to identify potential genetic causes of resistance. They were also able to detect previously unknown mechanisms of resistance that could not have been identified by genetic analysis alone. Such an approach can be helpful in the development of personalized therapies for resistant cancers that arise in clinical settings and guide future studies of cancer cell drug resistance.

The resistant biopsy cells were taken from patients with non-small cell lung cancers (NSCLCs) that had progressed in spite of treatment with common targeted oncogene therapies, such as EGFR or ALK tyrosine kinase inhibitors.2 To grow the resistant cell lines, in many cases, the researchers established cell viability on growth-arrested but bioactive “feeder” cells, and then transitioned off those cells prior to screening. The team had a 50 percent success rate at growing cell lines in the lab out of effusions and biopsy samples taken from NSCLC patients. Cell lines established from biopsy samples had a 38 percent survival rate.

Identifying Mechanisms of Resistance and Combination Therapies

To identify drug combinations that could effectively treat acquired resistance, the group then subjected these cells to 76 different pharmacological agents as single agents and in the presence of a single fixed concentration of the primary tyrosine kinase inhibitor (TKI) that inhibited the original oncogene. The 76 drugs were directed at a range of key regulators of cell proliferation and survival, including growth factor and development signaling pathways, apoptosis regulators, transcription and protein-folding machinery, and DNA damage sensors.

Their approach built on prior work that identified so-called bypass track mechanisms of acquired resistance, in which the original oncogene and bypass track both promote cell survival and proliferation through downstream signaling, such as PI3K (phosphatidylinositol 3-kinase) and MAPK (mitogen-activated protein kinase) pathways. To arrest growth and kill these cells requires simultaneous inhibition of the primary driver oncogene and the bypass track.

The soundness of their strategy was verified against five previously established models of acquired resistance developed in vitro with known bypass tracks. In these previously investigated models, unbiased screening of the 76 drug panels successfully identified known inhibitors. To identify effective combination treatments, the researchers then tested these same drug panels against 55 models of acquired resistance with unknown mechanisms of resistance.

Researchers are currently working to speed up testing so that effective drug combinations for individual patients can be identified as a routine diagnostic test within three to four weeks.

References:

(1) Crystal, Adam S., Alice T. Shaw, Lecia V. Sequist, et al., “Patient-Derived Models of Acquired Resistance Can Identify Effective Drug Combinations for Cancer,” Science, vol. 346, no. 6126 (Dec. 2014): 1480-1486.

(2) Niederst, Matthew J, and Jeffrey A. Engelman,“Bypass Mechanisms of Resistance to Receptor Tyrosine Kinase Inhibition in Lung Cancer,” Science Signaling, vol. 6, no. 294 (Sept. 2013): re6.