Synthetic lethality is a circumstance in which a drug is selectively deadly to cancer cells due to the mutations and genetic changes that have occurred during oncogenesis and progression. Oftentimes a cancer will lose redundancy, that is it will jettison certain survival/ repair mechanisms in favor of increased proliferation. By definition normal cells have not acquired these mutations, so synthetic lethal therapies should have limited toxic effect specifically targeting a cancer’s idiosyncrasy.
Finding synthetic lethal agents, such as inhibitors of poly-(ADP-ribose) polymerase 1 (PARP1) for BRCA1 and BRCA2 (DNA repair) deficient tumors, is a very attractive strategy for cancer drug discovery as such entities should have limited side effects compared to standard regimens such as chemotherapy. A cancer with a high rate of chromosomal instability (CIN) is more likely to contain synthetic lethal vulnerabilities than genetically more stable cancers. They are also potentially more susceptible to immunotherapies, which is being clinically investigated.
According to data from the Institute for Health Metrics and Evaluation, Seattle, 175,982 people died of ovarian cancer, world-wide, in 2017, the 14th most frequent cause of cancer death. The most prevalent form of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC), which is believed to originate from the fallopian tube is a cancer with a high CIN rate, permitted by mutant TP53.
Treatment options are limited, typically as much cancer is removed as possible from the abdominal region by cytoreductive (debulking) surgery followed by platinum/paclitaxel-based chemotherapy with or without anti-VEGF-A bevacizumab (Avastin). Estimated median overall survival time was 3 years, 8 months (43.8 months total), following initial surgical resection and treatment with bevacizumab combined with chemotherapy and then maintained by single-agent bevacizumab in a clinical trial (NCT00262847) of patients with epithelial ovarian, fallopian tube, or primary peritoneal cancer.
While many patients initially respond well to first line treatment, most develop recurrent disease, yielding relatively poor survival rates. More synthetic lethal follow-on options than only PARP inhibitors are needed, but suitable tools for drug discovery and development are required.
With this in mind Stephen S. Taylor of the University of Manchester, UK, and colleagues recently developed clinically annotated models that recapitulate HGSOC, building a living biobank of thus far 76 ex vivo cultures, and 312 patient samples. The methodology was published in the journal Nature Communications.
As proof of principle 15 ovarian cancer models (OCMs) were fully characterized by the latest cell and molecular biology techniques including exome, and single cell sequencing, followed by chemotherapy sensitivity profiling. There was a good correlation between the chemotherapy sensitivity of the OCMs and the therapy responses seen in the corresponding patients. Responses to paclitaxel were varied both between samples and between cancer cells within samples as has been previously observed. This confirms the utility of the models, which could be profiled for sensitivity to new drugs in the future.
A limitation of the methodology is that an OCM establishment success rate of only 26.2% was achieved, creating a selection bias that may impact the generalizability of results obtained from such models. It should not impact any patient personalized clinical inferences (acting as “predictive patient avatars”) that can be drawn. The authors note that they are investigating workflow modifications to increase the success rate.
“Living biobanks can potentially address limitations associated with established cancer cell lines, and indeed, our analysis shows that thus far, we have grossly underestimated the mitotic dysfunction in advanced human tumours. The biopsy pipeline and workflow we describe here generates ex vivo ovarian cancer cultures with extensive proliferative potential, rendering models amenable to detailed cell cycle studies, including characterisation of mitotic chromosome segregation and drug sensitivity profiling.”