Sara Cooper, PhD / Cooper Lab
Predicting multi-drug resistance in cancer using CRISPR technology
Although many cancers are initially susceptible to chemotherapy, over time they can develop resistance and stop responding to the treatment. This resistance is what leads to progression of the disease and is the ultimate cause of death for many cancer patients. The development of multiple drug resistance (MDR) is one of the major challenges in cancer treatment and represents the leading cause of treatment failure. Cancer cells acquire MDR in many ways. Scientists have identified changes in cancer cells grown in a dish that change how they respond to drugs. Some of these changes include increased expression of transporter pumps that remove the drugs from the cancer cell, met- abolic changes that break down the drug, and changes in cell cycle checkpoints that would normally prevent cell division in the presence of certain drugs. However, the translation of this knowledge to the clinic has not been widely successful. Therefore, identifying genes and mechanisms critical to the development of MDR and establishing a reliable method for detecting them in clinical samples could help predict the development of resistance and lead to treatments designed to avoid it.
their pancreatic cancer study were published to the preprint server bioRxiv in October 2020 1 . The group used CRISPR gene editing technology to activate and knockout genes in pancreatic cancer cell lines. They conducted four genome-wide CRISPR activation and knockout screens to identify genes whose loss or gain of expression were able to alter sensitivity to four of the most common chemotherapies used in the treat- ment of pancreatic cancer (gemcitabine, 5-fluorouracil, irinotecan, and oxaliplatin).
CRISPR activation of the cellular transport pump ABCG2 induced resistance in cell lines across each of the drug treatments. ABCG2 has been associated with multiple drug resistance in several previous studies. However, when the group looked at ABCG2 expression in pancreatic tumors from patients it was not high- ly expressed, suggesting it does not have significant relevance in patients. Further analysis of the CRISPR screen identified additional genes that were relevant for resistance in patient tissues. Using an algorithm developed in their lab, the group computed drug sen- sitivity scores based on expression levels of resis- tance genes, and separated cell lines and patients into different treatment response groups. Genes identified by the CRISPR screen could be used to predict drug sensitivity in cell lines and patients based on their gene expression profiles and direct personalized therapeutic approaches.
Sara Cooper, PhD in the lab
At the HudsonAlpha Institute for Biotechnolo- gy, Faculty Investigator Sara Cooper, PhD, and her lab are using genome-wide CRISPR screening methods to identify genes associated with chemotherapy resis- tance in pancreatic and ovarian cancer. Results from
HudsonAlpha Institute for Biotechnology
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