Bacteria readily acquires a sequence of other species’ DNA into their own, in specific areas that we now call CRISPR. In the lab, CRISPR was synthesized by linking together two guide RNA sequences into a format that would provide the target information and allow us to edit multiple genes simultaneously.
Cancer is a genetic disease, it works by creating certain changes to genes that control the way our cells function, especially how they grow and divide. Some rare cancers, sarcomas in particular, have been treated using CRISPR, which is why the gene-editing tool seems like a good diagnostic and therapeutic tool in the future of cancer treatments.
Obtaining rare cancerous tumors for research is difficult, but luckily organizations such as Pattern.org and the Rare Cancer Research Foundation (RCRF) come into play. These sister groups perform a matching program that enables patients to directly donate their tumor tissue and medical data to research. All the data generated by the project is freely available to the research community and is dedicated to open science.
“Using Pattern.org, the Broad Institute of MIT and Harvard has created over 40 next-generation de-identified cancer models,” Ms. Barbara Van Hare, Director of Foundation partnerships at RCRF said, “These models and associated data will be shared within the worldwide research community.”
After procuring these rare disease samples, Dr. Jesse Boehm from Eli and Edythe L. Broad Institute might have the answer to decipher the genetic landscape of cancer cells and use that to our advantage. Dr. Boehm is the scientific director of the Broad Institute’s Cancer Dependency Map Initiative where he works on the cancer cell line factory project and the cancer dependency map.
Cancer samples are broken apart into cell models and are coaxed into growing in different conditions over a year-long time period. The data from these new cell models are then shared broadly with the world. This is a pipeline activity called the cell line factory. It is a part of an international effort to create a large reference data set, that is called the cancer dependency map.
The cancer dependency map has a two-pronged approach, first by testing cell lines against drugs and then pooled CRISPR screening. First, all cell lines are systematically tested against all drugs developed for any disease. Some known drugs have shown to be effective against certain cancers, clinical trials are swift as these are existing therapies.
“There are 20,000 proteins in the human genome and only 6000 drug therapies. Only five percent of human genes can be targeted with drugs. The cancer dependency Map is completed with the help of CRISPR,” Dr Boehm said.
Pooled CRISPR screening is used and 100,000 CRISPRs target every gene in the genome. Every cell is challenged with all these CRISPRs and at the end of the experiment, the abundance is compared to the beginning of the experiment.
CRISPR is used to snip genes,the DNA repairs creating a broken gene. Cells that are required for viability die and drop out of the population. CRISPRs are bar coded, so if by the end of the experiment the CRISPR is absent, it targets the gene that the cell needed to survive. The genes that drop out are good drug targets, most of these make way for drug discovery projects right away.
“CRISPR is such a sharp tool, it inspires a lot more confidence than its predecessors,” Dr Boehm said. He uses the analogy of Google Maps for this project: “It needs to tell clinicians what to do and where to go, but for it to be relevant-the data needs to be dense enough in that area.”
An additional therapy for cancers involves making four genetic modifications to T cells (immune cells that can kill cancer). It basically adds genes to T cells to fight cancer. One of these is a synthetic gene that gives the T cells a protein that can identify cancer cells better. CRISPR is also used to mute three genes that limit the cells’ cancer-killing abilities (Stadtmauer et al. 2020). With these limiting genes removed, the T cells are less inhibited to fight cancer.
These therapeutics and the Cancer dependency map will take a few decades to develop but will prove to be a very sharp tool in our arsenal against rare cancers when complete.
References:
- Boehm JS, Golub TR. An ecosystem of cancer cell line factories to support a cancer dependency map. Nat Rev Genet. 2015 Jul;16(7):373-4.
- M. Jinek, K. Chylinski, I. Fonfara, M.Hauer, J.A. Doudna, E. Charpentier, A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science, 337 (2012), pp. 816–821.
- Stadtmauer, E. A., Fraietta, J. A., Davis, M. M., Cohen, A. D., Weber, K. L., Lancaster, E., … & Tian, L. (2020). CRISPR-engineered T cells in patients with refractory cancer. Science, 367(6481).
- Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., … & Meyers, R. M. (2017). Defining a cancer dependency map. Cell, 170(3), 564-576.
