Analysis of CRISPR-Cas9 datasets leads to largest genetic screen resource for cancer research

Study will help narrow down the list of targets for the next generation of cancer treatments

A comprehensive map of genes necessary for cancer survival is one step closer, following the validation of the two largest CRISPR-Cas9 genetic screens in 725 cancer models, across 25 different cancer types. Scientists at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard compared the consistency of the two datasets, independently verifying the methodology and findings.

The results, published today (20 December 2019) in Nature Communications, mean that the two datasets can be integrated to form the largest genetic screen of cancer cell lines to date, which will provide the basis for the Cancer Dependency Map in around 1,000 cancer models. The scale of this combined dataset will help to speed up the discovery and development of new cancer drugs.

The Cancer Dependency Map (Cancer DepMap) initiative* aims to create a detailed rulebook of precision cancer treatments for patients. Two key elements of the Cancer DepMap are the mapping of the genes critical for the survival of cancer cells and analytics of the resulting datasets. Despite recent advances in cancer research, making precision medicine widely available to cancer patients requires many new drug targets.

To find these drug targets, Cancer DepMap researchers take tumour cells from patients to create cell lines that can be grown in the laboratory. They then use CRISPR-Cas9 technology to edit the genes in these cancer cells, turning them off one-by-one to measure how critical they are for the cancer to survive. The results of these experiments indicate which genes are the most likely to make viable drug targets.

In this new study, researchers analysed data from two recently published CRISPR-Cas9 genetic screens performed on cancer cell lines at the Broad and Sanger Institutes. Despite significant differences in experimental protocols, the team found that the screen results were consistent with one another. Crucially, the same genes essential to cancer survival – known as dependencies – were found in both datasets.

“The Sanger and Broad Institute CRISPR-Cas9 screens were created using slightly different protocols, such as cell growth duration and reagents used. To verify each Institute’s dataset, we have repeated CRISPR-Cas9 screens using the protocols originally employed at the other Institute. Importantly, we have found the same genetic dependencies in each, meaning the new drug targets originally identified are consistent.”

Dr Clare Pacini A first author of the study from the Wellcome Sanger Institute and Open Targets

“This is the first analysis of its kind and is really important for the whole cancer research community. Not only have we reproduced common and specific dependencies across the two datasets, but we have taken biomarkers of gene dependency found in one dataset and recovered them in the other. Our analysis has been unbiased, rigorous and proves the veracity of the approach and the drug targets identified.”

Aviad Tsherniak Of the Broad Institute of MIT and Harvard

In 2013, results comparing two large pharmacogenomic datasets employing the cancer models used in this study raised concerns about the reproducibility of the experiments performed. Further independently-published analyses eventually proved the two resources to be reliable and consistent, restoring confidence in the robustness of large-scale drug screens, but the episode slowed the progress of cancer research.

This study validates the reproducibility of CRISPR-Cas9 functional genetic screens in order to remove any doubt about their efficacy. It sets rigorous standards for assessing these new types of dataset, facilitating the comparison and integration of large databases of cancer dependencies.

“It is worth remembering that when these datasets were originally produced we were dealing with a new, unproven technology. This study is important because it demonstrates the validity of the experimental methods and the consistency of the data that they produce. It also means that two large cancer dependency datasets are compatible. By joining them together, we will have access to much greater statistical power to narrow down the list of targets for the next generation of cancer treatments.”

Dr Francesco Iorio Of the Wellcome Sanger Institute and Open Targets

More information

* Mapping the dependencies of cancers is an international effort by the Sanger Institute in the UK and the Broad Institute in the United States. Researchers aim to bridge the translational gap that exists between genomic sequencing and providing precision medicine to the many cancer patients. Genes that are critical to a cancer’s survival represent dependencies: vulnerabilities that might serve as targets for designing new therapies or repurposing existing ones. Mapping these dependencies is essential to making precision cancer medicine a reality.

For more information about the Cancer Dependency Map initiative at the Sanger Institute, see https://depmap.sanger.ac.uk/

Publication:

Joshua M. Dempster, Clare Pacini and Sasha Pantel et al. (2019) Agreement between two large pan-cancer CRISPR-Cas9 gene dependency datasets. Nature Communications. DOI: https://www.doi.org/10.1038/s41467-019-13805-y

Funding:

This work was funded by Open Targets, Wellcome, the Estonian Research Council and the HL Snyder Foundation.