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Synthetic Lethal Phenotype Identification through Cancer Evolution Analysis

Periodic Reporting for period 3 - SPICE (Synthetic Lethal Phenotype Identification through Cancer Evolution Analysis)

Reporting period: 2018-10-01 to 2020-03-31

Human cancer is a widely spread disease that is often characterized by DNA alterations. In the last ten years, enormous progress in DNA sequencing technology has revolutionized genomic research; using Next Generation Sequencing (NGS) an entire human genome can be sequenced within a single day, at dramatically reduced costs. This has allowed the scientific community to sequence thousands of tumor samples and to compare their DNA with their healthy counterparts. Such sequencing effort generated a massive amount of genomic data that can be mined to identify cancer vulnerabilities. The overall aim of the SPICE research project is to identify those vulnerabilities. Specifically, mapping DNA alterations to the disruption of genes that accelerate disease progression potentially allows us to nominate new drug targets for patients with advanced disease. With SPICE the search for drug targets is based on a property of human cells, referred to as synthetic lethality, where the concomitant disruption of specific pairs (or combinations) of genes is fatal for the cell itself, while the disruption of one single gene is not. In practice, for such a gene combination and in the presence of the alteration of one gene in the tumor cells of a patient, a treatment to intentionally disrupt the second gene is selected; this will lead to a selective effect on tumor cells only while sparing all healthy cells. This approach could enormously reduce the toxic effects compared to the traditional chemotherapeutic drugs and improve the quality of life of cancer patients. In order to enhance the chances to nominate these drug targets, in this project we implement unbiased searches of biomarkers and synthetic lethal gene pairs using computational and mathematical methods to learn from the genomes of thousands of patients’ cancer cells and experimentally validate the most promising findings using state of the art techniques, including genome editing.

The project is designed to address specific clinical questions in the setting of lethal prostate cancers. Prostate cancer is a genetically and clinically heterogeneous disease with high incidence in the population; advances in targeted therapy have recently led to more effective management of metastatic disease, however it still results in the second cause of cancer death in men. While the focus is prostate cancer, the SPICE methodology can seemingly be transferred to diverse tumor types and is expected to extend both technology and knowledge beyond the state-of-the art. At the completion of the study, we intend to share our results with the scientific community and provide direct access to the research community to the data emerging from our large-scale computations.
The progress of the SPICE project counts on a motivated team of experimental biologists and computer scientists, dedicated computational power and storage, and experimental facilities for sequencing and large scale screenings. Importantly, cross-talk with senior scientists with diverse expertise and established international collaborations in the setting of prostate cancer enhances the capability of the team to utilize cutting-edge experimental tools and to tune the specific goals of the project to current advances in the clinical settings. Three main activities were pursued from the beginning of the project:
1) Significant effort was dedicated to design and implement robust and innovative computational approaches to the processing and mining of thousands of tumor samples at base-pair resolution. This activity is now completed. It led to the following main results: a) a pipeline to be used on any NGS dataset, b) a ultra-fast approach nominating potential synthetic lethal pairs, and c) comprehensive lists of synthetic lethal pairs tumor specific and non-specific. Those lists are now being considered for most promising nominated biomarkers and pairs for experimental validation.
2) Given the urgency to characterize the lethal class of prostate cancer, we focused on a set of patients that undergo tumor transformation during drug treatment and studied the genomics and biochemical characteristics of those tumors. This work led to the discovery of biomarkers that are now being studied in larger cohorts.
3) In parallel, combining preliminary data and knowledge driven selection criteria, we identified two pairs of potential synthetic lethality in prostate and bladder cancer and performed experimental work for their functional characterization. This work is ongoing.
The progress of the SPICE project relies on the continuous exchanges between experimental biologists, computer scientists, and clinicians, dedicated computational power and storage, and experimental facilities for sequencing and large scale screenings.

Thanks to the continuous and efficient interactions between the team members and integration of computational and biological knowledge, we designed a pipeline to be used on any NGS dataset, and an ultra-fast approach to nominate potential synthetic lethal pairs, named FaME (Fast Mutual Exclusivity). Such resources will be made available to the whole research community with the potential of accelerating drug discovery in fields beyond prostate and bladder cancer. Our team is now performing experimental work for the validation of two pairs of potential synthetic lethality genes in prostate and bladder cancer, while other pairs are shortlisted for further investigation. Our aim for the end of the project is to be able to propose novel therapeutic strategies.
Schematics of the SPICE project