SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery.

Area of Science:

• Genomics
• Computational Biology
• Cancer Research

Background:

• Synthetic lethal interactions (SLIs) are genetic interactions where simultaneous gene inactivation causes cell death.
• SLIs are promising therapeutic targets in cancer, as shown by PARP inhibitors for BRCA1/2-deficient tumors.
• Predicting SLIs is challenging due to large multi-omic datasets and diverse computational approaches.

Purpose of the Study:

• To introduce SL-Cloud, a novel component of the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC).
• To provide an integrated framework for cloud-hosted data and curated workflows to simplify SLI prediction.
• To address challenges in SLI inference, including data preprocessing and the need for multiple prediction methods.

Main Methods:

• SL-Cloud offers customizable computational inference of SLIs.
• It allows testing of various prediction approaches across multiple datasets.
• The framework integrates cloud-hosted data resources and curated workflows.

Main Results:

• SL-Cloud provides a unified platform for SLI prediction.
• It enables researchers to process large multi-omic datasets efficiently.
• The tool facilitates the comparison and validation of different SLI prediction strategies.

Conclusions:

• SL-Cloud is a valuable resource for cancer researchers.
• It supports the discovery of novel SLIs for potential anticancer drug targets.
• The platform enhances the investigation of synthetic lethality in cancer therapy.