Data analysis in proteogenomics has taken a marked step forward with the introduction of a new bioinformatics platform, Multiomics2Targets. This platform, developed by CPTAC researchers at the Icahn School of Medicine at Mount Sinai and published in Cell Reports Methods, integrates transcriptomics, proteomics, and phosphoproteomics data to identify potential therapeutic targets and is capable of generating detailed reports automatically. A companion protocol article describing how to use the system was also recently published in STAR Protocols.
Multiomics2Targets processes multiomics datasets using software tools to identify enriched biological pathways (with Enrichr), reveal regulatory kinases that drive abnormal signaling (with KEA3), highlight cell-surface proteins that are aberrantly expressed (with TargetRanger), and more. These tools, when paired with the team’s previously developed eXpression2Kinases (X2K) pipeline, enable the reconstruction of key cell signaling pathways using both differential gene expression and protein phosphorylation data. This “dual approach” provides a more complete view of the mechanisms driving cancer at an individual, cluster, and/or cohort scale.
Users can upload their own data and adjust parameters throughout the Multiomics2Targets workflow, resulting in customized outputs. After the analysis steps are complete, Multiomics2Targets automatically generates a report with all the features of a research publication, including: an abstract, methods, results, discussion, figures, and tables, and references. This is achieved through a combination of open-source visualization tools and integration with a large language model (GPT-4o).
Lead investigator Dr. Avi Ma’ayan commented on the platform’s synergy with CPTAC, “the CPTAC program is collecting multi-omics data from cohorts of pan-cancer patients at great depth and scale. Such data is expected to transform our understanding of the molecular mechanisms and pathways of cancer, and lead to the development of a new generation of cancer therapeutics. The Multiomics2Targets platform streamlines, democratizes, and systemizes the analysis of these complex and large datasets.”
So far, by analyzing CPTAC data, Multiomics2Targets has detected both previously validated and novel therapeutic targets across ten CPTAC cancer types. Notable findings from this investigation include the identification of VTCN1 as a potential pan-cancer target and AQP4 and DSG3 as subtype-specific targets in glioblastoma and head-and-neck cancers, respectively.