The Dependency Map (DepMap) is a genome-wide pooled
CRISPR-Cas9 knockout proliferation screen conducted in more than 700 cancer cell lines spanning many
different tumor lineages. Each cell line in the DepMap contains a unique barcode, and each gene
knockout is assigned a “dependency score” on a per cell-line basis which quantifies the rate of
CRISPR-Cas9 guide drop. It has been found that proteins with similar DepMap scores across cell
lines, a phenomenon known as co-dependent genes, have closely related biological functions. This can
include activity in the same or parallel pathways or membership in the same protein complex or the
We identified the strongest seven co-dependent genes (“Symbol”) for DUBs and ran GO enrichment
analysis. We used Biogrid, IntAct, and Pathway Commons PPIDs, and the NURSA protein-protein
interaction databases (PPIDs) to determine whether co-dependent genes interact with one another. The
“Evidence” column contains the PPIDs in which the interaction appears as well as whether there is
support for the association by an INDRA statement. As another approach to identify potential
interactors, we looked at proteomics data from the Broad Institute's Cancer Cell Line Encyclopedia (CCLE) for
proteins whose expression across ~375 cell lines strongly correlated with the abundance of each DUB;
it has previously been observed that proteins in the same complex are frequently significantly
co-expressed. The correlations and associated p-values in the CCLE proteomics dataset are provided.
And, we determined whether co-dependent genes yield similar transcriptomic signatures
in the Broad Institute's Connectivity
Map (CMap). A CMap score greater than 90 is considered significantly similar.
Using the biological processes and other Gene Ontology terms from well characterized DUBs as a
positive control, several gene set enrichment analyses were considered. Threshold-less methods
like GSEA had relatively poor results.
Over-representation analysis with a threshold of of the top 7 highest absolute value Dependency Map
correlations yielded the best results and is reported below.
INDRA was used to automatically assemble known mechanisms
related to USP41 from literature and knowledge bases.
The first section shows only DUB activity and the second shows all other results.
We knocked down E-cadherin in lung cancer cell lines using siRNA, and demonstrated that E-Cadherin knockout offseted the effect of inhibition of USP41 on cell migration, and inhibition of USP41 may reverse EMT of lung cancer cells.
Overexpression of the Ubiquitin Specific Proteases USP43, USP41, USP27x and USP6 in Osteosarcoma Cell Lines: Inhibition of Osteosarcoma Tumor Growth and Lung Metastasis Development by the USP Antagonist PR619.