Spider Map

The RAS signaling pathway model from KEGG

Predicting therapeutic resistance by finding points of cross-talk using KEGG

Cancer patients are now routinely screened for driver mutations at diagnosis. Identification of "hot-spot" mutations in some cancer types has spurred the development of new targeted therapies. These drugs and biologicals are designed against specific mutations, which helps reduce the adverse reactions caused by off-target effects of more traditional chemotherapeutics. However, the high degree of specificity can place an intense selective pressure against that mutation in the tumor and promote the development of resistant subpopulations. Identifying secondary targets that can overcome this resistance is a pressing need in the clinic.

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There weren't any figures generated for this work, so here's some ASCII art of a spider.

As part of a collaboration with Dr. George Blanck during my Master's work, I developed a small Python script that analyzes the signaling pathway networks in the KEGG Pathway Database to find points of cross-talk between two proteins. Using this script, which we called "Spider Map," we identified several known resistance mechanisms for targeted therapies, such as vemurafenib (a BRAFV600E specific drug used in melanoma treatment). We used the additional targets identified by our analysis to propose alternative secondary targets.

This work was published in "Anticipating designer drug-resistant cancer cells" (Frangione et al. 2014 Drug Dis Today).

I've included a link to the GitHub repository for the script, as the website created to provide public access to Spider Map is now offline. The code is provided as-is for archival purposes and may longer function due to version changes, database restructuring, or altered API calls.