Background

Cancer patients that present similar clinical features can have drastic differences in response to the same treatment. An additional challenge, the initial treatment may have limited efficacy once the tumor becomes resistant. Scientists have made great strides in understanding cancer at the genetic level and how these differences in cancer genomics lead to variability in therapeutic response.

Technology Overview

Bioinformatics experts at the Icahn School of Medicine at Mount Sinai developed a software that oncologists or cancer researchers can use to determine which drugs the cancer will be sensitive or resistant to base on the gene expression data of the cancer cells.

Stage of Development

Software is available
Therapeutic responses have been predicted from Patient Derived Xenograft models in lung cancer using the software

Benefits

User-friendly, comprehensive app that is accessible to various types of professionals working in the field of oncology: clinicians and researchers

Applications

Identification of potentially successful treatment for cancer patients based on the cancer genetic profile
Aid cancer researchers in identifying drugs that tumors are sensitive or resistant to. With this information, they can further characterize the mechanism behind the predicted response

CaGes - Cancer Gene Signatures Computational Tool