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Poster display

3839 - Functional characterization of mutations and their interaction using the novel functional annotation for cancer treatment (FACT) platform


10 Oct 2016


Poster display


Benjamin Miron


Annals of Oncology (2016) 27 (6): 401-406. 10.1093/annonc/mdw380


B. Miron1, N. Peled2, Z. Barbash1, O. Edelheit1, M. Vidne1, R. Sharivkin1, G. Tarcic1

Author affiliations

  • 1 R&d, NovellusDx, 91120 - Jerusalem/IL
  • 2 Thoracic Cancer Unit, Davidoff Cancer Center, Petach Tiqwa/IL


Abstract 3839


Mounting evidence indicates that histologically identical cancers are fueled by different sets of driving mutations in each patient. Most tumors possess several genetic alterations capable of stimulating growth and enabling resistance to treatment. Targeted therapy drugs (TTD) have demonstrated efficacy by inducing significant tumor regression. A percentage of patients do not respond to TTDs or develop drug resistance due to the interaction or "cross-talk" between multiple alterations providing a bypass mechanism for tumor survival. FACT is capable of functionally quantifying cross-talk driven by multiple mutations, including variants of unknown significance, to improve tailored therapy.


FACT is a cell-based assay which utilizes fluorescent reporters to quantify activity of multiple oncogenic signaling pathways. We focused on canonical resistance mechanisms driven by cross-talk which enact resistance to TTDs. Co-transfection is used to test cross-talk between multiple mutations. Relevant TTDs were tested in FACT to predict patient response to single-drug and combination therapies.


FACT quantified activation in a wide range of known oncogenes altered by patients' mutations in relevant signaling pathways. Using FACT, we were able to demonstrate cross-talk between co-existing mutations in known oncogenes (EGFR + KRAS, ERBB2 + BRAF, etc). These combinations were shown to affect resistance to certain TTDs which could be bypassed with TTD combination therapy.


These results demonstrate the value of an assay capable of providing actionable information regarding resistance, fueled by cross-talk, as well as use of combination therapy, in order to select the optimal course of treatment. These interactions, unidentified by NGS, are critical to predicting treatment response and provide another layer of critical information to physicians in the age of precision medicine.

Clinical trial identification

Legal entity responsible for the study





B. Miron, N. Peled, Z. Barbash, O. Edelheit, M. Vidne, R. Sharivkin, G. Tarcic: NovellusDx.

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