Utilizing data from patient-derived xenograft mouse models of human tumors to inform clinical decision making in Molecular Tumor Boards (MTB) deliberations.

person Jens Rueter The Jackson Laboratory, Bar Harbor, ME info_outline Jens Rueter, Susan D. Airhart, Carol J. Bult, Emily Jocoy, Kyle Draheim, Mingshan Cheng, Andrey Antov, Andrew Hesse, Honey Reddi, Derrick S. Haslem, Terence Duane Rhodes, Lincoln Nadauld

Authors person Jens Rueter The Jackson Laboratory, Bar Harbor, ME info_outline Jens Rueter, Susan D. Airhart, Carol J. Bult, Emily Jocoy, Kyle Draheim, Mingshan Cheng, Andrey Antov, Andrew Hesse, Honey Reddi, Derrick S. Haslem, Terence Duane Rhodes, Lincoln Nadauld Organizations The Jackson Laboratory, Bar Harbor, ME, The Jackson Laboratory, Sacramento, CA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, Precision Genomics Program, Intermountain Healthcare, St. George, UT Abstract Disclosures Research Funding Other Background: Molecular Tumor Boards (MTB) are often the critical decision-making step in identifying genome-guided treatments for patients with difficult-to-treat cancers, e.g. BRAF mutated metastatic colon cancers. A common challenge for MTBs is prioritizing between two or more actionable variants in a tumor. A potential solution to this challenge is to incorporate drug response in Patient-derived xenografts (PDX) models into MTB deliberations. The goal of this study was to evaluate the feasibility of using PDX models to elucidate drug-effectiveness in BRAF-mutated cancer as an example of a common clinical scenario. Methods: We selected BRAF-mutated PDX models from the JAX PDX resource based on the presence of an activating BRAF mutation and a second actionable variant from the JAX Cancer Treatment Profile (CTP). Somatic mutation data from PDX tumors were presented to members of the Intermountain MTB. PDX models were then treated with drugs recommended by the MTB; outcomes based on tumor growth inhibition (TGI) were shared with the MTB. Results: Gene/variant targets, associated drugs for the 2 nd mutation and responses are described in the table. The MTB members determined that PDX data presented in TGI format is helpful in MTB deliberations. Activity of BRAF-targeted therapy was expected while the low activity of olaparib in the BRCA1-mutated colon cancer model was unexpected. The MTB then discussed molecular mechanisms that contributed to these outcomes. Conclusions: The pilot study demonstrated that utilizing PDX drug response data as an additional molecular annotation for MTB deliberations is feasible. Future studies will further optimize this process. Model/ Tumor Type 1 BRAF V600E targeted Rx 2 Activity 3 2nd Actionable Gene 2nd Gene targeted Rx 4 2nd targeted Rx Activity CN01 H* BRCA1 O L CN02 H* SMO V L CN03 I* AKT1 Te I* CN04 I* NF1 Tr I* SKM01 I* PTEN Te L* SKM02 L SMO V L 1. CN = colon. SKM = skin, melanoma 2. Colon = Dabrafinib+Trametinib+Cetuximab. Melanoma = Dabrafinib+Trametinib 3. TGI Activity: H = High I = intermediate L = Low. 4. O: Olaparib V: Vismodegib Te: Temsirolimus Tr: Trametinib * Significantly different than untreated control group