Abstract A8: Combating adaptive ERBB3-mediated resistance to ERBB2 inhibitors: In Silico optimization of MM-111 and lapatinib dosing regimens
Authors: Kirouac Daniel C. , Lahdenranta Johanna , Overland Ryan , Du Jinyan , McDonagh Charlotte , Nielson Ulrik , Onsum Mathew 
Published: March 2013

Upregulation of ErbB3 (HER3) signaling has been implicated as a resistance mechanism to targeted ErbB1 and ErbB2 (HER1/2) inhibitors, limiting the efficacy of drugs such as lapatinib (Tykerb®), gefitinib (Iressa©), cetuximab (Erbitux®), and trastuzumab (Herceptin©) through compensatory activation of downstream PI3K/AKT and MAPK/ERK cascades. Combining ErbB1/2 inhibitors with novel ERBB3 targeted agents could therefore combat, or preempt this adaptive resistance mechanism. Doing so in a rational manner however requires selecting appropriate drug combinations, and designing dosing regimens, which maximize therapeutic synergy.

MM-111 is a novel bi-specific antibody against ErbB3, using an ErbB2 targeting arm to enhance avidity and inhibitor potency in HER2+ tumors. Pre-clinical data shows that combining MM-111 with the ErbB2 inhibitors lapatinib and/or trastuzumab results in synergistic tumor growth inhibition. We desired to leverage our preclinical signaling, pharmacokinetic (PK), pharmacodynamic (PD), and efficacy data to optimize dosing regimens of MM-111 combination therapies. To do so, we developed an integrated a mathematical model of MM-111′s mechanism of action, incorporating ErbB-family signal transduction, transcriptional regulation through FOXO, and resulting tumor proliferation, with pre-clinical PK information. This integrated model was trained using in vitro dose response data from BT-474-M3 and HER2 overexpressing MCF7 cells treated with the ErbB3 ligand heregulin, plus drug combinations. Levels of phospho- and total ErbB1, 2, 3, AKT, and ERK were quantified using ELISA, and cell growth effects quantified using the Cell Titer Glow assay. This was then integrated with a 2-compartment PK-model, to predict PD profiles and tumor growth effects in murine xenografts treated with the drug combinations.

The model accurately predicted ERBB3 protein upregulation in response to ErbB2 inhibitor treatment (lapatinib and/or trastuzumab) in vivo, maintaining downstream AKT and ERK activity and supporting tumor growth. MM-111 inhibited compensatory signaling through phospho-ErbB3, thus blocking AKT and ERK re-activation, resulting in synergistic tumor growth inhibition. We are now using our computational model to screen alternate combination dosing regimens in silico with the goal of identifying theoretically optimal schedules that we will validate in vivo. In particular, we are investigating novel intermittent high-dose lapatinib treatment in combination with MM-111. These results will be used to design phase I/II clinical trials of MM-111 given with lapatinib.

While this study design is focused on MM-111 combined with lapatinib, the strategy is generally applicable to molecular targeted therapeutics given alone or in combination. By integrating PK/PD with known molecular mechanisms of action, we are able to rationally design combination treatment strategies to combat adaptive resistance.