HER2 mutations occur in 3% of lung cancers and are highly diverse with more than 80 recurrent mutations observed. Targeted treatments are highly limited for HER2 mutant lung cancer patients. To date the only approved HER2 targeting therapeutic for this subgroup of patients is the HER2 antibody drug conjugate, trastuzumab-deruxtecan. Unfortunately, resistance often develops even in those who initially benefit from such treatments. Thus, to improve clinical outcome, studies are needed to establish a system to classify HER2 mutations based on protein structure and drug sensitivity, to define resistance mutations and mechanisms, and to identify effective inhibitors to overcome resistance. Clinic...

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HER2 mutations occur in 3% of lung cancers and are highly diverse with more than 80 recurrent mutations observed. Targeted treatments are highly limited for HER2 mutant lung cancer patients. To date the only approved HER2 targeting therapeutic for this subgroup of patients is the HER2 antibody drug conjugate, trastuzumab-deruxtecan. Unfortunately, resistance often develops even in those who initially benefit from such treatments. Thus, to improve clinical outcome, studies are needed to establish a system to classify HER2 mutations based on protein structure and drug sensitivity, to define resistance mutations and mechanisms, and to identify effective inhibitors to overcome resistance. Clinical trials results have shown heterogenous responses to HER2 inhibitors based on the specific mutation presented, and this is supported by our finding that sensitivity to HER2 inhibitors differs among cell lines expressing distinct mutations. Currently, there are no effective strategies to tailor the optimal HER2 targeting agent to specific mutations. Our team recently developed a system to classify distinct mutations in another mutated receptor, EGFR, based on receptor structure and drug sensitivity, and this classification approach can predict drug sensitivity and clinical outcome in EGFR-mutant patients. We hypothesize that a similar approach could be used to determine subgroups that predict drug response for HER2 mutant patients. We aim to develop a functional "atlas" of HER2 mutations and establish a structure/function-based classification approach that would inform clinicians of the best treatment options for HER2 mutant lung cancer and resistant disease. Since HER2 mutations also occur in breast and colon cancer, our findings could also benefit these patients. The work proposed here utilizes a multidisciplinary team with strong experience in cancer genomics, molecular modeling, and a track record of rapidly translating advances from the laboratory into clinical trials.

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