Abstract B1-57: HER2+ cancer dependence on PI3K vs. MAPK signaling pathways is predicted by expression of 3 protein biomarkers, and informs optimal combination treatment strategies
Authors: Daniel C. Kirouac, Jinyan Du, Johanna j. Lahdenranta, Charlotte Mcdongh, Ulrik Nielsen
Journal: Cancer Research (2015)

Abstract Human cancers are incredibly diverse with regard to molecular aberrations, dependence on oncogenic signaling pathways, and responses to pharmacological intervention. In this work we sought to quantify how cellular dependence on the canonical PI3K vs. MAPK pathways varies across HER2+ cancers, and how such dependence affects responses to targeted therapies. A panel of 18 HER2+ (ERBB2-amplified) cell lines covering a variety of indications was used to characterize the diversity within this oncogene-defined cancer. In vitro video microscopy was used to monitor cell growth responses to combinations of AKT (MK2206) and MEK (GSK1120212; trametinib) inhibitors, and Luminex-based quantitative proteomics to profile expression of HER-family receptors and intracellular signaling components. We find that HER2+ cell lines can be functionally classified by PI3K vs. MAPK pathway dependence, and this dependence is accurately predicted by a combination of protein measurements comprising EGFR, ErbB3, and the cyclin-dependent kinase inhibitor p27 (CDKN1B). Expression of these biomarkers varied by tissue, such that HER2+ lung, ovarian, and gastrointestinal cancer cell lines are preferentially dependent upon MAPK signaling, while breast cancers were primarily PI3K-dependent. mRNA expression patterns of these markers were consistent between immortalized cell lines and clinical samples (TCGA), and predicted differential sensitivity to multiple drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database, including AKT and MEK inhibitors, as well as agents targeting metabolism (AMPK, MTOR), stress response (HDAC) and cell cycle control (CHK, and CDK). To further assess how PI3K vs. MAPK pathway dependence affects responses to combinations of clinically-relevant therapies, we utilized a multi-scale model of HER2+ cancer linking cell signaling to proliferation and survival. Growth inhibitory responses to combinations of drugs targeting the ErbB signaling network were simulated across a diverse population of synthetic tumors. Activating mutations in the PI3K and MAPK pathways (PIK3CA and KRAS) and expression of the HER3 ligand Heregulin determined sensitivity to combinations of inhibitors against HER2 (lapatinib), HER3 (MM-111), AKT (MK-2206) and MEK (trametinib), in addition to the standard of care trastuzumab (Herceptin). These biomarker-response predictions were combined into a six-arm decision tree, and predictions validated by in vitro profiling of combination drug responses in a secondary panel of HER2+ cell lines. In summary, this work demonstrates that HER2+ cancers are both molecularly and functionally diverse, and suggests that measurement of this minimal set of three protein biomarkers could inform combination regimen design for this class of cancers. More broadly, the computational strategy presented for identifying effective combinations and predictive biomarkers may be extendable to other human cancers. Citation Format: Daniel C. Kirouac, Jinyan Du, Johanna j. Lahdenranta, Charlotte Mcdongh, Ulrik Nielsen. HER2+ cancer dependence on PI3K vs. MAPK signaling pathways is predicted by expression of 3 protein biomarkers, and informs optimal combination treatment strategies. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-57.