AKT1 E17K Inhibits Cancer Cell Migration by Abrogating ß-Catenin Signaling.

Mutational activation of the PI3K/AKT pathway is among the most common pro-oncogenic events in human cancers. The clinical utility of PI3K and AKT inhibitors has, however, been modest to date. Here, we used CRISPR-mediated gene editing to study the biological consequences of AKT1 E17K mutation by developing an AKT1 E17K-mutant isogenic system in a TP53-null background. AKT1 E17K expression under the control of its endogenous promoter enhanced cell growth and colony formation, but had a paradoxical inhibitory effect on cell migration and invasion. The mechanistic basis by which activated AKT1 inhibited cell migration and invasion was increased E-cadherin expression mediated by suppression of ZEB1 transcription via altered ß-catenin subcellular localization. This phenotypic effect was AKT1-specific, as AKT2 activation had the opposite effect, a reduction in E-cadherin expression. Consistent with the opposing effects of AKT1 and AKT2 activation on E-cadherin expression, a pro-migratory effect of AKT1 activation was not observed in breast cancer cells with PTEN loss or expression of an activating PIK3CA mutation, alterations which induce the activation of both AKT isoforms. The results suggest that the use of AKT inhibitors in patients with breast cancer could paradoxically accelerate metastatic progression in some genetic contexts and may explain the frequent coselection for CDH1 mutations in AKT1-mutated breast tumors. IMPLICATIONS: AKT1 E17K mutation in breast cancer impairs migration/invasiveness via sequestration of ß-catenin to the cell membrane leading to decreased ZEB1 transcription, resulting in increased E-cadherin expression and a reversal of epithelial-mesenchymal transition.

Leveraging Systematic Functional Analysis to Benchmark an In Silico Framework Distinguishes Driver from Passenger MEK Mutants in Cancer.

Despite significant advances in cancer precision medicine, a significant hurdle to its broader adoption remains the multitude of variants of unknown significance identified by clinical tumor sequencing and the lack of biologically validated methods to distinguish between functional and benign variants. Here we used functional data on MAP2K1 and MAP2K2 mutations generated in real-time within a co-clinical trial framework to benchmark the predictive value of a three-part in silico methodology. Our computational approach to variant classification incorporated hotspot analysis, three-dimensional molecular dynamics simulation, and sequence paralogy. In silico prediction accurately distinguished functional from benign MAP2K1 and MAP2K2 mutants, yet drug sensitivity varied widely among activating mutant alleles. These results suggest that multifaceted in silico modeling can inform patient accrual to MEK/ERK inhibitor clinical trials, but computational methods need to be paired with laboratory- and clinic-based efforts designed to unravel variabilities in drug response. SIGNIFICANCE: Leveraging prospective functional characterization of MEK1/2 mutants, it was found that hotspot analysis, molecular dynamics simulation, and sequence paralogy are complementary tools that can robustly prioritize variants for biologic, therapeutic, and clinical validation.See related commentary by Whitehead and Sebolt-Leopold, p. 4042.

Activity of M3814, an Oral DNA-PK Inhibitor, In Combination with Topoisomerase II Inhibitors in Ovarian Cancer Models.

DNA-dependent protein kinase (DNA-PK) has been shown to play a crucial role in repair of DNA double-strand breaks, facilitating nonhomologous end-joining. DNA-PK inhibitors have the potential to block DNA repair and therefore enhance DNA-damaging agents. M3814 is a DNA-PK inhibitor that has shown preclinical activity in combination with DNA-damaging agents, including radiotherapy and topoisomerase II inhibitors. Here we evaluated the activity of M3814 in combination with multiple topoisomerase II inhibitors, doxorubicin, etoposide, and pegylated liposomal doxorubicin (PLD) in vivo, utilizing ovarian cancer xenografts. Using cell lines representative of P53 wild-type ovarian cancer (A2780), and P53 mutant ovarian cancer (SKOV3), cells were implanted in the flank of athymic nude female mice. Mice were treated with vehicle, M3814 alone, topoisomerase II inhibitor alone, and M3814 in combination with topoisomerase II inhibitor, and change in tumor volume over time was documented. The addition of M3814 was well tolerated. We demonstrated that M3814 shows limited efficacy as a single agent in ovarian cancer models. The combination of M3814 with PLD showed enhanced activity over PLD as a single agent. Further study of this combination is warranted.

Precision Oncology: Three Small Steps Forward.

Only a subset of cancer patients currently benefit from personalized treatment approaches. Detection of actionable drug targets in cell-free DNA, more comprehensive molecular profiling integrating transcriptional analyses, and personalized combination regimens all hold promise in expanding the benefits of personalized oncology to larger numbers of cancer patients.