Search

KRAS is one of the most commonly mutated oncogenes in lung, colorectal, and pancreatic cancers. Recent clinical trials directly targeting KRAS G12C presented encouraging results for a large population of non-small cell lung cancer (NSCLC), but resistance to treatment is a concern. Continued exploration of new inhibitors and preclinical models is needed to address resistance mechanisms and improve duration of patient responses. To further enable the development of KRAS G12C inhibitors, we present a preclinical framework involving translational, non-invasive imaging modalities (CT and PET) and histopathology in a conventional xenograft model and a novel KRAS G12C knock-in mouse model of NSCLC. We utilized an in-house developed KRAS G12C inhibitor (Compound A) as a tool to demonstrate the value of this framework in studying in vivo pharmacokinetic/pharmacodynamic (PK/PD) relationship and anti-tumor efficacy. We characterized the Kras G12C-driven genetically engineered mouse model (GEMM) and identify tumor growth and signaling differences compared to its Kras G12D-driven counterpart. We also find that Compound A has comparable efficacy to sotorasib in the Kras G12C-driven lung tumors arising in the GEMM, but like observations in the clinic, some tumors inevitably progress on treatment. These findings establish a foundation for evaluating future KRAS G12C inhibitors that is not limited to xenograft studies and can be applied in a translationally relevant mouse model that mirrors human disease progression and resistance.

Understanding a drug's whole-body biodistribution and tumor targeting can provide important information regarding efficacy, safety, and dosing parameters. Current methods to evaluate biodistribution include in vivo imaging technologies like positron electron tomography and single-photon emission computed tomography or ex vivo quantitation of drug concentrations in tissues using autoradiography and standard biochemical assays. These methods use radioactive compounds or are cumbersome and do not give whole-body information. Here, for the first time, we show the utility of fluorescence molecular tomography (FMT) imaging to determine the biodistribution and targeting of an antibody–drug conjugate (ADC). An anti–5T4-antibody (5T4-Ab) and 5T4-ADC were conjugated with a near-infrared (NIR) fluorophore VivoTag 680XL (VT680). Both conjugated compounds were stable as determined by SEC-HPLC and plasma stability studies. Flow cytometry and fluorescence microscopy studies showed that VT680-conjugated 5T4-ADC specifically bound 5T4-expressing cells in vitro and also exhibited a similar cytotoxicity profile as the unconjugated 5T4-ADC. In vivo biodistribution and tumor targeting in an H1975 subcutaneous xenograft model demonstrated no significant differences between accumulation of VT680-conjugated 5T4-Ab or 5T4-ADC in either normal tissues or tumor. In addition, quantitation of heart signal from FMT imaging showed good correlation with the plasma pharmacokinetic profile suggesting that it (heart FMT imaging) may be a surrogate for plasma drug clearance. These results demonstrate that conjugation of VT680 to 5T4-Ab or 5T4-ADC does not change the behavior of native biologic, and FMT imaging can be a useful tool to understand biodistribution and tumor-targeting kinetics of antibodies, ADCs, and other biologics. Mol Cancer Ther; 15(10); 2530–40. ©2016 AACR.

Supplemental Figure 1: Standard curve of VT680 showing the 3-D quantitation and linearity by FMT imaging; Supplemental Figure 2: Evaluation of VT680 conjugated 5T4-Ab and 5T4-ADC; Supplemental Figure 3: Determination of antibody binding capacity (ABC) and receptor saturation in H1975 and MDA-MB-468 cells by flow cytometry; Supplemental Figure 4: Ex vivo FMT imaging showing the accumulation of 5T4-Ab-VT680, 5T4-ADC-VT680, Isotype control-Ab-VT680 and VT680 alone 48 h post-injection in tumor (A) and liver (B).

Precise temporal regulation of Type I interferon signaling is imperative to effectively fight infections and cancerous cells without triggering autoimmunity. The key negative regulator of Type I interferon signaling is ubiquitin-specific protease 18 (USP18). USP18 cleaves interferon-inducible ubiquitin-like modifications through its canonical catalytic function and directly inhibits interferon receptor signaling through its scaffold role.USP18loss-of-function dramatically impacts autoimmune disease, viral susceptibility, and cancer cell survival. However, the relative contribution of catalytic versus scaffold function is unresolved and must be determined to design effective therapeutics targeting USP18. To precisely delineate individual contribution, we evaluated the functional impact of single amino acid mutations that disrupt catalytic or scaffold activity. Here we demonstrate catalytic activity does not contribute to cell autonomous Type I interferon sensitivity across multiple cancer cell lineages. Furthermore, introducing a patient-derived mutation that disrupts scaffold function is sufficient to inhibit cancer growth. These findings establish a fundamental mechanistic basis for USP18 therapeutic design across diseases.OVERVIEWUSP18 is the key negative regulator of Type I interferon signaling in humans, mediating autoimmune disease, viral susceptibility, and cancer cell survival.USP18 cleaves interferon-inducible ubiquitin-like modifications through its canonical catalytic function and attenuates interferon receptor signaling through its scaffold role.Delineating the contribution of each function is critical to resolve the mechanistic basis of interferon regulation and enable the development of therapeutics targeting USP18.We demonstrate that cell intrinsic interferon sensitivity is not mediated by loss of catalytic activity. However, disruption of scaffold function by a patient-specific mutation inhibits cancer cell growth.Furthermore, we discovered that canonical catalytic activity is surprisingly inefficient in human cells.These results clarify a fundamental mechanism of immune regulation and cancer cell survival in humans.Abstract Figure

Nanoparticle (NP) technology holds significant promise to mediate targeted drug delivery to specific organs in the body. Understanding the 3D biodistribution of NPs in heterogeneous environments such as the tumor tissue can provide crucial information on efficacy, safety and potential clinical outcomes. Here we present a novel end-to-end workflow, VIOLA, which makes use of tissue clearing methodology in conjunction with high resolution imaging and advanced 3D image processing to quantify the spatiotemporal 3D biodistribution of fluorescently labeled ACCURIN® NPs. Specifically, we investigate the spatiotemporal biodistribution of NPs in three different murine tumor models (CT26, EMT6, and KPC-GEM) of increasing complexity and translational relevance. We have developed new endpoints to characterize NP biodistribution at multiple length scales. Our observations reveal that the macroscale NP biodistribution is spatially heterogeneous and exhibits a gradient with relatively high accumulation at the tumor periphery that progressively decreases towards the tumor core in all the tumor models. Microscale analysis revealed that NP extravasation from blood vessels increases in a time dependent manner and plateaus at 72 h post injection. Volumetric analysis and pharmacokinetic modeling of NP biodistribution in the vicinity of the blood vessels revealed that the local NP density exhibits a distance dependent spatiotemporal biodistribution which provide insights into the dynamics of NP extravasation in the tumor tissue. Our data represents a comprehensive analysis of NP biodistribution at multiple length scales in different tumor models providing unique insights into their spatiotemporal dynamics. Specifically, our results show that NPs exhibit a dynamic equilibrium with macroscale heterogeneity combined with microscale homogeneity.

Radiotherapy (RT) has traditionally been seen as a means to induce targeted tumor cell death, and more than 50% of all cancer patients receive RT. RT is also known to induce immune cell activation, and the advent of immunotherapeutic treatments such as checkpoint inhibition has sparked increased interest in using RT to enhance an anti-tumor immune response. However, to take advantage of the immunological effects of RT, a deeper understanding of the effects of RT on tumor-infiltrating leukocytes (TILs) is essential. Therefore, we systematically analyzed the effects of RT on tumor growth and the tumor-infiltrating immune cells in five syngeneic tumor models with diverse immune cell-infiltration profiles. These tumor types show strong differences in the overall immune cell infiltration, as well as in the composition of the infiltrating immune cell populations. After RT, tumors that were characterized as hot (e.g. CT26) showed increased sensitivity and dose-dependent tumor growth inhibition compared to cold tumor models (e.g. B16F10). Immune cell profiling indicated that RT led to strong changes in TILs of some tumor types, such as MC38 and CT26. These changes included reduced fractions of macrophages and increases in NK cells and also CD8 T cells. Single cell RNA sequencing also revealed an increase in CD8 T cells expressing proliferation-related genes. Furthermore, macrophage clusters expressing markers of proliferation were specifically eradicated by RT, while monocytes and neutrophils were less affected. The monocytes and neutrophils in the models that showed little changes in TILs after RT expressed marker genes of type-I interferon response. These findings predict that tumors that are highly infiltrated by neutrophils and monocytes, with little intra-tumoral proliferation and type-I interferon response signature, are likely resistant to an RT-mediated anti-tumor immune response. The present work has laid a strong foundation to develop next-generation combinatorial treatments using RT and immunotherapy. Citation Format: Tristan Wirtz, Catherine Lee, Tao Xie, Lisa Manzuk, Manfred Kraus, Christopher Dillon, Timothy Affolter, Anand Giddabasappa. Effects of targeted radiotherapy on tumor immune landscape in diverse murine tumor models [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2021 Oct 5-6. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(1 Suppl):Abstract nr P065.