Modeling spontaneous metastatic renal cell carcinoma (mRCC) in mice following nephrectomy

Effect of M2-like macrophages of the injured-kidney cortex on kidney cancer progression

Chronic kidney disease (CKD) affects kidney cancer patients' mortality. However, the underlying mechanism remains unknown. M2-like macrophages have pro-tumor functions, also exist in injured kidney, and promote kidney fibrosis. Thus, it is suspected that M2-like macrophages in injured kidney induce the pro-tumor microenvironment leading to kidney cancer progression. We found that M2-like macrophages present in the injured kidney promoted kidney cancer progression and induced resistance to anti-PD1 antibody through its pro-tumor function and inhibition of CD8⁺ T cell infiltration. RNA-seq revealed Slc7a11 was upregulated in M2-like macrophages. Inhibition of Slc7a11 with sulfasalazine inhibited the pro-tumor function of M2-like macrophages and synergized with anti-PD1 antibody. Moreover, SLC7A11-positive macrophages were associated with poor prognosis among kidney cancer patients. Collectively, this study dissects the characteristic microenvironment in the injured kidney that contributed to kidney cancer progression and anti-PD1 antibody resistance. This insight offers promising combination therapy with anti-PD1 antibody and macrophage targeted therapy.

Cabozantinib-Loaded PLGA Nanoparticles: A Potential Adjuvant Strategy for Surgically Resected High-Risk Non-Metastatic Renal Cell Carcinoma

Patients with high-risk non-metastatic renal cell carcinoma (RCC) are at risk of metastatic relapse following nephrectomy. Cabozantinib (CZ), a potent multitarget tyrosine kinase inhibitor, interferes with angiogenesis and immunosuppression associated with surgery-induced metastasis. Here, we explored the therapeutic potential of CZ-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles (CZ-PLGA-NPs) as an adjuvant strategy for targeting post-nephrectomy metastasis. A clinically relevant subline recapitulating post-nephrectomy lung metastasis of high-risk human RCC, namely Renca-SRLu5-Luc, was established through in vivo serial selection of luciferase-expressing murine RCC Renca-Luc cells. CZ was encapsulated into PLGA-NPs via the conventional single emulsion technique. The multifaceted preclinical antimetastatic efficacy of CZ-PLGA-NPs was assessed in Renca-SRLu5-Luc cells. CZ-PLGA-NPs with a smooth surface displayed desirable physicochemical properties, good CZ encapsulation efficiency, as well as controlled and sustained CZ release. CZ-PLGA-NPs exhibited remarkable dose-dependent toxicity against Renca-SRLu5-Luc cells by inducing G2/M cell cycle arrest and apoptosis. CZ-PLGA-NPs attenuated in vitro colony formation, migration, and invasion by abrogating AKT and ERK1/2 activation. An intravenous injection of CZ-PLGA-NPs markedly reduced lung metastatic burden and prolonged lifespan with favorable safety in the Renca-SRLu5-Luc experimental lung metastasis model. The novel CZ-PLGA-NPs system with multifaceted antimetastatic effects and alleviating off-target toxicity potential is a promising adjunctive agent for patients with surgically resected high-risk RCC.

Immunization with short peptide particles reveals a functional CD8+ T-cell neoepitope in a murine renal carcinoma model

BACKGROUND

Induction of CD8⁺ T cells that recognize immunogenic, mutated protein fragments in the context of major histocompatibility class I (MHC-I) is a pressing challenge for cancer vaccine development.

METHODS

Using the commonly used murine renal adenocarcinoma RENCA cancer model, MHC-I restricted neoepitopes are predicted following next-generation sequencing. Candidate neoepitopes are screened in mice using a potent cancer vaccine adjuvant system that converts short peptides into immunogenic nanoparticles. An identified functional neoepitope vaccine is then tested in various therapeutic experimental tumor settings.

RESULTS

Conversion of 20 short MHC-I restricted neoepitope candidates into immunogenic nanoparticles results in antitumor responses with multivalent vaccination. Only a single neoepitope candidate, Nesprin-2 L4492R (Nes2LR), induced functional responses but still did so when included within 20-plex or 60-plex particles. Immunization with the short Nes2LR neoepitope with the immunogenic particle-inducing vaccine adjuvant prevented tumor growth at doses multiple orders of magnitude less than with other vaccine adjuvants, which were ineffective. Nes2LR vaccination inhibited or eradicated disease in subcutaneous, experimental lung metastasis and orthotopic tumor models, synergizing with immune checkpoint blockade.

CONCLUSION

These findings establish the feasibility of using short, MHC-I-restricted neoepitopes for straightforward immunization with multivalent or validated neoepitopes to induce cytotoxic CD8⁺ T cells. Furthermore, the Nes2LR neoepitope could be useful for preclinical studies involving renal cell carcinoma immunotherapy.

Rational Development of Liquid Biopsy Analysis in Renal Cell Carcinoma

Simple Summary

Among patients affected by renal cell carcinoma (RCC), the most common type of kidney cancer, it remains difficult to identify those who are at high risk for relapse or metastasis. This is in part due to the absence of reliable clinical biomarkers and robust methods to capture them. The aim of our study was to develop an improved assay to capture prognostic genomic biomarkers in circulating tumor DNA (ctDNA) in RCC. For this purpose, we first established a next generation sequencing (NGS) assay, targeting genes that are tailored for RCC and that are largely excluded from commercially available assays. Next, we showed the reliable performance of this assay to detect prognostic gene mutations in tumor DNA isolated from plasma, and from extracellular vesicles. Thus, our study provides a resource to facilitate ctDNA analysis for precision medicine in RCC.

Abstract

Renal cell carcinoma (RCC) is known for its variable clinical behavior and outcome, including heterogeneity in developing relapse or metastasis. Recent data highlighted the potential of somatic mutations as promising biomarkers for risk stratification in RCC. Likewise, the analysis of circulating tumor DNA (ctDNA) for such informative somatic mutations (liquid biopsy) is considered an important advance for precision oncology in RCC, allowing to monitor molecular disease evolution in real time. However, our knowledge about the utility of ctDNA analysis in RCC is limited, in part due to the lack of RCC-appropriate assays for ctDNA analysis. Here, by interrogating different blood compartments in xenograft models, we identified plasma cell-free (cf) DNA and extracellular vesicles (ev) DNA enriched for RCC-associated ctDNA. Additionally, we developed sensitive targeted sequencing and bioinformatics workflows capable of detecting somatic mutations in RCC-relevant genes with allele frequencies ≥ 0.5%. Applying this assay to patient-matched tumor and liquid biopsies, we captured tumor mutations in cf- and ev-DNA fractions isolated from the blood, highlighting the potentials of both fractions for ctDNA analysis. Overall, our study presents an RCC-appropriate sequencing assay and workflow for ctDNA analysis and provides a proof of principle as to the feasibility of detecting tumor-specific mutations in liquid biopsy in RCC patients.

Cell-programmed nutrient partitioning in the tumour microenvironment

Cancer cells characteristically consume glucose through Warburg metabolism1, a process that forms the basis of tumour imaging by positron emission tomography (PET). Tumour-infiltrating immune cells also rely on glucose, and impaired immune cell metabolism in the tumour microenvironment (TME) contributes to immune evasion by tumour cells2-4. However, whether the metabolism of immune cells is dysregulated in the TME by cell-intrinsic programs or by competition with cancer cells for limited nutrients remains unclear. Here we used PET tracers to measure the access to and uptake of glucose and glutamine by specific cell subsets in the TME. Notably, myeloid cells had the greatest capacity to take up intratumoral glucose, followed by T cells and cancer cells, across a range of cancer models. By contrast, cancer cells showed the highest uptake of glutamine. This distinct nutrient partitioning was programmed in a cell-intrinsic manner through mTORC1 signalling and the expression of genes related to the metabolism of glucose and glutamine. Inhibiting glutamine uptake enhanced glucose uptake across tumour-resident cell types, showing that glutamine metabolism suppresses glucose uptake without glucose being a limiting factor in the TME. Thus, cell-intrinsic programs drive the preferential acquisition of glucose and glutamine by immune and cancer cells, respectively. Cell-selective partitioning of these nutrients could be exploited to develop therapies and imaging strategies to enhance or monitor the metabolic programs and activities of specific cell populations in the TME.

Anti-Cancer Activity of PAK4/NAMPT Inhibitor and Programmed Cell Death Protein-1 Antibody in Kidney Cancer

BACKGROUND

Kidney cancer (or renal cell carcinoma, RCC) is the sixth most common malignancy in the United States and is increasing in incidence. Despite new therapies, including targeted therapies and immunotherapies, most RCCs are resistant to treatment. Thus, several laboratories have been evaluating new approaches to therapy, both with single agents as well as combinations. Although we have previously shown efficacy of the dual PAK4/nicotinamide phosphoribosyltransferase (NAMPT) inhibitor KPT-9274, and the immune checkpoint inhibitors (CPI) have shown utility in the clinic, there has been no evaluation of this combination either clinically or in an immunocompetent animal model of kidney cancer.

METHODS

In this study, we use the renal cell adenocarcinoma (RENCA) model of spontaneous murine kidney cancer. Male BALB/cJ mice were injected subcutaneously with RENCA cells and, after tumors were palpable, they were treated with KPT-9274 and/or anti-programmed cell death 1 (PDCD1; PD1) antibody for 21 days. Tumors were measured and then removed at animal euthanasia for subsequent studies.

RESULTS

We demonstrate a significant decrease in allograft growth with the combination treatment of KPT-9274 and anti-PD1 antibody without significant weight loss by the animals. This is associated with decreased (MOUSE) Naprt expression, indicating dependence of these tumors on NAMPT in parallel to what we have observed in human RCC. Histology of the tumors showed substantial necrosis regardless of treatment condition, and flow cytometry of antibody-stained tumor cells revealed that the enhanced therapeutic effect of KPT-9274 and anti-PD1 antibody was not driven by infiltration of T cells into tumors.

CONCLUSIONS

This study highlights the potential of the RENCA model for evaluating immunologic responses to KPT-9274 and checkpoint inhibitor (CPI) and suggests that therapy with this combination could improve efficacy in RCC beyond what is achievable with CPI alone.

Choosing The Right Animal Model for Renal Cancer Research

The increase in the life expectancy of patients with renal cell carcinoma (RCC) in the last decade is due to changes that have occurred in the area of preclinical studies. Understanding cancer pathophysiology and the emergence of new therapeutic options, including immunotherapy, would not be possible without proper research. Before new approaches to disease treatment are developed and introduced into clinical practice they must be preceded by preclinical tests, in which animal studies play a significant role. This review describes the progress in animal model development in kidney cancer research starting from the oldest syngeneic or chemically-induced models, through genetically modified mice, finally to xenograft, especially patient-derived, avatar and humanized mouse models. As there are a number of subtypes of RCC, our aim is to help to choose the right animal model for a particular kidney cancer subtype. The data on genetic backgrounds, biochemical parameters, histology, different stages of carcinogenesis and metastasis in various animal models of RCC as well as their translational relevance are summarized. Moreover, we shed some light on imaging methods, which can help define tumor microstructure, assist in the analysis of its metabolic changes and track metastasis development.

Enhanced efficacy of sitravatinib in metastatic models of antiangiogenic therapy resistance

Tyrosine kinase inhibitors (TKIs) that primarily target angiogenesis are approved to treat several cancers in the metastatic setting; however, resistance is common. Sequential treatment or 'switching' from one TKI to another following failure can be effective, but predicting which drugs will have cross-over sensitivity remains a challenge. Here we examined sitravatinib (MGCD516), a spectrum-selective TKI able to block MET, TAM (TYRO3, AXL, MerTK) and multiple receptor families (including PDGFRs, VEGFRs, and Ephs). Transcriptomic analysis of several mouse and human cell lines revealed diverse molecular changes after resistance to two TKIs (sunitinib and axitinib) with multiple sitravatinib targets found to be upregulated. Sitravatinib treatment in vitro resulted in enhanced anti-proliferative effects in resistant cells and was improved compared to TKIs with similar target profiles. In vivo, primary tumor growth inhibition after sitravatinib treatment in mice was enhanced in resistant tumors and metastasis suppression improved when tumors were surgically removed. Together, these results suggest that the diverse and often inconsistent compensatory signaling mechanisms found to contribute to TKI resistance may paradoxically improve the tumor-inhibiting effects of broad-spectrum TKIs such as sitravatinib that are able to block multiple signaling pathways. Sitravatinib in the second-line setting following antiangiogenic TKI treatment may have enhanced inhibitory effects in local and disseminated disease, and improve outcomes in patients with refractory disease.

Adoptive T-Cell Therapy for Solid Tumors

Chimeric antigen receptor (CAR) T-cell therapy is an innovative form of immunotherapy wherein autologous T cells are genetically modified to express chimeric receptors encoding an antigen-specific single-chain variable fragment and various costimulatory molecules. Upon administration, these modified T cells traffic to, and recognize, cancer cells in an HLA-independent manner. CAR T-cell therapy has shown remarkable success in the treatment of CD-19-expressing B-cell acute lymphocytic leukemia. However, clinical gains to the same magnitude have not been reported in solid tumors. Several known obstacles to CAR T-cell therapy for solid tumors include target antigen identification, effective trafficking to the tumor, robust activation, proliferation, and in vivo cytotoxicity. Beyond these T-cell intrinsic properties, a complex and dynamic immunosuppressive tumor microenvironment in solid tumors hinders T-cell efficacy. Notable advancements in CAR design to include multiple costimulatory molecules, ligands, and soluble cytokines have shown promise in preclinical models, and some of these are currently in early-phase clinical trials. In this review, we discuss selected solid tumor malignancies and relevant preclinical data and highlight clinical trial results that are available. Furthermore, we outline some obstacles to CAR T-cell therapy for each tumor and propose strategies to overcome some of these limitations.

Adoptive T-Cell Therapy for Solid Tumors

Chimeric antigen receptor (CAR) T-cell therapy is an innovative form of immunotherapy wherein autologous T cells are genetically modified to express chimeric receptors encoding an antigen-specific single-chain variable fragment and various costimulatory molecules. Upon administration, these modified T cells traffic to, and recognize, cancer cells in an HLA-independent manner. CAR T-cell therapy has shown remarkable success in the treatment of CD-19-expressing B-cell acute lymphocytic leukemia. However, clinical gains to the same magnitude have not been reported in solid tumors. Several known obstacles to CAR T-cell therapy for solid tumors include target antigen identification, effective trafficking to the tumor, robust activation, proliferation, and in vivo cytotoxicity. Beyond these T-cell intrinsic properties, a complex and dynamic immunosuppressive tumor microenvironment in solid tumors hinders T-cell efficacy. Notable advancements in CAR design to include multiple costimulatory molecules, ligands, and soluble cytokines have shown promise in preclinical models, and some of these are currently in early-phase clinical trials. In this review, we discuss selected solid tumor malignancies and relevant preclinical data and highlight clinical trial results that are available. Furthermore, we outline some obstacles to CAR T-cell therapy for each tumor and propose strategies to overcome some of these limitations.

Murine Tumor Models for Oncolytic Rhabdo-Virotherapy

The preclinical optimization and validation of novel treatments for cancer therapy requires the use of laboratory animals. Although in vitro experiments using tumor cell lines and ex vivo treatment of patient tumor samples provide a remarkable first-line tool for the initial study of tumoricidal potential, tumor-bearing animals remain the primary option to study delivery, efficacy, and safety of therapies in the context of a complete tumor microenvironment and functional immune system. In this review, we will describe the use of murine tumor models for oncolytic virotherapy using vesicular stomatitis virus. We will discuss studies using immunocompetent and immunodeficient models with respect to toxicity and therapeutic treatments, as well as the various techniques and tools available to study cancer therapy with Rhabdoviruses.

CRISPR-Mediated VHL Knockout Generates an Improved Model for Metastatic Renal Cell Carcinoma

Metastatic renal cell carcinoma (mRCC) is nearly incurable and accounts for most of the mortality associated with RCC. Von Hippel Lindau (VHL) is a tumour suppressor that is lost in the majority of clear cell RCC (ccRCC) cases. Its role in regulating hypoxia-inducible factors-1α (HIF-1α) and -2α (HIF-2α) is well-studied. Recent work has demonstrated that VHL knock down induces an epithelial-mesenchymal transition (EMT) phenotype. In this study we showed that a CRISPR/Cas9-mediated knock out of VHL in the RENCA model leads to morphologic and molecular changes indicative of EMT, which in turn drives increased metastasis to the lungs. RENCA cells deficient in HIF-1α failed to undergo EMT changes upon VHL knockout. RNA-seq revealed several HIF-1α-regulated genes that are upregulated in our VHL knockout cells and whose overexpression signifies an aggressive form of ccRCC in the cancer genome atlas (TCGA) database. Independent validation in a new clinical dataset confirms the upregulation of these genes in ccRCC samples compared to adjacent normal tissue. Our findings indicate that loss of VHL could be driving tumour cell dissemination through stabilization of HIF-1α in RCC. A better understanding of the mechanisms involved in this phenomenon can guide the search for more effective treatments to combat mRCC.

Modeling Spontaneous Metastasis following Surgery: An In Vivo-In Silico Approach

Rapid improvements in the detection and tracking of early-stage tumor progression aim to guide decisions regarding cancer treatments as well as predict metastatic recurrence in patients following surgery. Mathematical models may have the potential to further assist in estimating metastatic risk, particularly when paired with in vivo tumor data that faithfully represent all stages of disease progression. Herein, we describe mathematical analysis that uses data from mouse models of spontaneous metastasis developing after surgical removal of orthotopically implanted primary tumors. Both presurgical (primary tumor) growth and postsurgical (metastatic) growth were quantified using bioluminescence and were then used to generate a mathematical formalism based on general laws of the disease (i.e., dissemination and growth). The model was able to fit and predict pre/postsurgical data at the level of the individual as well as the population. Our approach also enabled retrospective analysis of clinical data describing the probability of metastatic relapse as a function of primary tumor size. In these data-based models, interindividual variability was quantified by a key parameter of intrinsic metastatic potential. Critically, our analysis identified a highly nonlinear relationship between primary tumor size and postsurgical survival, suggesting possible threshold limits for the utility of tumor size as a predictor of metastatic recurrence. These findings represent a novel use of clinically relevant models to assess the impact of surgery on metastatic potential and may guide optimal timing of treatments in neoadjuvant (presurgical) and adjuvant (postsurgical) settings to maximize patient benefit.

Neoadjuvant antiangiogenic therapy reveals contrasts in primary and metastatic tumor efficacy

Thousands of cancer patients are currently in clinical trials evaluating antiangiogenic therapy in the neoadjuvant setting, which is the treatment of localized primary tumors prior to surgical intervention. The rationale is that shrinking a tumor will improve surgical outcomes and minimize growth of occult micrometastatic disease—thus delaying post-surgical recurrence and improving survival. But approved VEGF pathway inhibitors have not been tested in clinically relevant neoadjuvant models that compare pre- and post-surgical treatment effects. Using mouse models of breast, kidney, and melanoma metastasis, we demonstrate that primary tumor responses to neoadjuvant VEGFR TKI treatment do not consistently correlate with improved post-surgical survival, with survival worsened in certain settings. Similar negative effects did not extend to protein-based VEGF pathway inhibitors and could be reversed with altered dose, surgical timing, and treatment duration, or when VEGFR TKIs are combined with metronomic ‘anti-metastatic’ chemotherapy regimens. These studies represent the first attempt to recapitulate the complex clinical parameters of neoadjuvant therapy in mice and identify a novel tool to compare systemic antiangiogenic treatment effects on localized and disseminated disease.

Prioritizing therapeutic targets using patient-derived xenograft models

Effective systemic treatment of cancer relies on the delivery of agents with optimal therapeutic potential. The molecular age of medicine has provided genomic tools that can identify a large number of potential therapeutic targets in individual patients, heralding the promise of personalized treatment. However, determining which potential targets actually drive tumor growth and should be prioritized for therapy is challenging. Indeed, reliable molecular matches of target and therapeutic agent have been stringently validated in the clinic for only a small number of targets. Patient-derived xenografts (PDXs) are tumor models developed in immunocompromised mice using tumor procured directly from the patient. As patient surrogates, PDX models represent a powerful tool for addressing individualized therapy. Challenges include humanizing the immune system of PDX models and ensuring high quality molecular annotation, in order to maximize insights for the clinic. Importantly, PDX can be sampled repeatedly and in parallel, to reveal clonal evolution, which may predict mechanisms of drug resistance and inform therapeutic strategy design.