Lipid-based nanosystems: the next generation of cancer immune therapy.

Immunotherapy has become an important part of the oncotherapy arsenal. Its applicability in various cancer types is impressive, as well as its use of endogenous mechanisms to achieve desired ends. However, off-target or on-target-off-tumor toxicity, limited activity, lack of control in combination treatments and, especially for solid tumors, low local accumulation, have collectively limited clinical use thereof. These limitations are partially alleviated by delivery systems. Lipid-based nanoparticles (NPs) have emerged as revolutionary carriers due to favorable physicochemical characteristics, with specific applications and strengths particularly useful in immunotherapeutic agent delivery. The aim of this review is to highlight the challenges faced by immunotherapy and how lipid-based NPs have been, and may be further utilized to address such challenges. We discuss recent fundamental and clinical applications of NPs in a range of areas and provide a detailed discussion of the main obstacles in immune checkpoint inhibition therapies, adoptive cellular therapies, and cytokine therapies. We highlight how lipid-based nanosystems could address these through either delivery, direct modulation of the immune system, or targeting of the immunosuppressive tumor microenvironment. We explore advanced and emerging liposomal and lipid nanoparticle (LNP) systems for nucleic acid delivery, intrinsic and extrinsic stimulus-responsive formulations, and biomimetic lipid-based nanosystems in immunotherapy. Finally, we discuss the key challenges relating to the clinical use of lipid-based NP immunotherapies, suggesting future research directions for the near term to realize the potential of these innovative lipid-based nanosystems, as they become the crucial steppingstone towards the necessary enhancement of the efficacy of immunotherapy.

Gene-expression-based T-Cell-to-Stroma Enrichment (TSE) score predicts response to immune checkpoint inhibitors in urothelial cancer.

Immune checkpoint inhibitors (ICI) improve overall survival in patients with metastatic urothelial cancer (mUC), but therapeutic success at the individual patient level varies significantly. Here we identify predictive markers of response, based on whole-genome DNA (n = 70) and RNA-sequencing (n = 41) of fresh metastatic biopsy samples, collected prior to treatment with pembrolizumab. We find that PD-L1 combined positivity score does not, whereas tumor mutational burden and APOBEC mutagenesis modestly predict response. In contrast, T cell-to-stroma enrichment (TSE) score, computed from gene expression signature data to capture the relative abundance of T cells and stromal cells, predicts response to immunotherapy with high accuracy. Patients with a positive and negative TSE score show progression free survival rates at 6 months of 67 and 0%, respectively. The abundance of T cells and stromal cells, as reflected by the TSE score is confirmed by immunofluorescence in tumor tissue, and its good performance in two independent ICI-treated cohorts of patients with mUC (IMvigor210) and muscle-invasive UC (ABACUS) validate the predictive power of the TSE score. In conclusion, the TSE score represents a clinically applicable metric that potentially supports the prospective selection of patients with mUC for ICI treatment.

Retroviral Transduction of Human Primary T Cells Followed by Real-Time T-Cell-Mediated Cancer Cell Cytolysis Analysis.

Retroviral transduction is a highly useful tool to genetically engineer hard-to-transfect human primary cells. Here, we transduce human primary T cells with a tumor-specific T cell receptor. This creates a useful tool to analyze T cell-cancer cell interactions, such as cytolysis analysis using xCELLigence technology.