Delivery of miR-214 via extracellular vesicles downregulates Xbp1 expression and pro-inflammatory cytokine genes in macrophages.

Aim: Tumor-infiltrating macrophages are tumor-promoting and show activation of the unfolded protein response (UPR). The transcription factor X-box binding protein 1 (XBP1) is a conserved element of the UPR. Upon activation, the UPR mediates the transcriptional activation of pro-inflammatory cytokines and immune suppressive factors, hence contributing to immune dysregulation in the tumor microenvironment (TME). miR-214 is a short non-coding miRNA that targets the 3'-UTR of the Xbp1 transcript. Here, we tested a new method to efficiently deliver miR-214 to macrophages as a potential new therapeutic approach. Methods: We generated miR-214-laden extracellular vesicles (iEV-214) in a murine B cell and demonstrated that iEV-214 were enriched in miR-214 between 1,500 - 2,000 fold relative to control iEVs. Results: Bone marrow-derived macrophages (BMDM) treated with iEV-214 for 24 h underwent a specific enrichment in miR-214, suggesting transfer of the miR-214 payload from the iEVs to macrophages. iEV-214 treatment of BMDM markedly reduced (> 50%) Xbp1 transcription under endoplasmic reticulum stress conditions compared to controls. Immune-related genes downstream of XBP1s (Il-6, Il-23p19, and Arg1) were also reduced by 69%, 51%, and 34%, respectively. Conclusions: Together, these data permit to conclude that iEV-214 are an efficient strategy to downregulate the expression of Xbp1 mRNA and downstream genes in macrophages. We propose miRNA-laden iEVs are a new approach to target macrophages and control immune dysregulation in the TME.

Inhalable dry powders of microRNA-laden extracellular vesicles prepared by thin-film freeze-drying.

Extracellular vesicles (EVs) are endogenous vesicles that comprise a variety of submicron vesicular structures. Among these, exosomes have been widely investigated as delivery systems for small and large molecules. Herein, the thin-film freeze-drying technology was utilized to engineer aerosolizable dry powders of miR-335-laden induced EVs (iEV-335) generated in B cells for potential delivery into the lung to treat primary lung cancer and/or pulmonary metastases. The size distribution, structure, and morphology of iEV-335 were preserved after they were subjected to thin-film freeze-drying with the proper excipients. Importantly, iEV-335, in liquid or reconstituted from thin-film freeze-dried powders, were equally effective in downregulating SOX4 gene expression in LM2 human triple-negative mammary cancer cells. The iEV-335 dry powder compositions showed mass median aerodynamic diameters (MMAD) of around 1.2 µm with > 60 % of the emitted doses had an MMAD of ≤ 3 µm, indicating that the powders can potentially achieve efficient deposition within the alveolar region following oral inhalation, which is desirable for treatment of primary lung cancer and pulmonary metastases. Overall, it is concluded that it is feasible to apply thin-film freeze-drying to prepare aerosolizable dry powders of iEVs for pulmonary delivery.

Integrated germline and somatic features reveal divergent immune pathways driving ICB response.

Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses.