No abstract

Immunotherapy holds tremendous promise for improving cancer treatment1. Administering radiotherapy with immunotherapy has been shown to improve immune responses and can elicit an “abscopal effect”2. Unfortunately, response rates for this strategy remain low3. Herein, we report an improved cancer immunotherapy approach that utilizes antigen-capturing nanoparticles (AC-NPs). We engineered several AC-NPs formulations and demonstrated that the set of protein antigens captured by each AC-NP formulation is dependent upon NP surface properties. We showed that AC-NPs deliver tumor specific proteins to antigen-presenting cells and significantly improve the efficacy of αPD-1 treatment using the B16F10 melanoma model, generating up to 20% cure rate as compared to 0% without AC-NPs. Mechanistic studies revealed that AC-NPs induced an expansion of CD8+ cytotoxic T cells and increased both CD4+/Treg and CD8+/Treg ratios. Our work presents a novel strategy for improving cancer immunotherapy with nanotechnology.

Myeloid-derived suppressor cells (MDSCs

We have profiled, for the first time, an evolving human metastatic microenvironment, measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, ECM organization and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer (HGSOC) metastases that ranged from minimal to extensive disease, we show how non-malignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, whilst also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and twelve other primary solid cancers, suggesting that there may be a common matrix response to human cancer.

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.