Effective anti-tumor immunity in humans has been associated with the presence of T cells directed at cancer neoantigens1, which are T cell epitopes with tumor-specific expression arising from non-silent somatic mutations. They are highly immunogenic because they are not expressed in normal tissues and hence bypass central thymic tolerance. Although neoantigens were long-envisioned as optimal targets for an anti-tumor immune response2, their systematic discovery and evaluation only became feasible with the recent availability of massively-parallel sequencing for detection of all coding mutations within tumors, and of machine learning approaches to reliably predict those mutated peptides with high-affinity binding of autologous HLA molecules. We hypothesized that vaccination with neoantigens can both expand pre-existing neoantigen-specific T cell populations and induce a broader repertoire of new T cell specificities in cancer patients, tipping the intra-tumoral balance in favor of enhanced tumor control. Here we demonstrate the feasibility, safety and immunogenicity of a vaccine that targets up to 20 predicted personal tumor neoantigens. Vaccine-induced polyfunctional CD4+ and CD8+ T cells targeted 58 (60%) and 15 (16%), respectively, of the 97 unique neoantigens used across patients. These T cells discriminated mutated from wildtype antigens, and in some cases, directly recognized autologous tumor. Of 6 vaccinated patients, 4 had no recurrence at 25 months post-vaccination, while 2 with progressive disease were subsequently treated with anti-PD-1 therapy and experienced complete tumor regression, with expansion of the repertoire of neoantigen-specific T cells. These data provide a strong rationale for further development of this approach, alone and in combination with checkpoint therapies.

SUMMARY CRISPR-Cas9 is a versatile genome editing technology for studying the function of genetic elements. To broadly enable the application of Cas9 in vivo, we established a Cre-dependent Cas9 knockin mouse. We demonstrated in vivo as well as ex vivo genome editing using adeno-associated virus (AAV)-, lenti-virus-, or particle-mediated delivery of guide RNA in neurons, immune cells, and endothelial cells. Using these mice, we simultaneously modeled the dynamics of KRAS, p53, and LKB1, the top three significantly mutated genes in lung adenocarcinoma. Delivery of a single AAV vector in the lung generated loss-of-function mutations in p53 and LKB1, as well as homology-directed repair-mediated KRASG12D mutations, leading to macroscopic tumors of adeno-carcinoma pathology. Together, these results suggest that Cas9 mice empower a wide range of biological and disease modeling applications.

To enable arrayed or pooled loss-of-function screens in a wide range of mammalian cell types, including primary and nondividing cells, we are developing lentiviral short hairpin RNA (shRNA) libraries targeting the human and murine genomes. The libraries currently contain 104,000 vectors, targeting each of 22,000 human and mouse genes with multiple sequence-verified constructs. To test the utility of the library for arrayed screens, we developed a screen based on high-content imaging to identify genes required for mitotic progression in human cancer cells and applied it to an arrayed set of 5,000 unique shRNA-expressing lentiviruses that target 1,028 human genes. The screen identified several known and approximately 100 candidate regulators of mitotic progression and proliferation; the availability of multiple shRNAs targeting the same gene facilitated functional validation of putative hits. This work provides a widely applicable resource for loss-of-function screens, as well as a roadmap for its application to biological discovery.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA-seq and flow cytometry to T cells, B cells, monocytes and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis. Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics together revealed cell states expanded in RA synovia: THY1(CD90) + HLA-DRA hi sublining fibroblasts, IL1B + pro-inflammatory monocytes, ITGAX + TBX21 + autoimmune-associated B cells and PDCD1 + T peripheral helper (Tph) and T follicular helper (Tfh). We defined distinct subsets of CD8 + T cells characterized by a GZMK + , GZMB + and GNLY + phenotype. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1 + HLA-DRA hi fibroblasts, and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.