Metastatic castration-resistant prostate cancer is typically lethal, exhibiting intrinsic or acquired resistance to second-generation androgen-targeting therapies and minimal response to immune checkpoint inhibitors1. Cellular programs driving resistance in both cancer and immune cells remain poorly understood. We present single-cell transcriptomes from 14 patients with advanced prostate cancer, spanning all common metastatic sites. Irrespective of treatment exposure, adenocarcinoma cells pervasively coexpressed multiple androgen receptor isoforms, including truncated isoforms hypothesized to mediate resistance to androgen-targeting therapies2,3. Resistance to enzalutamide was associated with cancer cell–intrinsic epithelial–mesenchymal transition and transforming growth factor-β signaling. Small cell carcinoma cells exhibited divergent expression programs driven by transcriptional regulators promoting lineage plasticity and HOXB5, HOXB6 and NR1D2 (refs.4–6). Additionally, a subset of patients had high expression of dysfunction markers on cytotoxic CD8+T cells undergoing clonal expansion following enzalutamide treatment. Collectively, the transcriptional characterization of cancer and immune cells from human metastatic castration-resistant prostate cancer provides a basis for the development of therapeutic approaches complementing androgen signaling inhibition.
Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRISPR screening approaches to systematically profile the effects of activating or repressing 120 transcriptional and epigenetic regulators on human CD8+T cell state. We found that BATF3 overexpression promoted specific features of memory T cells and attenuated gene programs associated with cytotoxicity, regulatory T cell function, and exhaustion. Upon chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. Moreover, BATF3 enhanced the potency of CAR T cells in both in vitro and in vivo tumor models and programmed a transcriptional profile that correlates with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens that defined cofactors and downstream mediators of the BATF3 gene network.
more » « less- PAR ID:
- 10473443
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Nature Genetics
- Volume:
- 55
- Issue:
- 12
- ISSN:
- 1061-4036
- Format(s):
- Medium: X Size: p. 2211-2223
- Size(s):
- p. 2211-2223
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract -
T cell exhaustion limits immune responses against cancer and is a major cause of resistance to chimeric antigen receptor (CAR)–T cell therapeutics. Using murine xenograft models and an in vitro model wherein tonic CAR signaling induces hallmark features of exhaustion, we tested the effect of transient cessation of receptor signaling, or rest, on the development and maintenance of exhaustion. Induction of rest through enforced down-regulation of the CAR protein using a drug-regulatable system or treatment with the multikinase inhibitor dasatinib resulted in the acquisition of a memory-like phenotype, global transcriptional and epigenetic reprogramming, and restored antitumor functionality in exhausted CAR-T cells. This work demonstrates that rest can enhance CAR-T cell efficacy by preventing or reversing exhaustion, and it challenges the notion that exhaustion is an epigenetically fixed state.
-
Abstract Numerous studies are exploring the use of cell adoptive therapies to treat hematological malignancies as well as solid tumors. However, there are numerous factors that dampen the immune response, including viruses like human immunodeficiency virus. In this study, we leverage human-derived microphysiological models to reverse-engineer the HIV-immune system interaction and evaluate the potential of memory-like natural killer cells for HIV+head and neck cancer, one of the most common tumors in patients living with human immunodeficiency virus. Here, we evaluate multiple aspects of the memory-like natural killer cell response in human-derived bioengineered environments, including immune cell extravasation, tumor penetration, tumor killing, T cell dependence, virus suppression, and compatibility with retroviral medication. Overall, these results suggest that memory-like natural killer cells are capable of operating without T cell assistance and could simultaneously destroy head and neck cancer cells as well as reduce viral latency.
-
Abstract Regulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call “PERSIST which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies.
-
Abstract Clustered regularly interspaced short palindromic repeats (CRISPR) screening coupled with single-cell RNA sequencing has emerged as a powerful tool to characterize the effects of genetic perturbations on the whole transcriptome at a single-cell level. However, due to its sparsity and complex structure, analysis of single-cell CRISPR screening data is challenging. In particular, standard differential expression analysis methods are often underpowered to detect genes affected by CRISPR perturbations. We developed a statistical method for such data, called guided sparse factor analysis (GSFA). GSFA infers latent factors that represent coregulated genes or gene modules; by borrowing information from these factors, it infers the effects of genetic perturbations on individual genes. We demonstrated through extensive simulation studies that GSFA detects perturbation effects with much higher power than state-of-the-art methods. Using single-cell CRISPR data from human CD8+T cells and neural progenitor cells, we showed that GSFA identified biologically relevant gene modules and specific genes affected by CRISPR perturbations, many of which were missed by existing methods, providing new insights into the functions of genes involved in T cell activation and neurodevelopment.