Onco-Circuit Addiction and Onco-Nutrient mTORC1 Signaling Vulnerability in a Model of Aggressive T Cell Malignancy.

How genetic lesions drive cell transformation and whether they can be circumvented without compromising function of non-transformed cells are enduring questions in oncology. Here we show that in mature T cells-in which physiologic clonal proliferation is a cardinal feature- constitutive MYC transcription and Tsc1 loss in mice modeled aggressive human malignancy by reinforcing each other's oncogenic programs. This cooperation was supported by MYC-induced large neutral amino acid transporter chaperone SLC3A2 and dietary leucine, which in synergy with Tsc1 deletion overstimulated mTORC1 to promote mitochondrial fitness and MYC protein overexpression in a positive feedback circuit. A low leucine diet was therapeutic even in late-stage disease but did not hinder T cell immunity to infectious challenge, nor impede T cell transformation driven by constitutive nutrient mTORC1 signaling via Depdc5 loss. Thus, mTORC1 signaling hypersensitivity to leucine as an onco-nutrient enables an onco-circuit, decoupling pathologic from physiologic utilization of nutrient acquisition pathways.

Multilayered Immunity by Tissue-Resident Lymphocytes in Cancer.

Lymphocytes spanning the entire innate-adaptive spectrum can stably reside in tissues and constitute an integral component of the local defense network against immunological challenges. In tight interactions with the epithelium and endothelium, tissue-resident lymphocytes sense antigens and alarmins elicited by infectious microbes and abiotic stresses at barrier sites and mount effector responses to restore tissue homeostasis. Of note, such a host cell-directed immune defense system has been recently demonstrated to surveil epithelial cell transformation and carcinoma development, as well as cancer cell metastasis at selected distant organs, and thus represents a primordial cancer immune defense module. Here we review how distinct lineages of tissue-resident innate lymphoid cells, innate-like T cells, and adaptive T cells participate in a form of multilayered cancer immunity in murine models and patients, and how their convergent effector programs may be targeted through both shared and private regulatory pathways for cancer immunotherapy.

Deep generative model deciphers derailed trajectories in acute myeloid leukemia.

Single-cell genomics has the potential to map cell states and their dynamics in an unbiased way in response to perturbations like disease. However, elucidating the cell-state transitions from healthy to disease requires analyzing data from perturbed samples jointly with unperturbed reference samples. Existing methods for integrating and jointly visualizing single-cell datasets from distinct contexts tend to remove key biological differences or do not correctly harmonize shared mechanisms. We present Decipher, a model that combines variational autoencoders with deep exponential families to reconstruct derailed trajectories (https://github.com/azizilab/decipher). Decipher jointly represents normal and perturbed single-cell RNA-seq datasets, revealing shared and disrupted dynamics. It further introduces a novel approach to visualize data, without the need for methods such as UMAP or TSNE. We demonstrate Decipher on data from acute myeloid leukemia patient bone marrow specimens, showing that it successfully characterizes the divergence from normal hematopoiesis and identifies transcriptional programs that become disrupted in each patient when they acquire NPM1 driver mutations.

Cytotoxic granzyme C-expressing ILC1s contribute to antitumor immunity and neonatal autoimmunity.

Innate lymphocytes are integral components of the cellular immune system that can coordinate host defense against a multitude of challenges and trigger immunopathology when dysregulated. Natural killer (NK) cells and innate lymphoid cells (ILCs) are innate immune effectors postulated to functionally mirror conventional cytotoxic T lymphocytes and helper T cells, respectively. Here, we showed that the cytolytic molecule granzyme C was expressed in cells with the phenotype of type 1 ILCs (ILC1s) in mouse liver and salivary gland. Cell fate-mapping and transfer studies revealed that granzyme C-expressing innate lymphocytes could be derived from ILC progenitors and did not interconvert with NK cells, ILC2s, or ILC3s. Granzyme C defined a maturation state of ILC1s. These granzyme C-expressing ILC1s required the transcription factors T-bet and, to a lesser extent, Eomes and support from transforming growth factor-ß (TGF-ß) signaling for their maintenance in the salivary gland. In a transgenic mouse breast cancer model, depleting ILC1s caused accelerated tumor growth. ILC1s gained granzyme C expression following interleukin-15 (IL-15) stimulation, which enabled perforin-mediated cytotoxicity. Constitutive activation of STAT5, a transcription factor regulated by IL-15, in granzyme C-expressing ILC1s triggered lethal perforin-dependent autoimmunity in neonatal mice. Thus, granzyme C marks a cytotoxic effector state of ILC1s, broadening their function beyond "helper-like" lymphocytes.

Immune profiling of human tumors identifies CD73 as a combinatorial target in glioblastoma.

Immune checkpoint therapy with anti-CTLA-4 and anti-PD-1/PD-L1 has revolutionized the treatment of many solid tumors. However, the clinical efficacy of immune checkpoint therapy is limited to a subset of patients with specific tumor types1,2. Multiple clinical trials with combinatorial immune checkpoint strategies are ongoing; however, the mechanistic rationale for tumor-specific targeting of immune checkpoints is elusive. To garner an insight into tumor-specific immunomodulatory targets, we analyzed 94 patients representing five different cancer types, including those that respond relatively well to immune checkpoint therapy and those that do not, such as glioblastoma multiforme, prostate cancer and colorectal cancer. Through mass cytometry and single-cell RNA sequencing, we identified a unique population of CD73hi macrophages in glioblastoma multiforme that persists after anti-PD-1 treatment. To test if targeting CD73 would be important for a successful combination strategy in glioblastoma multiforme, we performed reverse translational studies using CD73-/- mice. We found that the absence of CD73 improved survival in a murine model of glioblastoma multiforme treated with anti-CTLA-4 and anti-PD-1. Our data identified CD73 as a specific immunotherapeutic target to improve antitumor immune responses to immune checkpoint therapy in glioblastoma multiforme and demonstrate that comprehensive human and reverse translational studies can be used for rational design of combinatorial immune checkpoint strategies.

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.