The immune system responds to cancer in two main ways. First, there are prewired responses involving myeloid cells, innate lymphocytes and innate-like adaptive lymphocytes that either reside in premalignant tissues or migrate directly to tumours, and second, there are antigen priming-dependent responses, in which adaptive lymphocytes are primed in secondary lymphoid organs before homing to tumours. Transforming growth factor-β (TGFβ) - one of the most potent and pleiotropic regulatory cytokines - controls almost every stage of the tumour-elicited immune response, from leukocyte development in primary lymphoid organs to their priming in secondary lymphoid organs and their effector functions in the tumour itself. The complexity of TGFβ-regulated immune cell circuitries, as well as the contextual roles of TGFβ signalling in cancer cells and tumour stromal cells, necessitates the use of rigorous experimental systems that closely recapitulate human cancer, such as autochthonous tumour models, to uncover the underlying immunobiology. The diverse functions of TGFβ in healthy tissues further complicate the search for effective and safe cancer therapeutics targeting the TGFβ pathway. Here we discuss the contextual complexity of TGFβ signalling in tumour-elicited immune responses and explain how understanding this may guide the development of mechanism-based cancer immunotherapy. <<<

Abhinav Achreja, Tao Yu, Anjali Mittal, Srinadh Choppara, Olamide Animasahun, Minal Nenwani, Fulei Wuchu, Noah Meurs, Aradhana Mohan, Jin Heon Jeon, Itisam Sarangi, Anusha Jayaraman, Sarah Owen, Reva Kulkarni, Michele Cusato, Frank Weinberg, Hye Kyong Kweon, Chitra Subramanian, Max S Wicha, Sofia D Merajver, Sunitha Nagrath, Kathleen R Cho, Analisa DiFeo, Xiongbin Lu, Deepak Nagrath <<<

Recurrent loss-of-function deletions cause frequent inactivation of tumour suppressor genes but often also involve the collateral deletion of essential genes in chromosomal proximity, engendering dependence on paralogues that maintain similar function. Although these paralogues are attractive anticancer targets, no methodology exists to uncover such collateral lethal genes. Here we report a framework for collateral lethal gene identification via metabolic fluxes, CLIM, and use it to reveal MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours. We show that MTHFD2 has a non-canonical oxidative function to provide mitochondrial NAD, and demonstrate the regulation of systemic metabolic activity by the paralogue metabolic pathway maintaining metabolic flux compensation. This UQCR11-MTHFD2 collateral lethality is confirmed in vivo, with MTHFD2 inhibition leading to complete remission of UQCR11-deleted ovarian tumours. Using CLIM's machine learning and genome-scale metabolic flux analysis, we elucidate the broad efficacy of targeting MTHFD2 despite distinct cancer genetic profiles co-occurring with UQCR11 deletion and irrespective of stromal compositions of tumours. <<<

The advent of immune checkpoint inhibition (ICI) using antibodies against PD1 and its ligand PDL1 has prompted substantial efforts to develop complementary drugs. Although many of these are antibodies directed against additional checkpoint proteins, there is an increasing interest in small-molecule immuno-oncology drugs that address intracellular pathways, some of which have recently entered clinical trials. In parallel, small molecules that target pro-tumorigenic pathways in cancer cells and the tumour microenvironment have been found to have immunostimulatory effects that synergize with the action of ICI antibodies, leading to the approval of an increasing number of regimens that combine such drugs. Combinations with small molecules targeting cancer metabolism, cytokine/chemokine and innate immune pathways, and T cell checkpoints are now under investigation. This Review discusses the recent milestones and hurdles encountered in this area of drug development, as well as our views on the best path forward. <<<

The human immune system is composed of a distributed network of cells circulating throughout the body, which must dynamically form physical associations and communicate using interactions between their cell-surface proteomes1. Despite their therapeutic potential2, our map of these surface interactions remains incomplete3,4. Here, using a high-throughput surface receptor screening method, we systematically mapped the direct protein interactions across a recombinant library that encompasses most of the surface proteins that are detectable on human leukocytes. We independently validated and determined the biophysical parameters of each novel interaction, resulting in a high-confidence and quantitative view of the receptor wiring that connects human immune cells. By integrating our interactome with expression data, we identified trends in the dynamics of immune interactions and constructed a reductionist mathematical model that predicts cellular connectivity from basic principles. We also developed an interactive multi-tissue single-cell atlas that infers immune interactions throughout the body, revealing potential functional contexts for new interactions and hubs in multicellular networks. Finally, we combined targeted protein stimulation of human leukocytes with multiplex high-content microscopy to link our receptor interactions to functional roles, in terms of both modulating immune responses and maintaining normal patterns of intercellular associations. Together, our work provides a systematic perspective on the intercellular wiring of the human immune system that extends from systems-level principles of immune cell connectivity down to mechanistic characterization of individual receptors, which could offer opportunities for therapeutic intervention. <<<

Joseph M Replogle, Reuben A Saunders, Angela N Pogson, Jeffrey A Hussmann, Alexander Lenail, Alina Guna, Lauren Mascibroda, Eric J Wagner, Karen Adelman, Gila Lithwick-Yanai, Nika Iremadze, Florian Oberstrass, Doron Lipson, Jessica L Bonnar, Marco Jost, Thomas M Norman, Jonathan S Weissman <<<

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena-from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function. <<<

Maintenance of tissue homeostasis is dependent on the communication between stem cells and supporting cells in the same niche. Regulatory T cells (T cells) are emerging as a critical component of the stem-cell niche for supporting their differentiation. How T cells sense dynamic signals in this microenvironment and communicate with stem cells is mostly unknown. In the present study, by using hair follicles (HFs) to study T cell-stem cell crosstalk, we show an unrecognized function of the steroid hormone glucocorticoid in instructing skin-resident T cells to facilitate HF stem-cell (HFSC) activation and HF regeneration. Ablation of the glucocorticoid receptor (GR) in T cells blocks hair regeneration without affecting immune homeostasis. Mechanistically, GR and Foxp3 cooperate in T cells to induce transforming growth factor β3 (TGF-β3), which activates Smad2/3 in HFSCs and facilitates HFSC proliferation. The present study identifies crosstalk between T cells and HFSCs mediated by the GR-TGF-β3 axis, highlighting a possible means of manipulating T cells to support tissue regeneration. <<<

C Domínguez Conde, C Xu, L B Jarvis, D B Rainbow, S B Wells, T Gomes, S K Howlett, O Suchanek, K Polanski, H W King, L Mamanova, N Huang, P A Szabo, L Richardson, L Bolt, E S Fasouli, K T Mahbubani, M Prete, L Tuck, N Richoz, Z K Tuong, L Campos, H S Mousa, E J Needham, S Pritchard, T Li, R Elmentaite, J Park, E Rahmani, D Chen, D K Menon, O A Bayraktar, L K James, K B Meyer, N Yosef, M R Clatworthy, P A Sims, D L Farber, K Saeb-Parsy, J L Jones, S A Teichmann <<<

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing. <<<

Neoantigen vaccines aiming to induce tumor-specific T cell responses have achieved promising antitumor effects in early clinical trials. However, the underlying mechanism regarding response or resistance to this treatment is unclear. Here we observe that neoantigen vaccine-generated T cells can synergize with the immune checkpoint blockade for effective tumor control. Specifically, we performed single-cell sequencing on over 100,000 T cells and uncovered that combined therapy induces an antigen-specific CD8 T cell population with active chemokine signaling (Cxcr3/Ccl5), lower co-inhibitory receptor expression (Lag3/Havcr2) and higher cytotoxicity (Fasl/Gzma). Furthermore, generation of neoantigen-specific T cells in the draining lymph node is required for combination treatment. Signature genes of this unique population are associated with T cell clonal frequency and better survival in humans. Our study profiles the dynamics of tumor-infiltrating T cells during neoantigen vaccine and immune checkpoint blockade treatments and high-dimensionally identifies neoantigen-reactive T cell signatures for future development of therapeutic strategies. <<<

Enormous progress has been made in the last half-century in the management of diseases closely integrated with excess body weight, such as hypertension, adult-onset diabetes and elevated cholesterol. However, the treatment of obesity itself has proven largely resistant to therapy, with anti-obesity medications (AOMs) often delivering insufficient efficacy and dubious safety. Here, we provide an overview of the history of AOM development, focusing on lessons learned and ongoing obstacles. Recent advances, including increased understanding of the molecular gut-brain communication, are inspiring the pursuit of next-generation AOMs that appear capable of safely achieving sizeable and sustained body weight loss. <<<

Alberto Santos, Ana R Colaço, Annelaura B Nielsen, Lili Niu, Maximilian Strauss, Philipp E Geyer, Fabian Coscia, Nicolai J Wewer Albrechtsen, Filip Mundt, Lars Juhl Jensen, Matthias Mann <<<

Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making. <<<