Cells respond to many stressors by senescing, acquiring stable growth arrest, morphologic and metabolic changes, and a proinflammatory senescence-associated secretory phenotype. The heterogeneity of senescent cells (SnCs) and senescence-associated secretory phenotype are vast, yet ill characterized. SnCs have diverse roles in health and disease and are therapeutically targetable, making characterization of SnCs and their detection a priority. The Cellular Senescence Network (SenNet), a National Institutes of Health Common Fund initiative, was established to address this need. The goal of SenNet is to map SnCs across the human lifespan to advance diagnostic and therapeutic approaches to improve human health. State-of-the-art methods will be applied to identify, define and map SnCs in 18 human tissues. A common coordinate framework will integrate data to create four-dimensional SnC atlases. Other key SenNet deliverables include innovative tools and technologies to detect SnCs, new SnC biomarkers and extensive public multi-omics datasets. This Perspective lays out the impetus, goals, approaches and products of SenNet.
The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.HuBMAP was founded with the goal of establishing state-of-the-art frameworks for building spatial multiomic maps of non-diseased human organs at single-cell resolution 1 . During the first phase (2018)(2019)(2020)(2021)(2022), the priorities of the project included the validation and development of assay platforms; workflows for data processing, management, exploration and visualization; and the establishment of protocols, quality control standards and standard operating procedures. Extensive infrastructure was established through a coordinated effort among the various HuB-MAP integration, visualization and engagement teams, tissue-mapping centres, technology and tools development and rapid technology implementation teams and working groups 1 . Single-cell maps, predominantly consisting of two-dimensional (2D) spatial data as well as data from dissociated cells, were generated for several organs. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) was established for open access to experimental tissue data and reference atlas data.The infrastructure was augmented with software tools for tissue data registration, processing, annotation, visualization, cell segmentation and automated annotation of cell types and cellular neighbourhoods from spatial data. Computational methods were developed for integrating multiple data types across scales and interpretation 2 . Standard reference terminology and a common coordinate framework spanning anatomical to biomolecular scales were established to ensure interoperability across organs, research groups and consortia 3 . Guidelines to capture high-quality multiplexed spatial data 4 were established including validated panels of cell-and structure-specific antibodies 5 . The first phase produced a large number of manuscripts (https://commonfund.nih.gov/ publications?pid=43) including spatially resolved single-cell maps [6][7][8][9][10][11] .The production phase of HuBMAP was launched in the autumn of 2022. The focus is on scaling data production spanning diverse biological variables (for example, age and ethnicity) and deployment and enhancement of analytical, visualization and navigational tools to generate high-resolution 3D accessible maps of major functional tissue units from more than 20 organs. This phase involves over 60 institutions and 400 researchers with opportunities for active intra-and inter-consortia collaborations and building a foundational resource for new biological insights and precision medicine. Below, ...
Receptors that help immune cells recognize 'self' cells can be functionally blocked with antibodies, and a fraction of cancer patients show durable cures through blockade of such T-cell checkpoints. Macrophages possess a similar checkpoint that we block in combination with tumor opsonization in order to target injected macrophages for phagocytosis of cancer cells. The approaches require immune cell infiltration, which motivates study of the physical properties of tumors. We are specifically blocking signal regulatory protein alpha (SIRPa) on macrophages, which binds the ubiquitous 'self'-marker CD47, and we inject these cells together with a pro-phagocytic antibody against tyrosinase-related protein 1 (Tyrp1) on syngeneic B16 melanoma in an immunocompetent mouse. This widely used preclinical murine model for evaluating immunotherapies is sometimes described as a 'solid' tumor, but macropipette aspiration of fresh tumors reveals high compliance and largely irreversible deformation. Such properties will generally modulate macrophage infiltration, interactions, and phenotype. As we continue to study such effects, we already find that systematic injection of engineered macrophages into mice with subcutaneous B16 tumors results in delayed tumor growth and even some durable cures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.