The macrophage checkpoint receptor SIRPα signals against phagocytosis by binding CD47 expressed on all cellsincluding macrophages. Here, we found that inhibiting cis interactions between SIRPα and CD47 on the same macrophage increased engulfment ('eating') by approximately the same level as inhibiting trans interactions. Antibody blockade of CD47, as pursued in clinical trials against cancer, was applied separately to human-derived macrophages and to red blood cell (RBC) targets for phagocytosis, and both scenarios produced surprisingly similar increases in RBC engulfment. Blockade of both macrophages and targets resulted in hyper-phagocytosis, and knockdown of macrophage-CD47 likewise increased engulfment of 'foreign' cells and particles, decreased the baseline inhibitory signaling of SIRPα, and linearly increased binding of soluble CD47 in trans, consistent with cis-trans competition. Many cell types express both SIRPα and CD47, including mouse melanoma B16 cells, and CRISPR-mediated deletions modulate B16 phagocytosis, consistent with cis-trans competition. Additionally, soluble SIRPα binding to human CD47 displayed on Chinese hamster ovary (CHO) cells was suppressed by SIRPα co-display, and atomistic computations confirm SIRPα bends and binds CD47 in cis. Safety and efficacy profiles for CD47-SIRPα blockade might therefore reflect a disruption of both cis and trans interactions.
Macrophages are abundant in solid tumours and typically associate with poor prognosis, but macrophage clusters in tumour nests have also been reported as beneficial even though dispersed macrophages would have more contacts with cancer cells. Here, by maximizing both phagocytic activity and macrophage numbers, we discover cooperative phagocytosis by low entropy clusters in rapidly growing engineered immuno-tumouroids. The results fit the calculus of proliferation-versus-engulfment, and rheological measurements and molecular perturbations provide a basis for understanding phagocytic disruption of a tumour's cohesive forces in soft cellular phases. The perturbations underscore the utility of suppressing a macrophage checkpoint in combination with an otherwise ineffective tumour-opsonizing monoclonal antibody, and the approach translates in vivo to tumour elimination that durably protects mice from re-challenge and metastasis. Adoptive transfer of engineered macrophages increases the fraction of mice that eliminate tumours and potentially overcomes checkpoint blockade challenges in solid tumours like insufficient permeation of blocking antibodies and on-target, off-tumour binding. Finally, anti-cancer IgG induced in vivo are tumour-specific but multi-epitope and contribute to a phagocytic feedback that drives macrophage clustering in vitro.Given that solid tumours remain challenging for immunotherapies, durable anti-tumour responses here illustrate unexpected advantages in maximizing net phagocytic activity.
Physicochemical principles such as stoichiometry and fractal assembly can give rise to characteristic scaling between components that potentially include coexpressed transcripts. For key structural factors within the nucleus and extracellular matrix, we discover specific gene-gene scaling exponents across many of the 32 tumor types in The Cancer Genome Atlas, and we demonstrate utility in predicting patient survival as well as scaling-informed machine learning (SIML). All tumors with adjacent tissue data show cancer-elevated proliferation genes, with some genes scaling with the nuclear filament LMNB1, including the transcription factor FOXM1 that we show directly regulates LMNB1. SIML shows that such regulated cancers cluster together with longer overall survival than dysregulated cancers, but high LMNB1 and FOXM1 in half of regulated cancers surprisingly predict poor survival, including for liver cancer. COL1A1 is also studied because it too increases in tumors, and a pan-cancer set of fibrosis genes shows substoichiometric scaling with COL1A1 but predicts patient outcome only for liver cancer—unexpectedly being prosurvival. Single-cell RNA-seq data show nontrivial scaling consistent with power laws from bulk RNA and protein analyses, and SIML segregates synthetic from contractile cancer fibroblasts. Our scaling approach thus yields fundamentals-based power laws relatable to survival, gene function, and experiments.
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