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Multiplexed protein imaging is limited to measuring 40-50 markers at one time. Here the authors break this limit using compressed sensing, a computational method leveraging biological patterns in protein expression.

Bodenmiller and colleagues pair imaging mass cytometry with data from the METABRIC cohort to define single-cell phenotypic and genomic features of breast cancer with spatial context, finding associations with breast cancer subtypes and prognosis.

High-resolution imaging mass cytometry attains subcellular resolution through a combination of oversampling and deconvolution and enables highly multiplex imaging of subcellular structures such as nuclear foci and mitochondrial networks.

The molecular mechanisms underlying drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML) remain to be explored. Here, the use of bulk and single cell multi-omics and ex vivo drug profiling for 21 rrAML patients reveals mechanisms of resistance to the Bcl-2 inhibitor venetoclax and treatment vulnerabilities.

In the Tumor Profiler proof-of-concept observational study, a multiomics approach for profiling tumors from patients with melanoma was feasible, returning data within 4 weeks and informing treatment recommendations in 75% of cases.

Mass cytometry can measure up to 34 markers on cells, but samples cannot be multiplexed. Bodenmiller et al. use metal ion tags to facilitate multiplexed mass cytometry analysis of human blood cell samples treated with 27 kinase inhibitors and 12 stimuli across a range of dosages and time points.

HistoPlexer, a deep learning model, generates multiplexed protein expression maps from H&E images, capturing tumour–immune cell interactions. It outperforms baselines, enhances immune subtyping and survival prediction and offers a cost-effective tool for precision oncology.

Mass cytometry is a powerful method of single cell analysis, but potential confounding effects of cell cycle and cell volume are not taken into account. Here the authors present a combined experimental and computational method to correct for these effects and reveal features of TNFα stimulation that are otherwise masked.

Bodenmiller and colleagues present a method for three-dimensional analysis of tissue architecture using imaging mass cytometry and demonstrate the utility in resolving cellular interactions in the tumor microenvironment, in human breast cancer samples.

Acquired resistance to immune checkpoint inhibitors limits therapeutic success in non-small-cell lung cancer, however, the underpinning immune parameters are largely unknown. Here authors distinguish resistance types based on immune cell infiltration, immune checkpoint molecule and cytokine expression level, using paired samples from patients in the sensitive and in the resistant disease phase.

A statistical approach for optimal design of multiplexed imaging studies has been developed. It determines experimental parameters that facilitate cell phenotype identification.

T cell exhaustion in breast tumours remains to be fully characterised. Here, single cell transcriptomics and imaging mass cytometry analysis of luminal breast tumours with or without exhausted T cells suggests distinct patterns of PD-1 and CXCL13 expression in T cells, and of MHC-I, but not PD-L1, expression in tumour cells.

Phenotypic earth mover’s distance (PhEMD) facilitates the comparison of single-cell experimental conditions, each of which is a high-dimensional dataset, and identifies axes of variation among multicellular biospecimens.

Cancer-associated fibroblasts (CAFs) have different subtypes and play diverse roles in the tumour microenvironment. Here, the authors use single-cell RNA-seq and multiplex imaging mass cytometry data to propose a CAF classification scheme of nine subtypes across different cancer types.

Mass-cytometry analysis reveals how signaling networks respond to changes in the abundance of their nodes.

The histology topography cytometry analysis toolbox (histoCAT) enables quantitative analysis and exploration of highly multiplexed imaging data for better understanding of individual cells in the context of tissue architecture.

Improved imaging techniques are required to help advance our understanding of the complex role of the tumour microenvironment (TME). Here, the authors develop a high-throughput, highly multiplexed tissue visualisation workflow and demonstrate its utility by characterising the response of the TME to radiotherapy in preclinical models of glioblastoma.

Imaging mass cytometry profiling of 693 breast tumors identified 10 recurrent tumor microenvironment spatial structures. These structures were enriched in different molecular subtypes and can be associated with genomic profiles and outcomes.

Multielement Z-tag X-ray fluorescence (MEZ-XRF) offers a new avenue for nondestructive and highly multiplexed tissue imaging and operates from the nanometer to whole-tissue scale, unlocking new biological observations.

A single-cell, spatially resolved analysis of breast cancer demonstrates the heterogeneity of tumour and stroma tissue and provides a more-detailed method of patient classification than the current histology-based system.

Spatial proteomics is advancing rapidly, transforming physiological and biomedical research by enabling the study of how multicellular structures and intercellular communication shape tissue function in health and disease. Through the analysis of large human tissue collections, spatial proteomics will reveal the complexities of human tissues and uncover multicellular modules that can serve as drug targets and diagnostics, paving the way for precision medicine and revolutionizing histopathology.

This paper reports the use of mass cytometry on adherent cells and tissue samples for highly multiplexed imaging at subcellular resolution.

In this Review, de Souza et al. discuss how advances in the ability to image protein markers at high-plex, at single-cell and even subcellular resolution, are expanding our understanding of tumour biology and clinical outcomes, and outline the future promise of combining such multiplex protein imaging methods with other forms of spatial omics.

SABER-IMC combines DNA-based signal amplification by exchange reaction (SABER) with imaging mass cytometry (IMC) to enable simultaneous and highly multiplexed marker detection, even of low-abundance markers not detectable with IMC alone.

Here the authors reveal that TORC2 inhibition and the rapid degradation of Las17/WASP elevates G-actin levels in the yeast nucleus which are responsible for altered long-patch base excision repair of clustered lesions, generating massive chromosome fragmentation.

By delivering precise, reproducible quantification of proteins of interest in biological samples, targeted proteomics approaches are allowing researchers to apply the scientific method using mass spectrometry.

Transition paths by which embryonic stem cells commit to different lineages are not well understood. Here, the authors use combined lineage plus 37-dimensional protein information to identify a developmental cell population co-expressing Sox1 and FoxA2.

Mutations near the ORMDL3 gene have been associated with childhood asthma. Here, in yeast, Orm proteins are shown to function in sphingolipid homeostasis; alterations in this control result in misregulation of sphingolipid production and accumulation of toxic metabolites. This raises the testable hypothesis that misregulation of sphingolipids may directly contribute to the development of asthma.

Maturation of innate immune cells is a graded stereotypic process which is often conserved across species. Here authors label distinct neutrophil leukocyte developmental stages via generating combinations of transgenic zebrafish reporter strains, followed by transcriptome analysis of different neutrophil maturation stages and comparison to the gene expression profile of developing neutrophils from humans and mice.

An integrated workflow for multiplexed tissue image processing and analysis, including interactive inspection of raw data, cell segmentation, feature extraction, single-cell analysis and spatial analysis.

We identified an oligodendrocyte signature associated with brain pathology in the 5xFAD model of amyloidosis, which we termed disease-associated oligodendrocytes. This signature was found to be shared by oligodendrocytes across pathologies.

Huber and colleagues utilize a multi-omic analytical pipeline to define an axis of proliferative drive involving mTOR, MYC and OXPHOS metabolic activity that is associated with disease heterogeneity and outcome in clinical cohorts of CLL.

Long-read single-cell RNA sequencing is capable of detecting isoform-level gene expression and genomic alterations such as mutations and gene fusions, thereby providing cell-specific genotype-phenotype information. Here, the authors use long-read scRNA-seq on metastatic ovarian cancer samples and detect cell-type specific isoforms and gene fusions that may otherwise be misclassified in short-read data.

Single-cell whole-genome sequencing shows that 'foreground' cell-to-cell structural variation and alterations in copy number are associated with genomic diversity and evolution in triple-negative breast and high-grade serous ovarian cancers.

Whole-genome sequencing of human cancer cells in patient-derived mouse xenograft models indicates a key role for TP53 in determining the fitness landscape of polyclonal cancer cell populations.

This protocol describes how to use mass-tag cell barcoding to label individual cell samples with unique combinatorial barcodes. The samples can then be pooled for processing and measurement on a mass cytometer.

HuBMAP supports technology development, data acquisition, and spatial analyses to generate comprehensive molecular and cellular three-dimensional tissue maps.

The LifeTime initiative is an ambitious, multidisciplinary programme that aims to improve healthcare by tracking individual human cells during disease processes and responses to treatment in order to develop and implement cell-based interceptive medicine in Europe.

The authors present a robust diagnostic algorithm based on digital pathology and image analysis that quantifies intratumoral and stromal CD8+ T-cell densities in the tumor center and invasive margin compartment in metastatic melanoma. Spatial CD8+ T-cell densities are translated into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”. Their approach also allows efficient immune phenotyping of metastatic lesions, on biopsy material or even in the absence of material from the invasive margin.