Multiplex protein imaging in tumour biology.

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Cancer-associated fibroblast phenotypes are associated with patient outcome in non-small cell lung cancer.

Despite advances in treatment, lung cancer survival rates remain low. A better understanding of the cellular heterogeneity and interplay of cancer-associated fibroblasts (CAFs) within the tumor microenvironment will support the development of personalized therapies. We report a spatially resolved single-cell imaging mass cytometry (IMC) analysis of CAFs in a non-small cell lung cancer cohort of 1,070 patients. We identify four prognostic patient groups based on 11 CAF phenotypes with distinct spatial distributions and show that CAFs are independent prognostic factors for patient survival. The presence of tumor-like CAFs is strongly correlated with poor prognosis. In contrast, inflammatory CAFs and interferon-response CAFs are associated with inflamed tumor microenvironments and higher patient survival. High density of matrix CAFs is correlated with low immune infiltration and is negatively correlated with patient survival. In summary, our data identify phenotypic and spatial features of CAFs that are associated with patient outcome in NSCLC.

Cancer-associated fibroblast classification in single-cell and spatial proteomics data.

Cancer-associated fibroblasts (CAFs) are a diverse cell population within the tumour microenvironment, where they have critical effects on tumour evolution and patient prognosis. To define CAF phenotypes, we analyse a single-cell RNA sequencing (scRNA-seq) dataset of over 16,000 stromal cells from tumours of 14 breast cancer patients, based on which we define and functionally annotate nine CAF phenotypes and one class of pericytes. We validate this classification system in four additional cancer types and use highly multiplexed imaging mass cytometry on matched breast cancer samples to confirm our defined CAF phenotypes at the protein level and to analyse their spatial distribution within tumours. This general CAF classification scheme will allow comparison of CAF phenotypes across studies, facilitate analysis of their functional roles, and potentially guide development of new treatment strategies in the future.

Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers.

Although breast cancer mortality is largely caused by metastasis, clinical decisions are based on analysis of the primary tumor and on lymph node involvement but not on the phenotype of disseminated cells. Here, we use multiplex imaging mass cytometry to compare single-cell phenotypes of primary breast tumors and matched lymph node metastases in 205 patients. We observe extensive phenotypic variability between primary and metastatic sites and that disseminated cell phenotypes frequently deviate from the clinical disease subtype. We identify single-cell phenotypes and spatial organizations of disseminated tumor cells that are associated with patient survival and a weaker survival association for high-risk phenotypes in the primary tumor. We show that p53 and GATA3 in lymph node metastases provide prognostic information beyond clinical classifiers and can be measured with standard methods. Molecular characterization of disseminated tumor cells is an untapped source of clinically applicable prognostic information for breast cancer.

A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer.

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I - but not PD-L1 - on tumor cells are strong distinguishing features between these environments.

Limited Proteolysis-Mass Spectrometry to Identify Metabolite-Protein Interactions.

Metabolite-protein interactions regulate diverse cellular processes, prompting the development of methods to investigate the metabolite-protein interactome at a global scale. One such method is our previously developed structural proteomics approach, limited proteolysis-mass spectrometry (LiP-MS), which detects proteome-wide metabolite-protein and drug-protein interactions in native bacterial, yeast, and mammalian systems, and allows identification of binding sites without chemical modification. Here we describe a detailed experimental and analytical workflow for conducting a LiP-MS experiment to detect small molecule-protein interactions, either in a single-dose (LiP-SMap) or a multiple-dose (LiP-Quant) format. LiP-Quant analysis combines the peptide-level resolution of LiP-MS with a machine learning-based framework to prioritize true protein targets of a small molecule of interest. We provide an updated R script for LiP-Quant analysis via a GitHub repository accessible at https://github.com/RolandBruderer/MiMB-LiP-Quant .

Mass cytometric and transcriptomic profiling of epithelial-mesenchymal transitions in human mammary cell lines.

Epithelial-mesenchymal transition (EMT) equips breast cancer cells for metastasis and treatment resistance. However, detection, inhibition, and elimination of EMT-undergoing cells is challenging due to the intrinsic heterogeneity of cancer cells and the phenotypic diversity of EMT programs. We comprehensively profiled EMT transition phenotypes in four non-cancerous human mammary epithelial cell lines using a flow cytometry surface marker screen, RNA sequencing, and mass cytometry. EMT was induced in the HMLE and MCF10A cell lines and in the HMLE-Twist-ER and HMLE-Snail-ER cell lines by prolonged exposure to TGFß1 or 4-hydroxytamoxifen, respectively. Each cell line exhibited a spectrum of EMT transition phenotypes, which we compared to the steady-state phenotypes of fifteen luminal, HER2-positive, and basal breast cancer cell lines. Our data provide multiparametric insights at single-cell level into the phenotypic diversity of EMT at different time points and in four human cellular models. These insights are valuable to better understand the complexity of EMT, to compare EMT transitions between the cellular models used here, and for the design of EMT time course experiments.

Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment.

A holistic understanding of tissue and organ structure and function requires the detection of molecular constituents in their original three-dimensional (3D) context. Imaging mass cytometry (IMC) enables simultaneous detection of up to 40 antigens and transcripts using metal-tagged antibodies but has so far been restricted to two-dimensional imaging. Here we report the development of 3D IMC for multiplexed 3D tissue analysis at single-cell resolution and demonstrate the utility of the technology by analysis of human breast cancer samples. The resulting 3D models reveal cellular and microenvironmental heterogeneity and cell-level tissue organization not detectable in two dimensions. 3D IMC will prove powerful in the study of phenomena occurring in 3D space such as tumor cell invasion and is expected to provide invaluable insights into cellular microenvironments and tissue architecture.

Deciphering the signaling network of breast cancer improves drug sensitivity prediction.

One goal of precision medicine is to tailor effective treatments to patients' specific molecular markers of disease. Here, we used mass cytometry to characterize the single-cell signaling landscapes of 62 breast cancer cell lines and five lines from healthy tissue. We quantified 34 markers in each cell line upon stimulation by the growth factor EGF in the presence or absence of five kinase inhibitors. These data-on more than 80 million single cells from 4,000 conditions-were used to fit mechanistic signaling network models that provide insight into how cancer cells process information. Our dynamic single-cell-based models accurately predicted drug sensitivity and identified genomic features associated with drug sensitivity, including a missense mutation in DDIT3 predictive of PI3K-inhibition sensitivity. We observed similar trends in genotype-drug sensitivity associations in patient-derived xenograft mouse models. This work provides proof of principle that patient-specific single-cell measurements and modeling could inform effective precision medicine strategies.

Suspected adverse drug interaction between spinosad and milbemycin oxime in a cat.

CASE SUMMARY: A 12-year-old male neutered Tonkinese cat was presented for acute ataxia, weakness, altered mentation and generalised tremors. The cat had been administered oral spinosad (140 mg; 33.5 mg/kg) 48 h prior to the onset of clinical signs, and an oral anthelmintic containing milbemycin oxime (16 mg; 3.8 mg/kg) and praziquantel (40 mg; 9.6 mg/kg) 12 h before the onset of clinical signs. On physical examination, dull-to-obtunded mentation, tetraparesis, ataxia and mild tremors of facial, limb and trunk muscles were noted. Serum biochemical changes and urinalysis were consistent with haemoconcentration. The results of a complete blood count, urine culture and serology for feline leukaemia virus, feline immunodeficiency virus and cryptococcal antigen were negative. The patient was monitored in hospital and all clinical signs resolved within 24 h. RELEVANCE AND NOVEL INFORMATION: The neurological signs in this case were consistent with macrocyclic lactone neurotoxicity, which is suspected to have occurred from an adverse drug interaction between spinosad and milbemycin oxime. This report serves to highlight the potential for this adverse drug interaction between these commonly used prophylactic drugs.

Too much of a good thing.

Culture of primary lymphocytes at physiological oxygen levels better maintains intracellular redox state.

Cartography of an organelle.

Peptide counting in mass spectrometry allows researchers to draw a quantitative proteomic map of the ER and Golgi.

SEL-2, the C. elegans neurobeachin/LRBA homolog, is a negative regulator of lin-12/Notch activity and affects endosomal traffic in polarized epithelial cells.

The vulval precursor cells (VPCs) of Caenorhabditis elegans are polarized epithelial cells that adopt a precise pattern of fates through regulated activity of basolateral LET-23/EGF receptor and apical LIN-12/Notch. During VPC patterning, there is reciprocal modulation of endocytosis and trafficking of both LET-23 and LIN-12. We identified sel-2 as a negative regulator of lin-12/Notch activity in the VPCs, and found that SEL-2 is the homolog of two closely related human proteins, neurobeachin (also known as BCL8B) and LPS-responsive, beige-like anchor protein (LRBA). SEL-2, neurobeachin and LRBA belong to a distinct subfamily of BEACH-WD40 domain-containing proteins. Loss of sel-2 activity leads to basolateral mislocalization and increased accumulation of LIN-12 in VPCs in which LET-23 is not active, and to impaired downregulation of basolateral LET-23 in VPCs in which LIN-12 is active. Downregulation of apical LIN-12 in the VPC in which LET-23 is active is not affected. In addition, in sel-2 mutants, the polarized cells of the intestinal epithelium display an aberrant accumulation of the lipophilic dye FM4-64 when the dye is presented to the basolateral surface. Our observations indicate that SEL-2/neurobeachin/LRBA is involved in endosomal traffic and may be involved in efficient delivery of cell surface proteins to the lysosome. Our results also suggest that sel-2 activity may contribute to the appropriate steady-state level of LIN-12 or to trafficking events that affect receptor activation.