Single-cell Expression Research Articles

Single-cell expression and immune infiltration analysis of polyamine metabolism in breast cancer.

Breast cancer is one of the most threatening women health diseases worldwide and its molecular heterogeneity offers a range of response to therapy. The role of polyamine metabolism is receiving increasing attention. Polyamine metabolism not only plays an important role in the occurrence and development of breast cancer, but also interacts with tumor immune microenvironment. In this work, we applied single-cell RNA-sequencing (scRNA-seq) and systems immunological approaches to interrogate immune cell infiltration gene-to-gene co-expressions in the bulk tumor transcriptomes of breast cancer. We acquired breast cancer sample data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), evaluated the infiltration status of 22 immune cell types using CIBERSORTx tool, respectively. By leveraging the Retrospective Breast sample of various technologies including gene expression and methylation, we identified 46 breast cancer proliferation-associated co-expression modules using weighted gene coexpression network analysis (WGCNA) approach along with machine learning models which in turn delineated single cell level expressions features that these selected module possessed. We observed substantial cellular heterogeneity in the breast cancer microenvironment, where lineage-specific gene expression patterns were highly associated with tumor progression. Moreover, we also identified the gene modules correlated with immune cell infiltration level that could function as regulators in response to tumors for immune therapy. Moreover, risk scores were correlated with immune cell function in different patient groups defined by high- and low-risk. The findings of this study shed a new light upon molecular classification prognostic assessment and personalized treatment in breast cancer.

TMIC-13. INTEGRATING SNRNASEQ AND SPATIAL TRANSCRIPTOME (ST) SHOWS DIVERSE TRANSCRIPTOMIC LANDSCAPE FOR TUMOR MICROENVIRONMENT (TME) IN INTRACRANIAL GERMINOMAS

Abstract The incidence of intracranial germ cell tumors is 5-8 times higher in East Asia and histologically, germinoma is well known to show intense lymphocytic infiltrates. In spite of germinoma’s well known immune infiltration, there have only been a few studies on its tumor micro-environment (TME). There has been no study using the recent and comprehensive techniques of single nucleus sequencing or spatial transcriptomics to study its TME. In this study, we studied snRNAseq (Chromium 10X) of FFPE tissues of 24 intracranial germinomas, and spatial transcriptomes (STs) (Visium Spatial) from fresh tissues from ten matched cases. For the TME, in contrast to common belief, macrophages and fibroblasts were equally represented as T- and NK-cells as immune cells. Clinical stage correlated with a lesser proportion of fibroblasts and T- and NK-cells. There was no correlation with proportion of tumor cells with either focal vs bifocal disease or clinical stage. Common gene modules (non-negative matrix factorization) were epithelial-mesenchymal transition (complete and partial), cell cycle and immune cells. Cell interaction analysis showed strong interaction between germ cells and macrophages involving CXCL, MIF and MK pathways. By ligand-receptor analysis, MIF combined with CD74 might promote tumor development. For ten cases, we studied STs with fresh tissues and integrated the results with snRNSeq, deconvoluting the spots for ST using snRNAseq cell types as reference (SPOTight) and achieved integrated single cell expression atlases of the STs (Seurat package). STs revealed a similar CNV plot pattern as those derived from snRNAseqs. Multimodal Intersection Analysis integrated significant genes based on snRNAseq and different regions’ significant genes based on STs. There was correlation between the expression of the four gene modules for tumor and immune cells for cell neighborhood. In conclusion, we showed in details the heterogenous expression landscape of TME of germinomas.

Infrared laser–induced gene expression in single cells characterized by quantitative imaging in Physcomitrium patens

A spatiotemporal understanding of gene function requires the precise control of gene expression in each cell. Here, we use an infrared laser–evoked gene operator (IR-LEGO) system to induce gene expression at the single-cell level in the moss Physcomitrium patens by heating a living cell with an IR laser and thereby activating the heat shock response. We identify the laser irradiation conditions that provide higher inducibility with lower invasiveness by changing the laser power and irradiation duration. Furthermore, we quantitatively characterize the induction profile of the heat shock response using a heat-induced fluorescence reporter system after the IR laser irradiation of single cells under different conditions. Our data indicate that IR laser irradiation with long duration leads to higher inducibility according to increase in the laser power but not vice versa, and that the higher laser power even without conferring apparent damage to the cells decelerates and/or delayed gene induction. We define the temporal shift in expression as a function of onset and duration according to laser power and irradiation duration. This study contributes to the versatile application of IR-LEGO in plants and improves our understanding of heat shock-induced gene expression.

A multi-modal single-cell and spatial expression map of metastatic breast cancer biopsies across clinicopathological features.

Although metastatic disease is the leading cause of cancer-related deaths, its tumor microenvironment remains poorly characterized due to technical and biospecimen limitations. In this study, we assembled a multi-modal spatial and cellular map of 67 tumor biopsies from 60 patients with metastatic breast cancer across diverse clinicopathological features and nine anatomic sites with detailed clinical annotations. We combined single-cell or single-nucleus RNA sequencing for all biopsies with a panel of four spatial expression assays (Slide-seq, MERFISH, ExSeq and CODEX) and H&E staining of consecutive serial sections from up to 15 of these biopsies. We leveraged the coupled measurements to provide reference points for the utility and integration of different experimental techniques and used them to assess variability in cell type composition and expression as well as emerging spatial expression characteristics across clinicopathological and methodological diversity. Finally, we assessed spatial expression and co-localization features of macrophage populations, characterized three distinct spatial phenotypes of epithelial-to-mesenchymal transition and identified expression programs associated with local T cell infiltration versus exclusion, showcasing the potential of clinically relevant discovery in such maps.

New insight into the development of synpolydactyly caused by expansion of HOXD13 polyalanine based on weighted gene co-expression network analysis

BackgroundSynpolydactyly (SPD) is mainly caused by mutations of polyalanine expansion (PAE) in the transcription factor gene HOXD13 and the involved cell types and signal pathway are still not clear possible pathways and single-cell expression characteristics of limb bud in HOXD13 PAE mice was analyzed in this study.MethodWe investigated a previous study of a mouse model with SPD and conducted weighted gene co-expression network analysis (WGCNA) using a single-cell RNA sequencing dataset from limb bud cells of SPD mouse model of HOXD13 + 7A heterozygote.ResultsAnalysis of WGCNA revealed that synpolydactyly-associated Hoxd13 PAEs alter the immune response and osteoclast differentiation, and enhance DNA replication. Bmp4, Hand2, Hoxd12, Lnp, Prrx1, Gmnn, and Cdc6 were found to play potentially key roles in synpolydactyly.ConclusionsThese findings evaluated the main genes related to SPD with PAE mutations in HOXD13 and advance our understanding of human limb development.

Genetic inference and single cell expression analysis of potential targets in heart failure and breast cancer

BackgroundBreast cancer and heart failure are major public health issues globally, characterized by significant genetic heterogeneity and complex molecular mechanisms. This study aims to explore potential genetic targets in heart failure and breast cancer through combining genetic inference and single-cell expression analysis, and to assess the causal relationships of these targets using Mendelian randomization methods.MethodsWe first identified genetic variants associated with heart failure and breast cancer using genome-wide association study (GWAS) data. Subsequently, we analyzed the expression patterns of these genetic variants in different cell types through single-cell RNA sequencing technology. Furthermore, we utilized in vitro experiment to assess the effects of ITM2B on MCF7 using immunofluorescence.ResultsOur study identified multiple genetic variants associated with heart failure and breast cancer, showing specific expression patterns in heart and breast cells. The ITM2B gene is highly expressed in breast cancer. ITM2B shows the highest expression in T cells and the lowest expression in proliferating cells. Silencing the ITM2B gene can promote apoptosis and inhibit proliferation and migration of MCF7 breast cancer cells.ConclusionBy integrating genetic inference and single-cell expression analysis, this study revealed potential genetic targets in heart failure and breast cancer, and validated the causal effects of these targets using Mendelian randomization methods.

CancerSCEM 2.0: an updated data resource of single-cell expression map across various human cancers.

The field of single-cell RNA sequencing (scRNA-seq) has advanced rapidly in the past decade, generating significant amounts of valuable data for researchers to study complex tumor profiles. This data is crucial for gaining innovative insights into cancer biology. CancerSCEM (https://ngdc.cncb.ac.cn/cancerscem) is a public resource that integrates, analyzesand visualizes scRNA-seq data related to cancer, and it provides invaluable support to numerous cancer-related studies. With CancerSCEM 2.0, scRNA-seq data have increased from 208 to 1466 datasets, covering tumor, matching-normaland peripheral blood samples across 127 research projects and 74 cancer types. The new version of this resource enhances transcriptome analysis by adding copy number variation evaluation, transcription factor enrichment, pseudotime trajectory construction, and diverse biological feature scoring. It also introduces a new cancer metabolic map at the single-cell level, providing an intuitive understanding of metabolic regulation across different cancer types. CancerSCEM 2.0 has a more interactive analysis platform, including four modules and 14 analytical functions, allowing researchers to perform cancer scRNA-seq data analyses in various dimensions. These enhancements are expected to expand the usability of CancerSCEM 2.0 to a broader range of cancer research and clinical applications, potentially revolutionizing our understanding of cancer mechanisms and treatments.

The mechanism underlying B-cell developmental dysfunction in Kawasaki disease based on single-cell transcriptomic sequencing.

Kawasaki disease (KD) is an acute systemic vasculitis that can lead to acquired heart disease in children mostly from in developed countries. The previous research showed that B cells in KD patients underwent a profound change in both the cell numbers and types after intravenous immunoglobulin (IVIG) therapy. We performed the single-cell RNA-sequencing for the peripheral blood mononuclear cells (PBMCs) from three febrile patients and three KD patients to investigate the possible mechanism underlying B cell developmental dysfunction in KD. The pseudo-time analysis was employed to study the developmental trajectories of the PBMCs in febrile control and KD patients. Overall single-cell expression profiles show that the biological processes of immunity, B cell activation pathway and their related biological entities are repressed in KD patients before IVIG treatment compared to febrile patient and KD patients after IVIG treatment. The differentially expressed gene analyses further demonstrate that B cell signaling pathway is downregulated in B cells and plasma blast cells of KD patients before treatment while cell cycle genes and MYC gene are upregulated in dendritic cells (DCs) and hematopoietic stem and progenitor cells (HSPCs) of KD patients before treatment. The biological process of immune response is upregulated in the HSPCs of KD patients before treatment in our dataset while the biological process of inflammatory response is upregulated in the HSPCs of KD patients before treatment in GSE168732 dataset. Single-cell trajectory analyses demonstrate that KD patients before treatment have a shortened developmental path in which B cells and T cells are failed to differentiate into separate lineages. HSPD1 and HSPE1 genes show an elevated expression level in the early cell development stage of KD patients before treatment accompanied with the repression of MYC, SPI1, MT2A and UBE2C genes. Our analyses of all B cells from KD patients before treatment show most of B cells are arrested in a transitional state with an ill developmental path compared with febrile patients and KD patients after treatment. Our results indicate that the immune premature HSPCs accompanied with the abnormal expression dynamics of cell cycle and SPI1 genes are the mechanism underlying B cell developmental dysfunction in KD patients.

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex In Situ Tagging for Single-Cell Proteomic Studies.

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

ScTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies.

Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-type heterogeneity in traditional TWAS results. As the field of scTWAS rapidly advances, there is a growing need for additional database platforms to integrate this wealth of data and knowledge effectively. To address this gap, we present scTWAS Atlas (https://ngdc.cncb.ac.cn/sctwas/), a comprehensive database of scTWAS information integrating literature curation and data analysis. The current version of scTWAS Atlas amasses 2,765,211 associations encompassing 34 traits, 30 cell types, 9 cell conditions and 16,470 genes. The database features visualization tools, including an interactive knowledge graph that integrates single-cell expression quantitative trait loci (sc-eQTL) and scTWAS associations to build a multi-omics level regulatory network at the cellular level. Additionally, scTWAS Atlas facilitates cross-cell-type analysis, highlighting cell-type-specific and shared TWAS genes. The database is designed with user-friendly interfaces and allows for easy browsing, searching, and downloading of relevant information. Overall, scTWAS Atlas is instrumental in exploring the genetic regulatory mechanisms at the cellular level and shedding light on the role of various cell types in biological processes, offering novel insights for human health research.

Single-cell stimulus-response gene expression trajectories reveal the stimulus specificities of dynamic responses by single macrophages

Macrophages induce the expression of hundreds of genes in response to immune threats. However, current technology limits our ability to capture single-cell inducible gene expression dynamics. Here, we generated high-resolution time series single-cell RNA sequencing (scRNA-seq) data from mouse macrophages responding to six stimuli, and imputed ensembles of real-time single-cell gene expression trajectories (scGETs). We found that dynamic information contained in scGETs substantially contributes to macrophage stimulus-response specificity (SRS). Dynamic information also identified correlations between immune response genes, indicating biological coordination. Furthermore, we showed that the microenvironmental context of polarizing cytokines profoundly affects scGETs, such that measuring response dynamics offered clearer discrimination of the polarization state of individual macrophage cells than single time-point measurements. Our findings highlight the important contribution of dynamic information contained in the single-cell expression responses of immune genes in characterizing the SRS and functional states of macrophages.

Chromatin interaction maps of human arterioles reveal new mechanisms for the genetic regulation of blood pressure.

Arterioles are small blood vessels located just upstream of capillaries in nearly all tissues. The constriction and dilation of arterioles regulate tissue perfusion and are primary determinants of systemic blood pressure (BP). Abnormalities in arterioles are central to the development of major diseases such as hypertension, stroke, and microvascular complications of diabetes. Despite the broad and essential role of arterioles in physiology and disease, current knowledge of the functional genomics of arterioles is largely absent, partly because it is challenging to obtain and analyze human arteriole samples. Here, we report extensive maps of chromatin interactions, single-cell expression, and other molecular features in human arterioles and uncover new mechanisms linking human genetic variants to gene expression in vascular cells and the development of hypertension. Compared to large arteries, arterioles exhibited a higher proportion of pericytes which were strongly associated with BP traits. BP-associated single nucleotide polymorphisms (SNPs) were enriched in chromatin interaction regions in arterioles, particularly through enhancer SNP-promoter interactions, which were further linked to gene expression specificity across tissue components and cell types. Using genomic editing in animal models and human induced pluripotent stem cells, we discovered novel mechanisms linking BP-associated noncoding SNP rs1882961 to gene expression through long-range chromatin contacts and revealed remarkable effects of a 4-bp noncoding genomic segment on hypertension in vivo. We anticipate that our rich data and findings will advance the study of the numerous diseases involving arterioles. Moreover, our approach of integrating chromatin interaction mapping in trait-relevant tissues with SNP analysis and in vivo and in vitro genome editing can be applied broadly to bridge the critical gap between genetic discoveries and physiological understanding.

Farm-dust mediated protection of childhood asthma: Mass cytometry reveals novel cellular regulation.

Farm-dust mediated asthma protection in childhood was replicated in numerous epidemiological studies. Central immune mechanisms are not fully understood. This exploratory study aimed to disentangle underlying immunological regulation of farm-dust mediated protection in peripheral blood on a single-cell level. Single-cell protein expression of invitro farm-dust stimulated and unstimulated cells from allergic asthmatics and healthy controls were measured using mass cytometry. Analysis of innate and adaptive cellular proportions (linear regression) and T-cell proliferation was performed. Functional marker intensity was investigated using Earth Mover's Distance and the Monte Carlo permutation test. Farm-dust stimulation induced cell type-specific regulation: Key-features of farm-dust stimulation comprised opposing regulation of immune-cell frequencies (downregulated innate cell populations (monocytes/DCs (p < .001), NK-cells (p < .05)) and upregulated adaptive populations (B-cells, CD4+ T-cells (both p < .05)), reduced CD4+ CD25- T-cell proliferation, and differential cell type-specific functional marker expression. Following stimulation, functional marker analysis revealed induced activation (CD25) in T-cells and NK-T-cells in both phenotypes even after correction for multiple testing. Cytotoxicity (GZMB) and inflammation (pERK1/2, pp38) related markers were reduced in T-cells exclusively in asthmatic children. Asthma-associated markers (Gata3, RORγ, and HLA-DR) were reduced in T- and innate- cell populations of asthmatics following stimulation. B-cells displayed a phenotypically independent increase of diverse functional markers upon farm-dust stimulation. This study mimicking invivo environmental exposure identified a novel profile of immune-regulatory markers using mass cytometry demonstrating decreased asthma-associated markers following farm-dust stimulation. These findings may be key for further studies on asthma prevention in childhood.

Tunable, self-contained gene dosage control via proteolytic cleavage of CRISPR-Cas systems.

Gene therapy holds great therapeutic potential. Yet, controlling cargo expression in single cells is limited due to the variability of delivery methods. We implement an incoherent feedforward loop based on proteolytic cleavage of CRISPR-Cas activation or inhibition systems to reduce gene expression variability against the variability of vector delivery. We demonstrate dosage control for activation and inhibition, post-delivery tuning, and RNA-based delivery, for a genome-integrated marker. We then target the RAI1 gene, the haploinsufficiency and triplosensitivity of which cause two autism-related syndromes, Smith-Magenis-Syndrome (SMS) and Potocki-Lupski-Syndrome, respectively. We demonstrate dosage control for RAI1 activation in HEK293s, Neuro-2As, and mouse cortical neurons via AAVs and lentiviruses. Finally, we activate the intact RAI1 copy in SMS patient-derived cells to an estimated two-copy healthy range, avoiding the harmful three-copy regime. Our circuit paves the way for viable therapy in dosage-sensitive disorders, creating precise and tunable gene regulation systems for basic and translational research.

Glucotoxicity suppresses function of pancreatic beta and duct cells via miR-335-targeted Runx2 and insulin-mediated mechanism.

Pancreatic cell dynamics have important contributions to the development of type 2 diabetes and related diseases such as nonalcoholic fatty pancreas disease. The aim of this study was to investigate the effects of prolonged excessive glucose exposure on the functions of pancreatic beta cells and duct cells in single and co-culture conditions. In this study, we focused on the effects of glucotoxicity on insulin secretion which is the main function of beta cells and on progenitor functions of duct cells. Rat primary INS1 beta cells and ARIP duct cells were exposed to glucose (25mM) for 72h under single or indirect co-culture conditions. Glucotoxicity stimuli increased insulin secretion and decreased insulin expression in single beta cells while stimulating beta-cell differentiation and adipogenesis in single duct cells. On the other hand, glucotoxicity caused functional loss and increased proliferation and apoptosis in beta cells while increasing proliferation but suppressed beta-cell differentiation and adipogenesis in duct cells under co-culture conditions. The expression level of miR-335, a microRNA known to be upregulated by leptin and target Runx2, was measured. As a result, unlike single-cell culture, glucotoxicity upregulated miR-335, downregulated Runx2, and decreased insulin signaling in beta cells while downregulating miR-335 and upregulating Runx2, and decreased insulin signaling in duct cells under co-culture conditions. When the results of single and co-culture experiments are compared, insulin and miR-335 may be seen as important mediators for setting up the relation between beta and duct cells. Our findings are important for preventing the development of type 2 diabetes and nonalcoholic fatty pancreas disease, even developing new diagnosis and treatment strategies.

Polybacterial Intracellular Macromolecules Shape Single-Cell Epikine Profiles in Upper Airway Mucosa.

The upper airway, particularly the nasal and oral mucosal epithelium, serves as a primary barrier for microbial interactions throughout life. Specialized niches like the anterior nares and the tooth are especially susceptible to dysbiosis and chronic inflammatory diseases. To investigate host-microbial interactions in mucosal epithelial cell types, we reanalyzed our single-cell RNA sequencing atlas of human oral mucosa, identifying polybacterial signatures (20% Gram-positive, 80% Gram-negative) within both epithelial- and stromal-resident cells. This analysis revealed unique responses of bacterial-associated epithelia when compared to two inflammatory disease states of mucosa. Single-cell RNA sequencing, in situ hybridization, and immunohistochemistry detected numerous persistent macromolecules from Gram-positive and Gram-negative bacteria within human oral keratinocytes (HOKs), including bacterial rRNA, mRNA and glycolipids. Epithelial cells with higher concentrations of 16S rRNA and glycolipids exhibited enhanced receptor-ligand signaling in vivo. HOKs with a spectrum of polybacterial intracellular macromolecular (PIM) concentrations were challenged with purified exogenous lipopolysaccharide, resulting in the synergistic upregulation of select innate (CXCL8, TNFSF15) and adaptive (CXCL17, CCL28) epikines. Notably, endogenous lipoteichoic acid, rather than lipopolysaccharide, directly correlated with epikine expression in vitro and in vivo. Application of the Drug2Cell algorithm to health and inflammatory disease data suggested altered drug efficacy predictions based on PIM detection. Our findings demonstrate that PIMs persist within mucosal epithelial cells at variable concentrations, linearly driving single-cell effector cytokine expression and influencing drug responses, underscoring the importance of understanding host-microbe interactions and the implications of PIMs on cell behavior in health and disease at single-cell resolution.

Single-cell expression profiling has its roots in in situ techniques.

Single-cell expression profiling has its roots in in situ techniques.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction.

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1 , which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

Single-cell multiplex immunocytochemistry in cell block preparations of metastatic breast cancer confirms sensitivity of GATA-binding protein 3 over gross cystic disease fluid protein 15 and mammaglobin.

Metastatic breast cancers are frequently encountered in cytology and require immunocytochemistry (ICC). In this study, traditional and multiplex ICC (mICC) for GATA-binding protein 3 (GATA3), gross cystic disease fluid protein 15 (GCDFP15), and mammaglobin (MMG) were performed with the aim of validating mICC in cell blocks, with further single-cell expression pattern analysis to identify the single markers and combinations of markers most sensitive in subtypes of breast cancer. GATA3, GCDFP15, and MMG were paired with OptiView 3,3'-diaminobenzidine and Ventana DISCOVERY Purple and Blue, respectively, with cyclical and serial staining. Bright-field imaging was performed with the Mantra 2 system and analyzed with the inForm Tissue Finder (Akoya Biosciences). Cell detection and phenotyping were further confirmed by two pathologists. In the 36 cases studied, traditional ICC and mICC demonstrated good concordance (kappa coefficient, >0.5; p<.01) at three cutoffs (1%, 5%, and 50%), except for GATA3 at the 1% cutoff. Single-marker positivity outnumbered double-marker positivity and the exceedingly rare triple-marker positivity (<3%). GATA3 was the leading single marker-positive phenotype in all breast cancer subtypes, except for MMG in estrogen receptor-positive, progesterone receptor-positive, and human epidermal growth factor receptor 2-positive (ER+/PR+/HER2+) breast cancers. Limited to two markers, GATA3/MMG included the greatest number of tumor cells for luminal breast cancers (ER+/PR+/HER2+, 60.6%; ER+/PR+/HER2+, 31.4%), whereas HER2-overexpressed breast cancers (27.4%) and triple-negative breast cancers (26.4%) favored the combination of GATA3/GCDFP15. For a single marker, GATA3 displayed the highest sensitivity. The addition of MMG for hormone receptor-positive breast cancers and GCDFP15 for hormone receptor-negative breast cancers further increased sensitivity. The low proportion of multimarker-positive cells suggested that the coexpression observed with traditional ICC is attributable to intratumoral heterogeneity, not genuine coexpression.

HER4 is a high-affinity dimerization partner for all EGFR/HER/ErbB family proteins.

Human epidermal growth factor receptors (HER)-also known as EGFR or ErbB receptors-are a subfamily of receptor tyrosine kinases (RTKs) that play crucial roles in cell growth, division, and differentiation. HER4 (ErbB4) is the least studied member of this family, partly because its expression is lower in later stages of development. Recent work has suggested that HER4 can play a role in metastasis by regulating cell migration and invasiveness; however, unlike EGFR and HER2, the precise role that HER4 plays in tumorigenesis is still unresolved. Early work on HER family proteins suggested that there are direct interactions between the four members, but to date, there has been no single study of all four receptors in the same cell line with the same biophysical method. Here, we quantitatively measure the degree of association between HER4 and the other HER family proteins in live cells with a time-resolved fluorescence technique called pulsed interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). PIE-FCCS is sensitive to the oligomerization state of membrane proteins in live cells, while simultaneously measuring single-cell protein expression levels and diffusion coefficients. Our PIE-FCCS results demonstrate that HER4 interacts directly with all HER family members in the cell plasma membrane. The interaction between HER4 and other HER family members intensified in the presence of a HER4-specific ligand. Our work suggests that HER4 is a preferred dimerization partner for all HER family proteins, even in the absence of ligands.