Nanostring Technologies (United States)

The sense of smell has potent effects on appetite, but the underlying neural pathways remain undefined. Here we investigated how olfactory signals reach two subsets of appetite-linked neurons in the hypothalamic arcuate nucleus: AgRP (agouti-related peptide) neurons, which stimulate appetite, and POMC (pro-opiomelanocortin) neurons, which suppress it. Using polysynaptic viral tracing, we show that AgRP and POMC neurons receive indirect input from partially overlapping but distinct areas of the olfactory cortex, indicating that they process different sets of olfactory information. We also identify different complements of neurons directly upstream of AgRP and POMC neurons that can relay olfactory cortical signals to the appetite neurons. Single cell transcriptomics shows heterogeneous expression of neuromodulator receptors among AgRP neurons, suggesting variations in the signals they receive. Integrated viral tracing and RNA localization further reveals selected brain areas where upstream neurons express cognate receptor ligands. Together, these findings outline multiple pathways by which distinct olfactory and modulatory signals are differentially routed to neurons that promote versus inhibit appetite.

BackgroundChemokines play critical roles in the recruitment and activation of immune cells in both homeostatic and pathologic conditions. Here, we examined chemokine ligand-receptor pairs to better understand the immunopathogenesis of cutaneous lupus erythematosus (CLE), a complex autoimmune connective tissue disorder.ObjectivesOur objectives were to (1) characterize the cellular and proteomic constitution of interface dermatitis in CLE using blister biopsies, (2) map chemokine:ligand receptor pairs that govern recruitment of immune cells to form interface dermatitis in CLE, and (3) perform unbiased analyses in tandem on different clinical subtypes to identify novel genes and proteins underlying discoid versus subacute CLE.MethodsWe used suction blister biopsies to measure cellular infiltrates with spectral flow cytometry in the interface dermatitis reaction, as well as 184 protein analytes in interstitial skin fluid using 96-plex immunoassay targeted proteomics. Flow and 96-plex immunoassay data concordantly demonstrated significant increases in T cells and antigen presenting cells (APCs). We also performed spatial transcriptomics and spatial proteomics of punch biopsies using digital spatial profiling (DSP) technology on CLE skin and healthy margin controls to examine discreet locations within the tissue.ResultsSpatial and 96-plex immunoassay data confirmed elevation of interferon (IFN) and IFN-inducible CXCR3 chemokine ligands. Comparing involved versus uninvolved keratinocytes in CLE samples revealed upregulation of essential inflammatory response genes in areas near interface dermatitis, including AIM2. 96-plex immunoassay data confirmed upregulation of Caspase 8, IL-18 which is the final product of AIM2 activation, and induced chemokines including CCL8 and CXCL6 in CLE lesional samples. Chemotaxis assays using PBMCs from healthy and CLE donors revealed that T cells are equally poised to respond to CXCR3 ligands, whereas CD14+CD16+ APC populations are more sensitive to CXCL6 via CXCR1 and CD14+ are more sensitive to CCL8 via CCR2.ConclusionsTaken together, our data map a pathway from keratinocyte injury to lymphocyte recruitment in CLE via AIM2-Casp8-IL-18-CXCL6/CXCR1 and CCL8/CCR2, and IFNG/IFNL1-CXCL9/CXCL11-CXCR3, and identify potential novel biomarkers of disease.

Abstract Background: TOPACIO was a phase I/II study evaluating the PARP inhibitor (PARPi) niraparib in combination with the anti-PD-1 antibody pembrolizumab in patients with locally advanced or metastatic triple-negative breast cancer (TNBC, n=55), irrespective of BRCA status. In the efficacy-evaluable population (n=47) the objective response rate (ORR) was 21% and disease control rate (DCR) 49%. Although activity was greater in BRCA-MUT patients (7/15, ORR=47% and 12/15, DCR=80%), durable clinical benefit was seen in patients with BRCA-WT tumors (3/27, ORR=11% and 9/27, DCR=33%). Patients with PD-L1+ tumors (28/47, 60%) achieved higher ORR (9/28, 32%) than those with PD-L1neg tumors (1/13, 8%). It remains unstudied whether tumor gene expression or immune composition in baseline biospecimens is predictive of treatment response. We conducted exploratory biomarker analyses to uncover gene expression patterns and immune states associated with treatment response. Methods: Transcriptional profiling of baseline samples was performed using the BC360 (n=41) and PanCancer IO360 (n=42) panels (Nanostring) and multigene signatures were used to measure tumor and immune activities. Transcriptional analysis was paired with high-dimensional, single-cell cyclic immunofluorescence (CyCIF) of samples with adequate tissue for analysis (n=22) to characterize the immune microenvironment at single-cell resolution. Results: BRCA-MUT tumors showed increased downstream interferon signaling and immune infiltration relative to BRCA-WT tumors (p < 0.05). Downstream interferon and immunoproteasome scores were elevated in objective responders (p < 0.05). Genes involved in WNT signaling (TANKS1, TANKS2, PARP4, and NETO2) associated with long-term response, defined by those still on therapy and responding at data cut off. Low NETO2 gene expression strongly associated with better ORR (p = 0.01). CyCIF analysis performed on whole tissue sections accounting for 2.97x106 single cells revealed that in BRCA-WT patients, baseline infiltration of immune cells - cells expressing CD45, CD3 (T cells), CD20 (B cells) or CD68/CD163 (macrophages) positively correlated with favorable PFS (R=0.81, p=0.0004, Spearman’s correlation). Further, increasing fractions of CD8+ and PD-1+ CD4+ T cells strongly associated with favorable PFS (R > 0.71, p < 0.0041). In BRCA-MUT patients, baseline immune composition did not correlate with clinical outcome. Conclusions: NETO2 expression, WNT pathway, and interferon signaling associate with response to niraparib plus pembrolizumab. While BRCA-MUT tumors showed higher baseline immune cell abundance compared to BRCA-WT, immune and T cell infiltration was predictive of PFS duration only in BRCA-WT patients, suggesting divergent mechanisms of response to PARPi and ICB dependent on BRCA status. Citation Format: Alexander P. Gottlieb, Gregory J. Baker, Jia-Ren Lin, Ricardo Pastorello, Yu-An Chen, Tuulia Vallius, Janae Davis, Clarence Yapp, Sarah E. Church, Eric Miller, Anniina Farkkila, Shaveta Vinayak, Melinda L. Telli, Sara M. Tolaney, Filipa Lynce, Joan S. Brugge, Alan D'Andrea, Geoffrey Shapiro, Sandro Santagata, Peter K. Sorger, Elizabeth A. Mittendorf, Jennifer L. Guerriero. High-dimensional, single-cell analysis and transcriptional profiling reveal novel correlatives of response to PARP inhibition plus PD-1 blockade in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7152.

BackgroundLatency remains a major obstacle to finding a cure for HIV despite the availability of antiretroviral therapy. Due to virus dormancy, limited biomarkers are available to identify latent HIV-infected cells. Profiling of individual HIV-infected cells is needed to explore potential latency biomarkers and to study the mechanisms of persistence that maintain the HIV reservoir.MethodsSingle cell spatial transcriptomic characterization using the CosMx Spatial Molecular Imager platform was conducted to analyze HIV-infected cells in formalin-fixed paraffin-embedded sections of splenic tissue surgically obtained from an HIV-infected humanized mouse model. Regulation of over a thousand human genes was quantified in both viremic and aviremic specimens. In addition, in situ hybridization and immunohistochemistry were performed in parallel to identify HIV viral RNA- and p24-containing cells, respectively. Finally, initial findings from CosMx gene profiling were confirmed by isolating RNA from CD4 + T cells obtained from a person living with HIV on antiretroviral therapy following either PMA/Ionomycin or DMSO treatment. RNA was quantified using qPCR for a panel of targeted human host genes.ResultsSupervised cell typing revealed that most of the HIV-infected cells in the mouse spleen sections were differentiated CD4 + T cells. A significantly higher number of infected cells, 2781 (1.61%) in comparison to 112 (0.06%), and total HIV transcripts per infected cell were observed in viremic samples compared to aviremic samples, respectively, which was consistent with the data obtained from ISH and IHC. Notably, the expression of 55 genes was different in infected cells within tissue from aviremic animals compared to viremic. In particular, both spleen tyrosine kinase (SYK) and CXCL17, were expressed approximately 100-fold higher. This data was further evaluated against bulk RNA isolated from HIV-infected human primary CD4 + T cells. A nearly 6-fold higher expression of SYK mRNA was observed in DMSO-treated CD4 + T cells compared to those stimulated with PMA/Ionomycin.ConclusionThis study found that the CosMx SMI platform is valuable for assessing HIV infection and providing insights into host biomarkers associated with HIV reservoirs. Higher relative expression of the SYK gene in aviremic-infected cells from the humanized mouse HIV model was consistent with levels found in CD4 + T cells of aviremic donors.

ABSTRACT The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard ‘omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell–cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2, highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22—which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis3–6—we identify that the causal gene, ETS2, is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures7, we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.

Single-cell technologies are revolutionizing the entire field of biology. The large volumes of data generated by single-cell technologies are high dimensional, sparse, and heterogeneous and have complicated dependency structures, making analyses using conventional machine learning approaches challenging and impractical. In tackling these challenges, deep learning often demonstrates superior performance compared to traditional machine learning methods. In this work, we give a comprehensive survey on deep learning in single-cell analysis. We first introduce background on single-cell technologies and their development, as well as fundamental concepts of deep learning including the most popular deep architectures. We present an overview of the single-cell analytic pipeline pursued in research applications while noting divergences due to data sources or specific applications. We then review seven popular tasks spanning different stages of the single-cell analysis pipeline, including multimodal integration, imputation, clustering, spatial domain identification, cell-type deconvolution, cell segmentation, and cell-type annotation. Under each task, we describe the most recent developments in classical and deep learning methods and discuss their advantages and disadvantages. Deep learning tools and benchmark datasets are also summarized for each task. Finally, we discuss the future directions and the most recent challenges. This survey will serve as a reference for biologists and computer scientists, encouraging collaborations.

Abstract Residual cancer burden (RCB) based on pathologic characteristics is the most powerful prognostic factor in breast cancer (BC) which received neoadjuvant chemotherapy (NAC) followed by surgery. According to RCB classification, class III predicted short survival duration regardless of BC subtypes according to hormone receptor (HR) and human epidermal growth factor receptor-2 (HER-2) state. However, up to 20-40% of BCs with RCB class III did not experience BC recurrence and had long term survival without disease recurrence. In our study, we evaluated genomic characteristics of BC which had high RCB class. We collected 96 fresh frozen BC specimens which had undergone surgery after NAC between 2010 and 2018 from Samsung Medical Center Biobank. We performed whole genome or exome sequencing, RNA sequencing and high-plex single-cell spatial transcriptomics. Of 96 BCs, 65 BCs had experienced BC recurrence and 31 BCs have not been BC recurrence. Of 65 BCs with dismal prognosis, 12 were HR+HER2-, four in HR+HER2+, 39 in triple negative breast cancer (TNBC) and 10 in HR-HER2+ BC. Of 31 BCs without recurrence, 11 were HR+HER2-, two in HR+HER2+, 14 in TNBC and four in HR-HER2+ BC. In HR+HER2- BC, ten of 12 BCs with dismal prognosis were categorized into basal like intrinsic subtype and two were into luminal B subtype compared that six of luminal A and five of luminal B subtype categorization in good prognosis BC group. Age associated mutation signature were enriched in HR+HER2- BC with good prognosis (p=0.027). Tumor microenvironment (TME) analysis using Kassandra suggested that high monocytes were associated with BC with dismal prognosis (p=0.00031). In single-cell spatial transcriptome analysis, T-cell abundance in the tumoral niche is associated with dismal prognosis in HR+HER2- BC (p=0.039). In TNBC, almost BCs (88.7%) were categorized into basal-like intrinsic subtype regardless of their prognosis. TME analysis presented that immune cells including macrophages and lymphocytes with CD4 and CD8 T cells were significantly enriched in TNBC with good prognosis (ps <0.05, respectively). In HER2+ BC, intrinsic subtypes were heterogeneous in both groups. Focal amplification in HER2+BC patient harbored DNA segments from different chromosomes more frequently than in those with good prognosis (p=0.00091), which was prominent in oncogenic extrachromosomal DNA amplifications compared to other oncogenic amplifications. In TME analysis, there were no specific cell enrichments according to BC prognosis but sing-cell spatial transcriptome analysis revealed that higher T-cell abundance in the tumoral niche was associated with HR+HER2+ BC with good prognosis (p=0.047). In conclusion, each BC subtype had their own genomic characteristics to determine their prognosis. Our study also suggested that TME characteristics was common prognostic factor for survival outcome of BC with residual tumor after NAC. Citation Format: Ji-Yeon Kim, Sabin Park, Sepil Ahn, Eun Seop Seo, Soyeon Kim, Mark Gregory, Emily Killingbeck, Eun Yoon Cho, Jeong Eon Lee, Jin Seok Ahn, Yeon Hee Park, Woong-Yang Park, Hoon Kim, Semin Lee, Young-Hyuck Im. Prognostication of genomic characteristics of residual breast cancer after neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7644.

The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify M1 macrophages to have elevated expression of IFI27 in areas of infection.

The emergence and international dissemination of multi-drug resistant Staphylococcus aureus (S. aureus) strains challenge current antibiotic-based therapies, representing an urgent threat to public health worldwide. In the U.S. alone, S. aureus infections are responsible for 11,000 deaths and 500,000 hospitalizations annually. Biofilm formation is a major contributor to antibiotic tolerance and resistance-induced delays in empirical therapy with increased infection severity, frequency, treatment failure, and mortality. Developing novel treatment strategies to prevent and disrupt biofilm formation is imperative. In this article, we test the Secretion Modification Region (SMR) peptides for inhibitory effects on resistant S. aureus biofilm-forming capacity by targeting the molecular chaperone DnaK. The dose effect of SMR peptides on biofilm formation was assessed using microtiter plate methods and confocal microscopy. Interaction between the antagonist and DnaK was determined by immune precipitation with anti-Flag M2 Affinity and Western blot analysis. Increasing SMR peptide concentrations exhibited increasing blockade of S. aureus biofilm formation with significant inhibition found at 18 µM, 36 µM, and 72 µM. This work supports the potential therapeutic benefit of SMR peptides in reducing biofilm viability and could improve the susceptibility to antimicrobial agents.IMPORTANCEThe development of anti-biofilm agents is critical to restoring bacterial sensitivity, directly combating the evolution of resistance, and overall reducing the clinical burden related to pervasive biofilm-mediated infections. Thus, in this study, the SMR peptide, a novel small molecule derived from the HIV Nef protein, was preliminarily explored for anti-biofilm properties. The SMR peptide was shown to effectively target the molecular chaperone DnaK and inhibit biofilm formation in a dose-dependent manner. These results support further investigation into the mechanism of SMR peptide-mediated biofilm formation and inhibition to benefit rational drug design and the identification of therapeutic targets.