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Results for “multiplexed proteomics”

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PubMed2026

Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays.

Humans↗

PubMed2025

SynchroSep-MS: Parallel LC Separations for Multiplexed Proteomics.

Achieving high throughput remains a challenge in MS-based proteomics for large-scale applications. We introduce SynchroSep-MS, a novel method for parallelized, label-free proteome analysis that leverages the rapid acquisition speed of modern mass spectrometers. This approach employs multiple liquid chromatography columns, each with an independent sample, simultaneously introduced into a single mass spectrometer inlet. A precisely controlled retention time offset between sample injections creates distinct elution profiles, facilitating unambiguous analyte assignment. We modified the DIA-NN workflow to effectively process these unique parallelized data, accounting for retention time offsets. Using a dual-column setup with mouse brain peptides, SynchroSep-MS detected approximately 16,700 unique protein groups, nearly doubling the peptide information obtained from a conventional single proteome analysis. The method demonstrated excellent precision and reproducibility (median protein %RSDs less than 4%) and high quantitative linearity (median R2 greater than 0.96) with minimal matrix interference. SynchroSep-MS represents a new paradigm for data collection and the first example of label-free multiplexed proteome analysis via parallel LC separations, offering a direct strategy to accelerate throughput for demanding applications such as large-scale clinical cohorts and single-cell analyses without compromising peak capacity or causing ionization suppression.

Proteomics↗

PubMed2026

Benchmarking the OptiSpray-μPAC Workflow against a Traditional Nanospray Capillary Interface for Multiplexed Quantitative Proteomics.

Nanoflow liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) underpins modern quantitative proteomics, yet the column-to-mass spectrometer interface remains an important yet often underappreciated determinant of analytical depth, sensitivity, and reproducibility. Here, we benchmark an integrated workflow comprising the newly developed OptiSpray ion source and a micropillar array column (μPAC) cartridge against a conventional Nanospray Flex Source with an Accucore resin-packed capillary column. We performed a TMTpro 18-plex experiment across nine human cell lines on a FAIMS Pro-equipped Orbitrap Exploris 480. Following basic-pH reversed-phase fractionation, 12 fractions were analyzed on both workflow configurations under matched chromatographic gradient and acquisition conditions. Across both configurations, we quantified >9000 protein groups with highly comparable quantitative reproducibility and principal component clustering. Direct comparison of protein abundance ratios across cell lines showed agreement (Pearson R2 ≈ 0.7-0.8) without systematic bias. These results were achieved without workflow-specific optimization of the OptiSpray-μPAC platform, enabling direct transfer of established acquisition methods. Despite differences in column architecture, both configurations delivered comparable proteome coverage and quantitative fidelity. These findings establish the OptiSpray-μPAC workflow as a standardized alternative to conventional capillary-based interfaces, offering simplified operation while preserving quantitative performance.

Humans↗

PubMed2025

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗

PubMed2026

Single-section multiplex spatial proteomics of immune microenvironments in kidney transplantation.

Characterizing kidney disease is challenged by marked cellular heterogeneity and limited tissue availability from renal biopsies. Conventional diagnostic workflows rely on multiple serial sections for parallel staining, increasing tissue consumption, sampling bias, and loss of spatial information, thereby constraining molecular characterization within intact tissue architecture. High-plex spatial proteomics may overcome these limitations by enabling comprehensive molecular profiling on a single section. Here, we present and evaluate a high-plex cyclic immunofluorescence imaging workflow (MACSima™, Miltenyi Biotec) applied to kidney transplant biopsies, including BK virus nephropathy (BKVN) and focal segmental glomerulosclerosis (FSGS), to characterize spatial immune organization with a focus on complement system components. Feasibility and subcellular resolution were first assessed in a lupus nephritis section, demonstrating compatibility with diagnostic immune panels and preservation of tissue morphology. A 48-marker multiplex panel interrogating immunity, oxidative stress, senescence, and fibrosis was then applied to BKVN samples, including paired pre- and post-treatment biopsies, revealing distinct proteomic patterns and dynamic changes following therapy. In FSGS, a glomerulus-focused panel identified spatially resolved innate and adaptive immune signatures, including complement-related patterns supporting exploratory analysis of glomerular immune architecture. Structural, nuclear, membrane, and phosphorylated signaling markers enabled precise delineation of renal compartments and assessment of cellular states such as proliferation, DNA damage, and pathway activation. The workflow also supported detection of extracellular vesicles in cultured renal cells, highlighting its versatility. Overall, this approach provides a robust, tissue-sparing platform for integrated spatial and molecular profiling of renal biopsies, reducing sampling bias while enabling discovery-level phenotyping from a single section. This unified strategy is particularly suited to kidney transplantation, where diagnosis, therapeutic decision-making, and longitudinal monitoring are closely interconnected.

Kidney Transplantation↗

PubMed2026

Odon: an ultra-fast viewer for spatial proteomics.

MOTIVATION: Multiplexed spatial proteomics and spatial transcriptomics generate large, high-dimensional imaging datasets that are challenging to visualize efficiently, particularly at whole-slide and cohort scale. Visualization is an essential step for rapid detection of staining artefacts, such as protein aggregates or non-specific staining. RESULTS: Here, we present Odon, a native Rust desktop viewer designed for rapid, interactive exploration of multiplex imaging data on a standard laptop. Odon is primarily built around the OME-Zarr imaging format, and supports annotations via GeoJSON and GeoParquet, with secondary support for SpatialData, Xenium containers, and TIFF. Data can be stored locally or streamed directly from HTTP or S3-compatible object storage using viewport-driven tile loading. Odon incorporates a highly optimized rendering engine designed for viewport-driven tile loading and GPU-based compositing. In scripted benchmarks using synthetic multiplex OME-Zarr datasets, Odon showed lower peak memory use, lower affine-derived zoom-step error, and faster warm-start image loading than napari and QuPath under the tested conditions. Its GPU-based compositing pipeline also enables smooth rendering and interaction with >1 000 000 segmented cells. Odon further supports integrated visual analytics, including live thresholding and cell selection, and a mosaic mode for simultaneous viewing of hundreds of regions of interest in cohort and tissue microarray studies. Together, these features establish Odon as a high-performance platform for scalable visualization of spatial proteomics data. AVAILABILITY AND IMPLEMENTATION: Source code and compiled installers are available at https://github.com/alexcoulton/odon.

Proteomics↗

PubMed2025

Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism.

Cellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments.

Humans↗

PubMed2026

Detection of cytokine release syndrome using wearables and cytokine profiling following CAR-T therapy for myeloma.

BACKGROUNDChimeric antigen receptor T-cell (CAR-T) therapies have revolutionized treatment for relapsed/refractory multiple myeloma (RRMM). However, cytokine release syndrome (CRS), a common and potentially severe complication, requires inpatient monitoring, limiting access and increasing costs. Wearable devices could support outpatient CAR-T delivery, but feasibility for CRS detection versus standard care remains unproven.METHODSWe conducted a prospective, single-center observational pilot study to assess the feasibility of using wearable devices for monitoring vital signs and detecting CRS. Thirty patients receiving idecabtagene vicleucel (ide-cel) or ciltacabtagene autoleucel (cilta-cel) were enrolled; 25 with sufficient monitoring data were evaluable. Sensors collected skin and axillary temperature, oxygen saturation, respiratory and heart rate, and motion. Peripheral blood cytokines were analyzed pre- and postinfusion using a multiplex proteomic platform. The primary outcome was feasibility, assessed by CRS detection sensitivity and specificity; secondary outcomes included adherence, lead time, and performance of models integrating wearable and cytokine data.RESULTSCRS occurred in 20 of 25 patients. The best-performing wearable model detected 18 or 20 CRS episodes with a sensitivity of 0.72 (mean 0.75; 95% CI 0.60-0.91) and a specificity of 0.80 (mean 0.76; 95% CI 0.68-0.84), and a median lead time of 7:00 hours before nursing recognition. Median adherence during high-risk periods was 71%. Cytokine changes paralleled temperature elevations, and IFN-γ emerged as a consistent biomarker.CONCLUSIONWearable devices are feasible for early CRS detection and may support outpatient CAR-T care. Larger outpatient studies are warranted.TRIAL REGISTRATIONThis study did not meet the criteria for ClinicalTrials.gov registration.

Humans↗

PubMed2026

Obese adipocytes induce fibroblast-to-myofibroblast transition through TGF-β1 signaling: implications in asthma pathogenesis.

Obesity, a key risk factor for severe asthma, is associated with worsening symptoms and poor responses to conventional therapies. Recent studies have highlighted the presence of adipocytes within airway walls, which correlates positively with body mass index (BMI). However, the role of adipocytes in asthma pathogenesis remains largely unknown. This study aims to explore their potential contribution to airway fibrosis, a progressive form of the disease, through fibroblast-to-myofibroblast transition (FMT). In vitro coculture models were developed to investigate the interactions between adipocytes (derived from patients with and without obesity) and fibroblasts (from patients with and without asthma) on FMT. Proteomic and multiplex analyses were used to identify potential mediators of adipocyte-induced FMT. Our data revealed a significant increase in fibrogenic markers, such as alpha-smooth muscle actin and vimentin, in fibroblasts cocultured with obese (Ob) adipocytes. Notably, this transition was more pronounced in asthmatic fibroblasts compared with healthy fibroblasts. Proteomic profiling of cocultured Ob-adipocytes and asthmatic fibroblasts identified several significantly upregulated proteins linked to the regulation of the transforming growth factor-beta (TGF-β) signaling pathway, including inhibin A, latent TGF-β binding protein 1, thrombospondin 1, and follistatin. The role of TGF-β was further substantiated by multiplex assays, which demonstrated a significant increase in TGF-β and leptin production by Ob-adipocytes following coculture. These findings suggest that Ob-adipocytes may promote FMT in fibroblasts, especially asthmatic fibroblasts, by activating the TGF-β signaling pathway. This highlights a potential mechanism by which obesity exacerbates asthma severity and fibrosis, providing new avenues for therapeutic intervention.NEW & NOTEWORTHY Adipocytes have been found in the airway wall of patients with obesity. This study is the first to show that adipocytes derived from patients with obesity can induce features of airway remodeling that is seen in patients with asthma such as fibroblast-to-myofibroblast transition via the TGF-beta signaling pathway in an indirect mode of cellular communication. This highlights a potential mechanism by which obesity exacerbates asthma severity and fibrosis, providing new avenues for therapeutic intervention.

Humans↗

PubMed2025

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci.

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics, targeted chemical perturbations, and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci. Furthermore, we establish that DNA O-MAP \ is applicable to both repetitive and unique genomic loci of varying sizes (kilobases to megabases), and that DNA O-MAP can measure proximal molecular effectors in a homolog-specific manner.

Journal Article↗

PubMed2026

Distinct immune landscapes characterize highly versus minimally invasive brain metastases.

Brain metastases (BrMs) occur in approximately 30% of cancer patients, causing nearly one-fifth of cancer deaths. While immune checkpoint inhibitors (ICIs) benefit some BrM patients, responses remain highly variable. This variability partly reflects distinct histopathological growth patterns that include minimally invasive (MI) and highly invasive (HI) brain BrMs. Here we show that MI BrMs exhibit robust immune infiltration, whereas HI lesions are immunosuppressed. However, histological differentiation between MI and HI can be challenging because of subjective margin assessment. Here, using highly multiplexed spatial proteomics on 119 tumor sections from 46 patients with BrMs, we identify CHI3L1 as a key mediator of the immunosuppressive microenvironment in HI BrMs. In preclinical models, genetic deletion of CHI3L1 converts immune-cold metastases into lymphocyte-rich, ICI-responsive lesions infiltrated by granzyme B+ CD8+ T cells. In BrM patients treated with ICI, immunohistochemical quantification of CHI3L1 expression was a stronger predictor of ICI response than traditional MI/HI classification. Thus, CHI3L1 represents a promising biomarker and therapeutic target for BrMs.

Humans↗

PubMed2025

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Single-Cell Analysis↗

PubMed2026

Immune profiling in a living human recipient of a gene-edited pig kidney.

Xenotransplantation of gene-edited pig kidneys offers a promising solution to the shortage of kidneys for organ transplantation. We recently performed a gene-edited pig kidney transplantation into a living human recipient with end-stage kidney disease. Here, using transcriptomics, proteomics, metabolomics and multiplexed imaging, we conducted high-dimensional immune profiling in this individual. Despite profound depletion of circulating T cells, early T cell-mediated rejection occurred within 1 week after transplantation, likely driven by subtherapeutic immunosuppression and the presence of residual CD8+ T cells in lymph nodes. This T cell-mediated rejection event was reversed by intensified immunosuppression. After treatment, adaptive immunity remained suppressed, whereas innate immune activation, characterized by sustained monocyte and macrophage activity along with elevated levels of interleukin-1 beta and granulocyte-macrophage colony-stimulating factor, persisted. Comparative transcriptomic analysis showed that xenograft rejection profiles resembled those typically observed in human allograft rejection, while also revealing unique innate immune signatures. We did not detect antibody-mediated rejection. The levels of circulating pig donor-derived cell-free DNA rose during the initial rejection episode and declined with treatment, supporting the potential of cell-free DNA measurements as a noninvasive biomarker of xenograft rejection. These findings define the distinct immune landscape of kidney xenotransplantation and highlight the need for regimens targeting both innate and adaptive immunity to improve outcomes.

Animals↗

PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

PubMed2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Journal Article↗

PubMed2026

Moving Beyond Morphology to Multiplexed Molecular Imaging as the Next Frontier in Diagnostic Pathology.

Diagnostic pathology has long relied on the morphologic interpretation of hematoxylin and eosin-stained tissues to guide diagnosis and assess prognostic features. Although pathologists intuitively recognize spatial patterns and architectural organization, these assessments remain largely qualitative and difficult to quantify systematically. Immunohistochemistry and immunofluorescence have introduced molecular specificity but are limited in multiplexing capacity, whereas bulk genomic and transcriptomic assays provide high molecular depth but lose spatial context by averaging signals across heterogeneous cell populations. Recent advances in spatial proteomics-including mass spectrometry-based imaging and cyclic immunofluorescence-now enable multiplexed, single-cell protein analysis within intact tissue architecture. These technologies have revealed complex immune and stromal microenvironments, spatially organized biomarkers predictive of therapeutic response, and molecular gradients underlying disease progression. By integrating histologic and molecular information, spatial proteomics bridges traditional microscopy with high-dimensional omics, allowing quantitative, spatially resolved insights into tissue organization and disease mechanisms. This review summarizes recent developments in multiplexed spatial proteomics from both scientific and pathologic perspectives, highlighting how these technologies extend beyond morphology to quantify histologic patterns, refine biomarker discovery, and facilitate clinical translation. The review also examines translational challenges and barriers to clinical implementation, including costs, standardization requirements, and workflow integration.

Humans↗

PubMed2026

PASTA: versatile tyramide-oligonucleotide amplification for multimodal spatial biology.

Spatial proteomics is limited by detection sensitivity, multiplexing and multimodal integration, leaving a gap between discovery and clinical assays. Here we present protein and nucleic acid serial tyramide amplification (PASTA), using horseradish peroxidase-mediated oligonucleotide deposition and cyclical imaging for high-plex, multimodal spatial profiling. Compatible with conjugated antibodies and in situ hybridization, PASTA enables simultaneous protein and RNA codetection from formalin-fixed, paraffin-embedded samples, providing a cost-effective bridge from discovery to clinical validation.

Tyramine↗

PubMed2026

High-Plex Tissue Imaging with Conventional Immunofluorescence Platforms and Open-Source Software via Iterative Bleaching Extends Multiplexity (IBEX).

Iterative bleaching extends multiplexity (IBEX) is an easy-to-use, highly multiplex immunofluorescent tissue imaging method that employs widely available microscopy platforms, commercial reagents, and open-source software. In this article, we describe how to implement this method in a laboratory that has minimal experience with immunohistochemistry.

Software↗