SurfaceGenie: a web-based application for prioritizing cell-type-specific marker candidates

SurfR: Riding the wave of RNA-seq data with a comprehensive bioconductor package to identify surface protein-coding genes

Motivation

Proteins at the cell surface connect signaling networks and largely determine a cell's capacity to communicate and interact with its environment. In particular, variations in transcriptomic profiles are often observed between healthy and diseased cells, leading to distinct sets of cell-surface proteins. For these reasons, cell-surface proteins may act as biomarkers for the detection of cells of interest in tissues or body fluids, are often the target of pharmaceutical agents, and hold significant promise in the clinical practice for diagnosis, prognosis, treatment development, and evaluation of therapy response. Therefore, implementing robust methods to identify condition-specific cell-surface proteins is of pivotal importance to advance biomedical research.

Results

We developed SurfR, an R/Bioconductor package providing a streamlined end-to-end workflow for computationally identifying surface protein-coding genes from expression data. Our user-friendly, comprehensive workflow performs systematic expression data retrieval from public databases, differential gene expression across conditions, integration of datasets, enrichment analysis, identification of targetable proteins on a condition of interest, and data visualization.

Availability and implementation

SurfR is released under GNU-GPL-v3.0 License. Source code, documentation, examples, and tutorials are available through Bioconductor (http://www.bioconductor.org/packages/SurfR). RMD notebooks with the use cases code described in the manuscript can be found on GitHub (https://github.com/auroramaurizio/SurfR_UseCases).

Immune System-Related Plasma Pathogenic Extracellular Vesicle Subpopulations Predict Osteoarthritis Progression

Certain molecules found on the surface or within the cargo of extracellular vesicles (EVs) are linked to osteoarthritis (OA) severity and progression. We aimed to identify plasma pathogenic EV subpopulations that can predict knee radiographic OA (rOA) progression. We analyzed the mass spectrometry-based proteomic data of plasma EVs and synovial fluid (SF) EVs from knee OA patients (n = 16, 50% female). The identified surface markers of interest were further evaluated in plasma EVs from an independent cohort of knee OA patients (n = 30, 47% female) using flow cytometry. A total of 199 peptides with significant correlation between plasma and SF EVs were identified. Of these, 41.7% were linked to immune system processes, 15.5% to inflammatory responses, and 16.7% to the complement system. Crucially, five previously identified knee rOA severity-indicating surface markers-FGA, FGB, FGG, TLN1, and AMBP-were confirmed on plasma EV subpopulations in an independent cohort. These markers' baseline frequencies on large plasma EVs predicted rOA progression with an AUC of 0.655-0.711. Notably, TLN1 was expressed in OA joint tissue, whereas FGA, FGB, FGG, and AMBP were predominantly liver derived. These surface markers define specific pathogenic EV subpopulations, offering potential OA prognostic biomarkers and novel therapeutic targets for disease modification.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma

Cancer immunotherapies produce remarkable results in B cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor and normal tissues to identify biologically relevant cell surface immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer. Proteogenomic analyses reveal sixty high-confidence candidate immunotherapeutic targets, and we prioritize delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlates with a super-enhancer. Immunofluorescence, flow cytometry, and immunohistochemistry show robust cell surface expression of DLK1. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells results in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Since high DLK1 expression is found in several adult and pediatric cancers, our study demonstrates the utility of a proteogenomic approach and credentials DLK1 as an immunotherapeutic target.

Unveiling Tumorigenesis Mechanisms and Drug Therapy in Neuroblastoma by Mass Spectrometry Based Proteomics

Neuroblastoma (NB) is the most common type of extracranial solid tumors in children. Despite the advancements in treatment strategies over the past years, the overall survival rate in patients within the high-risk NB group remains less than 50%. Therefore, new treatment options are urgently needed for this group of patients. Compared with genomic aberrations, proteomic alterations are more dynamic and complex, as well as more directly related to pathological phenotypes and external perturbations such as environmental changes and drug treatments. This review focuses on specific examples of proteomics application in various fundamental aspects of NB research, including tumorigenesis, drug treatment, drug resistance, and highlights potential protein signatures and related signaling pathways with translational values for clinical practice. Moreover, emerging cutting-edge proteomic techniques, such as single cell and spatial proteomics, as well as mass spectrometry imaging, are discussed for their potentials to probe intratumor heterogeneity of NB.

Cancer pharmacoinformatics: Databases and analytical tools

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Single-cell RNA sequencing of pediatric Hodgkin lymphoma to study the inhibition of T cell subtypes

Pediatric classic Hodgkin lymphoma (cHL) patients have a high survival rate but suffer from severe long-term side effects induced by chemo- and radiotherapy. cHL tumors are characterized by the low fraction (0.1%-10%) of malignant Hodgkin and Reed-Sternberg (HRS) cells in the tumor. The HRS cells depend on the surrounding immune cells for survival and growth. This dependence is leveraged by current treatments that target the PD-1/PD-L1 axis in cHL tumors. The development of more targeted therapies that are specific for the tumor and are therefore less toxic for healthy tissue compared with conventional chemotherapy could improve the quality of life of pediatric cHL survivors. Here, we applied single-cell RNA sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. Besides TNFRSF8 (CD30), we identified other genes of cell surface proteins that are consistently overexpressed in HRS cells, such as NRXN3 and LRP8, which can potentially be used as alternative targets for antibody-drug conjugates or CAR T cells. Finally, we identified potential interactions by which HRS cells inhibit T cells, among which are the galectin-1/CD69 and HLA-II/LAG3 interactions. RNAscope was used to validate the enrichment of CD69 and LAG3 expression on T cells near HRS cells and indicated large variability of the interaction strength with the corresponding ligands between patients and between tumor tissue regions. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets, specifically those that target tumor-immune cell interactions.

Veneer Is a Webtool for Rapid, Standardized, and Transparent Interpretation, Annotation, and Reporting of Mammalian Cell Surface N-Glycocapture Data

Currently, no consensus exists regarding criteria required to designate a protein within a proteomic data set as a cell surface protein. Most published proteomic studies rely on varied ontology annotations or computational predictions instead of experimental evidence when attributing protein localization. Consequently, standardized approaches for analyzing and reporting cell surface proteome data sets would increase confidence in localization claims and promote data use by other researchers. Recently, we developed Veneer, a web-based bioinformatic tool that analyzes results from cell surface N-glycocapture workflows─the most popular cell surface proteomics method used to date that generates experimental evidence of subcellular location. Veneer assigns protein localization based on defined experimental and bioinformatic evidence. In this study, we updated the criteria and process for assigning protein localization and added new functionality to Veneer. Results of Veneer analysis of 587 cell surface N-glycocapture data sets from 32 published studies demonstrate the importance of applying defined criteria when analyzing cell surface proteomics data sets and exemplify how Veneer can be used to assess experimental quality and facilitate data extraction for informing future biological studies and annotating public repositories.

Vaccine design and development: Exploring the interface with computational biology and AI

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.

Immunotherapeutic targeting of surfaceome heterogeneity in AML

Immunotherapy remains underexploited in acute myeloid leukemia (AML) compared to other hematological malignancies. Currently, gemtuzumab ozogamicin is the only therapeutic antibody approved for this disease. Here, to identify potential targets for immunotherapeutic intervention, we analyze the surface proteome of 100 genetically diverse primary human AML specimens for the identification of cell surface proteins and conduct single-cell transcriptome analyses on a subset of these specimens to assess antigen expression at the sub-population level. Through this comprehensive effort, we successfully identify numerous antigens and markers preferentially expressed by primitive AML cells. Many identified antigens are targeted by therapeutic antibodies currently under clinical evaluation for various cancer types, highlighting the potential therapeutic value of the approach. Importantly, this initiative uncovers AML heterogeneity at the surfaceome level, identifies several antigens and potential primitive cell markers characterizing AML subgroups, and positions immunotherapy as a promising approach to target AML subgroup specificities.

Prostate cancer reshapes the secreted and extracellular vesicle urinary proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Zinc-chelating BET bromodomain inhibitors equally target islet endocrine cell types

Inhibition of the bromodomain and extraterminal domain (BET) protein family is a potential strategy to prevent and treat diabetes; however, the clinical use of BET bromodomain inhibitors (BETis) is associated with adverse effects. Here, we explore a strategy for targeting BETis to β cells by exploiting the high-zinc (Zn2+) concentration in β cells relative to other cell types. We report the synthesis of a novel, Zn2+-chelating derivative of the pan-BETi (+)-JQ1, (+)-JQ1-DPA, in which (+)-JQ1 was conjugated to dipicolyl amine (DPA). As controls, we synthesized (+)-JQ1-DBA, a non-Zn2+-chelating derivative, and (-)-JQ1-DPA, an inactive enantiomer that chelates Zn2+. Molecular modeling and biophysical assays showed that (+)-JQ1-DPA and (+)-JQ1-DBA retain potent binding to BET bromodomains in vitro. Cellular assays demonstrated (+)-JQ1-DPA attenuated NF-ĸB target gene expression in β cells stimulated with the proinflammatory cytokine interleukin 1β. To assess β-cell selectivity, we isolated islets from a mouse model that expresses green fluorescent protein in insulin-positive β cells and mTomato in insulin-negative cells (non-β cells). Surprisingly, Zn2+ chelation did not confer β-cell selectivity as (+)-JQ1-DPA was equally effective in both β and α cells; however, (+)-JQ1-DPA was less effective in macrophages, a nonendocrine islet cell type. Intriguingly, the non-Zn2+-chelating derivative (+)-JQ1-DBA displayed the opposite selectivity, with greater effect in macrophages compared with (+)-JQ1-DPA, suggesting potential as a macrophage-targeting molecule. These findings suggest that Zn2+-chelating small molecules confer endocrine cell selectivity rather than β-cell selectivity in pancreatic islets and provide valuable insights and techniques to assess Zn2+ chelation as an approach to selectively target small molecules to pancreatic β cells.NEW & NOTEWORTHY Inhibition of BET bromodomains is a novel potential strategy to prevent and treat diabetes mellitus. However, BET inhibitors have negative side effects. We synthesized a BET inhibitor expected to exploit the high zinc concentration in β cells to accumulate in β cells. We show our inhibitor targeted pancreatic endocrine cells; however, it was less effective in immune cells. A control inhibitor showed the opposite effect. These findings help us understand how to target specific cells in diabetes treatment.

The landscape of immune dysregulation in pediatric sepsis at a single-cell resolution

Recognizing immune dysregulation as a hallmark of sepsis pathophysiology, leukocytes have attracted major attention of investigation. While adult and pediatric sepsis are clinically distinct, their immunological delineation remains limited. Single cell technologies facilitated the characterization of immune signatures. We tackled to delineate immunological profiles of pediatric sepsis at a single-cell level by analyzing blood samples from six septic children, at both acute and recovery phases, and four healthy children. 16 single-cell transcriptomic datasets were analyzed and compared to adult sepsis dataset. We showed a unique shift in neutrophil subpopulations and functions between acute and recovery phases, along with the regulatory role of resistin. Neutrophil signatures were comparable between adult and pediatric sepsis. Innate-like CD4 T cells were predominantly and uniquely observed in acute phase of pediatric sepsis. Our study serves as a rich source of information about the phenotypic diversity and trajectory of circulating immune cells during pediatric sepsis.

Droplet-based proteomics reveals CD36 as a marker for progenitors in mammary basal epithelium

Deep proteomic profiling of rare cell populations has been constrained by sample input requirements. Here, we present DROPPS (droplet-based one-pot preparation for proteomic samples), an accessible low-input platform that generates high-fidelity proteomic profiles of 100-2,500 cells. By applying DROPPS within the mammary epithelium, we elucidated the connection between mitochondrial activity and clonogenicity, identifying CD36 as a marker of progenitor capacity in the basal cell compartment. We anticipate that DROPPS will accelerate biology-driven proteomic research for a multitude of rare cell populations.

Proteomic and phosphoproteomic characterisation of primary mouse embryonic fibroblasts

Fibroblasts are the most common cell type in stroma and function in the support and repair of most tissues. Mouse embryonic fibroblasts (MEFs) are amenable to isolation and rapid growth in culture. MEFs are therefore widely used as a standard model for functional characterisation of gene knockouts, and can also be used in co-cultures, commonly to support embryonic stem cell cultures. To facilitate their use as a research tool, we have performed a comprehensive proteomic and phosphoproteomic characterisation of wild-type primary MEFs from C57BL/6 mice. EIF2/4 and MTOR signalling pathways were abundant in both the proteome and phosphoproteome, along with extracellular matrix (ECM) and cytoskeleton associated pathways. Consistent with this, kinase enrichment analysis identified activation of P38A, P90RSK, P70S6K, and MTOR. Cell surface markers and matrisome proteins were also annotated. Data are available via ProteomeXchange with identifier PXD043244. This provides a comprehensive catalogue of the wild-type MEF proteome and phosphoproteome which can be utilised by the field to guide future work.

Organelle resolved proteomics uncovers PLA2R1 as a novel cell surface marker required for chordoma growth

Chordomas are clinically aggressive tumors with a high rate of disease progression despite maximal therapy. Given the limited therapeutic options available, there remains an urgent need for the development of novel therapies to improve clinical outcomes. Cell surface proteins are attractive therapeutic targets yet are challenging to profile with common methods. Four chordoma cell lines were analyzed by quantitative proteomics using a differential ultracentrifugation organellar fractionation approach. A subtractive proteomics strategy was applied to select proteins that are plasma membrane enriched. Systematic data integration prioritized PLA2R1 (secretory phospholipase A2 receptor-PLA2R1) as a chordoma-enriched surface protein. The expression profile of PLA2R1 was validated across chordoma cell lines, patient surgical tissue samples, and normal tissue lysates via immunoblotting. PLA2R1 expression was further validated by immunohistochemical analysis in a richly annotated cohort of 25-patient tissues. Immunohistochemistry analysis revealed that elevated expression of PLA2R1 is correlated with poor prognosis. Using siRNA- and CRISPR/Cas9-mediated knockdown of PLA2R1, we demonstrated significant inhibition of 2D, 3D and in vivo chordoma growth. PLA2R1 depletion resulted in cell cycle defects and metabolic rewiring via the MAPK signaling pathway, suggesting that PLA2R1 plays an essential role in chordoma biology. We have characterized the proteome of four chordoma cell lines and uncovered PLA2R1 as a novel cell-surface protein required for chordoma cell survival and association with patient outcome.

Surface and Global Proteome Analyses Identify ENPP1 and Other Surface Proteins as Actionable Immunotherapeutic Targets in Ewing Sarcoma

PURPOSE

Ewing sarcoma is the second most common bone sarcoma in children, with 1 case per 1.5 million in the United States. Although the survival rate of patients diagnosed with localized disease is approximately 70%, this decreases to approximately 30% for patients with metastatic disease and only approximately 10% for treatment-refractory disease, which have not changed for decades. Therefore, new therapeutic strategies are urgently needed for metastatic and refractory Ewing sarcoma.

EXPERIMENTAL DESIGN

This study analyzed 19 unique Ewing sarcoma patient- or cell line-derived xenografts (from 14 primary and 5 metastatic specimens) using proteomics to identify surface proteins for potential immunotherapeutic targeting. Plasma membranes were enriched using density gradient ultracentrifugation and compared with a reference standard of 12 immortalized non-Ewing sarcoma cell lines prepared in a similar manner. In parallel, global proteome analysis was carried out on each model to complement the surfaceome data. All models were analyzed by Tandem Mass Tags-based mass spectrometry to quantify identified proteins.

RESULTS

The surfaceome and global proteome analyses identified 1,131 and 1,030 annotated surface proteins, respectively. Among surface proteins identified, both approaches identified known Ewing sarcoma-associated proteins, including IL1RAP, CD99, STEAP1, and ADGRG2, and many new cell surface targets, including ENPP1 and CDH11. Robust staining of ENPP1 was demonstrated in Ewing sarcoma tumors compared with other childhood sarcomas and normal tissues.

CONCLUSIONS

Our comprehensive proteomic characterization of the Ewing sarcoma surfaceome provides a rich resource of surface-expressed proteins in Ewing sarcoma. This dataset provides the preclinical justification for exploration of targets such as ENPP1 for potential immunotherapeutic application in Ewing sarcoma. See related commentary by Bailey, p. 934.

The landscape of immune dysregulation in pediatric sepsis at a single-cell resolution

Recognizing immune dysregulation as a hallmark of sepsis pathophysiology, leukocytes have attracted major attention of investigation. While adult and pediatric sepsis are clinically distinct, their immunological delineation remains limited. Breakthrough of single cell technologies facilitated the characterization of immune signatures. We tackled to delineate immunological profiles of pediatric sepsis at a single-cell level by analyzing blood samples from six septic children, at both acute and recovery phases, and four healthy children. 16 single-cell transcriptomic datasets (96,156 cells) were analyzed and compared to adult sepsis dataset. We showed a unique shift in neutrophil subpopulations and functions between acute and recovery phases, along with examining the regulatory role of resistin. Neutrophil signatures were comparable between adult and pediatric sepsis. Innate-like CD4 T cells were predominantly and uniquely observed in acute phase of pediatric sepsis. Our study provides a thorough and comprehensive understanding of immune dysregulation in pediatric sepsis.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target.

Highlights

Plasma membrane enriched proteomics defines surfaceome of neuroblastomaMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancersDLK1 expression is driven by a super-enhancer DLK1 silencing in neuroblastoma cells results in cellular differentiation ADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models.

Comprehensive characterization of pathogenic synovial fluid extracellular vesicles from knee osteoarthritis

Synovial fluid (SF) extracellular vesicles (EVs) play a pathogenic role in osteoarthritis (OA). However, the surface markers, cell and tissue origins, and effectors of these EVs are largely unknown. We found that SF EVs contained 692 peptides that were positively associated with knee radiographic OA severity; 57.4% of these pathogenic peptides were from 46 proteins of the immune system, predominantly the innate immune system. CSPG4, BGN, NRP1, and CD109 are the major surface markers of pathogenic SF EVs. Genes encoding surface marker CSPG4 and CD109 were highly expressed by chondrocytes from damaged cartilage, while VISG4, MARCO, CD163 and NRP1 were enriched in the synovial immune cells. The frequency of CSPG4+ and VSIG4+ EV subpopulations in OA SF was high. We conclude that pathogenic SF EVs carry knee OA severity-associated proteins and specific surface markers, which could be developed as a new source of diagnostic biomarkers or therapeutic targets in OA.

Identification and functional analysis of senescent cells in the cardiovascular system using omics approaches

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, and senescent cells have emerged as key contributors to its pathogenesis. Senescent cells exhibit cell cycle arrest and secrete a range of proinflammatory factors, termed the senescence-associated secretory phenotype (SASP), which promotes tissue dysfunction and exacerbates CVD progression. Omics technologies, specifically transcriptomics and proteomics, offer powerful tools to uncover and define the molecular signatures of senescent cells in cardiovascular tissue. By analyzing the comprehensive molecular profiles of senescent cells, omics approaches can identify specific genetic alterations, gene expression patterns, protein abundances, and metabolite levels associated with senescence in CVD. These omics-based discoveries provide insights into the mechanisms underlying senescence-induced cardiovascular damage, facilitating the development of novel diagnostic biomarkers and therapeutic targets. Furthermore, integration of multiple omics data sets enables a systems-level understanding of senescence in CVD, paving the way for precision medicine approaches to prevent or treat cardiovascular aging and its associated complications.

Translating Senotherapeutic Interventions into the Clinic with Emerging Proteomic Technologies

Cellular senescence is a state of irreversible growth arrest with profound phenotypic changes, including the senescence-associated secretory phenotype (SASP). Senescent cell accumulation contributes to aging and many pathologies including chronic inflammation, type 2 diabetes, cancer, and neurodegeneration. Targeted removal of senescent cells in preclinical models promotes health and longevity, suggesting that the selective elimination of senescent cells is a promising therapeutic approach for mitigating a myriad of age-related pathologies in humans. However, moving senescence-targeting drugs (senotherapeutics) into the clinic will require therapeutic targets and biomarkers, fueled by an improved understanding of the complex and dynamic biology of senescent cell populations and their molecular profiles, as well as the mechanisms underlying the emergence and maintenance of senescence cells and the SASP. Advances in mass spectrometry-based proteomic technologies and workflows have the potential to address these needs. Here, we review the state of translational senescence research and how proteomic approaches have added to our knowledge of senescence biology to date. Further, we lay out a roadmap from fundamental biological discovery to the clinical translation of senotherapeutic approaches through the development and application of emerging proteomic technologies, including targeted and untargeted proteomic approaches, bottom-up and top-down methods, stability proteomics, and surfaceomics. These technologies are integral for probing the cellular composition and dynamics of senescent cells and, ultimately, the development of senotype-specific biomarkers and senotherapeutics (senolytics and senomorphics). This review aims to highlight emerging areas and applications of proteomics that will aid in exploring new senescent cell biology and the future translation of senotherapeutics.

Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data are suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody-drug conjugates and immunotherapeutic agents.

Prostate Cancer Reshapes the Secreted and Extracellular Vesicle Urinary Proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions, and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome, and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Single-cell RNA sequencing of mouse lower respiratory tract epithelial cells: A meta-analysis

The respiratory system is a vital component of our body, essential for both oxygen uptake and immune defense. Knowledge of cellular composition and function in different parts of the respiratory tract provides the basis for a better understanding of the pathological processes involved in various diseases such as chronic respiratory diseases and cancer. Single-cell RNA sequencing (scRNA-seq) is a proficient approach for the identification and transcriptional characterization of cellular phenotypes. Although the mouse is an essential tool for the study of lung development, regeneration, and disease, a scRNA-seq mouse atlas of the lung in which all epithelial cell types are included and annotated systematically is lacking. Here, we established a single-cell transcriptome landscape of the mouse lower respiratory tract by performing a meta-analysis of seven different studies in which mouse lungs and trachea were analyzed by droplet and/or plate-based scRNA-seq technologies. We provide information on the best markers for each epithelial cell type, propose surface markers for the isolation of viable cells, harmonized the annotation of cell types, and compare the mouse single-cell transcriptomes with human scRNA-seq data of the lung.

Roles of glycosylation at the cancer cell surface: opportunities for large scale glycoproteomics

Cell surface glycosylation has a variety of functions, and its dysregulation in cancer contributes to impaired signaling, metastasis and the evasion of the immune responses. Recently, a number of glycosyltransferases that lead to altered glycosylation have been linked to reduced anti-tumor immune responses: B3GNT3, which is implicated in PD-L1 glycosylation in triple negative breast cancer, FUT8, through fucosylation of B7H3, and B3GNT2, which confers cancer resistance to T cell cytotoxicity. Given the increased appreciation of the relevance of protein glycosylation, there is a critical need for the development of methods that allow for an unbiased interrogation of cell surface glycosylation status. Here we provide an overview of the broad changes in glycosylation at the surface of cancer cell and describe selected examples of receptors with aberrant glycosylation leading to functional changes, with emphasis on immune checkpoint inhibitors, growth-promoting and growth-arresting receptors. Finally, we posit that the field of glycoproteomics has matured to an extent where large-scale profiling of intact glycopeptides from the cell surface is feasible and is poised for discovery of new actionable targets against cancer.

Targeting CLDN6 in germ cell tumors by an antibody-drug-conjugate and studying therapy resistance of yolk-sac tumors to identify and screen specific therapeutic options

BACKGROUND

Being the standard-of-care for four decades, cisplatin-based chemotherapy is highly efficient in treating germ cell tumors (GCT). However, often refractory patients present with a remaining (resistant) yolk-sac tumor (YST(-R)) component, resulting in poor prognosis due to lack of novel treatment options besides chemotherapy and surgery. The aim of this study was to identify novel targets for the treatment of YST by deciphering the molecular mechanisms of therapy resistance. Additionally, we screened the cytotoxic efficacy of a novel antibody-drug-conjugate targeting CLDN6 (CLDN6-ADC), as well as pharmacological inhibitors to target specifically YST.

METHODS

Protein and mRNA levels of putative targets were measured by flow cytometry, immunohistochemical stainings, mass spectrometry of formalin-fixed paraffin-embedded tissues, phospho-kinase arrays, or qRT-PCR. Cell viability, apoptosis and cell cycle assays of GCT and non-cancerous cells were performed using XTT cell viability assays or Annexin V / propidium iodide flow cytometry, respectively. Druggable genomic alterations of YST(-R) tissues were identified by the TrueSight Oncology 500 assay.

RESULTS

We demonstrated that treatment with a CLDN6-ADC enhanced apoptosis induction specifically in CLDN6+ GCT cells in comparison with non-cancerous controls. In a cell line-dependent manner, either an accumulation in the G2 / M cell cycle phase or a mitotic catastrophe was observed. Based on mutational and proteome profiling, this study identified drugs targeting the FGF, VGF, PDGF, mTOR, CHEK1, AURKA, or PARP signaling pathways as promising approaches to target YST. Further, we identified factors relevant for MAPK signaling, translational initiation and RNA binding, extracellular matrix-related processes as well as oxidative stress and immune response to be involved in therapy resistance.

CONCLUSIONS

In summary, this study offers a novel CLDN6-ADC to target GCT. Additionally, this study presents novel pharmacological inhibitors blocking FGF, VGF, PDGF, mTOR, CHEK1, AURKA, or PARP signaling for the treatment of (refractory) YST patients. Finally, this study shed light on the mechanisms of therapy resistance in YST.

Systematic characterization of extracellular glycoproteins using mass spectrometry

Surface and secreted glycoproteins are essential to cells and regulate many extracellular events. Because of the diversity of glycans, the low abundance of many glycoproteins, and the complexity of biological samples, a system-wide investigation of extracellular glycoproteins is a daunting task. With the development of modern mass spectrometry (MS)-based proteomics, comprehensive analysis of different protein modifications including glycosylation has advanced dramatically. This review focuses on the investigation of extracellular glycoproteins using MS-based proteomics. We first discuss the methods for selectively enriching surface glycoproteins and investigating protein interactions on the cell surface, followed by the application of MS-based proteomics for surface glycoprotein dynamics analysis and biomarker discovery. We then summarize the methods to comprehensively study secreted glycoproteins by integrating various enrichment approaches with MS-based proteomics and their applications for global analysis of secreted glycoproteins in different biological samples. Collectively, MS significantly expands our knowledge of extracellular glycoproteins and enables us to identify extracellular glycoproteins as potential biomarkers for disease detection and drug targets for disease treatment.

Surfaceome mapping of primary human heart cells with CellSurfer uncovers cardiomyocyte surface protein LSMEM2 and proteome dynamics in failing hearts

Cardiac cell surface proteins are drug targets and useful biomarkers for discriminating among cellular phenotypes and disease states. Here we developed an analytical platform, CellSurfer, that enables quantitative cell surface proteome (surfaceome) profiling of cells present in limited quantities, and we apply it to isolated primary human heart cells. We report experimental evidence of surface localization and extracellular domains for 1,144 N-glycoproteins, including cell-type-restricted and region-restricted glycoproteins. We identified a surface protein specific for healthy cardiomyocytes, LSMEM2, and validated an anti-LSMEM2 monoclonal antibody for flow cytometry and imaging. Surfaceome comparisons among pluripotent stem cell derivatives and their primary counterparts highlighted important differences with direct implications for drug screening and disease modeling. Finally, 20% of cell surface proteins, including LSMEM2, were differentially abundant between failing and non-failing cardiomyocytes. These results represent a rich resource to advance development of cell type and organ-specific targets for drug delivery, disease modeling, immunophenotyping and in vivo imaging.

Investigating SH-SY5Y Neuroblastoma Cell Surfaceome as a Model for Neuronal-Targeted Novel Therapeutic Modalities

The SH-SY5Y neuroblastoma cells are a widely used in vitro model approximating neurons for testing the target engagement of therapeutics designed for neurodegenerative diseases and pain disorders. However, their potential as a model for receptor-mediated delivery and uptake of novel modalities, such as antibody-drug conjugates, remains understudied. Investigation of the SH-SY5Y cell surfaceome will aid in greater in vitro to in vivo correlation of delivery and uptake, thereby accelerating drug discovery. So far, the majority of studies have focused on total cell proteomics from undifferentiated and differentiated SH-SY5Y cells. While some studies have investigated the expression of specific proteins in neuroblastoma tissue, a global approach for comparison of neuroblastoma cell surfaceome to the brain and dorsal root ganglion (DRG) neurons remains uninvestigated. Furthermore, an isoform-specific evaluation of cell surface proteins expressed on neuroblastoma cells remains unexplored. In this study, we define a bioinformatic workflow for the identification of high-confidence surface proteins expressed on brain and DRG neurons using tissue proteomic and transcriptomic data. We then delineate the SH-SY5Y cell surfaceome by surface proteomics and show that it significantly overlaps with the human brain and DRG neuronal surface proteome. We find that, for 32% of common surface proteins, SH-SY5Y-specific major isoforms are alternatively spliced, maintaining their protein-coding ability, and are predicted to localize to the cell surface. Validation of these isoforms using surface proteomics confirms a SH-SY5Y-specific alternative NRCAM (neuron-glia related cell adhesion molecule) isoform, which is absent in typical brain neurons, but present in neuroblastomas, making it a receptor of interest for neuroblastoma-specific therapeutics.

In vivo visualization and molecular targeting of the cardiac conduction system

Accidental injury to the cardiac conduction system (CCS), a network of specialized cells embedded within the heart and indistinguishable from the surrounding heart muscle tissue, is a major complication in cardiac surgeries. Here, we addressed this unmet need by engineering targeted antibody-dye conjugates directed against the CCS, allowing for the visualization of the CCS in vivo following a single intravenous injection in mice. These optical imaging tools showed high sensitivity, specificity, and resolution, with no adverse effects on CCS function. Further, with the goal of creating a viable prototype for human use, we generated a fully human monoclonal Fab that similarly targets the CCS with high specificity. We demonstrate that, when conjugated to an alternative cargo, this Fab can also be used to modulate CCS biology in vivo, providing a proof of principle for targeted cardiac therapeutics. Finally, in performing differential gene expression analyses of the entire murine CCS at single-cell resolution, we uncovered and validated a suite of additional cell surface markers that can be used to molecularly target the distinct subcomponents of the CCS, each prone to distinct life-threatening arrhythmias. These findings lay the foundation for translational approaches targeting the CCS for visualization and therapy in cardiothoracic surgery, cardiac imaging, and arrhythmia management.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

Glycoproteomics Identifies Plexin-B3 as a Targetable Cell Surface Protein Required for the Growth and Invasion of Triple-Negative Breast Cancer Cells

Driven by the lack of targeted therapies, triple-negative breast cancers (TNBCs) have the worst overall survival of all breast cancer subtypes. Considering that cell surface proteins are favorable drug targets and are predominantly glycosylated, glycoproteome profiling has significant potential to facilitate the identification of much-needed drug targets for TNBCs. Here, we performed N-glycoproteomics on six TNBCs and five normal control (NC) cell lines using hydrazide-based enrichment. Quantitative proteomics and integrative data mining led to the discovery of Plexin-B3 (PLXNB3), a previously undescribed TNBC-enriched cell surface protein. Furthermore, siRNA knockdown and CRISPR-Cas9 editing of in vitro and in vivo models show that PLXNB3 is required for TNBC cell line growth, invasion, and migration. Altogether, we provide insights into N-glycoproteome remodeling associated with TNBCs and functional evaluation of an extracted target, which indicate the surface protein PLXNB3 as a potential therapeutic target for TNBCs.

R-SPONDIN2+ mesenchymal cells form the bud tip progenitor niche during human lung development

The human respiratory epithelium is derived from a progenitor cell in the distal buds of the developing lung. These "bud tip progenitors" are regulated by reciprocal signaling with surrounding mesenchyme; however, mesenchymal heterogeneity and function in the developing human lung are poorly understood. We interrogated single-cell RNA sequencing data from multiple human lung specimens and identified a mesenchymal cell population present during development that is highly enriched for expression of the WNT agonist RSPO2, and we found that the adjacent bud tip progenitors are enriched for the RSPO2 receptor LGR5. Functional experiments using organoid models, explant cultures, and FACS-isolated RSPO2+ mesenchyme show that RSPO2 is a critical niche cue that potentiates WNT signaling in bud tip progenitors to support their maintenance and multipotency.

Deep Membrane Proteome Profiling Reveals Overexpression of Prostate-Specific Membrane Antigen (PSMA) in High-Risk Human Paraganglioma and Pheochromocytoma, Suggesting New Theranostic Opportunity

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors arising from chromaffin cells of adrenal medulla or sympathetic or parasympathetic paraganglia, respectively. To identify new therapeutic targets, we performed a detailed membrane-focused proteomic analysis of five human paraganglioma (PGL) samples. Using the Pitchfork strategy, which combines specific enrichments of glycopeptides, hydrophobic transmembrane segments, and non-glycosylated extra-membrane peptides, we identified over 1800 integral membrane proteins (IMPs). We found 45 “tumor enriched” proteins, i.e., proteins identified in all five PGLs but not found in control chromaffin tissue. Among them, 18 IMPs were predicted to be localized on the cell surface, a preferred drug targeting site, including prostate-specific membrane antigen (PSMA), a well-established target for nuclear imaging and therapy of advanced prostate cancer. Using specific antibodies, we verified PSMA expression in 22 well-characterized human PPGL samples. Compared to control chromaffin tissue, PSMA was markedly overexpressed in high-risk PPGLs belonging to the established Cluster 1, which is characterized by worse clinical outcomes, pseudohypoxia, multiplicity, recurrence, and metastasis, specifically including SDHB, VHL, and EPAS1 mutations. Using immunohistochemistry, we localized PSMA expression to tumor vasculature. Our study provides the first direct evidence of PSMA overexpression in PPGLs which could translate to therapeutic and diagnostic applications of anti-PSMA radio-conjugates in high-risk PPGLs.

Single-cell RNA sequencing of mouse islets exposed to proinflammatory cytokines

Exposure to proinflammatory cytokines is believed to contribute to pancreatic β-cell damage during diabetes development. Although some cytokine-mediated changes in islet gene expression are known, the heterogeneity of the response is not well-understood. After 6-h treatment with IL-1β and IFN-γ alone or together, mouse islets were subjected to single-cell RNA sequencing. Treatment with both cytokines together led to expression of inducible nitric oxide synthase mRNA (Nos2) and antiviral and immune-associated genes in a subset of β-cells. Interestingly, IL-1β alone activated antiviral genes. Subsets of δ- and α-cells expressed Nos2 and exhibited similar gene expression changes as β-cells, including increased expression of antiviral genes and repression of identity genes. Finally, cytokine responsiveness was inversely correlated with expression of genes encoding heat shock proteins. Our findings show that all islet endocrine cell types respond to cytokines, IL-1β induces the expression of protective genes, and cellular stress gene expression is associated with inhibition of cytokine signaling.

Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications

Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.

Rapid Enzyme-Mediated Biotinylation for Cell Surface Proteome Profiling

Cell surface is the primary site for sensing extracellular stimuli. The knowledge of the transient changes on the surfaceome upon a perturbation is very important as the initial changed proteins could be driving molecules for some phenotype. In this study, we report a fast cell surface labeling strategy based on peroxidase-mediated oxidative tyrosine coupling strategy, enabling efficient and selective cell surface labeling within seconds. With a labeling time of 1 min, 2684 proteins, including 1370 (51%) cell surface-annotated proteins (cell surface/plasma membrane/extracellular), 732 transmembrane proteins, and 81 cluster of differentiation antigens, were identified from HeLa cells. By comparison with the negative control experiment using quantitative proteomics, 500 (68%) out of the 731 significantly enriched proteins (p-value < 0.05, ≥2-fold) in positive experimental samples were cell surface-annotated proteins. Finally, this technology was applied to track the dynamic changes of the surfaceome upon insulin stimulation at two time points (5 min and 2 h) in HepG2 cells. Thirty-two proteins, including INSR, CTNNB1, TFRC, IGF2R, and SORT1, were found to be significantly regulated (p-value < 0.01, ≥1.5-fold) after insulin exposure by different mechanisms. We envision that this technique could be a powerful tool to analyze the transient changes of the surfaceome with a good time resolution and to delineate the temporal and spatial regulation of cellular signaling.

The quest of cell surface markers for stem cell therapy

Stem cells and their derivatives are novel pharmaceutics that have the potential for use as tissue replacement therapies. However, the heterogeneous characteristics of stem cell cultures have hindered their biomedical applications. In theory and practice, when cell type-specific or stage-specific cell surface proteins are targeted by unique antibodies, they become highly efficient in detecting and isolating specific cell populations. There is a growing demand to identify reliable and actionable cell surface markers that facilitate purification of particular cell types at specific developmental stages for use in research and clinical applications. The identification of these markers as very important members of plasma membrane proteins, ion channels, transporters, and signaling molecules has directly benefited from proteomics and tools for proteomics-derived data analyses. Here, we review the methodologies that have played a role in the discovery of cell surface markers and introduce cutting edge single cell proteomics as an advanced tool. We also discuss currently available specific cell surface markers for stem cells and their lineages, with emphasis on the nervous system, heart, pancreas, and liver. The remaining gaps that pertain to the discovery of these markers and how single cell proteomics and identification of surface markers associated with the progenitor stages of certain terminally differentiated cells may pave the way for their use in regenerative medicine are also discussed.

High-throughput approaches for precision medicine in high-grade serous ovarian cancer

High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

CIRFESS: An Interactive Resource for Querying the Set of Theoretically Detectable Peptides for Cell Surface and Extracellular Enrichment Proteomic Studies

Cell surface transmembrane, extracellular, and secreted proteins are high value targets for immunophenotyping, drug development, and studies related to intercellular communication in health and disease. As the number of specific and validated affinity reagents that target this subproteome are limited, mass spectrometry (MS)-based approaches will continue to play a critical role in enabling discovery and quantitation of these molecules. Given the technical considerations that make MS-based cell surface proteome studies uniquely challenging, it can be difficult to select an appropriate experimental approach. To this end, we have integrated multiple prediction strategies and annotations into a single online resource, Compiled Interactive Resource for Extracellular and Surface Studies (CIRFESS). CIRFESS enables rapid interrogation of the human proteome to reveal the cell surface proteome theoretically detectable by current approaches and highlights where current prediction strategies provide concordant and discordant information. We applied CIRFESS to identify the percentage of various subsets of the proteome which are expected to be captured by targeted enrichment strategies, including two established methods and one that is possible but not yet demonstrated. These results will inform the selection of available proteomic strategies and development of new strategies to enhance coverage of the cell surface and extracellular proteome. CIRFESS is available at www.cellsurfer.net/cirfess.

The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications

INTRODUCTION

Cellular senescence is a rapidly growing field with potential relevance for the treatment of multiple human diseases. In the last decade, cellular senescence and the senescence-associated secretory phenotype (SASP) have emerged as central drivers of aging and many chronic diseases, including cancer, neurodegeneration, heart disease and osteoarthritis. Major efforts are underway to develop drugs that selectively eliminate senescent cells (senolytics) or alter the SASP (senomorphics) to treat age-related diseases in humans. The translation of senescence-targeting therapies into humans is still in early stages. Nonetheless, it is clear that proteomic approaches will facilitate the discovery of important SASP proteins, development of senescence- and SASP-derived biomarkers, and identification of therapeutic targets for senolytic and senomorphic drugs.

AREAS COVERED

We review recent proteomic studies of cellular senescence and their translational relevance and, particularly, characterization of the secretory phenotype and preclinical development of biomarkers (from 2008-2020, PubMed). We focus on emerging areas, such as the heterogeneity of senescent cells and the SASP, extracellular vesicles released by senescent cells, and validating biomarkers of aging in vivo.

EXPERT OPINION

Proteomic and multi-omic approaches will be important for the development of senescence-based biomarkers to facilitate and monitor future therapeutic interventions that target senescent cells.