A mass spectrometric-derived cell surface protein atlas

Evaluation of tumor targets selected from public genomic databases for imaging of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a 5-year survival rate of approximately 5-7%, and complete surgical resection remains the only curative treatment but is often unfeasible. Fluorescence-guided surgery (FGS) using tumor-targeted probes may improve tumor visualization and facilitate complete resection. This study aimed to identify and validate tumor targets for FGS during PDAC resection procedures. RNA expression data from over 4000 cell surface genes, obtained from public genomic databases, were analyzed to identify genes encoding PDAC-associated proteins. Eleven potential tumor targets were identified, including CEACAM5, TMPRSS4, COL17A1, CLDN18, and AQP5. Protein expression was evaluated by immunohistochemistry (IHC) in tissues from 44 PDAC and 7 chronic pancreatitis (CP) patients. All targets, except COL17A1, showed significantly higher expression in PDAC tissue compared to healthy pancreatic, CP, and duodenal tissue (p < 0.001), as well as in tumor-positive versus tumor-negative lymph nodes. Especially CEACAM5, TMPRSS4, and AQP5 were identified as the most promising targets for distinguishing PDAC from healthy tissues and detecting lymph node metastasis during FGS. The development of probes targeting multiple markers, such as AQP5 with CEACAM5 and/or TMPRSS4, may help overcome interpatient variability and enhance detection across patients.

Taurine from tumour niche drives glycolysis to promote leukaemogenesis

Signals from the microenvironment are known to be critical for development, stem cell self-renewal and oncogenic progression. Although some niche-driven signals that promote cancer progression have been identified1-5, concerted efforts to map disease-relevant microenvironmental ligands of cancer stem cell receptors have been lacking. Here, we use temporal single-cell RNA-sequencing (scRNA-seq) to identify molecular cues from the bone marrow stromal niche that engage leukaemia stem-enriched cells (LSCs) during oncogenic progression. We integrate these data with our human LSC RNA-seq and in vivo CRISPR screen of LSC dependencies6 to identify LSC-niche interactions that are essential for leukaemogenesis. These analyses identify the taurine-taurine transporter (TAUT) axis as a critical dependency of aggressive myeloid leukaemias. We find that cysteine dioxygenase type 1 (CDO1)-driven taurine biosynthesis is restricted to osteolineage cells, and increases during myeloid disease progression. Blocking CDO1 expression in osteolineage cells impairs LSC growth and improves survival outcomes. Using TAUT genetic loss-of-function mouse models and patient-derived acute myeloid leukaemia (AML) cells, we show that TAUT inhibition significantly impairs in vivo myeloid leukaemia progression. Consistent with elevated TAUT expression in venetoclax-resistant AML, TAUT inhibition synergizes with venetoclax to block the growth of primary human AML cells. Mechanistically, our multiomic approaches indicate that the loss of taurine uptake inhibits RAG-GTP dependent mTOR activation and downstream glycolysis. Collectively, our work establishes the temporal landscape of stromal signals during leukaemia progression and identifies taurine as a key regulator of myeloid malignancies.

Identifying Immunomodulatory Subpopulations of Adipose Stromal Vascular Fraction and Stem/Stromal Cells Through Single-Cell Transcriptomics and Bulk Proteomics

A primary therapeutic characteristic of mesenchymal stem/stromal cells (MSCs) is their immunomodulatory activity. Adipose-derived stem/stromal cells (ASCs) are an abundant and easily isolated source of MSCs shown to have high immunosuppressive activity, making them attractive for therapy. Understanding the heterogeneous immunomodulatory potential of ASCs within the stromal vascular fraction (SVF) of adipose tissue could better inform treatment strategies. In this study, we integrate single-cell RNA sequencing (scRNA seq) with bulk proteomics to characterize subpopulations of SVF-derived ASCs that are phenotypically similar to cytokine-licensed, cultured ASCs. To better define the licensing process, we present scRNA seq and bulk proteomics data of cultured (P2) ASCs exposed to inflammatory cytokines, showing enrichment of pathways related to inflammation and apoptosis that positively correlate to the cytokine-mediated, trajectory-derived pseudotime. Using the Scissor algorithm, we integrate the proteomics data with uncultured (P0) SVF scRNA seq data, identifying an ASC subpopulation that is phenotypically like the cytokine-stimulated ASCs (Scissor-positive). Interactome analysis identifies Scissor-positive ASCs as stress adaptive immune regulators that function through IL6 and broad SEMA4 interactions and higher Visfatin signaling, while Scissor-negative ASCs show strong signatures of ECM remodeling through FN1 and immunosuppression through THY1 and MIF signaling. Our multimodal, integrative approach enabled identification of previously unidentified, distinct ASC subpopulations with differing immunomodulatory phenotypes that are present in, and can potentially be selected from, P0 SVF ASCs.

Identification of the Staphylococcus aureus endothelial cell surface interactome by proximity labeling

Virulence strategies of pathogens depend on interaction with host cells. The binding and activation of receptors located on the plasma membrane are crucial for the attachment to or pathogen internalization by host cells. Identifying host cell receptors is often difficult, and hence, the identity of many proteins that play important roles during host-pathogen interaction remains elusive. We developed a novel proximity labeling approach by decorating the opportunistic pathogen Staphylococcus aureus with ascorbate peroxidase 2. Upon addition of hydrogen peroxide, the peroxidase initiates proximity biotinylation of S. aureus host interaction partners, thereby enabling the identification of these proteins. Here, we demonstrate an endothelial cell surface interactome of 305 proteins, including novel S. aureus co-receptors such as neuronal adhesion molecule, protein tyrosine kinase PTK7, melanotransferrin, protein-tyrosine kinase MET, and CD109. Filtering the interactome for validated surface proteins resulted in a list of 89 protein candidates, 53% of which were described to interact with S. aureus or other pathogens.

IMPORTANCE

Staphylococcus aureus is an opportunistic pathogen that enters host cells such as epithelial or endothelial cells. Intracellular pathogens have been observed in vivo and are thought to serve immune evasion, avoidance of antibiotic treatment, and chronicity of infection. Thus, it is important to understand the mechanisms by which the bacteria are internalized by host cells; however, screening for pathogen-host receptors is difficult. Here, we developed a novel proximity labeling approach, which enabled the identification of several previously unknown host receptors of S. aureus that are engaged during a rapid uptake pathway for the bacteria.

Engaging T cells for cleanup

T-cell engagers represent a transformative approach to cancer immunotherapy leveraging bispecific and multispecific antibody constructs to redirect T-cell cytotoxicity toward malignant cells. These molecules bridge T cells and tumor cells by simultaneously binding CD3 on T cells and tumor-associated antigens on cancer cells, thereby enabling precise immune targeting even in immunologically "cold" tumors. Recent advancements include conditional T-cell engagers activated by tumor microenvironment proteases to minimize off-tumor toxicity as well as T-cell receptor-based engagers targeting intracellular antigens via MHC presentation. Clinical successes, such as Kimmtrak in metastatic uveal melanoma, underscore good potential of these modalities, while challenges persist in the management of cytokine release syndrome, neurotoxicity, and tumor resistance. Emerging multispecific engagers are aimed at enhancing efficacy via incorporation of costimulatory signals, thus offering a promising trajectory for next-generation immunotherapies. T-cell engagers are also gaining attention in the treatment of autoimmune disorders, where they can be designed to selectively modulate pathogenic immune responses. By targeting autoreactive T or B cells, T-cell engagers hold promise for restoring immune tolerance in such conditions as HLA-B*27-associated autoimmunity subtypes, multiple sclerosis, rheumatoid arthritis, and type 1 diabetes mellitus. Engineering strategies that incorporate inhibitory receptors or tissue-specific antigens may further refine T-cell engagers' therapeutic potential in autoimmunity, by minimizing systemic immunosuppression while preserving immune homeostasis.

Cellular immunotherapy targeting CLL-1 for juvenile myelomonocytic leukemia

Juvenile myelomonocytic leukemia (JMML) is a myeloproliferative disorder that predominantly affects infants and young children. Hematopoietic stem cell transplantation (HSCT) is standard of care, but post-HSCT relapse is common, highlighting the need for innovative therapies. While adoptive immunotherapy with chimeric antigen receptor (CAR) T cells has improved outcomes for patients with advanced lymphoid malignancies, it has not been comprehensively evaluated in JMML. In the present study, we use bulk and single-cell RNA sequencing, mass spectrometry, and flow cytometry to identify overexpression of CLL-1 (encoded by CLEC12A) on the cell surface of cells from patients with JMML. We develop immunotherapy with CLL-1 CAR T cells (CLL1CART) for preclinical testing and report in vitro and in vivo anti-leukemia activity. Notably, CLL1CART reduce the number of leukemic stem cells and serial transplantability in vivo. These preclinical data support the development and clinical investigation of CLL-1-targeting immunotherapy in children with relapsed/refractory JMML.

Engineered Proteins and Chemical Tools to Probe the Cell Surface Proteome

The cell surface proteome, or surfaceome, is the hub for cells to interact and communicate with the outside world. Many disease-associated changes are hard-wired within the surfaceome, yet approved drugs target less than 50 cell surface proteins. In the past decade, the proteomics community has made significant strides in developing new technologies tailored for studying the surfaceome in all its complexity. In this review, we first dive into the unique characteristics and functions of the surfaceome, emphasizing the necessity for specialized labeling, enrichment, and proteomic approaches. An overview of surfaceomics methods is provided, detailing techniques to measure changes in protein expression and how this leads to novel target discovery. Next, we highlight advances in proximity labeling proteomics (PLP), showcasing how various enzymatic and photoaffinity proximity labeling techniques can map protein-protein interactions and membrane protein complexes on the cell surface. We then review the role of extracellular post-translational modifications, focusing on cell surface glycosylation, proteolytic remodeling, and the secretome. Finally, we discuss methods for identifying tumor-specific peptide MHC complexes and how they have shaped therapeutic development. This emerging field of neo-protein epitopes is constantly evolving, where targets are identified at the proteome level and encompass defined disease-associated PTMs, complexes, and dysregulated cellular and tissue locations. Given the functional importance of the surfaceome for biology and therapy, we view surfaceomics as a critical piece of this quest for neo-epitope target discovery.

Acetylation-ubiquitination crosstalk of DJ-1 mediates microcalcification formation in diabetic plaques via collagen-matrix vesicles interaction

AIMS

Microcalcification increases the vulnerability of plaques and has become an important driver of acute cardiovascular events in diabetic patients. However, the regulatory mechanisms remain unclear. DJ-1, a multifunctional protein, may play a potential role in the development of diabetic complications. Therefore, this study aims to explore the relationship between DJ-1 and microcalcification in diabetic plaques and investigate the mechanisms.

METHODS AND RESULTS

The regulatory relationship between DJ-1 and diabetic vascular microcalcification was determined in anterior tibial arteries from diabetic foot amputated patients, a diabetic apolipoprotein E-deficient (ApoE-/-) mouse model, and a vascular smooth muscle cell (VSMC) model. The ubiquitination and acetylation levels of DJ-1 were detected, and the acetylation-ubiquitination crosstalk was explored. Then, the regulatory effects of DJ-1 on receptor for advanced glycation end products (RAGE) were clarified. Further, the role of DJ-1 in collagen-matrix vesicles (MVs) interaction in diabetic microenvironment was observed. The collagen interacting surface protein of MVs was verified with proteomics and the biomimetic MVs model. In clinical samples, the number of microcalcification nodules in anterior tibial artery plaques was negatively correlated with DJ-1 expression. In diabetic ApoE-/- mice and VSMCs models, knocking down DJ-1 significantly increased the number of microcalcified nodules. N-acetyltransferase 10 (NAT10) was an acetyltransferase of DJ-1. NAT10 could crosstalk the ubiquitination of DJ-1 and enhance the ubiquitination of DJ-1 by E3 ubiquitin ligase tripartite motif-containing protein 32 (TRIM32). Besides, the knockdown of DJ-1 activated signal transducer and activator of transcription 1 (STAT1), and then STAT1 could bind to RAGE promoter, thus up-regulating RAGE. Furthermore, the knockdown of DJ-1 significantly promoted collagen-MVs interaction in diabetic microenvironment. Milk fat globule epidermal growth factor 8 (MFGE8) may serve as a collagen-interacting protein. The coating of MFGE8 protein could increase the interaction between collagen and biomimetic MVs.

CONCLUSION

In the diabetic microenvironment, DJ-1 was a protective factor for vascular microcalcification. NAT10- and TRIM32-mediated acetylation-ubiquitination crosstalk resulted in the degradation of DJ-1. The decrease of DJ-1 could activate DJ-1/STAT1/RAGE microcalcification signal. Further, under the stimulation of DJ-1-mediated microcalcification signal, VSMCs released MVs with high abundance of MFGE8. MFGE8 promoted collagen-MVs interaction and finally accelerated the formation of microcalcification.

Dissection of single-cell landscapes for the development of chimeric antigen receptor T cells in Hodgkin lymphoma

ABSTRACT

The success of targeted therapies for hematological malignancies has heralded their potential as both salvage treatment and early treatment lines, reducing the need for high-dose, intensive, and often toxic chemotherapeutic regimens. For young patients with classic Hodgkin lymphoma (cHL), immunotherapies provide the possibility to lessen long-term, treatment-related toxicities. However, suitable therapeutic targets are lacking. By integrating single-cell dissection of the tumor landscape and an in-depth, single-cell-based off-tumor antigen prediction, we identify CD86 as a promising therapeutic target in cHL. CD86 is highly expressed on Hodgkin and Reed-Sternberg cancer cells and cHL-specific tumor-associated macrophages. We reveal CD86-CTLA-4 as a key suppressive pathway in cHL, driving T-cell exhaustion. Cellular therapies targeting CD86 had extraordinary efficacy in vitro and in vivo and were safe in immunocompetent mouse models without compromising bacterial host defense in sepsis models. Our results prove the potential value of anti-CD86 immunotherapies for treating cHL.

Human sensory-like neuron surfaceome analysis

Acral and triggerable pain is a hallmark of diseases involving small nerve fiber impairment, yet the underlying cellular mechanisms remain elusive. A key role is attributed to pain-related proteins located within the neuronal plasma membrane of nociceptive neurons. To explore this, we employed human induced pluripotent stem cell-derived sensory-like neurons and enriched their surface proteins by biotinylation. Samples from three independent cell differentiations were analyzed via liquid chromatography tandem mass spectrometry. Detected proteins were categorized by cellular location and function, followed by generating an interaction network for deregulated surface proteins. Gene expression of selected proteins was quantified using real-time PCR. A comparative analysis was performed between a patient with Fabry disease (FD) and a healthy control, which we used as model system. We successfully extracted surfaceome proteins from human sensory-like neurons, revealing deregulation of 48 surface proteins in FD-derived neurons. Among the candidates with potential involvement in pain pathophysiology were CACNA2D3, GPM6A, EGFR, and ABCA7. Despite the lack of gene expression differences in these candidates, the interaction network indicated compromised neuronal network integrity. Our approach successfully enabled the extraction and comprehensive analysis of the surfaceome from human sensory-like neurons, establishing a novel methodological framework for investigating human sensory-like neuron biology and cellular disease mechanisms.

High-throughput capture and in situ protein analysis of extracellular vesicles by chemical probe-based array

Extracellular vesicles (EVs) are small particles with phospholipid bilayers that carry a diverse range of cargoes including nucleic acids, proteins and metabolites. EVs have important roles in various cellular processes and are increasingly recognized for their ubiquitous role in cell-cell communications and potential applications in therapeutics and diagnostics. Although many methods have been developed for the characterization and measurement of EVs, analyzing them from biofluids remains a challenge with regard to throughput and sensitivity. Recently, we introduced an approach to facilitate high-throughput analysis of EVs from trace amounts of sample. In this method, an amphiphile-dendrimer supramolecular probe (ADSP) is coated onto a nitrocellulose membrane for array-based capture and to enable an in situ immunoblotting assay. Here, we describe the protocol for our array-based method of EV profiling. We describe an enhanced version of the method that incorporates an automated printing workstation, ensuring high throughput and reproducibility. We further demonstrate the use of our array to profile specific glycosylations on the EV surface using click chemistry of an azide group introduced by metabolic labeling. In this protocol, the synthesis of ADSP and the fabrication of ADSP nitrocellulose membrane array can be completed on the same day. EVs are efficiently captured from biological or clinical samples through a 30-min incubation, followed by an immunoblotting assay within a 3-h window, thus providing a high-throughput platform for EV isolation and in situ targeted analysis of EV proteins and their modifications.

The Proteomic Landscape of the Coronary Accessible Heart Cell Surfaceome

Cell surface proteins (surfaceome) represent key signalling and interaction molecules for therapeutic targeting, biomarker profiling and cellular phenotyping in physiological and pathological states. Here, we employed coronary artery perfusion with membrane-impermeant biotin to label and capture the surface-accessible proteome in the neo-native (intact) heart. Using quantitative proteomics, we identified 701 heart cell surfaceome accessible by the coronary artery, including receptors, cell surface enzymes, adhesion and junctional molecules. This surfaceome comprises to 216 cardiac cell-specific surface proteins, including 29 proteins reported in cardiomyocytes (CXADR, CACNA1C), 12 in cardiac fibroblasts (ITGA8, COL3A1) and 63 in multiple cardiac cell types (ICAM1, SLC3A2, CDH2). Further, this surfaceome comprises to 53 proteins enriched in heart tissue compared to other tissues in humans and implicated in cardiac cell signalling networks involving cardiomyopathy (CDH2, DTNA, PTKP2, SNTA1, CAM, K2D/B), cardiac muscle contraction and development (ENG, SNTA1, SGCG, MYPN), calcium ion binding (SGCA, MASP1, THBS4, FBLN2, GSN) and cell metabolism (SDHA, NUDFS1, GYS1, ACO2, IDH2). This method offers a powerful tool for dissecting the molecular landscape of the coronary artery accessible heart cell surfaceome, its role in maintaining cardiac and vascular function, and potential molecular leads for studying cardiac cell interactions and systemic delivery to the neo-native heart.

Deep profiling of gene expression across 18 human cancers

Clinical and biological information in large datasets of gene expression across cancers could be tapped with unsupervised deep learning. However, difficulties associated with biological interpretability and methodological robustness have made this impractical. Here we describe an unsupervised deep-learning framework for the generation of low-dimensional latent spaces for gene-expression data from 50,211 transcriptomes across 18 human cancers. The framework, which we named DeepProfile, outperformed dimensionality-reduction methods with respect to biological interpretability and allowed us to unveil that genes that are universally important in defining latent spaces across cancer types control immune cell activation, whereas cancer-type-specific genes and pathways define molecular disease subtypes. By linking latent variables in DeepProfile to secondary characteristics of tumours, we discovered that mutation burden is closely associated with the expression of cell-cycle-related genes, and that the activity of biological pathways for DNA-mismatch repair and MHC class II antigen presentation are consistently associated with patient survival. We also found that tumour-associated macrophages are a source of survival-correlated MHC class II transcripts. Unsupervised learning can facilitate the discovery of biological insight from gene-expression data.

Methylstat sensitizes ovarian cancer cells to PARP-inhibition by targeting the histone demethylases JMJD1B/C

PARP-inhibitors (PARPi) are an integral part of ovarian cancer treatment. However, overcoming acquired PARPi resistance or increasing the benefit of PARPi in patients without homologous recombination deficiency (HRD) remains an unmet clinical need. We sought to identify genetic modulators of PARPi response, guiding pharmacological PARPi sensitization. CRISPR-Cas9 mediated loss-of-function screen with a focused sgRNA library revealed that DNA-demethylases JMJD1B/JMJD1C, targetable by the small inhibitor methylstat, promote PARPi resistance. Methylstat synergistically interacted with olaparib, and (re-)sensitized ovarian cancer cells to PARPi treatment, surpassing the efficacy of common demethylase inhibitors. Genetic knockout of JMJD1B and/or JMJD1C phenocopied the effect of methylstat in an additive manner. Validation studies revealed methylstat to be a universal PARPi-sensitizing drug, effective, regardless of PARPi resistance status or BRCA1 mutational background. Methylstat modulated clonal cancer dynamics by mitigating positive selection of PARPi-resistant or BRCA1-proficient cells under olaparib treatment. Using a model of PARPi-induced cellular toxicity, we showed that methylstat impairs cellular DNA repair, indicated by an increased susceptibility of ovarian cancer cells to olaparib-induced DNA double strand breaks after methylstat exposure. This study proposes the histone demethylase inhibitor methylstat as an epigenetic drug for overcoming PARPi-resistance or for increasing efficacy of PARPi beyond HRD in ovarian cancer patients.

Novel Assignment of Gene Markers to Hematological and Immune Cells Based on Single-Cell Transcriptomics

There are many different cells that perform highly specialized functions in the human hematological and immune systems. Due to the relevance of their activity, in this work we investigated the cell types and subtypes that form this complex system, using single-cell RNA sequencing (scRNA-seq) to dissect and assess the markers that best define each cell population. We first developed an optimized computational workflow for analyzing large scRNA-seq datasets. We then used it to find gene markers of the different cell types present in bone marrow (BM) and peripheral blood (PB). We analyzed three different single-cell datasets to find specific cell markers using this strategy: first, we searched in the CD marker genes and then in the genes encoding membrane proteins and finally in all detected protein-coding genes. This allowed us not only to confirm known CDs that best mark some cell types (e.g., monocytes, B cells, NK cells, etc.) but also to test the ability of new genes to distinguish specific cell types. Finally, we applied a machine learning method (Random Forest) to test the accuracy of the different markers we found. As a result of all this work, we have found and propose specific and robust gene signatures to identify different types and subtypes of hematological and immune cells.

Optimized Biotinylated Peptide Detection Method for Characterizing the Cell Surface Proteome

Cell surface proteins (CSPs) play a pivotal role in cellular processes and are crucial for differentiating various cell types. Despite the significance of the cell surface-localized proteome, it is often characterized using low-throughput techniques that provide limited information from the surface-exposed protein segments of individual cells. If such information is available, it is often scattered across numerous publications, making it time-consuming to gather. To address these challenges, we present a high-throughput method that utilizes biotinylation of accessible primary amino groups within the extracellular regions of CSPs to simultaneously generate several hundred CSP-specific peptides in a single experiment. The steps of the method have been meticulously refined to capture an increasing number of cell type-specific biotinylated peptides localized in cell surface accessible protein regions.The protocol developed is readily applicable to the analysis of both soluble and adherent cell surface proteins as described in detailed in this paper. Additionally, the method can be used for side-selective protein biotinylation on biological barrier-forming epithelial cells, allowing the qualitative and quantitative characterization of proteins in both their apical and basolateral membranes. The identified amino-modified surface peptides derived from CSPs have potential as targets for various molecular biology research applications, including antibody staining, inhibitor development and monitoring of host-pathogen interactions. Furthermore, label-free quantification of CSPs via mass spectrometry (based on identified peptide list) provides valuable insights into their relative abundance in different cell surface or plasma membrane regions.

Arrayed CRISPR libraries for the genome-wide activation, deletion and silencing of human protein-coding genes

Arrayed CRISPR libraries extend the scope of gene-perturbation screens to non-selectable cell phenotypes. However, library generation requires assembling thousands of vectors expressing single-guide RNAs (sgRNAs). Here, by leveraging massively parallel plasmid-cloning methodology, we show that arrayed libraries can be constructed for the genome-wide ablation (19,936 plasmids) of human protein-coding genes and for their activation and epigenetic silencing (22,442 plasmids), with each plasmid encoding an array of four non-overlapping sgRNAs designed to tolerate most human DNA polymorphisms. The quadruple-sgRNA libraries yielded high perturbation efficacies in deletion (75-99%) and silencing (76-92%) experiments and substantial fold changes in activation experiments. Moreover, an arrayed activation screen of 1,634 human transcription factors uncovered 11 novel regulators of the cellular prion protein PrPC, screening with a pooled version of the ablation library led to the identification of 5 novel modifiers of autophagy that otherwise went undetected, and 'post-pooling' individually produced lentiviruses eliminated template-switching artefacts and enhanced the performance of pooled screens for epigenetic silencing. Quadruple-sgRNA arrayed libraries are a powerful and versatile resource for targeted genome-wide perturbations.

2D Nano-Photosensitizer Facilitates Proximity Labeling for Living Cells Surfaceome Deciphering

Photocatalytic proximity labeling has shown great promise for mapping the spatiotemporal dynamics of surfaceome. Although cell-surface targeting photosensitizers relying on antibodies, lipid molecules, and metabolic labeling have gained effects, the development of simpler and stable methods that avoid complex chemical synthesis and biosynthesis steps is still a huge challenge. Here, the study has introduced 2D nanomaterials with the ability of cell surface engineering to perform the in situ anchoring of photosensitizer on living cell surface. Photosensitizer can be stabilized on nanomaterials by coordination after one-step mixing, resulting in the nano-photosensitizer combining cell surface targeting ability and photosensitivity that allowing surface-specific proximity labeling. Nano-photosensitizer can be dispersed stably in aqueous solution, avoiding the defects of poor water solubility and aggregation of traditional organic photosensitizers. Singlet oxygen is generated locally under light irradiation, enabling spatiotemporally-resolved activating and labeling of cell surface proteome. Further application in the brain metastatic lung cancer has been found effective with numerous quantified differential cell surfaces proteins highly correlated with cancer metastasis and three potential players have been validated via immunoblotting and immunofluorescence, providing important insights for metastasis supported molecular mechanism.

Multiple myeloma long-term survivors exhibit sustained immune alterations decades after first-line therapy

The long-term consequences of cancer and its therapy on the patients' immune system years after cancer-free survival remain poorly understood. Here, we present an in-depth characterization of the bone marrow immune ecosystem of multiple myeloma long-term survivors, from initial diagnosis up to 17 years following a single therapy line and cancer-free survival. Using comparative single-cell analyses combined with molecular, genomic, and functional approaches, we demonstrate that multiple myeloma long-term survivors exhibit pronounced alterations in their bone marrow microenvironment associated with impaired immunity. These immunological alterations were frequently linked to an inflammatory immune circuit fueled by the long-term persistence or resurgence of residual myeloma cells. Notably, even in the complete absence of any detectable residual disease for decades, sustained changes in the immune system were observed, suggesting an irreversible 'immunological scarring' caused by the initial exposure to the cancer and therapy. Collectively, our study provides key insights into the molecular and cellular bone marrow ecosystem of long-term survivors of multiple myeloma, revealing both reversible and irreversible alterations in the immune compartment.

Unlocking Intracellular Oncology Targets: The Unique Role of Antibody-Based T-Cell Receptor Mimic (TCRm) Therapeutics in T-Cell Engagers (TCEs) and Antibody-Drug Conjugates (ADCs)

Effectively targeting intracellular tumor-associated proteins presents a formidable challenge in oncology, as they are traditionally considered inaccessible to conventional antibody-based therapies and CAR-T cell therapies. However, recent advancements in antibody engineering have revolutionized this field, offering promising new strategies to combat cancer. This review focuses on the innovative use of T-cell receptor mimic (TCRm) antibodies within the therapeutic frameworks of T-cell engagers (TCE) and antibody-drug conjugates (ADCs). TCRm antibodies, designed to recognize peptide-MHC complexes rather than cell surface proteins, integrate the capacity of T-cells to reach intracellular targets with the unique strengths of antibodies. When incorporated into T-cell engaging therapeutics, TCRms redirect T cells to cancer cells, facilitating direct cytotoxicity. In ADCs, TCRm antibodies deliver cytotoxic agents with highly specific targeting to cancer cells, sparing healthy tissues. Together, these antibody-based strategies represent a significant leap forward in oncology, opening new avenues for the treatment of cancers previously deemed untreatable, with other potential applications in autoimmune diseases. This review discusses the mechanisms, clinical advancements, and future prospects of these cutting-edge therapies, highlighting their potential to transform the landscape of cancer treatment.

Extracellular proximal interaction profiling by cell surface-targeted TurboID reveals LDLR as a partner of liganded EGFR

Plasma membrane proteins play pivotal roles in receiving and transducing signals from other cells and from the environment and are vital for cellular functionality. Enzyme-based, proximity-dependent approaches, such as biotin identification (BioID), combined with mass spectrometry have begun to illuminate the landscape of proximal protein interactions within intracellular compartments. To extend the potential of these approaches to study the extracellular environment, we developed extracellular TurboID (ecTurboID), a method designed to profile the interactions between proteins on the surfaces of living cells over short timescales using the fast-acting biotin ligase TurboID. After optimizing our experimental and data analysis strategies to capture extracellular proximity interactions, we used ecTurboID to reveal the proximal interactomes of several plasma membrane proteins, including the epidermal growth factor receptor (EGFR). We found that EGF stimulation induced an association between EGFR and the low-density lipoprotein receptor (LDLR) and changed the interactome of LDLR by increasing its proximity with proteins that regulate EGFR signaling. The identification of this interaction between two well-studied and clinically relevant receptors illustrates the utility of our modified proximity labeling methodology for identifying dynamic extracellular associations between plasma membrane proteins.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer (BC) is defined by distinct molecular subtypes with different cells of origin. The transcriptional networks that characterize the subtype-specific tumor-normal lineages are not established. In this work, we applied bulk, single-cell and single-nucleus multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 patients with BC to show characteristic links in gene expression and chromatin accessibility between BC subtypes and their putative cells of origin. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal BC and luminal mature cells and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like (SOX6 and KCNQ3) and luminal A/B (FAM155A and LRP1B) lineages. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like BC, suggesting an altered means of immune dysfunction. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single-cell level is a powerful tool for investigating cancer lineage and highlight transcriptional networks that define basal and luminal BC lineages.

A proteomic atlas of glypican-3 interacting partners: Identification of alpha-fetoprotein and other extracellular proteins as potential immunotherapy targets in liver cancer

Antibody and cell-based therapeutics targeting cell surface receptors have emerged as a major class of immune therapeutics for treating cancer. However, the number of cell surface targets for cancer immunotherapy remains limited. Glypican-3 (GPC3) is a cell surface proteoglycan and an oncofetal antigen. In this study, we report a large-scale tumor-associated GPC3 co-immunoprecipitation (CoIP)-proteomic study using liver cancer xenograft tumors in mice. We identified 153 GPC3-associated proteins through mass spectrometry. To identify potential drug targets, we categorized GPC3-associated proteins based on their subcellular locations using UniProt annotations, with a focus on extracellular proteins. Additionally, we annotated differentially expressed proteins in hepatocellular carcinoma (HCC) versus non-tumor liver samples based on the literature, analyzed expression levels in tumor versus normal tissues using TCGA and GTEx databases via GEPIA, and identified prognostic liver cancer markers according to GEPIA. Among GPC3-associated proteins, Immunoglobulin Superfamily Member 1 (IGSF1), alpha-fetoprotein (AFP), FAT Atypical Cadherin 1 (FAT1), Formin 1 (FMN1), and Guanylate Cyclase 2C (GUCY2C), were identified as potential therapeutic targets. Furthermore, we validated the direct protein interaction between GPC3 and AFP through immunoprecipitation with purified proteins and through co-localization imaging using immunofluorescence microscopy. This study provides large proteomic datasets related to GPC3-associated proteins, enhancing our understanding of glypican biology in cancer cells and offering a new approach to identifying immunotherapy targets.

Cell-surface Milieu Remodeling in Human Dendritic Cell Activation

Dendritic cells (DCs) are specialized sentinel and APCs coordinating innate and adaptive immunity. Through proteins on their cell surface, DCs sense changes in the environment, internalize pathogens, present processed Ags, and communicate with other immune cells. By combining chemical labeling and quantitative mass spectrometry, we systematically profiled and compared the cell-surface proteomes of human primary conventional DCs (cDCs) in their resting and activated states. TLR activation by a lipopeptide globally reshaped the cell-surface proteome of cDCs, with >100 proteins upregulated or downregulated. By simultaneously elevating positive regulators and reducing inhibitory signals across multiple protein families, the remodeling creates a cell-surface milieu promoting immune responses. Still, cDCs maintain the stimulatory-to-inhibitory balance by leveraging a distinct set of inhibitory molecules. This analysis thus uncovers the molecular complexity and plasticity of the cDC cell surface and provides a roadmap for understanding cDC activation and signaling.

Sphingosine-1 phosphate receptor 1 (S1PR1) expression maintains stemness of acute myeloid leukemia stem cells

Acute myeloid leukemia (AML) arises from leukemia stem cells (LSCs) and is maintained by cells which have acquired features of stemness. We compared transcription profiles of AML cells with/without stem cell features defined as in vitro clonogenicity and serial engraftment in immune-deficient mice xenograft model. We used multi-parameter flow cytometry (MPFC) to separate CD34+ bone marrow-derived leukemia cells into sphingosine-1 phosphate receptor 1 (S1PR1)+ and S1PR1- fractions. Cells in the S1PR1+ fraction demonstrated significantly higher clonogenicity and higher engraftment potential compared with those in the S1PR1- fraction. In contrast, CD34+ bone marrow cells from normal samples showed reduced clonogenicity in the S1PR1+ fraction compared with the S1PR1- fraction. Inhibition of S1PR1 expression in an AML cell line reduced the colony-forming potential of KG1 cells. Transcriptomic analyses and rescue experiments indicated PI3K/AKT pathway and MYBL2 are downstream mediators of S1PR1-associated stemness. These findings implicate S1PR1 as a functional biomarker of LSCs and suggest its potential as a therapeutic target in AML treatment.

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.

Mapping the cancer surface proteome in search of target antigens for immunotherapy

Immune-based therapeutic interventions recognizing proteins localized on the cell surface of cancer cells are emerging as a promising cancer treatment. Antibody-based therapies and engineered T cells are now approved by the Food and Drug Administration to treat some malignancies. These therapies utilize a few cell surface proteins highly expressed on cancer cells to release the negative regulation of immune activation that limits antitumor responses (e.g., PD-1, PD-L1, CTLA4) or to redirect the T cell specificity toward blood cancer cells (e.g., CD19 and B cell maturation antigen). One limitation preventing broader application of these novel therapeutic strategies to all cancer types is the lack of suitable target antigens for all indications owing in part to the challenges in identifying such targets. Ideal target antigens are cell surface proteins highly expressed on malignant cells and absent in healthy tissues. Technological advances in mass spectrometry, enrichment protocols, and computational tools for cell surface protein isolation and annotation have recently enabled comprehensive analyses of the cancer cell surface proteome, from which novel immunotherapeutic target antigens may emerge. Here, we review the most recent progress in this field.

Lentiviral vector determinants of anion-exchange chromatography elution heterogeneity

The demand for Lentiviral Vector (LV) drug substance is increasing. However, primary capture using convective anion-exchange chromatography remains a significant manufacturing challenge. This stems from a poor understanding of the complex adsorption behaviors linked to LVs intricate and variable structure, such as high binding heterogeneity which is typically characterized by a gradient elution profile consisting of two peaks. Understanding which LV structural components drive these phenomena is therefore crucial for rational process design. This work identifies the key LV envelope components responsible for binding to quaternary-amine membrane adsorbents. Eliminating the pseudotype protein (Vesicular Stomatitis Virus G glycoprotein [VSV-G]) did not impact the heterogenous two-peak elution profile, suggesting it is not a major binding species. Digestion of envelope glycosaminoglycans (GAGs), present on proteoglycans, leads to a dramatic reduction in the proportion of vector eluted in peak 2, decreasing from 50% to 3.1%, and a threefold increase in peak 1 maximum. Data from reinjection experiments point towards interparticle envelope heterogeneity from discrete LV populations, where the two-peak profile emerges from a subpopulation of LVs interacting via highly charged GAGs (peak 2) along with a weaker binding population likely interacting through the phospholipid membrane and envelope protein (peak 1).

SLAPSHOT reveals rapid dynamics of extracellularly exposed proteome in response to calcium-activated plasma membrane phospholipid scrambling

To facilitate our understanding of proteome dynamics during signaling events, robust workflows affording fast time resolution without confounding factors are essential. We present Surface-exposed protein Labeling using PeroxidaSe, H2O2, and Tyramide-derivative (SLAPSHOT) to label extracellularly exposed proteins in a rapid, specific, and sensitive manner. Simple and flexible SLAPSHOT utilizes recombinant soluble APEX2 protein applied to cells, thus circumventing the engineering of tools and cells, biological perturbations, and labeling biases. We applied SLAPSHOT and quantitative proteomics to examine the TMEM16F-dependent plasma membrane remodeling in WT and TMEM16F KO cells. Time-course data ranging from 1 to 30 min of calcium stimulation revealed co-regulation of known protein families, including the integrin and ICAM families, and identified proteins known to reside in intracellular organelles as occupants of the freshly deposited extracellularly exposed membrane. Our data provide the first accounts of the immediate consequences of calcium signaling on the extracellularly exposed proteome.

Pan-cancer proteogenomics expands the landscape of therapeutic targets

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

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.

trans-Interacting Plasma Membrane Proteins and Binding Partner Identification

Plasma membrane proteins (PMPs) play critical roles in a myriad of physiological and disease conditions. A unique subset of PMPs functions through interacting with each other in trans at the interface between two contacting cells. These trans-interacting PMPs (tiPMPs) include adhesion molecules and ligands/receptors that facilitate cell-cell contact and direct communication between cells. Among the tiPMPs, a significant number have apparent extracellular binding domains but remain orphans with no known binding partners. Identification of their potential binding partners is therefore important for the understanding of processes such as organismal development and immune cell activation. While a number of methods have been developed for the identification of protein binding partners in general, very few are applicable to tiPMPs, which interact in a two-dimensional fashion with low intrinsic binding affinities. In this review, we present the significance of tiPMP interactions, the challenges of identifying binding partners for tiPMPs, and the landscape of method development. We describe current avidity-based screening approaches for identifying novel tiPMP binding partners and discuss their advantages and limitations. We conclude by highlighting the importance of developing novel methods of identifying new tiPMP interactions for deciphering the complex protein interactome and developing targeted therapeutics for diseases.

Shifts in receptors during submergence of an encephalitic arbovirus

Western equine encephalitis virus (WEEV) is an arthropod-borne virus (arbovirus) that frequently caused major outbreaks of encephalitis in humans and horses in the early twentieth century, but the frequency of outbreaks has since decreased markedly, and strains of this alphavirus isolated in the past two decades are less virulent in mammals than strains isolated in the 1930s and 1940s1-3. The basis for this phenotypic change in WEEV strains and coincident decrease in epizootic activity (known as viral submergence3) is unclear, as is the possibility of re-emergence of highly virulent strains. Here we identify protocadherin 10 (PCDH10) as a cellular receptor for WEEV. We show that multiple highly virulent ancestral WEEV strains isolated in the 1930s and 1940s, in addition to binding human PCDH10, could also bind very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), which are recognized by another encephalitic alphavirus as receptors4. However, whereas most of the WEEV strains that we examined bind to PCDH10, a contemporary strain has lost the ability to recognize mammalian PCDH10 while retaining the ability to bind avian receptors, suggesting WEEV adaptation to a main reservoir host during enzootic circulation. PCDH10 supports WEEV E2-E1 glycoprotein-mediated infection of primary mouse cortical neurons, and administration of a soluble form of PCDH10 protects mice from lethal WEEV challenge. Our results have implications for the development of medical countermeasures and for risk assessment for re-emerging WEEV strains.

Cell surface protein-protein interaction profiling for biological network analysis and novel target discovery

The secretome is composed of cell surface membrane proteins and extracellular secreted proteins that are synthesized via secretory machinery, accounting for approximately one-third of human protein-encoding genes and playing central roles in cellular communication with the external environment. Secretome protein-protein interactions (SPPIs) mediate cell proliferation, apoptosis, and differentiation, as well as stimulus- or cell-specific responses that regulate a diverse range of biological processes. Aberrant SPPIs are associated with diseases including cancer, immune disorders, and illness caused by infectious pathogens. Identifying the receptor/ligand for a secretome protein or pathogen can be a challenging task, and many SPPIs remain obscure, with a large number of orphan receptors and ligands, as well as viruses with unknown host receptors, populating the SPPI network. In addition, proteins with known receptors/ligands may also interact with alternative uncharacterized partners and exert context-dependent effects. In the past few decades, multiple varied approaches have been developed to identify SPPIs, and these methods have broad applications in both basic and translational research. Here, we review and discuss the technologies for SPPI profiling and the application of these technologies in identifying novel targets for immunotherapy and anti-infectious agents.

Harnessing host enhancers of SARS-CoV-2 entry as novel targets for antiviral therapy

The WHO declared the official end of the SARS-CoV-2 caused public health emergency on May 5th, 2023, after two years in which the virus infected approximately 750 Mio individuals causing estimated up to 7 Mio deaths. Likely, the virus will continue to evolve in the human population as a seasonal respiratory pathogen. To now prevent severe infection outcomes in vulnerable individuals, effective antivirals are urgently needed to complement the protection provided by vaccines. SARS-CoV-2 enters its host cell via ACE2 mediated membrane fusion, either at the plasma membrane, if the protease TMPRSS2 is present or via the endosome, in a cathepsin dependent fashion. A small number of positive regulators of viral uptake were described in the literature, which are potentially useful targets for host directed antiviral therapy or biomarkers indicating increased or diminished susceptibility to infection. We identified here by cell surface proximity ligation novel proteins, required for efficient virion uptake. Importantly, chemical inhibition of one of these factors, SLC3A2, resulted in robust reduction of viral replication, to that achieved with a TMPRSS2 inhibitor. Our screen identified new host dependency factors for SARS-CoV-2 entry, which could be targeted by novel antiviral therapies.

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.

From bottom-up to cell surface proteomics: detergents or no detergents, that is the question

Measuring the expression levels of membrane proteins (MPs) is crucial for understanding cell differentiation and tissue specificity, defining disease characteristics, identifying biomarkers, and developing therapeutics. While bottom-up proteomics addresses the need for accurately surveying the membrane proteome, the lower abundance and hydrophobic nature of MPs pose challenges in sample preparation. As MPs normally reside in the lipid bilayer, conventional extraction methods rely on detergents, introducing here a paradox - detergents prevent aggregation and facilitate protein processing, but themselves become contaminants that interfere with downstream analytical applications. Various detergent removal methods exist to mitigate this issue, including filter-aided sample preparation, SP3, suspension trapping, and membrane mimetics. This review delves into the fundamentals of each strategy, applications, merits, and limitations, providing insights into their effectiveness in MP research.

Secretome of Cancer-Associated Fibroblasts (CAFs) Influences Drug Sensitivity in Cancer Cells

Resistance is a major problem with effective cancer treatment and the stroma forms a significant portion of the tumor mass but traditional drug screens involve cancer cells alone. Cancer-associated fibroblasts (CAFs) are a major tumor stroma component and its secreted proteins may influence the function of cancer cells. The majority of secretome studies compare different cancer or CAF cell lines exclusively. Here, we present the direct characterization of the secreted protein profiles between CAFs and KRAS mutant-cancer cell lines from colorectal, lung, and pancreatic tissues using multiplexed mass spectrometry. 2573 secreted proteins were annotated, and differential analysis highlighted understudied CAF-enriched secreted proteins, including Wnt family member 5B (WNT5B), in addition to established CAF markers, such as collagens. The functional role of CAF secreted proteins was explored by assessing its effect on the response to 97 anticancer drugs since stromal cells may cause a differing cancer drug response, which may be missed on routine drug screening using cancer cells alone. CAF secreted proteins caused specific effects on each of the cancer cell lines, which highlights the complexity and challenges in cancer treatment and so the importance to consider stromal elements.

Temporal Single Cell Analysis of Leukemia Microenvironment Identifies Taurine-Taurine Transporter Axis as a Key Regulator of Myeloid Leukemia

Signals from the microenvironment are known to be critical for development, sustaining adult stem cells, and for oncogenic progression. While candidate niche-driven signals that can promote cancer progression have been identified1-6, concerted efforts to comprehensively map microenvironmental ligands for cancer stem cell specific surface receptors have been lacking. Here, we use temporal single cell RNA-sequencing to identify molecular cues from the bone marrow stromal niche that engage leukemia stem cells (LSC) during oncogenic progression. We integrate these data with our RNA-seq analysis of human LSCs from distinct aggressive myeloid cancer subtypes and our CRISPR based in vivo LSC dependency map7 to develop a temporal receptor-ligand interactome essential for disease progression. These analyses identify the taurine transporter (TauT)-taurine axis as a critical dependency of myeloid malignancies. We show that taurine production is restricted to the osteolineage population during cancer initiation and expansion. Inhibiting taurine synthesis in osteolineage cells impairs LSC growth and survival. Our experiments with the TauT genetic loss of function murine model indicate that its loss significantly impairs the progression of aggressive myeloid leukemias in vivo by downregulating glycolysis. Further, TauT inhibition using a small molecule strongly impairs the growth and survival of patient derived myeloid leukemia cells. Finally, we show that TauT inhibition can synergize with the clinically approved oxidative phosphorylation inhibitor venetoclax8, 9 to block the growth of primary human leukemia cells. Given that aggressive myeloid leukemias continue to be refractory to current therapies and have poor prognosis, our work indicates targeting the taurine transporter may be of therapeutic significance. Collectively, our data establishes a temporal landscape of stromal signals during cancer progression and identifies taurine-taurine transporter signaling as an important new regulator of myeloid malignancies.

CB307: A Dual Targeting Costimulatory Humabody VH Therapeutic for Treating PSMA-Positive Tumors

PURPOSE

CD137 is a T- and NK-cell costimulatory receptor involved in consolidating immunologic responses. The potent CD137 agonist urelumab has shown clinical promise as a cancer immunotherapeutic but development has been hampered by on-target off-tumor toxicities. A CD137 agonist targeted to the prostate-specific membrane antigen (PSMA), frequently and highly expressed on castration-resistant metastatic prostate cancer (mCRPC) tumor cells, could bring effective immunotherapy to this immunologically challenging to address disease.

EXPERIMENTAL DESIGN

We designed and manufactured CB307, a novel half-life extended bispecific costimulatory Humabody VH therapeutic to elicit CD137 agonism exclusively in a PSMA-high tumor microenvironment (TME). The functional activity of CB307 was assessed in cell-based assays and in syngeneic mouse antitumor pharmacology studies. Nonclinical toxicology and toxicokinetic properties of CB307 were assessed in a good laboratory practice (GLP) compliant study in cynomolgus macaques.

RESULTS

CB307 provides effective CD137 agonism in a PSMA-dependent manner, with antitumor activity both in vitro and in vivo, and additional activity when combined with checkpoint inhibitors. A validated novel PSMA/CD137 IHC assay demonstrated a higher prevalence of CD137-positive cells in the PSMA-expressing human mCRPC TME with respect to primary lesions. CB307 did not show substantial toxicity in nonhuman primates and exhibited a plasma half-life supporting weekly clinical administration.

CONCLUSIONS

CB307 is a first-in-class immunotherapeutic that triggers potent PSMA-dependent T-cell activation, thereby alleviating toxicologic concerns against unrestricted CD137 agonism.

Targeting ferroptosis for leukemia therapy: exploring novel strategies from its mechanisms and role in leukemia based on nanotechnology

The latest findings in iron metabolism and the newly uncovered process of ferroptosis have paved the way for new potential strategies in anti-leukemia treatments. In the current project, we reviewed and summarized the current role of nanomedicine in the treatment and diagnosis of leukemia through a comparison made between traditional approaches applied in the treatment and diagnosis of leukemia via the existing investigations about the ferroptosis molecular mechanisms involved in various anti-tumor treatments. The application of nanotechnology and other novel technologies may provide a new direction in ferroptosis-driven leukemia therapies. The article explores the potential of targeting ferroptosis, a new form of regulated cell death, as a new therapeutic strategy for leukemia. It discusses the mechanisms of ferroptosis and its role in leukemia and how nanotechnology can enhance the delivery and efficacy of ferroptosis-inducing agents. The article not only highlights the promise of ferroptosis-targeted therapies and nanotechnology in revolutionizing leukemia treatment, but also calls for further research to overcome challenges and fully realize the clinical potential of this innovative approach. Finally, it discusses the challenges and opportunities in clinical applications of ferroptosis.

Mapping AML heterogeneity - multi-cohort transcriptomic analysis identifies novel clusters and divergent ex-vivo drug responses

Subtyping of acute myeloid leukaemia (AML) is predominantly based on recurrent genetic abnormalities, but recent literature indicates that transcriptomic phenotyping holds immense potential to further refine AML classification. Here we integrated five AML transcriptomic datasets with corresponding genetic information to provide an overview (n = 1224) of the transcriptomic AML landscape. Consensus clustering identified 17 robust patient clusters which improved identification of CEBPA-mutated patients with favourable outcomes, and uncovered transcriptomic subtypes for KMT2A rearrangements (2), NPM1 mutations (5), and AML with myelodysplasia-related changes (AML-MRC) (5). Transcriptomic subtypes of KMT2A, NPM1 and AML-MRC showed distinct mutational profiles, cell type differentiation arrests and immune properties, suggesting differences in underlying disease biology. Moreover, our transcriptomic clusters show differences in ex-vivo drug responses, even when corrected for differentiation arrest and superiorly capture differences in drug response compared to genetic classification. In conclusion, our findings underscore the importance of transcriptomics in AML subtyping and offer a basis for future research and personalised treatment strategies. Our transcriptomic compendium is publicly available and we supply an R package to project clusters to new transcriptomic studies.

T Cell Receptor-Directed Bispecific T Cell Engager Targeting MHC-Linked NY-ESO-1 for Tumor Immunotherapy

Antibody-based bispecific T cell engagers (TCEs) that redirect T cells to kill tumor cells have shown a promising therapeutic effect on hematologic malignancies. However, tumor-specific targeting is still a challenge for TCEs, impeding the development of TCEs for solid tumor therapy. The major histocompatibility complex (MHC) presents almost all intracellular peptides (including tumor-specific peptides) on the cell surface to be scanned by the TCR on T cells. With the premise of choosing optimal peptides, the final complex peptide-MHC could be the tumor-specific target for TCEs. Here, a novel TCR-directed format of a TCE targeting peptide-MHC was designed named IgG-T-TCE, which was modified from the IgG backbone and prepared in a mammalian cell expression system. The recombinant IgG-T-TCE-NY targeting NY-ESO-1157-165/HLA-A*02:01 could be generated in HEK293 cells with a glycosylated TCR and showed potency in T cell activation and redirecting T cells to specifically kill target tumor cells. We also found that the in vitro activity of IgG-T-TCE-NY could be leveraged by various anti-CD3 antibodies and Fc silencing. The IgG-T-TCE-NY efficiently inhibited tumor growth in a tumor-PBMC co-engrafted mouse model without any obvious toxicities.

Proteomics applications in next generation induced pluripotent stem cell models

INTRODUCTION

Induced pluripotent stem (iPS) cell technology has transformed biomedical research. New opportunities now exist to create new organoids, microtissues, and body-on-a-chip systems for basic biology investigations and clinical translations.

AREAS COVERED

We discuss the utility of proteomics for attaining an unbiased view into protein expression changes during iPS cell differentiation, cell maturation, and tissue generation. The ability to discover cell-type specific protein markers during the differentiation and maturation of iPS-derived cells has led to new strategies to improve cell production yield and fidelity. In parallel, proteomic characterization of iPS-derived organoids is helping to realize the goal of bridging in vitro and in vivo systems.

EXPERT OPINIONS

We discuss some current challenges of proteomics in iPS cell research and future directions, including the integration of proteomic and transcriptomic data for systems-level analysis.

Nucleolar protein TAAP1/C22orf46 confers pro-survival signaling in non-small cell lung cancer

Tumor cells subvert immune surveillance or lytic stress by harnessing inhibitory signals. Hence, bispecific antibodies have been developed to direct CTLs to the tumor site and foster immune-dependent cytotoxicity. Although applied with success, T cell-based immunotherapies are not universally effective partially because of the expression of pro-survival factors by tumor cells protecting them from apoptosis. Here, we report a CRISPR/Cas9 screen in human non-small cell lung cancer cells designed to identify genes that confer tumors with the ability to evade the cytotoxic effects of CD8+ T lymphocytes engaged by bispecific antibodies. We show that the gene C22orf46 facilitates pro-survival signals and that tumor cells devoid of C22orf46 expression exhibit increased susceptibility to T cell-induced apoptosis and stress by genotoxic agents. Although annotated as a non-coding gene, we demonstrate that C22orf46 encodes a nucleolar protein, hereafter referred to as "Tumor Apoptosis Associated Protein 1," up-regulated in lung cancer, which displays remote homologies to the BH domain containing Bcl-2 family of apoptosis regulators. Collectively, the findings establish TAAP1/C22orf46 as a pro-survival oncogene with implications to therapy.

High-throughput virtual search of small molecules for controlling the mechanical stability of human CD4

Protein mechanical stability determines the function of a myriad of proteins, especially proteins from the extracellular matrix. Failure to maintain protein mechanical stability may result in diseases and disorders such as cancer, cardiomyopathies, or muscular dystrophy. Thus, developing mutation-free approaches to enhance and control the mechanical stability of proteins using pharmacology-based methods may have important implications in drug development and discovery. Here, we present the first approach that employs computational high-throughput virtual screening and molecular docking to search for small molecules in chemical libraries that function as mechano-regulators of the stability of human cluster of differentiation 4, receptor of HIV-1. Using single-molecule force spectroscopy, we prove that these small molecules can increase the mechanical stability of CD4D1D2 domains over 4-fold in addition to modifying the mechanical unfolding pathways. Our experiments demonstrate that chemical libraries are a source of mechanoactive molecules and that drug discovery approaches provide the foundation of a new type of molecular function, that is, mechano-regulation, paving the way toward mechanopharmacology.

Extracellular Matrix Interactome in Modulating Vascular Homeostasis and Remodeling

The ECM (extracellular matrix) is a major component of the vascular microenvironment that modulates vascular homeostasis. ECM proteins include collagens, elastin, noncollagen glycoproteins, and proteoglycans/glycosaminoglycans. ECM proteins form complex matrix structures, such as the basal lamina and collagen and elastin fibers, through direct interactions or lysyl oxidase-mediated cross-linking. Moreover, ECM proteins directly interact with cell surface receptors or extracellular secreted molecules, exerting matricellular and matricrine modulation, respectively. In addition, extracellular proteases degrade or cleave matrix proteins, thereby contributing to ECM turnover. These interactions constitute the ECM interactome network, which is essential for maintaining vascular homeostasis and preventing pathological vascular remodeling. The current review mainly focuses on endogenous matrix proteins in blood vessels and discusses the interaction of these matrix proteins with other ECM proteins, cell surface receptors, cytokines, complement and coagulation factors, and their potential roles in maintaining vascular homeostasis and preventing pathological remodeling.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

The proteome of the blood-brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

BACKGROUND

The active transport of molecules into the brain from blood is regulated by receptors, transporters, and other cell surface proteins that are present on the luminal surface of endothelial cells at the blood-brain barrier (BBB). However, proteomic profiling of proteins present on the luminal endothelial cell surface of the BBB has proven challenging due to difficulty in labelling these proteins in a way that allows efficient purification of these relatively low abundance cell surface proteins.

METHODS

Here we describe a novel perfusion-based labelling workflow: in vivo glycocapture. This workflow relies on the oxidation of glycans present on the luminal vessel surface via perfusion of a mild oxidizing agent, followed by subsequent isolation of glycoproteins by covalent linkage of their oxidized glycans to hydrazide beads. Mass spectrometry-based identification of the isolated proteins enables high-confidence identification of endothelial cell surface proteins in rats and mice.

RESULTS

Using the developed workflow, 347 proteins were identified from the BBB in rat and 224 proteins in mouse, for a total of 395 proteins in both species combined. These proteins included many proteins with transporter activity (73 proteins), cell adhesion proteins (47 proteins), and transmembrane signal receptors (31 proteins). To identify proteins that are enriched in vessels relative to the entire brain, we established a vessel-enrichment score and showed that proteins with a high vessel-enrichment score are involved in vascular development functions, binding to integrins, and cell adhesion. Using publicly-available single-cell RNAseq data, we show that the proteins identified by in vivo glycocapture were more likely to be detected by scRNAseq in endothelial cells than in any other cell type. Furthermore, nearly 50% of the genes encoding cell-surface proteins that were detected by scRNAseq in endothelial cells were also identified by in vivo glycocapture.

CONCLUSIONS

The proteins identified by in vivo glycocapture in this work represent the most complete and specific profiling of proteins on the luminal BBB surface to date. The identified proteins reflect possible targets for the development of antibodies to improve the crossing of therapeutic proteins into the brain and will contribute to our further understanding of BBB transport mechanisms.

A novel class of inhibitors that disrupts the stability of integrin heterodimers identified by CRISPR-tiling-instructed genetic screens

The plasma membrane is enriched for receptors and signaling proteins that are accessible from the extracellular space for pharmacological intervention. Here we conducted a series of CRISPR screens using human cell surface proteome and integrin family libraries in multiple cancer models. Our results identified ITGAV (integrin αV) and its heterodimer partner ITGB5 (integrin β5) as the essential integrin α/β pair for cancer cell expansion. High-density CRISPR gene tiling further pinpointed the integral pocket within the β-propeller domain of ITGAV for integrin αVβ5 dimerization. Combined with in silico compound docking, we developed a CRISPR-Tiling-Instructed Computer-Aided (CRISPR-TICA) pipeline for drug discovery and identified Cpd_AV2 as a lead inhibitor targeting the β-propeller central pocket of ITGAV. Cpd_AV2 treatment led to rapid uncoupling of integrin αVβ5 and cellular apoptosis, providing a unique class of therapeutic action that eliminates the integrin signaling via heterodimer dissociation. We also foresee the CRISPR-TICA approach to be an accessible method for future drug discovery studies.