Bioinformatics construction of the human cell surfaceome

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.

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.

Defining the Cell Surface Cysteinome Using Two-Step Enrichment Proteomics

The plasma membrane proteome is a rich resource of functionally important and therapeutically relevant protein targets. Distinguished by high hydrophobicity, heavy glycosylation, disulfide-rich sequences, and low overall abundance, the cell surface proteome remains undersampled in established proteomic pipelines, including our own cysteine chemoproteomics platforms. Here, we paired cell surface glycoprotein capture with cysteine chemoproteomics to establish a two-stage enrichment method that enables chemoproteomic profiling of cell Surface Cysteinome. Our "Cys-Surf" platform captures >2,800 total membrane protein cysteines in 1,046 proteins, including 1,907 residues not previously captured by bulk proteomic analysis. By pairing Cys-Surf with an isotopic chemoproteomic readout, we uncovered 821 total ligandable cysteines, including known and novel sites. Cys-Surf also robustly delineates redox-sensitive cysteines, including cysteines prone to activation-dependent changes to cysteine oxidation state and residues sensitive to addition of exogenous reductants. Exemplifying the capacity of Cys-Surf to delineate functionally important cysteines, we identified a redox sensitive cysteine in the low-density lipoprotein receptor (LDLR) that impacts both the protein localization and uptake of low-density lipoprotein (LDL) particles. Taken together, the Cys-Surf platform, distinguished by its two-stage enrichment paradigm, represents a tailored approach to delineate the functional and therapeutic potential of the plasma membrane cysteinome.

Defining the Cell Surface Cysteinome using Two-step Enrichment Proteomics

The plasma membrane proteome is a rich resource of functional and therapeutically relevant protein targets. Distinguished by high hydrophobicity, heavy glycosylation, disulfide-rich sequences, and low overall abundance, the cell surface proteome remains undersampled in established proteomic pipelines, including our own cysteine chemoproteomics platforms. Here we paired cell surface glycoprotein capture with cysteine chemoproteomics to establish a two-stage enrichment method that enables chemoproteomic profiling of cell Surface Cysteinome. Our "Cys-Surf" platform captures >2,800 total membrane protein cysteines in 1,046 proteins, including 1,907 residues not previously captured by bulk proteomic analysis. By pairing Cys-Surf with an isotopic chemoproteomic readout, we uncovered 821 total ligandable cysteines, including known and novel sites. Cys-Surf also robustly delineates redox-sensitive cysteines, including cysteines prone to activation-dependent changes to cysteine oxidation state and residues sensitive to addition of exogenous reductants. Exemplifying the capacity of Cys-Surf to delineate functionally important cysteines, we identified a redox sensitive cysteine in the low-density lipoprotein receptor (LDLR) that impacts both the protein localization and uptake of LDL particles. Taken together, the Cys-Surf platform, distinguished by its two-stage enrichment paradigm, represents a tailored approach to delineate the functional and therapeutic potential of the plasma membrane cysteinome.

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.

A target discovery pipeline identified ILT3 as a target for immunotherapy of multiple myeloma

Multiple myeloma (MM) is an incurable malignancy of plasma cells. To identify targets for MM immunotherapy, we develop an integrated pipeline based on mass spectrometry analysis of seven MM cell lines and RNA sequencing (RNA-seq) from 900+ patients. Starting from 4,000+ candidates, we identify the most highly expressed cell surface proteins. We annotate candidate protein expression in many healthy tissues and validate the expression of promising targets in 30+ patient samples with relapsed/refractory MM, as well as in primary healthy hematopoietic stem cells and T cells by flow cytometry. Six candidates (ILT3, SEMA4A, CCR1, LRRC8D, FCRL3, IL12RB1) and B cell maturation antigen (BCMA) present the most favorable profile in malignant and healthy cells. We develop a bispecific T cell engager targeting ILT3 that shows potent killing effects in vitro and decreased tumor burden and prolonged mice survival in vivo, suggesting therapeutic relevance. Our study uncovers MM-associated antigens that hold great promise for immune-based therapies of MM.

Surfaceome Profiling Identifies Basigin-Chaperoned Protein Clients

The surface proteome or "surfaceome" is a critical mediator of cellular biology, facilitating cell-to-cell interactions and communication with extracellular biomolecules. Constituents of the surfaceome can serve as biomarkers for changing cell states and as targets for pharmacological intervention. While some pathways of cell surface trafficking are well characterized to allow prediction of surface localization, some non-canonical trafficking mechanisms do not. Basigin (Bsg), a cell surface glycoprotein, has been shown to chaperone protein clients to the cell surface. However, understanding which proteins are served by Bsg is not always straightforward. To accelerate such identification, we applied a surfaceome proximity labeling method that is integrated with quantitative mass spectrometry-based proteomics to discern changes in the surfaceome of hepatic stellate cells that occur in response to the genetic loss of Bsg. Using this strategy, we observed that the loss of Bsg leads to corresponding reductions in the cell surface expression of monocarboxylate transporters MCT1 and MCT4. We also found that these relationships were unique to Bsg and not found in neuroplastin (Nptn), a related family member. These results establish the utility of the surfaceome proximity labeling method to determine clients of cell surface chaperone proteins.

Highly selective and quantitative in situ monitoring of cell surface proteins by SERS immunoassay system

Due to their pivotal roles in many biological functions, cell surface proteins (CSPs) are often used for cancer prognosis, as evidenced by a number of studies that have reported significant changes in the expression levels of specific surface proteins depending on the stage of tumorigenesis and selection/variety of reprogrammed cells during cell fate conversion. Current CSP detection strategies suffer from poor selectivity and lack the ability for in situ analysis but maintain the spatial information between cells. Here, we have fabricated nanoprobes for surface-enhanced Raman scattering (SERS) immunoassays by conjugating a specific antibody onto silica-coated gold nanoparticles incorporating an individual Raman reporter (Au-tag@SiO₂-Ab NPs) for highly sensitive and selective in situ detection in different types of cells. When multiple HEK293 cell lines stably expressing different levels of the CSP, ACE2, were investigated by the SERS immunoassay, we demonstrated that the level of ACE2 expression in each cell line could be statistically distinguished from that in the other cell lines, indicating the quantitative feature of this biosensing system. When detecting living cells without cell lysis or fixation, as well as fixed cells, the levels of the epithelial CSPs, EpCAM (epithelial cell adhesion molecule) and E-cadherin, were successfully determined using our Au-tag@SiO₂-Ab NPs and SERS immunoassay system in a highly selective and quantitative manner without significant cytotoxicity. Hence, our work provides technical insight into the development of a biosensing platform for a variety of biomedical applications, such as cancer metastasis prognosis and the in situ monitoring of stem cell reprogramming and differentiation.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

LRRC15 mediates an accessory interaction with the SARS-CoV-2 spike protein

The interactions between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and human host factors enable the virus to propagate infections that lead to Coronavirus Disease 2019 (COVID-19). The spike protein is the largest structural component of the virus and mediates interactions essential for infection, including with the primary angiotensin-converting enzyme 2 (ACE2) receptor. We performed two independent cell-based systematic screens to determine whether there are additional proteins by which the spike protein of SARS-CoV-2 can interact with human cells. We discovered that in addition to ACE2, expression of LRRC15 also causes spike protein binding. This interaction is distinct from other known spike attachment mechanisms such as heparan sulfates or lectin receptors. Measurements of orthologous coronavirus spike proteins implied the interaction was functionally restricted to SARS-CoV-2 by accessibility. We localized the interaction to the C-terminus of the S1 domain and showed that LRRC15 shares recognition of the ACE2 receptor binding domain. From analyzing proteomics and single-cell transcriptomics, we identify LRRC15 expression as being common in human lung vasculature cells and fibroblasts. Levels of LRRC15 were greatly elevated by inflammatory signals in the lungs of COVID-19 patients. Although infection assays demonstrated that LRRC15 alone is not sufficient to permit viral entry, we present evidence that it can modulate infection of human cells. This unexpected interaction merits further investigation to determine how SARS-CoV-2 exploits host LRRC15 and whether it could account for any of the distinctive features of COVID-19.

Understanding How Cells Probe the World: A Preliminary Step towards Modeling Cell Behavior?

Cell biologists have long aimed at quantitatively modeling cell function. Recently, the outstanding progress of high-throughput measurement methods and data processing tools has made this a realistic goal. The aim of this paper is twofold: First, to suggest that, while much progress has been done in modeling cell states and transitions, current accounts of environmental cues driving these transitions remain insufficient. There is a need to provide an integrated view of the biochemical, topographical and mechanical information processed by cells to take decisions. It might be rewarding in the near future to try to connect cell environmental cues to physiologically relevant outcomes rather than modeling relationships between these cues and internal signaling networks. The second aim of this paper is to review exogenous signals that are sensed by living cells and significantly influence fate decisions. Indeed, in addition to the composition of the surrounding medium, cells are highly sensitive to the properties of neighboring surfaces, including the spatial organization of anchored molecules and substrate mechanical and topographical properties. These properties should thus be included in models of cell behavior. It is also suggested that attempts at cell modeling could strongly benefit from two research lines: (i) trying to decipher the way cells encode the information they retrieve from environment analysis, and (ii) developing more standardized means of assessing the quality of proposed models, as was done in other research domains such as protein structure prediction.

Antibody variable region engineering for improving cancer immunotherapy

The efficacy and specificity of conventional monoclonal antibody (mAb) drugs in the clinic require further improvement. Currently, the development and application of novel antibody formats for improving cancer immunotherapy have attracted much attention. Variable region-retaining antibody fragments, such as antigen-binding fragment (Fab), single-chain variable fragment (scFv), bispecific antibody, and bi/trispecific cell engagers, are engineered with humanization, multivalent antibody construction, affinity optimization and antibody masking for targeting tumor cells and killer cells to improve antibody-based therapy potency, efficacy and specificity. In this review, we summarize the application of antibody variable region engineering and discuss the future direction of antibody engineering for improving cancer therapies.

Cancer/Testis Antigens as Biomarker and Target for the Diagnosis, Prognosis, and Therapy of Lung Cancer

Lung cancer is the leading type of malignant tumour among cancer-caused death worldwide, and the 5-year survival rate of lung cancer patients is only 18%. Various oncogenes are abnormally overexpressed in lung cancer, including cancer/testis antigens (CTAs), which are restrictively expressed in the male testis but are hardly expressed in other normal tissues, if at all. CTAs are aberrantly overexpressed in various types of cancer, with more than 60 CTAs abnormally overexpressed in lung cancer. Overexpression of oncogenic CTAs drives the initiation, metastasis and progression of lung cancer, and is closely associated with poor prognosis in cancer patients. Several CTAs, such as XAGE, SPAG9 and AKAP4, have been considered as biomarkers for the diagnosis and prognostic prediction of lung cancer. More interestingly, due to the high immunogenicity and specificity of CTAs in cancer, several CTAs, including CT45, BCAP31 and ACTL8, have been targeted for developing novel therapeutics against cancer. CTA-based vaccines, chimeric antigen receptor-modified T cells (CAR-T) and small molecules have been used in lung cancer treatment in pre-clinical and early clinical trials, with encouraging results being obtained. However, there are still many hurdles to be overcome before these therapeutics can be routinely used in clinical lung cancer therapy. This review summarises the recent rapid progress in oncogenic CTAs, focusing on CTAs as biomarkers for lung cancer diagnosis and prognostic prediction, and as targets for novel anti-cancer drug discovery and lung cancer therapy. We also identify challenges and opportunities in CTA-based cancer diagnosis and treatment. Finally, we provide perspectives on the mechanisms of oncogenic CTAs in lung cancer development, and we also suggest CTAs as a new platform for lung cancer diagnosis, prognostic prediction, and novel anti-cancer drug discovery.

Cell Surface Engineering Enables Surfaceome Profiling

Cell surface proteins (CSPs) are vital molecular mediators for cells and their extracellular environment. Thus, understanding which CSPs are displayed on cells, especially in different cell states, remains an important endeavor in cell biology. Here, we describe the integration of cell surface engineering with radical-mediated protein biotinylation to profile CSPs. This method relies on the prefunctionalization of cells with cholesterol lipid groups, followed by sortase-catalyzed conjugation with an APEX2 ascorbate peroxidase enzyme. In the presence of biotin-phenol and H₂O₂, APEX2 catalyzes the formation of highly reactive biotinyl radicals that covalently tag electron-rich residues within CSPs for subsequent streptavidin-based enrichment and analysis by quantitative mass spectrometry. While APEX2 is traditionally used to capture proximity-based interactomes, we envisioned using it in a "baitless" manner on cell surfaces to capture CSPs. We evaluate this strategy in light of another CSP labeling method that relies on the presence of cell surface sialic acid. Using the APEX2 strategy, we describe the CSPs found in three mammalian cell lines and compare CSPs in adherent versus three-dimensional pancreatic adenocarcinoma cells.

Landscape of surfaceome and endocytome in human glioma is divergent and depends on cellular spatial organization

Cancer immunotherapies, including checkpoint inhibitor blocking antibodies and antibody drug conjugates, currently revolutionize cancer treatment. However, a remaining challenge is the identification of tumor surfaceome (TS) targets for the design of more rational, individualized treatments. We have developed a procedure for unbiased mapping of TS targets in glioblastoma (GBM), i.e., the most common primary malignant brain tumor that remains among the most aggressive forms of cancer, and for which attempts to find effective treatments have failed so far. The present study provides additional layers of understanding fundamental to the future development of immunotherapy strategies, as well as procedures for proteomics-based target identification aimed at a better understanding of how to harness the TS for personalized immunotherapy.

Therapeutic strategies directed at the tumor surfaceome (TS), including checkpoint inhibitor blocking antibodies, antibody drug conjugates (ADCs), and chimeric antigen receptor T (CAR-T) cells, provide a new armament to fight cancer. However, a remaining bottleneck is the lack of strategies to comprehensively interrogate patient tumors for potential TS targets. Here, we have developed a platform (tumor surfaceome mapping [TS-MAP]) integrated with a newly curated TS classifier (SURFME) that allows profiling of primary 3D cultures and intact patient glioma tumors with preserved tissue architecture. Moreover, TS-MAP specifically identifies proteins capable of endocytosis as tractable targets for ADCs and other modalities requiring toxic payload internalization. In high-grade gliomas that remain among the most aggressive forms of cancer, we show that cellular spatial organization (2D vs. 3D) fundamentally transforms the surfaceome and endocytome (e.g., integrins, proteoglycans, semaphorins, and cancer stem cell markers) with general implications for target screening approaches, as exemplified by an ADC targeting EGFR. The TS-MAP platform was further applied to profile the surfaceome and endocytome landscape in a cohort of freshly resected gliomas. We found a highly diverse TS repertoire between patient tumors, not directly associated with grade and histology, which highlights the need for individualized approaches. Our data provide additional layers of understanding fundamental to the future development of immunotherapy strategies, as well as procedures for proteomics-based target identification and selection. The TS-MAP platform should be widely applicable in efforts aiming at a better understanding of how to harness the TS for personalized immunotherapy.

Flow Cytometry Analysis of Cell-Surface Markers to Identify Human Naïve Pluripotent Stem Cells

Cell-surface proteins provide excellent biomarkers to identify specific cell types and resolve heterogeneous cell populations. The analysis of cell-surface proteins by flow cytometry produces robust and quantitative information with single-cell resolution, and allows live target cells to be purified and characterized or re-cultured. Studies using antibody screens, proteomics, and candidate analysis have identified a comprehensive set of proteins that are expressed on the surface of naïve and primed human pluripotent stem cells. These findings have led to the development of suitable protein markers and antibodies to accurately distinguish between these two cell types. Here, a detailed protocol is provided that uses multi-color flow cytometry to analyze cell-surface protein expression in naïve and primed human pluripotent stem cells. This method enables the unambiguous identification of pluripotent cell types and the opportunity to sort target cells including during cell state transitions. The protocol can be combined to additionally investigate the expression of reporter genes and other informative features, such as DNA content.

VLDLR and ApoER2 are receptors for multiple alphaviruses

Alphaviruses, like many other arthropod-borne viruses, infect vertebrate species and insect vectors separated by hundreds of millions of years of evolutionary history. Entry into evolutionarily divergent host cells can be accomplished by recognition of different cellular receptors in different species, or by binding to receptors that are highly conserved across species. Although multiple alphavirus receptors have been described^1–3, most are not shared among vertebrate and invertebrate hosts. Here we identify the very low-density lipoprotein receptor (VLDLR) as a receptor for the prototypic alphavirus Semliki forest virus. We show that the E2 and E1 glycoproteins (E2–E1) of Semliki forest virus, eastern equine encephalitis virus and Sindbis virus interact with the ligand-binding domains (LBDs) of VLDLR and apolipoprotein E receptor 2 (ApoER2), two closely related receptors. Ectopic expression of either protein facilitates cellular attachment, and internalization of virus-like particles, a VLDLR LBD–Fc fusion protein or a ligand-binding antagonist block Semliki forest virus E2–E1-mediated infection of human and mouse neurons in culture. The administration of a VLDLR LBD–Fc fusion protein has protective activity against rapidly fatal Semliki forest virus infection in mouse neonates. We further show that invertebrate receptor orthologues from mosquitoes and worms can serve as functional alphavirus receptors. We propose that the ability of some alphaviruses to infect a wide range of hosts is a result of their engagement of evolutionarily conserved lipoprotein receptors and contributes to their pathogenesis.

Studies using viral coat glycoproteins show that alphaviruses can enter cells via the very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), members of an evolutionarily conserved family of lipoprotein receptors.

The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets

Cell-surface proteins (SPs) are a rich source of immune and targeted therapies. By systematically integrating single-cell and bulk genomics, functional studies and target actionability, in the present study we comprehensively identify and annotate genes encoding SPs (GESPs) pan-cancer. We characterize GESP expression patterns, recurrent genomic alterations, essentiality, receptor-ligand interactions and therapeutic potential. We also find that mRNA expression of GESPs is cancer-type specific and positively correlates with protein expression, and that certain GESP subgroups function as common or specific essential genes for tumor cell growth. We also predict receptor-ligand interactions substantially deregulated in cancer and, using systems biology approaches, we identify cancer-specific GESPs with therapeutic potential. We have made this resource available through the Cancer Surfaceome Atlas ( http://fcgportal.org/TCSA ) within the Functional Cancer Genome data portal.

Identification of Oocyst-Driven Toxoplasma gondii Infections in Humans and Animals through Stage-Specific Serology-Current Status and Future Perspectives

The apicomplexan zoonotic parasite Toxoplasma gondii has three infective stages: sporozoites in sporulated oocysts, which are shed in unsporulated form into the environment by infected felids; tissue cysts containing bradyzoites, and fast replicating tachyzoites that are responsible for acute toxoplasmosis. The contribution of oocysts to infections in both humans and animals is understudied despite being highly relevant. Only a few diagnostic antigens have been described to be capable of discriminating which parasite stage has caused an infection. Here we provide an extensive overview of the antigens and serological assays used to detect oocyst-driven infections in humans and animals according to the literature. In addition, we critically discuss the possibility to exploit the increasing knowledge of the T. gondii genome and the various 'omics datasets available, by applying predictive algorithms, for the identification of new oocyst-specific proteins for diagnostic purposes. Finally, we propose a workflow for how such antigens and assays based on them should be evaluated to ensure reproducible and robust results.

Integration of RNA-Seq and proteomics data identifies glioblastoma multiforme surfaceome signature

Background

Glioblastoma multiforme (GBM) is a highly lethal, stage IV brain tumour with a prevalence of approximately 2 per 10,000 people globally. The cell surface proteins or surfaceome serve as information gateway in many oncogenic signalling pathways and are important in modulating cancer phenotypes. Dysregulation in surfaceome expression and activity have been shown to promote tumorigenesis. The expression of GBM surfaceome is a case in point; OMICS screening in a cell-based system identified that this sub-proteome is largely perturbed in GBM. Additionally, since these cell surface proteins have ‘direct’ access to drugs, they are appealing targets for cancer therapy. However, a comprehensive GBM surfaceome landscape has not been fully defined yet. Thus, this study aimed to define GBM-associated surfaceome genes and identify key cell-surface genes that could potentially be developed as novel GBM biomarkers for therapeutic purposes.

Methods

We integrated the RNA-Seq data from TCGA GBM (n = 166) and GTEx normal brain cortex (n = 408) databases to identify the significantly dysregulated surfaceome in GBM. This was followed by an integrative analysis that combines transcriptomics, proteomics and protein-protein interaction network data to prioritize the high-confidence GBM surfaceome signature.

Results

Of the 2381 significantly dysregulated genes in GBM, 395 genes were classified as surfaceome. Via the integrative analysis, we identified 6 high-confidence GBM molecular signature, HLA-DRA, CD44, SLC1A5, EGFR, ITGB2, PTPRJ, which were significantly upregulated in GBM. The expression of these genes was validated in an independent transcriptomics database, which confirmed their upregulated expression in GBM. Importantly, high expression of CD44, PTPRJ and HLA-DRA is significantly associated with poor disease-free survival. Last, using the Drugbank database, we identified several clinically-approved drugs targeting the GBM molecular signature suggesting potential drug repurposing.

Conclusions

In summary, we identified and highlighted the key GBM surface-enriched repertoires that could be biologically relevant in supporting GBM pathogenesis. These genes could be further interrogated experimentally in future studies that could lead to efficient diagnostic/prognostic markers or potential treatment options for GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08591-0.

Biomimetic Nanotechnology: A Natural Path Forward for Tumor-Selective and Tumor-Specific NIR Activable Photonanomedicines

The emergence of biomimetic nanotechnology has seen an exponential rise over the past decade with applications in regenerative medicine, immunotherapy and drug delivery. In the context of nanomedicines activated by near infrared (NIR) photodynamic processes (photonanomedicines; PNMs), biomimetic nanotechnology is pushing the boundaries of activatable tumor targeted nanoscale drug delivery systems. This review discusses how, by harnessing a unique collective of biological processes critical to targeting of solid tumors, biomimetic PNMs (bPNMs) can impart tumor cell specific and tumor selective photodynamic therapy-based combination regimens. Through molecular immune evasion and self-recognition, bPNMs can confer both tumor selectivity (preferential bulk tumor accumulation) and tumor specificity (discrete molecular affinity for cancer cells), respectively. They do so in a manner that is akin, yet arguably superior, to synthetic molecular-targeted PNMs. A particular emphasis is made on how bPNMs can be engineered to circumvent tumor cell heterogeneity, which is considered the Achilles’ heel of molecular targeted therapeutics. Forward-looking propositions are also presented on how patient tumor heterogeneity can ultimately be recapitulated to fabricate patient-specific, heterogeneity-targeting bPNMs.

Elucidation of host-virus surfaceome interactions using spatial proteotyping

The cellular surfaceome and its residing extracellularly exposed proteins are involved in a multitude of molecular signaling processes across the viral infection cycle. Successful viral propagation, including viral entry, immune evasion, virion release and viral spread rely on dynamic molecular interactions with the surfaceome. Decoding of these viral-host surfaceome interactions using advanced technologies enabled the discovery of fundamental new functional insights into cellular and viral biology. In this review, we highlight recently developed experimental strategies, with a focus on spatial proteotyping technologies, aiding in the rational design of theranostic strategies to combat viral infections.

Interacting Proteins, Polymorphisms and the Susceptibility of Animals to SARS-CoV-2

COVID-19, caused by SARS-CoV-2, is a world-wide problem for the human population. It is known that some animal species, such as mink, can become infected and transmit the virus. However, the susceptibility of most animals is not known. Here, we review the use of sequence analysis of the proteins which are known to interact with SARS-CoV-2 as a way to estimate an animal's susceptibility. Although most such work concentrates on the angiotensin-converting enzyme 2 receptor (ACE2), here TMPRSS2 (Transmembrane Serine Protease 2), neuropilin-1 and furin are also considered. Polymorphisms, especially ones which are known to alter viral/host interactions are also discussed. Analysis of ACE2 and TMPRSS2 protein sequences across species suggests this approach may be of some utility in predicting susceptibility; however, this analysis fails to highlight some susceptible animals such as mink. However, combined with observational data which emerges over time about which animals actually become infected, this may, in the future, be a useful tool to assist the management of risks associated with human/animal contact and support conservation and animal welfare measures.

Targeted biologic inhibition of both tumor cell-intrinsic and intercellular CLPTM1L/CRR9-mediated chemotherapeutic drug resistance

Recurrence of therapy-resistant tumors is a principal problem in solid tumor oncology, particularly in ovarian cancer. Despite common complete responses to first line, platinum-based therapies, most women with ovarian cancer recur, and eventually, nearly all with recurrent disease develop platinum resistance. Likewise, both intrinsic and acquired resistance contribute to the dismal prognosis of pancreatic cancer. Our previous work and that of others has established CLPTM1L (cleft lip and palate transmembrane protein 1-like)/CRR9 (cisplatin resistance related protein 9) as a cytoprotective oncofetal protein that is present on the tumor cell surface. We show that CLPTM1L is broadly overexpressed and accumulated on the plasma membrane of ovarian tumor cells, while weakly or not expressed in normal tissues. High expression of CLPTM1L is associated with poor outcome in ovarian serous adenocarcinoma. Robust re-sensitization of resistant ovarian cancer cells to platinum-based therapy was achieved using human monoclonal biologics inhibiting CLPTM1L in both orthotopic isografts and patient-derived cisplatin resistant xenograft models. Furthermore, we demonstrate that in addition to cell-autonomous cytoprotection by CLPTM1L, extracellular CLPTM1L confers resistance to chemotherapeutic killing in an ectodomain-dependent fashion, and that this intercellular resistance mechanism is inhibited by anti-CLPTM1L biologics. Specifically, exosomal CLPTM1L from cisplatin-resistant ovarian carcinoma cell lines conferred resistance to cisplatin in drug-sensitive parental cell lines. CLPTM1L is present in extracellular vesicle fractions of tumor culture supernatants and in patients' serum with increasing abundance upon chemotherapy treatment. These findings have encouraging implications for the use of anti-CLPTM1L targeted biologics in the treatment of therapy-resistant tumors.

Tumors Widely Express Hundreds of Embryonic Germline Genes

We have recently described a class of 756 genes that are widely expressed in cancers, but are normally restricted to adult germ cells, referred to as germ cell cancer genes (GC genes). We hypothesized that carcinogenesis involves the reactivation of biomolecular processes and regulatory mechanisms that, under normal circumstances, are restricted to germline development. This would imply that cancer cells share gene expression profiles with primordial germ cells (PGCs). We therefore compared the transcriptomes of human PGCs (hPGCs) and PGC-like cells (PGCLCs) with 17,382 samples from 54 healthy somatic tissues (GTEx) and 11,003 samples from 33 tumor types (TCGA), and identified 672 GC genes, expanding the known GC gene pool by 387 genes (51%). We found that GC genes are expressed in clusters that are often expressed in multiple tumor types. Moreover, the amount of GC gene expression correlates with poor survival in patients with lung adenocarcinoma. As GC genes specific to the embryonic germline are not expressed in any adult tissue, targeting these in cancer treatment may result in fewer side effects than targeting conventional cancer/testis (CT) or GC genes and may preserve fertility. We anticipate that our extended GC dataset enables improved understanding of tumor development and may provide multiple novel targets for cancer treatment development.

Single-cell lineage analysis reveals extensive multimodal transcriptional control during directed beta-cell differentiation

The in vitro differentiation of insulin-producing beta-like cells can model aspects of human pancreatic development. Here, we generate 95,308 single-cell transcriptomes and reconstruct a lineage tree of the entire differentiation process from human embryonic stem cells to beta-like cells to study temporally regulated genes during differentiation. We identify so-called 'switch genes' at the branch point of endocrine/non-endocrine cell fate choice, revealing insights into the mechanisms of differentiation-promoting reagents, such as NOTCH and ROCKII inhibitors, and providing improved differentiation protocols. Over 20% of all detectable genes are activated multiple times during differentiation, even though their enhancer activation is usually unimodal, indicating extensive gene reuse driven by different enhancers. We also identify a stage-specific enhancer at the TCF7L2 locus for diabetes, uncovered by genome-wide association studies, that drives a transient wave of gene expression in pancreatic progenitors. Finally, we develop a web app to visualize gene expression on the lineage tree, providing a comprehensive single-cell data resource for researchers studying islet biology and diabetes.

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.

Rapid and sensitive large-scale screening of low affinity extracellular receptor protein interactions by using reaction induced inhibition of Gaussia luciferase

Extracellular protein interactions mediated by cell surface receptors are essential for intercellular communication in multicellular organisms. Assays to detect extracellular interactions must account for their often weak binding affinities and also the biochemical challenges in solubilising membrane-embedded receptors in an active form. Methods based on detecting direct binding of soluble recombinant receptor ectodomains have been successful, but genome-scale screening is limited by the usual requirement of producing sufficient amounts of each protein in two different forms, usually a "bait" and "prey". Here, we show that oligomeric receptor ectodomains coupled to concatenated units of the light-generating Gaussia luciferase enzyme robustly detected low affinity interactions and reduced the amount of protein required by several orders of magnitude compared to other reporter enzymes. Importantly, we discovered that this flash-type luciferase exhibited a reaction-induced inhibition that permitted the use of a single protein preparation as both bait and prey thereby halving the number of expression plasmids and recombinant proteins required for screening. This approach was tested against a benchmarked set of quantified extracellular interactions and shown to detect extremely weak interactions (KDs ≥ μM). This method will facilitate large-scale receptor interaction screening and contribute to the goal of mapping networks of cellular communication.

Prediction of the Secretome and the Surfaceome: A Strategy to Decipher the Crosstalk between Adipose Tissue and Muscle during Fetal Growth

Crosstalk between adipose and muscular tissues is hypothesized to regulate the number of muscular and adipose cells during fetal growth, with post-natal consequences on lean and fat masses. Such crosstalk largely remains, however, to be described. We hypothesized that a characterization of the proteomes of adipose and muscular tissues from bovine fetuses may enhance the understanding of the crosstalk between these tissues through the prediction of their secretomes and surfaceomes. Proteomic experiments have identified 751 and 514 proteins in fetal adipose tissue and muscle. These are mainly involved in the regulation of cell proliferation or differentiation, but also in pathways such as apoptosis, Wnt signalling, or cytokine-mediated signalling. Of the identified proteins, 51 adipokines, 11 myokines, and 37 adipomyokines were predicted, together with 26 adipose and 13 muscular cell surface proteins. Analysis of protein–protein interactions suggested 13 links between secreted and cell surface proteins that may contribute to the adipose–muscular crosstalk. Of these, an interaction between the adipokine plasminogen and the muscular cell surface alpha-enolase may regulate the fetal myogenesis. The in silico secretome and surfaceome analyzed herein exemplify a powerful strategy to enhance the elucidation of the crosstalk between cell types or tissues.

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

MOTIVATION

Cell-type-specific surface proteins can be exploited as valuable markers for a range of applications including immunophenotyping live cells, targeted drug delivery and in vivo imaging. Despite their utility and relevance, the unique combination of molecules present at the cell surface are not yet described for most cell types. A significant challenge in analyzing 'omic' discovery datasets is the selection of candidate markers that are most applicable for downstream applications.

RESULTS

Here, we developed GenieScore, a prioritization metric that integrates a consensus-based prediction of cell surface localization with user-input data to rank-order candidate cell-type-specific surface markers. In this report, we demonstrate the utility of GenieScore for analyzing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem cell and islet biology. We also demonstrate that permutations of GenieScore, termed IsoGenieScore and OmniGenieScore, can efficiently prioritize co-expressed and intracellular cell-type-specific markers, respectively.

AVAILABILITY AND IMPLEMENTATION

Calculation of GenieScores and lookup of SPC scores is made freely accessible via the SurfaceGenie web application: www.cellsurfer.net/surfacegenie.

CONTACT

Rebekah.gundry@unmc.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The dark side of immunotherapy: pancreatic cancer

Since the journal Science deemed cancer immunotherapy as the "breakthrough of the year" in 2014, there has been an explosion of clinical trials involving immunotherapeutic approaches that, in the last decade - thanks also to the renaissance of the immunosurveillance theory (renamed the three Es theory) - have been continuously and successfully developed. In the latest update of the development of the immuno-oncology drug pipeline, published last November by Nature Review Drug Discovery, it was clearly reported that the immunoactive drugs under study almost doubled in just two years. Of the different classes of passive and active immunotherapies, "cell therapy" is the fastest growing. The aim of this review is to discuss the preclinical and clinical studies that have focused on different immuno-oncology approaches applied to pancreatic cancer, which we assign to the "dark side" of immunotherapy, in the sense that it represents one of the solid tumors showing less response to this type of therapeutic strategy.

A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk

Background

Tumors comprise a complex microenvironment of interacting malignant and stromal cell types. Much of our understanding of the tumor microenvironment comes from in vitro studies isolating the interactions between malignant cells and a single stromal cell type, often along a single pathway.

Result

To develop a deeper understanding of the interactions between cells within human lung tumors, we perform RNA-seq profiling of flow-sorted malignant cells, endothelial cells, immune cells, fibroblasts, and bulk cells from freshly resected human primary non-small-cell lung tumors. We map the cell-specific differential expression of prognostically associated secreted factors and cell surface genes, and computationally reconstruct cross-talk between these cell types to generate a novel resource called the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identify and validate a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also find a prognostically favorable association between infiltration of mast cells and less aggressive tumor cell behavior.

Conclusion

These results illustrate the utility of the LTMI as a resource for generating hypotheses concerning tumor-microenvironment interactions that may have prognostic and therapeutic relevance.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s13059-020-02019-x.

Surfaceome of Exosomes Secreted from the Colorectal Cancer Cell Line SW480: Peripheral and Integral Membrane Proteins Analyzed by Proteolysis and TX114

Exosomes are important bidirectional cell-cell communicators in normal and pathological physiology. Although exosomal surface membrane proteins (surfaceome) enable target cell recognition and are an attractive source of disease marker, they are poorly understood. Here, a comprehensive surfaceome analysis of exosomes secreted by the colorectal cancer cell line SW480 is described. Sodium carbonate extraction/Triton X-114 phase separation and mild proteolysis (proteinase K, PK) of intact exosomes is used in combination with label-free quantitative mass spectrometry to identify 1025 exosomal proteins of which 208 are predicted to be integral membrane proteins (IMPs) according to TOPCONS and GRAVY scores. Interrogation of UniProt database-annotated proteins reveals 124 predicted peripherally-associated membrane proteins (PMPs). Surprisingly, 108 RNA-binding proteins (RBPs)/RNA nucleoproteins (RNPs) are found in the carbonate/Triton X-114 insoluble fraction. Mild PK treatment of SW480-GFP labeled exosomes reveal 58 proteolytically cleaved IMPs and 14 exoplasmic PMPs (e.g., CLU/GANAB/LGALS3BP). Interestingly, 18 RBPs/RNPs (e.g., EIF3L/RPL6) appear bound to the outer exosome surface since they are sensitive to PK proteolysis. The finding that outer surface-localized miRNA Let-7a-5p is RNase A-resistant, but degraded by a combination of RNase A/PK treatment suggests exosomal miRNA species also reside on the outer surface of exosomes bound to RBPs/RNPs.

Cell-Surface Proteomics Identifies Differences in Signaling and Adhesion Protein Expression between Naive and Primed Human Pluripotent Stem Cells

Naive and primed human pluripotent stem cells (hPSC) provide valuable models to study cellular and molecular developmental processes. The lack of detailed information about cell-surface protein expression in these two pluripotent cell types prevents an understanding of how the cells communicate and interact with their microenvironments. Here, we used plasma membrane profiling to directly measure cell-surface protein expression in naive and primed hPSC. This unbiased approach quantified over 1,700 plasma membrane proteins, including those involved in cell adhesion, signaling, and cell interactions. Notably, multiple cytokine receptors upstream of JAK-STAT signaling were more abundant in naive hPSC. In addition, functional experiments showed that FOLR1 and SUSD2 proteins are highly expressed at the cell surface in naive hPSC but are not required to establish human naive pluripotency. This study provides a comprehensive stem cell proteomic resource that uncovers differences in signaling pathway activity and has identified new markers to define human pluripotent states.

Induced pluripotent stem cell-derived vascular smooth muscle cells

The reproducible generation of human-induced pluripotent stem cell (hiPSC)-derived vascular smooth muscle cells (vSMCs) in vitro has been critical to overcoming many limitations of animal and primary cell models of vascular biology and disease. Since this initial advance, research in the field has turned toward recapitulating the naturally occurring subtype specificity found in vSMCs throughout the body, and honing functional models of vascular disease. In this review, we summarize vSMC derivation approaches, including current phenotype and developmental origin-specific methods, and applications of vSMCs in functional disease models and engineered tissues. Further, we discuss the challenges of heterogeneity in hiPSC-derived tissues and propose approaches to identify and isolate vSMC subtype populations.

A modular approach for cytosolic protein delivery: metal ion-induced self-assembly of gold nanoclusters as a general platform

We developed a versatile and modular method for cytosolic protein delivery through metal ion-induced co-assembly of gold nanoclusters and proteins into supramolecular assemblies. The versatility and high efficiency of this strategy to assemble and deliver various proteins into living cells were demonstrated. Importantly, the activity of proteins was maintained during the delivery. This modular approach provides an exciting and promising new nano-platform for cytosolic protein delivery.

High-Content Imaging for Large-Scale Detection of Low-Affinity Extracellular Protein Interactions

Extracellular protein interactions coordinate cellular responses with their local environment and have important roles in pathogen invasion and disease. Due to technical challenges associated with studying binding events at the cell surface, the systematic and reliable identification of novel ligand–receptor pairs remains difficult. Here, we describe the development of a cell-based assay using large-scale transient transfections and high-content imaging (HCI) to detect extracellular binding events. We optimized the parameters for efficient transfection of human cells with cDNA plasmids encoding full-length cell surface receptors in 384-well plates. Using a range of well-characterized structurally diverse low-affinity cell surface interactions, we show that transfected cells probed with highly avid ligands can be used to successfully identify ligand–receptor pairs using an HCI platform and automated image analysis software. To establish the high-throughput potential of this approach, we also screened a pool of ligands against a collection of 2455 cell surface expression clones and found that known ligand–receptor interactions could be robustly and consistently detected across the library using this technology.

Quantitative proteomics of MDCK cells identify unrecognized roles of clathrin adaptor AP-1 in polarized distribution of surface proteins

Epithelial cells perform critical protective, secretory, absorptive, and sensory functions, for which they require plasma membrane polarization into apical and basolateral domains. Impaired polarity causes cancer and developmental and degenerative disorders. Research on fundamental polarity mechanisms has been hindered by the paucity of model proteins and by the use of overexpression systems. Here, we introduce a high-throughput surface proteomics approach based on domain-selective biotinylation and quantitative mass spectrometry that provides candidate proteins to study polarity under normal expression levels. Using this approach, we described that clathrin adaptors mediate apical and basolateral distribution of surface proteins, expanding the traditional notion that clathrin adaptors mediate only basolateral polarity. Our results establish quantitative surface proteomics as a powerful tool to study epithelial polarity.

The current model of polarized plasma membrane protein sorting in epithelial cells has been largely generated on the basis of experiments characterizing the polarized distribution of a relatively small number of overexpressed model proteins under various experimental conditions. Thus, the possibility exists that alternative roles of various types of sorting machinery may have been underestimated or missed. Here, we utilize domain-selective surface biotinylation combined with stable isotope labeling with amino acids in cell culture (SILAC) and mass spectrometry to quantitatively define large populations of apical and basolateral surface proteins in Madin-Darby canine kidney (MDCK) cells. We identified 313 plasma membrane proteins, of which 38% were apical, 51% were basolateral, and 11% were nonpolar. Silencing of clathrin adaptor proteins (AP) AP-1A, AP-1B, or both caused redistribution of basolateral proteins as expected but also, of a large population of apical proteins. Consistent with their previously reported ability to compensate for one another, the strongest loss of polarity was observed when we silenced AP-1A and AP-1B simultaneously. We found stronger evidence of compensation in the apical pathway compared with the basolateral pathway. Surprisingly, we also found subgroups of proteins that were affected after silencing just one adaptor, indicating previously unrecognized independent roles for AP-1A and AP-1B. While AP-1B silencing mainly affected basolateral polarity, AP-1A silencing seemed to cause comparable loss of apical and basolateral polarity. Our results uncover previously overlooked roles of AP-1 in polarized distribution of apical and basolateral proteins and introduce surface proteomics as a method to examine mechanisms of polarization with a depth not possible until now.

Killer-like receptors and GPR56 progressive expression defines cytokine production of human CD4+ memory T cells

All memory T cells mount an accelerated response on antigen reencounter, but significant functional heterogeneity is present within the respective memory T-cell subsets as defined by CCR7 and CD45RA expression, thereby warranting further stratification. Here we show that several surface markers, including KLRB1, KLRG1, GPR56, and KLRF1, help define low, high, or exhausted cytokine producers within human peripheral and intrahepatic CD4⁺ memory T-cell populations. Highest simultaneous production of TNF and IFN-γ is observed in KLRB1⁺KLRG1⁺GPR56⁺ CD4 T cells. By contrast, KLRF1 expression is associated with T-cell exhaustion and reduced TNF/IFN-γ production. Lastly, TCRβ repertoire analysis and in vitro differentiation support a regulated, progressive expression for these markers during CD4⁺ memory T-cell differentiation. Our results thus help refine the classification of human memory T cells to provide insights on inflammatory disease progression and immunotherapy development.

Despite the current human CD4 memory T cell stratification by CD45RA/CCR7, functional heterogeneities still exist within the respective subsets. Here the authors show that several surface markers, including KLRB1, KLRG1, GPR56 and KLRF1, help to further refine the subsetting of human CD4 memory T cells and provide insights for their differentiation.

Syndecan 1 is a critical mediator of macropinocytosis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) remains recalcitrant to all forms of cancer treatment and carries a dismal 5-year survival rate of 8%¹. Inhibition of oncogenic KRAS (hereafter KRAS*), the earliest lesion in disease development that is present in >90% of PDAC, and its signaling surrogates has yielded encouraging preclinical results with experimental agents^2-4. However, KRAS*-independent disease recurrence following genetic extinction of Kras* in mouse models anticipates the need for co-extinction strategies^5,6. Multiple oncogenic processes are initiated at the cell surface, where KRAS* physically and functionally interacts to direct signaling essential for malignant transformation and tumor maintenance. Insights into the complexity of the functional surfaceome have been technologically limited until recently, and, in the case of PDAC, the genetic control of the function and composition of the PDAC surfaceome in the context of KRAS* signaling remains largely unexplored. Here, we developed an unbiased, functional target discovery platform to query KRAS*-dependent changes of the PDAC surfaceome, which uncovered syndecan-1 (SDC1) as a protein upregulated at the cell surface by KRAS*. Cell surface localization of SDC1 is essential for disease maintenance and progression, where it regulates macropinocytosis, an essential metabolic pathway that fuels PDAC cell growth. Thus, our study forges a mechanistic link between KRAS* signaling and a targetable molecule driving nutrient salvage pathways in PDAC and validates oncogene-driven surfaceome annotation as a strategy to identify cancer-specific vulnerabilities.

Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease Genes

Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis algorithm to identify both common and specific signature genes for obesity and T2D. We mapped both β-cell-specific genes and disease signature genes to the insulin regulatory network identified from a genome-wide CRISPR screen. Our integrative analysis discovered the previously unrecognized roles of the cohesin loading complex and the NuA4/Tip60 histone acetyltransferase complex in regulating insulin transcription and release. Our study demonstrated the power of combining single-cell heterogeneity analysis and functional genomics to dissect the etiology of complex diseases.

T-cells "à la CAR-T(e)" - Genetically engineering T-cell response against cancer

The last decade will be remembered as the dawn of the immunotherapy era during which we have witnessed the approval by regulatory agencies of genetically engineered CAR T-cells and of checkpoint inhibitors for cancer treatment. Understandably, T-lymphocytes represent the essential player in these approaches. These cells can mediate impressive tumor regression in terminally-ill cancer patients. Moreover, they are amenable to genetic engineering to improve their function and specificity. In the present review, we will give an overview of the most recent developments in the field of T-cell genetic engineering including TCR-gene transfer and CAR T-cells strategies. We will also elaborate on the development of other types of genetic modifications to enhance their anti-tumor immune response such as the use of co-stimulatory chimeric receptors (CCRs) and unconventional CARs built on non-antibody molecules. Finally, we will discuss recent advances in genome editing and synthetic biology applied to T-cell engineering and comment on the next challenges ahead.

Transcription factor TFAP2B up-regulates human corneal endothelial cell-specific genes during corneal development and maintenance

The corneal endothelium, which originates from the neural crest via the periocular mesenchyme (PM), is crucial for maintaining corneal transparency. The development of corneal endothelial cells (CECs) from the neural crest is accompanied by the expression of several transcription factors, but the contribution of some of these transcriptional regulators to CEC development is incompletely understood. Here, we focused on activating enhancer-binding protein 2 (TFAP2, AP-2), a neural crest-expressed transcription factor. Using semiquantitative/quantitative RT-PCR and reporter gene and biochemical assays, we found that, within the AP-2 family, the TFAP2B gene is the only one expressed in human CECs in vivo and that its expression is strongly localized to the peripheral region of the corneal endothelium. Furthermore, the TFAP2B protein was expressed both in vivo and in cultured CECs. During mouse development, TFAP2B expression began in the PM at embryonic day 11.5 and then in CECs during adulthood. siRNA-mediated knockdown of TFAP2B in CECs decreased the expression of the corneal endothelium-specific proteins type VIII collagen α2 (COL8A2) and zona pellucida glycoprotein 4 (ZP4) and suppressed cell proliferation. Of note, we also found that TFAP2B binds to the promoter of the COL8A2 and ZP4 genes. Furthermore, CECs that highly expressed ZP4 also highly expressed both TFAP2B and COL8A2 and showed high cell proliferation. These findings suggest that TFAP2B transcriptionally regulates CEC-specific genes and therefore may be an important transcriptional regulator of corneal endothelial development and homeostasis.

Pooled extracellular receptor-ligand interaction screening using CRISPR activation

Extracellular interactions between cell surface receptors are necessary for signaling and adhesion but identifying them remains technically challenging. We describe a cell-based genome-wide approach employing CRISPR activation to identify receptors for a defined ligand. We show receptors for high-affinity antibodies and low-affinity ligands can be unambiguously identified when used in pools or as individual binding probes. We apply this technique to identify ligands for the adhesion G-protein-coupled receptors and show that the Nogo myelin-associated inhibitory proteins are ligands for ADGRB1. This method will enable extracellular receptor-ligand identification on a genome-wide scale.

The in silico human surfaceome

Cell-surface proteins are of great biomedical importance, as demonstrated by the fact that 66% of approved human drugs listed in the DrugBank database target a cell-surface protein. Despite this biomedical relevance, there has been no comprehensive assessment of the human surfaceome, and only a fraction of the predicted 5,000 human transmembrane proteins have been shown to be located at the plasma membrane. To enable analysis of the human surfaceome, we developed the surfaceome predictor SURFY, based on machine learning. As a training set, we used experimentally verified high-confidence cell-surface proteins from the Cell Surface Protein Atlas (CSPA) and trained a random forest classifier on 131 features per protein and, specifically, per topological domain. SURFY was used to predict a human surfaceome of 2,886 proteins with an accuracy of 93.5%, which shows excellent overlap with known cell-surface protein classes (i.e., receptors). In deposited mRNA data, we found that between 543 and 1,100 surfaceome genes were expressed in cancer cell lines and maximally 1,700 surfaceome genes were expressed in embryonic stem cells and derivative lines. Thus, the surfaceome diversity depends on cell type and appears to be more dynamic than the nonsurface proteome. To make the predicted surfaceome readily accessible to the research community, we provide visualization tools for intuitive interrogation (wlab.ethz.ch/surfaceome). The in silico surfaceome enables the filtering of data generated by multiomics screens and supports the elucidation of the surfaceome nanoscale organization.

Systemic surfaceome profiling identifies target antigens for immune-based therapy in subtypes of advanced prostate cancer

Advanced prostate cancer is a deadly disease made up of multiple cancer subtypes that evolve during its natural history. Unfortunately, antibody- and cell-based therapies in development that target single tumor antigens found in conventional prostate cancer do not account for this heterogeneity. Here, we show that two major subtypes of advanced prostate cancer, prostate adenocarcinoma (PrAd) and neuroendocrine prostate cancer (NEPC), exhibit distinct cell-surface expression profiles. Integrated analysis of gene expression and cell-surface protein expression of prostate cancer nominated multiple subtype-specific cell-surface antigens. We specifically characterize FXYD3 and CEACAM5 as targets for immune-based therapies in PrAd and NEPC and provide preliminary evidence of the antigen-specific cytotoxic activity of CEACAM5-directed chimeric antigen receptor T cells in NEPC.

Prostate cancer is a heterogeneous disease composed of divergent molecular and histologic subtypes, including prostate adenocarcinoma (PrAd) and neuroendocrine prostate cancer (NEPC). While PrAd is the major histology in prostate cancer, NEPC can evolve from PrAd as a mechanism of treatment resistance that involves a transition from an epithelial to a neurosecretory cancer phenotype. Cell surface markers are often associated with specific cell lineages and differentiation states in normal development and cancer. Here, we show that PrAd and NEPC can be broadly discriminated by cell-surface profiles based on the analysis of prostate cancer gene expression datasets. To overcome a dependence on predictions of human cell-surface genes and an assumed correlation between mRNA levels and protein expression, we integrated transcriptomic and cell-surface proteomic data generated from a panel of prostate cancer cell lines to nominate cell-surface markers associated with these cancer subtypes. FXYD3 and CEACAM5 were validated as cell-surface antigens enriched in PrAd and NEPC, respectively. Given the lack of effective treatments for NEPC, CEACAM5 appeared to be a promising target for cell-based immunotherapy. As a proof of concept, engineered chimeric antigen receptor T cells targeting CEACAM5 induced antigen-specific cytotoxicity in NEPC cell lines. Our findings demonstrate that the surfaceomes of PrAd and NEPC reflect unique cancer differentiation states and broadly represent vulnerabilities amenable to therapeutic targeting.