Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation.

Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.

The emerging landscape of single-molecule protein sequencing technologies.

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

FAK suppresses antigen processing and presentation to promote immune evasion in pancreatic cancer.

OBJECTIVE: Immunotherapy for the treatment of pancreatic ductal adenocarcinoma (PDAC) has shown limited efficacy. Poor CD8 T-cell infiltration, low neoantigen load and a highly immunosuppressive tumour microenvironment contribute to this lack of response. Here, we aimed to further investigate the immunoregulatory function of focal adhesion kinase (FAK) in PDAC, with specific emphasis on regulation of the type-II interferon response that is critical in promoting T-cell tumour recognition and effective immunosurveillance. DESIGN: We combined CRISPR, proteogenomics and transcriptomics with mechanistic experiments using a KrasG12Dp53R172H mouse model of pancreatic cancer and validated findings using proteomic analysis of human patient-derived PDAC cell lines and analysis of publicly available human PDAC transcriptomics datasets. RESULTS: Loss of PDAC cell-intrinsic FAK signalling promotes expression of the immunoproteasome and Major Histocompatibility Complex class-I (MHC-I), resulting in increased antigen diversity and antigen presentation by FAK-/- PDAC cells. Regulation of the immunoproteasome by FAK is a critical determinant of this response, optimising the physicochemical properties of the peptide repertoire for high affinity binding to MHC-I. Expression of these pathways can be further amplified in a STAT1-dependent manner via co-depletion of FAK and STAT3, resulting in extensive infiltration of tumour-reactive CD8 T-cells and further restraint of tumour growth. FAK-dependent regulation of antigen processing and presentation is conserved between mouse and human PDAC, but is lost in cells/tumours with an extreme squamous phenotype. CONCLUSION: Therapies aimed at FAK degradation may unlock additional therapeutic benefit for the treatment of PDAC through increasing antigen diversity and promoting antigen presentation.

MicroPOTS Analysis of Barrett's Esophageal Cell Line Models Identifies Proteomic Changes after Physiologic and Radiation Stress.

Moving from macroscale preparative systems in proteomics to micro- and nanotechnologies offers researchers the ability to deeply profile smaller numbers of cells that are more likely to be encountered in clinical settings. Herein a recently developed microscale proteomic method, microdroplet processing in one pot for trace samples (microPOTS), was employed to identify proteomic changes in ∼200 Barrett's esophageal cells following physiologic and radiation stress exposure. From this small population of cells, microPOTS confidently identified >1500 protein groups, and achieved a high reproducibility with a Pearson's correlation coefficient value of R > 0.9 and over 50% protein overlap from replicates. A Barrett's cell line model treated with either lithocholic acid (LCA) or X-ray had 21 (e.g., ASNS, RALY, FAM120A, UBE2M, IDH1, ESD) and 32 (e.g., GLUL, CALU, SH3BGRL3, S100A9, FKBP3, AGR2) overexpressed proteins, respectively, compared to the untreated set. These results demonstrate the ability of microPOTS to routinely identify and quantify differentially expressed proteins from limited numbers of cells.

Insights into the Effects of Cancer Associated Mutations at the UPF2 and ATP-Binding Sites of NMD Master Regulator: UPF1.

Nonsense-mediated mRNA decay (NMD) is a quality control mechanism that recognizes post-transcriptionally abnormal transcripts and mediates their degradation. The master regulator of NMD is UPF1, an enzyme with intrinsic ATPase and helicase activities. The cancer genomic sequencing data has identified frequently mutated residues in the CH-domain and ATP-binding site of UPF1. In silico screening of UPF1 stability change as a function over 41 cancer mutations has identified five variants with significant effects: K164R, R253W, T499M, E637K, and E833K. To explore the effects of these mutations on the associated energy landscape of UPF1, molecular dynamics simulations (MDS) were performed. MDS identified stable H-bonds between residues S152, S203, S205, Q230/R703, and UPF2/AMPPNP, and suggest that phosphorylation of Serine residues may control UPF1-UPF2 binding. Moreover, the alleles K164R and R253W in the CH-domain improved UPF1-UPF2 binding. In addition, E637K and E833K alleles exhibited improved UPF1-AMPPNP binding compared to the T499M variant; the lower binding is predicted from hindrance caused by the side-chain of T499M to the docking of the tri-phosphate moiety (AMPPNP) into the substrate site. The dynamics of wild-type/mutant systems highlights the flexible nature of the ATP-binding region in UPF1. These insights can facilitate the development of drug discovery strategies for manipulating NMD signaling in cell systems using chemical tools.

Onco-proteogenomics: cancer proteomics joins forces with genomics.

The complexities of tumor genomes are rapidly being uncovered, but how they are regulated into functional proteomes remains poorly understood. Standard proteomics workflows use databases of known proteins, but these databases do not capture the uniqueness of the cancer transcriptome, with its point mutations, unusual splice variants and gene fusions. Onco-proteogenomics integrates mass spectrometry-generated data with genomic information to identify tumor-specific peptides. Linking tumor-derived DNA, RNA and protein measurements into a central-dogma perspective has the potential to improve our understanding of cancer biology.

pH-induced conformational changes in human ABO(H) blood group glycosyltransferases confirm the importance of electrostatic interactions in the formation of the semi-closed state.

The homologous human ABO(H) A and B blood group glycosyltransferases GTA and GTB have two mobile polypeptide loops surrounding their active sites that serve to allow substrate access and product egress and to recognize and sequester substrates for catalysis. Previous studies have established that these enzymes can move from the "open" state to the "semi-closed" then "closed" states in response to addition of a substrate. The contribution of electrostatic interactions to these conformational changes has now been demonstrated by the determination at various pH of the structures of GTA, GTB and the chimeric enzyme ABBA. At near-neutral pH, GTA displays the closed state in which both mobile loops order around the active site, whereas ABBA and GTB display the open state. At low pH, the apparent protonation of the DXD motif in GTA leads to the expulsion of the donor analog to yield the open state, whereas at high pH, both ABBA and GTB form the semi-closed state in which the first mobile loop becomes an ordered α-helix. Step-wise deprotonation of GTB in increments of 0.5 between pH 6.5 and 10.0 shows that helix ordering is gradual, which indicates that the formation of the semi-closed state is dependent on electrostatic forces consistent with the binding of substrate. Spectropolarimetric studies of the corresponding stand-alone peptide in solution reveal no tendency toward helix formation from pH 7.0 to 10.0, which shows that pH-dependent stability is a product of the larger protein environment and underlines the importance of substrate in active site ordering.

Untranslated regions (UTRs) are a potential novel source of neoantigens for personalised immunotherapy.

Background: Neoantigens, mutated tumour-specific antigens, are key targets of anti-tumour immunity during checkpoint inhibitor (CPI) treatment. Their identification is fundamental to designing neoantigen-directed therapy. Non-canonical neoantigens arising from the untranslated regions (UTR) of the genome are an overlooked source of immunogenic neoantigens. Here, we describe the landscape of UTR-derived neoantigens and release a computational tool, PrimeCUTR, to predict UTR neoantigens generated by start-gain and stop-loss mutations. Methods: We applied PrimeCUTR to a whole genome sequencing dataset of pre-treatment tumour samples from CPI-treated patients (n = 341). Cancer immunopeptidomic datasets were interrogated to identify MHC class I presentation of UTR neoantigens. Results: Start-gain neoantigens were predicted in 72.7% of patients, while stop-loss mutations were found in 19.3% of patients. While UTR neoantigens only accounted 2.6% of total predicted neoantigen burden, they contributed 12.4% of neoantigens with high dissimilarity to self-proteome. More start-gain neoantigens were found in CPI responders, but this relationship was not significant when correcting for tumour mutational burden. While most UTR neoantigens are private, we identified two recurrent start-gain mutations in melanoma. Using immunopeptidomic datasets, we identify two distinct MHC class I-presented UTR neoantigens: one from a recurrent start-gain mutation in melanoma, and one private to Jurkat cells. Conclusion: PrimeCUTR is a novel tool which complements existing neoantigen discovery approaches and has potential to increase the detection yield of neoantigens in personalised therapeutics, particularly for neoantigens with high dissimilarity to self. Further studies are warranted to confirm the expression and immunogenicity of UTR neoantigens.

The Immunopeptidomics Ontology (ImPO).

The adaptive immune response plays a vital role in eliminating infected and aberrant cells from the body. This process hinges on the presentation of short peptides by major histocompatibility complex Class I molecules on the cell surface. Immunopeptidomics, the study of peptides displayed on cells, delves into the wide variety of these peptides. Understanding the mechanisms behind antigen processing and presentation is crucial for effectively evaluating cancer immunotherapies. As an emerging domain, immunopeptidomics currently lacks standardization-there is neither an established terminology nor formally defined semantics-a critical concern considering the complexity, heterogeneity, and growing volume of data involved in immunopeptidomics studies. Additionally, there is a disconnection between how the proteomics community delivers the information about antigen presentation and its uptake by the clinical genomics community. Considering the significant relevance of immunopeptidomics in cancer, this shortcoming must be addressed to bridge the gap between research and clinical practice. In this work, we detail the development of the ImmunoPeptidomics Ontology, ImPO, the first effort at standardizing the terminology and semantics in the domain. ImPO aims to encapsulate and systematize data generated by immunopeptidomics experimental processes and bioinformatics analysis. ImPO establishes cross-references to 24 relevant ontologies, including the National Cancer Institute Thesaurus, Mondo Disease Ontology, Logical Observation Identifier Names and Codes and Experimental Factor Ontology. Although ImPO was developed using expert knowledge to characterize a large and representative data collection, it may be readily used to encode other datasets within the domain. Ultimately, ImPO facilitates data integration and analysis, enabling querying, inference and knowledge generation and importantly bridging the gap between the clinical proteomics and genomics communities. As the field of immunogenomics uses protein-level immunopeptidomics data, we expect ImPO to play a key role in supporting a rich and standardized description of the large-scale data that emerging high-throughput technologies are expected to bring in the near future. Ontology URL: https://zenodo.org/record/10237571 Project GitHub: https://github.com/liseda-lab/ImPO/blob/main/ImPO.owl.

Comparative characterization of two monoclonal antibodies targeting canine PD-1.

Monoclonal antibodies targeting immune checkpoints have revolutionized oncology. Yet, the effectiveness of these treatments varies significantly among patients, and they are associated with unexpected adverse events, including hyperprogression. The murine research model used in drug development fails to recapitulate both the functional human immune system and the population heterogeneity. Hence, a novel model is urgently needed to study the consequences of immune checkpoint blockade. Dogs appear to be uniquely suited for this role. Approximately 1 in 4 companion dogs dies from cancer, yet no antibodies are commercially available for use in veterinary oncology. Here we characterize two novel antibodies that bind canine PD-1 with sub-nanomolar affinity as measured by SPR. Both antibodies block the clinically crucial PD-1/PD-L1 interaction in a competitive ELISA assay. Additionally, the antibodies were tested with a broad range of assays including Western Blot, ELISA, flow cytometry, immunofluorescence and immunohistochemistry. The antibodies appear to bind two distinct epitopes as predicted by molecular modeling and peptide phage display. Our study provides new tools for canine oncology research and a potential veterinary therapeutic.

Heterogeneity between diagnostic tests for IgA anti-beta2 glycoprotein I: explaining the controversy in studies of association with vascular pathology.

IgA antibeta 2 Glycoprotein I (ß2GPI) antibodies test can identify some patients with antiphospholipid syndrome (APS) that are negative for other isotypes. Controversy exists because some studies have reported a strong association of these antibodies with vascular disease, while others have not confirmed this observation. Our hypothesis is that these contradictory results may be due to differences among commercial diagnostic kits. To answer this question, we have compared the results obtained with several of the most commonly used commercial IgA anti ß2GPI antibodies (aß2GPI) diagnostic assays on specimens from individuals suspected of having APS. Sera from 69 patients (37 positive and 32 negative for IgA aß2GPI) were analyzed with seven different commercial ELISA kits for IgA aß2GPI, following instructions and cutoffs provided by the manufacturer. Our results showed important differences in the sensitivity and specificity of the different assays. Two of the seven kits tested had a sensitivity level below 65% for IgA aß2GPI, and three showed levels of specificity lower than 80%. Some commercial kits to detect IgA aß2GPI are suboptimal. Variability between kits may account for the discrepancy in results obtained and for the lack of consensus concerning their clinical significance. It is important that the scientific community work to standardize assay performance so that the true clinical significance of this important clinical marker can be clearly established.

Unraveling the glycosylated immunopeptidome with HLA-Glyco.

Recent interest in targeted therapies has been sparked by the study of MHC-associated peptides (MAPs) that undergo post-translational modifications (PTMs), particularly glycosylation. In this study, we introduce a fast computational workflow that merges the MSFragger-Glyco search algorithm with a false discovery rate control for glycopeptide analysis from mass spectrometry-based immunopeptidome data. By analyzing eight large-scale publicly available studies, we find that glycosylated MAPs are predominantly presented by MHC class II. Here, we present HLA-Glyco, a comprehensive resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. This resource provides valuable insights, including high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between HLA allele groups. We integrate the workflow within the FragPipe computational platform and provide HLA-Glyco as a free web resource. Overall, our work provides a valuable tool and resource to aid the nascent field of glyco-immunopeptidomics.

The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides.

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I-associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

Sequence-dependent effects of cryoprotectants on the active sites of the human ABO(H) blood group A and B glycosyltransferases.

The human ABO(H) A and B blood group glycosyltransferases GTA and GTB differ by only four amino acids, yet this small dissimilarity is responsible for significant differences in biosynthesis, kinetics and structure. Like other glycosyltransferases, these two enzymes have been shown to recognize substrates through dramatic conformational changes in mobile polypeptide loops surrounding the active site. Structures of GTA, GTB and several chimeras determined by single-crystal X-ray diffraction demonstrate a range of susceptibility to the choice of cryoprotectant, in which the mobile polypeptide loops can be induced by glycerol to form the ordered closed conformation associated with substrate recognition and by MPD [hexylene glycol, (±)-2-methyl-2,4-pentanediol] to hinder binding of substrate in the active site owing to chelation of the Mn²âº cofactor and thereby adopt the disordered open state. Glycerol is often avoided as a cryoprotectant when determining the structures of carbohydrate-active enzymes as it may act as a competitive inhibitor for monosaccharide ligands. Here, it is shown that the use of glycerol as a cryoprotectant can additionally induce significant changes in secondary structure, a phenomenon that could apply to any class of protein.

Gorham-Stout case report: a multi-omic analysis reveals recurrent fusions as new potential drivers of the disease.

BACKGROUND: Gorham-Stout disease is a rare condition characterized by vascular proliferation and the massive destruction of bone tissue. With less than 400 cases in the literature of Gorham-Stout syndrome, we performed a unique study combining whole-genome sequencing and RNA-Seq to probe the genomic features and differentially expressed pathways of a presented case, revealing new possible drivers and biomarkers of the disease. CASE PRESENTATION: We present a case report of a white 45-year-old female patient with marked bone loss of the left humerus associated with vascular proliferation, diagnosed with Gorham-Stout disease. The analysis of whole-genome sequencing showed a dominance of large structural DNA rearrangements. Particularly, rearrangements in chromosomes seven, twelve, and twenty could contribute to the development of the disease, especially a gene fusion involving ATG101 that could affect macroautophagy. The study of RNA-sequencing data from the patient uncovered the PI3K/AKT/mTOR pathway as the most affected signaling cascade in the Gorham-Stout lesional tissue. Furthermore, M2 macrophage infiltration was detected using immunohistochemical staining and confirmed by deconvolution of the RNA-seq expression data. CONCLUSIONS: The way that DNA and RNA aberrations lead to Gorham-Stout disease is poorly understood due to the limited number of studies focusing on this rare disease. Our study provides the first glimpse into this facet of the disease, exposing new possible therapeutic targets and facilitating the clinicopathological diagnosis of Gorham-Stout disease.

Interfaces with Structure Dynamics of the Workhorses from Cells Revealed through Cross-Linking Mass Spectrometry (CLMS).

The fundamentals of how protein-protein/RNA/DNA interactions influence the structures and functions of the workhorses from the cells have been well documented in the 20th century. A diverse set of methods exist to determine such interactions between different components, particularly, the mass spectrometry (MS) methods, with its advanced instrumentation, has become a significant approach to analyze a diverse range of biomolecules, as well as bring insights to their biomolecular processes. This review highlights the principal role of chemistry in MS-based structural proteomics approaches, with a particular focus on the chemical cross-linking of protein-protein/DNA/RNA complexes. In addition, we discuss different methods to prepare the cross-linked samples for MS analysis and tools to identify cross-linked peptides. Cross-linking mass spectrometry (CLMS) holds promise to identify interaction sites in larger and more complex biological systems. The typical CLMS workflow allows for the measurement of the proximity in three-dimensional space of amino acids, identifying proteins in direct contact with DNA or RNA, and it provides information on the folds of proteins as well as their topology in the complexes. Principal CLMS applications, its notable successes, as well as common pipelines that bridge proteomics, molecular biology, structural systems biology, and interactomics are outlined.

Functional Interfaces, Biological Pathways, and Regulations of Interferon-Related DNA Damage Resistance Signature (IRDS) Genes.

Interferon (IFN)-related DNA damage resistant signature (IRDS) genes are a subgroup of interferon-stimulated genes (ISGs) found upregulated in different cancer types, which promotes resistance to DNA damaging chemotherapy and radiotherapy. Along with briefly discussing IFNs and signalling in this review, we highlighted how different IRDS genes are affected by viruses. On the contrary, different strategies adopted to suppress a set of IRDS genes (STAT1, IRF7, OAS family, and BST2) to induce (chemo- and radiotherapy) sensitivity were deliberated. Significant biological pathways that comprise these genes were classified, along with their frequently associated genes (IFIT1/3, IFITM1, IRF7, ISG15, MX1/2 and OAS1/3/L). Major upstream regulators from the IRDS genes were identified, and different IFN types regulating these genes were outlined. Functional interfaces of IRDS proteins with DNA/RNA/ATP/GTP/NADP biomolecules featured a well-defined pharmacophore model for STAT1/IRF7-dsDNA and OAS1/OAS3/IFIH1-dsRNA complexes, as well as for the genes binding to GDP or NADP+. The Lys amino acid was found commonly interacting with the ATP phosphate group from OAS1/EIF2AK2/IFIH1 genes. Considering the premise that targeting IRDS genes mediated resistance offers an efficient strategy to resensitize tumour cells and enhances the outcome of anti-cancer treatment, this review can add some novel insights to the field.

Structural determinants of peptide-dependent TAP1-TAP2 transit passage targeted by viral proteins and altered by cancer-associated mutations.

The TAP1-TAP2 complex transports antigenic peptide substrates into the endoplasmic reticulum (ER). In ER, the peptides are further processed and loaded on the major histocompatibility class (MHC) I molecules by the peptide loading complex (PLC). The TAP transporters are linked with the PLC; a target for cancers and viral immune evasion. But the mechanisms whereby the cancer-derived mutations in TAP1-TAP2 or viral factors targeting the PLC, interfere peptide transport are only emerging. This study describes that transit of peptides through TAP can take place via two different channels (4 or 8 helices) depending on peptide length and sequence. Molecular dynamics and binding affinity predictions of peptide-transporters demonstrated that smaller peptides (8-10 mers; e.g. AAGIGILTV, SIINFEKL) can transport quickly through the transport tunnel compared to longer peptides (15-mer; e.g. ENPVVHFFKNIVTPR). In line with a regulated and selective peptide transport by TAPs, the immunopeptidome upon IFN-γ treatment in melanoma cells induced the shorter length (9-mer) peptide presentation over MHC-I that exhibit a relatively weak binding affinity with TAP. A conserved distance between N and C terminus residues of the studied peptides in the transport tunnel were reported. Furthermore, by adversely interacting with the TAP transport passage or affecting TAPNBD domains tilt movement, the viral proteins and cancer-derived mutations in TAP1-TAP2 may induce allosteric effects in TAP that block conformation of the tunnel (closed towards ER lumen). Interestingly, some cancer-associated mutations (e.g. TAP1R372Q and TAP2R373H) can specifically interfere with selective transport channels (i.e. for longer-peptides). These results provide a model for how viruses and cancer-associated mutations targeting TAP interfaces can affect MHC-I antigen presentation, and how the IFN-γ pathway alters MHC-I antigen presentation via the kinetics of peptide transport.

Kinomics platform using GBM tissue identifies BTK as being associated with higher patient survival.

Better understanding of GBM signalling networks in-vivo would help develop more physiologically relevant ex vivo models to support therapeutic discovery. A "functional proteomics" screen was undertaken to measure the specific activity of a set of protein kinases in a two-step cell-free biochemical assay to define dominant kinase activities to identify potentially novel drug targets that may have been overlooked in studies interrogating GBM-derived cell lines. A dominant kinase activity derived from the tumour tissue, but not patient-derived GBM stem-like cell lines, was Bruton tyrosine kinase (BTK). We demonstrate that BTK is expressed in more than one cell type within GBM tissue; SOX2-positive cells, CD163-positive cells, CD68-positive cells, and an unidentified cell population which is SOX2-negative CD163-negative and/or CD68-negative. The data provide a strategy to better mimic GBM tissue ex vivo by reconstituting more physiologically heterogeneous cell co-culture models including BTK-positive/negative cancer and immune cells. These data also have implications for the design and/or interpretation of emerging clinical trials using BTK inhibitors because BTK expression within GBM tissue was linked to longer patient survival.