The role of eosinophils in COPD and their utility as biomarkers for cytokine targeting monoclonal therapies remains unclear. We investigated the distribution of eosinophils across different tissue compartments in COPD and analysed gene expression to understand the possible mechanistic drivers of eosinophilic inflammation in COPD. Blood and BAL from ex-smoking volunteers with mild/moderate COPD (n = 31) and healthy ex-smoking controls (n = 20), and bronchial biopsy tissue in a subcohort (n = 19 and n = 8, respectively) was analysed. Differentially-expressed genes (DEGs) were characterised using RNASeq. Proteomic analysis of BAL was conducted using mass-spectrometry. COPD subjects had more eosinophils in blood and lung tissue compared to controls, with increased eosinophil protein CLC/Galectin-10 in BAL. However, peripheral blood eosinophil counts related poorly to numbers in lung tissue (rho = -0.09192, p = 0.3541) or proportions in BAL (rho = 0.01762, p = 0.4632). Tissue IL-5Rα expression was higher in frequent exacerbators and related to tissue eosinophils, but not peripheral blood eosinophils. Higher blood eosinophils were associated with DEGs that differed with compartment. Higher tissue eosinophil levels were associated with IL-13-induced DEGs including POSTN in bronchial brushes and CCL26 in bronchial biopsies. Gene-set enrichment analysis on data from brushings revealed significant enrichment of IL-4/IL-13, but not IL-5, pathways associated with eosinophil presence. Eosinophilic lung inflammation is related to exacerbation frequency, but lung eosinophils are not predicted by blood eosinophil counts in COPD. Our data suggest IL-13-mediated pathways may be responsible for the presence of tissue eosinophils in COPD. Further work to establish more predictive biomarkers of lung eosinophil biology are required to unlock this axis to optimised treatment.

Blood is a valuable resource for clinical research, offering insight into physiological and pathological states. However, the specific proteins detectable in blood and the optimal proteomic methods for their detection have not been rigorously investigated and documented. To address this, we conducted various blood proteomic strategies, including directly blood proteomic analysis, high-abundance protein depletion, low-abundance protein enrichment, and extracellular vesicle enrichment using data-independent acquisition or targeted proteomics. These approaches identified 11,679 protein groups in plasma from healthy individuals. In 136 pancreatic ductal adenocarcinoma whole blood samples, 6,956 protein groups were found, including 678 not seen in healthy samples, expanding the total to 12,357 blood proteins. This represents the most comprehensive blood proteome to date. To support broader access and analysis, we developed the Human Blood Proteome (HuBP) database, detailing protein detectability, abundance, and reproducibility across workflows, sample types, and disease contexts.

Supplementary Figures 1-5 from Identification of Secreted Proteins that Mediate Cell-Cell Interactions in an In vitro Model of the Lung Cancer Microenvironment

The 361-ADCr, a MEDI0641 resistant line, has downregulated target 5T4

Differentially expressed proteins identified in the 361-PBDr cell line

Supplementary Table 2 from Identification of Secreted Proteins that Mediate Cell-Cell Interactions in an In vitro Model of the Lung Cancer Microenvironment

Supplementary Table 1 from Identification of Secreted Proteins that Mediate Cell-Cell Interactions in an In vitro Model of the Lung Cancer Microenvironment

DNA damage checkpoint activation mediated by SLFN11 and ATR pathways in response to SG3199.

The addition of the ATR inhibitor, AZD6738, did not show synergistic cytotoxicity with SG3199 or ADCs in parental MDA-MB-361 cells

Knockdown of 5T4 expression do not confer SG3199 resistance to parental MDA-MB-361 cells.

Characterization of 361-PBDr resistant line

Supplementary Table S3 from Antitumor activity and molecular effects of the novel heat shock protein 90 inhibitor, IPI-504, in pancreatic cancer

Human antigen R (HuR) is a ubiquitously expressed RNA-binding protein, which functions as an RNA regulator. Overexpression of HuR correlates with high grade tumours and poor patient prognosis, implicating it as an attractive therapeutic target. However, an effective small molecule antagonist to HuR for clinical use remains elusive. Here, a single domain antibody (VHH) that binds HuR with low nanomolar affinity was identified and shown to inhibit HuR binding to RNA. This VHH was used to engineer a TRIM21-based biological PROTAC (bioPROTAC) that could degrade endogenous HuR. Significantly, HuR degradation reverses the tumour-promoting properties of cancer cells in vivo by altering the HuR-regulated proteome, highlighting the benefit of HuR degradation and paving the way for the development of HuR-degrading therapeutics. These observations have broader implications for degrading intractable therapeutic targets, with bioPROTACs presenting a unique opportunity to explore targeted-protein degradation through a modular approach.

Omics-based tools were coupled with bioinformatics for a systeomics analysis of two biopharma cell types: Chinese hamster ovary (M-CHO and CHO-K1) and SP2/0. Exponential and stationary phase samples revealed more than 10,000 transcripts and 6000 proteins across these two manufacturing cell lines. A statistical comparison of transcriptomics and proteomics data identified downregulated genes involved in protein folding, protein synthesis and protein metabolism, including PPIA-cyclophilin A, HSPD1, and EIF3K, in M-CHO compared to SP2/0 while cell cycle and actin cytoskeleton genes were reduced in SP2/0. KEGG pathway comparisons revealed glycerolipids, glycosphingolipids, ABC transporters, calcium signaling, cell adhesion, and secretion pathways depleted in M-CHO while retinol metabolism was upregulated. KEGG and IPA also indicated apoptosis, RNA degradation, and proteosomes enriched in CHO stationary phase. Alternatively, gene ontology analysis revealed an underrepresentation in ion and potassium channel activities, membrane proteins, and secretory granules including Stxbpt2, Syt1, Syt9, and Cma1 proteins in M-CHO. Additional enrichment strategies involving ultracentrifugation, biotinylation, and hydrazide chemistry identified over 4000 potential CHO membrane and secretory proteins, yet many secretory and membrane proteins were still depleted. This systeomics pipeline has revealed bottlenecks and potential opportunities for cell line engineering in CHO and SP2/0 to improve their production capabilities.

Rationale Pulmonary surfactant is vital for lung homeostasis as it reduces surface tension to prevent alveolar collapse and provides essential immune-regulatory and antipathogenic functions. Previous studies demonstrated dysregulation of some individual surfactant components in COPD. We investigated relationships between COPD disease measures and dysregulation of surfactant components to gain new insights into potential disease mechanisms. Methods Bronchoalveolar lavage proteome and lipidome were characterised in ex-smoking mild/moderate COPD subjects (n=26) and healthy ex-smoking (n=20) and never-smoking (n=16) controls using mass spectrometry. Serum surfactant protein analysis was performed. Results Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, surfactant protein (SP)-B, SP-A and SP-D concentrations were lower in COPD versus controls (log2 fold change (log2FC) −2.0, −2.2, −1.5, −0.5, −0.7 and −0.5 (adjusted p<0.02), respectively) and correlated with lung function. Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D, napsin A and CD44 inversely correlated with computed tomography small airways disease measures (expiratory to inspiratory mean lung density) (r= −0.56, r= −0.58, r= −0.45, r= −0.36, r= −0.44, r= −0.37, r= −0.40 and r= −0.39 (adjusted p<0.05)). Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D and NAPSA inversely correlated with emphysema (% low-attenuation areas): r= −0.55, r= −0.61, r= −0.48, r= −0.51, r= −0.41, r= −0.31 and r= −0.34, respectively (adjusted p<0.05). Neutrophil elastase, known to degrade SP-A and SP-D, was elevated in COPD versus controls (log2FC 0.40, adjusted p=0.0390), and inversely correlated with SP-A and SP-D. Serum SP-D was increased in COPD versus healthy ex-smoking volunteers, and predicted COPD status (area under the curve 0.85). Conclusions Using a multiomics approach, we demonstrate, for the first time, global surfactant dysregulation in COPD that was associated with emphysema, giving new insights into potential mechanisms underlying the cause or consequence of disease.

With the aim of increasing protein productivity of Chinese hamster ovary (CHO) cells, we sought to generate new CHO hosts with favorable biomanufacturing phenotypes and improved functionality. Here, we present an innovative approach of enriching the CHO host cells with a high mitochondrial membrane potential (MMP). Stable transfectant pools and clonal cell lines expressing difficult-to-express bispecific molecules generated from the MMP-enriched host outperformed the parental host by displaying (1) improved fed-batch productivity; (2) enhanced long-term cell viability of pools; (3) more favorable lactate metabolism; and (4) improved cell cloning efficiency during monoclonal cell line generation. Proteomic analysis together with Western blot validation were used to investigate the underlying mechanisms by which high MMP influenced production performance. The MMP-enriched host exhibited multifaceted protection against mitochondrial dysfunction and endoplasmic reticulum stress. Our findings indicate that the MMP-enriched host achieved an overall "fitter" phenotype that contributes to the significant improvement in biomanufacturing capability.

Citrullination is an important post-translational modification implicated in many diseases including rheumatoid arthritis (RA), Alzheimer's disease, and cancer. Neutrophil and mast cells have different expression profiles for protein-arginine deiminases (PADs), and ionomycin-induced activation makes them an ideal cellular model to study proteins susceptible to citrullination. We performed high-resolution mass spectrometry and stringent data filtration to identify citrullination sites in neutrophil and mast cells treated with and without ionomycin. We identified a total of 833 validated citrullination sites on 395 proteins. Several of these citrullinated proteins are important components of pathways involved in innate immune responses. Using this benchmark primary sequence data set, we developed machine learning models to predict citrullination in neutrophil and mast cell proteins. We show that our models predict citrullination likelihood with 0.735 and 0.766 AUCs (area under the receiver operating characteristic curves), respectively, on independent validation sets. In summary, this study provides the largest number of validated citrullination sites in neutrophil and mast cell proteins. The use of our novel motif analysis approach to predict citrullination sites will facilitate the discovery of novel protein substrates of protein-arginine deiminases (PADs), which may be key to understanding immunopathologies of various diseases.

Abstract Resistance to antibody–drug conjugates (ADCs) has been observed in both preclinical models and clinical studies. However, mechanisms of resistance to pyrrolobenzodiazepine (PBD)-conjugated ADCs have not been well characterized and thus, this study was designed to investigate development of resistance to PBD dimer warheads and PBD-conjugated ADCs. We established a PBD-resistant cell line, 361-PBDr, by treating human breast cancer MDA-MB-361 cells with gradually increasing concentrations of SG3199, the PBD dimer released from the PBD drug-linker tesirine. 361-PBDr cells were over 20-fold less sensitive to SG3199 compared with parental cells and were cross-resistant to other PBD warhead and ADCs conjugated with PBDs. Proteomic profiling revealed that downregulation of Schlafen family member 11 (SLFN11), a putative DNA/RNA helicase, sensitizing cancer cells to DNA-damaging agents, was associated with PBD resistance. Confirmatory studies demonstrated that siRNA knockdown of SLFN11 in multiple tumor cell lines conferred reduced sensitivity to SG3199 and PBD-conjugated ADCs. Treatment with EPZ011989, an EZH2 inhibitor, derepressed SLFN11 expression in 361-PBDr and other SLFN11-deficient tumor cells, and increased sensitivity to PBD and PBD-conjugated ADCs, indicating that the suppression of SLFN11 expression is associated with histone methylation as reported. Moreover, we demonstrated that combining an ataxia telangiectasia and Rad3-related protein (ATR) inhibitor, AZD6738, with SG3199 or PBD-based ADCs led to synergistic cytotoxicity in either resistant 361-PBDr cells or cells that SLFN11 was knocked down via siRNA. Collectively, these data provide insights into potential development of resistance to PBDs and PBD-conjugated ADCs, and more importantly, inform strategy development to overcome such resistance.

Introduction and Objectives Pulmonary surfactant homeostasis is critical to lung function as it coats the vast air-liquid interface, reducing surface tension and preventing alveolar collapse. surfactant proteins (SP)-A and D play essential anti-pathogenic defence and immunoregulation roles to maintain lung homeostasis. SP-D is reduced in COPD. We hypothesised lipid and protein surfactant dysregulation could contribute to pathological COPD mechanisms, this requires detailed characterisation. Methods We conducted mass spectrometry-based multiomic (proteomic, lipidomic and metabolomic) analysis of bronchoalveolar lavage to comprehensively characterize surfactant dysregulation in a well-characterised ex-smoking mild/moderate COPD cohort (n=31), with median (IQR) age of 70 (9.5) and FEV1% predicted 73 (21), compared with healthy ex-smoking volunteers (n=20), with age 67.5 (6.75) and FEV1% predicted 100.5 (11.75). To identify the multiomic signatures of COPD, we fitted linear mixed-effects models to the data, accounting for the effects of confounding variables, such as age, gender and individual differences simultaneously. We further characterised purified alveolar macrophage gene expression differences. Results SP-A, SP-B, and SP-D levels were lower in COPD vs control with log2fold changes (FC) of -0.7 (p=1.1x10-6), -0.6 (p=4.8x10-6) and -0.6 (p=3.0x10-5), and showed positive correlations of 0.65 (p=1.5x10-12), 0.62 (p=7.7x10-11) and 0.43 (p=2.3x10-4) with lung function (FEV1/FVC), respectively. SP-C was below detection limit. NAPSA and CTSH, responsible for SP-B synthesis, were lower in COPD, log2FC of -0.1 (p=2.8x10-6) and -0.4 (p=4.3x10-4), respectively. Fatty acid binding protein 4 (FABP4) and CD44, involved in surfactant regulation, were decreased in COPD, log2FC of -0.4 (p=8.0x10-3) and -0.7 (p=1.1x10-5), respectively. Histamine and hypoxanthine metabolites were increased in COPD, log2FC of 0.8 (p=2.5x10-2) and 1.0 (p=4.0x10-2), respectively, which could indicate immune-dysregulation and inflammation. Surfactant lipid levels were decreased in COPD, specifically, PC, PG, and PI, log2FC of -2.1 (p=2.6×10-7), -2.4 (p=5.3×10-8) and -1.5 (p=9.0×10-6), respectively. Conclusions We used a multiomics approach to comprehensively describe surfactant dysregulation in a well-characterised COPD cohort, with an aim to generate novel insights into key aspects of this biology within the COPD lung. Further mechanistic studies could help to understand the role this plays in pathological mechanisms and allow novel therapeutic target identification. Please refer to page A190 for declarations of interest related to this abstract.

Neoantigens act as surrogates for T cell immunoreactivity and have been shown to correlate with patients’ response to immune checkpoint inhibitors (ICI). Here, we have developed a multi-allele convolutional neural network-based model, MINERVA, for predicting HLA class I (HLA-I) presentation of tumor antigenic peptides using transfer learning with immunopeptidome data from cancer patients. We show that MINERVA recapitulates physicochemical properties of naturally presented peptides that are relevant to tumor biology and is more sensitive to tumor-derived HLA presented peptides than existing algorithms. Without a priori knowledge provided to MINERVA, the model was able to learn the determinants of peptide-HLA presentation and we utilized the learnt features to understand the impact of mutations on neoantigen presentation. Furthermore, we show that the diversity of tumor peptides being presented by a pair of alleles are significantly correlated with HLA sequence divergence. In conclusion, MINERVA is an open source software that can greatly facilitate tumor neoantigen discovery and guide cancer immunotherapies.