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Executive Summary A national survey on integrated diabetes services was carried out by the Association of British Clinical Diabetologists (ABCD) during the COVID-19 pandemic and has provided some very useful insights into the current state of integration to deliver a joined-up diabetes service in the UK. This survey was carried out during the second half of 2020 and explored three main areas: (1) current state of clinical integration between primary and secondary (specialist) diabetes services; (2) the state of IT integration among the diabetes IT systems and hospital-based electronic patient records (EPR) and between hospital and primary care; (3) to ascertain the membership of their views on a ‘one-stop service’ for collecting annual review data for diabetes and the potential barriers to achieve this. The results presented are a summary of the survey, while the full unedited survey report, especially on the qualitative aspects, is available to ABCD members. The survey was mailed to 518 individuals, of which 431 (83.2%) were consultants and 53 (10.2%) were specialist registrars. Of the 83 replies received, 98% were from consultants and the responses represented a total of 73 hospital diabetes services. The findings of this survey revealed that full integration of clinical services among primary care and specialist diabetes teams is uncommon, although there are good examples of clinical integration in different formats. In a number of areas, primary care and specialist diabetes services continue to work in silos despite a universal recognition that integrated services are desirable and are likely to improve quality of care. Clinical leadership, resources and buy-in from those who commission services were deemed important factors to help improve the development of integrated care systems. In hospitals with dedicated diabetes IT systems the information flow from these diabetes systems to the EPR was not universal, raising concerns that vital information about an individual’s diabetes may not be available to other hospital clinical specialities at the time of delivery of care, posing a significant clinical risk. IT integration among primary and specialist diabetes teams in England was only available in certain areas and was mostly based around the use of SystmOne. The survey also identified a diversity of opinions regarding the current arrangements of the Quality Outcome Framework (QOF), where GPs are incentivised to collect data for annual review of routine diabetes care. Many were of the opinion that annual review processes should be performed by clinical teams who are tasked to deliver diabetes care to the individual, while others felt that the status quo should continue with primary care GPs being responsible. A one-stop service for eye screening for diabetes and other annual measurements nearer to people’s homes was identified as an improvement, but several logistic barriers were identified. We recognise the limitations of any survey which expresses opinions of participants. However, we believe the present survey represents a significant proportion of diabetes units in the UK and provides insights into the current state of integrated services in diabetes. There are significant learnings for diabetes communities, and the information can be used to improve and galvanise delivery of integrated diabetes care in the UK.

Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified. Multi-omics datasets are integrated to generate a unified and clinically informed molecular classification of meningiomas.

Axons are complex subcellular compartments that are extremely long in relation to cell bodies, especially in peripheral nerves. Many processes are required and regulated during axon injury, including anterograde and retrograde transport, glia-to-axon macromolecular transfer, and local axonal protein synthesis. Many in vitro omics approaches have been used to gain insight into these processes, but few have been applied in vivo. Here we adapted the osmotic ex vivo axoplasm isolation method and analyzed the adult rat sciatic-nerve-extruded axoplasm by label-free quantitative proteomics before and after injury. 2087 proteins groups were detected in the axoplasm, revealing translation machinery and microtubule-associated proteins as the most overrepresented biological processes. Ribosomal proteins (73) were detected in the uninjured axoplasm and increased their levels after injury but not within whole sciatic nerves. Meta-analysis showed that detected ribosomal proteins were present in in vitro axonal proteomes. Because local protein synthesis is important for protein localization, we were interested in detecting the most abundant newly synthesized axonal proteins in vivo. With an MS/MS-BONCAT approach, we detected 42 newly synthesized protein groups. Overall, our work indicates that proteomics profiling is useful for local axonal interrogation and suggests that ribosomal proteins may play an important role, especially during injury.

Triple negative breast cancer (TNBC) stands out due to its aggressive course and high metastatic rates. No consistent protein biomarker has been described for TNBC, resulting in a scarcity of adjuvant therapies for the afflicted patients. Hence, there is an urgent need to determine novel TNBC-associated proteins for the development of new therapeutics and the identification of novel molecular mechanisms driving this malignancy. Cell surface proteins represent attractive targets for novel therapies, due to their easily accessible localization and their involvement in essential signaling pathways. Objectives: We aimed to uncover novel TNBC-associated cell surface proteins involved in carcinogenesis and metastasis for the development of novel targeted therapeutics. Rationale: Taking advantage of the fact that cell surface proteins are often N-glycosylated, we employed hydrazide chemistry to isolate N-glycopeptides. The glycoproteome of six immortalized TNBC cell lines and five ‘healthy’ controls (HC) (the immortalized cell line MCF10A and four patient-derived human mammary epithelial cell lines) was analyzed using LC-MS/MS and label-free quantification. A data mining strategy was employed to select candidates of interest. We knocked-down (k.d.) the top five candidates of interest (using siRNA technology) and evaluated cell growth using growth-curve analysis. Plexin B3 (PLXNB3) was selected for subsequent functional validations. The effects of PLXNB3 k.d. (using siRNA and CRISPR technology) on cancer cell growth, apoptosis and adhesion were interrogated using western blotting and standard cell biology protocols.Results: The N-glycoproteomics approach led to the identification of 1044 glycoproteins, with over 70% described as plasma membrane/secreted proteins. Gene Ontology analysis revealed that the TNBC-associated glycoproteome was enriched in biological processes such as: mesenchyme development, MAPK signaling, positive regulation of proliferation and regulation of neuron projection development. Candidates of interest were selected from our list by focusing on those plasma membrane proteins that were enriched in TNBC cells compared to HC according to our label-free quantified proteomics data, and that showed limited expression in healthy tissues according to the Human Protein Atlas. We further restricted the list of candidates to those proteins whose k.d. impaired cancer cell growth, with little effect on the HC. PLXNB3, an understudied protein typically expressed in healthy neuronal tissues, was selected for in depth functional analysis. Elevated mRNA PLXNB3 levels in breast cancer patients is associated with poorer overall survival compared to low mRNA expression (Integrated TCGA Pan-Cancer Clinical Data Resource, 2018). PLXNB3 k.d. (using siRNA and CRISPR technologies) impaired TNBC cell growth (in both adherent and spheroid cultures) and was associated with elevated levels of cleaved-caspase 3 and cleaved-caspase 7 compared to scrambled controls. Furthermore, PLXNB3 k.d. negatively impacted TNBC cell adhesion to extracellular matrixes compared to scrambled controls. Subsequent tests will evaluate PLXNB3’s role in tumor growth and metastasis in vivo, using orthotopic tumor models in immunocompromised mice. Citation Format: Laura Kuhlmann, Ankit Sinha, Vladimir Ignatchenko, Andrew Macklin, Lydia Liu, Meinusha Govindarajan, Amanda Khoo, Salvador Mejia-Guerrero, Jennifer Cruickshank, Hal Berman, Thomas Kislinger. Identification of cell surface proteins in triple negative breast cancer for the development of novel targeted therapies [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-31.

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.

Medulloblastoma (MB) is the most common type of malignant pediatric brain cancer. Current standard of care (SOC) involves maximal safe resection and neuraxis radiotherapy and chemotherapy in individuals older than 3 years. To date, these cytotoxic SOC combined with craniospinal irradiation led to devastating neurocognitive and developmental deficits impacting quality of life for pediatric patients. The biological heterogeneity of MB is highlighted by the existence of four distinct molecular subgroups (WNT, SHH, Group 3, and Group 4). Group 3 and Group 4 have the poorest patient outcomes because of their aggressive, metastatic nature, and so often remain treatment refractory to SOC. Group 3 has a poor prognosis due to its high incidence of leptomeningeal spread and an overall survival rate of less than 50%. The cytotoxic nature and lack of response in specific subtypes to SOC underscores the urgent need for developing and translating novel treatment options including immunotherapies. In our earlier work, we have developed a therapy-adapted patient derived xenograft (PDX) model of the Group 3 MB as the tumor cells undergoes therapy in vitro and in vivo. N-glycocapture surfaceome profiling of the MB cells through this PDX model identified Integrin α5 (ITGA5) as one of the most differentially expressed targets found at recurrence when compared to engraftment and untreated timepoints. Through shRNA knockdown and small molecule inhibition, we identify ITGA5 expression marks a MB cell subpopulation with increased self-renewal ability both in vitro and in vivo. Access to recurrent MB (rMB) post-therapy allowed us to investigate the changes in the surfaceome of MB cells using proteomics profiling to identify promising rMB-specific targets for rational development of novel immunotherapies.

To model the problem of radiation resistance in prostate cancer, cell lines mimicking a clinical course of conventionally fractionated or hypofractionated radiotherapy have been generated. Proteomic analysis of radiation resistant and radiosensitive DU145 prostate cancer cells detected 4410 proteins. Over 400 proteins were differentially expressed across both radiation resistant cell lines and pathway analysis revealed enrichment in epithelial to mesenchymal transition, glycolysis and hypoxia. From the radiation resistant protein candidates, the cell surface protein CD44 was identified in the glycolysis and epithelial to mesenchymal transition pathways and may serve as a potential therapeutic target.

Sodium glucose co-transporter 2 (SGLT2) inhibitors are now an established class of medications for the treatment of type 2 diabetes (T2D), no longer reserved for use by specialists in diabetes. They are being used increasingly for their cardiac and renal benefits by primary care, cardiology and renal teams for indications in parallel with diabetes care as part of holistic management. This guidance provides essential information on SGLT therapy, including the main advantages and the important risks of which healthcare professionals should be aware.

SummaryPancreatic ductal adenocarcinoma (PDAC) remains resistant to most treatments and demonstrates a complex pathobiology. Here, we deconvolute regional heterogeneity in the human PDAC tumor microenvironment (TME), a long-standing obstacle, to define precise stromal contributions to PDAC progression. Large scale integration of histology-guided multiOMICs with clinical data sets and functional in vitro models uncovers two microenvironmental programs in PDAC that were anchored in fibroblast differentiation states. These sub-tumor microenvironments (subTMEs) co-occurred intratumorally and were spatially confined, producing patient-specific cellular and molecular heterogeneity associated with shortened patient survival. Each subTME was uniquely structured to support discrete aspects of tumor biology: reactive regions rich in activated fibroblast communities were immune-hot and promoted aggressive tumor progression while deserted regions enriched in extracellular matrix supported tumor differentiation yet were markedly chemoprotective. In conclusion, PDAC regional heterogeneity derives from biologically distinct reactive and protective TME elements with a defined, active role in PDAC progression.Graphical Abstract & Key findingsPDAC regional heterogeneity originates in sub-tumor microenvironments (subTMEs)SubTMEs exhibit distinct immune phenotypes and CAF differentiation statesDifferent subTMEs are either tumor-promoting or chemoprotectiveIntratumoral subTME co-occurrence links stromal heterogeneity to patient outcome

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality., Distributed multi-omic digitization of clinical specimen across multiple sites is a prerequisite for turning molecular precision medicine into reality. Here, the authors show that coordinated proteotype data acquisition is feasible using standardized MS data acquisition and analysis strategies.

Dapagliflozin (sodium-glucose co-transporter (SGLT-2) inhibitor) and sotagliflozin (SGLT-1/2 inhibitor) are two of the drugs of the SGLT inhibitor class which have been recommended by the National Institute for Health and Care Excellence (NICE) in people with type 1 diabetes with body mass index ≥27 kg/m2. Dapagliflozin is licensed in the UK for use in the NHS while sotagliflozin may be available in future. These and possibly other SGLT inhibitors may be increasingly used in people with type 1 diabetes as new licences are obtained. These drugs have the potential to improve glycaemic control in people with type 1 diabetes with the added benefit of weight loss, better control of blood pressure and more time in optimal glucose range. However, SGLT inhibitors are associated with a higher incidence of diabetic ketoacidosis without significant hyperglycaemia. The present ABCD/Diabetes UK joint updated position statement is to guide people with type 1 diabetes and clinicians using these drugs to help mitigate this risk and other potential complications. Particularly, caution needs to be exercised in people who are at risk of diabetic ketoacidosis due to low calorie diets, illnesses, injuries, starvation, excessive exercise, excessive alcohol consumption and reduced insulin administration, among other precipitating factors for diabetic ketoacidosis.

The development of functionally selective or biased ligands is a promising approach towards drugs with less side effects. Biased ligands for G protein-coupled receptors can selectively induce G protein activation or β-arrestin recruitment. The consequences of this selective action on cellular functions, however, are not fully understood. Here, we investigated the impact of five biased and balanced dopamine D2 receptor agonists and antagonists on the global protein expression in HEK293T cells by untargeted nanoscale liquid chromatography–tandem mass spectrometry. The proteome analysis detected 5290 protein groups. Hierarchical clustering and principal component analysis based on the expression levels of 1462 differential proteins led to a separation of antagonists and balanced agonist from the control treatment, while the biased ligands demonstrated larger similarities to the control. Functional analysis of affected proteins revealed that the antagonists haloperidol and sulpiride regulated exocytosis and peroxisome function. The balanced agonist quinpirole, but not the functionally selective agonists induced a downregulation of proteins involved in synaptic signaling. The β-arrestin-preferring agonist BM138, however, regulated several proteins related to neuron function and the dopamine receptor-mediated signaling pathway itself. The G protein-selective partial agonist MS308 influenced rather broad functional terms such as DNA processing and mitochondrial translation.

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

Programmed cell death 4 (PDCD4) protein is a tumor suppressor that inhibits translation through the mTOR-dependent initiation factor EIF4A, but its functional role and mRNA targets in neurons remain largely unknown. Our work identified that PDCD4 is highly expressed in axons and dendrites of CNS and PNS neurons. Using loss- and gain-of-function experiments in cortical and dorsal root ganglia primary neurons, we demonstrated the capacity of PDCD4 to negatively control axonal growth. To explore PDCD4 transcriptome and translatome targets, we used Ribo-seq and uncovered a list of potential targets with known functions as axon/neurite outgrowth regulators. In addition, we observed that PDCD4 can be locally synthesized in adult axons in vivo, and its levels decrease at the site of peripheral nerve injury and before nerve regeneration. Overall, our findings demonstrate that PDCD4 can act as a new regulator of axonal growth via the selective control of translation, providing a target mechanism for axon regeneration and neuronal plasticity processes in neurons.

Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. Here, we deconvolute the human pancreatic TME through large-scale integration of histology-guided regional multiOMICs with clinical data and patient-derived preclinical models. We discover "subTMEs," histologically definable tissue states anchored in fibroblast plasticity, with regional relationships to tumor immunity, subtypes, differentiation, and treatment response. "Reactive" subTMEs rich in complex but functionally coordinated fibroblast communities were immune hot and inhabited by aggressive tumor cell phenotypes. The matrix-rich "deserted" subTMEs harbored fewer activated fibroblasts and tumor-suppressive features yet were markedly chemoprotective and enriched upon chemotherapy. SubTMEs originated in fibroblast differentiation trajectories, and transitory states were notable both in single-cell transcriptomics and in situ. The intratumoral co-occurrence of subTMEs produced patient-specific phenotypic and computationally predictable heterogeneity tightly linked to malignant biology. Therefore, heterogeneity within the plentiful, notorious pancreatic TME is not random but marks fundamental tissue organizational units.

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics’ integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Pancreatic ductal adenocarcinoma (PDAC) remains mostly untreatable while its incidence is on the rise. PDAC stroma should be a reservoir for novel therapeutic targets. Yet, stromal cellular complexity and an extensive intratumoral heterogeneity in human patients have left the functions of PDAC stroma poorly understood and likely hamper its targeting. Here, we set out to deconvolute regional heterogeneity in human PDAC stroma and assess its role in disease progression. Using resected & advanced biospecimens with known patient outcome, we mapped the stromal and epithelial landscapes of PDAC by combining integrative histopathology, quantitative image analysis of a 30-marker IHC panel, genomics and proteomics, machine learning, scRNAseq of PDAC-derived fibroblasts, and controlled functional assays. This histology-guided multidimensional approach revealed two overarching types of sub-tumormicroenvironments (subTMEs) in PDAC, present across stages and primary and metastatic sites. These subTMEs co-occurred intratumourally but were spatially confined, producing patient-specific cellular and molecular heterogeneity in PDAC stroma. SubTME-resolved IHC characterization of PDAC specimens and multiplexed functional analyses with subTME-specific patient-derived fibroblasts and organoids then identified how both microenvironmental programs were uniquely structured to support crucial aspects of tumour biology. Forming a complementary stromal support system, reactive subTME regions rich in fibroblasts and immune cells were vascularized and promoted features of aggressive tumour progression, while protective subTME regions enriched in ECM supported tumour differentiation yet were markedly chemoprotective and translated into poor treatment response during 1st line chemotherapy. Consequently, tumours benefited from concomitant presence of both subTMEs and patients with phenotypically heterogenous stroma displayed shortened survival. Our patient-matched multidimensional data were then used to train a Random Forest model for prediction of subTME presence from bulk RNAseq samples. This again stratified PDAC patients in the independent TCGA cohort into distinct clinical outcomes by stromal phenotypic heterogeneity. In conclusion, we have delineated human PDAC stroma to subtype its heterogeneity into phenotypically distinct reactive and protective elements. This defines the active role of two overarching sub-microenvironment types in PDAC progression and sets a path towards developing novel stroma-instructed therapies. Citation Format: Barbara T. Grünwald, Antoine Devisme, Foram Vyas, Geoffroy Andrieux, Gun Ho Jang, Kazeera Aliar, Curtis McCloskey, Andrew Macklin, Joan Miguel Romero, Laura Tamblyn, Nikolina Radulovich, Peter Bronsert, Grainne O’Kane, Julie Wilson, Jennifer Knox, Sandra Fischer, Thomas Kislinger, Melanie Boerries, Steven Gallinger, Rama Khokha. Stromal phenotypic heterogeneity fosters pancreatic cancer progression [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-002.

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in humans, bearing an overwhelmingly poor prognosis and characterized by a diverse cellular phenotype and genetic heterogeneity. Despite multimodal therapy, patients on average experience relapse at 9 months and median survival rarely extends beyond 15 months. Treatment of human GBM with standard-of-care (SOC) chemo-radiotherapy invariably leads to resistance. Poor patient survival correlates with marker expression of brain tumor-initiating cells (BTICs), which are implicated in therapeutic resistance and may explain tumor relapse. Targeting the cells that drive GBM formation as well as its inevitable and rapid recurrence post-therapy has remained a major challenge, likely due to intra-tumoral heterogeneity. Proteomic profiling constitutes a promising tool to identify novel cancer targets. In this study, we have adopted a non-biased mass spectrometry approach to identify cell surface peptides isolated from patient-derived GBM BTIC lines through a glycocapture approach. We have identified proteins that are differentially expressed in recurrent GBM BTICs compared to primary GBM BTICs. Moreover, we perform comparative proteomics from recurrent GBM BTICs generated from our in vivo mouse-adapted therapy model, which has the distinct advantage of generating recurrent, treatment-refractory GBM. Our surface proteomic profiling thus provides a comprehensive network of signaling molecules selectively enriched in recurrent GBM cells. Identification of cell surface proteins that may drive treatment resistance will contribute greatly to identify novel immunotherapeutic targets for GBM.

The use of engineered viral strains such as gene therapy vectors and oncolytic viruses (OV) to selectively destroy cancer cells is poised to make a major impact in the clinic and revolutionize cancer therapy. In particular, several studies have shown that OV therapy is safe and well tolerated in humans and can infect a broad range of cancers. Yet in clinical studies OV therapy has highly variable response rates. The heterogeneous nature of tumors is widely accepted to be a major obstacle for OV therapeutics and highlights a need for strategies to improve viral replication efficacy. Here, we describe the development of a new class of small molecules for selectively enhancing OV replication in cancer tissue. Medicinal chemistry studies led to the identification of compounds that enhance multiple OVs and gene therapy vectors. Lead compounds increase OV growth up to 2000-fold in vitro and demonstrate remarkable selectivity for cancer cells over normal tissue ex vivo and in vivo. These small molecules also demonstrate enhanced stability with reduced electrophilicity and are highly tolerated in animals. This pharmacoviral approach expands the scope of OVs to include resistant tumors, further potentiating this transformative therapy. It is easily foreseeable that this approach can be applied to therapeutically enhance other attenuated viral vectors.

Human soluble insulin Humulin R U-500 has been in use worldwide for marked insulin resistance but is not specifically licensed in the UK. The Association of British Clinical Diabetologists conducted a nationwide audit of Humulin R U-500 to understand its use in the UK. The results show that 67 out of 119 clinicians who responded to the survey are using U-500R. The commonest indication for using it was a high daily insulin dose. These results are the first glimpse of the practical usage of high strength insulin in the UK and may help our approach to patients with high insulin resistance and the use of newly available higher concentration insulins.