Cardiolipin Membranes Promote Cytochrome c Transformation of Polycyclic Aromatic Hydrocarbons and Their In Vivo Metabolites.

The catalytic properties of cytochrome c (Cc) have captured great interest in respect to mitochondrial physiology and apoptosis, and hold potential for novel enzymatic bioremediation systems. Nevertheless, its contribution to the metabolism of environmental toxicants remains unstudied. Human exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with impactful diseases, and animal models have unveiled concerning signs of PAHs' toxicity to mitochondria. In this work, a series of eight PAHs with ionization potentials between 7.2 and 8.1 eV were used to challenge the catalytic ability of Cc and to evaluate the effect of vesicles containing cardiolipin mimicking mitochondrial membranes activating the peroxidase activity of Cc. With moderate levels of H2O2 and at pH 7.0, Cc catalyzed the oxidation of toxic PAHs, such as benzo[a]pyrene, anthracene, and benzo[a]anthracene, and the cardiolipin-containing membranes clearly increased the PAH conversions. Our results also demonstrate for the first time that Cc and Cc-cardiolipin complexes efficiently transformed the PAH metabolites 2-hydroxynaphthalene and 1-hydroxypyrene. In comparison to horseradish peroxidase, Cc was shown to reach more potent oxidizing states and react with PAHs with ionization potentials up to 7.70 eV, including pyrene and acenaphthene. Spectral assays indicated that anthracene binds to Cc, and docking simulations proposed possible binding sites positioning anthracene for oxidation. The results give support to the participation of Cc in the metabolism of PAHs, especially in mitochondria, and encourage further investigation of the molecular interaction between PAHs and Cc.

Altered expression of Sialyl Lewis X in experimental models of Parkinson's disease.

The mechanisms underlying neurodegeneration in Parkinson's disease (PD) are still not fully understood. Glycosylation is an important post-translational modification that affects protein function, cell-cell contacts and inflammation and can be modified in pathologic conditions. Although the involvement of aberrant glycosylation has been proposed for PD, the knowledge of the diversity of glycans and their role in PD is still minimal. Sialyl Lewis X (sLeX) is a sialylated and fucosylated tetrasaccharide with essential roles in cell-to-cell recognition processes. Pathological conditions and pro-inflammatory mediators can up-regulate sLeX expression on cell surfaces, which has important consequences in intracellular signalling and immune function. Here, we investigated the expression of this glycan using in vivo and in vitro models of PD. We show the activation of deleterious glycation-related pathways in mouse striatum upon treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), a toxin-based model of PD. Importantly, our results show that MPTP triggers the presentation of more proteins decorated with sLeX in mouse cortex and striatum in a time-dependent manner, as well as increased mRNA expression of its rate-limiting enzyme fucosyltransferase 7. sLeX is expressed in neurons, including dopaminergic neurons, and microglia. Although the underlying mechanism that drives increased sLeX epitopes, the nature of the protein scaffolds and their functional importance in PD remain unknown, our data suggest for the first time that sLeX in the brain may have a role in neuronal signalling and immunomodulation in pathological conditions. KEY MESSAGES: MPTP triggers the presentation of proteins decorated with sLeX in mouse brain. MPTP triggers the expression of sLeX rate-limiting enzyme FUT 7 in striatum. sLeX is expressed in neurons, including dopaminergic neurons, and microglia. sLeX in the brain may have a role in neuronal signalling and immunomodulation.

Generation of Monocyte-Derived Dendritic Cells with Differing Sialylated Phenotypes.

Sialic acids are negatively charged monosaccharides typically found at the termini of cell surface glycans. Due to their hydrophilicity and biophysical characteristics, they are involved in numerous biological processes, such as modulation of the immune response, recognition of self and non-self antigens, carbohydrate-protein interactions, etc. The cellular content of sialic acid is regulated by sialidase, which catalyzes the removal of sialic acid residues. Several studies have shown that sialo-glycans are critical in monitoring immune surveillance by engaging with cis and trans inhibitory Siglec receptors on immune cells. Likewise, glyco-immune checkpoints in cancer are becoming crucial targets for developing immunotherapies. Additionally, dendritic cells (DCs) are envisioned as an important component in immunotherapies, especially in cancer research, due to their unique role as professional antigen-presenting cells (APC) and their capacity to trigger adaptive immune responses and generate immunologic memory. Nevertheless, the function of DCs is dependent on their full maturation. Immature DCs have an opposing function to mature DCs and a high sialic acid content, which further dampens their maturation level. This downregulates the ability of immature DCs to activate T-cells, leading to a compromised immune response. Consequently, removing sialic acid from the cell surface of human DCs induces their maturation, thus increasing the expression of MHC molecules and antigen presentation. In addition, it can restore the expression of co-stimulatory molecules and IL-12, resulting in DCs having a higher ability to polarize T-cells toward a Th1 phenotype and specifically activate cytotoxic T-cells to kill tumor cells. Therefore, sialic acid has emerged as a key modulator of DCs and is being used as a novel target to advance their therapeutic use. This study provides a unique approach to treat in vitro monocyte-derived DCs with sialidase, aimed at generating DC populations with different cell surface sialic acid phenotypes and tailored maturation and co-stimulatory profiles.

Congenital disorders of glycosylation (CDG): state of the art in 2022.

Congenital disorders of glycosylation (CDG) are a complex and heterogeneous family of rare metabolic diseases. With a clinical history that dates back over 40 years, it was the recent multi-omics advances that mainly contributed to the fast-paced and encouraging developments in the field. However, much remains to be understood, with targeted therapies' discovery and approval being the most urgent unmet need. In this paper, we present the 2022 state of the art of CDG, including glycosylation pathways, phenotypes, genotypes, inheritance patterns, biomarkers, disease models, and treatments. In light of our current knowledge, it is not always clear whether a specific disease should be classified as a CDG. This can create ambiguity among professionals leading to confusion and misguidance, consequently affecting the patients and their families. This review aims to provide the CDG community with a comprehensive overview of the recent progress made in this field.

Computational Approaches Drive Developments in Immune-Oncology Therapies for PD-1/PD-L1 Immune Checkpoint Inhibitors.

Computational approaches in immune-oncology therapies focus on using data-driven methods to identify potential immune targets and develop novel drug candidates. In particular, the search for PD-1/PD-L1 immune checkpoint inhibitors (ICIs) has enlivened the field, leveraging the use of cheminformatics and bioinformatics tools to analyze large datasets of molecules, gene expression and protein-protein interactions. Up to now, there is still an unmet clinical need for improved ICIs and reliable predictive biomarkers. In this review, we highlight the computational methodologies applied to discovering and developing PD-1/PD-L1 ICIs for improved cancer immunotherapies with a greater focus in the last five years. The use of computer-aided drug design structure- and ligand-based virtual screening processes, molecular docking, homology modeling and molecular dynamics simulations methodologies essential for successful drug discovery campaigns focusing on antibodies, peptides or small-molecule ICIs are addressed. A list of recent databases and web tools used in the context of cancer and immunotherapy has been compilated and made available, namely regarding a general scope, cancer and immunology. In summary, computational approaches have become valuable tools for discovering and developing ICIs. Despite significant progress, there is still a need for improved ICIs and biomarkers, and recent databases and web tools have been compiled to aid in this pursuit.

Sialyl LewisX/A and Cytokeratin Crosstalk in Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) encompasses multiple entities and is generally highly aggressive and metastatic. We aimed to determine the clinical and biological relevance of Sialyl-Lewis X and A (sLeX/A)-a fucosylated glycan involved in metastasis-in TNBC. Here, we studied tissues from 50 TNBC patients, transcripts from a TNBC dataset from The Cancer Genome Atlas (TCGA) database, and a primary breast cancer cell line. All 50 TNBC tissue samples analysed expressed sLeX/A. Patients with high expression of sLeX/A had 3 years less disease-free survival than patients with lower expression. In tissue, sLeX/A negatively correlated with cytokeratins 5/6 (CK5/6, which was corroborated by the inverse correlation between fucosyltransferases and CK5/6 genes. Our observations were confirmed in vitro when inhibition of sLeX/A remarkably increased expression of CK5/6, followed by a decreased proliferation and invasion capacity. Among the reported glycoproteins bearing sLeX/A and based on the STRING tool, α6 integrin showed the highest interaction score with CK5/6. This is the first report on the sLeX/A expression in TNBC, highlighting its association with lower disease-free survival and its inverse crosstalk with CK5/6 with α6 integrin as a mediator. All in all, sLeX/A is critical for TNBC malignancy and a potential prognosis biomarker and therapeutic target.

A Community-Based Participatory Framework to Co-Develop Patient Education Materials (PEMs) for Rare Diseases: A Model Transferable across Diseases.

At least 50% of chronic disease patients don't follow their care plans, leading to lower health outcomes and higher medical costs. Providing Patient Education Materials (PEMs) to individuals living with a disease can help to overcome these problems. PEMs are especially beneficial for people suffering from multisystemic and underrecognized diseases, such as rare diseases. Congenital disorders of glycosylation (CDG) are ultra-rare diseases, where a need was identified for PEMs in plain language that can clearly explain complex information. Community involvement in the design of PEMs is extremely important for diseases whose needs are underserved, such as rare diseases; however, attempts to involve lay and professional stakeholders are lacking. This paper presents a community-based participatory framework to co-create PEMs for CDG, that is transferable to other diseases. A literature review and questionnaire were performed, and only four articles describing the development of PEMS for rare diseases have been found, which demonstrates a lack of standardized approaches. The framework and PEMs were co-developed with CDG families and will be crucial in increasing health literacy and empowering families. We will close a gap in the creation of PEMs for CDG by delivering these resources in lay language in several languages.

A Participatory Framework for Plain Language Clinical Management Guideline Development.

BACKGROUND: Clinical management guidelines (CMGs) are decision support tools for patient care used by professionals, patients, and family caregivers. Since clinical experts develop numerous CMGs, their technical language hinders comprehension and access by nonmedical stakeholders. Additionally, the views of affected individuals and their families are often not incorporated into treatment guidelines. We developed an adequate methodology for addressing the needs and preferences of family and professional stakeholders regarding CMGs, a recently developed protocol for managing congenital disorders of glycosylation (CDG), a family of rare metabolic diseases. We used the CDG community and phosphomannomutase 2 (PMM2)-CDG CMGs as a pilot to test and implement our methodology. RESULTS: We listened to 89 PMM2-CDG families and 35 professional stakeholders and quantified their CMG-related needs and preferences through an electronic questionnaire. Most families and professionals rated CMGs as relevant (86.5% and 94.3%, respectively), and valuable (84.3% and 94.3%, respectively) in CDG management. The most identified challenges were the lack of CMG awareness (50.6% of families) and the lack of plain language CMG (39.3% of professionals). Concordantly, among families, the most suggested solution was involving them in CMG development (55.1%), while professionals proposed adapting CMGs to include plain language (71.4%). Based on these results, a participatory framework built upon health literacy principles was created to improve CMG comprehension and accessibility. The outputs are six complementary CMG-related resources differentially adapted to the CDG community's needs and preferences, with a plain language PMM2-CDG CMG as the primary outcome. Additionally, the participants established a distribution plan to ensure wider access to all resources. CONCLUSIONS: This empowering, people-centric methodology accelerates CMG development and accessibility to all stakeholders, ultimately improving the quality of life of individuals living with a specific condition and raising the possibility of application to other clinical guidelines.

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG).

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

Stakeholders' views on drug development: the congenital disorders of glycosylation community perspective.

BACKGROUND: Congenital disorders of glycosylation (CDG) are a large family of rare genetic diseases for which therapies are virtually nonexistent. However, CDG therapeutic research has been expanding, thanks to the continuous efforts of the CDG medical/scientific and patient communities. Hence, CDG drug development is a popular research topic. The main aim of this study was to understand current and steer future CDG drug development and approval by collecting and analysing the views and experiences of the CDG community, encompassing professionals and families. An electronic (e-)survey was developed and distributed to achieve this goal. RESULTS: A total of 128 respondents (46 CDG professionals and 82 family members), mainly from Europe and the USA, participated in this study. Most professionals (95.0%) were relatively familiar with drug development and approval processes, while CDG families revealed low familiarity levels, with 8.5% admitting to never having heard about drug development. However, both stakeholder groups agreed that patients and families make significant contributions to drug development and approval. Regarding their perceptions of and experiences with specific drug development and approval tools, namely biobanks, disease models, patient registries, natural history studies (NHS) and clinical trials (CT), the CDG community stakeholders described low use and participation, as well as variable familiarity. Additionally, CDG professionals and families shared conflicting views about CT patient engagement and related information sharing. Families reported lower levels of involvement in CT design (25.0% declared ever being involved) and information (60.0% stated having been informed) compared to professionals (60.0% and 85.7%, respectively). These contrasting perceptions were further extended to their insights and experiences with patient-centric research. Finally, the CDG community (67.4% of professionals and 54.0% of families) reported a positive vision of artificial intelligence (AI) as a drug development tool. Nevertheless, despite the high AI awareness among CDG families (76.8%), professionals described limited AI use in their research (23.9%). CONCLUSIONS: This community-centric study sheds new light on CDG drug development and approval. It identifies educational, communication and research gaps and opportunities for CDG professionals and families that could improve and accelerate CDG therapy development.

A Community-Led Approach as a Guide to Overcome Challenges for Therapy Research in Congenital Disorders of Glycosylation.

Congenital Disorders of Glycosylation (CDG) are a large family of rare genetic diseases for which effective therapies are almost nonexistent. To better understand the reasons behind this, to analyze ongoing therapy research and development (R&D) for CDG, and to provide future guidance, a community-led mixed methods approach was organized during the 4th World Conference on CDG for Families and Professionals. In the quantitative phase, electronic surveys pointed to the prioritization of six therapeutic R&D tools, namely biobanks, registries, biomarkers, disease models, natural history studies, and clinical trials. Subsequently, in the qualitative phase, the challenges and solutions associated with these research tools were explored through community-driven think tanks. The multiple challenges and solutions identified administrative/regulatory, communication, financial, technical, and biological issues, which are directly related to three fundamental aspects of therapy R&D, namely data, sample, and patient management. An interdependence was traced between the prioritized tools, with diagnosis and therapies acting as bidirectional triggers that fuel these interrelationships. In conclusion, this study's pioneering and adaptable community-led methodology identified several CDG therapy R&D gaps, many common to other rare diseases, without easy solutions. However, the strong proactive attitude towards research, based on inclusive and international partnerships and involving all members of the CDG community, sets the direction for better future therapy R&D.

The road to successful people-centric research in rare diseases: the web-based case study of the Immunology and Congenital Disorders of Glycosylation questionnaire (ImmunoCDGQ).

BACKGROUND: Congenital Disorders of Glycosylation (CDG) are a complex family of rare metabolic diseases. Robust clinical data collection faces many hurdles, preventing full CDG biological and clinical comprehension. Web-based platforms offer privileged opportunities for biomedical data gathering, and participant recruitment, particularly in rare diseases. The immunology and CDG electronic (e-) questionnaire (ImmunoCDGQ) explores this paradigm, proposing a people-centric framework to advance health research and participant empowerment. OBJECTIVE: The objectives of this study were to: (1) Describe and characterize the ImmunoCDGQ development, engagement, recruitment, participation, and result dissemination strategies; (2) To critically compare this framework with published literature and making recommendations. METHODS: An international, multistakeholder people-centric approach was initiated to develop and distribute the ImmunoCDGQ, a multi-lingual e-questionnaire able to collect immune-related data directly from patients and family caregivers. An adapted version was produced and distributed among the general "healthy" population (ImmunoHealthyQ), serving as the control group. Literature screening was performed to identify and analyze comparable studies. RESULTS: The ImmunoCDGQ attained high participation and inclusion rates (94.6%, 209 out of 221). Comparatively to the control, CDG participants also showed higher and more variable questionnaire completion times as well as increased English version representativeness. Additionally, 20% of the CDG group (42 out of 209) chose not to complete the entire questionnaire in one go. Conditional logic structuring guided participant data provision and accurate data analysis assignment. Multi-channel recruitment created sustained engagement with Facebook emerging as the most followed social media outlet. Still, most included ImmunoCDGQ questionnaires (50.7%, 106 out of 209) were submitted within the first month of the project's launch. Literature search and analysis showed that most e-questionnaire-based studies in rare diseases are author-built (56.8%, 25 out of 44), simultaneously addressing medical and health-related quality of life (HRQoL) and/or information needs (79.5%, 35 out of 44). Also, over 68% of the studies adopt multi-platform recruitment (30 out of 44) actively supported by patient organizations (52.3%, 23 out of 44). CONCLUSIONS: The ImmunoCDGQ, its methodology and the CDG Community served as models for health research, hence paving a successful and reproducible road to people-centricity in biomedical research.

A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully translated into clinical cancer treatment. Here we developed a Quantitative Structure-Activity Relationships (QSAR) classification models using empirical molecular descriptors and fingerprints to predict the activity against the p53 protein, using the potency value with the active or inactive label, were developed. These models were built using in total 10,505 molecules that were extracted from the ChEMBL, ZINC and Reaxys® databases, and recent literature. Three machine learning (ML) techniques e.g., Random Forest, Support Vector Machine, Convolutional Neural Network were explored to build models for p53 inhibitor prediction. The performances of the models were successfully evaluated by internal and external validation. Moreover, based on the best in silico p53 model, a virtual screening campaign was carried out using 1443 FDA-approved drugs that were extracted from the ZINC database. A list of virtual screening hits was assented on base of some limits established in this approach, such as: (1) probability of being active against p53; (2) applicability domain; (3) prediction of the affinity between the p53, and ligands, through molecular docking. The most promising according to the limits established above was dihydroergocristine. This compound revealed cytotoxic activity against a p53-expressing CRC cell line with an IC50 of 56.8 µM. This study demonstrated that the computer-aided drug design approach can be used to identify previously unknown molecules for targeting p53 protein with anti-cancer activity and thus pave the way for the study of a therapeutic solution for CRC.

Development of Dl1.72, a Novel Anti-DLL1 Antibody with Anti-Tumor Efficacy against Estrogen Receptor-Positive Breast Cancer.

The Notch-signaling ligand DLL1 has emerged as an important player and promising therapeutic target in breast cancer (BC). DLL1-induced Notch activation promotes tumor cell proliferation, survival, migration, angiogenesis and BC stem cell maintenance. In BC, DLL1 overexpression is associated with poor prognosis, particularly in estrogen receptor-positive (ER+) subtypes. Directed therapy in early and advanced BC has dramatically changed the natural course of ER+ BC; however, relapse is a major clinical issue, and new therapeutic strategies are needed. Here, we report the development and characterization of a novel monoclonal antibody specific to DLL1. Using phage display technology, we selected an anti-DLL1 antibody fragment, which was converted into a full human IgG1 (Dl1.72). The Dl1.72 antibody exhibited DLL1 specificity and affinity in the low nanomolar range and significantly impaired DLL1-Notch signaling and expression of Notch target genes in ER+ BC cells. Functionally, in vitro treatment with Dl1.72 reduced MCF-7 cell proliferation, migration, mammosphere formation and endothelial tube formation. In vivo, Dl1.72 significantly inhibited tumor growth, reducing both tumor cell proliferation and liver metastases in a xenograft mouse model, without apparent toxicity. These findings suggest that anti-DLL1 Dl1.72 could be an attractive agent against ER+ BC, warranting further preclinical investigation.

Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases.

More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this "big data" age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.

L1CAM as an E-selectin Ligand in Colon Cancer.

Metastasis is the main cause of death among colorectal cancer (CRC) patients. E-selectin and its carbohydrate ligands, including sialyl Lewis X (sLeX) antigen, are key players in the binding of circulating tumor cells to the endothelium, which is one of the major events leading to organ invasion. Nevertheless, the identity of the glycoprotein scaffolds presenting these glycans in CRC remains unclear. In this study, we firstly have characterized the glycoengineered cell line SW620 transfected with the fucosyltransferase 6 (FUT6) coding for the α1,3-fucosyltransferase 6 (FUT6), which is the main enzyme responsible for the synthesis of sLeX in CRC. The SW620FUT6 cell line expressed high levels of sLeX antigen and E-selectin ligands. Moreover, it displayed increased migration ability. E-selectin ligand glycoproteins were isolated from the SW620FUT6 cell line, identified by mass spectrometry, and validated by flow cytometry and Western blot (WB). The most prominent E-selectin ligand we identified was the neural cell adhesion molecule L1 (L1CAM). Previous studies have shown association of L1CAM with metastasis in cancer, thus the novel role as E-selectin counter-receptor contributes to understand the molecular mechanism involving L1CAM in metastasis formation.

New Insights into Immunological Involvement in Congenital Disorders of Glycosylation (CDG) from a People-Centric Approach.

Congenital disorders of glycosylation (CDG) are rare diseases with variable phenotypes and severity. Immunological involvement remains a largely uncharted topic in CDG, mainly due to lack of robust data. To better characterize immune-related manifestations' prevalence, relevance, and quality-of-life (QoL) impact, we developed electronic questionnaires targeting (1) CDG patients and (2) the general "healthy" population. Two-hundred and nine CDG patients/caregivers and 349 healthy participants were included in this study. PMM2-CDG was the most represented CDG (n = 122/209). About half of these participants (n = 65/122) described relevant infections with a noteworthy prevalence of those affecting the gastrointestinal tract (GI) (63.1%, n = 41/65). Infection burden and QoL impact were shown as infections correlated with more severe clinical phenotypes and with a set of relevant non-immune PMM2-CDG signs. Autoimmune diseases had only a marginal presence in PMM2-CDG (2.5%, n = 3/122), all being GI-related. Allergy prevalence was also low in PMM2-CDG (33%, n = 41/122) except for food allergies (26.8%, n = 11/41, of PMM2-CDG and 10.8%, n = 17/158, of controls). High vaccination compliance with greater perceived ineffectiveness (28.3%, n = 17/60) and more severe adverse reactions were described in PMM2-CDG. This people-centric approach not only confirmed literature findings, but created new insights into immunological involvement in CDG, namely by highlighting the possible link between the immune and GI systems in PMM2-CDG. Finally, our results emphasized the importance of patient/caregiver knowledge and raised several red flags about immunological management.

Extended half-life target module for sustainable UniCAR T-cell treatment of STn-expressing cancers.

BACKGROUND: Adapter chimeric antigen receptor (CAR) approaches have emerged has promising strategies to increase clinical safety of CAR T-cell therapy. In the UniCAR system, the safety switch is controlled via a target module (TM) which is characterized by a small-size and short half-life. The rapid clearance of these TMs from the blood allows a quick steering and self-limiting safety switch of UniCAR T-cells by TM dosing. This is mainly important during onset of therapy when tumor burden and the risk for severe side effects are high. For long-term UniCAR therapy, the continuous infusion of TMs may not be an optimal setting for the patients. Thus, in later stages of treatment, single infusions of TMs with an increased half-life might play an important role in long-term surveillance and eradication of residual tumor cells. Given this, we aimed to develop and characterize a novel TM with extended half-life targeting the tumor-associated carbohydrate sialyl-Tn (STn). METHODS: The extended half-life TM is composed of the STn-specific single-chain variable fragment (scFv) and the UniCAR epitope, fused to the hinge region and Fc domain of a human immunoglobulin 4 (IgG4) antibody. Specific binding and functionality of the αSTn-IgG4 TM as well as pharmacokinetic features were assessed using in vitro and in vivo assays and compared to the already established small-sized αSTn TM. RESULTS: The novel αSTn-IgG4 TM efficiently activates and redirects UniCAR T-cells to STn-expressing tumors in a target-specific and TM-dependent manner, thereby promoting the secretion of proinflammatory cytokines and tumor cell lysis in vitro and in experimental mice. Moreover, PET-imaging results demonstrate the specific enrichment of the αSTn-IgG4 TM at the tumor site, while presenting a prolonged serum half-life compared to the short-lived αSTn TM. CONCLUSION: In a clinical setting, the combination of TMs with different formats and pharmacokinetics may represent a promising strategy for retargeting of UniCAR T-cells in a flexible, individualized and safe manner at particular stages of therapy. Furthermore, as these molecules can be used for in vivo imaging, they pose as attractive candidates for theranostic approaches.

Functional and Physiological Methods of Evaluating Median Nerve Regeneration in the Rat.

The main goal of this investigation is to show how to create and repair different types of median nerve (MN) lesions in the rat. Moreover, different methods of simulating postoperative physiotherapy are presented. Multiple standardized strategies are used to assess motor and sensory recovery using an MN model of peripheral nerve lesion and repair, thus permitting easy comparison of the results. Several options are included for providing a postoperative physiotherapy-like environment to rats that have undergone MN injuries. Finally, the paper provides a method to evaluate the recovery of the MN using several noninvasive tests (i.e., grasping test, pin prick test, ladder rung walking test, rope climbing test, and walking track analysis), and physiological measurements (infrared thermography, electroneuromyography, flexion strength evaluation, and flexor carpi radialis muscle weight determination). Hence, this model seems particularly appropriate to replicate a clinical scenario, facilitating extrapolation of results to the human species. Although the sciatic nerve is the most studied nerve in peripheral nerve research, analysis of the rat MN presents various advantages. For example, there is a reduced incidence of joint contractures and automutilation of the affected limb in MN lesion studies. Furthermore, the MN is not covered by muscle masses, making its dissection easier than that of the sciatic nerve. In addition, MN recovery is observed sooner, because the MN is shorter than the sciatic nerve. Also, the MN has a parallel path to the ulnar nerve in the arm. Hence, the ulnar nerve can be easily used as the nerve graft for repairing MN injuries. Finally, the MN in rats is located in the forelimb, akin to the human upper limb; in humans, the upper limb is the site of most peripheral nerve lesions.