Unlocking protein-based biomarker potential for graft-versus-host disease following allogenic hematopoietic stem cell transplants.

Despite the numerous advantages of allogeneic hematopoietic stem cell transplants (allo-HSCT), there exists a notable association with risks, particularly during the preconditioning period and predominantly post-intervention, exemplified by the occurrence of graft-versus-host disease (GVHD). Risk stratification prior to symptom manifestation, along with precise diagnosis and prognosis, relies heavily on clinical features. A critical imperative is the development of tools capable of early identification and effective management of patients undergoing allo-HSCT. A promising avenue in this pursuit is the utilization of proteomics-based biomarkers obtained from non-invasive biospecimens. This review comprehensively outlines the application of proteomics and proteomics-based biomarkers in GVHD patients. It delves into both single protein markers and protein panels, offering insights into their relevance in acute and chronic GVHD. Furthermore, the review provides a detailed examination of the site-specific involvement of GVHD. In summary, this article explores the potential of proteomics as a tool for timely and accurate intervention in the context of GVHD following allo-HSCT.

Corrigendum: Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

[This corrects the article DOI: 10.3389/fimmu.2023.1265044.].

ExpoSeq: simplified analysis of high-throughput sequencing data from antibody discovery campaigns.

Summary: High-throughput sequencing (HTS) offers a modern, fast, and explorative solution to unveil the full potential of display techniques, like antibody phage display, in molecular biology. However, a significant challenge lies in the processing and analysis of such data. Furthermore, there is a notable absence of open-access user-friendly software tools that can be utilized by scientists lacking programming expertise. Here, we present ExpoSeq as an easy-to-use tool to explore, process, and visualize HTS data from antibody discovery campaigns like an expert while only requiring a beginner's knowledge. Availability and implementation: The pipeline is distributed via GitHub and PyPI, and it can either be installed as a package with pip or the user can choose to clone the repository.

Systematic evaluation of B-cell clonal family inference approaches.

The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.

The dengue-specific immune response and antibody identification with machine learning.

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

Predicting the immune escape of SARS-CoV-2 neutralizing antibodies upon mutation.

COVID-19 has resulted in millions of deaths and severe impact on economies worldwide. Moreover, the emergence of SARS-CoV-2 variants presented significant challenges in controlling the pandemic, particularly their potential to avoid the immune system and evade vaccine immunity. This has led to a growing need for research to predict how mutations in SARS-CoV-2 reduces the ability of antibodies to neutralize the virus. In this study, we assembled a set of 1813 mutations from the interface of SARS-CoV-2 spike protein's receptor binding domain (RBD) and neutralizing antibody complexes and developed a machine learning model to classify high or low escape mutations using interaction energy, inter-residue contacts and predicted binding free energy change. Our approach achieved an Area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.91 using the Random Forest classifier on the test dataset with 217 mutations. The model was further utilized to predict the escape mutations on a dataset of 29,165 mutations located at the interface of 83 RBD-neutralizing antibody complexes. A small subset of this dataset was also validated based on available experimental data. We found that top 10 % high escape mutations were dominated by charged to nonpolar mutations whereas low escape mutations were dominated by polar to nonpolar mutations. We believe that the present method will allow prioritization of high/low escape mutations in the context of neutralizing antibodies targeting SARS-CoV-2 RBD region and assist antibody design for current and emerging variants.

NKG2A discriminates natural killer cells with a suppressed phenotype in pediatric acute leukemia.

Natural killer (NK) cells are important for early tumor immune surveillance. In patients with hematological cancers, NK cells are generally functional deficient and display dysregulations in their receptor repertoires. Acute leukemia is the most common cancer in children, and we here performed a comparative phenotypic profiling of NK cells from B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients to identify aberrant NK cell phenotypes. NK cell phenotypes, maturation, and function were analyzed in matched bone marrow and blood NK cells from BCP-ALL patients at diagnosis, during treatment, and at end of treatment and compared with age-matched pediatric control subjects. Expression of several markers were skewed in patients, but with large interindividual variations. Undertaking a multiparameter approach, we found that high expression levels of NKG2A was the single predominant marker distinguishing NK cells in BCP-ALL patients compared with healthy control subjects. Moreover, naïve CD57-NKG2A NK cells dominated in BCP-ALL patients at diagnosis. Further, we found dysregulated expression of the activating receptor DNAM-1 in resident bone marrow CXCR6+ NK cells. CXCR6+ NK cells lacking DNAM-1 expressed NKG2A and had a tendency for lower degranulation activity. In conclusion, high expression of NKG2A dominates NK cell phenotypes from pediatric BCP-ALL patients, indicating that NKG2A could be targeted in therapies for this patient group.

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune Profiler (NIP) to scrutinize and predict regions of T cell immunogenicity (hotspots) from the entire SARS-CoV-2 viral proteome. These immunogenic regions offer potential for the development of universally protective T cell vaccine candidates. Here, we validated and characterized T cell responses to a set of minimal epitopes from these AI-identified universal hotspots. Utilizing a flow cytometry-based T cell activation-induced marker (AIM) assay, we identified 59 validated screening hits, of which 56% (33 peptides) have not been previously reported. Notably, we found that most of these novel epitopes were derived from the non-spike regions of SARS-CoV-2 (Orf1ab, Orf3a, and E). In addition, ex vivo stimulation with NIP-predicted peptides from the spike protein elicited CD8+ T cell response in PBMC isolated from most vaccinated donors. Our data confirm the predictive accuracy of AI platforms modelling bona fide immunogenicity and provide a novel framework for the evaluation of vaccine-induced T cell responses.

Application and challenges of TCR and BCR sequencing to investigate T- and B-cell clonality in elastase-induced experimental murine abdominal aortic aneurysm.

Background: An abdominal aortic aneurysm (AAA) is a life-threatening cardiovascular disease. Although its pathogenesis is still poorly understood, recent evidence suggests that AAA displays autoimmune disease characteristics. Particularly, T cells responding to AAA-related antigens in the aortic wall may contribute to an initial immune response. Single-cell RNA (scRNA) T cell receptor (TCR) and B cell receptor (BCR) sequencing is a powerful tool for investigating clonality. However, difficulties such as limited numbers of isolated cells must be considered during implementation and data analysis, making biological interpretation challenging. Here, we perform a representative single-cell immune repertoire analysis in experimental murine AAA and show a reliable bioinformatic processing pipeline highlighting opportunities and limitations of this approach. Methods: We performed scRNA TCR and BCR sequencing of isolated lymphocytes from the infrarenal aorta of male C57BL/6J mice 3, 7, 14, and 28 days after AAA induction via elastase perfusion of the aorta. Sham-operated mice at days 3 and 28 and non-operated mice served as controls. Results: Comparison of complementarity-determining region (CDR3) length distribution of 179 B cells and 796 T cells revealed neither differences between AAA and control nor between the disease stages. We found no clonal expansion of B cells in AAA. For T cells, we identified several clones in 11 of 16 AAA samples and one of eight control samples. Immune receptor repertoire comparison indicated that only a few clones were shared between the individual AAA samples. The most frequently used V-genes in the TCR beta chain in AAA were TRBV3, TRBV19, and the splicing variant TRBV12-2 + TRBV13-2. Conclusion: We found no clonal expansion of B cells but evidence for clonal expansion of T cells in elastase-induced AAA in mice. Our findings imply that a more precise characterization of TCR and BCR distribution requires a more extensive number of lymphocytes to prevent undersampling and potentially detect rare clones. Thus, further experiments are necessary to confirm our findings. In summary, this paper examines TCR and BCR sequencing results, identifies limitations and pitfalls, and offers guidance for future studies.

Insights into next generation sequencing guided antibody selection strategies.

Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random colony picking and Sanger sequencing, which has limitations. Next-generation sequencing (NGS) offers a cost-effective solution with increased read depth, allowing a comprehensive understanding of diversity. Our study establishes NGS guidelines for antibody drug discovery, demonstrating its advantages in expanding the number of unique HCDR3 clusters, broadening the number of high affinity antibodies, expanding the total number of antibodies recognizing different epitopes, and improving lead prioritization. Surprisingly, our investigation into the correlation between NGS-derived frequencies of CDRs and affinity revealed a lack of association, although this limitation could be moderately mitigated by leveraging NGS clustering, enrichment and/or relative abundance across different regions to enhance lead prioritization. This study highlights NGS benefits, offering insights, recommendations, and the most effective approach to leverage NGS in therapeutic antibody discovery.

Human thymic putative CD8αα precursors exhibit a biased TCR repertoire in single cell AIRR-seq.

Thymic T cell development comprises T cell receptor (TCR) recombination and assessment of TCR avidity towards self-peptide-MHC complexes presented by antigen-presenting cells. Self-reactivity may lead to negative selection, or to agonist selection and differentiation into unconventional lineages such as regulatory T cells and CD8[Formula: see text] T cells. To explore the effect of the adaptive immune receptor repertoire on thymocyte developmental decisions, we performed single cell adaptive immune receptor repertoire sequencing (scAIRR-seq) of thymocytes from human young paediatric thymi and blood. Thymic PDCD1+ cells, a putative CD8[Formula: see text] T cell precursor population, exhibited several TCR features previously associated with thymic and peripheral ZNF683+ CD8[Formula: see text] T cells, including enrichment of large and positively charged complementarity-determining region 3 (CDR3) amino acids. Thus, the TCR repertoire may partially explain the decision between conventional vs. agonist selected thymocyte differentiation, an aspect of importance for the development of therapies for patients with immune-mediated diseases.

Design and preclinical testing of an anti-CD41 CAR T cell for the treatment of acute megakaryoblastic leukaemia.

Acute megakaryoblastic leukaemia (AMkL) is a rare subtype of acute myeloid leukaemia (AML) representing 5% of all reported cases, and frequently diagnosed in children with Down syndrome. Patients diagnosed with AMkL have low overall survival and have poor outcome to treatment, thus novel therapies such as CAR T cell therapy could represent an alternative in treating AMkL. We investigated the effect of a new CAR T cell which targets CD41, a specific surface antigen for M7-AMkL, against an in vitro model for AMkL, DAMI Luc2 cell line. The performed flow cytometry evaluation highlighted a percentage of 93.8% CAR T cells eGFP-positive and a limited acute effect on lowering the target cell population. However, the interaction between effector and target (E:T) cells, at a low ratio, lowered the cell membrane integrity, and reduced the M7-AMkL cell population after 24 h of co-culture, while the cytotoxic effect was not significant in groups with higher E:T ratio. Our findings suggest that the anti-CD41 CAR T cells are efficient for a limited time spawn and the cytotoxic effect is visible in all experimental groups with low E:T ratio.

Defining and Studying B Cell Receptor and TCR Interactions.

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Pathology and Molecular Biology of Melanoma.

Almost every death in young patients with an advanced skin tumor is caused by melanoma. Today, with the help of modern treatments, these patients survive longer or can even achieve a cure. Advanced stage melanoma is frequently related with poor prognosis and physicians still find this disease difficult to manage due to the absence of a lasting response to initial treatment regimens and the lack of randomized clinical trials in post immunotherapy/targeted molecular therapy settings. New therapeutic targets are emerging from preclinical data on the genetic profile of melanocytes and from the identification of molecular factors involved in the pathogenesis of malignant transformation. In the current paper, we present the diagnostic challenges, molecular biology and genetics of malignant melanoma, as well as the current therapeutic options for patients with this diagnosis.

RNA sequencing suggests that non-coding RNAs play a role in the development of acquired haemophilia.

Acquired haemophilia (AH) is a rare disorder characterized by bleeding in patients with no personal or family history of coagulation/clotting-related diseases. This disease occurs when the immune system, by mistake, generates autoantibodies that target FVIII, causing bleeding. Small RNAs from plasma collected from AH patients (n = 2), mild classical haemophilia (n = 3), severe classical haemophilia (n = 3) and healthy donors (n = 2), for sequencing by Illumina, NextSeq500. Based on bioinformatic analysis, AH patients were compared to all experimental groups and a significant number of altered transcripts were identified with one transcript being modified compared to all groups at fold change level. The Venn diagram shows that haemoglobin subunit alpha 1 was highlighted to be the common upregulated transcript in AH compared to classical haemophilia and healthy patients. Non-coding RNAs might play a role in AH pathogenesis; however, due to the rarity of HA, the current study needs to be translated on a larger number of AH samples and classical haemophilia samples to generate more solid data that can confirm our findings.

Flow Cytometry of CD5-Positive Hairy Cell Leukemia.

BACKGROUND AND OBJECTIVE: Hairy cell leukemia (HCL) is a chronic lymphoproliferative disorder for which diagnosis is typically straightforward, based on bone marrow morphology and flow cytometry (FC) or immunohistochemistry. Nevertheless, variants present atypical expressions of cell surface markers, as is the case of CD5, for which the differential diagnosis can be more difficult. The aim of the current paper was to describe diagnosis of HCL with atypical CD5 expression, with an emphasis on FC. METHODS: The detailed diagnostic methodology for HCL with atypical CD5 expression is presented, including differential diagnosis from other lymphoproliferative diseases with similar pathologic features, by FC analysis of the bone marrow aspirate. RESULTS: Diagnosis of HCL by means of FC started by gating all events based on side scatter (SSC) versus CD45 and B lymphocytes were selected from the lymphocytes gate as CD45/CD19 positive. The gated cells were positive for CD25, CD11c, CD20, and CD103, while CD10 proved to be dim to negative. Moreover, cells positive for CD3, CD4, and CD8, the three pan-T markers, as well as CD19, showed a bright expression of CD5. The atypical CD5 expression is usually correlated with a negative prognosis and thus chemotherapy with cladribine should be initiated. CONCLUSION: HCL is an indolent chronic lymphoproliferative disorder and diagnosis is usually straightforward. However, atypical expression of CD5 renders its differential diagnosis more difficult, but FC is a useful tool that allows an optimal classification of the disease and allows initiation of timely satisfactory therapy.

Pitfalls in patenting academic CAR-T cells therapy.

INTRODUCTION: Emerging immunotherapies are pushing the boundaries of cancer treatment, with chimeric antigen receptor (CAR)-T cell therapy being one of the most advanced. Due to the increasingly crowded CAR-T cell field, patenting and protecting the intellectual property of these CAR-T cells implies a good knowledge of the legal landscape. AREAS COVERED: The present manuscript focuses on the challenges regarding the patenting process of CAR-T technology, beginning with a description of the main characteristics of CAR-T cells and their functionalities, continuing with the legal landscape applicable to patenting processes, and concluding by presenting the potential strategies to overcome the impediments that can appear when trying to patent CAR-T cells. It is meant to offer insights for those who are exploring possible patenting options in CAR-T cells territory. PubMed and Patenscope databases were used for patent and literature searching (2013-2023). EXPERT OPINION: There is no one-size-fits-all solution in this matter and the medical evolution of this therapy will certainly bring out even more challenges. Comprehensive knowledge of the intellectual property, exposure to potential litigation, growing competition, and the high price of therapy, are strikingly relevant in the broader landscape. Future endeavors would be to take steps toward the harmonization of the CAR-T patenting procedure.