Therapeutic Solutions International Submits Publication on StemVacs™ Preclinical Data Supporting COVID-19 Indication

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STEMVACS2 -Alterations in peripheral blood monocyte and dendritic cell subset homeostasis in relapsing-remitting MS pati

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Alterations in peripheral blood monocyte and dendritic cell subset homeostasis in relapsing-remitting multiple sclerosis patients ... qOFPHycYEa

In patients with relapsing-remitting MS, researchers analyzed the frequency of plasmacytoid (pDC) and myeloid (mDC) dendritic cells and the classical, intermediate and non-classical monocytes subsets, as well as their phenotypic and functional profile. They assessed peripheral blood from relapsing-remitting patients treated with IFN-β in remission and relapse phases as well as from healthy people. The authors observed that the mDC/pDC ratio was reduced in remission and a return to normal values in relapse. The frequency of non-classical monocytes decreased in both phases. An increased HLA-DR expression in remission and a decreased one in relapse were observed with respect to the phenotypic characterization, revealing alterations in monocytes and dendritic cells homeostasis.
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STEMVACS2 - Dermal IRF4+ dendritic cells and monocytes license CD4+ T helper cells to distinct cytokine profiles

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Dermal IRF4+ dendritic cells and monocytes license CD4+ T helper cells to distinct cytokine profiles

Antigen (Ag)-presenting cells (APC) instruct CD4+ helper T (Th) cell responses, but it is unclear whether different APC subsets contribute uniquely in determining Th differentiation in pathogen-specific settings. Here, we use skin-relevant, fluorescently-labeled bacterial, helminth or fungal pathogens to track and characterize the APC populations that drive Th responses in vivo. All pathogens are taken up by a population of IRF4+ dermal migratory dendritic cells (migDC2) that similarly upregulate surface co-stimulatory molecules but express pathogen-specific cytokine and chemokine transcripts. Depletion of migDC2 reduces the amount of Ag in lymph node and the development of IFNγ, IL-4 and IL-17A responses without gain of other cytokine responses. Ag+ monocytes are an essential source of IL-12 for both innate and adaptive IFNγ production, and inhibit follicular Th cell development. Our results thus suggest that Th cell differentiation does not require specialized APC subsets, but is driven by inducible and pathogen-specific transcriptional programs in Ag+ migDC2 and monocytes.

The differentiation of CD4+ T cells into distinct functional populations is a key event in adaptive immunity: IFNγ+ T helper (Th)1 cells clear intracellular pathogens and some bacterial infections, while IL-4+ Th2 and IL-17+ Th17 cells respond to helminth and fungal infections, respectively1. The context of antigen recognition is a major factor in determining CD4+ T cell differentiation2,3. Through the expression of pattern recognition and cytokine receptors, antigen-presenting cells (APCs) perceive pathogens while sensing the response of bystander cells to the same stimuli4, thereby conveying the sum of these signals to initiate the appropriate CD4+ T cell differentiation program.

Dendritic cells (DC) are considered the primary APC population capable of priming CD4+ T cell responses in vivo5. They comprise two main populations: IRF8+ DC1 and IRF4+ DC2, which can be either lymphoid tissue-resident or migratory6,7. In addition, epidermal Langerhans cells (LC) and blood-borne classical Ly6Chi monocytes may also participate in driving CD4+ T cell responses. The presence of such a diverse repertoire of APC has led to the proposal that APC populations may specialize in promoting certain CD4+ T cell differentiation programs, a notion that is supported by the differential expression of key cytokines and co-stimulatory molecules by different DC subsets (reviewed in ref. 8). Mouse models lacking specific populations of APC also suggest a similar conclusion, with DC1 driving IFNγ+ CD4+ T cell responses and KLF4-dependent DC2, NOTCH2-dependent DC2 and LC implicated in promoting the differentiation of IL-4+ or IL-17+, but not IFNγ+ CD4+ T cells8,9,10,11. Depending on the model and environment, monocytes favor the differentiation of IFNγ+ CD4+ T cells, but can also support allergic inflammation or anti-fungal Th17 responses (reviewed in ref. 12).

Besides individual APC populations having a role in driving specific types of CD4+ T cell responses, there is also evidence that APC exposed to appropriate stimuli can display a degree of functional plasticity to induce different types of responses13,14,15,16. This evidence stems mainly from in vitro culture experiments, although some in vivo evidence also exists17. Stimuli are thought to act mostly via induction of specific polarizing cytokines1, but also by tuning the strength of TCR-signaling via modulation of TCR ligands and costimulatory molecule expression on APC18.

While there is good experimental evidence supporting both DC specialization and plasticity, few studies have addressed this question in a systematic fashion. To date, most studies have employed either in vitro culture models, or in vivo models focused on individual pathogens in specific tissues, with overarching conclusions drawn from the collation of several in vivo studies performed using different readouts, tissues, and models. When different models of Th response were compared in vivo, they were often based on protein antigen combined with adjuvants such as polyI:C, CpG or alum, which are unlikely to recapitulate the localization, distribution, and innate activating properties of complex particulate pathogens such as bacteria, fungi, or multicellular parasites.

In this study, we formally test the notion of APC plasticity by comparing the role of APC subsets in mice immunized via the same intradermal route with different skin-relevant pathogens. By using mutant mouse strains that are defective in either migDC2 or monocytes, we report that the same population of dermal migDC2 can take up different pathogens and support the optimal differentiation of CD4+ T cells producing IFNγ, IL-4, or IL-17A, whilst monocytes are essential for early innate IFNγ production and full Th1 differentiation after bacterial immunization. Therefore, pathogen signals activate dermal migDC2 to express specific transcriptional programs that support the differentiation of Th cells into diverse functional phenotypes.

Ag+ DC2 in the lymph node of mice immunized with different pathogens express similar surface markers
To investigate the APC requirements for Th1, Th2, and Th17 development, we used the skin-relevant pathogenic or opportunistic microorganisms Mycobacterium smegmatis (Ms), Nippostrongylus brasiliensis (Nb) and Candida albicans (Ca), which induce CD4 + T cell responses that are characterized by production of IFNγ, IL-4, and IL-17A, and expression of the transcription factors Tbet, GATA-3 and RORγt, respectively (Supplementary Fig. 1a, b)19,20. Although IL-17A expression was observed only after Ca immunization, other cytokines especially IFNγ are also expressed in this model19.

Intradermal (i.d.) injection of inactivated, fluorescently-labeled Ms, Nb, or Ca enabled the identification of Ag+ cells in the ear-draining lymph node (dLN) of recipient mice on day 1-3 (Supplementary Fig. 1c). On day 2, these cells were predominantly migDC2 (MHCIIhi Ly6C- XCR1− CD326−) and classical monocytes (Ly6Chi CD11b+) with rare resDC (Fig. 1a–c, Supplementary Fig. 1c, d), an identity which is confirmed by single-cell RNAseq data19. A UMAP analysis of flow cytometry data examining the migDC markers CD11b, CD11c, CD103, CD206, CD301b, CD326, PDL2, MHCII, and Ag-AF488, showed that Ag+ migDC from all conditions fell into two major clusters: CD11bhi migDC2 and CD11blow migDC2 (which we previously termed triple-negative, or “TN”21) (Fig. 1c) that were equally represented across all conditions (Fig. 1d). Within the Ag+ CD11bhi and CD11blow clusters, all cells were PDL2+ and a proportion co-expressed the migDC2 markers CD301b and CD206 (Fig. 1c, e, Supplementary Fig. 1d).

Cell sorting
DC were enriched from single-cell suspensions by negative selection using a Dynabead® Mouse DC Enrichment kit (Invitrogen™, ThermoFisher Scientific) as per the manufacturer’s instructions. Enriched DC were stained with fluorescently labeled antibodies including: anti-CD11b (M1/70; BD Pharmingen), anti-CD11c (HL3; BD Horizon), anti-IA/IE (MHCII; M5/114; BD Horizon), anti-XCR1 (ZET; BioLegend), anti-CD326 (G8.8; BioLegend), anti-Ly6C (HK1.4; BioLegend), anti-Ly6G (1A8; BD Horizon), anti-CD45R (B220; RA3-6B2; BD Horizon) and anti-CD3 (145-2C11), then sorted into total monocytes, Ag− XCR1+ DC1, Ag− CD11bhi DC2, Ag+ CD11bhi DC2, Ag− CD11blow DC2 and Ag+ CD11blow DC2 subsets using a BD Influx (Becton Dickinson) using BD FACSTM version software. For each subset, 2000 cells were collected.

RNA extraction and qRT-PCR on sorted DC subsets
RNA was extracted from sorted DC populations using a Quick-RNA™ MicroPrep kit (Zymo Research) and converted to cDNA using a High Capacity RNA-to-cDNA kit (Applied Biosystems, ThermoFisher Scientific) according to the manufacturer’s directions. cDNA was pre-amplified using a Sso-Advanced™ PreAmp Supermix kit (Bio-Rad) before running qRT-PCR, which was performed using the TaqMan™ Gene Assay platform (Applied Biosystems, ThermoFisher Scientific). The TaqMan™ probes used in this study were: Il12a (Mm00434169_m1), Il12b (Mm01288989_m1), Il27a (Mm01313472_m1), Ebi3 (Mm00469294_m1), Cxcl9 (Mm00434946_m1), Ccl17 (Mm01244826_g1), Ccl22 (Mm00436439_m1), Tnfsf4 (Mm00437214_m1), Il23a (Mm00518984_m1) and Il6 (Mm00446190_m1).

Statistical analyses
Statistical analyses were performed using Prism 8.0 GraphPad software. Data were analyzed using an un/paired two-sided Student’s t test, One-Way ANOVA with Holm–Sidak’s post-test, Two-Way ANOVA with Sidak’s multiple comparisons test, or as indicated in Figure legends. p-values < 0.05 were considered statistically significant and are reported in figures using the following notation: NS: not significant; **,##p < 0.01; ***,###p < 0.001; ****,####p < 0.0001 (with * and # referring to the comparisons specified in each Figure legend). Exact values are shown for 0.05 > p > 0.01.
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STEMVACS2 - Synergistic therapeutic effect of mesenchymal stem cells and tolerogenic dendritic cells in an acute colitis

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Synergistic therapeutic effect of mesenchymal stem cells and tolerogenic dendritic cells in an acute colitis mouse model ... 6920316556
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DENDRITIC CELLS - Lecture 9: "Immunology: T cells"

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Lecture 9: "Immunology: T cells"

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How activated dendritic cells can boost the immune system and fight diseases

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How activated dendritic cells can boost the immune system and fight diseases ... -diseases/

What are dendritic cells?
Dendritic cells (DCs) are an important part of the immune system, which coordinate between different types of immune responses. These responses can be:

Innate, involving non-specific defense mechanisms that come into play immediately or within hours of an antigen’s appearance in the body.
Adaptive, involving a complex, antigen-specific response and a “memory” that allows for more efficient future responses.

Scientists are now able to harness DCs to attack multiple pieces of a complex cancer simultaneously. Therapies based on DCs such as cancer vaccines have the potential to create large, sustained immune responses against cancer, and could become an important aspect of personalized immunotherapies.

The role of DCs in our immune system:
DCs (also known as accessory cells) process and present soluble antigens, in complex with either class I or class II major histocompatibility complex (MHC) molecules on their cell surface, to the B or T cells, which carry receptor molecules that recognize specific targets. DCs thus act as messengers between the innate immune system and the adaptive immune system.

DCs are present in trace numbers in most tissues and in a relatively immature state, especially in the blood. However, in the presence of inflammatory signals, they rapidly recognize foreign antigens and undergo maturation. Once activated, they migrate to the lymph nodes, where they interact with T and B cells to initiate an immune response.

How are DCs activated?
Dendritic cell activation can occur in two ways:

Directly by conserved pathogen molecules.
Indirectly by inflammatory mediators (which are produced by other cell types that recognize such molecules), cellular stress molecules, or disturbances in the internal body environment.

It is possible that these different activation pathways have evolved to ensure the early detection of infections before invading pathogens replicate in overwhelming numbers.

What are the latest scientific advancements of DCs?
Currently, it is possible to proliferate populations of DCs in vitro from various cellular sources including bone marrow, umbilical cord blood, and peripheral blood. Following appropriate stimulation, T cells can proliferate extensively in vitro. Traditionally, mitogenic lectins such as phytohemagglutinin (PHA) and concanavalin A (Con A) have been used for polyclonal T cell stimulation. Nowadays, beads coated with anti-CD3 and anti-CD28 are used to stimulate T cells in a manner that partially mimics stimulation by antigen-presenting cells.

This has shed light on the developmental biology of DCs and improved our knowledge of the mechanisms of antigen processing and presentation, which has ultimately led to improved strategies for vaccination and immunotherapy.

How does activated DC technology work?
Novel technologies are using activated DCs designed to regenerate and educate the immune system to attack cancer profiles. Cancer is a complex and variable disease; tumor profiles vary among patients with the same type of cancer, and cancer cells change their proliferation strategies after being treated with different drugs. Unlike conventional cancer drugs, which use a single active agent to attack a single target on the cancer cells, therapies based on activated DCs aim to use many active molecules that target different components of a cancer cell.

Usually, a sample that contains antigens of a patient with cancer is collected and used to produce activated autologous DCs, programmed to target these specific antigens. These activated, antigen-loaded DCs are then fused with the patient’s plasma, and administered via intradermal injection as a personalized immunotherapy.

Advantages of activated DCs:
Once in the patient’s body, these activated dendritic cells can mobilize a number of different biomarkers in a patient’s tumor profile (including antibodies, T cells, particular interleukins, and interferons). Dendritic cell-based immunotherapy is safe and can induce anti-tumor immunity, even in patients with advanced disease. Clinical studies and scientific research have shown that in some cases, this treatment has slowed disease progression or extended patient’s survival over standard drug treatments.

DC-based vaccines: A promising alternative for cancer treatment?
Findings from emerging research indicate that DC-based vaccination might also improve survival of cancer patients. Vaccination is one of the most effective methods to prevent many diseases. Preventive vaccines induce specific antibodies and long-lived memory B cells, but they can also induce cellular immunity. As mentioned above, DCs play a central role in the orchestration of immune responses, and are thus key targets in cancer vaccine design.

In contrast to chemotherapy, DC-based vaccines do not have a direct anti-tumor activity, but aim to reinvigorate patients’ immune systems in order to achieve this goal. In addition, they can generate long-lived memory CD8+ T cells that will act to prevent relapse.

As mentioned in the review of K. Palucka and J. Banchereau (2013), DCs can be exploited for vaccination against cancer through various means including:

Non-targeted peptide/protein and nucleic acids-based vaccines captured by DCs in vivo.
Vaccines composed of antigens directly coupled to anti-DC antibodies.
Vaccines composed of ex vivo generated DCs that are loaded with antigens.

The FDA approved the first DC-based cancer vaccine (Sipuleucel-T, trade name Provenge) in 2010. Since that time, scientific advancements have made the design of DC-based vaccines more efficient and there has been increasing interest in exploiting these cells as a therapeutic option for the treatment of tumors of diverse origin.

Many clinical trials using DC-based vaccines have shown them to be feasible—able to elicit immunological responses with few side effects. However, recent reviews that discuss the clinical effects of DC-based vaccines highlight the major difference observed between the immunogenicity and the therapeutic efficacy in terms of inducing tumor rejection. This clinical challenge emphasizes the importance and the need for further research.

Future prospects:
Therapies based on activated DCs are a promising tool for personalized cancer treatments. They can mobilize large and sustained immune responses, and appear to be non-toxic.

However, the clinical benefit provided by DC-based vaccines is still limited, and the choice of the optimal antigen formulation remains an unresolved issue. One promising future approach could use polyvalent vaccines, which target distinct yet specific DC subsets, to trigger an ideal composite anti-cancer immune response. Improvements in patient selection, vaccine delivery strategies, immune monitoring, and vaccine manufacturing will be crucial in moving DC-based vaccines closer to reality for the treatment of cancer.
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