Project description:Background: CD4+CD25hiCD127lo/-FOXP3+ regulatory T cells (Tregs) play a key role in preventing autoimmunity. In type 1 diabetes, adoptive transfer of autologous polyclonal Tregs has been shown to be safe in adults in Phase I clinical trials. Methods: We explore factors contributing to efficacy in autologous polyclonal expanded Tregs (expTregs) Phase 2 clinical trial in 111 children and adolescents with new-onset type 1 diabetes (Sanford/Lisata Therapeutics Trex Phase 2 clinical trial) randomized 1:1:1 high and low treatment to placebo. Cytometry, bulk and single cell RNA-seq were perfomed on selected expTregs and PBMC samples from subjects. Results: A single dose of expTreg therapy (1-24x106cells/kg) was safe but did not prevent the decline in residual beta cell function over one year compared to placebo (p=0.39), regardless of age, baseline C-peptide, or dose of expTregs. ExpTregs were highly activated and suppressive, and a transient increase of activated memory Tregs was detectable one week after infusion in the high dose cohort, suggesting effective transfer of expTregs. However, in vitro fold expansion on expTregs varied across subjects even when accounting for age. Lower fold expansion and its’ associated gene signature was linked with better outcome, regardless of Treg dose. Conclusion: These results suggest that expTregs quantity alone does not alter outcome; instead, expTreg quality may be an important factor contributing to the efficacy of adoptive Treg therapy to prevent type 1 diabetes progression.
Project description:Adoptive transfer of CD4+CD25hiCD127low FOXP3+ regulatory T cells (Treg) improves outcome as an adjunct treatment in transplantation to maintain tolerance. Phase I clinical trials have shown safety in adults, however, adoptive Treg tolerance is poorly understood in autoimmunity. Here, we explore factors contributing to efficacy in an autologous polyclonal expanded Treg (expTregs) Phase 2 clinical trial in 107 adolescents with recent-onset T1D (Sanford/Lisata Therapeutics Trex Phase 2 clinical trial) randomized 1:1:1 high and low treatment to placebo. A single dose of expTreg therapy (1-24x106cells/kg) did not prevent the decline in the residual beta cell function over two years compared to placebo (p=0.39), regardless of age, baseline c-peptide, or dose of expTreg (p=0.27). expTregs were a highly activated, pure, and suppressive Treg population as determined using flow cytometry and bulk RNA-seq prior to adoptive transfer. A transient increase of activated memory Tregs was detectable by flow cytometry and single-cell RNA-seq one week after infusion in the high dose cohort (p=0.003), suggesting effective transfer of expTreg. However, lower in vitro fold expansion and its linked gene signature associated with better outcome regardless of Treg dose. Together, these results suggest that expTregs quantity alone does not alter outcome; instead, expTreg quality, likely influenced by endogenous Treg features, may be important factors contributing to the efficacy of this treatment in preventing T1D progression.
Project description:Maintenance of beta cell function in adolescent T1D subjects treated with a single dose of polyclonal expanded Treg is linked to lower ex vivo Treg expansion
Project description:Purpose: identify differentially expressed genes between ex-Treg obtained 5, 10 or 15 days post-adoptive transfer into a lymphopenic environment compared to ex vivo Treg in order to identify Treg subset with heightened instability. Method: Treg from Foxp3YFP-Cre Rosa26RFP (PMID: 18387831, PMID: 17171761) were co-injected with congenically-disparated naive T cells in a 1:1 ratio into Rag1KO mice and ex-Treg were sorted at 15 days, 10 days or 5 days post-transfer. As a control, ex vivo Treg were sorted from Foxp3YFP-Cre Rosa26RFP (d0 sample). Next, samples were stained with multiplexing antibodies using the BD Single-Cell Multiplexing Kit (BD biosciences), then pooled and stained with the following oligonucleotide-conjugated antibodies: anti‑CD25 (PC61), anti-CD44 (IM7), anti-CD62L (MEL-14), anti-GITR (DTA-1), anti-CD4 (RM4-5), anti‑TCRb (H57-597), anti‑CD69 (H1.2F3), anti‑TIGIT (1G9), anti‑CD95 (Jo2), anti‑CD122 (TM‑1β), anti‑Tim-3 (5D12), anti‑CCR7 (4B12), anti‑CD103 (M290), anti‑CD279 (J43), anti‑CD274 (MIH5), anti‑CD233 (C9B7W), anti‑CD71 (C2), anti‑CD278 (7E7G9), anti‑ITGB7 (M293), anti‑CD137 (1AH2), anti‑CD40 (3/23), anti‑CD3e (145-2C) from BD Biosciences. Single-cell capture and cDNA library preparation was performed using the BD Rhapsody Single-cell analysis system (BD Biosciences), according to the manufacturer’s instructions, using a custom gene panel (591 genes). Sequencing was performed on an Illumina NextSeq500 instrument using a Mid‑Output kit v2.5 (150 cycles, paired-end). Sample demultiplexing, barcode processing, alignment, filtering, UMI counting were done using the standard BD Biosciences Rhapsody analysis pipeline on Seven Bridges (www.sevenbridges.com). Result: In this study, we showed that ex-Treg downregulate Treg core-specific genes immediatly upon adoptive transfer into a lymphopenic environment. Further, we identified a Treg population enriched for unstable Trg clones. Conclusion: Our study was able to identify a Treg subset enriched for unstable Treg with plastic potential. This Treg subset appears highly enriched for naïve peripheral-induced Treg.
Project description:Regulatory T (Treg) cells that express the FoxP3 transcription factor are essential for lymphoid homeostasis and immune tolerance to self. Other non-immunological functions of Treg cells, such as controlling metabolic function in adipose tissue, are also emerging. Treg cells originate primarily in the thymus, but can also be elicited from conventional T cells by in vivo exposure to low-dose antigen or homeostatic expansion, or by activation in the presence of TGFβ in vitro. Treg cells are characterized by a distinct transcriptional signature controlled in part, but not solely, by FoxP3. For a better perspective on transcriptional control in Treg cells, we compared gene expression profiles of a broad panel of Treg cells from various origins or anatomical locations. Treg cells generated by different means form different sub-phenotypes identifiable by particular combinations of transcripts, none of which fully encompass the entire Treg signature. Molecules involved in Treg effector function, chemokine receptors, and the transcription factors that control them are differentially represented in these subphenotypes. Treg cells from the gut proved dissimilar to cells elicited by exposure to TGFβ, but instead they resembled a CD103+Klrg1+ subphenotype preferentially generated in response to lymphopenia. All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. To reduce variability, cells from multiple mice were pooled for sorting, and replicates or triplicates were generated for all groups. RNA from 1-5 x 104 cells was amplified, labeled, and hybridized to Affymetrix M430v2 microarrays. Raw data were preprocessed with the RMA algorithm in GenePattern, and averaged expression values were used for analysis.
Project description:Regulatory T (Treg) cells that express the FoxP3 transcription factor are essential for lymphoid homeostasis and immune tolerance to self. Other non-immunological functions of Treg cells, such as controlling metabolic function in adipose tissue, are also emerging. Treg cells originate primarily in the thymus, but can also be elicited from conventional T cells by in vivo exposure to low-dose antigen or homeostatic expansion, or by activation in the presence of TGFβ in vitro. Treg cells are characterized by a distinct transcriptional signature controlled in part, but not solely, by FoxP3. For a better perspective on transcriptional control in Treg cells, we compared gene expression profiles of a broad panel of Treg cells from various origins or anatomical locations. Treg cells generated by different means form different sub-phenotypes identifiable by particular combinations of transcripts, none of which fully encompass the entire Treg signature. Molecules involved in Treg effector function, chemokine receptors, and the transcription factors that control them are differentially represented in these subphenotypes. Treg cells from the gut proved dissimilar to cells elicited by exposure to TGFβ, but instead they resembled a CD103+Klrg1+ subphenotype preferentially generated in response to lymphopenia.
Project description:The UCSF Treg cell therapy program manufactured over 60 human regulatory T cell (Treg) products under the GMP condition in support of 9 clinical trials between 2011 and 2021. These products were manufactured using two alternative protocols of either two rounds of polyclonal stimulations (PolyTregs) or first allogeneic B cell stimulation followed by polyclonal stimulation (arTregs). A high degree of individual variability in Treg expansion with both protocols was observed. RNA-seq analysis was performed on freshly isolated peripheral blood Tregs to identify transcriptome profile associated with Treg expansions.
Project description:Beside suppressing immune responses, regulatory T cells (Tregs) maintain tissue homeostasis and control systemic metabolism. Whether iron, a fundamental element for all living cells, is required for Treg expansion, is completely unknown. Here, we showed that the transferrin receptor CD71 was upregulated on activated proliferating Tregs infiltrating human liver cancer. Mice with a Treg-restricted CD71 deficiency spontaneously developed a scurfy-like disease, caused by a severe impairment in perinatal Treg expansion. CD71-null Tregs display decreased proliferation and mitochondrial functions, and a tissue-Treg signature loss. In the perinatal life, CD71 deficiency in Tregs triggered a hepatic response to iron overload, characterized by increased hepcidin transcription and iron accumulation in macrophages. A lower bacterial diversity, and a reduction of beneficial species, were detected in the faecal microbiota of CD71 conditional knock-out neonates. Our findings indicate that the CD71-mediated iron absorption is required for Treg perinatal expansion and controls the systemic iron homeostasis, which in turn shapes the bacterial gut colonization.
Project description:Direct contact with mesenchymal stromal impacts on migratory behavior and gene expression profile of CD133+ hematopoietic stem cells during ex-vivo expansion Objective: To investigate the impact of direct contact between mesenchymal stromal cells (MSCs) and CD133+ hematopoietic stem cells (HSCs) in terms of expansion potential differentiation, migratory capacity and gene expression profile. Methods: CD133+ purified HSCs were cultured for 7 days on subconfluent MSCs supplemented with growth factor containing medium. After ex-vivo expansion, non-adherent and adherent cells were collected and analyzed separately. Results: The adherent cells were found to have a more immature phenotype compared to the non-adherent fraction. CXCR4 was up regulated in the adherent fraction which was associated with a higher migration capacity towards a SDF-1 gradient. CFU-GM and LTC-IC assays demonstrated a higher clonogenicity and repopulating capacity of the adherent fraction. Genes involved in adhesion, cell cycle control, motility, self-renewal and apoptosis were expressed at a higher level in the adherent fraction. Conclusion: Adhesion and direct cell-cell contact with a MSC feeder layer supports ex-vivo expansion, migratory potential and stemness of CD133+ HSCs. Keywords: co-culture hematopoietic stem cells (HSCs) on mesenchymal stromal cells (MSCs) Non-adherent and adherent fractions from three independent experiments were isolated and collected. Cells were stabilized in PreProtct™ buffer (Miltenyi Biotec, Germany) and stored at -80ºC. Samples were shipped to Miltenyi Biotec (Bergisch Gladbach, Germany) a Whole Human Genome expression analysis. Briefly RNA was extracted and overall quality of total RNA samples was checked via the Agilent 2100 Bioanalyzer platform (Agilent Technologies). RNA samples were amplified and labelled using the Agilent Low RNA Input Linear Amp Kit (Agilent Technologies). Non-adherent samples were pooled as “Non-adherent pool” and adherent samples were pooled as “adherent pool” and labelled with Cy3 and Cy5, respectively. Fluorescence signals of the hybridized Agilent Oligo Microarrays were detected using Agilent’s DNA microarray scanner and the microarray image files were processed with The Agilent Feature Extraction Software (FES).