scholarly journals Abstract 1550: Single-cell RNA-Seq identified an immunosuppressive IL-17 producing tumor-infiltrating T cells in murine gastric tumor model

Author(s):  
Masataka Shirai ◽  
Koji Nagaoka ◽  
Kiyomi Taniguchi ◽  
Changbo Sun ◽  
Akihiro Hosoi ◽  
...  
2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A799-A799
Author(s):  
Dhiraj Kumar ◽  
Sreeharsha Gurrapu ◽  
Hyunho Han ◽  
Yan Wang ◽  
Seongyeon Bae ◽  
...  

BackgroundLong non-coding RNAs (lncRNAs) are involved in various biological processes and diseases. Malat1 (metastasis-associated lung adenocarcinoma transcript 1), also known as Neat2, is one of the most abundant and highly conserved nuclear lncRNAs. Several studies have shown that the expression of lncRNA Malat1 is associated with metastasis and serving as a predictive marker for various tumor progression. Metastatic relapse often develops years after primary tumor removal as a result of disseminated tumor cells undergoing a period of latency in the target organ.1–4 However, the correlation of tumor intrinsic lncRNA in regulation of tumor dormancy and immune evasion is largely unknown.MethodsUsing an in vivo screening platform for the isolation of genetic entities involved in either dormancy or reactivation of breast cancer tumor cells, we have identified Malat1 as a positive mediator of metastatic reactivation. To functionally uncover the role of Malat1 in metastatic reactivation, we have developed a knock out (KO) model by using paired gRNA CRISPR-Cas9 deletion approach in metastatic breast and other cancer types, including lung, colon and melanoma. As proof of concept we also used inducible knockdown system under in vivo models. To delineate the immune micro-environment, we have used 10X genomics single cell RNA-seq, ChIRP-seq, multi-color flowcytometry, RNA-FISH and immunofluorescence.ResultsOur results reveal that the deletion of Malat1 abrogates the tumorigenic and metastatic potential of these tumors and supports long-term survival without affecting their ploidy, proliferation, and nuclear speckles formation. In contrast, overexpression of Malat1 leads to metastatic reactivation of dormant breast cancer cells. Moreover, the loss of Malat1 in metastatic cells induces dormancy features and inhibits cancer stemness. Our RNA-seq and ChIRP-seq data indicate that Malat1 KO downregulates several immune evasion and stemness associated genes. Strikingly, Malat1 KO cells exhibit metastatic outgrowth when injected in T cells defective mice. Our single-cell RNA-seq cluster analysis and multi-color flow cytometry data show a greater proportion of T cells and reduce Neutrophils infiltration in KO mice which indicate that the immune microenvironment playing an important role in Malat1-dependent immune evasion. Mechanistically, loss of Malat1 is associated with reduced expression of Serpinb6b, which protects the tumor cells from cytotoxic killing by the T cells. Indeed, overexpression of Serpinb6b rescued the metastatic potential of Malat1 KO cells by protecting against cytotoxic T cells.ConclusionsCollectively, our data indicate that targeting this novel cancer-cell-initiated domino effect within the immune system represents a new strategy to inhibit tumor metastatic reactivation.Trial RegistrationN/AEthics ApprovalFor all the animal studies in the present study, the study protocols were approved by the Institutional Animal Care and Use Committee(IACUC) of UT MD Anderson Cancer Center.ConsentN/AReferencesArun G, Diermeier S, Akerman M, et al., Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes Dev 2016 Jan 1;30(1):34–51.Filippo G. Giancotti, mechanisms governing metastatic dormancy and reactivation. Cell 2013 Nov 7;155(4):750–764.Gao H, Chakraborty G, Lee-Lim AP, et al., The BMP inhibitor Coco reactivates breast cancer cells at lung metastatic sites. Cell 2012b;150:764–779.Gao H, Chakraborty G, Lee-Lim AP, et al., Forward genetic screens in mice uncover mediators and suppressors of metastatic reactivation. Proc Natl Acad Sci U S A 2014 Nov 18; 111(46): 16532–16537.


2020 ◽  
Vol 11 ◽  
Author(s):  
Noudjoud Attaf ◽  
Iñaki Cervera-Marzal ◽  
Chuang Dong ◽  
Laurine Gil ◽  
Amédée Renand ◽  
...  

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 42-43
Author(s):  
Prajish Iyer ◽  
Lu Yang ◽  
Zhi-Zhang Yang ◽  
Charla R. Secreto ◽  
Sutapa Sinha ◽  
...  

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab


2020 ◽  
Vol 11 ◽  
Author(s):  
Noudjoud Attaf ◽  
Iñaki Cervera-Marzal ◽  
Chuang Dong ◽  
Laurine Gil ◽  
Amédée Renand ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Juber Herrera-Uribe ◽  
Jayne E. Wiarda ◽  
Sathesh K. Sivasankaran ◽  
Lance Daharsh ◽  
Haibo Liu ◽  
...  

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B-cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B-cell, conventional CD4 and CD8 αβ T-cells, NK cells, and γδ T-cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T-cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.


2020 ◽  
Author(s):  
Yan Zhou ◽  
Dong Yang ◽  
Qing-Cheng Yang ◽  
Xiao-Bin Lv ◽  
Wen-Tao Huang ◽  
...  

ABSTRACTOsteosarcoma (OS) has high heterogeneity and poor prognosis. In order to explore the molecular mechanism of OS and the tumor micro-environment (TME) on OS, we employed single-cell RNA-sequencing (scRNA-seq) on 110,745 individual cells from OS primary lesion, recurrent focal and metastatic tissues. We identified 5 main malignant subpopulations of OS cells, 3 clusters of osteoclast(OC) and 2 types of cancer-associated fibroblasts (CAFs). Further we found that the progenitor OC and, antigen presenting CAF (apCAF) were lower in lung metastatic and recurrent tumor tissues than in primary tumor tissue. M2-like macrophages were predominant in the TME myeloid cells. Inactivation state of tumor-infiltrating T cells, mainly the CD4-/CD8-T and Treg cells, existed in lung metastatic tissues. T-cell immunoreceptor with Ig and ITIM domains (TIGIT) expressed in 11 samples. We then blocked TIGIT which significantly enhancd the cytotoxic effects of primary T cells on OS cell lines. Our report represents the first use of scRNA-seq for the transcriptomic profiling of OS cells. Thus, the findings in this study will serve as a valuable resource for deciphering the intra-tumoral heterogeneity in OS and provide potential therapeutic strategies for OS in clinic.


PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258029
Author(s):  
Ying Yao ◽  
Łukasz Wyrozżemski ◽  
Knut E. A. Lundin ◽  
Geir Kjetil Sandve ◽  
Shuo-Wang Qiao

Gluten-specific CD4+ T cells drive the pathogenesis of celiac disease and circulating gluten-specific T cells can be identified by staining with HLA-DQ:gluten tetramers. In this first single-cell RNA-seq study of tetramer-sorted T cells from untreated celiac disease patients blood, we found that gluten-specific T cells showed distinct transcriptomic profiles consistent with activated effector memory T cells that shared features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in T-cell receptor signaling, translational processes, apoptosis, fatty acid transport, and redox potentials. Many of the gluten-specific T cells studied shared T-cell receptor with each other, indicating that circulating gluten-specific T cells belong to a limited number of clones. Moreover, the transcriptional profiles of cells that shared the same clonal origin were transcriptionally more similar compared with between clonally unrelated gluten-specific cells.


2020 ◽  
Vol 8 (2) ◽  
pp. e001358
Author(s):  
Koji Nagaoka ◽  
Masataka Shirai ◽  
Kiyomi Taniguchi ◽  
Akihiro Hosoi ◽  
Changbo Sun ◽  
...  

BackgroundAlthough immune checkpoint blockade is effective for several malignancies, a substantial number of patients remain refractory to treatment. The future of immunotherapy will be a personalized approach adapted to each patient’s cancer-immune interactions in the tumor microenvironment (TME) to prevent suppression of antitumor immune responses. To demonstrate the feasibility of this kind of approach, we developed combination therapy for a preclinical model guided by deep immunophenotyping of the TME.MethodsGastric cancer cell lines YTN2 and YTN16 were subcutaneously inoculated into C57BL/6 mice. YTN2 spontaneously regresses, while YTN16 grows progressively. Bulk RNA-Seq, single-cell RNA-Seq (scRNA-Seq) and flow cytometry were performed to investigate the immunological differences in the TME of these tumors.ResultsBulk RNA-Seq demonstrated that YTN16 tumor cells produced CCL20 and that CD8+ T cell responses were impaired in these tumors relative to YTN2. We have developed a vertical flow array chip (VFAC) for targeted scRNA-Seq to identify unique subtypes of T cells by employing a panel of genes reflecting T cell phenotypes and functions. CD8+ T cell dysfunction (cytotoxicity, proliferation and the recruitment of interleukin-17 (IL-17)-producing cells into YTN16 tumors) was identified by targeted scRNA-Seq. The presence of IL-17-producing T cells in YTN16 tumors was confirmed by flow cytometry, which also revealed neutrophil infiltration. IL-17 blockade suppressed YTN16 tumor growth, while tumors were rejected by the combination of anti-IL-17 and anti-PD-1 (Programmed cell death protein 1) mAb treatment. Reduced neutrophil activation and enhanced expansion of neoantigen-specific CD8+ T cells were observed in tumors of the mice receiving the combination therapy.ConclusionsDeep phenotyping of YTN16 tumors identified a sequence of events on the axis CCL20->IL-17-producing cells->IL-17-neutrophil-angiogenesis->suppression of neoantigen-specific CD8+ T cells which was responsible for the lack of tumor rejection. IL-17 blockade together with anti-PD-1 mAb therapy eradicated these YTN16 tumors. Thus, the deep immunological phenotyping can guide immunotherapy for the tailored treatment of each individual patient’s tumor.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Karren Dai Yang ◽  
Anastasiya Belyaeva ◽  
Saradha Venkatachalapathy ◽  
Karthik Damodaran ◽  
Abigail Katcoff ◽  
...  

AbstractThe development of single-cell methods for capturing different data modalities including imaging and sequencing has revolutionized our ability to identify heterogeneous cell states. Different data modalities provide different perspectives on a population of cells, and their integration is critical for studying cellular heterogeneity and its function. While various methods have been proposed to integrate different sequencing data modalities, coupling imaging and sequencing has been an open challenge. We here present an approach for integrating vastly different modalities by learning a probabilistic coupling between the different data modalities using autoencoders to map to a shared latent space. We validate this approach by integrating single-cell RNA-seq and chromatin images to identify distinct subpopulations of human naive CD4+ T-cells that are poised for activation. Collectively, our approach provides a framework to integrate and translate between data modalities that cannot yet be measured within the same cell for diverse applications in biomedical discovery.


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