High‐dimensional single cell mapping of cerium distribution in the lung immune microenvironment of an active smoker

Abstract High-grade glioma are the main cause of cancer-related death in children. Despite extensive research, their prognosis remains poor with very few treatment options. This can be attributed to the highly heterogeneous and plastic nature of glioma tumor cells and their interactions with the microenvironment, although quantitative data are still largely missing. Here, we used high-dimensional, multiplexed immunohistochemistry to map the spatial, single-cell tissue architecture of 31 pediatric glioma samples covering 9 histologic diagnoses. This novel approach allowed us to map the spatial distribution of the various tumoral subtypes, which typically occur in specific tumoral niches, and how these interact with their local immune-microenvironment. Finally, by aligning these findings to the clinical data of the patients and comparing these to adult glioblastoma, we are now able to more precisely describe the heterogeneous landscape of pediatric glioma at single-cell resolution.

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High-dimensional single cell-based immune profiling of the tumor immune microenvironment in prostate cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.376 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 376-376

Author(s):

Michela Masetti ◽

Federica Portale ◽

Roberta Carriero ◽

Bianca Partini ◽

Nicolò Morina ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Flow Cytometry ◽

Single Cell ◽

High Dimensional ◽

Immune Microenvironment ◽

Single Cell Sequencing ◽

Single Cell Rna Sequencing ◽

Immune Changes ◽

Immune Profiling

376 Background: Genetic lesions that drive prostate cancer (PCa) development are able to modify the immune response and tumor infiltrating immune subsets, resulting in tumor progression. We investigated the profile of the immune microenvironment in PCa by high dimensional single cell analysis. Methods: We conducted an immune profiling study based on integrated RNA single cell sequencing and multiparametric flow cytometry in order to dissect the immune landscape of PCa. CD45+ immune cells infiltrating tumoral and adjacent non tumoral tissues were isolated from patients with PCa who underwent software assisted fusion biopsy, based on MRI, and/or radical prostatectomy, and analyzed by single cell sequencing. The primary endpoint was to evaluate the effectiveness of single cell RNA sequencing on CD45+ cell sorted from tumoral and adjacent non-tumoral tissues. Secondary endpoint was the identification of tumor-driven immune changes in prostatic lesions. Results: The cohort consisted of 3 patients who underwent radical prostatectomy (RP) and 45 patients with positive prostate biopsy; the negative control was checked by pathological assessment. In patients who underwent RP the gene expression analysis identified a modulation in the abundance of several immune subsets infiltrating the tumoral tissue, when compared with the non tumoral, evident for Tumor associated macrophages (TAMs), Natural Killer cells (NK) and T regulatory cells. We then implemented a 22 parameters flow cytometry panel that we tested on fresh prostatic tissue and peripheral blood from positive PCa biopsies. We identified a subset of tumor infiltrating macrophages showing an altered gene expression profile when compared with macrophages infiltrating the non-tumoral tissue. Importantly we derived a genetic signature from this subset of tumoral TAMs that resulted to be associated with cancer progression. Conclusions: Our findings support the effectiveness of single cell RNA sequencing in the dissection of the immune landscape in PCa and identified immune changes in patients when comparing neoplastic tissue with non tumoral areas. Such data may be useful for understanding the role of immune system in PCa carcinogenesis.

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Faculty Opinions recommendation of Single-cell mapping of the thymic stroma identifies IL-25-producing tuft epithelial cells.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.733651501.793549521 ◽

2018 ◽

Author(s):

Joonsoo Kang

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Cell Mapping ◽

Thymic Stroma

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773 Adoptive Cell Therapy Response in Melanoma is Mediated by Stem-like CD8 T cells

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0773 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A822-A822

Author(s):

Sri Krishna ◽

Frank Lowery ◽

Amy Copeland ◽

Stephanie Goff ◽

Grégoire Altan-Bonnet ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Cell Therapy ◽

Single Cell ◽

Cd8 T Cells ◽

Tumor Infiltrating Lymphocytes ◽

High Dimensional ◽

Tumor Control ◽

Intrinsic Factors ◽

Infiltrating Lymphocytes

BackgroundAdoptive T cell therapy (ACT) utilizing ex vivo-expanded autologous tumor infiltrating lymphocytes (TILs) can result in complete regression of human cancers.1 Successful immunotherapy is influenced by several tumor-intrinsic factors.2 3 Recently, T cell-intrinsic factors have been associated with immunotherapy response in murine and human studies.4 5 Analyses of tumor-reactive TILs have concluded that anti-tumor neoantigen-specific TILs are enriched in subsets defined by the expression of PD-1 or CD39.6 7 Thus, there is a lack of consensus regarding the tumor-reactive TIL subset that is directly responsible for successful immunotherapies such as ICB and ACT. In this study, we attempted to define the fitness landscape of TIL-enriched infusion products to specifically understand its phenotypic impact on human immunotherapy responses.MethodsWe compared the phenotypic differences that could distinguish bulk ACT infusion products (I.P.) administered to patients who had complete response to therapy (complete responders, CRs, N = 24) from those whose disease progressed following ACT (non-responders, NRs, N = 30) by high dimensional single cell protein and RNA analysis of the I.P. We further analyzed the phenotypic states of anti-tumor neoantigen specific TILs from patient I.P (N = 26) by flow cytometry and single cell transcriptomics.ResultsWe identified two CD8+ TIL populations associated with clinical outcomes: a memory-progenitor CD39-negative stem-like TIL (CD39-CD69-) in the I.P. associated with complete cancer regression (overall survival, P < 0.0001, HR = 0.217, 95% CI 0.101 to 0.463) and TIL persistence, and a terminally differentiated CD39-positive TIL (CD39+CD69+) population associated with poor TIL persistence post-treatment. Although the majority (>65%) of neoantigen-reactive TILs in both responders and non-responders to ACT were found in the differentiated CD39+ state, CR infusion products also contained a pool of CD39- stem-like neoantigen-specific TILs (median = 8.8%) that was lacking in NR infusion products (median = 23.6%, P = 1.86 x 10-5). Tumor-reactive stem-like T cells were capable of self-renewal, expansion, and persistence, and mediated superior anti-tumor response in vivo.ConclusionsOur results support the hypothesis that responders to ACT received infusion products containing a pool of stem-like neoantigen-specific TILs that are able to undergo prolific expansion, give rise to differentiated subsets, and mediate long-term tumor control and T cell persistence, in line with recent murine ICB studies mediated by TCF+ progenitor T cells.4 5 Our data also suggest that TIL subsets mediating ACT-response (stem-like CD39-) might be distinct from TIL subsets enriched for anti-tumor-reactivity (terminally differentiated CD39+) in human TIL.6 7AcknowledgementsWe thank Don White for curating the melanoma patient cohort, and J. Panopoulos (Flowjo) for helpful discussions on high-dimensional analysis, and NCI Surgery Branch members for helpful insights and suggestions. S. Krishna acknowledges funding support from NCI Director’s Innovation Award from the National Cancer Institute.Trial RegistrationNAEthics ApprovalThe study was approved by NCI’s IRB ethics board.ReferencesGoff SL, et al. Randomized, prospective evaluation comparing intensity of lymphodepletion before adoptive transfer of tumor-infiltrating lymphocytes for patients with metastatic melanoma. J Clin Oncol 2016;34:2389–2397.Snyder A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014;371:2189–2199.McGranahan N, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016;351:1463–1469.Sade-Feldman M, et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 2019;176:404.Miller BC, et al. Subsets of exhausted CD8 T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol 2019;20:326–336.Simoni Y, et al. Bystander CD8 T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature 2018;557:575–579.Gros A, et al. PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors. J Clin Invest 2014;124:2246–2259.

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Correction to: High-dimensional single cell mass cytometry analysis of the murine hematopoietic system reveals signatures induced by ageing and physiological pathogen challenges

Immunity & Ageing ◽

10.1186/s12979-021-00235-y ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Christos Nikolaou ◽

Kerstin Muehle ◽

Stephan Schlickeiser ◽

Alberto Sada Japp ◽

Nadine Matzmohr ◽

...

Keyword(s):

Single Cell ◽

Cell Mass ◽

High Dimensional ◽

Mass Cytometry ◽

Hematopoietic System

An amendment to this paper has been published and can be accessed via the original article.

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Conditional out-of-distribution generation for unpaired data using transfer VAE

Bioinformatics ◽

10.1093/bioinformatics/btaa800 ◽

2020 ◽

Vol 36 (Supplement_2) ◽

pp. i610-i617

Author(s):

Mohammad Lotfollahi ◽

Mohsen Naghipourfar ◽

Fabian J Theis ◽

F Alexander Wolf

Keyword(s):

Single Cell ◽

Generative Models ◽

Response To Treatment ◽

High Dimensional ◽

Compact Representation ◽

Hair Color ◽

Great Success ◽

Cell Type ◽

Style Transfer ◽

Cell Type Specific

Abstract Motivation While generative models have shown great success in sampling high-dimensional samples conditional on low-dimensional descriptors (stroke thickness in MNIST, hair color in CelebA, speaker identity in WaveNet), their generation out-of-distribution poses fundamental problems due to the difficulty of learning compact joint distribution across conditions. The canonical example of the conditional variational autoencoder (CVAE), for instance, does not explicitly relate conditions during training and, hence, has no explicit incentive of learning such a compact representation. Results We overcome the limitation of the CVAE by matching distributions across conditions using maximum mean discrepancy in the decoder layer that follows the bottleneck. This introduces a strong regularization both for reconstructing samples within the same condition and for transforming samples across conditions, resulting in much improved generalization. As this amount to solving a style-transfer problem, we refer to the model as transfer VAE (trVAE). Benchmarking trVAE on high-dimensional image and single-cell RNA-seq, we demonstrate higher robustness and higher accuracy than existing approaches. We also show qualitatively improved predictions by tackling previously problematic minority classes and multiple conditions in the context of cellular perturbation response to treatment and disease based on high-dimensional single-cell gene expression data. For generic tasks, we improve Pearson correlations of high-dimensional estimated means and variances with their ground truths from 0.89 to 0.97 and 0.75 to 0.87, respectively. We further demonstrate that trVAE learns cell-type-specific responses after perturbation and improves the prediction of most cell-type-specific genes by 65%. Availability and implementation The trVAE implementation is available via github.com/theislab/trvae. The results of this article can be reproduced via github.com/theislab/trvae_reproducibility.

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Mapping the immune microenvironment for mandibular alveolar bone homeostasis at single-cell resolution

Bone Research ◽

10.1038/s41413-021-00141-5 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Weimin Lin ◽

Qiwen Li ◽

Danting Zhang ◽

Xiaohan Zhang ◽

Xingying Qi ◽

...

Keyword(s):

Single Cell ◽

Alveolar Bone ◽

Immune Cell ◽

Adipogenic Differentiation ◽

Oncostatin M ◽

Long Bone ◽

Bone Homeostasis ◽

Oral Diseases ◽

Immune Microenvironment ◽

Occlusal Force

AbstractAlveolar bone is the thickened ridge of jaw bone that supports teeth. It is subject to constant occlusal force and pathogens invasion, and is therefore under active bone remodeling and immunomodulation. Alveolar bone holds a distinct niche from long bone considering their different developmental origin and postnatal remodeling pattern. However, a systematic explanation of alveolar bone at single-cell level is still lacking. Here, we construct a single-cell atlas of mouse mandibular alveolar bone through single-cell RNA sequencing (scRNA-seq). A more active immune microenvironment is identified in alveolar bone, with a higher proportion of mature immune cells than in long bone. Among all immune cell populations, the monocyte/macrophage subpopulation most actively interacts with mesenchymal stem cells (MSCs) subpopulation. Alveolar bone monocytes/macrophages express a higher level of Oncostatin M (Osm) compared to long bone, which promotes osteogenic differentiation and inhibits adipogenic differentiation of MSCs. In summary, our study reveals a unique immune microenvironment of alveolar bone, which may provide a more precise immune-modulatory target for therapeutic treatment of oral diseases.

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A generalization of t-SNE and UMAP to single-cell multimodal omics

Genome Biology ◽

10.1186/s13059-021-02356-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Van Hoan Do ◽

Stefan Canzar

Keyword(s):

Dimensionality Reduction ◽

Single Cell ◽

Cell Types ◽

High Dimensional ◽

Omics Data ◽

Relative Contribution ◽

Reduction Techniques ◽

Dimensionality Reduction Techniques ◽

Concise Representation ◽

Cellular Identity

AbstractEmerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes.

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