Single-cell lymphocyte heterogeneity inadvanced Cutaneous T-Cell Lymphoma skin tumors
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PROVIDER: PRJNA528020 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: The heterogeneity of tumor cells presents a major challenge to cancer diagnosis and therapy. Cutaneous T cell lymphomas (CTCL) are a group of T lymphocyte malignanciesthat primarily affect skin. Lack of highly specific markers for malignant lymphocytes prevents early diagnosis, while only limited treatment options are available for patients with advanced-stage CTCL.Droplet-basedsingle-cell transcriptome analysis of CTCL skin biopsiesopens avenues for dissecting patient-specificT lymphocyte heterogeneity, providing a basis for identifying specific markers for diagnosis and cure of CTCL. Experimental Design: Single-cell RNA-sequencing was performed by Droplet-based sequencing (10X Genomics), focusing on 14,056 CD3+lymphocytes (448 cells from normal and 13,608 cells from CTCL skin samples) from skin biopsies of 5 patients with advanced-stage CTCL and 4 healthy donors.Protein expression of identified genes was validated in advanced-stage CTCL skin tumors byimmunohistochemistry and confocal immunofluorescence microscopy. Results: Our analysis revealed a large inter- and intra-tumor gene expression heterogeneity in the T lymphocyte subset, as well as a common gene expression signature in highly proliferating lymphocytes that was validated in multiple advanced-stage skin tumors. In addition, we established the immunological state of reactive lymphocytes and found heterogeneity in effector and exhaution programs across patient samples. Conclusions: Single-cell analysis of CTCL skin tumor samples reveals patient-specific landscapes of malignant and reactive lymphocytes within the local microenvironment of each tumor, giving anunprecedented view of lymphocyte heterogeneity and identifying tumor-specific molecular signatures, withimportant implications for diagnosis and personalized disease treatment.
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Project description:We studied gene expression profiles of 17 cutaneous B-cell lymphomas that were collected with 4-6 millimeter skin punch biopsies. We also included tissue from 2 cases of mycosis fungoides (MF), 3 normal skin biopsies and 3 tonsils to create a framework for further interpretation. A hierarchical cluster algorithm was applied for data analysis. Our results indicate that small amounts of skin tissue can be used successfully to perform microarray analysis and result in distinct gene expression patterns. Duplicate specimens clustered together demonstrating a reproducible technique. Within the cutaneous B-cell lymphoma specimens two specific B-cell differentiation stage signatures of germinal center B-cells and plasma cells could be identified. Primary cutaneous follicular and primary cutaneous diffuse large B-cell lymphomas had a germinal center B-cell signature while a subset of marginal zone lymphomas demonstrated a plasma cell signature. Primary and secondary follicular B-cell lymphoma of the skin were closely related, despite previously reported genetic and phenotypic differences. In contrast primary and secondary cutaneous diffuse large B-cell lymphoma were less related to each other. This pilot study allows a first glance into the complex and unique microenvironment of B-cell lymphomas of the skin and provides a basis for future studies, that may lead to the identification of potential histologic and prognostic markers as well as therapeutic targets. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed
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Project description:Genetic disruption of class I HLA is a common mechanism of immune evasion and immunotherapy resistance in many other cancers but has not yet been characterized in cutaneous T-cell lymphoma (CTCL). We performed single-cell RNA sequencing (scRNA-seq) on tumor samples from patients with CTCL to demonstrate the tumor-specificity and intratumoral heterogeneity of such abnormalities.
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Project description:We studied gene expression profiles of 17 cutaneous B-cell lymphomas that were collected with 4-6 millimeter skin punch biopsies. We also included tissue from 2 cases of mycosis fungoides (MF), 3 normal skin biopsies and 3 tonsils to create a framework for further interpretation. A hierarchical cluster algorithm was applied for data analysis. Our results indicate that small amounts of skin tissue can be used successfully to perform microarray analysis and result in distinct gene expression patterns. Duplicate specimens clustered together demonstrating a reproducible technique. Within the cutaneous B-cell lymphoma specimens two specific B-cell differentiation stage signatures of germinal center B-cells and plasma cells could be identified. Primary cutaneous follicular and primary cutaneous diffuse large B-cell lymphomas had a germinal center B-cell signature while a subset of marginal zone lymphomas demonstrated a plasma cell signature. Primary and secondary follicular B-cell lymphoma of the skin were closely related, despite previously reported genetic and phenotypic differences. In contrast primary and secondary cutaneous diffuse large B-cell lymphoma were less related to each other. This pilot study allows a first glance into the complex and unique microenvironment of B-cell lymphomas of the skin and provides a basis for future studies, that may lead to the identification of potential histologic and prognostic markers as well as therapeutic targets. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
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