Single-cell profiling of cutaneous T-cell lymphoma reveals underlying heterogeneity predicting with disease progression.
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ABSTRACT:
PROVIDER: PRJNA506054 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8207940_1.fastq.gz | Fastqsanger.gz | |||
| SRR8207940_2.fastq.gz | Fastqsanger.gz | |||
| SRR8207941_1.fastq.gz | Fastqsanger.gz | |||
| SRR8207941_2.fastq.gz | Fastqsanger.gz |
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Project description:Cutaneous T cell lymphomas (CTCL), encompassing a spectrum of T-cell lymphoproliferative disorders involving the skin, have collectively increased in incidence over the last 40 years. Sézary syndrome (SS) is an aggressive form of CTCL characterized by significant presence of malignant cells in both the blood and skin. The guarded prognosis for SS reflects a lack of reliably effective therapy, due in part to an incomplete understanding of disease pathogenesis. Using single-cell sequencing of RNA, we confirm that SS is a clonal disease, but we further define a more complex model featuring distinct transcriptomic states within SS. Our analysis showed the involvement of FOXP3+ malignant T cells during clonal evolution, transitioning from FOXP3+ T cells to GATA3+ or IKZF2+ (HELIOS) tumor cells. Transcriptomic diversities in a clonal tumor can be used to predict disease stage, and we were able to characterize a gene signature that predicts disease stage with close to 80% accuracy. Supporting the critical role of FOXP3+ T cell involvement during clonal evolution, FOXP3 was found to be the most important factor to predict early disease in SS, along with another 19 genes used to predict CTCL stage. This work offers insight into the heterogeneity of SS, providing better understanding of the transcriptomic diversities within a clonal tumor, which can predict tumor stage and thereby offer guidance of therapy.
2019-03-22 | GSE122703 | GEO
Project description:Study of cutaneous biology of cutaneous T cell lymphoma
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Project description:PURPOSE:Cutaneous T-cell lymphomas (CTCL), encompassing a spectrum of T-cell lymphoproliferative disorders involving the skin, have collectively increased in incidence over the last 40 years. Sézary syndrome is an aggressive form of CTCL characterized by significant presence of malignant cells in both the blood and skin. The guarded prognosis for Sézary syndrome reflects a lack of reliably effective therapy, due, in part, to an incomplete understanding of disease pathogenesis. EXPERIMENTAL DESIGN:Using single-cell sequencing of RNA and the machine-learning reverse graph embedding approach in the Monocle package, we defined a model featuring distinct transcriptomic states within Sézary syndrome. Gene expression used to differentiate the unique transcriptional states were further used to develop a boosted tree classification for early versus late CTCL disease. RESULTS:Our analysis showed the involvement of FOXP3 + malignant T cells during clonal evolution, transitioning from FOXP3 + T cells to GATA3 + or IKZF2 + (HELIOS) tumor cells. Transcriptomic diversities in a clonal tumor can be used to predict disease stage, and we were able to characterize a gene signature that predicts disease stage with close to 80% accuracy. FOXP3 was found to be the most important factor to predict early disease in CTCL, along with another 19 genes used to predict CTCL stage. CONCLUSIONS:This work offers insight into the heterogeneity of Sézary syndrome, providing better understanding of the transcriptomic diversities within a clonal tumor. This transcriptional heterogeneity can predict tumor stage and thereby offer guidance for therapy.
| S-EPMC6659117 | biostudies-literature
Project description:Single-cell profiling of cutaneous T-cell lymphoma
| PRJNA514234 | ENA
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
2005-12-16 | E-GEOD-3827 | biostudies-arrayexpress
Project description:SATB1 is an important T-cell specific chromatin organizer in cutaneous T cell lymphoma, while its expression and function in Mycosis fungoides (MF) remain ambiguous. RNA-sequencing was conducted to investigate the genes regulated by SATB1 in MF-derived MJ cells by RNA-sequencing after SATB1-knockdown. With the criteria of P<0.05 and |fold change|>1.3, there were 988 genes upregulated and 1373 genes downregulated in SATB1-silencing MJ cells and further subjected to KEGG analysis. SATB1 silencing in MJ cells showed that SATB1 upregulated genes involved in eosinophil recruitment, including STAT3 and IL13, and downregulated genes in cell cycle progression.
2020-12-31 | GSE144667 | GEO
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
2005-12-17 | GSE3827 | GEO
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.
2019-05-10 | GSE128531 | GEO