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Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression.

ABSTRACT: 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.

SUBMITTER: Borcherding N

PROVIDER: S-EPMC6659117 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression.

Borcherding Nicholas N Voigt Andrew P AP Liu Vincent V Link Brian K BK Zhang Weizhou W Jabbari Ali A

Clinical cancer research : an official journal of the American Association for Cancer Research 20190204 10

<h4>Purpose</h4>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.<h4>Experim ...[more]

PMID: 30718356

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Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC.

Dataset Information

Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression.

Publications

Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression.

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