Dataset Information

Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues.

ABSTRACT: Single cell transcriptome analysis of a cancer tissue can provide objective assessment of subtype population or the activation of each of various microenvironment component cells. In this study, we applied our newly developed technique of single cell analysis to the myometrial infiltration side (M-side) and the endometrial side (E-side) of a human endometrioid adenocarcinoma with squamous differentiation tissues. We also analyzed spherogenic cultures derived from the same tissue to identify putative regulators of stemness in vivo. Cancer cells in the E-side were highly malignant compared with those in the M-side. Many cells on the E-side were positive for spheroid-specific tumorigenesis-related markers including SOX2. In addition, there were higher numbers of epithelial-to-mesenchymal transition (EMT) cells in the E-side compared with the M-side. This study identified a site containing cells with high malignant potential such as EMT and cancer stem-like cells in cancer tissues. Finally, we demonstrate that established endometrioid adenocarcinoma subtype classifiers were variably expressed across individual cells within a tumor. Thus, such intratumoral heterogeneity may be related to prognostic implications.

SUBMITTER: Hashimoto S

PROVIDER: S-EPMC5660171 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues.

Hashimoto Shinichi S Tabuchi Yuta Y Yurino Hideaki H Hirohashi Yoshihiko Y Deshimaru Shungo S Asano Takuya T Mariya Tasuku T Oshima Kenshiro K Takamura Yuzuru Y Ukita Yoshiaki Y Ametani Akio A Kondo Naoto N Monma Norikazu N Takeda Tadayuki T Misu Sadahiko S Okayama Toshitugu T Ikeo Kazuho K Saito Tsuyoshi T Kaneko Shuich S Suzuki Yutaka Y Hattori Masahira M Matsushima Kouji K Torigoe Toshihiko T

Scientific reports 20171027 1

Single cell transcriptome analysis of a cancer tissue can provide objective assessment of subtype population or the activation of each of various microenvironment component cells. In this study, we applied our newly developed technique of single cell analysis to the myometrial infiltration side (M-side) and the endometrial side (E-side) of a human endometrioid adenocarcinoma with squamous differentiation tissues. We also analyzed spherogenic cultures derived from the same tissue to identify puta ...[more]

PMID: 29079795

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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

Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues.

Publications

Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues.

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