scholarly journals A Microfluidic Chip for Efficient Circulating Tumor Cells Enrichment, Screening and Single‐cell RNA Sequencing

PROTEOMICS ◽  
2020 ◽  
pp. 2000060
Author(s):  
Fanghao Shi ◽  
Fei Jia ◽  
Zewen Wei ◽  
Yan Ma ◽  
Zhiguo Fang ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Circulating Tumor Cells ◽  
Microfluidic Chip ◽  
Single Cell Rna Sequencing

scholarly journals Single-Cell RNA Sequencing Identifies Extracellular Matrix Gene Expression by Pancreatic Circulating Tumor Cells

Cell Reports ◽  
2014 ◽  
Vol 8 (6) ◽  
pp. 1905-1918 ◽  
Author(s):  
David T. Ting ◽  
Ben S. Wittner ◽  
Matteo Ligorio ◽  
Nicole Vincent Jordan ◽  
Ajay M. Shah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Extracellular Matrix ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Circulating Tumor Cells ◽  
Matrix Gene ◽  
Single Cell Rna Sequencing

Abstract IA09: Single cell RNA-sequencing of circulating tumor cells

2016 ◽  
Author(s):  
David T. Miyamoto ◽  
Yu Zheng ◽  
Ben S. Wittner ◽  
Richard J. Lee ◽  
Huili Zhu ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Circulating Tumor Cells ◽  
Single Cell Rna Sequencing

scholarly journals Whole transcriptomics analyses of mimicking circulating tumor cells (CTCs) by single-cell RNA sequencing (scRNAseq)

2019 ◽  
Vol 30 ◽  
pp. v13 ◽  
Author(s):  
J. Garcia ◽  
F. Monjaret ◽  
F. Geiguer ◽  
J.-P. Aurel ◽  
A. Puisieux ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Circulating Tumor Cells ◽  
Single Cell Rna Sequencing

scholarly journals Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yu-Heng Cheng ◽  
Yu-Chih Chen ◽  
Eric Lin ◽  
Riley Brien ◽  
Seungwon Jung ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Circulating Tumor Cells ◽  
High Throughput ◽  
Single Cell Rna Sequencing

scholarly journals IMMU-27. SINGLE CELL RNA-SEQUENCING IDENTIFIES NOVEL BONE MARROW DERIVED MYELOID CELLS IN GLIOBLASTOMA ASSOCIATED WITH TUMOR AGGRESSION

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii110-ii110
Author(s):  
Christina Jackson ◽  
Christopher Cherry ◽  
Sadhana Bom ◽  
Hao Zhang ◽  
John Choi ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Metabolic Pathways ◽  
Myeloid Cells ◽  
Tumor Grade ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Two Populations

Abstract BACKGROUND Glioma associated myeloid cells (GAMs) can be induced to adopt an immunosuppressive phenotype that can lead to inhibition of anti-tumor responses in glioblastoma (GBM). Understanding the composition and phenotypes of GAMs is essential to modulating the myeloid compartment as a therapeutic adjunct to improve anti-tumor immune response. METHODS We performed single-cell RNA-sequencing (sc-RNAseq) of 435,400 myeloid and tumor cells to identify transcriptomic and phenotypic differences in GAMs across glioma grades. We further correlated the heterogeneity of the GAM landscape with tumor cell transcriptomics to investigate interactions between GAMs and tumor cells. RESULTS sc-RNAseq revealed a diverse landscape of myeloid-lineage cells in gliomas with an increase in preponderance of bone marrow derived myeloid cells (BMDMs) with increasing tumor grade. We identified two populations of BMDMs unique to GBMs; Mac-1and Mac-2. Mac-1 demonstrates upregulation of immature myeloid gene signature and altered metabolic pathways. Mac-2 is characterized by expression of scavenger receptor MARCO. Pseudotime and RNA velocity analysis revealed the ability of Mac-1 to transition and differentiate to Mac-2 and other GAM subtypes. We further found that the presence of these two populations of BMDMs are associated with the presence of tumor cells with stem cell and mesenchymal features. Bulk RNA-sequencing data demonstrates that gene signatures of these populations are associated with worse survival in GBM. CONCLUSION We used sc-RNAseq to identify a novel population of immature BMDMs that is associated with higher glioma grades. This population exhibited altered metabolic pathways and stem-like potentials to differentiate into other GAM populations including GAMs with upregulation of immunosuppressive pathways. Our results elucidate unique interactions between BMDMs and GBM tumor cells that potentially drives GBM progression and the more aggressive mesenchymal subtype. Our discovery of these novel BMDMs have implications in new therapeutic targets in improving the efficacy of immune-based therapies in GBM.

scholarly journals Single-cell RNA sequencing reveals heterogeneous tumor and immune cell populations in early-stage lung adenocarcinomas harboring EGFR mutations

Oncogene ◽  
2020 ◽  
Author(s):  
Di He ◽  
Di Wang ◽  
Ping Lu ◽  
Nan Yang ◽  
Zhigang Xue ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Early Stage ◽  
Cell Types ◽  
Egfr Mutations ◽  
Advanced Tumor ◽  
Single Cell Rna Sequencing

Abstract Lung adenocarcinoma (LUAD) harboring EGFR mutations prevails in Asian population. However, the inter-patient and intra-tumor heterogeneity has not been addressed at single-cell resolution. Here we performed single-cell RNA sequencing (scRNA-seq) of total 125,674 cells from seven stage-I/II LUAD samples harboring EGFR mutations and five tumor-adjacent lung tissues. We identified diverse cell types within the tumor microenvironment (TME) in which myeloid cells and T cells were the most abundant stromal cell types in tumors and adjacent lung tissues. Within tumors, accompanied by an increase in CD1C+ dendritic cells, the tumor-associated macrophages (TAMs) showed pro-tumoral functions without signature gene expression of defined M1 or M2 polarization. Tumor-infiltrating T cells mainly displayed exhausted and regulatory T-cell features. The adenocarcinoma cells can be categorized into different subtypes based on their gene expression signatures in distinct pathways such as hypoxia, glycolysis, cell metabolism, translation initiation, cell cycle, and antigen presentation. By performing pseudotime trajectory, we found that ELF3 was among the most upregulated genes in more advanced tumor cells. In response to secretion of inflammatory cytokines (e.g., IL1B) from immune infiltrates, ELF3 in tumor cells was upregulated to trigger the activation of PI3K/Akt/NF-κB pathway and elevated expression of proliferation and anti-apoptosis genes such as BCL2L1 and CCND1. Taken together, our study revealed substantial heterogeneity within early-stage LUAD harboring EGFR mutations, implicating complex interactions among tumor cells, stromal cells and immune infiltrates in the TME.

scholarly journals Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Daniel Wai-Hung Ho ◽  
Yu-Man Tsui ◽  
Lo-Kong Chan ◽  
Karen Man-Fong Sze ◽  
Xin Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Tumor Heterogeneity ◽  
Sequencing Analysis ◽  
T Cell Infiltration ◽  
Single Cell Rna Sequencing ◽  
Immune Oncology

AbstractInteraction between tumor cells and immune cells in the tumor microenvironment is important in cancer development. Immune cells interact with the tumor cells to shape this process. Here, we use single-cell RNA sequencing analysis to delineate the immune landscape and tumor heterogeneity in a cohort of patients with HBV-associated human hepatocellular carcinoma (HCC). We found that tumor-associated macrophages suppress tumor T cell infiltration and TIGIT-NECTIN2 interaction regulates the immunosuppressive environment. The cell state transition of immune cells towards a more immunosuppressive and exhaustive status exemplifies the overall cancer-promoting immunocellular landscape. Furthermore, the heterogeneity of global molecular profiles reveals co-existence of intra-tumoral and inter-tumoral heterogeneity, but is more apparent in the latter. This analysis of the immunosuppressive landscape and intercellular interactions provides mechanistic information for the design of efficacious immune-oncology treatments in hepatocellular carcinoma.

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