Dataset Information

A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing.

ABSTRACT: Gastric cancer (GC) development trends have identified multiple processes ranging from inflammation to carcinogenesis, however, key pathogenic mechanisms remain unclear. Tissue microenvironment (TME) cells are critical for the progression of malignant tumors. Here, we generated a dynamic transcriptome map of various TME cells during multi-disease stages using single-cell sequencing analysis. We observed a set of key transition markers related to TME cell carcinogenic evolution, and delineated landmark dynamic carcinogenic trajectories of these cells. Of these, macrophages, fibroblasts, and endothelial cells exerted considerable effects toward epithelial cells, suggesting these cells may be key TME factors promoting GC occurrence and development. Our results suggest a phenotypic convergence of different TME cell types toward tumor formation processes in GC. We believe our data would pave the way for early GC detection, diagnosis, and treatment therapies.

SUBMITTER: Yin H

PROVIDER: S-EPMC8566821 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing.

Yin Honghao H Guo Rui R Zhang Huanyu H Liu Songyi S Gong Yuehua Y Yuan Yuan Y

Frontiers in immunology 20211021

Gastric cancer (GC) development trends have identified multiple processes ranging from inflammation to carcinogenesis, however, key pathogenic mechanisms remain unclear. Tissue microenvironment (TME) cells are critical for the progression of malignant tumors. Here, we generated a dynamic transcriptome map of various TME cells during multi-disease stages using single-cell sequencing analysis. We observed a set of key transition markers related to TME cell carcinogenic evolution, and delineated la ...[more]

PMID: 34745098

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Project description:BackgroundPollination reduces flower longevity in many angiosperms by accelerating corolla senescence. This response requires hormone signaling between the floral organs and results in the degradation of macromolecules and organelles within the petals to allow for nutrient remobilization to developing seeds. To investigate early pollination-induced changes in petal gene expression, we utilized high-throughput sequencing to identify transcripts that were differentially expressed between corollas of pollinated Petunia × hybrida flowers and their unpollinated controls at 12, 18, and 24 hours after opening.ResultsIn total, close to 0.5 billion Illumina 101 bp reads were generated, de novo assembled, and annotated, resulting in an EST library of approximately 33 K genes. Over 4,700 unique, differentially expressed genes were identified using comparisons between the pollinated and unpollinated libraries followed by pairwise comparisons of pollinated libraries to unpollinated libraries from the same time point (i.e. 12-P/U, 18-P/U, and 24-P/U) in the Bioconductor R package DESeq2. Over 500 gene ontology terms were enriched. The response to auxin stimulus and response to 1-aminocyclopropane-1-carboxylic acid terms were enriched by 12 hours after pollination (hap). Using weighted gene correlation network analysis (WGCNA), three pollination-specific modules were identified. Module I had increased expression across pollinated corollas at 12, 18, and 24 h, and modules II and III had a peak of expression in pollinated corollas at 18 h. A total of 15 enriched KEGG pathways were identified. Many of the genes from these pathways were involved in metabolic processes or signaling. More than 300 differentially expressed transcription factors were identified.ConclusionsGene expression changes in corollas were detected within 12 hap, well before fertilization and corolla wilting or ethylene evolution. Significant changes in gene expression occurred at 18 hap, including the up-regulation of autophagy and down-regulation of ribosomal genes and genes involved in carbon fixation. This transcriptomic database will greatly expand the genetic resources available in petunia. Additionally, it will guide future research aimed at identifying the best targets for increasing flower longevity by delaying corolla senescence.

Dataset Information

A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing.

Publications

A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing.

Similar Datasets

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