Substantial progress has been made in cancer biology and treatment in recent years, but the clinical outcome of patients with renal cell carcinoma (RCC) remains unsatisfactory. The tumor microenvironment (TME) is a potential target. By analyzing single-cell RNA sequencing (sc-RNAseq) data from six RCC tumor samples, this study identified 11 different cell types in the RCC cellular microenvironment, indicating a high degree of intratumoral heterogeneity. Through re-dimensionality reduction clustering of epithelial cells, neutrophils, macrophages, and T cells, we deeply reveal differences in the RCC tumor microenvironment. By analyzing differentially expressed genes in normal epithelial cells and malignant epithelial cells, we identify RNASET2 and GATM as potential prognostic biomarkers in RCC. In addition, by transcriptional factor analysis, we found significant differences in the expression of GZMK-CD8 T cell and B cell transcription factors between cancer tissues and normal tissues. By cell correlation analysis, we found significant correlations between neutrophils and macrophages and between IL7R-CD4 T cells and T regulatory (Treg) cells in RCC, which may be involved in the formation of immune TMEs. By cell developmental trajectory analysis, we showed that macrophages may be derived from neutrophils, whereas Treg cells may be derived from IL7R-CD4 T cells. By cell communication analysis, we found a clear interaction between macrophages and endothelial cells, neutrophils, and GZMK-CD8 T cells. In addition, we found that ADGRE5 signaling was mainly derived from mast cells and GZMK-CD8 T cells, and had a significant communication effect with neutrophils. The COLLAGEN signaling pathway is mainly derived from fibroblasts and has a significant communication effect with mast cells. Finally, we verified that RNASET2, which is highly expressed in epithelial cells, promotes proliferation and migration of RCC in vitro. RNASET2 is likely to be a potential target for renal cell carcinoma therapy. The results based on sc-RNAseq data analysis help to further elucidate the cellular microenvironment of RCC and provide help for cancer heterogeneity studies. This will help to provide more accurate personalized treatment for patients in clinical diagnosis.
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http://dx.doi.org/10.1007/s10142-023-01113-0 | DOI Listing |
Reprod Biol Endocrinol
January 2025
Department of Molecular and Developmental Medicine, Siena University, Siena, 53100, Italy.
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January 2025
Department of Surgery, Faculty of General of Medicine, Koya University, Koya, Kurdistan Region - F.R., KOY45, Iraq.
Background: During mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during spermatogenesis.
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Sci Rep
January 2025
Department of Pathology, Division of Microbiology, Faculty of Veterinary Medicine, Wroclaw University of Environmental and Life Sciences, 50-375, Wroclaw, Poland.
The process of viral entry into host cells is crucial for the establishment of infection and the determination of viral pathogenicity. A comprehensive understanding of entry pathways is fundamental for the development of novel therapeutic strategies. Standard techniques for investigating viral entry include confocal microscopy and flow cytometry, both of which provide complementary qualitative and quantitative data.
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January 2025
Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Clear cell renal cell carcinoma is a prevalent urological malignancy, imposing substantial burdens on both patients and society. In our study, we used bioinformatics methods to select four putative target genes associated with EMT and prognosis and developed a nomogram model which could accurately predicting 5-year patient survival rates. We further analyzed proteome and single-cell data and selected PLCG2 and TMEM38A for the following experiments.
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January 2025
Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA.
The aberrant vascular response associated with tendon injury results in circulating immune cell infiltration and a chronic inflammatory feedback loop leading to poor healing outcomes. Studying this dysregulated tendon repair response in human pathophysiology has been historically challenging due to the reliance on animal models. To address this, our group developed the human tendon-on-a-chip (hToC) to model cellular interactions in the injured tendon microenvironment; however, this model lacked the key element of physiological flow in the vascular compartment.
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