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Biology subjects

Bono, H.

Publications and source records attributed to Bono, H..

2 recordsLinked to original sources

In renal cell carcinoma, cancerous phenotypes linked to hypoxia-inducible factors are insensitive to the volatile anesthetic isoflurane

The possibility that anesthesia during cancer surgery may affect cancer recurrence, metastasis, and patient prognosis has become one of the most important topics of interest in cancer treatment. For example, the volatile anesthetic isoflurane was reported in several studies to induce hypoxia-inducible factors, and thereby enhance malignant phenotypes in vitro. Indeed, these transcription factors are considered critical regulators of cancer-related hallmarks, including "sustained proliferative signaling, evasion of growth suppressors, resistance to cell death, replicative immortality, angiogenesis, invasion, and metastasis." This study aimed to investigate the impact of isoflurane on the growth and migration of derivatives of the renal cell line RCC4. We indicated that isoflurane treatment did not positively influence cancer cell phenotypes, and that hypoxia-inducible factors (HIFs) maintain hallmark cancer cell phenotypes including gene expressions signature, metabolism, cell proliferation and cell motility. The present results indicate that HIF activity is not influenced by the volatile anesthetic isoflurane.

cancer biology

Meta-analysis of hypoxic transcriptomes from public databases

Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs HIF-1 and HIF-2 to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

bioinformatics