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Daiki Taniyama

Publications and source records attributed to Daiki Taniyama.

2 recordsLinked to original sources

Peroxiredoxin 1 safeguards the nucleolar genome from oxidative damage.

Peroxiredoxin 1 (PRDX1) is a highly conserved, thiol-dependent peroxidase that rapidly scavenges reactive oxygen species to modulate redox signaling. PRDX1-null mice exhibited genomic instability, shortened life span, and accelerated tumorigenesis, including development of lymphomas, sarcomas, and carcinomas. Despite extensive characterization of these phenotypes, the molecular mechanism by which PRDX1 loss causes genomic instability remains poorly understood. Here, we show that PRDX1 deficiency alters nucleolar morphology, impairs RNA polymerase I (POL-I)-dependent transcription of pre-ribosomal RNAs, and triggers nucleolar genomic instability. This oxidative stress-induced nucleolar dysfunction promotes the stability of secondary DNA structures, such as RNA-DNA hybrids and G-quadruplex DNA, contributing to nucleolar genomic instability. We demonstrate that PRDX1 loss reduces nascent ribosomal RNA (rRNA) levels and impairs rRNA processing, further affecting ribosome biogenesis. Mechanistically, we established that PRDX1 loss triggers activation of the nucleolar DNA damage response characterized by activation of the DNA repair kinase ATM and elevated TCOF1 within the nucleolus. In addition, we observed recruitment of the MRE11-RAD50-NBS1 (MRN) complex subunit NBS1 to ribosomal DNA (rDNA) loci and this was further increased under oxidative stress. NBS1 accumulation correlates with the repression of rDNA transcription by POL-I, potentially delaying rRNA synthesis, and safeguarding the nucleolar genome from further oxidative damage. Collectively, these findings uncover a previously unrecognized, but critical role, for PRDX1 in maintaining nucleolar integrity and ribosomal biogenesis through redox-dependent regulation of rDNA transcription and processing machinery.

Oxidative Stress

SCLC TumorMiner: A genomics platform for small cell lung cancer precision oncology.

Small cell lung cancer (SCLC) is among the most aggressive malignancies. Unlike many other cancers, it is not represented in The Cancer Genome Atlas, and available datasets are fragmented across institutions, disease stages, and treatment settings. RNA sequencing provides a powerful and cost-effective approach, but the high dimensionality of transcriptomic data and the heterogeneity of patient cohorts pose significant challenges. To address such challenges, we developed SCLC TumorMiner (https://discover.nci.nih.gov/SclcTumorMinerCDB/), which includes 50 tumor samples from relapsed patients at the National Cancer Institute (NCI) and 154 samples from untreated patients at the University of Cologne and Tongji University. SCLC TumorMiner enables molecular classification, genomic pathway analyses, risk stratification, identification of predictive cell-surface biomarkers such as DLL3 or TROP2, and drug-response biomarkers such as SLFN11. SCLC TumorMiner illustrates profound differences between untreated and relapsed patient samples. Additionally, "MyPatient", one of SCLC TumorMiner's modules, is presented as a medical assistant application prototype.

SCLC