Biology subjects

Fujikura, K.

Publications and source records attributed to Fujikura, K..

5 recordsLinked to original sources

bioRxiv2024

Genome-wide analysis of somatic non-coding mutation patterns and mitochondrial heteroplasmy in type B1 and B2 thymomas

IntroductionType B1 and B2 thymomas are lymphocyte-rich malignant tumors with few somatic mutations in protein-coding regions of the nuclear genome; nonetheless, non-coding regions remain uncharacterized. Here, we developed a rigorous tumor isolation method from lymphocyte-rich thymoma tissues and identified somatic mutations in non-coding and mitochondrial DNA. MethodsCD205+CD45- pure tumor cells were isolated from fresh-frozen tissues using DEPArray system. Deep whole-genome sequencing was performed, and recurrent somatic alterations in coding, non-coding, and mitochondria regions were systemically identified by computational framework. The mutations were classified according to gene function, cis-regulatory element, and mutational signature. ResultsThe total number of somatic mutations was approximately 80 times higher in non-coding regions than in coding regions in type B1-2 thymomas (1,671.3 vs. 21.1 per case). Coding mutations were identified in epigenetic regulators, DNA repair genes, and some other genes. Nevertheless, 40% of cases exhibited fewer than four mutations in coding regions. A systematic non-coding analysis identified a total of 405.0 mutations per case on cis-regulatory elements, and detected six recurrent mutations: one interferon regulatory factor (IRF8), two E3 ubiquitin ligases (UBR2 and RNF213), and three intergenic regions. Mitochondrial heteroplasmy was observed in 90% of cases, with a significant proportion of mutations located in D-loop region. The single-base substitution pattern was signature 12. ConclusionsNumerous non-coding mutations and mitochondrial heteroplasmy were detected in type B1 and B2 thymomas. Given the paucity of coding mutations observed in this disease entity, disruption of the non-coding landscape and mitochondrial heteroplasmic shift may be the primary cause of thymoma.

genomics↗

bioRxiv2023

Three-dimensional assessments are necessary to determine the true spatial tissue composition of diseased tissues

Methods for spatially resolved cellular profiling using thinly cut sections have enabled in-depth quantitative tissue mapping to study inter-sample and intra-sample differences in normal human anatomy and disease onset and progression. These methods often profile extremely limited regions, which may impact the evaluation of heterogeneity due to tissue sub-sampling. Here, we applied CODA, a deep learning-based tissue mapping platform, to reconstruct the three-dimensional (3D) microanatomy of grossly normal and cancer-containing human pancreas biospecimens obtained from individuals who underwent pancreatic resection. To compare inter-and intra-sample heterogeneity, we assessed bulk and spatially resolved tissue composition in a cohort of two-dimensional (2D) whole slide images (WSIs) and a cohort of thick slabs of pancreas tissue that were digitally reconstructed in 3D from serial sections. To demonstrate the marked under sampling of 2D assessments, we simulated the number of WSIs and tissue microarrays (TMAs) necessary to represent the compositional heterogeneity of 3D data within 10% error to reveal that tens of WSIs and hundreds of TMA cores are sometimes needed. We show that spatial correlation of different pancreatic structures decay significantly within a span of microns, demonstrating that 2D histological sections may not be representative of their neighboring tissues. In sum, we demonstrate that 3D assessments are necessary to accurately assess tissue composition in normal and abnormal specimens and in order to accurately determine neoplastic content. These results emphasize the importance of intra-sample heterogeneity in tissue mapping efforts.

cancer biology↗

bioRxiv2022

Spatial transcriptomics of FFPE pancreatic intraepithelial neoplasias reveals cellular and molecular alterations of progression to pancreatic ductal carcinoma

Spatial transcriptomics (ST) is a powerful new approach to characterize the cellular and molecular architecture of the tumor microenvironment. Previous single-cell RNA-sequencing (scRNA-seq) studies of pancreatic ductal adenocarcinoma (PDAC) have revealed a complex immunosuppressive environment characterized by numerous cancer associated fibroblasts (CAFs) subtypes that contributes to poor outcomes. Nonetheless, the evolutionary processes yielding that microenvironment remain unknown. Pancreatic intraepithelial neoplasia (PanIN) is a premalignant lesion with potential to develop into PDAC, but the formalin-fixed and paraffin-embedded (FFPE) specimens required for PanIN diagnosis preclude scRNA-seq profiling. We developed a new experimental pipeline for FFPE ST analysis of PanINs that preserves clinical specimens for diagnosis. We further developed novel multi-omics analysis methods for threefold integration of imaging, ST, and scRNA-seq data to analyze the premalignant microenvironment. The integration of ST and imaging enables automated cell type annotation of ST spots at a single-cell resolution, enabling spot selection and deconvolution for unique cellular components of the tumor microenvironment (TME). Overall, this approach demonstrates that PanINs are surrounded by the same subtypes of CAFs present in invasive PDACs, and that the PanIN lesions are predominantly of the classical PDAC subtype. Moreover, this new experimental and computational protocol for ST analysis suggests a biological model in which CAF-PanIN interactions promote inflammatory signaling in neoplastic cells which transitions to proliferative signaling as PanINs progress to PDAC. SummaryPancreatic intraepithelial neoplasia (PanINs) are pre-malignant lesions that progress into pancreatic ductal adenocarcinoma (PDAC). Recent advances in single-cell technologies have allowed for detailed insights into the molecular and cellular processes of PDAC. However, human PanINs are stored as formalin-fixed and paraffin-embedded (FFPE) specimens limiting similar profiling of human carcinogenesis. Here, we describe a new analysis protocol that enables spatial transcriptomics (ST) analysis of PanINs while preserving the FFPE blocks required for clinical assessment. The matched H&E imaging for the ST data enables novel machine learning approaches to automate cell type annotations at a single-cell resolution and isolate neoplastic regions on the tissue. Transcriptional profiles of these annotated cells enable further refinement of imaging-based cellular annotations, showing that PanINs are predominatly of the classical subtype and surrounded by PDAC cancer associated fibroblast (CAF) subtypes. Applying transfer learning to integrate ST PanIN data with PDAC scRNA-seq data enables the analysis of cellular and molecular progression from PanINs to PDAC. This analysis identified a transition between inflammatory signaling induced by CAFs and proliferative signaling in PanIN cells as they become invasive cancers. Altogether, this integration of imaging, ST, and scRNA-seq data provides an experimental and computational approach for the analysis of cancer development and progression.

cancer biology↗

bioRxiv2020

Massive occurrence of benthic plastic debris at the abyssal seafloor beneath the Kuroshio Extension, the North West Pacific

The deep-sea is considered to be an ultimate sink for marine plastic debris. The abyssal (3500-6500 m) covers the bulk of the deep ocean floor yet little is known about the extent of plastic debris on the abyssal seafloor. We undertook a quantitative assessment of debris presents on the abyssal seafloor (5700-5800 m depth) beneath the Kuroshio Extension current system in the Northwest Pacific, which is one of the major transit points for massive amounts of debris sourced from Asia that are entering the North Pacific Ocean. The dominant type of debris was single-use plastics-mainly bags and food packaging. The density of plastic debris (average 4561 items km-2) in the abyssal zone was the highest recorded for an abyssal plain, suggesting that the deep-sea basin of the Northwest Pacific is a significant reservoir of plastic debris.

ecology↗

bioRxiv2019

Bacterial diversity in deep-sea sediments under influence of asphalt seep at the Sao Paulo Plateau

Here we investigated the diversity of bacterial communities from deep-sea surface sediments under influence of asphalt seeps at the Sao Paulo Plateau using next-generation sequencing (NGS) method. Sampling was performed at North Sao Paulo Plateau using the human occupied vehicle Shinkai 6500 and her support vessel Yokosuka. The microbial diversity was studied at two surficial sediment layers (0-1 and 1-4 cm) of five samples collected in cores in water depths ranging from 2,456-2,728 m. Bacterial communities were studied through sequencing of 16S rRNA gene on the Ion Torrent platform and clustered in operational taxonomic units. We observed high diversity of bacterial sediment communities as previously described by other studies. When we considered community composition, the most abundant classes were Alphaprotebacteria (27.7%), Acidimicrobiia (20%), Gammaproteobacteria (11.3%) and Deltaproteobacteria (6.6%). Most abundant OTUs at family level were from two uncultured bacteria from Actinomarinales (5.95%) and Kiloniellaceae (3.17%). The unexpected high abundance of Alphaproteobacteria and Acidimicrobiia in our deep-sea microbial communities may be related to the presence of asphalt seep at North Sao Paulo Plateau, since these bacterial classes contain bacteria that possess the capability of metabolizing hydrocarbon compounds.

microbiology↗