A5026986503- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Cancer Immunotherapy and Biomarkers
- T-cell and B-cell Immunology
- Genomics and Phylogenetic Studies
- Genetic factors in colorectal cancer
- Genomics and Rare Diseases
- Bioinformatics and Genomic Networks
- Evolution and Genetic Dynamics
- RNA modifications and cancer
- Genomics and Chromatin Dynamics
- Chromosomal and Genetic Variations
- Cancer-related molecular mechanisms research
- vaccines and immunoinformatics approaches
- RNA Research and Splicing
- Cell Image Analysis Techniques
- Immune Cell Function and Interaction
- Monoclonal and Polyclonal Antibodies Research
- Genomic variations and chromosomal abnormalities
- Gene Regulatory Network Analysis
- Immune cells in cancer
- Epigenetics and DNA Methylation
- Nutrition, Genetics, and Disease
- Immunotherapy and Immune Responses
- Microbial infections and disease research
Tokyo Medical and Dental University
2023-2024
Nagoya University
2022-2024
Institute of Science Tokyo
2024
Hokuto Hospital
2024
The University of Tokyo
2017-2022
National Center of Neurology and Psychiatry
2019-2021
Tokyo University of Science
2020
The cellular interactions in the tumor microenvironment of colorectal cancer (CRC) are poorly understood, hindering patient treatment. In current study, we investigate whether events occurring at invasion front particular importance for CRC treatment strategies. To this end, analyze tissues by combining spatial transcriptomics from patients with a public single-cell transcriptomic atlas to determine cell-cell front. We show that cells localized specifically These induce human leukocyte...
Advanced colorectal cancer harbors extensive intratumor heterogeneity shaped by neutral evolution; however, in precancerous lesions has been poorly studied. We perform multiregion whole-exome sequencing on ten early tumors, which contained adenoma and carcinoma situ. By comparing with data from advanced we show that the tumors accumulate a higher proportion of subclonal driver mutations than is highlighted KRAS APC. also demonstrate variant allele frequencies tend to be suggesting are...
Cell-cell interaction factors that facilitate the progression of adenoma to sporadic colorectal cancer (CRC) remain unclear, thereby hindering patient survival.
The tumor microenvironment can be classified into immunologically active "inflamed" tumors and inactive "non-inflamed" based on the infiltration of cytotoxic immune cells. Previous studies liver cancer have reported a superior prognosis for inflamed compared to non-inflamed tumors. However, is highly heterogeneous genetically, finer classification may improve our understanding its immunological diversity response therapy.We characterized gene signatures 234 primary cancers, mainly...
Abstract Cancers develop through somatic mutagenesis, however germline genetic variation can markedly contribute to tumorigenesis via diverse mechanisms. We discovered and phased 88 million single nucleotide variants, short insertions/deletions, large structural variants in whole genomes from 2,642 cancer patients, employed this genomic resource study determinants of mutagenesis across 39 types. Our analyses implicate damaging a variety predisposition DNA damage response genes with specific...
Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA data has been achieved in recent years, accurate from genome (WGS) remains a challenge due to the low depth. Furthermore, there is no method identify sequences of unknown HLA types not registered databases.We developed Bayesian model, called ALPHLARD, that collects reads potentially generated genes accurately determines pair for each HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1 at 3rd...
It is known that some mutant peptides, such as those resulting from missense mutations and frameshift insertions, can bind to the major histocompatibility complex be presented antitumor T cells on surface of a tumor cell. These peptides are termed neoantigen, it important understand this process for cancer immunotherapy. Here, we introduce an R package Neoantimon predict list potential neoantigens variety mutations, which include not only somatic point but deletions structural variants....
Abstract Immune reactions in the tumor microenvironment are an important hallmark of cancer, and emerging immune therapies have been proven effective against several types cancers. To investigate cancer genome-immune interactions role immunoediting or escape mechanisms development, we analyzed 2834 whole genome RNA sequencing datasets across 31 distinct with respect to key immunogenomic aspects provided comprehensive profiles pan-cancers. We found that selective copy number changes...
Somatic mutations in protein-coding regions can generate 'neoantigens' causing developing cancers to be eliminated by the immune system. Quantitative estimates of strength this counterselection phenomenon have been lacking. We quantified extent which somatic are depleted peptides that predicted displayed major histocompatibility complex (MHC) class I proteins. The depletion depended on expression level neoantigenic gene, and whether patient had one or two MHC-encoding alleles display...
The presence of some amino acid mutations in the sequence that determines a protein's structure can significantly affect 3D and its biological function. However, effects upon structural functional changes differ for each displaced acid, it is very difficult to predict these advance. Although computer simulations are effective at predicting conformational changes, they struggle determine whether mutation interest induces sufficient unless researcher specialist molecular calculations....
Detection of somatic mutations from tumor and matched normal sequencing data has become among the most important analysis methods in cancer research. Some existing mutation callers have focused on additional information, e.g. heterozygous single-nucleotide polymorphisms (SNPs) nearby candidates or overlapping paired-end read information. However, cannot take multiple information sources into account simultaneously. Existing Bayesian hierarchical model-based construct two generative models,...
1 Abstract RNA velocity estimation helps elucidate temporal changes in the single-cell transcriptome. However, current methodologies for inferring transcriptome dynamics ignore extrinsic factors, such as experimental conditions and neighboring cell. Here, we propose ExDyn—a deep generative model integrated with splicing kinetics estimating cell state dependent on factors. ExDyn enables counterfactual inference of under different conditions. Among can extract key features which have large...
Abstract Background Hyalinizing trabecular tumor (HTT) is an uncommon follicular cell-derived thyroid classified as a low-risk neoplasm by the World Health Organization Classification of Tumors Endocrine Organs, 5th edition. The PAX8-GLIS3 gene fusion reportedly pathognomonic genetic alteration HTT. Case presentation A 43-year-old Japanese female was incidentally discovered to have 8-mm, well-defined, hypoechoic mass in left lobe gland ultrasound examination. Contrast-enhanced computed...
Human leukocyte antigen (HLA) genes provide useful information on the relationship between cancer and immune system. Despite ease of obtaining these data through next-generation sequencing methods, interpretation relationships remains challenging owing to complexity HLA genes. To resolve this issue, we developed a Bayesian method, ALPHLARD-NT, identify germline somatic mutations as well genotypes from whole-exome (WES) whole-genome (WGS) data. ALPHLARD-NT showed 99.2% accuracy for WGS-based...
Macadamia is an iconic Australian plant, being the only international commercial food crop developed from indigenous flora. The preferred species for production of highly valued kernel integrifolia, which endemic to subtropical rainforests south-east Queensland. first domesticated macadamia probably a tree planted in Brisbane Botanical gardens by Walter Hill 1858. Crop development was led Hawaii following introductions late 19th century. Complete chloroplast (cp) genome sequencing, using...
1 Abstract Analyzing colocalization of single cells with heterogeneous molecular phenotypes is essential for understanding cell-cell interactions, cellular responses to external stimuli, and their biological functions in diseases tissues. However, high-throughput methods identifying spatial proximity at single-cell resolution are practically unavailable. Here, we introduce DeepCOLOR, a computational framework based on deep generative model that recovers inter-cellular networks cell by the...
Important roles of humoral tumor immunity are often pointed out; however, precise profiles dominant antigens and developmental mechanisms remain elusive. We systematically investigated the intratumor immunoglobulin clones found in human cancers. that approximately half corresponding were restricted to strongly densely negatively charged polymers, resulting simultaneous reactivities antibodies both sulfated glycosaminoglycans (dsGAGs) nucleic acids (NAs). These anti-dsGAG/NA matured expanded...
Abstract Immune reactions in the tumor micro-environment are one of cancer hallmarks and emerging immune therapies have been proven effective many types cancer. To investigate genome-immune interactions role immuno-editing or escape mechanisms development, we analyzed 2,834 whole genomes RNA-seq datasets across 31 distinct from PanCancer Analysis Whole Genomes (PCAWG) project with respect to key immuno-genomic aspects. We show that selective copy number changes immune-related genes could...
A bstract Messenger RNA splicing and degradation are critical for gene expression regulation, the abnormality of which leads to diseases. Previous methods estimating kinetic rates have limitations, assuming uniform across cells. We introduce DeepKINET, a deep generative model that estimates at single-cell resolution from scRNA-seq data. DeepKINET outperformed existing on simulated metabolic labeling datasets. Applied forebrain breast cancer data, it identified RNA-binding proteins...
We developed an unsupervised deep learning method to simultaneously perform deblurring, super-resolution, and segmentation of two-photon microscopy images. Two-photon is excellent technique for non-invasively observing biological tissues, but blurring during imaging has been a challenge. Conventional deblurring methods have limited performance are not suitable Moreover, that segmentation, which usually required in downstream analysis, developed. Therefore, this (TENET), we precisely modeled...
ABSTRACT Single-cell omics analysis has unveiled the heterogeneity of various cell types within tumors. However, no methodology currently reveals how this influences cancer patient survival at single-cell resolution. Here, we introduce scSurv, combining a Cox proportional hazards model with deep generative transcriptome, to estimate individual cellular contributions clinical outcomes. The accuracy scSurv was validated using both simulated and real datasets. This method identifies cells...