Publications by authors named "Ai Okada"

Programmed death-ligand 1 (PD-L1/CD274) structural variation (SV) disrupting the 3'-untranslated region has been highlighted as being associated with PD-L1 overexpression. In the present study, we evaluated lymphoma tissue samples to investigate the applicability of immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) for detecting the PD-L1 SV involving the 3'-untranslated region. In total, 1052 lymphoma samples were screened using IHC, and 99 IHC screening-positive samples were evaluated with FISH (non-Hodgkin lymphoma [NHL, n=58] and Hodgkin lymphoma [HL, n=41]).

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Genomic variants causing abnormal splicing play important roles in genetic disorders and cancer development. Among them, variants that cause the formation of novel splice-sites (splice-site creating variants, SSCVs) are particularly difficult to identify and often overlooked in genomic studies. Additionally, these SSCVs are frequently considered promising candidates for treatment with splice-switching antisense oligonucleotides (ASOs).

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The KEAP1-NRF2 system plays a crucial role in responding to oxidative and electrophilic stress. Its dysregulation can cause the overexpression of downstream genes, a known cancer hallmark. Understanding and detecting abnormal KEAP1-NRF2 activity is essential for understanding disease mechanisms and identifying therapeutic targets.

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Extranodal NK/T-cell lymphoma (ENKTCL) is an Epstein-Barr virus (EBV)-related neoplasm preferentially involving the upper aerodigestive tract. Here we show that NK-cell-specific Trp53 disruption in mice leads to the development of NK-cell lymphomas after long latency, which involve not only the hematopoietic system but also the salivary glands. Before tumor onset, Trp53 knockout causes extensive gene expression changes, resulting in immature NK-cell expansion, exclusively in the salivary glands.

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Extranodal NK/T-cell lymphoma (ENKTCL) is an Epstein-Barr virus (EBV)-related neoplasm with male dominance and a poor prognosis. A better understanding of the genetic alterations and their functional roles in ENKTCL could help improve patient stratification and treatments. In this study, we performed a comprehensive genetic analysis of 178 ENKTCL cases to delineate the landscape of mutations, copy number alterations (CNA), and structural variations, identifying 34 driver genes including six previously unappreciated ones, namely, HLA-B, HLA-C, ROBO1, CD58, POT1, and MAP2K1.

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Article Synopsis
  • Innovations in sequencing technology have improved the detection of genetic mutations related to inherited diseases, yet many patients remain undiagnosed due to limitations in current methods.
  • The study introduces a new computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) that enhances diagnostic accuracy by effectively identifying both single nucleotide variants and complex structural variations.
  • The TAS-LRS method not only discovered new mutations related to familial adenomatous polyposis and Lynch syndrome but also demonstrated the potential to analyze off-target reads for comprehensive genetic risk assessments.
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Patients with von Hippel-Lindau disease (vHL) are at risk of developing spatially and temporally multiple clear cell renal cell carcinomas (ccRCCs), which offers a valuable opportunity to analyze inter- and intra-tumor heterogeneity of genetic and immune profiles within the same patient. Here, we perform whole-exome and RNA sequencing, digital gene expression, and immunohistochemical analyses for 81 samples from 51 ccRCCs of 10 patients with vHL. Inherited ccRCCs are clonally independent and have less genomic alterations than sporadic ccRCCs.

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We present our novel software, nanomonsv, for detecting somatic structural variations (SVs) using tumor and matched control long-read sequencing data with a single-base resolution. The current version of nanomonsv includes two detection modules, Canonical SV module, and Single breakend SV module. Using tumor/control paired long-read sequencing data from three cancer and their matched lymphoblastoid lines, we demonstrate that Canonical SV module can identify somatic SVs that can be captured by short-read technologies with higher precision and recall than existing methods.

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Article Synopsis
  • - This study focuses on identifying genomic variants that disrupt gene function through abnormal splicing, particularly intron retention, using only transcriptome sequencing data due to the lack of combined genomic and transcriptomic datasets.
  • - The researchers developed a new methodology that evaluated 230,988 transcriptome sequencing data and identified 27,049 intron retention associated variants (IRAVs), 3,000 of which are potentially linked to diseases like cancer and other genetic disorders.
  • - Their in-silico framework shows the potential for automated discovery of medical insights from large publicly available sequencing data, with the collected IRAV information accessible through the database IRAVDB (https://iravdb.io/).
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Ferrets are animals that are known to be susceptible to influenza A virus (IAV) infection. To evaluate the risk of IAV transmission from diseased ferrets to humans, a survey was performed to detect specific antibodies against the H1, H3, H5, and H7 subtypes of IAV. Using enzyme-linked immunosorbent assay for hemagglutinin proteins, we found a high positive rate for the H1 (24.

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Rabbit hepatitis E virus (HEV) has been detected among rabbits and recently isolated from immunocompromised patients, suggesting zoonotic transmission. In this study, HEV infection among feral rabbits (Oryctolagus cuniculus) was assessed by detection of anti-HEV antibodies and HEV RNA. The prevalence of anti-HEV antibodies in sera was of 33 % (20/60) and HEV RNA was detected from only one of fecal swabs (1.

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Article Synopsis
  • * High-dimensional single-cell mass cytometry revealed a shift in T cell types from naïve to effector forms, indicating a T helper 1-polarized immune profile and an increase in effector regulatory T cells at relapse.
  • * RNA transcriptome analysis showed that immune-related pathways in leukemia cells are upregulated during relapse, suggesting interactions with the tumor environment and highlighting potential targets for future immunotherapy strategies.
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Adult T-cell leukemia/lymphoma (ATL) is an aggressive neoplasm immunophenotypically resembling regulatory T cells, associated with human T-cell leukemia virus type-1. Here, we performed whole-genome sequencing (WGS) of 150 ATL cases to reveal the overarching landscape of genetic alterations in ATL. We discovered frequent (33%) loss-of-function alterations preferentially targeting the CIC long isoform, which were overlooked by previous exome-centric studies of various cancer types.

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Mixed-lineage leukemia (MLL) gene rearrangements are among the most frequent chromosomal abnormalities in acute myeloid leukemia (AML). MLL fusion patterns are associated with the patient's prognosis; however, their relationship with driver mutations is unclear. We conducted sequence analyses of 338 genes in pediatric patients with MLL-rearranged (MLL-r) AML (n = 56; JPLSG AML-05 study) alongside data from the TARGET study's pediatric cohorts with MLL-r AML (n = 104), non-MLL-r AML (n = 581), and adult MLL-r AML (n = 81).

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In acute myeloid leukemia (AML), () rearrangements are among the most frequent chromosomal abnormalities; however, knowledge of the genetic landscape of -rearranged AML is limited. In this study, we performed whole-exome sequencing (n = 9) and targeted sequencing (n = 56) of samples from pediatric -rearranged AML patients enrolled in the Japanese Pediatric Leukemia/Lymphoma Study Group AML-05 study. Additionally, we analyzed 105 pediatric t(8;21) AML samples and 30 adult -rearranged AML samples.

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Although many driver mutations are thought to promote carcinogenesis via abnormal splicing, the landscape of splicing-associated variants (SAVs) remains unknown due to the complexity of splicing abnormalities. Here, we developed a statistical framework to systematically identify SAVs disrupting or newly creating splice site motifs and applied it to matched whole-exome and transcriptome sequencing data from 8976 samples across 31 cancer types, generating a catalog of 14,438 SAVs. Such a large collection of SAVs enabled us to characterize their genomic features, underlying mutational processes, and influence on cancer driver genes.

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