A germ-line mutation of hMSH6 (also called GTBP) was found in a hereditary nonpolyposis colorectal cancer (HNPCC)-like patient in whom germ-line mutations of hMSH2, hMSH3, or hMLH1 had not been detected. The patient had rectal cancer and two colon adenomas at 62 years of age and a weak family history of gastrointestinal tumors, indicating atypical HNPCC. Somatic mutations of hMSH6 were observed in three colorectal tumors from the patient, indicating two-hit inactivation. Microsatellite instabilities at mononucleotide repeats were detected in all three tumors. These data suggest that hMSH6 is responsible for tumorigenesis in atypical HNPCC.
Peritoneal metastases are often found at surgery of pT4 gastric cancers, preventing R0 resection. In the event of successful R0 resection, distant metastases still occur in a sizeable proportion of patients. Estimation of the depth of invasion has a relatively low accuracy (57%-86%) compared with pathological findings. This study sought to develop a clinical score to distinguish between pathological stage T4 (pT4) and pT1-3 gastric cancer.Reviewing the data of 2,771 patients who had undergone gastrectomy at our hospital from January 1996-December 2016, we assessed demographic factors plus tumor markers, diameter, location, histology, and macroscopic type according to the fifth edition (2019) of the WHO classification. Significant factors on multivariate analysis were used to develop a pT4 gastric cancer depth prediction score (T4 score).Multivariate analysis revealed that the clinical factors associated with pT4 disease were CA19-9 elevation, tumor diameter ≥50 mm, poorly cohesive type adenocarcinoma, mucinous adenocarcinoma, and WHO macroscopic types 2-4. The T4 score was obtained by weighing these factors according to the β-coefficient. The optimum cutoff value of the T4 score was 4 points. A total of 79.4% of cases with a T4 score ≥4 points were stage pT4. A total of 93.9% of cases with a T4 score <4 points were stage pT1-3, with 91.1% sensitivity, 85.3% specificity, 79.4% positive predictive value, and 93.9% negative predictive value.T4 scoring can differentiate pT4 gastric cancer from pT1-3 gastric cancer.
iPath2.0 is a web-based tool (http://pathways.embl.de) for the visualization and analysis of cellular pathways. Its primary map summarizes the metabolism in biological systems as annotated to date. Nodes in the map correspond to various chemical compounds and edges represent series of enzymatic reactions. In two other maps, iPath2.0 provides an overview of secondary metabolite biosynthesis and a hand-picked selection of important regulatory pathways and other functional modules, allowing a more general overview of protein functions in a genome or metagenome. iPath2.0's main interface is an interactive Flash-based viewer, which allows users to easily navigate and explore the complex pathway maps. In addition to the default pre-computed overview maps, iPath offers several data mapping tools. Users can upload various types of data and completely customize all nodes and edges of iPath2.0's maps. These customized maps give users an intuitive overview of their own data, guiding the analysis of various genomics and metagenomics projects.
The roles of chemical compounds in biological systems are now systematically analyzed by high-throughput experimental technologies. To automate the processing and interpretation of large-scale data it is necessary to develop bioinformatics methods to extract information from the chemical structures of these small molecules by considering the interactions and reactions involving proteins and other biological macromolecules. Here we focus on metabolic compounds and present a knowledge-based approach for understanding reactivity and metabolic fate in enzyme-catalyzed reactions in a given organism or group. We first constructed the KEGG RPAIR database containing chemical structure alignments and structure transformation patterns, called RDM patterns, for 7091 reactant pairs (substrate-product pairs) in 5734 known enzyme-catalyzed reactions. A total of 2205 RDM patterns were then categorized based on the KEGG PATHWAY database. The majority of RDM patterns were uniquely or preferentially found in specific classes of pathways, although some RDM patterns, such as those involving phosphorylation, were ubiquitous. The xenobiotics biodegradation pathways contained the most distinct RDM patterns, and we developed a scheme for predicting bacterial biodegradation pathways given chemical structures of, for example, environmental compounds.
Abstract Aspergillus oryzae is an industrially useful species, of which various strains have been identified; however, their genetic relationships remain unclear. A. oryzae was previously thought to be asexual and unable to undergo crossbreeding. However, recent studies revealed the sexual reproduction of Aspergillus flavus, a species closely related to A. oryzae. To investigate potential sexual reproduction in A. oryzae and evolutionary history among A. oryzae and A. flavus strains, we assembled 82 draft genomes of A. oryzae strains used practically. The phylogenetic tree of concatenated genes confirmed that A. oryzae was monophyletic and nested in one of the clades of A. flavus but formed several clades with different genomic structures. Our results suggest that A. oryzae strains have undergone multiple inter-genomic recombination events between A. oryzae ancestors, although sexual recombination among domesticated species did not appear to have occurred during the domestication process, at least in the past few decades. Through inter- and intra-cladal comparative analysis, we found that evolutionary pressure induced by the domestication of A. oryzae appears to selectively cause non-synonymous and gap mutations in genes involved in fermentation characteristics, as well as intra-genomic rearrangements, with the conservation of industrially useful catalytic enzyme-encoding genes.
212 Background: Prostate cancer (PCa) is clinically associated with dietary habits such as high-fat diets. The gut microbiota is strongly influenced by dietary habits and is involved in the host immune response and metabolic pathways. Recently, the gut microbiota has been shown to influence a variety of diseases, including PCa. We have found that the gut microbiome and its metabolite, short-chain fatty acids (SCFA), promote cancer growth in PCa mouse models. To clarify the association between gut microbiota and PCa in humans, we conducted a study of PCa, gut microbiome, and lifestyle in Japan (PROMISE-JAPAN). In this study, we evaluated the gut microbiota profiles in PCa patients with a particular focus on differences between non-metastatic PCa (nmPCa) and metastatic PCa (mPCa). Methods: This multicenter, prospective, observational study enrolled 869 Japanese patients between 2020 and 2022. Eligibility criteria were men with suspected PCa who underwent prostate biopsy, and rectal swab samples were collected before prostate biopsy. Men who had taken antibiotics within 6 months before sample collection or whose previous antibiotic use was unknown were excluded. The gut microbiota composition was analyzed using 16S rRNA gene sequencing. The raw sequencing data was processed by the QIIME2 pipeline. The Mann-Whitney U tests were used to compare characteristics between groups. Results: A total of 723 participants were eligible for analysis, including 262 men without cancer and 461 men with PCa, including 56 men with mPCa. The composition of the gut microbiota differed significantly between the non-cancer and the PCa group, with PCa having more Lachnospiraceae, which produce SCFA. The mPCa group had a higher abundance of Ruminococcaceae (UCG-005 and NK4A214), which belong to the Firmicutes pylum, compared to the nmPCa group. The mPCa group had a lower abundance of Prevotella, which belongs to the Bacteroidota pylum, compared to the nmPCa group. In mPCa compared to nmPCa, 19 gut microbiota pathways were significantly altered. In particular, the androstenedione degradation pathway was significantly increased in the mPCa group (p=0.0287). Conclusions: The composition of the gut microbiota differed between the non-cancer, the nmPCa and the PCa group. The gut microbiome associated with androgen metabolism was more common in mPCa patients. Clinical trial information: UMIN000043489 .
We characterized the oral conditions, salivary microbiome, and metabolome after dental treatment by investigating the state after treatment completion and transition to self-care. Dental treatment improved oral health conditions, resulting in oral disease remission; however, the imbalanced state of the salivary microbiome continued even after remission. Although the results of this study are preliminary, owing to the small number of participants in each group when compared to larger cohort studies, they indicate that the risk of disease may remain higher than that of healthy participants, thereby demonstrating the importance of removing dental plaque containing disease-related bacteria using appropriate care even after treatment completion. We also identified bacterial species with relative abundances that differed from those of healthy participants even after remission of symptoms, which may indicate that the maturation of certain bacterial species must be controlled to improve the oral microbiome and reduce the risk of disease recurrence.
