Biology subjects

Kageyama, S.-I.

Publications and source records attributed to Kageyama, S.-I..

5 recordsLinked to original sources

bioRxiv2026

Catalog of gut microbiota alterations associated with anticancer therapies across multiple cancer types

BackgroundAnticancer therapies can alter the gut microbiota and may affect gut bacteria associated with treatment response. However, most longitudinal studies have focused on specific cancer types or individual treatment regimens, and systematic analyses across diverse cancer therapies remain limited. We analyzed longitudinal fecal microbiota profiles using 16S ribosomal RNA gene amplicon sequencing in the pan-cancer SCRUM-Japan MONSTAR-SCREEN cohort. We included 528 paired pre- and post-treatment fecal samples from 264 patients with advanced solid tumors across 18 cancer types and characterized the gut microbiota alterations associated with 22 anticancer drugs and related clinical factors. ResultsAcross the cohort, Shannon diversity did not significantly change after treatment (mean, 3.81 vs. 3.78; P = 0.58), and pre- and post-treatment samples exhibited no clear separation in ordination space. However, within-patient analysis detected a subtle but significant longitudinal microbiota shift (paired PERMANOVA, P = 0.0001), highlighting the importance of accounting for paired sampling. Clustering of genus-level compositional alterations revealed patient groups with distinct degrees of microbiota alteration, with the largest shifts associated with antibiotic exposure, transition from normal stool to diarrhea, and specific treatment regimens. Multivariable regression analysis of 22 anticancer drugs identified drug-bacteria associations and demonstrated that drugs with similar mechanisms of action, including epidermal growth factor receptor (EGFR) inhibitors and immune checkpoint inhibitors, exhibited similar microbiota change profiles. Targeted analyses highlighted concordant reductions in the Christensenellaceae R-7 group among EGFR inhibitor-exposed patients and depletion of Faecalibacterium among immune checkpoint inhibitor-exposed patients. ConclusionsThis study provides a cross-cancer catalog of microbiota alterations associated with anticancer therapies and highlights therapy-related shifts in the gut ecosystem, including patterns shared by drugs with similar mechanisms of action.

microbiology↗

bioRxiv2026

Single-cell spatial multiomics identifies POSTN+ CAFs mediating chemoradiotherapy resistance in rectal cancer

Neoadjuvant chemoradiotherapy (CRT) is standard for locally advanced rectal cancer (LARC), yet many patients retain residual disease. To resolve CRT-associated remodeling of the tumor microenvironment, we generated a multimodal spatial atlas from serial sections of paired pretreatment and post-treatment specimens from 24 patients using Xenium single-cell spatial transcriptomics and PhenoCycler multiplex proteomics, profiling 2.8 million cells; matched Visium HD datasets were generated on adjacent serial sections. Resistance was most strongly associated with fibroblast and myeloid programs adjacent to residual tumor. We identify a periostin (POSTN)-expressing CAF subset selectively enriched around residual tumor cells in non-responders, displaying a myofibroblastic phenotype and activating extracellular matrix remodeling, noncanonical WNT signaling, and immunosuppressive pathways. Tumor cells neighboring POSTN+ CAFs show consistent epithelial-mesenchymal transition signatures. Together, this atlas enables interrogation of CRT-induced spatial remodeling and nominates POSTN+ CAFs as key mediators and targets of CRT resistance, with direct relevance to CRT-based combination strategies.

cancer biology↗

bioRxiv2026

SpatialCompassV (SCOMV): De novo cell and gene spatial pattern classification and spatially differential gene identification

Spatial omics technologies enable the detection of gene expression together with spatial information in tissues. However, many existing analytical methods rely on prior biological knowledge or predefined annotations, while being limited in their ability to systematically characterize spatial distribution patterns. Here, we developed SpatialCompassV (SCOMV), a computational tool that clusters genes and cell types based on vectorial relationships between transcript locations and regions of interest, such as tumors. This tool quantifies the spatial positioning of genes and cells relative to a defined reference region by encoding their distance and direction into structured feature representations. SCOMV captured tumor-associated spatial patterns and enabled the unsupervised classification of genes into internal, peripheral, partially peripheral, and ubiquitous distribution types in breast and lung cancer spatial transcriptomic datasets of Xenium. Notably, SCOMV detected immune cell-related signatures that were preferentially localized in CAF-low regions. Extending the analysis to multiple regions of interest further enabled malignant state discrimination. Moreover, SCOMV identifies genes that differ not only in gene expression levels, but also in spatial distribution patterns, which we termed spatially differential genes (spatially DEGs).

bioinformatics↗

bioRxiv2024

Giant extrachromosomal element "Inocle" potentially expands the adaptive capacity of the human oral microbiome

Survival strategy of bacteria is expanded by extrachromosomal elements (ECEs). However, their genetic diversity and functional roles for adaptability are largely unknown. Here, we discovered a novel family of intracellular ECEs using 56 saliva samples by developing an efficient microbial DNA extraction method coupled with long-read metagenomics assembly. Even though this ECE family was not hitherto unidentified, our global prevalence analysis using 476 salivary metagenomic datasets elucidated that these ECEs reside in 74% of the population. These ECEs, which we named, "Inocles", are giant plasmid-like circular genomic elements of 395 kb in length, having Streptococcus as a host bacterium. Inocles encode a series of genes that contribute to intracellular stress tolerance, such as oxidative stress and DNA damage, and cell wall biosynthesis and modification involved in the interactions with oral epithelial cells. Moreover, Inocles exhibited significant positive correlations with immune cells and proteins responding to microbial infection in peripheral blood. Intriguingly, we examined and found their marked reductions among 68 patients of head and neck cancers and colorectal cancers, suggesting its potential usage for a novel biomarker of gastrointestinal cancers. Our results suggest that Inocles potentially boost the adaptive capacity of host bacteria against various stressors in the oral environment.

genomics↗

bioRxiv2024

Spatial domain analysis to estimate spatiotemporal pathological mechanisms in microenvironment with single-cell spatial omics data

Single-cell spatial omics analysis requires consideration of biological functions and mechanisms in a microenvironment. However, microenvironment analysis using bioinformatic methods is limited by the need to detect histological morphology. In this study, we developed SpatialKNife (SKNY), an image-processing-based toolkit that detects spatial domains that potentially reflect histology and extends these domains to the microenvironment. The SKNY algorithm identified tumour spatial domains from spatial transcriptomic data of breast cancer, followed by clustering of these domains, trajectory estimation, and spatial extension to the tumour microenvironment (TME). The results of the trajectory estimation were consistent with the known mechanisms of cancer progression. We observed endothelial cell and macrophage infiltration into the TME at mid-stage progression. Our results suggest that analysis using the spatial domain as a unit reflects pathological mechanisms in the TME. This approach may be applicable to the biological estimation of diverse microenvironments.

bioinformatics↗