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Fucoidans are senotherapeutics that enhance SIRT6-Dependent DNA repair

ABSTRACT: Aging is marked by the accumulation of senescent cells (SnCs), which contribute to tissue dysfunction and age-related diseases. Senotherapeutics, including senolytics which specifically induce lysis of SnCs and senomorphics, which suppress the senescence phenotype, represent promising therapeutic interventions for mitigating age- related pathologies and extending healthspan. Using a phenotypic-based senescent cell screening assay, we identified fucoidans, a class of sulfated polysaccharides derived from brown algae and seaweed, as novel senotherapeutics. In particular, fucoidan from Fucus vesiculosus (Fucoidan-FV) displayed potent senomorphic activity in different types of SnCs, reduced senescence in multiple tissues in aged mice, and extended healthspan in a mouse model of accelerated aging. Fucoidan-FV also enhanced the deacetylation and mono-ADP-ribosylation (mADPr) activity of SIRT6 and improved DNA repair and reduced senescence, in part, through SIRT6-dependent pathways. In addition, Fucoidan-FV downregulated genes associated with inflammation, Wnt signaling, and ECM remodeling pathways in SnCs and increased expression of genes involved with DNA repair. These findings support the translational potential of fucoidans as novel senotherapeutics that also are able to improve SIRT6-mediated DNA repair.

ORGANISM(S): Mus musculus

PROVIDER: GSE298234 | GEO | 2026/05/25

REPOSITORIES: GEO

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Project description:Cellular senescence is a primordial driver of tissue and organ aging, and the accumulation of senescent cells (SnCs) has been implicated in numerous age-related diseases. A major barrier to studying senescence is the rarity and heterogeneity of SnCs, which are not a uniform population but instead comprise diverse senotypes shaped by cell-of-origin and microenvironmental context. Such heterogeneity exceeds what classical senescence hallmarks can resolve at single-cell resolution, motivating the need for computational frameworks that can capture senotype-level diversity intrinsically. Here, we introduce DeepSAS, a deep graph representation learning framework that robustly identifies cell-type-specific SnCs and their senescence-associated genes (SnGs). DeepSAS incorporates a heterogeneous graph that integrates intracellular transcriptional states with intercellular communication cues, enabling the joint inference of senescent cells and senescence-linked genes through attention-based contrastive learning. Applied to public healthy eye and lung atlases, DeepSAS identified SnCs whose proportions positively correlate with aging. From in-house idiopathic pulmonary fibrosis (IPF) patient scRNA-seq data, DeepSAS detected 1,678 SnCs (out of 24,125 cells) and 263 SnGs across 26 cell types, including 43 SnGs that are uniquely associated with a single cell type. We generated high-resolution Xenium spatial transcriptomics data to further validate SnGs in IPF, revealing NFE2L2 as a SnG specifically enriched in CTHRC1+ fibroblasts. Notably, the ex vivo bleomycin-induced senescence in human precision-cut lung slice (hPCLS) samples similarly identified NFE2L2 as an SnG in CTHRC1+ fibroblasts, albeit with stronger transcriptional signals, suggesting mechanistic differences in senescence cells associated with chronic and acute injury. Overall, DeepSAS uncovers distinct senescence programs and infers cell-type-specific SnGs that are difficult to resolve using existing marker-based approaches. We believe it offers a generalizable and translationally relevant strategy for advancing senescence biology and therapeutic development.

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Fucoidans are senotherapeutics that enhance SIRT6-Dependent DNA repair

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