TXNL4B regulates radioresistance by controlling the PRP3‐mediated alternative splicing of FANCI

Zhao, Jiang; Jing, Xiang; Xiao, Liang; He, Yongmei; Zhang, Le; Yin, Wen; Lei, Ridan; Nie, Yiming; Yang, Ling; Miszczyk, Justyna; Zhou, Ping‐Kun; Huang, Ruixue

doi:10.1002/mco2.258

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…We also identified several genome-wide significant genes on chromosome 16, such as TXNL4B , HPR , and HP . These genes play integral roles in modulating the core biological mechanisms, including cell cycle progression, oxidative balance maintenance, protein conformational dynamics and stability, which all exhibit profound interdependencies with the aging process 36,37 .Moreover, the MAGMA gene-set analysis unveiled the critical involvement of lipid metabolism, CYP2E1-mediated reactions, and liver-specific genes in metabolomic aging, providing valuable insights into the underlying molecular mechanisms and potential therapeutic targets pertinent to this process. The tissue-enrichment analysis further emphasizes the importance of liver in metabolomic aging.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneous metabolomic aging across the same age and prediction of health outcome

Jia,

Fan,

et al. 2024

Preprint

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Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, we leveraged metabolomic profiles of 239,291 UK Biobank participants for 10-year all-cause mortality prediction to generate and validate a new aging measure--MetaboAgeMort. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to conventional risk factors model improved the predictive ability of 10-year mortality. We identified 99 modifiable factors for MetaboAgeMort, where 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. Our study illuminates heterogeneous metabolomic aging across the same age, which provides avenues for developing anti-aging therapies and personalized interventions.

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Section: Discussionmentioning

confidence: 99%

Heterogeneous metabolomic aging across the same age and prediction of health outcome

Jia,

Fan,

et al. 2024

Preprint

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A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Jia,

Fan,

et al. 2024

Advanced Science

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Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non‐modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure—MetaboAgeMort—is developed using metabolomic profiles from 239,291 UK Biobank participants for 10‐year all‐cause mortality prediction. The MetaboAgeMort showed significant associations with all‐cause mortality, cause‐specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10‐year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue‐enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high‐risk individuals, developing anti‐aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

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High expression of SRSF1 facilitates osteosarcoma progression and unveils its potential mechanisms

Li,

Huang,

Zheng

et al. 2024

BMC Cancer

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Background SRSF1, a member of Serine/Arginine-Rich Splicing Factors (SRSFs), has been observed to significantly influence cancer progression. However, the precise role of SRSF1 in osteosarcoma (OS) remains unclear. This study aims to investigate the functions of SRSF1 and its underlying mechanism in OS. Methods SRSF1 expression level in OS was evaluated on the TCGA dataset, TAGET-OS database. qRT-PCR and Western blotting were employed to assess SRSF1 expression in human OS cell lines as well as the interfered ectopic expression states. The effect of SRSF1 on cell migration, invasion, proliferation, and apoptosis of OS cells were measured by transwell assay and flow cytometry. RNA sequence and bioinformatic analyses were conducted to elucidate the targeted genes, relevant biological pathways, and alternative splicing (AS) events regulated by SRSF1. Results SRSF1 expression was consistently upregulated in both OS samples and OS cell lines. Diminishing SRSF1 resulted in reduced proliferation, migration, and invasion and increased apoptosis in OS cells while overexpressing SRSF1 led to enhanced growth, migration, invasion, and decreased apoptosis. Mechanistically, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA) revealed that the biological functions of SRSF1 were closely associated with the dysregulation of the protein targeting processes, location of the cytosolic ribosome, extracellular matrix (ECM), and proteinaceous extracellular matrix, along with the PI3K-AKT pathway, Wnt pathway, and HIPPO pathway. Transcriptome analysis identified AS events modulated by SRSF1, especially (Skipped Exon) SE events and (Mutually exclusive Exons) MXE events, revealing potential roles of targeted molecules in mRNA surveillance, RNA degradation, and RNA transport during OS development. qRT-PCR confirmed that SRSF1 knockdown resulted in the occurrence of alternative splicing of SRRM2, DMKN, and SCAT1 in OS. Conclusions Our results highlight the oncogenic role of high SRSF1 expression in promoting OS progression, and further explore the potential mechanisms of action. The significant involvement of SRSF1 in OS development suggests its potential utility as a therapeutic target in OS.

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TXNL4B regulates radioresistance by controlling the PRP3‐mediated alternative splicing of FANCI

Cited by 3 publications

References 51 publications

Heterogeneous metabolomic aging across the same age and prediction of health outcome

Heterogeneous metabolomic aging across the same age and prediction of health outcome

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

High expression of SRSF1 facilitates osteosarcoma progression and unveils its potential mechanisms

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