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Xu Chen

Publications and source records attributed to Xu Chen.

8 recordsLinked to original sources
PubMed2026

A fitness advantage from the pLVPK plasmid fuels the global spread of a carbapenem-resistant hypervirulent Klebsiella pneumoniae high-risk clone: ST11-KL64.

BACKGROUND: The global emergence of carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKP), particularly the ST11-KL64 subclone acquiring pLVPK-like virulence plasmids, represents a critical public health threat. This study investigates the epidemiological dominance and molecular mechanisms underlying ST11-KL64's fitness advantage over KL47 variants. METHODS: We performed comparative genomic analysis on 43,722 K. pneumoniae genomes (2011-2022) from 112 countries, focusing on ST11-CRKP strains. Capsular typing (KL64 vs. KL47), virulence gene profiling (aerobactin, RmpADC), and plasmid stability analysis were conducted using Kleborate, RAST, and PlasmidFinder. Plasmid-chromosome interactions were characterized through hybrid assembly approaches. RESULTS: ST11-KL64 demonstrated rapid expansion post-2016, surpassing KL47 as China's dominant CRKP subtype (40.5% vs. 28.9%), with regional predominance in Zhejiang (62.3%) and Sichuan (58.7%) provinces. Notably, 94.8% of KL64 strains maintained intact pLVPK plasmids with high aerobactin carriage (60.5%), while KL47 exhibited frequent plasmid fusion (58.8% with IncFIB[pNDM-Mar]) or chromosomal integration (41.4%), resulting in lower virulence potential (27.3% aerobactin+). Genomic analysis revealed KL64's superior plasmid stability (71.2% gene retention vs. KL47's 43.6%) and clinical correlation with severe outcomes (OR = 2.34, 95%CI 1.67-3.28). CONCLUSION: The ST11-KL64 subclone's epidemiological success stems from stable pLVPK plasmid maintenance, enabling simultaneous carbapenem resistance and hypervirulence. These findings highlight the urgent need for genomic surveillance targeting plasmid-mediated virulence in CRKP outbreaks, particularly in critical care settings where horizontal gene transfer may accelerate strain evolution.

Klebsiella pneumonia↗
PubMed2026

Dietary Polyphenol Acteoside-Related Molecular Signatures in Clear Cell Renal Cell Carcinoma: Multi-Omics Profiling and Functional Validation of IMPDH1.

Clear cell renal cell carcinoma (ccRCC) is characterized by substantial metabolic and molecular heterogeneity, but the disease-relevant programs associated with acteoside, a dietary polyphenol, remain poorly understood. We integrated predicted acteoside targets with bulk, single-cell, and spatial transcriptomic data from ccRCC and combined molecular subtyping with cross-cohort machine-learning analysis. Acteoside-related signatures were preferentially enriched in malignant compartments and increased with tumor grade and stage. Consensus clustering identified two molecular subtypes with distinct biological and clinical features. C1 was associated with immune activation, metabolic activity, and more favorable survival, whereas C2 showed greater genomic instability, reduced renal epithelial differentiation, and poorer outcomes. We further benchmarked multiple machine-learning strategies and established a 10-gene prognostic model that retained predictive performance across independent cohorts, with IMPDH1 emerging as the strongest risk-associated feature. Functional experiments confirmed the biological relevance of IMPDH1: its knockdown suppressed ccRCC cell proliferation, DNA synthesis, colony formation, and migration, whereas overexpression produced the opposite effects. Together, these findings indicate that acteoside-related molecular signatures capture clinically relevant heterogeneity in ccRCC and provide a framework for linking dietary-polyphenol-related molecular space with tumor biology. The identification and functional validation of IMPDH1 further highlight its potential importance in ccRCC progression.

IMPDH1↗
PubMed2026

Pathomics-based machine learning models for predicting METTL5 expression and prognosis in lung adenocarcinoma.

BACKGROUND: METTL5, an N6-methyladenosine (m6A) RNA methyltransferase, has been implicated in tumor progression, but its prognostic value and non-invasive prediction in lung adenocarcinoma (LUAD) remain unclear. This study aimed to develop a pathomics-based machine learning model to predict METTL5 expression from histopathological images and evaluate its prognostic significance in LUAD. METHODS: A total of 327 LUAD patients from The Cancer Genome Atlas (TCGA) with matched hematoxylin and eosin (H&E) slides, transcriptomic, and clinical data were included and randomly divided into training and validation sets (7:3). Quantitative histopathological features were extracted using PyRadiomics. Feature selection was performed via maximum relevance minimum redundancy (mRMR) and recursive feature elimination (RFE), followed by construction of a Gradient Boosting Machine (GBM) model. A pathomics score (PS) was generated to assess prognostic relevance. Survival analyses, gene set variation analysis (GSVA), tumor mutational burden (TMB), immune infiltration analysis, and in vitro functional assays were conducted. RESULTS: METTL5 overexpression was independently associated with poor overall survival [hazard ratio (HR) =1.637, P=0.007]. The model achieved good predictive performance [area under the curve (AUC) =0.847 in the training set and 0.752 in the validation set]. High PS was significantly associated with worse survival and remained an independent prognostic factor (HR =1.563, P=0.03). Elevated PS correlated with altered metabolic pathways, increased TMB, and immune microenvironment changes. METTL5 knockdown reduced proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in A549 cells. CONCLUSIONS: The pathomics-based model accurately predicts METTL5 expression and provides prognostic stratification in LUAD, supporting its potential as a practical imaging-derived biomarker.

Methyltransferase-like 5↗
PubMed2026

Resveratrol Attenuates Gemcitabine Resistance in Hepatocellular Carcinoma Cells by Inhibiting Thymidylate Synthase.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Gemcitabine (Gem) is a commonly used drug against HCC, but its efficacy is limited by the development of resistance. Resveratrol (Res), a natural polyphenol with antitumor activity, may reverse Gem resistance in HCC, although the mechanism remains unclear. METHODS: The effects of Res on the proliferation, apoptosis, cell cycle, and invasion of Hep3B and HuH-7 cells were assessed via cell counting kit-8 (CCK-8), clonogenic, flow cytometry, and Transwell assays, respectively. Potential Res targets were predicted by network pharmacology, and markers of HCC prognosis were identified from the cancer genome atlas (TCGA) data. The interaction between Res and thymidylate synthase (TYMS) was validated by molecular docking and dynamics simulation. A Gem-resistant HuH-7 cell line (HuH-7/GR) was established, and when these cells were treated with Res combined with Gem, the effect on Gem sensitivity was detected by CCK-8 assay, clonogenic assay, and flow cytometry. Finally, a subcutaneous nude mouse model of HCC was used to evaluate the in vivo effects of Res combined with Gem. RESULTS: Res inhibited HCC cell proliferation, induced apoptosis and G2/M arrest, and suppressed invasion in a concentration-dependent manner. Network pharmacology and TCGA analysis identified TYMS as an important target gene for Res. TYMS was highly expressed in HCC tissues and correlated with poor prognosis. Res treatment reduced TYMS expression, while molecular docking and simulation showed stable binding of Res to TYMS. TYMS levels were elevated in HuH-7/GR resistant cells. Res combined with Gem was found to reverse drug resistance, inhibit proliferation and colony formation, and induce apoptosis. The Res + Gem combination group showed the smallest tumor volume in the in vivo model. CONCLUSION: By attenuating Gem resistance through TYMS inhibition, Res holds promise as a clinically viable adjunct to Gem-based chemotherapy, offering a potential strategy to improve outcomes in HCC patients.

Resveratrol↗
PubMed2026

Miniature and versatile genome regulation TnpB-ωRNA toolkits facilitate cancer immunotherapy.

CRISPR‒Cas systems represent powerful tools for genome regulation. However, the large size of Cas proteins limits their efficient delivery via an adeno-associated virus (AAV), thereby restricting their clinical translation. Here, we engineer the IS200/IS605 transposon-encoded nuclease TnpB, along with its ωRNA scaffold, to create an enhanced TnpB system, which serves as a compact toolkit for gene activation, genome editing, and base editing. The gene activator enTnpBa increases expression by 2889-fold with a minimized 93 nt ωRNA and robustly activates endogenous genes in mammalian cells. We develop a single-AAV-based regimen for immune activation (AAV-ImmunAct) that delivers enTnpBa to activate CXCL9, IL-15, and IFN-γ. AAV-ImmunAct effectively enhances T cell migration and activation, increases killing of cancer cell lines and patient-derived organoids, and synergizes with anti-PD-1 therapy in humanized mice. Here, we establish enTnpB as a compact and versatile platform for genome regulation and a promising tool for cancer immunotherapy.

Humans↗
PubMed2026

TRIM49 Deficiency Stabilizes a Galectin-3/EGR1 Transcriptional Complex That Drives Invasiveness of Gastric Adenocarcinoma.

UNLABELLED: Tissue invasion is an initiating step of the cancer metastatic cascade. Unraveling the mechanisms underlying intracellular signaling pathway rewiring that activates downstream transcriptional machinery to drive invasiveness could help identify improved strategies to prevent and treat metastasis. Through an unbiased genome-wide CRISPR screen in a mouse model of gastric adenocarcinoma (GAC), an E3 ubiquitin ligase, tripartite motif-containing protein 49 (TRIM49), was identified as a potent suppressor of cancer invasiveness. In two thirds of GAC, TRIM49 expression was downregulated in invading cancer cells, in which TRIM49 deficiency correlated with deeper tumor infiltration and lymph node metastasis and was indicative of shorter overall patient survival. In multiple orthotopic GAC mouse models, TRIM49-deficient cancer cells were highly infiltrative, leading to multiorgan metastasis. Mechanistically, galectin-3, a putative regulator of cancer invasion, was stabilized in TRIM49-deficient cancer, largely because of the failure to undergo TRIM49-mediated polyubiquitination and proteasomal degradation. Consequently, galectin-3 assembled a complex with EGR1, thereby regulating transcriptional activities of a proinvasive gene module. As the galectin-3/EGR1 complex acted as a key node relaying proinvasive signaling, its disruption using GB1107, an oral galectin-3 inhibitor, suppressed tissue infiltration and metastasis of patient-derived xenografts. Taken together, a proinvasive galectin-3/EGR1 transcriptional complex was exploited by TRIM49-deficient GAC to fuel tissue invasion, representing an Achilles' heel that is potentially targetable to prevent metastasis. SIGNIFICANCE: A proinvasion galectin-3/EGR1 transcriptional complex is a therapeutic vulnerability in the highly invasive TRIM49-deficient gastric adenocarcinoma, which can be disrupted by the oral galectin-3 inhibitor GB1107 to prevent cancer spreading.

Stomach Neoplasms↗
PubMed2025

The GSA Family in 2025: A Broadened Sharing Platform for Multi-omics and Multimodal Data.

The Genome Sequence Archive family (GSA family) provides a comprehensive suite of database resources for archiving, retrieving, and sharing multi-omics data for the global academic and industrial communities. It currently comprises four distinct database members: the Genome Sequence Archive (GSA, https://ngdc.cncb.ac.cn/gsa), the Genome Sequence Archive for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human), the Open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix), and the Open Biomedical Imaging Archive (OBIA, https://ngdc.cncb.ac.cn/obia). Compared to its 2021 version, the GSA family has expanded significantly by introducing a new repository, the OBIA, and by comprehensively upgrading the existing databases. Notable enhancements to the existing members include broadening the range of accepted data types, strengthening quality control systems, improving the data retrieval system, and refining data-sharing management mechanisms.

Humans↗