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yuan, t.

Publications and source records attributed to yuan, t..

2 recordsLinked to original sources

16S rRNA Survey Reveals the Potential of Oral Microbiota in Distinguishing Patients with Chronic Heart Failure from Healthy Controls

BackgroundOral microbiota can reflect physiological functions and pathological conditions in human body. Patients with chronic heart failure (CHF) exhibit distinct oral health status compared to healthy controls (HCs), which is attributed to the differences in dominant microbial communities present in the oral cavity. Up to date, there are few studies examined the association between CHF and dominant oral microbiota. To fill in this research gap, this study aimed to investigate the differences of oral microbiota between CHF patients and HCs, to identify valuable novel biomarkers for CHF. MethodsChronic heart failure patients and healthy volunteers were recruited. Oral microbiota samples were then collected using oral swabs, and 16S rRNA sequencing was employed to analyze the microbiota. Statistical analysis was conducted to identify key bacteria at multiple taxonomic levels in the oral microbiota samples from both the CHF patient and healthy control groups, with a focus on core genera to identify potential biomarkers and evaluate their diagnostic efficacy. ResultsThere were 60 CHF patients and 30 HCs were recruited, with 42 CHF patients with New York Heart Association (NYHA) functional class II-IV and 28 HCs were included in the final analysis. The alpha diversity was higher in HCs, while beta diversity was higher in CHF patients. The CHF patients showed significant differences from HCs at five gene (phylum, class, order, family and genus) levels by analyzing the relative richness of microbiota at different taxomal levels. Altogether 14 microbes could distinguish CHF patients from HCs, i.e., Abiotrophia, Butyrivibrio, Lactobacillus, Capnocytophaga and Neisseria which are more abundant in CHF patients, and Actinomyces, Anaerovorax, Eubacterium, Kingella, Mogibacterium, Peptococcus, Peptostreptococcus, Solobacterium and TM7_genus_incertae_sedis which are more abundant in HCs. Furthermore, the AUC of their combined diagnosis was 83.7% (95% confidential interval 74.1%-93.3%), which have high reliability for the diagnostic significance. In accordance to Spearmans correlation, Eubacterium, Solobacterium and Rhizobium were core genera and the abundance of Eubacterium and Solobacterium exhibited downward trends as NYHA class increases. ConclusionThis study revealed the dysbiosis of the oral microbiota in CHF patients and identified potential biomarkers for CHF diagnosis and management. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/669863v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@d60f6eorg.highwire.dtl.DTLVardef@18f17ceorg.highwire.dtl.DTLVardef@163f0daorg.highwire.dtl.DTLVardef@599bcd_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Ligand-independent c-Met activation by HHLA2 drives hepatocellular carcinoma and predicts c-MET inhibitor efficacy

The HGF/c-Met signaling pathway facilitates the initiation, progression, and metastasis of hepatocellular carcinoma (HCC). c-Met activation, however, is complex and not solely dependent on HGF, hindering targeted therapy development. This study identifies a critical oncogenic role for HHLA2, a B7 family member, in HCC and highlights its potential as a therapeutic target. We demonstrate that HHLA2 directly interacts with and activates c-Met through N-glycosylation, triggering sustained signaling and promoting aggressive HCC features. Mechanistically, we identified the pro-tumorigenic role of HHLA2 required downstream upregulation of MMP9 and VEGFA, both implicated in tumor progression. In multiple mouse models, HHLA2 overexpression accelerated tumor progression, metastasis, and reduced liver NK cell infiltration, all of which were reversed by c-Met inhibition. In a cohort of 176 HCC patients, HHLA2 expression strongly correlated with c-Met phosphorylation, advanced tumor stage, and poor prognosis. Importantly, HHLA2 expression predicted sensitivity to c-Met inhibitors in cell lines and patient-derived organoids and could be detected in patient serum, suggesting its potential as a prognostic biomarker. Collectively, our findings reveal an HHLA2-mediated mechanism of c-Met activation and provide a strong rationale for targeting the HHLA2-c-Met axis as a novel therapeutic strategy, with HHLA2 serving as a potential prognostic biomarker. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/622557v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@8b10dforg.highwire.dtl.DTLVardef@b43dorg.highwire.dtl.DTLVardef@394c4aorg.highwire.dtl.DTLVardef@1bfbc8c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗