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Pan-Cancer Landscape of the Novel Oxygen Sensor ADO and Its Potential Role in Hepatocellular Carcinoma

J Hepatocell Carcinoma. 2026 Sep 24;13:637010. doi: 10.2147/JHC.S637010. eCollection 2026.

ABSTRACT

BACKGROUND: Hypoxia is a key driver of tumor progression across cancers, yet oxygen-sensing mechanisms beyond HIFs remain underexplored. 2-Aminoethanethiol dioxygenase (ADO) has recently been identified as an oxygen sensor, but its role in malignancy is poorly defined. We conducted a pan-cancer analysis of ADO with a special focus on hepatocellular carcinoma (HCC), to assess its oncogenic significance and clinical potential.

METHODS: A multi-omics pan-cancer analysis of ADO expression and survival was performed using TCGA and GTEx, with validation in HCC across ICGC, GEO, and CNHPP proteomic cohorts. Correlations with genetic, epigenetic, immune, and pathways were evaluated. Drug sensitivity was predicted. Functional validation was conducted in HCC cells through proliferation, colony formation, Western blotting, and xenograft assays.

RESULTS: ADO was aberrantly expressed across cancers and showed cancer type-specific survival associations. Integrative analyses revealed links with tumor mutation burden, microsatellite instability, chromatin regulator methylation, RNA modification, proliferative signaling (G2M checkpoint, MYC, TGF-Ξ²), an immunosuppressive microenvironment, and negative correlations with ROS-responsive genes. In HCC, ADO was consistently overexpressed, associated with advanced stage, poor differentiation, residual disease, and unfavorable survival across independent cohorts. ADO-high HCC showed reduced predicted responsiveness to checkpoint blockade but increased sensitivity to sorafenib and fluorouracil. Experimentally, ADO overexpression activated ERK signaling, upregulated CD276 and HMGB1, and promoted HCC cell proliferation, while ADO depletion suppressed tumor growth in vitro and in vivo, reversible upon re-expression.

CONCLUSION: ADO plays oncogenic and immunomodulatory roles in HCC, and may serve as a potential prognostic biomarker and therapeutic target in liver cancer.

PMID:42812529 | PMC:PMC13620309 | DOI:10.2147/JHC.S637010

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Multi-omics integrated analysis to explore the molecular mechanisms of Xinkai Kujiang formula in treating gastric intestinal metaplasia in rats

Front Pharmacol. 2026 Aug 26;17:1881703. doi: 10.3389/fphar.2026.1881703. eCollection 2026.

ABSTRACT

BACKGROUND: Gastric intestinal metaplasia (GIM) is a typical precancerous lesion of gastric cancer (PLGC). Previous studies have demonstrated that Xinkai Kujiang formula can effectively alleviate GIM, but its underlying mechanism remains largely unclear.

METHODS: The GIM rat model was established using 2% sodium salicylate and 20 mmol/L sodium deoxycholate, and then the rats were treated with Banxia Xiexin Decoction (BXD) and Xinkai Kujiang Decoction (XKD) for 4 weeks. Multi-omics analyses including 16 S ribosomal RNA gene sequencing, transcriptomics, single-cell RNA sequencing, network pharmacology, and component identification were performed to explore the therapeutic mechanisms of Xinkai Kujiang formula on GIM.

RESULTS: In the model rats, severe gastric mucosal atrophy was observed, characterized by disordered glands and goblet cells. Following intervention with BXD and XKD, gastric mucosal thickness was restored, glandular structures became regularly arranged, and the number of metaplastic goblet cells markedly decreased. Microbiota profiling of gastric mucosa revealed significant enrichment of Lactobacillus and Enterococcus in the model group. These abundances were reduced in the BXD group, and short-chain fatty acid-producing bacteria such as Alistipes and Lachnospira were enriched. In the intestine, opportunistic pathogens like Streptococcus and Enterococcus were enriched in the model group, whereas Corynebacterium and Bifidobacterium were enriched in the XKD group. Transcriptomic analysis presented that BXD upregulated innate immune-related genes in the gastric mucosa, and single-cell RNA sequencing (scRNA-Seq) showed that XKD alleviated GIM by inhibiting the VEGF and HIF-1Ξ± pathways, reducing angiogenesis, suppressing inflammatory infiltration, and regulating energy metabolism.

CONCLUSION: BXD and XKD improve gastrointestinal microbiota disorders and metabolic disorders, enhance gastric mucosal immunity, and inhibit the VEGF and HIF-1Ξ± pathway. Collectively, these multi-omics data provide novel insights into the therapeutic mechanisms of Xinkai Kujiang formula for GIM.

PMID:42718732 | PMC:PMC13553361 | DOI:10.3389/fphar.2026.1881703

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NBR1-Mediated Autophagic Degradation of YTHDF1 Curtails <em>FDX1</em> Translation to Drive Concurrent Multikinase Inhibitor Resistance and Cuproptosis Tolerance

Cancer Commun (Lond). 2026 Sep 11;46:0048. doi: 10.34133/cancomm.0048. eCollection 2026.

ABSTRACT

Background: Cancer cells frequently acquire adaptive resistance to targeted therapies; however, strategies capable of concurrently overcoming treatment tolerance and reactivating cell death pathways are currently lacking. Here, we investigated the dual role of ferredoxin 1 (FDX1) in modulating both multikinase inhibitor (MKI) sensitivity and cuproptosis susceptibility in hepatocellular carcinoma (HCC), and sought to develop a therapeutic approach for reversing resistance. Methods: HCC models, both in vitro and in vivo, were employed to investigate the role of FDX1 in MKI resistance and cuproptosis evasion. Polysome profiling, SunTag translation reporters, CRISPR-Cas9 mutagenesis, and mass spectrometry were employed to delineate the underlying mechanisms. A codelivery nanoliposome system was engineered and tested in orthotopic HCC models. Results: Prolonged exposure to MKIs led to the down-regulation of FDX1 protein levels, resulting in MKI resistance and cuproptosis tolerance in HCC both in vitro and in vivo. Mechanistically, we found that MKIs inactivated protein kinase B (PKB, also known as AKT)-mechanistic target of rapamycin (mTOR) signaling, thereby suppressing the SET and MYND domain-containing protein 2 (SMYD2)-mediated methylation of YTH domain family protein 1 (YTHDF1) at lysine 515 (K515). Hypomethylated YTHDF1 was degraded via next to BRCA1 gene 1 protein (NBR1)-dependent autophagy, leading to the repression of N6-methyladenosine modification-dependent translation of FDX1 mRNA. FDX1 deficiency drove MKI resistance by reactivating AKT survival signaling while impairing cuproptosis through reduced divalent copper ions (Cu2+) to monovalent copper ions (Cu+) conversion and the loss of protein lipoylation. Additionally, restoring FDX1 expression through NBR1 knockdown or YTHDF1 overexpression overcame MKI resistance and resensitized HCC cells to cuproptosis. Finally, a nanoliposomal system, super cuproptosis detonator liposome, designed for the codelivery of NBR1 small interfering RNA, a copper ionophore, and sorafenib restored FDX1-dependent cuproptosis and exhibited marked anti-HCC efficacy, suppressing HCC growth in vivo. Conclusions: MKIs suppressed SMYD2-mediated YTHDF1 methylation at K515 via the inactivation of AKT-mTOR signaling. This led to the inhibition of FDX1 translation, resulting in AKT signaling reactivation and protein lipoylation impairment, effects that contributed to both MKI resistance and cuproptosis tolerance in HCC. Overcoming MKI resistance and resensitizing cells to cuproptosis by targeting NBR1-mediated YTHDF1 degradation using a nanoliposomal codelivery system represents a promising strategy for HCC treatment.

PMID:42729649 | PMC:PMC13562797 | DOI:10.34133/cancomm.0048

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Can Heterogeneous Language Models Be Fused?

arXiv:2604.01674v1 Announce Type: new Abstract: Model merging aims to integrate multiple expert models into a single model that inherits their complementary strengths without incurring the inference-time cost of ensembling. Recent progress has shown that merging can be highly effective when all source models are \emph{homogeneous}, i.e., derived from the same pretrained backbone and therefore share aligned parameter coordinates or compatible task vectors. Yet this assumption is increasingly unrealistic in open model ecosystems, where useful experts are often built on different families such as Llama, Qwen, and Mistral. In such \emph{heterogeneous} settings, direct weight-space fusion becomes ill-posed due to architectural mismatch, latent basis misalignment, and amplified cross-source conflict. We address this problem with \texttt{HeteroFusion} for heterogeneous language model fusion, which consists of two key components: topology-based alignment that transfers knowledge across heterogeneous backbones by matching functional module structures instead of raw tensor coordinates, and conflict-aware denoising that suppresses incompatible or noisy transfer signals during fusion. We further provide analytical justification showing that preserving the target adapter basis while predicting structured updates leads to a stable and well-conditioned transfer process. Across heterogeneous transfer, multi-source fusion, noisy-source robustness, and cross-family generalization settings, \texttt{HeteroFusion} consistently outperforms strong merging, fusion, and ensemble baselines.
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PsychAgent: An Experience-Driven Lifelong Learning Agent for Self-Evolving Psychological Counselor

arXiv:2604.00931v2 Announce Type: replace Abstract: Existing methods for AI psychological counselors predominantly rely on supervised fine-tuning using static dialogue datasets. However, this contrasts with human experts, who continuously refine their proficiency through clinical practice and accumulated experience. To bridge this gap, we propose an Experience-Driven Lifelong Learning Agent (\texttt{PsychAgent}) for psychological counseling. First, we establish a Memory-Augmented Planning Engine tailored for longitudinal multi-session interactions, which ensures therapeutic continuity through persistent memory and strategic planning. Second, to support self-evolution, we design a Skill Evolution Engine that extracts new practice-grounded skills from historical counseling trajectories. Finally, we introduce a Reinforced Internalization Engine that integrates the evolved skills into the model via rejection fine-tuning, aiming to improve performance across diverse scenarios. Comparative analysis shows that our approach achieves higher scores than strong general LLMs (e.g., GPT-5.4, Gemini-3) and domain-specific baselines across all reported evaluation dimensions. These results suggest that lifelong learning can improve the consistency and overall quality of multi-session counseling responses.
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Mirror-enhanced 4Pi-SMLM with one objective enables isotropic nanoscale imaging

Nature Biotechnology, Published online: 31 March 2026; doi:10.1038/s41587-026-03083-7

Single-molecule 4Pi microscopy is simplified and made accessible by using a single objective.
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