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KDM4A drives TGCT metastasis by inducing focal adhesion disassembly via STAT1-mediated <i>CCL3</i> transcriptional activation

Oncogene, Published online: 04 October 2026; doi:10.1038/s41388-026-04002-5

KDM4A drives TGCT metastasis by inducing focal adhesion disassembly via STAT1-mediated CCL3 transcriptional activation

FCGR2B (+) Macrophages as a Critical Node Linking Ferroptosis and Immunosuppression: A Multiomics Framework for Prognosis and Therapy in High-Grade Serous Ovarian Cancer

Hum Mutat. 2026 Apr 6;2026:8027584. doi: 10.1155/humu/8027584. eCollection 2026.

ABSTRACT

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is characterized by a complex tumor microenvironment and poor prognosis, yet the roles of specific tumor-associated macrophages (TAMs) subpopulations in driving disease progression remain elusive.

METHODS: This study evaluated the prognostic relevance of FCGR2B in HGSOC. Single-cell RNA sequencing identified FCGR2B + TAMs as a distinct macrophage subpopulation with unique transcriptional features. Integrative analyses combining single-cell and bulk differentially expressed genes, macrophage-associated modules, and ferroptosis-related gene sets identified 26 candidate prognostic genes, from which a four-gene signature (CRYAB, PLAUR, EREG, and C5AR1) was derived to construct the prognostic risk model. The model was validated in an independent cohort. Immune infiltration, single-cell trajectory, copy number variation, and drug-gene associations were analyzed to explore the molecular and therapeutic implications of risk stratification.

RESULTS: HGSOC patients classified as high risk exhibited poorer survival outcomes, increased infiltration of M2-like macrophages, elevated expression of immune checkpoints, and enrichment of immune- and ferroptosis-related pathways. Trajectory and copy number variation analyses revealed stage-specific gene expression patterns and amplification-associated regulation. Drug-gene association analyses further suggested that high-risk patients may be more responsive to targeted therapies and proteasome inhibitors, whereas low-risk patients may benefit from conventional chemotherapy.

CONCLUSION: FCGR2B + TAMs are closely linked to HGSOC progression, and the proposed prognostic model based on FCGR2B + TAMs provides predictive value and potential therapeutic insights for patient stratification.

PMID:41953398 | PMC:PMC13054137 | DOI:10.1155/humu/8027584

Agentization of Digital Assets for the Agentic Web: Concepts, Techniques, and Benchmark

arXiv:2604.04226v1 Announce Type: cross Abstract: Agentic Web, as a new paradigm that redefines the internet through autonomous, goal-driven interactions, plays an important role in group intelligence. As the foundational semantic primitives of the Agentic Web, digital assets encapsulate interactive web elements into agents, which expand the capacities and coverage of agents in agentic web. The lack of automated methodologies for agent generation limits the wider usage of digital assets and the advancement of the Agentic Web. In this paper, we first formalize these challenges by strictly defining the A2A-Agentization process, decomposing it into critical stages and identifying key technical hurdles on top of the A2A protocol. Based on this framework, we develop an Agentization Agent to agentize digital assets for the Agentic Web. To rigorously evaluate this capability, we propose A2A-Agentization Bench, the first benchmark explicitly designed to evaluate agentization quality in terms of fidelity and interoperability. Our experiments demonstrate that our approach effectively activates the functional capabilities of digital assets and enables interoperable A2A multi-agent collaboration. We believe this work will further facilitate scalable and standardized integration of digital assets into the Agentic Web ecosystem.

Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

Transl Oncol. 2026 Apr 3;67:102748. doi: 10.1016/j.tranon.2026.102748. Online ahead of print.

ABSTRACT

BACKGROUND: Epithelial ovarian cancer (EOC) encompasses five major histological subtypes with marked genetic, immunological, and clinical heterogeneity. While genome-wide association studies (GWAS) have identified subtype-specific risk loci, a critical gap remains in understanding how plasma proteins influence immune-cell traits and contribute to EOC pathogenesis.

METHODS: We integrated subtype-stratified GWAS data from two EOC cohorts with plasma proteomics and immune-cell traits to construct protein-immune-EOC regulatory landscapes using a three-stage Mendelian randomization framework. Single-cell RNA-seq and multiplex immunofluorescence were employed to delineate the cellular distribution and spatial context of causal proteins. Subsequent analyses characterized immune infiltration, macrophage polarization, and clinicopathological associations. Drug-gene correlations were used to identify potential therapeutic targets, and transcriptomic analyses were applied to delineate the underlying transcriptional landscape.

RESULTS: We identified 20 subtype-specific protein-immune-EOC regulatory axes, with FCGR2B emerging as a causal plasma protein in immune regulation and high-grade serous ovarian cancer (HGSOC) progression. FCGR2B was highly expressed in tumor-associated macrophages and was associated with an M2-like polarization phenotype. Functional characterization revealed that FCGR2B was associated with shorter progression-free survival and an immunosuppressive tumor microenvironment. Transcriptomic analyses revealed altered NF-κB signaling upon FCGR2B knockdown, and drug-response data suggested a potential association between high FCGR2B expression and sensitivity to NF-κB inhibitors.

CONCLUSIONS: These findings delineate subtype-specific genetically informed protein-immune regulatory landscapes in EOC and identify FCGR2B as a key immunoregulatory and prognostic biomarker in HGSOC, suggesting FCGR2B as a potential therapeutic vulnerability that warrants further investigation.

PMID:41934917 | DOI:10.1016/j.tranon.2026.102748

Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search

arXiv:2602.22983v3 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly used, their security risks have drawn increasing attention. Existing research reveals that LLMs are highly susceptible to jailbreak attacks, with effectiveness varying across language contexts. This paper investigates the role of classical Chinese in jailbreak attacks. Owing to its conciseness and obscurity, classical Chinese can partially bypass existing safety constraints, exposing notable vulnerabilities in LLMs. Based on this observation, this paper proposes a framework, CC-BOS, for the automatic generation of classical Chinese adversarial prompts based on multi-dimensional fruit fly optimization, facilitating efficient and automated jailbreak attacks in black-box settings. Prompts are encoded into eight policy dimensions-covering role, behavior, mechanism, metaphor, expression, knowledge, trigger pattern and context; and iteratively refined via smell search, visual search, and cauchy mutation. This design enables efficient exploration of the search space, thereby enhancing the effectiveness of black-box jailbreak attacks. To enhance readability and evaluation accuracy, we further design a classical Chinese to English translation module. Extensive experiments demonstrate that effectiveness of the proposed CC-BOS, consistently outperforming state-of-the-art jailbreak attack methods.
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