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Vasculogenic mimicry (VM) formed by aggressive tumor cells to mimic vasculogenic networks plays an important role in the tumor malignancy of HCC. However, the pathogenesis underlying VM is complex and has not been fully defined. m6A is a common mRNA modification and has many biological effects. However, the relationship between m6A and VM remains unclear. In this research, we found that m6A methyltransferase METTL3 in HCC tissues was positively correlated with VM. The m6A level of mRNA significantly increased in 3D cultured cells treated with VEGFa and was related to VM formation. Transcriptome sequencing analysis of 3D cultured cells with knockdown Mettl3 showed that the Hippo pathway was involved in m6A-mediated VM formation. Further mechanism research indicated that the m6A modification of YAP1 mRNA affected the translation of YAP1 mRNA. In conclusion, m6A methylation plays a key role in VM formation in HCC. METTL3 and YAP1 could be potential therapeutic targets via impairing VM formation in anti-metastatic strategies.

Background Although HLA-II molecules are classically associated with professional antigen-presenting cells, their expression by cancer cells has been recognized for several decades. It has been linked to immune infiltration, responses to immune checkpoint blockade, and clinical outcomes. However, the regulatory mechanisms governing tumor-associated HLA-II expression remain incompletely understood. Methods Genome-wide CRISPR-Cas9 screening was employed to identify candidate regulators of HLA-II expression in human melanoma cells. Key candidates were functionally validated through genetic and pharmacological perturbation approaches. Integrated transcriptomic and epigenomic analyses were conducted to characterize regulatory mechanisms. Retrospective clinical analyses were performed using publicly available The Cancer Genome Atlas (TCGA) datasets to assess associations with immune infiltration, immunotherapy response, and survival. Results We identified the aryl hydrocarbon receptor (AHR) and its dimerization partner ARNT as critical, FICZ-responsive, positive regulators of HLA-II expression. AHR-ARNT promoted transcription of CIITA through direct binding to its promoter II (pII), in the absence of IFN-γ signaling. Clinically, an AHR-ARNT loss-of-function signature correlated with reduced immune infiltration, poorer response to immunotherapy, and inferior survival across cancer types. Conclusions These findings reveal a previously unrecognized regulatory axis controlling HLA-II expression on cancer cells, suggesting that targeting the AHR-ARNT pathway may enhance tumor immunogenicity and improve immunotherapy efficacy.

Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. Here, we generate serial tissue sections from colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer samples for systematic evaluation. Using these uniformly processed samples, we generate spatial transcriptomics data across four high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profile proteins on tissue sections adjacent to all platforms using CODEX and perform single-cell RNA sequencing on the same samples. Leveraging manual nuclear segmentation and detailed annotations, we systematically assess each platform’s performance across capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and concordance with adjacent CODEX. The uniformly generated and processed multi-omics dataset could advance computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download. This study benchmarks four cutting-edge spatial transcriptomics platforms using human tumour tissues, performs multi-metric evaluation with multi-omics references, and presents the SPATCH portal for visualisation and download.

Background: Despite breakthroughs in treatment, ovarian cancer (OC) remains one of the most lethal gynecological malignancies, with an increasing age-standardized mortality rate. This underscores an urgent need for novel biomarkers and therapeutic targets. Although growth factor receptor-bound protein 7 (GRB7) is implicated in cell signaling and tumorigenesis, its expression pattern and clinical implications in OC remain poorly characterized. Methods: To systematically investigate GRB7’s expression in OC, our study utilized extensive datasets from TCGA, GTEx, CCLE, and GEO. The prognostic significance of GRB7 was evaluated by means of Kaplan–Meier and Cox regression analyses. Using a correlation analysis and gene set enrichment analysis, relationships between GRB7’s expression and gene networks, immune cell infiltration and immunotherapy response were investigated. In vitro experiments were conducted to confirm GRB7’s function in the biology of OC. Results: Compared to normal tissues, OC tissues exhibited a substantial upregulation of GRB7. Reduced overall survival, disease-specific survival, and disease-free interval were all connected with high GRB7 mRNA levels. The network study demonstrated that GRB7 is involved in pathways relevant to the course of OC and has a positive connection with several key driver genes. Notably, GRB7’s expression was linked to the infiltration of M2 macrophage and altered response to immunotherapy. Data from single-cell RNA sequencing data across multiple cancer types indicated GRB7’s predominant expression in malignant cells. Moreover, OC cells with GRB7 deletion showed decreased proliferation and migration, as well as increased susceptibility to T cell-mediated cytotoxicity. Conclusion: With respect to OC, our results validated GRB7 as a viable prognostic biomarker and a promising therapeutic target, providing information about its function in tumorigenesis and immune modulation. GRB7’s preferential expression in malignant cells highlights its significance in the biology of cancer and bolsters the possibility that it could be useful in enhancing the effectiveness of immunotherapy.

Rationale: Malignant ascites caused by cancer cells results in poor prognosis and short average survival time. No effective treatment is currently available for malignant ascites. In this study, the effects of lentinan (LNT)-functionalized selenium nanoparticles (Selene) on malignant ascites were evaluated. Furthermore, the mechanism of Selene targeting mitochondria of tumor cells were also investigated. Methods: Selene were synthesized and characterized by TEM, AFM and particle size analysis. The OVCAR-3 and EAC cells induced ascites models were used to evaluate the effects of Selene on malignant ascites. Proteomic analysis, immunofluorescence, TEM and ICP-MS were used to determine the location of Selene in tumor cells. Mitochondrial membrane potential, ROS, ATP content, and caspase-1/3 activity were detected to evaluate the effect of Selene on mitochondrial function and cell apoptosis. Immunofluorescence, Co-IP, pull-down, duolink, Western blot, and FPLC were used to investigate the pathway of Selene targeting mitochondria. Results: Selene could effectively inhibit ascites induced by OVCAR-3 and EAC cells. Selene was mainly located in the mitochondria of tumor cells and induced apoptosis of tumor cells. The LNT in Selene was involved in caveolae-mediated endocytosis through the interaction between toll-like receptor-4 (TLR4) and caveolin 1 (CAV1). Furthermore, the Selene in the endocytic vesicles could enter the mitochondria via the mitochondrial membrane fusion pathway, which was mediated by TLR4/TNF receptor associated factor 3 (TRAF3)/mitofusin-1 (MFN1) protein complex. Conclusion: Selene is a candidate anticancer drug for the treatment of malignant ascites. And TLR4/TRAF3/MFN1 may be a specific nano-drug delivery pathway that could target the mitochondria.

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Female genital tumors (FGTs), including ovarian, endometrial, and cervical cancers, pose a major global health challenge, yet their spatial and molecular determinants of progression and therapy resistance remain poorly understood. Here we present a large-scale integrative spatial and multi-omics atlas of FGTs, combining exome, transcriptome, methylome, and miRNA sequencing with high-resolution Visium HD spatial transcriptomics, profiling over 62 million cells from 100 tumors. We show that HPV-driven suppression of TGFβ signaling in cervical cancer disrupts myofibroblast (myCAF) formation and reshapes immune infiltration, while serous tumors exhibit extensive oncogene amplifications that activate MYC and PI3K pathways, linking chromosomal instability (CIN) to proliferative, immune-cold phenotypes. In high-grade serous ovarian cancer, we identify a previously unrecognized malignant domain, the Proliferating Core Desert (PCD) niche, defined by CIN-high epithelial enrichment, immune exclusion, stromal protection, and chemotherapy resistance, maintained through crosstalk with macrophages and fibroblasts. Finally, we develop POWER, a pathology foundation model that predicts PCD niche abundance from routine H&E slides, enabling robust stratification of prognosis and anti-angiogenic therapy response.

Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. To address this, we collected clinical samples from three cancer types - colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer - and generated serial tissue sections for systematic evaluation. Using these uniformly processed samples, we generated spatial transcriptomics data across five high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, Visium HD FF, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profiled proteins from adjacent tissue sections corresponding to all five platforms using CODEX and performed single-cell RNA sequencing on the same samples. Leveraging manual cell segmentation and detailed annotations, we systematically assessed each platform's performance across key metrics, including capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and transcript-protein alignment with adjacent CODEX. The uniformly generated, processed, and annotated multi-omics dataset is valuable for advancing computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download (http://spatch.pku-genomics.org/).Competing Interest StatementThe authors have declared no competing interest.