Bladder cancer is the tenth most common cancer worldwide and the sixth most common among men. However, research into representative tumor models for bladder cancer remains underdeveloped, limiting insights into tumor biology and drug development.

SpaFun is a novel, non-model-based method developed to address limitations in existing spatially variable gene detection techniques, particularly for large-scale spatially resolved transcriptomics datasets. These limitations include computational inefficiency, limited statistical power with increasing data size, and the inability to capture spatial heterogeneity and co-expression patterns among genes. Built on functional principal component analysis, SpaFun identifies domain-representative genes with significantly better computational efficiency and greater statistical power while accounting for spatial heterogeneity and co-expression patterns among genes. We applied SpaFun to three spatially resolved transcriptomics datasets and demonstrated that SpaFun outperformed state-of-the-art algorithms for identifying representative genes for tumor regions (e.g. DESeq, edgeR, and limma), as well as recently developed novel algorithms designed for spatial omics to identify the representative genes (e.g. SPARK and CSIDE). This highlights SpaFun's ability to accurately identify genes most representative of each spatial domain (e.g. tumor, immune, or stroma regions). By uncovering novel disease-relevant genes overlooked by existing algorithms, SpaFun could provide insights into new molecular mechanisms and propose innovative therapeutic strategies to improve patient outcomes.

Spatially resolved transcriptomic (ST) technologies offer transformative opportunities to chart gene expression landscapes within intact tissue architecture. Uncovering spatially discrete domains of biological function is essential for deciphering tissue heterogeneity, developmental processes, and disease mechanisms. Yet, the inherent noise, high dimensionality, and spatial sparsity of ST data present substantial challenges to the unsupervised delineation of these domains. We present SpatialDG, a dual-graph self-supervised contrastive learning framework for ST. SpatialDG combines graph neural networks with self-supervised contrastive learning to learn informative and discriminative spot representations by maximizing the agreement between local (node) and global (graph) embeddings and leveraging spatial adjacency to enhance representation learning. Specifically, SpatialDG constructs both a gene expression similarity graph and a spatial adjacency graph, integrating them via a dual-view contrastive architecture that aligns molecular and spatial information, while a zero-inflated negative binomial reconstruction loss accounts for the count-based and sparse nature of gene expression data. SpatialDG achieves significant gains over state-of-the-art algorithms in both healthy and cancer datasets, demonstrating robust generalization across diverse ST landscapes. In conclusion, SpatialDG efficiently unravels biologically meaningful domains from spatial and genetic signals, providing a powerful and generalizable tool to mine tissue architecture in ST datasets.

Angiogenesis, which is the formation of new blood vessels from existing vasculature, exhibits a pivotal role in breast cancer progression and promotes metastasis. This complex biological process is influenced by the dynamic balance of pro- and anti-angiogenic factors within the tumor microenvironment, such as vascular endothelial growth factor, fibroblast growth factors, and angiopoietins. Targeted therapeutic strategies have been developed to interfere with angiogenic signaling, aiming to normalize or inhibit the tumor vasculature. In recent years, miRNAs have arisen as crucial post-transcriptional regulators of gene expression implicated in angiogenic homeostasis. These microRNAs can function as either promoters or suppressors of angiogenesis by targeting mRNAs that encode angiogenic factors or other signaling molecules. Deregulated expressions of these miRNAs in BC are associated with perturbed angiogenesis, tumor progression, and therapeutic resistance. This review presents a thorough overview of the molecular processes controlling angiogenesis in BC and highlights the emerging roles of angioregulatory miRNAs. The article also discusses the therapeutic potential of targeting miRNAs to modulate tumor angiogenesis, providing novel insights for the development of miRNA-based diagnostics and therapeutics in BC management.

Germline sequencing is increasingly integrated into pediatric oncology, yet data on adolescents' experiences with genetic testing remain limited.

Pharmacovigilance has revealed an alarming correlation between certain medications and a higher risk of cancer. In this narrative review, included research from 2020 to 2025, along with a few seminal older studies, so that it provides a clear picture of which drugs actually set off cancer and mechanisms involved at the molecular level. An extensive literature review of the subject was designed on PubMed, Embase, Scopus, and Web of Science using systematic search. Search words and phrases included: "Carcinogenic drugs," "drug-induced cancer," "medication-induced carcinogenesis," "immunosuppressant cancer risk," "hormone therapy and cancer," "chemotherapy-induced secondary malignancies," and names of relevant drugs.

SWI/SNF chromatin remodeling complexes are perturbed in 20% of all cancers and in several developmental disorders, yet the mechanisms by which these mutations dysregulate transcription and drive disease are poorly understood. To both elucidate these mechanisms and identify vulnerabilities caused by these mutations, we leverage genome-wide CRISPR-Cas9 screening in hundreds of cancer cell lines and identify the chromatin reader protein PHIP as a specific dependency in cancers with broadly disrupted SWI/SNF function. Mechanistically, we reveal that PHIP cooperates with SWI/SNF to facilitate transcriptional activation by ubiquitinating and suppressing subunits of the repressive Nucleosome Remodeling and Deacetylase (NuRD) complex. We demonstrate that loss of SWI/SNF results in NuRD complexes accumulating at promoters where they would otherwise cause widespread transcriptional silencing if not antagonized by PHIP. Collectively, we identify PHIP as a regulator of the interplay between distinct chromatin regulators that function in development and disease and as a targetable vulnerability in cancers with broad SWI/SNF inactivation.

Chemotherapy resistance remains a critical bottleneck limiting its clinical efficacy in small cell lung cancer (SCLC), with its core mechanisms and targeted intervention strategies urgently requiring breakthroughs. Our study revealed that the BMX (bone marrow tyrosine kinase on chromosome X)-E2F1 (E2F transcription factor 1) axis is a pivotal regulator of chemoresistance in SCLC. Synchronous upregulation of phosphorylated BMX (Tyr566) and E2F1 was observed in SCLC tissues and cells. Mechanistically, BMX stabilized E2F1 via the ERK1/2 (extracellular signal-regulated kinase 1/2)-Cyclin D1/CDK4/6 (cyclin-dependent kinase 4/6) signaling axis, phosphorylating E2F1 at Ser332/337 and inhibiting its degradation via the ubiquitin-proteasome pathway. Inhibition or knockdown of BMX reduced E2F1 stability, promoting its degradation and reversing chemoresistance. E2F1 knockdown decreased the expression of genes associated with cell cycle regulation, migration, invasion, and DNA repair, further sensitizing chemoresistant SCLC cells to cisplatin. We also discovered IHMT-15137, a potent and selective BMX inhibitor. In vitro studies using SCLC patient-derived cells (PDCs)/patient-derived organoids (PDOs) and chemoresistant cell lines revealed that IHMT-15137, combined with cisplatin, synergistically induced cell cycle arrest, apoptosis, and DNA damage while suppressing cell migration and invasion. In vivo xenograft models demonstrated that the combination significantly inhibited tumor growth without causing significant toxicity. Our findings reveal the molecular mechanisms of SCLC chemoresistance and suggest potential therapeutic strategies targeting the BMX-E2F1 axis to overcome this challenge.

Resistance to lenvatinib remains a major barrier in the treatment of advanced hepatocellular carcinoma (HCC), underscoring the urgent need to elucidate the underlying mechanisms and identify actionable therapeutic targets. In this study, we identified a neurosecretory factor derived from HCC cells, Nerve Growth Factor (NGF), as a critical mediator of lenvatinib resistance. Utilizing an innovative in vivo-in vitro cross-circulated strategy, we established a phenotypically stable lenvatinib-resistant HCC cell line (LenR-cells). Through proteomic screening of conditioned media and subsequent functional validation, we demonstrated that NGF secretion progressively increases with the acquisition of resistance. Mechanistically, we uncovered that the SRPK1-SRSF1 axis drives enhanced NGF production by regulating alternative splicing of its precursor transcript, specifically promoting the expression of a shorter, translationally efficient isoform (proNGF-B). Elevated NGF subsequently activates the non-canonical MAPK pathway (MEK5-ERK5) via its high-affinity receptor TrkA, thereby sustaining tumor cell viability and proliferation under sustained tyrosine kinase inhibitor pressure. Critically, pharmacological co-targeting of TrkA with the clinically approved inhibitor larotrectinib restored lenvatinib sensitivity in both patient-derived organoids and xenograft models, producing marked synergistic anti-tumor effects without evidence of exacerbated toxicity. Clinical analyses of two independent patient cohorts further confirmed that elevated NGF expression is significantly associated with poor response to lenvatinib, shorter recurrence-free survival, and worse overall survival. Our findings unveil a critical and previously underappreciated role for tumor-derived NGF in orchestrating adaptive signaling through a precise post-transcriptional regulatory circuit and propose a readily translatable, biomarker-guided combination strategy to overcome lenvatinib resistance in HCC.

Perineural invasion (PNI), a prominent pathological feature of pancreatic ductal adenocarcinoma (PDAC), is closely associated with poor prognosis. Clarifying its mechanism is therefore critical for developing new therapies. Recent research has focused on the crosstalk between tumors and Schwann cells (SCs), particularly the role of SC dedifferentiation in facilitating PNI. In this study, by integrating RNA-seq, spatial transcriptomics, and single-cell analysis of clinical samples, we identified significant enrichment of dedifferentiated SCs and upregulation of key markers (p75NTR, SOX2, and c-Jun) in PNI regions. Moreover, PTGES was more highly expressed in the central region of the PNI than in the other regions of the PNI. Coculture experiments revealed that PANC-1 and BxPC-3 cells enhanced SC dedifferentiation, and this process facilitated pancreatic cancer cell malignancy. Furthermore, PTGES upregulation in the coculture system mediated prostaglandin E2 (PGE2) synthesis. Functional experiments revealed that PGE₂ drove morphological alterations in SCs-characterized by bipolar stretching-and elevated the expression of dedifferentiation markers, including p75NTR, c-Jun, SOX2, and GDNF. In the 3D coculture model, treatment with a PTGES inhibitor (CAY10526), siPTGES or PTGES-KO impaired the directional migration and neurite outgrowth of SCs toward PDAC cells. Mechanistically, PGE₂-stimulated SCs secrete elevated levels of LIF and ADAMTS-1, factors that promote extracellular matrix degradation and neural remodeling to facilitate tumor invasion. In summary, we delineate a novel paracrine axis in which PDAC-derived PGE₂ drives SC dedifferentiation and the production of proinvasive factors (LIF and ADAMTS-1), collectively establishing a microenvironment conducive to PNI. Our findings suggest that the PTGES-SC axis is a promising therapeutic target for inhibiting PNI in PDAC.

Accumulating evidence shows that bacteria influence cancer homeostasis, yet the effects of tumor‑associated microbes and their products remain largely unexplored. We previously reported that P. aeruginosa-cancer crosstalk suppresses tumors via the bacterial cupredoxin azurin, and we developed an azurin‑derived peptide that was tested in clinical trials. Building on our previous studies, we studied tumor-resident bacteria for novel therapeutics and targets. Photosynthetic bacteria from the phylum Chloroflexota, including a member of the class Chloroflexia, identified in tumors, carry the cupredoxin auracyanin gene. Based on the structural and chemical characteristics of auracyanin, we designed a novel cell-penetrating peptide, aurB. Plant chloroplasts are thought to have evolved from a bacterial endosymbiont, and both chloroplasts and mitochondria possess shared proteins essential for ATP-dependent energy production, indicating that these bacterial-derived proteins may influence mitochondrial function. Consistent with this model, we demonstrated that aurB, a peptide from cupredoxin auracyanin B, localized at mitochondria, blocked energy production by targeting ATP synthase in prostate cancer cells, thereby significantly inhibiting tumor growth. More strikingly, combination treatment with aurB and radiation therapy significantly inhibited tumor growth in a tibial bone metastasis model. Moreover, the number of metastatic lesions in the lungs was also significantly lower upon aurB treatment. Multiplex RNA-expression profiling revealed that the inhibition of ATP production by aurB increased the efficacy of radiation therapy by modulating multiple pathways involving HIF-1α. Our findings indicate that electron transfer proteins could represent an important source of promising novel peptide-based agents that target the aberrantly activated mitochondrial energy system in cancer.

Gastric synovial sarcoma (GSS) is an exceptionally rare mesenchymal malignancy, with only 51 cases reported. We present a case of a man in his 50s with dyspeptic symptoms and epigastric pain. Gastroscopy revealed an ulcerous tumour below the gastro-oesophageal junction. Histology, immunohistochemistry and molecular analysis confirmed SS18::SSX1 fusion, diagnostic of synovial sarcoma. The patient underwent successful robot-assisted partial gastric resection with negative margins. No recurrence was noted at 6-month follow-up. This case underscores the diagnostic challenge of GSS, the critical role of molecular techniques and the efficacy of minimally invasive surgical management.

One of the most prevalent oral cancers, oral squamous cell carcinoma (OSCC), is distinguished by its rapid growth, invasiveness, and high metastatic potential. Green AgNPs are important because they can reduce systemic toxicity by inducing oxidative stress, cytotoxicity, and apoptosis in cancer cells. The goal of this study was to use saponins as natural stabilizers to create AgNPs, and the detrimental apoptotic effects on cancer cells were examined using high-content screening (HCS) assays such as TNI, CMP, and VCC.

HPV types 16 and 18 are associated with 70% of invasive cervical cancers. Between these two types of HPV, HPV type 16 is more commonly found in cervical cancer patients, whereas HPV type 18 is less frequently reported. Currently, the molecular mechanism underlying the increased cancer risk in HPV type 16, compared to HPV type 18, has not yet been fully elucidated.

Acute lymphoblastic leukemia (ALL) is one of the most common malignancies worldwide. The long non-coding RNA MEG3 functions as a tumor suppressor in several cancers, potentially influencing gene expression through transcriptional, translational, and epigenetic mechanisms. let-7i plays a role in leukemia progression. This study aimed to evaluate MEG3 gene expression in adult ALL patients and investigate its possible regulatory interaction with let-7i-3p and let-7i-5p.

This study aimed to create a genetic and clinical roadmap for the TGF-β pathway in an Iraqi population, focusing on the TGF-β1 (+869 C/T) polymorphism.

Lymphoma is the most common hematologic malignancy in Thailand, with diffuse large B-cell lymphoma (DLBCL) being the predominant subtype. Early prognostic indicators are essential for guiding clinical decisions. Genetic alterations, particularly in regulatory regions, may serve as potential biomarkers. This study investigated sequence alterations upstream of exon 1 of the OSBPL10 gene and their clinical relevance in a Northern Thai DLBCL population.

A key element of computational drug discovery is the precise prediction of drug-gene interactions, particularly when working with intricate biological systems where relational dependencies are essential. Because biological networks are graph-structured, traditional machine learning techniques frequently fall short. Graph Neural Networks (GNNs) have emerged as a viable approach for learning meaningful representations from this data type in response to this challenge. In this study, three state-of-the-art GNN architectures Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), and GraphSAGE are comprehensively compared using a bipartite graph constructed from drug-target biochemical activity data.

The present study was planned to examine the possible association of polymorphisms in the superoxide dismutase and catalase genes with adverse normal tissue effects or injury resulting from radiotherapy in HNC patients.

The aim of the study was to determine how the chemotherapeutic alkylating agent dacarbazine, together with the application of the miR-204-5p mimic in vivo, affects the presence of disseminated melanoma cells in distant organs - the lungs and liver.