Inflammation is a key feature in breast cancer progression, with neutrophil extracellular traps (NETs) playing an important role. NETs are DNA-based structures released by neutrophils that can promote tumor adhesion, invasion, and immune evasion. Another crucial mechanism is the inflammasome, a multiprotein complex that drives inflammation through cytokine release. Both mechanisms are present in tumors and may act synergistically. In this study, we evaluated how isolated NETs modulate the NLRP3 inflammasome in a human breast cancer model. Exposure of MDA-MB-231 cells to NETs increased the expression of NLRP3, CASP1, and IL1B. Blocking IL-1R with Anakinra reduced IL1B expression, while inhibition of the P2X7 receptor with A740003 decreased NLRP3 and IL1B. ELISA confirmed that NETs stimulate IL-1β release, which was reduced by MCC950, Anakinra, and A740003. Functionally, NETs accelerated tumor cell migration, and this effect was inhibited by MCC950 and Anakinra. Bioinformatics analysis of TCGA breast cancer samples showed differential inflammasome gene expression among subtypes and a positive correlation between inflammasome components and NET-related genes. These findings highlight the interplay between inflammatory and immune mechanisms in breast cancer progression and may support the development of new therapeutic strategies.

The Mediator complex is a central regulator of eukaryotic transcription, functioning as a dynamic molecular interface between gene-specific transcription factors and RNA polymerase II (Pol II). Although its overall architecture and general role in transcription have been extensively reviewed, accumulating genetic, genomic, and clinical evidence indicates that individual Mediator subunits make distinct and non-redundant contributions to human physiology and disease. In this review, we move beyond a generic description of Mediator function and present a subunit-resolved synthesis of Mediator biology with an emphasis on disease pathogenesis. A key feature of this review is a comprehensive table integrating disease associations and molecular functions of individual human Mediator subunits, enabling rapid assessment of functional specialization across the complex. We further discuss chromatin-based mechanisms of Mediator action, including cooperation with cohesin and architectural factors to regulate enhancer-promoter communication and higher-order genome organization. By organizing recent structural, mechanistic, and pathological findings into a unified framework, this review highlights how disruption of specific Mediator subunits contributes to cancer, developmental disorders, and metabolic disease, and outlines emerging opportunities for therapeutic intervention.

Cancer immunotherapy has revolutionized the treatment of cancer by harnessing the immune system to recognize and destroy malignant cells. However, a substantial proportion of patients exhibit primary or acquired resistance to these therapies, underscoring the urgent need to identify novel molecular targets to enhance therapeutic efficacy. Autophagy, an evolutionarily conserved cellular process of degradation and recycling, has emerged as a critical modulator of tumor immunity and the function of immune cells. In cancer cells, autophagy modulates antigen presentation, immunogenic cell death, metabolic reprogramming, and resistance to immune-mediated cell death. Concurrently, autophagy rigorously governs the viability, differentiation, and functional capacity of immune cells, including T cells, dendritic cells, macrophages, and natural killer (NK) cells. Dysfunctional autophagic flux in the tumor microenvironment can enhance immune evasion and limit the efficacy of immune checkpoint inhibitors, adoptive cell therapies, and cancer vaccines. In this review, we provide an in-depth analysis of emerging molecular targets involved in the regulation of autophagy relevant to cancer immunotherapy. This includes key signaling pathways such as PI3K/AKT/mTOR, AMPK, Beclin-1 complexes, ULK1, and lysosomal regulators. Additionally, we explore the rational integration of the pharmacological modulation of autophagy, including small molecules, natural compounds, and nanoparticle-based drug delivery systems, with immunotherapeutic approaches. We highlight the importance of rational drug selection and combination therapies to overcome resistance to immunotherapy and minimize toxicity. Understanding the context-dependent role of autophagy will be essential for the development of next-generation, precision-targeted cancer immunotherapies. Therefore, a comprehensive understanding of the context-specific functions of autophagy in tumor and immune cells is crucial for devising precision-targeted combination methods that overcome immunotherapy resistance and produce more sustainable cancer treatment outcomes.

Gastric cancer (GC), also known as stomach adenocarcinoma (STAD), remains a highly lethal malignancy due to late diagnosis, limited therapeutic efficacy, and frequent metastasis. Although extensive molecular profiling has been performed, post-transcriptional regulatory mechanisms underlying GC progression are still incompletely characterized. In this study, we applied an integrative multi-omics framework to elucidate the regulatory roles and clinical relevance of circular RNAs (circRNAs) in GC. Transcriptomic data of mRNAs, microRNAs, and circRNAs from eight independent GEO datasets were jointly analyzed, resulting in the identification of 249 differentially expressed genes (DEGs), 8 differentially expressed microRNAs (DEmiRNAs), and 4 differentially expressed circRNAs (DEcircRNAs). These molecules were integrated into a competing endogenous RNA (ceRNA) network, enabling systems-level characterization of GC-associated regulatory interactions. Network topology and survival analyses prioritized 13 hub molecules, including IGF2BP3, COL4A1, MMP14, and TGM2, which showed both central network positions and significant associations with patient survival. To explore therapeutic implications, transcriptomics-guided drug repositioning combined with molecular docking analysis identified five candidate compounds-celastrol, fedratinib, pevonedistat, tozasertib, and withaferin A-predicted to target key network hubs. Overall, this in silico study provides a ceRNA-centered regulatory framework for GC and prioritizes biologically informed biomarkers and repositioned drug candidates with potential applicability across other malignancies to converge precision oncology.

Lymphovascular invasion is an adverse pathologic feature in prostate cancer, but its independent molecular drivers remain unclear due to strong confounding by tumor grade and stage. We performed a confounder-adjusted transcriptomic analysis of 403 TCGA-PRAD samples. Differential expression was adjusted for Gleason score and pathological T stage. A transcriptional profile associated with LVI was derived and tested in multivariable logistic and Cox proportional hazards models for biochemical recurrence-free survival, with bootstrap internal validation. After multivariable adjustment, 129 genes were independently associated with LVI. This gene set was overwhelmingly enriched for interferon-alpha/beta signaling and antiviral response pathways. A continuous composite score derived from this profile predicted a reduced risk of biochemical recurrence independently of standard clinicopathological factors (adjusted HR per unit = 0.911, 95% CI: 0.835-0.993, p = 0.033). Multi-omics integration revealed subtle promoter hypomethylation and strong correlations between methylation and expression for key interferon genes, supporting transcriptional regulation. We identify a robust, interferon-response transcriptional profile that specifically defines LVI in prostate cancer after accounting for major clinical confounders. This transcriptional signature provides independent prognostic information, refines the biological understanding of LVI, and presents a novel targetable pathway for further investigation.

Cancer immunotherapy has experienced substantial progress in recent years, particularly with the advancement of chimeric antigen receptor (CAR) technology, which enables immune cells to selectively target tumor-associated antigens. CARs, now in their fifth generation, are engineered by combining monoclonal antibody fragments with signaling and co-stimulatory domains and have been successfully applied to T cell, natural killer (NK) cell, and macrophage-based therapies. Notable clinical successes, such as tisagenlecleucel and lisocabtagene maraleucel underscore the therapeutic potential of CAR-T, CAR-NK and CAR-macrophages (CAR-Ms), which are currently being evaluated in numerous clinical trials. One promising extension of this approach involves the use of extracellular vesicles (EVs) derived from these immune cells. These nano-sized vesicles offer a cell-free platform to deliver diverse anticancer mediators, addressing the complex and dynamic nature of tumor environments. In this review, we examine the therapeutic potential and immunogenic properties of CAR-derived EVs, along with their role in modulating immune responses. Furthermore, we explore their application as targeted delivery vehicles for chemotherapeutic agents, with the goal of enhancing anti-tumor efficacy while minimizing systemic toxicity.

MicroRNAs (miRNAs) are ~19-25-nt post-transcriptional regulators whose dysregulation promotes hallmark cancer traits and therapy resistance. This review synthesizes translational principles for developing miRNA therapeutics in oncology, integrating miRNA biology and target engagement with delivery design and clinical experience. We summarize key determinants that shape efficacy and safety, including sequence and chemistry choices, biodistribution and intracellular delivery, dosing strategy, and biomarker-informed patient selection. We compare the main therapeutic modalities, miRNA mimics and inhibitors, and evaluate leading delivery approaches relevant to cancer, including lipid-based systems, polymer-based carriers and conjugates, and extracellular vesicle-inspired platforms, highlighting trade-offs in stability, specificity, immune activation, and tumor exposure. Early clinical programs such as MRX34, TargomiR/MesomiR-1, and cobomarsen, together with experience from non-oncology indications, illustrate both opportunities and practical constraints on tolerability and regimen optimization. We conclude with pragmatic priorities for the field, including standardized analytics for isoforms and target engagement, PK/PD- and biomarker-guided dose selection, and rational combination strategies to safely integrate miRNA-based interventions into precision oncology.

This study utilized network pharmacology, bioinformatics, along with machine learning to investigate the multi-target synergistic anti-cancer mechanisms of three edible medicinal plants (EMPs)-mulberry leaf, lotus leaf, and sea buckthorn-against oral and esophageal squamous cell carcinomas (OSCC and ESCC). We identified potential active constituents and their targets through mining Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. Concurrently, integration with differential expression profiles and co-expression modules identified crucial intersection targets between the EMPs and these two cancers. Subsequent machine learning algorithms and cross-cancer analysis consistently identified Matrix Metalloproteinase-1 (MMP1) as a critical hub gene. Its overexpression is closely associated with tumor invasion and metastasis. Molecular simulations revealed stable binding interactions between active constituents from three EMPs and hub proteins. Furthermore, research on immune cell infiltration suggested that the active components of three EMPs may impact the tumor immune microenvironment in both OSCC and ESCC through the regulation of pivotal gene expression. Collectively, this work systematically elucidates the molecular basis underlying the multi-target, multi-pathway synergistic anti-cancer effects of these EMPs, providing a theoretical foundation for developing natural drugs against these squamous cell carcinomas.

Several receptors have received considerable attention as therapeutic targets in gastric cancer (GC), and numerous receptor inhibitors have been developed. However, the development of novel gastric cancer therapeutics is time-consuming. Therefore, this study aimed to identify drugs effective against gastric cancer from existing anticancer agents originally developed for other malignancies. In this study, the cancer-related genomic profiles of 286 genes were analyzed in 14 gastric cancer cell lines using targeted DNA sequencing, and these cell lines were utilized as models to evaluate the efficacy of 35 anticancer drugs. The 14 cell lines were assessed for 286 gene alterations, copy number variations, amplification of 14 gastric cancer-related therapeutic targets, and sensitivity to 35 drugs. p-MET and MET were overexpressed in the SNU5, SNU620, MKN45, and Hs746T cell lines, while p-EGFR was overexpressed in the NCI-N87 cell line. FGFR2 overexpression was observed in the Kato III and SNU16 cell lines. TGFβR1 was overexpressed in the MKN7 cell line. HER2 and CDK12 were overexpressed in the NCI-N87 and MKN7 cell lines. PD-L1 overexpression was detected in the Hs746T and MKN7 cell lines. CD44 was overexpressed in the SNU5 and Hs746T cell lines and CLDN18 overexpression was observed in the MKN7 cell line. Well-characterized gastric cancer cell lines are essential for drug development research. This study provides a framework for selecting cell lines that are responsive to each of the 35 anticancer drugs and elucidating their underlying therapeutic mechanisms through follow-up studies. Ultimately, clinical studies are required to confirm the therapeutic efficacy of the selected drugs.

Breast cancer is a heterogeneous malignancy that often changes during diagnosis and treatment, so timely monitoring of tumors, patients and treatment responses is crucial to improve the prognosis of patients. With the development of precision oncology, early patient stratification and the formulation of tailored therapeutic approaches have become essential strategies to maximize treatment efficacy. Several techniques, such as molecular pathology and genomics analysis have been thoroughly studied in the diagnosis and treatment of breast cancer, but they only evaluate and analyze from the perspective of patients or tumors in isolation. Metabolomics uses high-throughput analytical techniques to provide a functional readout of the biological phenotype, reflecting the sum of alterations occurring at the DNA, RNA, and protein levels. Therefore, through the detection of tumor tissues and peripheral blood of patients, metabolomics could describe the bidirectional interaction between the tumor and its microenvironment, as well as the systemic metabolic changes in patients to evaluate cancer progression from both tumor and patient aspects in a more comprehensive way. In this review, we summarize the currently available techniques for metabolomics and how metabolomics can be used to improve the clinical management of breast cancer patients, including diagnosis, treatment, and prognosis. We also discuss current challenges and future directions in metabolomics research.