Search Results (1,673)

The intricate intercellular communication within the tumor microenvironment (TME) critically drives cancer progression and therapeutic resistance. Natural killer (NK) cells are potent sentinels of the innate immune system, but their antitumor functions are often severely compromised by the TME’s immunosuppressive networks. Moving beyond protein-coding genes, non-coding RNAs (ncRNAs)—with microRNAs (miRNAs) playing a foundational role alongside long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs)—have emerged as vital components of the regulatory networks influencing immune responses. Rather than dictating immune cell fate, these diverse transcriptomic classes form complex networks that modulate NK cell functional states and TME immunosuppression. This review systematically elucidates the molecular mechanisms by which these ncRNA networks influence NK cell biology in the TME. We dissect three core regulatory axes driven by extracellular vesicle (EV)-mediated communication, competitive endogenous RNA crosstalk, and epigenetic remodeling: the extrinsic suppression of NK cells by EV-derived and secreted ncRNAs from TME-resident cells, the reciprocal modulation of TME components by NK cell-derived ncRNAs, and the intrinsic regulation of NK cell functions by endogenous ncRNAs. Furthermore, we critically assess the clinical translational potential of targeting these networks. We highlight specific ncRNAs as non-invasive prognostic biomarkers and summarize targeted therapeutic interventions using antisense oligonucleotides, small interfering RNAs, and nano-delivery systems. Modulating these core ncRNA nodes to mitigate TME immunosuppression offers a novel paradigm for precision oncology, holding substantial promise for enhancing immune checkpoint blockade and NK cell-directed immunotherapies. Full article

Antibody–drug conjugates (ADCs) have received renewed attention in oncology following the clinical and commercial success of agents such as trastuzumab deruxtecan (Enhertu^®), which underscored the clinical importance of coordinated optimization of the antibody, linker, payload, and conjugation strategy. Among these parameters, conjugation strategy strongly influences drug-to-antibody ratio (DAR) distribution, pharmacokinetics, manufacturability, and safety. Over the past two decades, ADC conjugation technologies have evolved from first-generation stochastic modification approaches to second-generation site-specific engineering strategies and, more recently, to third-generation site-selective platforms applicable to native antibodies. First-generation approaches remain the most clinically validated and have the strongest regulatory precedent despite their intrinsic heterogeneity. Second-generation approaches improve positional control and DAR homogeneity, but often increase demands on antibody engineering, expression, and process complexity. Third-generation approaches aim to preserve controlled conjugation while reducing sequence-engineering requirements, yet remain limited by a restricted number of accessible sites and less extensive clinical and regulatory experience. In this review, we summarize the evolution of ADC conjugation technologies, highlight representative clinical and translational examples, and discuss the major trade-offs of each platform. We also propose a practical selection framework based on payload properties, required DAR control, antibody stability, manufacturability, and regulatory considerations, with relevance to next-generation ADCs including dual-payload and bispecific formats. Overall, conjugation strategy should be selected according to the scientific, manufacturing, and regulatory requirements of each ADC program rather than on the basis of a presumed technological hierarchy. Full article

Personalized oncology seeks to selectively block specific dysregulated pathways to arrest cancer development. Increased glutamine metabolism is a hallmark of cancer, and 6-diazo-5-oxo-L-norleucine (DON), a structural analog of L-glutamine, was the first compound used to target the exacerbated nitrogen metabolism observed in cancer cells. However, its clinical application was limited by unacceptable toxicity. With the same goal of blocking glutamine metabolism, several specific glutaminase inhibitors have been characterized in recent decades, showing promising antitumor activity. Nevertheless, this strategy frequently induces adaptive metabolic resistance that must be counteracted. In this context, glutaminase has become a key target in combination therapies for several tumor types aimed at restricting anabolic adaptation when single metabolic therapy fails, emerging as a possible synergistic therapeutic intervention. Consequently, combination therapies that include glutaminase inhibition alongside additional agents to counteract the metabolic plasticity of cancer have emerged as a promising approach in personalized antitumor pharmacology. This review provides a historical-to-translational overview of glutamine-targeted therapies, with particular emphasis on glutaminase inhibitors, including compound 968, BPTES, CB-839, and next-generation inhibitors, as well as DON-derived prodrugs. We discuss their mechanisms of action and their integration with chemotherapy, targeted therapies, radiotherapy, and immunotherapy, highlighting how glutamine metabolism targeting influences tumor metabolic adaptation, redox homeostasis, therapy resistance, and tumor–immune interactions. Finally, we examine current clinical developments, emerging therapeutic combinations, and the challenges that must be addressed for the incorporation of glutamine metabolism targeting into precision oncology. Full article

Pancreatic cancer ranks among the most lethal malignancies, characterized by a five-year survival rate of approximately 10%. This dismal prognosis is largely attributable to diagnoses occurring at advanced stages and the inherent limitations of conventional imaging modalities in detecting early lesions, identifying metastases, and assessing tumor heterogeneity. Consequently, there is a critical need for non-invasive imaging techniques capable of visualizing pancreatic cancer lesions to enable accurate diagnosis, risk assessment, and the development of personalized treatment strategies. Molecular imaging, which combines highly specific targeted probes with advanced imaging technologies, offers the potential to elucidate disease-associated pathways. This review provides a comprehensive overview of recent advancements in molecular imaging platforms for pancreatic cancer, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), optical molecular imaging, photoacoustic imaging, and molecular MRI. We begin by elucidating the biological rationale for targeting key molecules, including fibroblast activation protein (FAP), integrins, and programmed death ligand 1 (PD-L1). Moreover, we critically evaluate the development and clinical translation of these probes, highlighting their ability to enhance lesion detectability, characterize intratumoral heterogeneity, and guide both targeted therapy and surgical resection. Compared with existing reviews, this work uniquely integrates a comprehensive cross-modality analysis of the latest molecular imaging strategies for pancreatic cancer. Furthermore, we examine prevailing challenges and emerging frontiers in this domain, specifically focusing on multimodal hybrid imaging, artificial intelligence-driven analytics, and integrated theranostic platforms as pivotal strategies to advance precision oncology. Full article

Immune checkpoint inhibitor (ICI)-based combinations have become central systemic treatment options for advanced hepatocellular carcinoma (HCC) and are now being integrated into selected intermediate-stage settings. As tumor responses have improved, some patients who were not initially candidates for curative-intent treatment may later become candidates for resection, ablation, or liver transplantation. However, radiographic response alone does not define curative-intent candidacy, and no shared framework currently guides how post-immunotherapy response should be translated into a treatment decision. Terminology also differs regionally: Asian literature frames a resection-anchored paradigm, whereas Western practice uses transplant-anchored downstaging. This narrative review proposes a multidisciplinary framework for immunotherapy-based conversion to curative-intent treatment in HCC. We first clarify the lexicon of conversion, downstaging, bridging, neoadjuvant therapy, post-ICI transplantation, and drug-free or treatment-free status. We then summarize conversion-relevant evidence across key clinical decision settings, including transarterial chemoembolization (TACE)-unsuitable intermediate-stage disease, portal vein tumor thrombus or macrovascular invasion, borderline-resectable or locally advanced disease, and transplant downstaging or bridging. The central framework defines curative-intent transition through the intersection of three domains: technical suitability, oncologic suitability, and physiologic or liver-reserve suitability. Biomarkers, imaging response, tumor-marker kinetics, liver function, and treatment-related toxicity are discussed as inputs into candidacy rather than as response measures alone. Finally, we propose a multidisciplinary workflow and highlight lessons from pancreatic cancer, biliary tract cancer, and colorectal liver metastases. As an expert-opinion-based framework, this approach should structure multidisciplinary discussion rather than serve as validated selection criteria; harmonized terminology, prospective conversion registries, and conversion-specific endpoints are needed for prospective validation. Full article

Cancer multidrug resistance (MDR), particularly mediated by ATP-binding cassette (ABC) transporters, can link ABC transporters’ ATP-dependent efflux to Nrf2-driven antioxidant defence. This connection reduces the oxidative threshold in MDR cancer cells. Natural or nature-inspired compounds can target this vulnerability and induce collateral sensitivity (CS) by simultaneously modulating the redox balance and ABC transporters’ activity in MDR cancer cells. Moreover, natural-origin compounds can act on multiple targets by combining efflux inhibition, redox modulation, and immune evasion into a unique therapeutic strategy. However, many challenges should be addressed in their characterisation and preclinical validation to ensure their usefulness for clinical application. These include poor bioavailability, pharmacokinetic interactions, safe toxicity windows, and tumour heterogeneity. In perspective, adaptive trial designs employing biomarker-guided patient stratification can translate natural-origin compounds from preclinical promise to precision partners in clinical oncology. Full article

Ferroptosis is an iron-dependent regulated form of cell death characterized by lethal lipid peroxidation and is increasingly implicated in cancer, neurodegenerative diseases, cardiovascular injury, and metabolic disorders. Metformin, a widely prescribed antidiabetic biguanide, exerts pleiotropic effects beyond glucose lowering and has emerged as a context-dependent regulator of ferroptosis. In malignant cells, metformin may enhance ferroptotic susceptibility through activation of AMP-activated protein kinase (AMPK), suppression of mechanistic target of rapamycin (mTOR) signaling and SLC7A11, induction of ferritinophagy, mitochondrial complex I stress, and promotion of lipid peroxidation. Conversely, in normal or stressed non-malignant tissues, metformin may limit ferroptotic injury by activating nuclear factor erythroid 2-related factor 2 (NRF2), supporting glutathione peroxidase 4 (GPX4) and SLC7A11-dependent antioxidant defenses, improving mitochondrial quality control, and stabilizing iron homeostasis. This review synthesizes the molecular basis of this duality, evaluates therapeutic opportunities in oncology and cytoprotection, and outlines biomarker-driven and clinical trial strategies required for translation. Overall, metformin should not be regarded as a universal ferroptosis inducer or inhibitor, but rather as a context-dependent metabolic regulator whose effects are shaped by cell type, dose, exposure duration, transporter expression, iron status, and antioxidant capacity. Full article

Background: The high costs, long development timelines, and low clinical success rates in oncology highlight an urgent need for reliable computational strategies for drug repositioning. Current machine learning approaches often integrate heterogeneous pharmacogenomic datasets, which may lose biological specificity and limit model interpretability. Methods: In this study, we propose Separate XAI, an explainable artificial intelligence framework that retains dataset-specific biological features by adopting separate preprocessing and training pipelines for the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets. Different deep learning architectures such as Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) were used to predict the drug response in the cancer cell lines. We also used SHapley Additive exPlanations (SHAP) to improve interpretability and identify biologically relevant features. Results: The developed framework showed good predictions with 94.49% accuracy in the CCLE dataset and a mean squared error of 0.0725 in the GDSC dataset. Explainability analysis identified important biomarkers and signaling pathways such as TP53 and KRAS, providing mechanistic insights into drug sensitivity and therapeutic response. Conclusions: The distinct XAI presented here offers an interpretable, biologically grounded framework for cancer drug repositioning by integrating dataset-specific modeling and explainable artificial intelligence. However, integration-based approaches often suffer from confounding effects of experimental and biological heterogeneity, but the proposed framework explicitly preserves dataset-specific characteristics, which potentially could lead to more robust predictions and higher interpretability for precision oncology and translational cancer research. Full article

Messenger RNA (mRNA) vaccines represent a transformative platform in vaccinology, with applications extending beyond SARS-CoV-2 to other infectious diseases and cancer immunotherapy. However, patients with solid tumors receiving active anticancer treatment were largely underrepresented in pivotal vaccination trials, limiting understanding of vaccine-induced immunity in this population. In this prospective exploratory study, we assessed humoral and cellular immune responses after two doses of SARS-CoV-2 mRNA vaccines in 39 patients with solid tumors undergoing active treatment. Blood samples were collected before vaccination and approximately two months after the second vaccine dose, prior to the next treatment cycle. Anti-spike IgG, neutralizing antibodies, receptor-binding domain (RBD) levels, interleukin-6 (IL-6), hematological parameters, immune cell subsets, T-cell differentiation, and early apoptosis in αβ and γδ T-cell subsets were analyzed. Vaccination induced a robust humoral response, with high post-vaccination anti-spike IgG levels (median 988.69 BAU/mL), 97.44% seropositivity, 96.88% true seroconversion among baseline IgG−/NAb− patients, and strong neutralizing antibody activity (median 85.73%). Hematological parameters and IL-6 levels remained broadly stable, suggesting no detectable increase in systemic inflammation during the study period. Cellular analyses identified a reduction in peripheral CD19+ B-cell frequencies and decreased early apoptosis, particularly in CD8+ T cells and CD3+CD56+ NKT-like cells. Although changes in T-cell frequencies and differentiation profiles were also observed, these findings were attenuated after exclusion of participants with possible prior SARS-CoV-2 exposure and should be interpreted as exploratory. Overall, these results show that patients with solid tumors receiving active treatment can mount robust humoral responses to SARS-CoV-2 mRNA vaccination and suggest measurable post-vaccination changes in lymphocyte dynamics, including reduced early T-cell apoptosis. Full article

Head and neck squamous cell carcinoma (HNSCC) is characterized by marked intratumoral heterogeneity and complex tumor–immune–stromal interactions, which shape therapeutic response and clinical outcome. Despite extensive transcriptomic efforts, bulk RNA sequencing has faced significant limitations, often failing to generate robust prognostic or predictive biomarkers, highlighting the need for approaches capable of resolving the cellular and spatial complexity of the tumor ecosystem. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have refined our understanding of HNSCC biology by enabling high-resolution mapping of malignant, stem-like, immune, and stromal compartments. Three major spatial domains have been defined in HNSCC: tumor core (TC), tumor invasion front (TIF), and leading edge (LE). Each ecosystem exhibits distinct cellular programs that promote immune evasion, tumor dissemination, and therapy resistance, particularly in high-risk clinical settings. In this Review, we integrate recent single-cell and spatial studies and propose a translational framework linking ecosystem architecture with clinical stratification across resectable locally advanced (r-LAD), unresectable locally advanced (u-LAD), and recurrent/metastatic (R/M) disease. We further discuss how spatially resolved transcriptomic approaches may support biomarker discovery and hypothesis generation for risk stratification and trial design, while emphasizing that clinical implementation remains limited by cohort size, methodological heterogeneity, and the need for large-scale prospective validation. Finally, we outline key methodological and translational challenges that must be addressed before these technologies can reliably inform precision oncology and decision-making in HNSCC. Full article

Background/Objectives: Intraoperative molecular imaging (IMI) enables real-time visualization of tumor biology during surgery using fluorescent probes and near-infrared imaging systems. As lung cancer screening increases detection of small and nonpalpable pulmonary nodules, conventional localization and margin assessment techniques remain limited, particularly during minimally invasive surgery. This review summarizes the technical foundations, imaging agents, clinical applications, and future directions of IMI in thoracic oncology. Methods: We performed a narrative review to synthesize current evidence regarding the technical foundations, molecular imaging agents, clinical applications, and future directions of intraoperative molecular imaging in thoracic oncology. Given the multidisciplinary scope of the field, a narrative approach was selected to integrate mechanistic, translational, and clinical evidence rather than to answer a single narrowly defined clinical question. Results: IMI generates dynamic intraoperative contrast based on preferential probe accumulation or activation within malignant tissue. Current approaches include non-specific fluorophores such as indocyanine green, activatable probes targeting tumor-associated proteases or acidic microenvironments, and receptor-targeted agents such as pafolacianine. Across prospective studies and multicenter trials, IMI improved localization of nonpalpable lesions, identified occult synchronous malignancies, and enhanced intraoperative margin assessment, frequently altering surgical management. Phase 2 and 3 studies of folate receptor-targeted imaging demonstrated clinically significant findings in a substantial proportion of patients, including lesions not detected by conventional imaging or palpation. However, performance remains dependent on tumor biology, target expression, lesion depth, and optical constraints. Conclusions: IMI represents an emerging transition from anatomy-guided toward biology-informed thoracic surgery by providing real-time molecular information during resection. Current evidence supports its role as a complementary intraoperative technology that augments conventional imaging and surgical techniques, particularly for small, peripheral, and nonpalpable lesions. Full article

Rare subtypes of gastroesophageal malignancies represent a small but biologically meaningful fraction of upper gastrointestinal cancers. Although most therapeutic algorithms are derived from conventional squamous cell carcinoma and adenocarcinoma, uncommon entities such as variants of squamous cell carcinoma, lymphoepithelioma-like carcinoma, adenosquamous carcinoma, neuroendocrine carcinoma, and others display distinct clinicopathologic, immunologic, and molecular features that may influence prognosis and therapeutic decision-making. This review synthesizes current evidence regarding the epidemiology, histopathology, molecular alterations, and emerging therapeutic vulnerabilities across these rare subtypes. Importantly, these tumors frequently exhibit aggressive clinical behavior and are often managed by extrapolation from more common histologies due to the absence of prospective data. Increasing integration of genomic profiling, immune characterization, and biomarker-driven stratification is essential to refine diagnoses, expand precision therapeutic strategies, and improve outcomes. Recognition of these rare subtypes in routine practice is critical, as even small molecularly defined populations may carry disproportionate biological and translational significance within oncology. Full article

Oral squamous cell carcinoma (OSCC) remains a major global health burden with limited improvement in survival rates. While traditional risk factors such as tobacco and alcohol are well established, increasing evidence highlights the role of the oral microbiome in carcinogenesis. Among microbial species, Candida albicans (C. albicans) has emerged as a potential contributor to tumor-promoting processes. Clinical studies consistently report increased fungal colonization in oral potentially malignant disorders and OSCC, with associations to disease severity and recurrence. Mechanistically, C. albicans contributes to carcinogenesis through acetaldehyde production, chronic inflammation, oxidative stress, epithelial signaling modulation, and extracellular vesicle (EV)-mediated communication. These pathways promote tumor microenvironment remodeling and epithelial transformation. However, conflicting evidence exists regarding causality, suggesting that fungal colonization may also result from tumor-associated ecological changes. From a translational perspective, C. albicans and EV-associated signatures may represent promising biomarkers and therapeutic targets, although further validation is required. This review highlights the emerging role of fungal–host interactions in OSCC and underscores their potential in microbiome-informed precision oncology. Full article

Animal venoms represent an extraordinary, yet largely untapped, biochemical reservoir for oncological drug discovery. This review provides a comprehensive analysis of venom-derived enzyme inhibitors as emerging anticancer agents, emphasizing their chemical diversity, structure–activity relationships (SAR), molecular targets, and mechanistic pathways. Venom-derived peptides and proteins exhibit exceptional binding affinity and structural rigidity, characteristics frequently enforced by conserved disulfide networks. This specific architecture allows them to selectively modulate critical cancer-associated enzymes, including matrix metalloproteinases, phospholipases A₂, serine proteases, and kinases. Inhibiting these highly specific targets successfully disrupts tumour angiogenesis, extracellular matrix remodelling, and metastatic dissemination, while simultaneously inducing apoptosis through unique pathways such as reactive oxygen species generation. Modern computational approaches, encompassing deep learning algorithms, molecular docking, and molecular dynamics simulations, are substantially accelerating and transforming the discovery pipeline by rapidly mapping intricate peptide–receptor interactions and guiding rational drug design. Translating these potent molecules into clinical therapeutics remains heavily challenged by pharmacokinetic instability, rapid proteolytic degradation, and systemic toxicity. The integration of computationally optimized scaffolds with advanced targeted delivery platforms, such as nanocarriers and liposomal encapsulation, offers a highly viable strategy to overcome these barriers, ultimately paving the way for next-generation, venom-inspired cancer therapies. Full article

In this Perspective, we present a non-systematic narrative synthesis and propose a hypothesis-generating framework that links regional anesthesia, local anesthetic strategies, surgery-induced NETosis, and perioperative metastatic biology. Surgical tumor resection coincides with a biologically vulnerable perioperative period characterized by inflammatory activation, innate immune remodeling, and potential metastatic susceptibility. Preclinical evidence suggests that this interval may represent a transient metastatic window in which circulating tumor cells and host inflammatory responses overlap, potentially favoring metastatic implantation. Among the mechanisms implicated in this process, neutrophil extracellular traps (NETs) have been implicated in tumor-cell capture, endothelial interaction, immune evasion, and metastatic outgrowth. Experimental studies further suggest that surgery-induced NETosis may contribute to prometastatic signaling and tumor-cell metabolic adaptation during the postoperative period. Human evidence remains more limited and heterogeneous. Observational studies indicate that NET-related biology is active during oncologic surgery, with the presence of tissue NETs and circulating NET-associated biomarkers correlating with tumor stage, inflammatory context, or tumor burden in selected malignancies. Perioperative clinical studies also suggest that regional anesthesia and local anesthetic-based strategies, including intravenous lidocaine, may influence neutrophil activation and postoperative NET-associated biomarkers. However, robust evidence of clinical oncologic outcomes remains limited, and a clear distinction between surrogate perioperative endpoints and long-term clinical outcomes is still lacking. Within this context, we propose that regional anesthesia may influence pathways associated with perioperative tumor–host interactions not primarily through opioid sparing but through modulation of mechanisms related to surgery-induced NETosis during a short-lived biological window. The neutral results of large survival-based trials do not necessarily invalidate this hypothesis; rather, they underscore the limitations of conventional oncologic endpoints in capturing transient perioperative biological effects. This Perspective outlines a translational research agenda centered on biomarker-driven perioperative studies integrating NET-specific markers, circulating tumor cell dynamics, and temporally precise postoperative sampling. Full article