Search Results (1,129)

Fusobacterium nucleatum (F. nucleatum), a Gram-negative anaerobe traditionally associated with periodontal disease, has recently emerged as a putative contributor to gastric carcinoma (GC) pathogenesis. Beyond its detection in gastric tissues, particularly in patients negative for Helicobacter pylori (H. pylori) or in advanced GC cases, F. nucleatum exerts diverse oncogenic effects. It promotes GC progression by modulating the tumor microenvironment through IL−17/NF-κB signaling, inducing tumor-associated neutrophils (TANs), upregulating PD-L1 expression, and enhancing immune evasion. Moreover, it increases tumor invasiveness via cytoskeletal reorganization, while extracellular vesicles (EVs) induced by the infection contribute to tumor cell proliferation, invasion, and migration. Clinically, its presence correlates with increased tumor mutational burden (TMB), venous thromboembolism, and poor prognosis. This review summarizes the current evidence regarding the emerging role of F. nucleatum in gastric tumorigenesis, examines its potential utility as a diagnostic and prognostic biomarker within the framework of precision oncology, and outlines the molecular methodologies presently employed for its detection in gastric tissue specimens. Full article

Background: Melanoma is one of the most aggressive types of skin cancer. Its diagnosis appears to be challenging due to morphological similarities to benign melanocytic lesions. Even though histopathological evaluation is the diagnostic gold standard, immunohistochemistry (IHC) proves to be useful in challenging cases. Preferentially Expressed Antigen in Melanoma (PRAME) has emerged as a promising diagnostic, prognostic, and therapeutic marker in melanoma. Methods: This review critically examines the role of PRAME across clinical domains. It presents an evaluation of PRAME’s diagnostic utility in differentiating melanomas from benign nevi, its prognostic significance across melanoma subtypes, and therapeutic applications in emerging immunotherapy strategies. An extensive analysis of the current literature was conducted, with a focus on PRAME expression patterns in melanocytic lesions and various malignancies, along with its integration into IHC protocols and investigational therapies. Results: PRAME demonstrates high specificity and sensitivity in distinguishing melanoma from benign melanocytic proliferations, particularly in challenging subtypes such as acral, mucosal, and spitzoid lesions. Its overexpression correlates with poor prognosis in numerous malignancies. Therapeutically, PRAME’s HLA class I presentation enables T-cell-based targeting. Early-phase trials show promising results using PRAME-directed TCR therapies and bispecific ImmTAC agents. However, immune evasion mechanisms (i.e., heterogeneous antigen expression, immune suppression in the tumor microenvironment, and HLA downregulation) pose significant challenges to therapy. Conclusions: PRAME is a valuable biomarker for melanoma diagnosis and a promising target for immunotherapy. Its selective expression in malignancies supports its clinical utility in diagnostic precision, prognostic assessment, and precision oncology. Ongoing research aimed at overcoming immunological barriers will be essential for optimizing PRAME-directed therapies and establishing their place in the personalized management of melanoma. Full article

Background: Keratinocyte carcinomas (KCs), including basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs), are the most prevalent malignancies globally, particularly affecting sun-exposed facial areas. Achieving clear surgical margins in these regions is essential to ensure oncologic control while preserving cosmetic outcomes. Reflectance confocal microscopy (RCM) is a noninvasive imaging technique that enables real-time, high-resolution visualization of skin structures and may aid in margin assessment during KC surgery. This systematic review aims to evaluate the role of in vivo RCM in the surgical treatment of KCs. Methods: This review followed PRISMA guidelines. A comprehensive search of PubMed, Scopus, Web of Science, Medline, and EBSCO databases was conducted for studies published between January 1992 and December 2024. Inclusion criteria focused on clinical studies utilizing in vivo RCM for diagnostic or surgical applications in KC management. Results: Eighteen studies involving 1112 patients were included. RCM was used preoperatively in 5 studies and intraoperatively in another 5. Nine studies assessed margin delineation, while eight focused on diagnostic accuracy. RCM improved diagnostic confidence and allowed for more precise margin assessment, potentially reducing the extent of surgical excision in cosmetically sensitive areas. However, its broader clinical adoption is limited by operator dependency, procedural complexity, and lack of standardization. Conclusions: RCM shows promise as a supportive tool in KC surgery, particularly for preoperative planning. While its diagnostic utility is well established, its intraoperative role requires further validation. Larger, standardized, and cost-effective studies are needed to confirm its impact on surgical outcomes and patient quality of life. Full article

Background/Objectives: Transoral robotic surgery (TORS) has advanced treatment for complex oropharyngeal cancers (OPC) by offering minimally invasive, precise approaches, initially for ablative and now for reconstructive procedures. This review examines TORS in OPC reconstruction, comparing it to traditional methods and presenting a TORS case with free flap reconstruction in recurrent OPC. Methods: A PubMed review assessed TORS-based reconstruction outcomes, technical challenges, and innovations. Additionally, a recurrent OPC case was treated with TORS resection and lateral arm free flap. Surgical techniques and outcomes were detailed. Results: TORS is associated with reduced morbidity and length of hospitalization, and showed positive functional outcomes in primary, salvage, and post-radiation cases. Our case achieved favorable oncologic and functional outcomes, such as preserved speech and swallowing. Conclusions: TORS-based reconstruction represents a major advancement in minimally invasive head and neck oncology, providing comparable oncologic outcomes to open surgery with fewer complications. Although technically demanding, TORS is promising for complex reconstructions, warranting further research to refine techniques and standardize protocols. Full article

Background/Objectives: Acute Lymphoblastic Leukemia (ALL) poses significant diagnostic challenges due to its ambiguous symptoms and the limitations of conventional methods like bone marrow biopsies and flow cytometry, which are invasive, costly, and time-intensive. Methods: This study introduces Neuro-Bridge-X, a novel neuro-symbolic hybrid model designed for automated, explainable ALL diagnosis using peripheral blood smear (PBS) images. Leveraging two comprehensive datasets, ALL Image (3256 images from 89 patients) and C-NMC (15,135 images from 118 patients), the model integrates deep morphological feature extraction, vision transformer-based contextual encoding, fuzzy logic-inspired reasoning, and adaptive explainability. To address class imbalance, advanced data augmentation techniques were applied, ensuring equitable representation across benign and leukemic classes. The proposed framework was evaluated through 5-fold cross-validation and fixed train-test splits, employing Nadam, SGD, and Fractional RAdam optimizers. Results: Results demonstrate exceptional performance, with SGD achieving near-perfect accuracy (1.0000 on ALL, 0.9715 on C-NMC) and robust generalization, while Fractional RAdam closely followed (0.9975 on ALL, 0.9656 on C-NMC). Nadam, however, exhibited inconsistent convergence, particularly on C-NMC (0.5002 accuracy). A Meta-XAI controller enhances interpretability by dynamically selecting optimal explanation strategies (Grad-CAM, SHAP, Integrated Gradients, LIME), ensuring clinically relevant insights into model decisions. Conclusions: Visualizations confirm that SGD and RAdam models focus on morphologically critical features, such as leukocyte nuclei, while Nadam struggles with spurious attributions. Neuro-Bridge-X offers a scalable, interpretable solution for ALL diagnosis, with potential to enhance clinical workflows and diagnostic precision in oncology. Full article

Immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) have revolutionized cancer therapy, substantially improving survival across a broad range of malignancies. However, these agents are associated with a unique profile of endocrine immune-related adverse events (irAEs), including thyroiditis, hypophysitis, adrenalitis, and pancreatitis, which differ significantly from the toxicities seen with conventional chemotherapy. These complications often arise unpredictably during treatment and may result in irreversible hormone deficiencies requiring lifelong replacement, underscoring the importance of early detection. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has emerged as a valuable tool not only for oncologic staging and response assessment but also for detecting metabolic changes in endocrine organs. PET/CT can identify irAEs before the appearance of clinical symptoms or biochemical abnormalities. Emerging evidence suggests that the presence of endocrine irAEs identified by ¹⁸F-FDG PET/CT may correlate with improved treatment response and survival, possibly reflecting enhanced immune activation. This comprehensive review discusses the role of ¹⁸F-FDG PET/CT in the early recognition of therapy-induced endocrine toxicities, facilitating timely intervention through hormone replacement or immunosuppressive therapy while minimizing unnecessary treatment interruptions. Effective integration of metabolic imaging with clinical and laboratory evaluation requires coordinated multidisciplinary collaboration among oncologists, endocrinologists, and nuclear medicine physicians to optimize outcomes and reduce endocrine-related morbidity in the era of precision oncology. Full article

The serine protease kazal-type inhibitor (SPINK) family is central to the regulation of proteolytic function, the establishment of physiological homeostasis, and the development of many disease states, including cancer. Emerging research has identified that members of the SPINK family are commonly overexpressed in most malignancies and are deeply implicated in pivotal oncogenic pathways like cell growth, epithelial-to-mesenchymal transition (EMT), metastasis, and drug resistance. This review provides an in-depth examination of structural and functional characteristics of SPINK proteins and their involvement in the onset and development of multiple cancers, which include prostrate, pancreatic, and colorectal carcinomas. Significantly, SPINK proteins regulate major signalling pathways, including EGFR, NF-κB, and MAPK, highlighting their role as prognostic biomarkers and therapeutic targets. The review underscores the most recent advancements in therapeutic strategies for SPINK-related pathways and outlines the bottlenecks that have restricted their use in the clinic. By integrating current evidence, this work signals the potential of SPINK proteins as good precision oncology candidates with novel options for cancer prognosis, treatment, and management. Full article

Lung cancer (LC), with non-small-cell lung cancer (NSCLC) as its predominant subtype, remains the leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors (ICIs) have redefined the therapeutic paradigm in advanced NSCLC, durable responses are confined to a limited subset of patients. A major clinical challenge persists: the inability to accurately predict which patients will derive meaningful benefit, which will exhibit primary resistance, and which are at risk for severe immune-related toxicities. The imperative to individualize ICI therapy necessitates robust, dynamic, and accessible biomarkers. Liquid biopsy has emerged as a transformative, minimally invasive tool that enables real-time molecular and immunologic profiling. Through analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, and peripheral blood immune components, liquid biopsy offers a window into both tumor intrinsic and host-related determinants of ICI response. These biomarkers not only hold promise for identifying predictive signatures—such as tumor mutational burden, neoantigen landscape, or immune activation states—but also for uncovering mechanisms of acquired resistance and guiding treatment adaptation. Beyond immunotherapy, liquid biopsy plays an increasingly central role in the landscape of targeted therapies, allowing early detection of actionable driver mutations and resistance mechanisms (e.g., EGFR T790M, MET amplification, and ALK fusion variants). Importantly, serial sampling via liquid biopsy facilitates longitudinal disease monitoring and timely therapeutic intervention without the need for repeated tissue biopsies. By guiding therapy selection, monitoring response, and detecting resistance early, liquid biopsy has the potential to significantly improve outcomes in NSCLC. Full article

The growing success of oncologic therapies has led to a significant improvement in patient survival; however, this has been accompanied by an increasing incidence of cardiovascular adverse events, particularly cancer therapy-related cardiac dysfunction (CTRCD). Among these, left ventricular impairment represents a major concern due to its potential to compromise both cardiac and oncologic outcomes. This review provides an in-depth overview of the cardiotoxic adverse events associated with several classes of anticancer agents. Particular focus is given to the molecular mechanisms involved in myocardial injury, such as oxidative stress, mitochondrial dysfunction, calcium dysregulation, endothelial reticulum stress, autophagy, and apoptosis. In parallel, established and emerging cardioprotective strategies, from conventional to newer therapeutic approaches, are explored. The role of advanced imaging modalities, as well as cardiac biomarkers, is discussed in the context of early detection and monitoring of subclinical cardiac injury. Finally, the integration of pharmacogenomics and epigenetics is considered as a promising avenue to personalize risk stratification and preventive therapy. By elucidating the complex interplay between cancer treatments and cardiovascular health, this review underscores the importance of a multidisciplinary, precision medicine approach to optimizing the care of patients undergoing potentially cardiotoxic therapies. Full article

Background/Objectives: Mutant isocitrate dehydrogenase (IDH) inhibitors represent a major advance in precision oncology. The recent Food and Drug Administration approval of vorasidenib for IDH-mutant glioma highlights its therapeutic potential in this setting. As this and other mutant IDH inhibitors enter the clinical setting, providers are tasked with staying informed of the evolving therapeutic landscape as more is learned about this unique class of medications. We aimed to summarize insights from preclinical studies and clinical trials exploring their use in IDH-mutant glioma. Methods: We reviewed notable preclinical studies establishing the rationale for targeting mutant IDH. We performed a systematic review of clincaltrials.gov to identify both completed and ongoing interventional IDH-directed trials in patients with IDH-mutant glioma. Results: We identified 8 published and 15 ongoing clinical trials evaluating IDH-directed therapies. IDH inhibitors have been shown to slow and, in some cases, reverse glioma tumor growth, with activity that may extend beyond their currently approved indications. The presence of contrast enhancement is consistently a negative predictor of response for ivosidenib and vorasidenib, although safusidenib and olutasidenib preliminarily may retain efficacy in these cases. Novel approaches such as IDH-directed vaccines and combination therapy using mutant IDH inhibitors with immunotherapy are currently under active investigation. Conclusions: Mutant IDH inhibition is a promising, well-tolerated, and evolving approach for many patients with IDH-mutant glioma. Ongoing research will clarify its optimal clinical utility and potentially expand its indication. Full article

Background: The accurate classification of brain tumors from magnetic resonance imaging (MRI) scans is pivotal for timely clinical intervention, yet remains challenged by tumor heterogeneity, morphological variability, and imaging artifacts. Methods: This paper presents a novel hybrid approach for improved brain tumor classification and proposes a novel hybrid deep learning framework that amalgamates the hierarchical feature extraction capabilities of VGG-16, a convolutional neural network (CNN), with the global contextual modeling of FTVT-b16, a fine-tuned vision transformer (ViT), to advance the precision of brain tumor classification. To evaluate the recommended method’s efficacy, two widely known MRI datasets were utilized in the experiments. The first dataset consisted of 7.023 MRI scans categorized into four classes gliomas, meningiomas, pituitary tumors, and no tumor. The second dataset was obtained from Kaggle, which consisted of 3000 scans categorized into two classes, consisting of healthy brains and brain tumors. Results: The proposed framework addresses critical limitations of conventional CNNs (local receptive fields) and pure ViTs (data inefficiency), offering a robust, interpretable solution aligned with clinical workflows. These findings underscore the transformative potential of hybrid architectures in neuro-oncology, paving the way for AI-assisted precision diagnostics. The proposed framework was run on these two different datasets and demonstrated outstanding performance, with accuracy of 99.46% and 99.90%, respectively. Conclusions: Future work will focus on multi-institutional validation and computational optimization to ensure scalability in diverse clinical settings. Full article

Tumors are a major disease that seriously threatens human health, with their incidence and mortality rates increasing year by year. However, traditional therapies such as surgery, chemotherapy, and radiotherapy have significant limitations, including significant side effects and propensity for drug resistance. In recent years, with the rapid development of medical technology, RNA therapy has shown great potential as an emerging treatment method in anti-tumor therapy, bringing new hope for tumor treatment. RNA therapy mainly includes small interfering RNA, antisense oligonucleotides, and aptamers. Hydrogels, as a polymer material with three-dimensional network structure, have good biocompatibility and can effectively improve the efficiency of RNA delivery. This review specifically focuses on the application of hydrogels as RNA carriers in anti-tumor therapy, along with the classification, delivery advantages, and challenges. However, despite existing deficiencies in safety and targeting, hydrogel-mediated RNA delivery for tumor treatment still shows unique advantages and broad application prospects. In the future, research and cutting-edge innovations are expected to facilitate precision oncology solutions, offering superior treatment options and catalyzing the evolution of cancer management strategies. Full article

High-risk prostate cancer (PC) accounts for 50–75% of 10-year relapse after primary treatment. Routine clinicopathological parameters for PC patient stratification have proven insufficient to inform clinical decisions in this setting. Tumor genomic profiling allowed overcoming the limits of diagnostic accuracy in the field of PC, integrated with radiomic features, automated platforms, evaluation of patient-related factors (age, performance status, comorbidity) and tumor-related factors (risk class, volume, T stage). In this scenario, the use of biomarkers to guide decision-making in localized, high-risk PC is evolving actively and rapidly. Additional tests for prostate-specific antigen have demonstrated superior sensitivity and specificity for detecting clinically significant PC, as well as commercially available genomic classifiers improving the risk prediction of disease recurrence/progression/metastasis, in combination with common clinical variables. This narrative review aimed to summarize the state of the art on the utility and evolution of old and emerging biomarkers in the diagnosis and prognosis of localized, high-risk PC, and the potential for their application in clinical practice. We focused on the theoretical molecular foundation of prostate carcinogenesis and explored the impact of genomic profiling, next-generation sequencing, and artificial intelligence in the extrapolation of customized features able to predict disease aggressiveness and possibly drive personalized therapeutic decisions. Full article

Background: Esophageal cancer (EC), including esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), remains a lethal malignancy with limited molecularly tailored treatment options. Due to substantial histologic and transcriptomic differences between subtypes, therapeutic responses often vary, underscoring the need for subtype-stratified analysis and precision drug discovery. Methods: We integrated transcriptomic data from GEO and TCGA to identify differentially expressed genes (DEGs) specific to EAC, ESCC, and their shared profiles. Functional enrichment (GO, KEGG) and protein–protein interaction (PPI) network analyses were conducted to extract hub genes using DAVID, STRING, and Cytoscape. Survival associations were evaluated using TCGA-ESCA and UALCAN. Drug repurposing was performed using L1000FWD, L1000CDS2, and SigCom LINCS. Results: We identified 79, 59, and 17 hub genes in the DEG-EAC, DEG-ESCC, and DEG-EAC&ESCC datasets, respectively. In EAC, 16 novel hub genes including SCARB1, SERPINH1, and DSC2 were discovered, which had not been previously implicated in this subtype. These genes were significantly enriched in pathways related to extracellular matrix (ECM) remodeling and epithelial structure. In addition, shared hub genes across EAC and ESCC—such as COL1A1, SPARC, and MMP1—were enriched in ECM organization and cell adhesion processes, highlighting convergent tumor–stroma interactions. Drug repositioning analysis consistently prioritized MEK inhibitors, trametinib and selumetinib, as potential therapeutic candidates across all DEG datasets. Conclusions: This study presents a comprehensive, subtype-stratified transcriptomic framework for EC, identifying both unique and shared hub genes with potential functional relevance to ECM dynamics. Our findings suggest that ECM remodelers may serve as therapeutic targets, and highlight MEK inhibition as a promising, yet exploratory, repurposing strategy. While these results offer a molecular foundation for future precision oncology efforts in EC, further validation through proteomic analysis, functional studies, and clinical evaluation is warranted. Full article

Background/Objectives: Advances in understanding immune checkpoint pathways and tumor immune biology have enabled the development of immune checkpoint inhibitors (ICIs), particularly targeting the PD-1/PD-L1 axis, which has transformed cancer immunotherapy. While they have shown remarkable success in various cancer types, including melanoma, non-small cell lung cancer, and gastrointestinal malignancies, variability in patient response, immune-related adverse events (irAEs), and resistance mechanisms remain significant. This review aims to evaluate clinical pharmacology, mechanisms of action, resistance pathways, and pharmacogenomic influences shaping interindividual responses to ICIs. Methods: This comprehensive review synthesizes current literature on FDA-approved ICIs, exploring their clinical use, underlying biological mechanisms, and emerging pharmacogenomic data. It also assesses key biomarkers such as tumor mutational burden (TMB), microsatellite instability (MSI), HLA diversity, and epigenetic factors influencing ICI efficacy and safety. Results: We outline key mechanisms contributing to ICI resistance, including T cell dysfunction, altered antigen presentation, and immunosuppressive tumor microenvironment components. Furthermore, we highlight promising pharmacogenomic findings, including single-nucleotide polymorphisms (SNPs) in PD-1/PD-L1 and immune-regulatory genes, offering predictive and prognostic utility. Variability in PD-L1 expression and the role of epigenetic modifications are also addressed as challenges in treatment optimization. Conclusions: Interindividual variability in ICI response underscores the need for biomarker-driven strategies. By integrating pharmacogenomic insights with clinical pharmacology, future approaches may support more personalized and effective use of ICIs. Combination therapies and novel modalities hold promise for overcoming resistance, enhancing therapeutic efficacy, and enabling precision oncology. Full article