Search Results (521)

The use of opioids for cancer-related pain is essential but poses significant challenges due to the risk of misuse and the development of opioid use disorder (OUD). This review takes a multidisciplinary perspective based on the current scientific literature to analyze the pharmacological mechanisms, classification, and therapeutic roles of opioids in oncology. Key risk factors for opioid misuse—including psychiatric comorbidities, prior substance use, and insufficient clinical monitoring—are discussed in conjunction with validated tools for pain assessment and international guidelines. The review emphasizes the importance of integrating toxicological, pharmacological, physiological, and public health perspectives to promote rational opioid use. Pharmacogenetic variability is explored as a determinant of treatment response and addiction risk, underscoring the value of personalized medicine. Evidence-based strategies such as early screening, psychosocial interventions, and the use of buprenorphine-naloxone are presented as effective measures for managing OUD in cancer patients. Ultimately, this work advocates for safe, patient-centered opioid prescribing practices that ensure effective pain relief without compromising safety or quality of life. Full article

Background/Objectives: Biofeedback interventions are increasingly utilized in pediatric and adult care, with evidence in treating specific medical conditions and specific symptoms. However, evidence supporting their efficacy among children and adolescents and young adults (AYAs, aged 15–39) with cancer is limited. The aims of this systematic review are to present, assess, and synthesize the existing research on biofeedback in pediatric and AYA oncology, identify gaps in biofeedback research within this population, and provide recommendations for future research and clinical implications. Methods: A systematic search for articles was conducted using six bibliographic databases—PubMed/MEDLINE (NLM), EMBASE (Elsevier), CINAHL (EBSCO), SPORTDiscus (EBSCO), PsycINFO (OVID), and PEDro (NeuRA)—with an update on 5/7/2025. Included were studies involving pediatric/AYA oncology participants (0–39 years old) and those receiving at least one biofeedback modality. The methodological quality and risk of bias among included articles were assessed using the Cochrane Risk of Bias (ROB) Tool (modified version for non-randomized studies). A narrative synthesis of included studies examined the type of cancer studied, type of biofeedback used, study designs and methodological quality, and key outcomes evaluated. Results: While the literature suggests that biofeedback may offer beneficial outcomes for managing various pediatric/AYA oncology-related symptoms, such as pain, anxiety, and fatigue, only 8 studies out of 1013 screened (<1%) met inclusion criteria. Limitations included low study quality (small sample sizes, lack of control groups, and methodological inconsistencies). Conclusions: While biofeedback shows promise as a feasible and effective intervention, there is a call to action for well-designed, methodologically rigorous studies to substantiate its effectiveness and inform evidence-based practice specifically for pediatric/AYA oncology patients and clinicians. Full article

The development of scalable, non-invasive tools to assess tumor responsiveness to structurally active immunoformulations remains a critical unmet need in solid tumor immunotherapy. Here, we introduce a real-time, ex vivo functional system to classify tumor cell lines exposed to a phospholipoproteomic platform, without relying on cytotoxicity, co-culture systems, or molecular profiling. Tumor cells were monitored using IncuCyte^® S3 (Sartorius) real-time imaging under ex vivo neutral conditions. No dendritic cell components or immune co-cultures were used in this mode. All results are derived from direct tumor cell responses to structurally active formulations. Using eight human tumor lines, we captured proliferative behavior, cell death rates, and secretomic profiles to assign each case into stimulatory, inhibitory, or neutral categories. A structured decision-tree logic supported the classification, and a Functional Stratification Index (FSI) was computed to quantify the response magnitude. Inhibitory lines showed early divergence and high IFN-γ/IL-10 ratios; stimulatory ones exhibited a proliferative gain under balanced immune signaling. The results were reproducible across independent batches. This system enables quantitative phenotypic screening under standardized, marker-free conditions and offers an adaptable platform for functional evaluation in immuno-oncology pipelines where traditional cytotoxic endpoints are insufficient. This approach has been codified into the STIP (Structured Traceability and Immunophenotypic Platform), supporting reproducible documentation across tumor models. This platform contributes to upstream validation logic in immuno-oncology workflows and supports early-stage regulatory documentation. Full article

The protein p53, often referred to as the “guardian of the genome,” is essential for preserving cellular balance and preventing cancerous transformations. As one of the most commonly altered genes in human cancers, its impaired function is associated with tumor initiation, development, and resistance to treatment. Exploring the diverse roles of p53, which include regulating the cell cycle, repairing DNA, inducing apoptosis, reprogramming metabolism, and modulating immunity, provides valuable insights into cancer mechanisms and potential treatments. This review integrates recent findings on p53′s dual nature, functioning as both a tumor suppressor and an oncogenic promoter, depending on the context. Wild-type p53 suppresses tumors by inducing cell cycle arrest or apoptosis in response to genotoxic stress, while mutated variants often lose these functions or gain novel pro-oncogenic activities. Emerging evidence highlights p53′s involvement in non-canonical pathways, such as regulating tumor microenvironment interactions, metabolic flexibility, and immune evasion mechanisms. For instance, p53 modulates immune checkpoint expression and influences the efficacy of immunotherapies, including PD-1/PD-L1 blockade. Furthermore, advancements in precision diagnostics, such as liquid biopsy-based detection of p53 mutations and AI-driven bioinformatics tools, enable early cancer identification and stratification of patients likely to benefit from targeted therapies. Therapeutic strategies targeting p53 pathways are rapidly evolving. Small molecules restoring wild-type p53 activity or disrupting mutant p53 interactions, such as APR-246 and MDM2 inhibitors, show promise in clinical trials. Combination approaches integrating gene editing with synthetic lethal strategies aim to exploit p53-dependent vulnerabilities. Additionally, leveraging p53′s immunomodulatory effects through vaccine development or adjuvants may enhance immunotherapy responses. In conclusion, deciphering p53′s complex biology underscores its unparalleled potential as a biomarker and therapeutic target. Integrating multi-omics analyses, functional genomic screens, and real-world clinical data will accelerate the translation of p53-focused research into precision oncology breakthroughs, ultimately improving patient outcomes. Full article

Background/Objectives: Despite the psychological benefits of breast reconstruction (BR) after mastectomy, uptake remains limited among women with breast cancer. This study explores psychosocial and personality predictors of BR intentions in the pre-mastectomy phase, aiming to inform strategies for mental health promotion in oncology care. Methods: This cross-sectional analysis used preoperative data from a longitudinal study at a university hospital in Greece. Women with primary breast cancer scheduled for mastectomy completed a battery of validated self-report measures, including the International Personality Item Big-Five Factor Markers (IPIP-BFFM), the Hospital Anxiety and Depression Scale (HADS), and the Short Form-36 Health Survey (SF-36). Demographic, clinical, and psychosocial data were also collected. Binary logistic regression was used to examine predictors of (a) BR information-seeking and (b) BR intention. Results: Seventy-four women participated (mean age = 61.1 years). Older age predicted lower BR intention (Exp(b) = 0.897, 95% CI: 0.829–0.970) and information-seeking (Exp(b) = 0.925, 95% CI: 0.859–0.997). Single/divorced status was associated with reduced BR information-seeking (Exp(b) = 0.053, 95% CI: 0.005–0.549). Openness to experience significantly predicted both outcomes (BR information-seeking: Exp(b) = 1.115, 95% CI: 1.028–1.209); BR intention: Exp(b) = 1.095, 95% CI: 1.016–1.181). Higher physical health-related QoL scores were associated with increased BR intention (Exp(b) = 1.039, 95% CI: 1.007–1.072), whereas higher mental health-related QoL (Exp(b) = 0.952, 95% CI: 0.912–0.994) and higher depression scores (Exp(b) = 0.797, 95% CI: 0.638–0.996) were linked to decreased BR intent. No psychological factor significantly predicted information-seeking. Conclusions: These findings underscore the value of psychosocial screening and personality-informed counseling prior to surgery. By identifying individuals less likely to seek information or consider BR, pre-mastectomy assessments can contribute to tailored, mental health-promoting interventions and support informed, patient-centered surgical decision-making. Full article

Polypharmacology, the rational design of small molecules that act on multiple therapeutic targets, offers a transformative approach to overcome biological redundancy, network compensation, and drug resistance. This review outlines the scientific rationale for polypharmacology, highlighting its success across oncology, neurodegeneration, metabolic disorders, and infectious diseases. Emphasis is placed on how polypharmacological agents can synergize therapeutic effects, reduce adverse events, and improve patient compliance compared to combination therapies. We also explore how computational methods—spanning ligand-based modeling, structure-based docking, network pharmacology, and systems biology—enable target selection and multi-target ligand prediction. Recent advances in artificial intelligence (AI), particularly deep learning, reinforcement learning, and generative models, have further accelerated the discovery and optimization of multi-target agents. These AI-driven platforms are capable of de novo design of dual and multi-target compounds, some of which have demonstrated biological efficacy in vitro. Finally, we discuss the integration of omics data, CRISPR functional screens, and pathway simulations in guiding multi-target design, as well as the challenges and limitations of current AI approaches. Looking ahead, AI-enabled polypharmacology is poised to become a cornerstone of next-generation drug discovery, with potential to deliver more effective therapies tailored to the complexity of human disease. Full article

Background and Objectives: The aim of our study was to assess the diagnostic accuracy of four imaging modalities—digital mammography (DM), digital breast tomosynthesis (DBT), ultrasound (US), and breast magnetic resonance imaging (MRI)—applied individually and in combination in early cancer detection in women with dense breasts. Methods: This single-center retrospective study was conducted from January 2021 to September 2024 at the Oncology Institute of Vojvodina in Serbia and included 168 asymptomatic and symptomatic women with dense breasts. Based on the exclusion criteria, the final number of women who were screened with all four imaging methods was 156. The reference standard for checking the diagnostic accuracy of these methods is the result of a histopathological examination, if a biopsy is performed, or a stable radiological finding in the next 12–24 months. Results: The findings underscore the superior diagnostic performance of breast MRI with the highest sensitivity (95.1%), specificity (78.7%), and overall accuracy (87.2%). In contrast, DM showed the lowest sensitivity (87.7%) and low specificity (49.3%). While the combination of DM + DBT + US demonstrated improved sensitivity to 96.3%, its specificity drastically decreased to 32%, illustrating as ensitivity–specificity trade-off. Notably, the integration of all four modalities increased sensitivity to 97.5% but decreased specificity to 29.3%, suggesting an overdiagnosis risk. DBT significantly improved performance over DM alone, likely due to enhanced tissue differentiation. US proved valuable in dense breast tissue but was associated with a high false-positive rate. Breast MRI, even when used alone, confirmed its status as the gold standard for dense breast imaging. However, its widespread use is constrained by economic and logistical barriers. ROC curve analysis further emphasized MRI’s diagnostic superiority (AUC = 0.958) compared with US (0.863), DBT (0.828), and DM (0.820). Conclusions: This study provides a unique, comprehensive comparison of all four imaging modalities within the same patient cohort, offering a rare model for optimizing diagnostic pathways in women with dense breasts. The findings support the strategic integration of complementary imaging approaches to improve early cancer detection while highlighting the risk of increased false-positive rates. In settings where MRI is not readily accessible, a combined DM + DBT + US protocol may serve as a pragmatic alternative, though its limitations in specificity must be carefully considered. Full article

This study systematically reviews the non-traditional pharmacological effects of diclofenac, a well-known nonsteroidal anti-inflammatory drug, to explore its potential for drug repositioning beyond its established analgesic and anti-inflammatory applications. A comprehensive literature search was conducted using the PubMed, Scopus and Web of Science databases, covering studies from 1981 to 2025. It was revealed that over 94% of records in Scopus and Web of Science are duplicated in PubMed, so the latter was used for the search in our study. After duplicate removal and independent screening, 89 from 1123 retrieved studies were selected for the search. The analysis revealed a broad spectrum of diclofenac’s non-traditional pharmacological activities, including neuroprotective, antiamyloid, anticancer, antiviral, immunomodulatory, antibacterial, antifungal, anticonvulsant, radioprotective, and antioxidant properties, primarily identified through preclinical In vitro and In vivo studies. These effects are mediated through diverse molecular pathways beyond cyclooxygenase inhibition, such as modulation of neurotransmitter release, apoptosis, and cellular proliferation. Diclofenac showed potential for repositioning in oncology, neurodegenerative disorders, infectious diseases, and immune-mediated conditions. Its hepatotoxicity and cardiovascular risks necessitate strategies like advanced drug formulations, dose optimization, and personalized medicine to enhance safety. Large-scale randomized clinical trials are essential to validate these findings and ensure safe therapeutic expansion. Full article

The advent of immune checkpoint inhibitors (ICIs) has revolutionized cancer treatment, significantly improving patient outcomes across multiple malignancies. Nonetheless, these therapies are associated with immune-related adverse effects, including cardiotoxicity, which remains a critical concern. This review provides a comprehensive analysis of ICI-related cardiotoxicity, encompassing its pathophysiological mechanisms, risk factors, diagnostic modalities, and management strategies. The onset of cardiotoxicity varies widely, ranging from acute myocarditis to long-term cardiovascular complications. Early identification through clinical assessment, biomarkers, and advanced imaging techniques is crucial for timely intervention. Management strategies include high-dose corticosteroids, other immunosuppressive agents, and supportive therapies, with a focus on balancing oncologic efficacy and cardiovascular safety. Additionally, rechallenging patients with ICIs following cardiotoxic events remains a complex clinical decision requiring multidisciplinary evaluation. As immunotherapy indications expand to include high-risk populations in a curative setting too, optimizing screening, prevention, and treatment strategies is essential to mitigate cardiovascular risks. A deep understanding of the molecular and clinical aspects of ICI-related cardiotoxicity will enhance patient safety and therapeutic decision-making, underscoring the need for ongoing research in this rapidly evolving field. Full article

According to the guidelines of the American Society of Clinical Oncology (ASCO) and the European Society of Medical Oncology (ESMO), the most significant genetic factor in the diagnosis and treatment of breast cancer is the mutation status of the BRCA1 and BRCA2 genes. Additional genes with a significant influence on cancer risk were selected for genetic panel screening. For these genes, the disease risk score was predicted to be greater than 20%. In clinical practice, it is observed that rare genetic variants have a significant impact in young patients, characterized by increased pathogenesis and a poorer overall prognosis. The ability to predict the potential effects of these rare variants may reveal important information regarding possible phenotypes and may also provide new insights leading to more efficacious treatments and overall improved clinical management. This paper presents the case of a 38-year-old woman with bilateral breast cancer who is likely a carrier of a pathogenic point mutation in the LZTR1 gene (LZTR1: c.1260+1del variant). With this clinical case report herein described, we intend to display the usefulness of performing detailed molecular tests in the field of genetic diagnostics for patients with breast cancer. Understanding the pathogenesis of hereditary cancer development, which is more predictable and reliable than that of sporadic tumors, will allow for the discovery of hitherto hidden intrinsic signaling pathways, facilitating replicable experimentation and thereby expediting the discovery of novel therapeutic treatments. Full article

Despite remarkable progress in cancer immunotherapy, many agents that show efficacy in murine or in vitro models fail to translate clinically. Zebrafish (Danio rerio) have emerged as a powerful complementary model that addresses several limitations of traditional systems. Their optical transparency, genetic tractability, and conserved immune and oncogenic signaling pathways enable high-resolution, real-time imaging of tumor–immune interactions in vivo. Importantly, zebrafish offer a unique opportunity to study the core mechanisms of health and sickness, complementing other models and expanding our understanding of fundamental processes in vivo. This review provides an overview of zebrafish immune system development, highlighting tools for tracking innate and adaptive responses. We discuss their application in modeling immune evasion, checkpoint molecule expression, and tumor microenvironment dynamics using transgenic and xenograft approaches. Platforms for high-throughput drug screening and personalized therapy assessment using patient-derived xenografts (“zAvatars”) are evaluated, alongside limitations, such as temperature sensitivity, immature adaptive immunity in larvae, and interspecies differences in immune responses, tumor complexity, and pharmacokinetics. Emerging frontiers include humanized zebrafish, testing of next-generation immunotherapies, such as CAR T/CAR NK and novel checkpoint inhibitors (LAG-3, TIM-3, and TIGIT). We conclude by outlining the key challenges and future opportunities for integrating zebrafish into the immuno-oncology pipeline to accelerate clinical translation. Full article

Background and Objective: Dysregulated tyrosine kinase signaling is a central driver of tumorigenesis, metastasis, and therapeutic resistance. While tyrosine kinase inhibitors (TKIs) have revolutionized targeted cancer treatment, identifying compounds with optimal bioactivity remains a critical bottleneck. This study presents a robust machine learning framework—leveraging deep artificial neural networks (dANNs), convolutional neural networks (CNNs), and structural molecular fingerprints—to accurately predict TKI bioactivity, ultimately accelerating the preclinical phase of drug development. Methods: A curated dataset of 28,314 small molecules from the ChEMBL database targeting 11 tyrosine kinases was analyzed. Using Morgan fingerprints and physicochemical descriptors (e.g., molecular weight, LogP, hydrogen bonding), ten supervised models, including dANN, SVM, CatBoost, and CNN, were trained and optimized through a randomized hyperparameter search. Model performance was evaluated using F1-score, ROC–AUC, precision–recall curves, and log loss. Results: SVM achieved the highest F1-score (87.9%) and accuracy (85.1%), while dANNs yielded the lowest log loss (0.25096), indicating superior probabilistic reliability. CatBoost excelled in ROC–AUC and precision–recall metrics. The integration of Morgan fingerprints significantly improved bioactivity prediction across all models by enhancing structural feature recognition. Conclusions: This work highlights the transformative role of machine learning—particularly dANNs and SVM—in rational drug discovery. By enabling accurate bioactivity prediction, our model pipeline can effectively reduce experimental burden, optimize compound selection, and support personalized cancer treatment design. The proposed framework advances kinase inhibitor screening pipelines and provides a scalable foundation for translational applications in precision oncology. By enabling early identification of bioactive compounds with favorable pharmacological profiles, the results of this study may support more efficient candidate selection for clinical drug development, particularly in regards to cancer therapy and kinase-associated disorders. Full article

Cancer remains a major global public health concern, driving the need for innovative therapeutic agents with intensified efficacy and safety. Growth factor receptors (GFRs), often overexpressed in cancer cells and critical in regulating cell proliferation, survival, and tumor progression, represent key targets for cancer therapy. Halophytic plants like Salicornia spp. are known for their diverse bioactive compounds with notable pharmacological properties. This study comprehensively evaluated the anti-cancer potentials of phytochemicals derived from Salicornia herbacea and Salicornia brachiata using molecular docking and ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) profiling. A total of 37 bioactive compounds from Salicornia spp. were screened against HER1, HER2, and HER4 receptors. Among them, 3,5-di-O-caffeoylquinic acid, 3-O-caffeoylquinic acid, myricetin, quercetin, stigmasterol, kaempferol, isorhamnetin, rhamnetin, and hesperitin featured strong predicted binding affinities to the HER1, HER2, and HER4 growth factor receptors, comparable to those of standard anti-cancer drugs such as gefitinib and dovitinib. Further pharmacokinetic assessments, including bioavailability and toxicity analyses, identified compounds with favorable drug-likeness properties and minimal toxicity risks, except for myricetin and quercetin. These findings underscore the potential of Salicornia-derived phytochemicals as promising candidates for the development of safe, novel, and effective anti-cancer agents targeting GFRs, contributing to the advances in precision oncology, pending further validation through in vitro and/or in vivo experiments. Full article

Background and Objectives: Systemic conversion of stage III–IV non-small-cell lung cancer (NSCLC) to a surgically resectable state with immune checkpoint inhibitors (ICIs) or tyrosine kinase inhibitors (TKIs) creates an emerging cohort of candidates for “salvage” pulmonary resection. No comprehensive evidence synthesis has yet evaluated the feasibility, safety, or oncologic value of this strategy. We aimed to systematically review peri-operative and survival outcomes of salvage lung resection following ICI or TKI therapy. Methods: MEDLINE, Embase, and PubMed were searched (inception–1 May 2025). Studies reporting ≥5 adult NSCLC patients who underwent anatomical lung resection after at least one cycle of ICI or TKI were eligible. Two reviewers screened records, extracted predefined variables, and assessed risk of bias with the Newcastle–Ottawa Scale. Pooled proportions were calculated with a random-effects model. Results: Fourteen observational series (n = 312 patients) met inclusion. Median age was 62 years (range 38–81); 58% were male. Lobectomy (63%) and segmentectomy (21%) were most frequent. Video-assisted/robotic approaches were achieved in 48%. The pooled R0 rate was 93% (95% CI 89–97%); pathologic complete response occurred in 27% (95% CI 19–36%). Major complications (Clavien–Dindo ≥ III) were 11% (95% CI 7–16%), and 30-day mortality was 1.3% (95% CI 0–3%). One-year disease-free and overall survival were 68% and 88%, respectively. Conclusions: Current evidence—albeit heterogeneous—indicates that salvage pulmonary resection after modern systemic conversion therapy is technically feasible, associated with acceptably low morbidity, and yields encouraging short-term oncologic outcomes. Prospective, registry-based studies are needed to define selection criteria and long-term benefit. Full article

Cervical cancer remains one of the main causes of female mortality, especially in middle- and low-income countries, despite efforts towards the implementation of global vaccination against human papillomavirus (HPV). The aim of this study was to review and compare the most recently published international guidelines providing recommendations on cervical cancer screening strategies among average and high-risk women. Thus, a comparative review of guidelines by the US Preventive Services Task Force (USPSTF), the American Cancer Society (ACS), the American Society of Clinical Oncology (ASCO), the World Health Organization (WHO), the Canadian Task Force on Preventive Health Care (CTFPHC), the Cancer Council Australia (CCA), and the European Guidelines (EG) was conducted. There is an overall agreement regarding the suggestions made for women younger than 21 and those older than 65, with all guidelines stating against routine screening, with the exceptions of CTFPHC and CCA that expand the age group to up to 70 and 75 years, respectively. Continuation of screening in older women is also suggested in those with a history of a precancerous lesion and those with inadequate screening. Most guidelines recommend routine screening at 30–65 years, while the WHO advises that screening should be prioritized at 30–49 years. HPV DNA testing is the method of choice recommended by most guidelines, followed by cytology as an alternative, except for CTFPHC, which refers to cytology only, with self-sampling being an acceptable method by most medical societies. Agreements exist regarding recommendations for specific groups, such as women with a history of total hysterectomy for benign reasons, women with a complete vaccination against HPV, individuals from the lesbian, gay, bisexual, transgender, and queer communities and women with multiple sexual partners or early initiation of sexual activity. On the other hand, the age group of 21–29 is addressed differently by the reviewed guidelines, while differentiations also occur in the screening strategies in cases of abnormal screening results, in women with immunodeficiency, those with in utero exposure to diethylstilbestrole and pregnant women. The development of consistent practice protocols for the most appropriate cervical cancer screening programs seems to be of major importance to reduce mortality rates and safely guide everyday clinical practice. Full article