Search Results (1,407)

Background/Objectives: Cancer pain affects 55–95% of patients with advanced malignancy, representing a complex syndrome involving nociceptive, neuropathic and nociplastic mechanisms. Despite therapeutic advances, two-thirds of patients with metastatic cancer experience inadequate pain control. This scoping review synthesizes recent advances in cancer pain pathophysiology and management, focusing on molecular and cellular mechanisms, emerging pharmacological, interventional and technological therapies and key evidence gaps to inform future precision-based pain management strategies. Methods: Following PRISMA-ScR methodology, we searched PubMed, Embase, Scopus, and Web of Science for studies published between January 2022 and September 2025. After screening 3412 records, 278 studies were included and analyzed across different domains: biological mechanisms, pharmacological management, interventional and neuromodulatory approaches, radiotherapy developments, and digital health innovations. Results: Recent mechanistic research reveals cancer pain arises from tumor–neuron–immune crosstalk, with malignant cells secreting neurotrophic factors that promote axonal sprouting and nociceptor sensitization. Genetic polymorphisms and epigenetic modifications contribute to inter-individual pain variability. Management strategies are evolving toward multimodal precision medicine: NSAIDs and opioids remain foundational, complemented by adjuvant agents and interventional procedures including nerve blocks, intrathecal delivery, and neuromodulation (spinal cord and dorsal root ganglion stimulation). Stereotactic body radiotherapy demonstrates superior analgesic durability versus conventional approaches. Digital health innovations, such as mobile applications, remote monitoring, wearables, and AI-enabled predictive models, enable continuous assessment and personalized treatment optimization. Conclusions: Cancer pain management is transitioning toward mechanism-based precision medicine integrating biological insights, advanced interventional techniques, and digital technologies. However, implementation challenges persist, including limited randomized trials for interventional approaches, the incomplete external validation of AI tools, and digital health equity concerns. Future research must prioritize prospective controlled studies and equitable integration into routine care. Full article

Prostate cancer (PCa) is the leading cause of cancer-related deaths worldwide and the second most common cancer among men. Treatment options depend on factors like age, androgen sensitivity, PSA levels, Gleason score, TNM stage, and recurrence risk. Available treatments include hormonal therapy, radiation, surgery, and chemotherapy. Early immunological treatments were limited by poor lymphocyte infiltration and an immunosuppressive environment. Today, strategies such as dendritic cell vaccines, immune checkpoint inhibitors (ICIs), and adoptive cell therapy (ACT) are used. ACT, especially CAR T-cell strategies, aims to overcome traditional treatment limitations, particularly in advanced and metastatic castration-resistant prostate cancer (mCRPC), though it remains in early development. Personalized medicine uses molecular insights from the diseased tissue to tailor treatments. Variability in patient response, due to tumor heterogeneity and prior treatments, highlights the importance of personalized and combination therapies as future strategies for effective immunotherapy. This review explores the current landscape of PCa. We analyze treatment guidelines established by NCCN and EANM-ESTRO-ESUR-ISUP-SIOG. We comprehensively examine immunotherapeutic strategies currently available or under investigation for prostate cancer, with particular emphasis on ICIs, ACT with a focus on CAR T-cell therapy, combination approaches and therapeutic synergies, and predictive biomarkers of immunotherapy response. Additionally, we discuss the challenges and future directions in the implementation of immunotherapy for the management of prostate cancer. Full article

Prostate cancer (PCa) remains one of the most prevalent malignancies in men and a leading cause of cancer-related mortality worldwide. Over the last century, PCa modelling has evolved from basic cell-based to more complex systems. Despite this, the clinical translation of research findings is limited by the constraints of current preclinical models. In this review, rat and zebrafish models are highlighted due to their long-standing and emerging translational relevance, respectively. Rat models have played a pivotal role in understanding carcinogenesis and supporting the preclinical evaluation of drugs currently approved for clinical use, such as antiandrogens and androgen-deprivation agents. In parallel, zebrafish models are increasingly recognized as powerful complementary tools for studying tumor biology, metastasis, and drug response, offering unique advantages for high-throughput and personalized medicine approaches. We summarize historical milestones, current advances, and translational perspectives, emphasizing how combining multiple model systems can bridge the gap between molecular research and clinical application. Collectively, the development and refinement of these models represent essential steps toward more predictive and ethically responsible PCa research. Full article

Patient-derived organoids (PDOs) have emerged as promising preclinical models for studying tumor biology and testing therapeutic strategies in oncology. These three-dimensional culture systems retain key histological, genetic, and functional characteristics of the original tumors, offering a unique opportunity to advance personalized medicine approaches in liver cancer. In this study, we present the methodological framework and preliminary findings of a prospective study aimed at generating and characterizing PDOs from patients with hepatocellular carcinoma (HCC) undergoing surgical resection. Tumor specimens were processed using an optimized protocol for organoid derivation, expansion, and cryopreservation. We evaluated the success rate of organoid establishment and the histo-molecular fidelity to the parental tumor. These early results demonstrate promising engraftment efficiency and maintenance of tumor-specific markers across passages. Our work highlights the potential of PDOs as a reliable and scalable platform for translational research in HCC, setting the stage for future applications in drug screening and biomarker discovery. Full article

Objective: Pain is among the most common and debilitating symptoms experienced by oncology patients and has been associated with adverse mental health outcomes, including depression and suicide. Nevertheless, the relationship between pain and suicide in oncology populations remains insufficiently characterized. A clearer understanding of this interplay is essential to guide personalized approaches aimed at reducing cancer-related burden and improving quality of life. Methods: We searched PubMed and PsycInfo without imposing limits regarding publication date using pain* AND (suicid* OR “self-harm” OR “self-injurious behavior” OR “self-inflicted injury” or “self-killing”) AND (cancer* OR oncolog* OR tumor* OR neoplasm* OR metasta*). A total of 832 articles were identified, and 15 of them were included in our review. Results: Inadequately managed pain in cancer patients is associated with a significantly elevated risk of suicidal ideation. This association is further exacerbated in individuals presenting with depressive symptoms, advanced-stage disease, or limited access to timely psychological support. These factors may interact synergistically, intensifying the emotional and cognitive burden of pain, thereby increasing vulnerability in cancer patients. Conclusions: Cancer-related pain should be conceptualized as a highly variable indicator of psychological vulnerability. Factors influencing this variability include cancer type and severity, as well as the presence of past psychopathology. These findings support the need for a personalized medicine approach, whereby pain management and psychosocial interventions are tailored to patient-specific factors such as disease stage, psychological comorbidity, and access to supportive care. Full article

Cholangiocarcinoma (CCA) is a highly aggressive cancer of the biliary tract, distinguished by significant intratumoral heterogeneity (ITH), which contributes to therapy resistance and unfavorable clinical outcomes. Traditional genome profiling has revealed recurring driver changes in CCA; yet, genomic data alone fails to elucidate functional pathway activation, adaptive signaling, and the diverse treatment responses reported among tumor locations and disease subtypes. This review analyses the use of integrated sequencing technologies, proteogenomics, and phosphoproteomics to systematically characterize intratumoral heterogeneity in cholangiocarcinoma and convert molecular diversity into therapeutically applicable discoveries. We present evidence that the combination of genomic sequencing and mass spectrometry–based proteomics facilitates the direct correlation of genetic mutations with protein expression, post-translational modifications, and signaling system activity. Phosphoproteomic profiling specifically offers functional insights into kinase-driven networks that dictate tumor aggressiveness, therapeutic susceptibility, and adaptive resistance mechanisms, which cannot be anticipated only from DNA-level analysis. We propose that integrating proteogenomic and phosphoproteomic analyses into diagnostic and therapeutic assessments can enhance molecular classification, reveal subtype- and region-specific therapeutic dependencies, and guide rational combination treatment strategies, based on recent extensive proteogenomic studies and functional proteomic investigations in CCA. Pathway-level analysis of intratumoral heterogeneity provides a framework for selecting targeted medicines, predicting resistance, and informing personalized treatment strategies in CCA. The combination of sequencing, proteogenomics, and phosphoproteomics is essential for advancing precision oncology in cholangiocarcinoma. The implementation of this multi-layered analytical approach may better patient classification, refine therapy choices, and eventually improve clinical outcomes for individuals with this particular heterogeneous cancer. Full article

Background: Artificial intelligence (AI) is rapidly transforming clinical medicine by enabling earlier disease detection, personalized risk stratification, precision diagnostics, and optimized therapeutic decision-making across multiple specialties. Methods: This narrative review synthesizes the most recent evidence from prospective randomized controlled trials, large cohort studies, and real-world implementations of AI in cardiology, pulmonology, neurology, hepatology, pancreatic diseases, and other key areas of internal medicine. Studies were selected based on clinical impact, external validation, and regulatory approval status where applicable. Results: AI systems now outperform traditional clinical tools in numerous high-stakes applications: >88% freedom from atrial fibrillation at 1 year with AI-guided ablation, noninferior stent optimization versus OCT guidance, >95% sensitivity for atrial fibrillation and low ejection fraction detection on single-lead ECG, substantial increases in adenoma detection rate and melanoma triage accuracy, automated pancreatic cancer detection on routine CT with 89–90% sensitivity, and significant improvements in palliative care consultation rates and post-PCI outcomes using AI-supported telemedicine. Over 850 FDA-cleared AI devices exist as of November 2025, with cardiology and radiology dominating clinical adoption. Conclusions: AI has transitioned from experimental to clinically indispensable in multiple specialties, delivering measurable reductions in mortality, morbidity, hospitalizations, and healthcare resource utilization. Remaining challenges include external validation gaps, bias mitigation, and the need for large-scale prospective trials before universal implementation. Full article

Every year, the scientific community continues to drive advances in healthcare, opening up new perspectives in the treatment and management of various diseases. Despite vast strides being made in the quality of life and longevity, we still face an equally significant growth in the burden of oncological pathologies. Although current trends lean towards preventive and personalized medicine, numerous hurdles remain to be cleared to develop robust strategies in the field of oncology. Among all types of tumors, one of the prominent positions is occupied by hepatocellular carcinoma (HCC), which is one of the most widespread primary cancers with a high mortality rate. Conventional approaches to HCC therapy, such as surgery or chemotherapy, rarely provide steady performance due to the highly polymorphous nature of the cancerous process. In this study, we suggest an alternative methodological framework for designing potent siRNAs targeting genes implicated in hepatocellular carcinoma, implementing RNA interference mediated by synthetic small interfering RNAs (siRNAs) against mRNAs of ITGB1 and CD47 genes. Products of these genes are renowned drivers of tumor progression. We have developed a software algorithm for the design of unmodified and modified siRNAs, carried out solid-phase synthesis of the most promising molecules, and proved their capability to perform a more than 50-fold suppression of expression of the target genes in vitro. Full article

Bladder cancer (BC) represents a major global health issue with high recurrence and significant mortality rates in cases of advanced disease. Currently, the development of molecular profiling, liquid biopsy technologies, and artificial intelligence (AI) software has resulted in unprecedented opportunities to improve diagnosis, prognostic assessment, and treatment selection. Recent multicenter studies have identified emerging metabolomic, proteomic, and genomic biomarkers with high sensitivity and specificity that may help replace or complement invasive approaches. AI-driven models that combine multi-omics datasets with radiomics and clinical parameters have demonstrated improved accuracy for predicting both therapeutic response and long-term outcomes, compared to standard approaches for risk stratification. Additionally, the incremental clinical usefulness of liquid biopsy platforms has been demonstrated for the monitoring of non-muscle-invasive bladder cancer and minimal disease detection. As these innovations converge, they herald the advent of a new era of personalized management of urothelial carcinoma; however, broad-based clinical implementation will require large-scale validation, standardization, regulatory harmonization, and economic analyses. Background: Bladder cancer continues to be a global health problem, particularly in the advanced disease setting where treatment options are limited, and mortality remains high. The exciting advances in precision medicine, including breakthrough molecular profiling techniques, liquid biopsy, and opportunities to apply AI to interpret these molecular data, hold unprecedented promise in improving the accuracy of diagnosis, prognostic stratification, and therapeutic decision-making. Full article

Background/Objectives: The hypothalamic-pituitary-testis axis is known to be dysregulated in patients with hematological malignancies. However, data on the association between the type of hematological malignancies and semen quality are discordant. In the era of personalized medicine, identifying disease-specific patterns of reproductive impairment is crucial to optimize fertility preservation strategies. While patients with leukemia often show a clear deterioration in semen quality, studies on Hodgkin and non-Hodgkin lymphomas have shown that spermatogenesis is not always compromised. Indeed, some patients may present normospermia before treatment. This study aimed to assess semen parameters in males affected by hematological malignancies compared with a non-cancer population and to explore implications for individualized fertility preservation counseling. Methods: We performed a retrospective monocentric study including all patients affected by hematological malignancies who underwent fertility preservation at the Maternal and Child Department, Gynecology and Obstetrics, Oncofertility Unit, Federico II of Naples, from January 2017 through December 2024. In total, 247 patients with hematological malignancies and 63 non-cancer males undergoing in vitro fertilization for female tubal factor, selected as a control group, were included in the analysis. Sperm parameters (semen volume, sperm concentration, motility, and morphology) were first compared between the hematological malignancy group and the control group, and then among hematological malignancies classified as Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and leukemia (L). Results: Overall, according to World Health Organization (WHO, 2021) criteria, semen parameters of patients with hematological malignancies were at the 25th percentile, except for motility, which was below the 5th percentile. Significant differences were observed in sperm concentration/mL, total sperm number, and percentage of total sperm motility between the hematological malignancy group and the control group (p = 0.0004; p = 0.0003; p < 0.0001). Based on disease classification, 158 patients had Hodgkin lymphoma, 54 had non-Hodgkin lymphoma, and 35 had leukemia. Significant differences in concentration/mL and total sperm number were found between the Hodgkin lymphoma group and the control group (p = 0.003; p = 0.001). The percentage of total sperm motility was significantly decreased in all subtypes of hematological malignancies compared with controls, especially in the leukemia group (HL p = 0.001; NHL p = 0.004; L p < 0.001). Conclusions: These findings highlight significant impairment of semen quality, particularly motility, reinforcing the role of personalized medicine in tailoring fertility preservation strategies according to malignancy subtype and baseline reproductive risk. Full article

Adverse effects of chemotherapeutic agents remain a significant clinical challenge in the management of gastric cancer. Across the literature, discussions of chemotherapy consistently document a range of toxicities, underscoring that even when treatment halts disease progression, it can leave substantial clinical sequelae. Chemotherapy can impact virtually every organ system, producing multiorgan toxicity with meaningful implications for patient quality of life and treatment feasibility. When initiating a new chemotherapy regimen, prior lack of therapeutic benefit is often associated with difficult recovery or inability to tolerate subsequent chemotherapy, thereby constraining future therapeutic options. Given these considerations and the current absence of universally personalized treatment, a multidisciplinary team—comprising a medical oncologist, gastroenterologist, and internist—is essential to the planning and execution of chemotherapy regimens. We recommend that these chemotherapy regimens be administered within internal medicine departments, in collaboration with the medical oncologist and gastroenterologist, because in many cases the adverse effects outweigh the potential benefits of chemotherapy. Full article

Microfluidic cell culture systems and organ-on-a-chip platforms provide powerful tools for modeling physiological processes, disease progression, and drug responses under controlled microenvironmental conditions. These technologies rely on diverse cell culture methodologies, including 2D and 3D culture formats, spheroids, scaffold-based systems, hydrogels, and organoid models, to recapitulate tissue-level functions and generate rich, multiparametric datasets through high-resolution imaging, integrated sensors, and biochemical assays. The heterogeneity and volume of these data introduce substantial challenges in pre-processing, feature extraction, multimodal integration, and biological interpretation. Artificial intelligence (AI), particularly machine learning and deep learning, offers solutions to these analytical bottlenecks by enabling automated phenotyping, predictive modeling, and real-time control of microfluidic environments. Recent advances also highlight the importance of technical frameworks such as dimensionality reduction, explainable feature selection, spectral pre-processing, lightweight on-chip inference models, and privacy-preserving approaches that support robust and deployable AI–microfluidic workflows. AI-enabled microfluidic and organ-on-a-chip systems now span a broad application spectrum, including cancer biology, drug screening, toxicity testing, microbial and environmental monitoring, pathogen detection, angiogenesis studies, nerve-on-a-chip models, and exosome-based diagnostics. These platforms also hold increasing potential for precision medicine, where AI can support individualized therapeutic prediction using patient-derived cells and organoids. As the field moves toward more interpretable and autonomous systems, explainable AI will be essential for ensuring transparency, regulatory acceptance, and biological insight. Recent AI-enabled applications in cancer modeling, drug screening, etc., highlight how deep learning can enable precise detection of phenotypic shifts, classify therapeutic responses with high accuracy, and support closed-loop regulation of microfluidic environments. These studies demonstrate that AI can transform microfluidic systems from static culture platforms into adaptive, data-driven experimental tools capable of enhancing assay reproducibility, accelerating drug discovery, and supporting personalized therapeutic decision-making. This narrative review synthesizes current progress, technical challenges, and future opportunities at the intersection of AI, microfluidic cell culture platforms, and advanced organ-on-a-chip systems, highlighting their emerging role in precision health and next-generation biomedical research. Full article

Ferroptosis and senescence are unique cellular processes that lead to irreversible cell abnormalities and tissue damage in many diseases, such as cancer, neurodegeneration, cardiac, liver, and kidney damage. Despite distinct differences between the two processes, essential shared features in their causes and development include increased redox iron toxicity and oxidative stress, together with reduced antioxidant capacity, such as decreased glutathione levels and downregulation of glutathione peroxidase. The consequences of these toxicities include increased lipid peroxidation and aggregation, causing cell damage and death in ferroptosis, whereas in senescence, they lead to DNA and other biomolecular damage, resulting in a form of cell growth arrest with specific characteristics, such as the progressive accumulation of senescent cells across tissues in aging. Many potential therapeutic strategies have emerged to regulate ferroptosis and senescence pathways, including targeting and modulating iron toxicity and redox imbalance, and metabolic, transcriptional, genomic, and other associated pathways and factors. Experimental evidence suggests that iron chelating drugs such as deferiprone, deferoxamine, and deferasirox, and other drugs such as sorafenib, may be potential therapeutics for ferroptosis. Similarly, in senescence, in addition to iron chelating drugs that can act as senomorphic and senolytic agents, several other drugs, such as navitoclax and the combination of dasatinib and quercetin, have shown promising results in preliminary clinical trials as senolytic agents, while rapalogs and several nutraceuticals, such as quercetin, have been studied as senomorphic agents. Despite the absence of antioxidant drugs in clinical practice, the development of therapeutic strategies, including the repurposing of iron chelating drugs and the use of natural antioxidants, may be crucial for therapeutic advances in diseases associated with ferroptosis and senescence. The design of new therapeutic strategies based on the modulation of multiple targets, particularly the control of redox iron and oxidative stress toxicity using combinations of iron chelators with other drugs or nutraceuticals, may improve therapeutic outcomes in many diseases associated with ferroptosis, senescence, and aging. In each case, target selection and specific considerations may apply within the context of personalized medicine. Full article

Background and Aims: Gastric cancer (GC) remains a leading cause of cancer-related mortality, frequently diagnosed at advanced stages. High-risk features—tumor size ≥ 40 mm, cT3/cT4, nodal involvement, diffuse histology, and Borrmann type III/IV—are associated with peritoneal metastasis (PM). Staging laparoscopy with peritoneal washing (PW) is superior to conventional preoperative imaging modalities, including contrast-enhanced CT, MRI, PET/CT and endoscopic ultrasound, in detecting occult peritoneal disease. In this era of personalized medicine and expanding loco-regional strategies such as cytoreductive surgery (CRS)/Hyperthermic IntraPEritoneal Chemotherapy (HIPEC) and Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC), accurate staging is crucial. This study assessed the impact of SL and PW in high-risk GC. Methods: We retrospectively analyzed 113 consecutive high-risk GC patients who underwent SL and PW between 2014 and 2024 at our institution. The primary endpoint was detection of PM or positive cytology (CY+). Secondary endpoints were treatment modification, eligibility for loco-regional therapy, and safety. Results: SL/PW identified PM or CY+ in 26 patients (23%), including 16 with CY+ only. None had radiologic signs of peritoneal disease. SL findings altered treatment in all cases: 21 patients (81%) with Peritoneal Cancer Index (PCI) < 6 underwent induction chemotherapy followed by CRS + HIPEC; 5 patients (PCI > 6) were spared non-therapeutic laparotomy and treated with bidirectional systemic chemotherapy and PIPAC. In 10 patients, systemic therapy was shifted from FLOT (fluorouracil, leucovorin, oxaliplatin, and docetaxel) to FOLFOX (fluorouracil, leucovorin, and oxaliplatin) ± nivolumab. No perioperative complications occurred; all patients were discharged within 24 h without delay in systemic treatment. Conclusions: SL with PW is safe and significantly improves staging accuracy in high-risk GC, enabling personalized therapeutic planning. Routine integration of SL should be considered essential in treatment algorithms to guide systemic and loco-regional strategies. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for the majority of cases. Among the NSCLC subtypes, squamous cell carcinoma (SCC) is less frequently associated with actionable genetic alterations. Herein, we present the first known case of ROS1 rearrangement in pure SCC, identified using next-generation sequencing (NGS), and successfully treated with entrectinib for approximately one year. This case highlights the potential of ROS1 as a therapeutic target in SCC, which has historically been considered rare, as ROS1-rearranged SCC accounts for only 0.2% according to the Foundation Medicine database. This underscores the importance of incorporating NGS into clinical practice, particularly for never smokers/light smokers or patients with advanced SCC of the lungs, to identify targetable mutations and guide personalized therapy. Full article