The diagnosis of advanced tumour disease significantly impacts patients' and their family caregivers' (FCs) life, affecting the physical, emotional, and social well-being. Our study aimed to assess the burden and quality of life (QoL) of FCs of advanced cancer patients in Luxembourg. Furthermore, the acceptance and feasibility of the used questionnaires were evaluated.

A cross-sectional study was conducted over 6 months, including FCs of patients with advanced cancer receiving active treatment or best supportive care. The Short-Form Zarit Burden Interview (ZBI-12) and Short-Form Health Survey (SF-36) were used to assess FCs' burden and QoL. Sociodemographic and clinical data were collected through a self-completed questionnaire. The Pearson and Spearman correlations, t-tests, and ANOVA were performed.

One hundred FCs were invited of whom 88.0% agreed to participate, and 60.2% returned completed questionnaires. FCs reported impaired QoL across all SF-36 subscales, with health change and energy/fatigue being the most impaired. ZBI-12 scores showed a statistically significant negative correlation with SF-36 scores, particularly in health domains such as role limitations due to emotional problems and (overall) health change (Pearson's r = 0.650-0.640, p < 0.001). Higher caregiving burden was associated with significantly lower QoL, influenced by individual caregiver characteristics.

This is the first study in Luxembourg to assess burden and QoL of FCs of patients with advanced cancer. Findings demonstrate a strong association between increased caregiver burden and lower QoL. The questionnaire was highly accepted by the FCs. Regular assessments of caregiver burden and tailored support interventions by healthcare professionals are recommended.

Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lacking. We aimed to explore whether AI can enhance gastric neoplasm detection.

Participants from 24 hospitals in China from December 21, 2021, to November 11, 2023, were randomized to AI-assisted or nonassisted esophagogastroduodenoscopy. Primary outcome was detection rate of gastric neoplasms after pathologic review. Secondary outcomes included detection rate of gastric neoplasms before review, relative early gastric cancer detection ratio, detection rate of intestinal metaplasia and/or gastric atrophy before or after review, biopsy rate, number of blind spots, and procedure/inspection time. We did intention-to-treat (ITT), per-protocol, and exploratory subgroup analysis.

In the ITT cohort, 29,514 patients were enrolled. AI did not improve detection rate of gastric neoplasm after pathological review (RR, 1.13; 0.92-1.38; 1.42 vs 1.25%; P = .25). However, based on original pathology, an improvement with AI was observed (RR, 1.14; 1.0-1.28; 4.06 vs 3.57%; P = .03). AI reduced blind spots number from 2.52 to 1.07 (P < .001) and prolonged procedure and inspection time. No significant differences were observed for relative early gastric cancer detection ratio or detection rate of intestinal metaplasia and/or gastric atrophy before/after pathologic review in ITT cohort. Subgroup analysis suggested potential benefit among less experienced endoscopists and during fatigue periods. In the experimental group, AI diagnosed 100%, 91.9%, and 57.1% of pathologically confirmed gastric adenocarcinoma, high-grade, and low-grade intraepithelial neoplasia, respectively.

AI did not improve the detection rate of gastric neoplasms. Further real-world studies are needed to fully address the adaptability of AI. (Chinese Clinical Trial Registry, ChiCTR2100054449.).

Paclitaxel-induced peripheral neuropathy (PIPN) is a condition that persists chronically in more than 60% of affected individuals, and currently there are no proven PIPN prophylaxis. Pre-clinical data suggest the angiotensin-II-receptor blocker losartan may attenuate neuro-inflammation and nerve injury. This study was conducted to assess losartan's neuroprotective effect against PIPN in patients with breast cancer.

In this single-center, open-label, randomized, controlled trial, women with early-stage breast cancer scheduled for weekly paclitaxel (80 mg/mg² or 12 doses) were enrolled and randomized 1:1 to losartan 100 mg once daily plus standard care or standard care alone. The primary end point was incidence of grade 2 or higher neuropathy, per National Cancer Institute Common Terminology Criteria of Adverse Events (NCI-CTCAE v5.0). Secondary end points included time-to-neuropathy (in days), patient quality of life (QoL) assessed by Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity (FACT/GOG-NTX), pain intensity using visual-analogue scale (VAS), serum nerve growth factor (NGF) levels, and safety.

Between December 2023 and December 2024, 89 Patients Were Randomized (Losartan, n = 45; Control, n = 44). Losartan Significantly Reduced Grade ≥ 2 Neuropathy Incidence (33.3% vs. 86.4%, p < 0.001) and Delayed Its Onset (73.27 vs. 43.75 Days; Hazards Ratio [HR] = 0.2, 95% Confidence Interval [CI]: 0.11-0.35) Compared With Standard Care Alone, Respectively. At 12 Weeks, Patients Treated With Losartan Reported Superior QoL (FACT/GOG-NTX: 31.87 ± 6.43 vs. 15.45 ± 10.04; p < 0.001) and Reduced Pain Scores (Median VAS 3 vs. 8; p < 0.001) Compared With Standard Care Alone, Respectively. NGF Levels Were Comparable and Adverse Events Were Similar Between Groups.

Daily losartan reduced and delayed clinically significant paclitaxel-induced neuropathy while improving patient-reported outcomes, without additional toxicity. These findings support repurposing losartan as a low-cost PIPN prophylactic and justify validation in larger, multicenter trials.

ClinicalTrials.gov (NCT06135493).

Cholangiocarcinoma (CCA) has a complex tumor microenvironment that critically influences tumor progression and therapeutic resistance. Glycosylation abnormalities have been linked to cancer growth and progression. This work was designed to develop a prognostic model based on glycosylation-related genes (GRGs) for predicting CCA outcomes and immunotherapy responses. Glycosylation patterns in macrophage subsets of CCA were analyzed via scRNA-seq. Key genes were identified by integrating module genes from WGCNA and DEGs. A risk model for CCA was established utilizing LASSO Cox regression. In vitro tests were conducted to validate the function of PGK1. The immune checkpoint blockade group exhibited elevated M1 signature scores and higher glycosylation levels. A risk model incorporating five genes (ANXA3, PGK1, PLAUR, CREB5, SPP1) for CCA was established. The high macrophage glycosylation-related risk score group had a considerable infiltration of M0 macrophages. In vitro experiments confirmed that PGK1 advanced glycation end products accumulation, drove M2 polarization of macrophages, and increased CCA cell proliferation and migration. This work proposes a glycosylation-based risk model for predicting CCA prognosis and directing therapeutic strategies. PGK1 is highlighted as a potential therapeutic target in CCA.

Artificial intelligence (AI)-assisted three-dimensional (3D) surgical platforms, integrated with augmented reality, have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive, dynamic operating environment during uro-oncological procedures. This review aims to examine the current applications of AI in robotic uro-oncology, with a particular focus on its role in facilitating intraoperative navigation during complex surgeries.

A systematic literature search was performed across PubMed, the National Library of Medicine, MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and Google Scholar to identify relevant studies published up to July 2025. The search strategy incorporated a predefined set of keywords, including AI, machine learning, radical prostatectomy (RP), robotic-assisted radical prostatectomy (RARP), robot-assisted partial nephrectomy (RAPN), and robot-assisted radical cystectomy (RARC). Only clinical trials, full-text peer-reviewed publications, and original research articles were included. Studies were eligible for inclusion if they evaluated or described applications of AI in RARP, RAPN, or RARC.

Technological advancements have substantially transformed the field of uro-oncologic surgery. In particular, AI and AI-assisted intraoperative navigation in RARP demonstrate considerable potential to objectively assess surgical performance and predict clinical outcomes. In RAPN, the adoption of preoperative, interactive 3D virtual models for surgical planning has influenced surgical decisions, thus, enhanced precision in resection planning correlates with superior nephron-sparing outcomes and optimized selective clamping. AI applications in RARC, techniques such as augmented reality (AR) can overlay critical information on the surgical field, by facilitating navigation through complex anatomical planes and enhancing identification of critical structures.

AI appears to enhance robotic uro-oncologic procedures by increasing operative precision and supporting individualised surgical treatment strategies.

Artificial intelligence (AI) is transforming the diagnostic landscape of malignant tumors in the urinary system, including prostate cancer, bladder cancer, and renal cell carcinoma (RCC). By integrating imaging, pathology, and molecular data, AI enhances the precision and reproducibility of tumor detection, grading, and risk stratification. In prostate cancer, AI-assisted multiparametric Magnetic resonance imaging (MRI) and digital pathology systems improve lesion localization and Gleason scoring. For bladder cancer, deep learning-based cystoscopy and radiomics models from Computed tomography/magnetic resonance imaging (CT/MRI) enable real-time lesion segmentation and non-invasive biomarker prediction, such as Programmed Cell Death-Ligand 1 (PD-L1) expression. In RCC, AI, combined with CT/MRI and multi-omics data, aids in subtype classification and prognostic prediction, supporting personalized therapy. However, despite these promising advances, challenges such as data standardization, model generalizability, interpretability, and regulatory compliance hinder AI's clinical translation. This review outlines the current state of AI in urological cancer diagnosis and prognosis, its technological innovations, and the clinical challenges and opportunities that lie ahead.

Prostate-specific membrane antigen (PSMA) is a surface membrane antigen that is highly overexpressed in prostate cancer, with heterogenous expression throughout the natural history of the disease. This has generated significant interest as a potential biomarker for use in early diagnosis and treatment of prostate cancer. We reviewed the literature surrounding PSMA and its current clinical applications in diagnosing and managing early prostate cancer that is confined to the prostate and local lymph nodes. A search on PubMed, Medline, and Web of Science was performed using the following keywords: "PSMA", "Prostate Specific Membrane Antigen", "Prostate cancer", "Biomarker", "Diagnosis". We considered all available articles relevant to the topic of PSMA as a biomarker in early prostate cancer when developing this narrative review. Key articles assessing the biology of PSMA, as well as its use as a potential diagnostic and therapeutic target in early prostate cancer, were assessed. The role of PSMA PET as a potential diagnostic and risk stratification tool was assessed. The current use of antibody-drug conjugates and radioligand therapy targeting PSMA was assessed, along with any current evidence to support their use in early prostate cancer. PSMA is heavily expressed throughout the early stages of prostate cancer, and this has significant therapeutic implications. There is a growing body of evidence that shows PSMA PET can play a role in the diagnosis, risk stratification, and prognostication of localised prostate cancer. PSMA-targeted therapies such as Lu-177 currently do not have any proven benefit in treating early prostate cancer; however, this remains an area of ongoing research.

This review explores nanocapsules as a versatile platform to overcome the limitations of drug resistance inherent in conventional cancer therapy and immunotherapy. These nanosystems are capable of enhancing drug delivery, facilitating immune activation and modulating the tumor microenvironment. The review systematically classifies nanocapsules into distinct categories, including bacterial carriers, protein frameworks, lipids, metals, inorganic non-metals and polymers. Key findings demonstrate that nanocapsules possess the capacities for targeted delivery, stimuli-responsive release and synergistic combination with chemotherapy, radiotherapy, as well as photodynamic/photothermal therapy. However, several hurdles remain for their clinical translation, namely insufficient clinical trials and challenges in production scalability. In addition, the review discusses the impacts of different physical properties of nanocapsules and the underlying mechanisms of drug resistance. By uniquely integrating the classification of nanocapsules with corresponding therapeutic strategies, this review provides valuable insights for improving the efficacy of tumor immunotherapy.

Severe hyponatremia is a common complication (21.6%) in patients with decompensated cirrhosis. It can sometimes manifest as a paraneoplastic syndrome, which may precede the diagnosis of cancer in 5% of cases. It can be associated with lung cancer (25 - 45%), colorectal cancer, breast cancer, or lymphomas. Hyponatremia reflects the complexity of the interactions between liver disease and oncological processes. In decompensated cirrhotic patients, hyponatremia is usually caused by the kidney´s inability to excrete free water, resulting in dilution of blood sodium. However, in the context of cancer, factors such as ectopic antidiuretic hormone secretion by tumors can exacerbate this condition. This inappropriate antidiuretic hormone secretion can lead to additional water retention, worsening the hyponatremia in these patients. We present two clinical cases that illustrate this relationship: a patient with liver metastases and a patient with pulmonary nodules, both with compensated cirrhosis as a chronic disease, who were admitted with severe hyponatremia. The management of these patients requires a multidisciplinary approach, searching for occult neoplasms and carefully normalizing sodium levels to prevent neurological complications. Early identification of hyponatremia is crucial due to its prognostic impact.

Primary mediastinal seminoma is a rare germ cell tumor that predominantly affects young men. Clinical presentation is variable, and diagnosis relies on imaging studies, tumor markers, and histopathological confirmation. This case report describes the diagnostic and therapeutic approach in a patient with mediastinal seminoma, in accordance with CARE guidelines.

A 33-year-old man presented with hoarseness, progressive dyspnea, dysphagia, and cough. Diagnostic investigation revealed a large mass in the anterior and middle mediastinum, which was confirmed as seminoma by biopsy and immunohistochemical analysis. Treatment with cisplatin-based chemotherapy (BEP regimen) resulted in a favorable response and significant tumor reduction.

Early diagnosis and appropriate treatment of primary mediastinal seminoma are essential for achieving a favorable prognosis.