Kidney stone disease (KSD) is one of the most common urological diseases. The incidence of kidney stones has increased dramatically in the last few decades. Kidney stones are mineral deposits in the calyces or the pelvis, free or attached to the renal papillae. They contain crystals and organic components, and they are made when urine is supersaturated with minerals. Calcium-containing stones are the most common, with calcium oxalate as the main component of most stones. However, many of these form on a calcium phosphate matrix called Randall’s plaque, which is found on the surface of the kidney papilla. The etiology is multifactorial, and the recurrence rate is as high as 50% within 5 years after the first stone onset. There is a great need for recurrence prevention that requires a better understanding of the mechanisms involved in stone formation to facilitate the development of more effective drugs. This review aims to understand the pathophysiology and the main molecular mechanisms known to date to prevent recurrences, which requires behavioral and nutritional interventions, as well as pharmacological treatments that are specific to the type of stone.

Purpose: The addition of androgen receptor pathway inhibitors (ARPIs) to androgen deprivation therapy (ADT), with or without docetaxel (Doc), is currently recommended for metastatic, hormone-sensitive prostate cancer (mHSPC). Recently, the ARANOTE trial evaluated the efficacy and safety of Darolutamide + ADT in this setting. We aimed to update a network meta-analysis (NMA) of these combination therapies. Methods: We conducted a systematic search for RCTs on systemic therapies for mHSPC using MEDLINE, Embase, and the Web of Science Core Collection in September 2024. An NMA utilizing random-effects models was performed to compare progression-free survival (PFS), overall survival (OS), and adverse event (AE) incidence (PROSPERO: CRD42024591458). Results: A total of 12 RCTs (n = 11,954) were included in our NMAs. Triplet therapies were associated with significant improvements in PFS compared to ARPI-based doublet therapies (hazard ratio [HR]: 0.74; 95% confidence interval [CI]: 0.59–0.93; p = 0.01), but the difference did not reach the conventional levels of statistical significance for OS (HR: 0.82; 95% CI: 0.67–1.01; p = 0.059). In a subset analysis, compared to ARPI-based doublet therapies, triplet therapies showed a significant improvement in PFS in patients with high-volume disease (HR: 0.64; 95% CI: 0.47–0.88; p < 0.01), whereas no significant improvement was observed in those with low-volume disease (HR: 0.86; 95% CI: 0.45–1.67; p = 0.7). No significant difference in grade ≥ 3 AEs was observed between triplet therapies and ARPI-based doublet therapies. The main limitations include patient heterogeneity and limited follow-up in some studies. Conclusions: Triplet therapies can improve the oncologic outcomes of patients with mHSPC compared to ARPI-based doublet therapies, without significantly increasing severe AEs. These findings warrant further confirmation in a head-to-head trial powered for overall survival.

Prostate cancer (PCa) remains one of the most prevalent malignancies among men worldwide and continues to pose significant therapeutic challenges, especially in its metastatic and castration-resistant forms. Over the past two decades, the treatment paradigm has evolved from monotherapy with androgen deprivation therapy (ADT) to a multifaceted approach integrating chemotherapy, androgen receptor axis-targeted therapies (ARATs), radiopharmaceuticals, and precision medicine. This review explores the molecular underpinnings of PCa, including genetic and epigenetic alterations such as BRCA1/2, TP53, and PTEN mutations, and their role in disease progression and treatment resistance. We detail the evidence supporting the integration of systemic agents like abiraterone, enzalutamide, and darolutamide into both hormone-sensitive and castration-resistant settings. Furthermore, we highlight the expanding role of radioligand therapies, including radium-223 and Lutetium-177-labeled PSMA-617 (Lu-PSMA-617), as well as the growing impact of PARP inhibitors in genomically selected patients. The emergence of theranostic strategies and next-generation sequencing has paved the way for personalized treatment algorithms, moving toward a truly precision oncology model in PCa. This comprehensive review synthesizes current therapeutic strategies, clinical trial evidence, and future directions aimed at optimizing outcomes and quality of life for patients with advanced prostate cancer.

Renal cell carcinoma (RCC) comprises various histologically distinct subtypes, each characterized by specific genetic alterations, necessitating individualized management and treatment strategies for each subtype. An exhaustive search of the PubMed database was conducted without any filters or restrictions. Inclusion criteria encompassed original English articles focusing on molecular mechanisms of kidney cancer. On the other hand, all non-original articles and articles published in any language other than English were excluded. Hereditary kidney cancer represents 5–8% of all kidney cancer cases and is associated with syndromes such as von Hippel–Lindau syndrome, Birt–Hogg–Dubè syndrome, succinate dehydrogenase-deficient renal cell cancer syndrome, tuberous sclerosis complex, hereditary papillary renal cell carcinoma, fumarate hydratase deficiency syndrome, BAP1 tumor predisposition syndrome, and other uncommon hereditary cancer syndromes. These conditions are characterized by distinct genetic mutations and related extra-renal symptoms. The majority of renal cell carcinoma predispositions stem from loss-of-function mutations in tumor suppressor genes. These mutations promote malignant advancement through the somatic inactivation of the remaining allele. This review aims to elucidate the main molecular mechanisms underlying the pathophysiology of major syndromes associated with renal cell carcinoma. By providing a comprehensive overview, it aims to facilitate early diagnosis and to highlight the principal therapeutic options available.

Artificial intelligence (AI) is increasingly influencing the field of urologic oncology, offering novel tools to support for clinical decision-making, enhance diagnostic precision, and assist in surgical and pathological workflows. Machine learning (ML) and deep learning (DL) approaches—artificial neural networks, particularly convutional ones—have demonstrated potential across various urologic malignancies, with applications ranging from imaging interpretation and tumor grading to risk stratification and operative planning. While prostate cancer remains the most explored domain, growing interest surrounds AI’s use in bladder and renal tumors, and more recently in testicular and penile cancers. Moreover, the integration of AI into robotic surgery and medical writing is opening new frontiers in performance evaluation and patient communication. Despite these advances, critical limitations persist. Issues such as data heterogeneity, lack of external validation, ethical and legal ambiguity, and algorithmic bias continue to hinder widespread adoption. This narrative review examines current developments in AI across major genitourinary cancers, highlighting both clinical opportunities and unresolved challenges in translating these technologies into practice.