Explore the vast range of titles available.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet. Prostate cancer progression may be enhanced by a high-fat diet. Here the authors show that a diet high in saturated fats enhance the MYC-driven transcriptional program, a feature that independently predicts prostate cancer progression and death.

IntroductionProstate cancer diagnosis and treatment planning depend on accurate histopathological assessment of needle biopsies, particularly through the Gleason scoring system. The inherently subjective nature of the grading creates variability between pathologists, potentially resulting in suboptimal patient management decisions. These reproducibility challenges extend beyond Gleason scoring to encompass other critical diagnostic and prognostic markers, including cancer volume quantification and detection of cribriform morphology patterns and perineural invasion. Artificial intelligence (AI) applications in digital pathology have emerged as promising solutions for enhancing diagnostic consistency and accuracy, with recent research demonstrating that automated systems can match expert-level performance in prostate biopsy evaluation. Nevertheless, comprehensive validation studies have revealed concerning limitations in model generalisability when deployed across different clinical environments and patient populations. Recent systematic reviews revealed widespread risk-of-bias limitations and insufficient external validation in AI diagnostic studies, highlighting critical needs for accumulated evidence supporting generalisability before clinical implementation. Rigorous external validation with preregistered protocols using independent datasets from diverse clinical settings remains essential to establish the reliability and safety of AI-assisted prostate pathology systems.Methods and analysisThis study protocol establishes a framework for the retrospective external validation of an AI system developed for prostate biopsy assessment, to be conducted on the case-control samples of the National Prostate Cancer Register of Sweden, ProMort study (1998-2015). The primary aim is to evaluate the AI model’s diagnostic accuracy and Gleason grading performance using completely independent datasets separate from any model development or previously used validation cohorts. The diversity of the validation samples, spanning multiple geographic regions, temporal collection periods and reference standards, allows evaluation of model robustness across varied clinical contexts. Secondary aims encompass evaluating AI performance in cancer length estimation and detection of cribriform patterns and perineural invasion. This protocol delineates procedures for data collection, reference standard clarification and prespecified statistical analyses, ensuring comprehensive validation and reliable performance assessment. The study design conforms to established reporting guidelines Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Standards for Reporting Diagnostic Accuracy Studies using Artificial Intelligence (STARD-AI), and recognised best practices for AI validation in medical imaging.Ethics and disseminationData collection and usage were approved by the Swedish Regional Ethics Review Board and the Swedish Ethical Review Authority (permits 2012/1586-31/1, 2016/613-31/2, 2019-01395, 2019-05220). The study adheres to the Declaration of Helsinki principles, and findings will be made available in open access peer-reviewed publications.

Virtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998–2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen’s kappa and Bland and Altman’s limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice.

Urothelial carcinoma (UC) is a frequent cause of cancer-related deaths worldwide. Metastatic UC has been historically associated with poor prognosis, with a median overall survival of approximately 15 months and a 5-year survival rate of 18%. Although platinum-based chemotherapy remains the mainstay of medical treatment for patients with metastatic UC, chemotherapy clinical trials produced modest benefit with short-lived, disappointing responses. In recent years, the better understanding of the role of immune system in cancer control has led to the development and approval of several immunotherapeutic approaches in UC therapy, where immune checkpoint inhibitors have been revolutionizing the treatment of metastatic UC. Because of a better tumor molecular profiling, FGFR inhibitors, PARP inhibitors, anti-HER2 agents, and antibody drug conjugates targeting Nectin-4 are also emerging as new therapeutic options. Moreover, a wide number of trials is ongoing with the aim to evaluate several other alterations and pathways as new potential targets in metastatic UC. In this review, we will discuss the recent advances and highlight future directions of the medical treatment of UC, with a particular focus on recently published data and ongoing active and recruiting trials.

The rapid evolution of digital pathology has enabled large-scale data acquisition, driving sophisticated clinical research and advancing the development of AI-driven tools. These innovations have also revolutionised histopathological slide review, especially the annotation step (i.e. the process of marking specific areas of interest on glass-mounted tissue samples to add relevant clinical information) by digitising the process, enhancing precision and efficiency, and facilitating collaboration. However, currently available open-source annotation tools typically employ single-label approaches that provide a flat representation of whole-slide images (WSI), limiting their ability to capture the complexity of the diagnosis-significant elements in a detailed and structured way. Furthermore, the difficulty of strictly following precise review protocols and lack of provenance tracking during annotation processes can result in high variability and limit reproducibility and reusability of the collected data. In this work we present the CRS4 Digital Pathology Platform (CDPP), an open-source system for research studies that manages WSI collections and focuses on high-quality, structured annotations, gathered according to well-defined protocols. Its main features include: (1) structured, multi-label morphological and clinical image annotation; (2) support for controlled but customisable annotation protocols; (3) dedicated annotation tools to facilitate enhanced accuracy, efficiency and consistency in the annotation process; and (4) workflow-based computational analysis with integrated provenance tracking. We show how the platform has successfully supported three different studies, demonstrating the CDPP’s ability to assist pathologists in the generation of high-quality annotated datasets, also suitable for reuse, in the context of digital pathology research.

IntroductionImmune checkpoint inhibitors (ICIs) have transformed the therapeutic landscape of advanced non-small cell lung cancer (NSCLC), offering durable survival in selected patients. However, ICIs can induce immune-related adverse events (irAEs), among which pneumonitis represents one of the most clinically significant due to its potential severity and diagnostic challenges. Different radiological patterns have been reported, although they may overlap with infectious or radiation-induced lung injury, complicating a timely diagnosis.ResultsWe report two cases of young patients with metastatic NSCLC and high PD-L1 expression who achieved long-term benefit from first-line pembrolizumab but were burdened by severe immune-related pneumonitis. Imaging findings in both patients were suggestive of organizing pneumonia associated with the presence of the so-called “atoll sign” (or reversed halo sign), a radiological feature rarely reported in the context of ICI-related pneumonitis. In both cases, the diagnosis was supported by imaging, microbiological tests, and histology. The subsequent administration of high-dose steroids led to rapid relief of symptoms associated with radiological improvement. Despite pembrolizumab discontinuation, both patients maintained durable systemic disease control.ConclusionThese cases emphasize the importance of recognizing uncommon radiological patterns such as the atoll sign in patients receiving ICIs, highlighting the need for vigilance even after prolonged therapy and underscoring the potential for sustained oncologic benefit despite treatment discontinuation.

While progression from normal prostatic epithelium to invasive cancer is driven by molecular alterations, tumor cells and cells in the cancer microenvironment are co-dependent and co-evolve. Few human studies to date have focused on stroma. Here, we performed gene expression profiling of laser capture microdissected normal non-neoplastic prostate epithelial tissue and compared it to non-transformed and neoplastic low-grade and high-grade prostate epithelial tissue from radical prostatectomies, each with its immediately surrounding stroma. Whereas benign epithelium in prostates with and without tumor were similar in gene expression space, stroma away from tumor was significantly different from that in prostates without cancer. A stromal gene signature reflecting bone remodeling and immune-related pathways was upregulated in high compared to low-Gleason grade cases. In validation data, the signature discriminated cases that developed metastasis from those that did not. These data suggest that the microenvironment may influence prostate cancer initiation, maintenance, and metastatic progression. Stromal cells contribute to tumor development but the mechanisms regulating this process are still unclear. Here the authors analyze gene expression profiles in the prostate and show that stromal gene signature changes ahead of the epithelial gene signature as prostate cancer initiates and progresses.

In the last decade, immunotherapy has revolutionized the treatment landscape of several hematological and solid malignancies, reporting unprecedented response rates. Unfortunately, this is not the case for metastatic castration-resistant prostate cancer (mCRPC), as several phase I and II trials assessing programmed death receptor 1 (PD-1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors have shown limited benefits. Moreover, despite sipuleucel-T representing the only cancer vaccine approved by the Food and Drug Administration (FDA) for mCRPC following the results of the IMPACT trial, the use of this agent is relatively limited in everyday clinical practice. The identification of specific histological and molecular biomarkers that could predict response to immunotherapy represents one of the current challenges, with an aim to detect subgroups of mCRPC patients who may benefit from immune checkpoint monoclonal antibodies as monotherapy or in combination with other anticancer agents. Several unanswered questions remain, including the following: is there—or will there ever be—a role for immunotherapy in prostate cancer? In this review, we aim at underlining the failures and promises of immunotherapy in prostate cancer, summarizing the current state of art regarding cancer vaccines and immune checkpoint monoclonal antibodies, and discussing future research directions in this immunologically “cold” malignancy.

Background Non-Small Cell Lung Cancer (NSCLC) is the leading cause of cancer death worldwide. Although immune checkpoint inhibitors (ICIs) have shown remarkable clinical efficacy, they can also induce a paradoxical cancer acceleration, known as hyperprogressive disease (HPD), whose causative mechanisms are still unclear. Methods This study investigated the mechanisms of ICI resistance in an HPD-NSCLC model. Two primary cell cultures were established from samples of a NSCLC patient, before ICI initiation (“baseline”, NSCLC-B) and during HPD (“hyperprogression”, NSCLC-H). The cell lines were phenotypically and molecularly characterized through immunofluorescence, Western Blotting and RNA-Seq analysis. To assess cell plasticity and aggressiveness, cellular growth patterns were evaluated both in vitro and in vivo through 2D and 3D cell growth assays and patient-derived xenografts establishment. In vitro investigations, including the evaluation of cell sensitivity to interferon-gamma (IFN-γ) and cell response to PD-L1 modulation, were conducted to explore the influence of these factors on cell plasticity regulation. Results NSCLC-H exhibited increased expression of specific CD44 isoforms and a more aggressive phenotype, including organoid formation ability, compared to NSCLC-B. Plastic changes in NSCLC-H were well described by a deep transcriptome shift, that also affected IFN-γ–related genes, including PD-L1. IFN-γ–mediated cell growth inhibition was compromised in both 2D-cultured NSCLC-B and NSCLC-H cells. Further, the cytokine induced a partial activation of both type I and type II IFN-pathway mediators, together with a striking increase in NSCLC-B growth in 3D cell culture systems. Finally, low IFN-γ doses and PD-L1 modulation both promoted plastic changes in NSCLC-B, increasing CD44 expression and its ability to produce spheres. Conclusions Our findings identified plasticity as a relevant hallmark of ICI-mediated HPD by demonstrating that ICIs can modulate the IFN-γ and PD-L1 pathways, driving tumor cell plasticity and fueling HPD development.

PurposeThe conventional imaging flowchart for prostate cancer (PCa) staging may fail in correctly detecting lymph node metastases (LNM). Pelvic lymph node dissection (PLND) represents the only reliable method, although invasive. A new amino acid PET compound, [18F]-fluciclovine, was recently authorized in suspected PCa recurrence but not yet included in the standard staging work-up of primary PCa. A prospective monocentric study was designed to evaluate [18F]-fluciclovine PET/CT diagnostic performance for preoperative LN staging in primary high-risk PCa.MethodsConsecutive patients (pts) with biopsy-proven PCa, standard staging (including [11C]choline PET/CT), eligible for PLND, were enrolled to undergo an investigational [18F]-fluciclovine PET/CT. Nodal uptake higher than surrounding background was reported by at least two readers (blinded to [11C]choline) using a visual 5-point scale (1–2 probably negative; 4–5 probably positive; 3 equivocal); SUVmax, target-to-background (aorta—A; bone marrow—BM) ratios (TBRs), were also calculated. PET results were validated with PLND. [18F]-fluciclovine PET/CT performance using visual score and semi-quantitative indexes was analyzed both per patient and per LN anatomical region, compared to conventional [11C]choline and clinical predictive factors (to note that diagnostic performance of [18F]-fluciclovine was explored for LNM but not examined for intrapelvic or extrapelvic M1 lesions).ResultsOverall, 94 pts underwent [18F]-fluciclovine PET/CT; 72/94 (77%) high-risk pts were included in the final analyses (22 pts excluded: 8 limited PLND; 3 intermediate-risk; 2 treated with radiotherapy; 4 found to be M1; 5 neoadjuvant hormonal therapy). Median LNM risk by Briganti nomogram was 19%. LNM confirmed on histology was 25% (18/72 pts). Overall, 1671 LN were retrieved; 45/1671 (3%) LNM detected. Per pt, median no. of removed LN was 22 (mean 23 ± 10; range 8–51), of LNM was 2 (mean 3 ± 2; range 1–10). Median LNM size was 5 mm (mean 5 ± 2.5; range 2–10). On patient-based analyses (n = 72), diagnostic performance for LNM resulted significant with [18F]-fluciclovine (AUC 0.66, p 0.04; 50% sensitivity, 81% specificity, 47% PPV, 83% NPV, 74% accuracy), but not with [11C]choline (AUC 0.60, p 0.2; 50%, 70%, 36%, 81%, and 65% respectively). Briganti nomogram (OR = 1.03, p = 0.04) and [18F]-fluciclovine visual score (≥ 4) (OR = 4.27, p = 0.02) resulted independent predictors of LNM at multivariable analyses. On region-based semi-quantitative analyses (n = 576), PET/CT performed better using TBR parameters (TBR-A similar to TBR-BM; TBR-A fluciclovine AUC 0.61, p 0.35, vs choline AUC 0.57 p 0.54; TBR-BM fluciclovine AUC 0.61, p 0.36, vs choline AUC 0.58, p 0.52) rather than using absolute LN SUVmax (fluciclovine AUC 0.51, p 0.91, vs choline AUC 0.51, p 0.94). However, in all cases, diagnostic performance was not statistically significant for LNM detection, although slightly in favor of the experimental tracer [18F]-fluciclovine for each parameter. On the contrary, visual interpretation significantly outperformed PET semi-quantitative parameters (choline and fluciclovine: AUC 0.65 and 0.64 respectively; p 0.03) and represents an independent predictive factor of LNM with both tracers, in particular [18F]-fluciclovine (OR = 8.70, p 0.002, vs OR = 3.98, p = 0.03).ConclusionIn high-risk primary PCa, [18F]-fluciclovine demonstrates some advantages compared with [11C]choline but sensitivity for metastatic LN detection is still inadequate compared to PLND. Visual (combined morphological and functional), compared to semi-quantitative assessment, is promising but relies mainly on readers’ experience rather than on unquestionable LN avidity.Trial registrationEudraCT number: 2014–003,165-15