Combination therapies integrating immune checkpoint inhibitors (ICIs) with vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs), or dual ICI regimens, currently represent the standard of care for advanced clear cell renal cell carcinoma (ccRCC). However, in most favorable-risk patients according to the IMDC classification-particularly those with a low disease burden and without disease-related symptoms-first-line monotherapy with VEGFR-TKIs remains a valid option. This review summarizes the preclinical and clinical evidence supporting this approach, with the aim of guiding oncologists in personalizing therapy while minimizing overtreatment and toxicity.

Survival outcome within oligoAR and sysAR subgroups

Survival outcome of the overall study population

Despite many treatment strategies available for metastatic renal cell carcinoma (mRCC), predictive biomarkers of response to immunotherapy are still needed. In this context, growing efforts have been devoted to translational research, especially focusing on the immune tumor microenvironment (I-TME). The Meet-URO 18 is a multicentric retrospective study assessing the I-TME of mRCC patients receiving ≥ 2nd line nivolumab, divided into responders and non-responders according to clinical benefit [progression-free survival ≥ 12 and ≤ 3 months]. The primary objective was to identify differential immunohistochemical and molecular patterns between the two groups. We present the transcriptomic analysis performed on primary tumor tissues using a custom NanoString panel of 66 genes from the D’Costa et al. signature, grouped into angiogenesis, T-effector response, tumor invasion, and calcium signaling. Forty-two samples (25 responders and 17 non-responders) underwent transcriptomic analysis using the NanoString 66-gene immune-oncology panel. Hierarchical clustering recapitulated the transcriptional axes described by D’Costa et al. but did not distinguish patients by immunotherapy response. No genes were significantly differentially expressed after multiple testing correction; however, CD34 showed the strongest nominal association with responder tumors and was upregulated in this group, but did not retain statistical significance after adjustment. CD34 expression also correlated with CD8+ T-cell infiltration. Our findings confirm the applicability of the D’Costa molecular signature and identify CD34 as the strongest nominally associated transcript in responder tumors, warranting further orthogonal and prospective validation.

BACKGROUND:Non-clear cell renal cell carcinoma (nccRCC) represents a heterogeneous group of rare malignancies with limited evidence guiding systemic therapy. The recent introduction of immune checkpoint inhibitors (ICIs) and their combinations with tyrosine kinase inhibitors (TKIs) has shown promising results, but real-world data remain scarce. METHODS:We retrospectively collected clinical and pathological data from patients with metastatic nccRCC included in the Italian Meet-URO-23/I-RARE database and from Vall d'Hebron Institute of Oncology (VHIO). Prognostic factors for overall survival (OS) were analyzed using univariate and multivariate Cox regression. Treatment outcomes were assessed by histology and therapeutic regimen. RESULTS:A total of 156 patients were included: papillary (56.4%), chromophobe (22.4%), translocated (10.9%), and unclassified (10.3%) RCC. Median OS was 17.5 months (95%CI 14.7-27.6) and median progression free survival (PFS) 10.2 months (95%CI 7.6-13.7). Patients treated with ICI-combinations (ICI plus ICI or ICI plus VEGF-TKI) showed significantly improved survival (median OS not reached vs 14.7 months for other regimens, p = 0.0053). The overall objective response rate (ORR) and disease free survival (DFS) for ICI+TKI was 53.3% (16/30 evaluable) and 93.3% (28/30), with ORR of 55.5% (10/18) in papillary and 46.1% (6/13) in chromophobe subtypes. In the overall ICI-combination group, ORR was 48%. In multivariate analysis, International Metastatic RCC Database Consortium (IMDC) score, presence of bone metastases, and type of first-line therapy were independently associated with OS. CONCLUSIONS:In this large international real-world cohort, ICI-based combinations demonstrated superior outcomes compared to other regimens in metastatic nccRCC. These results reinforce the role of immunotherapy combinations as a preferred first-line approach and confirm the IMDC score as a reliable prognostic tool in this population.

BACKGROUND:The immunonutritional background has been deeply implicated in cancer behavior and clinical outcomes. In this study, we explored the prognostic impact of the Controlling Nutritional Status (CONUT) score through its correlation with blood immunophenotypes and cytokines to provide an easily available non-invasive tool to predict the survival benefit from first-line immune checkpoint inhibitors±chemotherapy (ICI±CHT) in patients affected by advanced non-small cell lung cancer (aNSCLC). MATERIAL AND METHODS:From a prospective cohort of patients with aNSCLC treated with first-line ICI±CHT, clinicopathological data and baseline blood samples for the assessment of CONUT score (albumin, lymphocytes, total cholesterol), relevant immunophenotypes (flow cytometry) and cytokines (multiplex array) were collected. Correlations of CONUT score with survival outcomes (progression-free/overall survival [PFS/OS]) and circulating immune-inflammatory benchmarks were analyzed. RESULTS:Among 178 patients enrolled in the AIRC (Italian Association for Cancer Research) project, 153 received ICI±CHT as first-line. Nutritional status tested by CONUT score was available in 137 cases and was <3, meaning good nutritional status, in 77 (56.2%), whereas scored ≥3 in 60 (43.8%), meaning an impaired nutritional status. At a median follow-up of 27.4 months (95% CI 22.9 to 32.0), patients with a CONUT score <3, compared to those with CONUT score ≥3, experienced significantly longer PFS (median PFS 8.03 vs 3.88 months, HR 0.58, 95% CI 0.40 to 0.84, p=0.004) and OS (median OS 22.24 vs 8.75 months, HR 0.61, 95% CI 0.40 to 0.94, p=0.03). The multivariable analysis, adjusting for age, histology, metastatic sites, sex, programmed death-ligand 1 (PD-L1), Eastern Cooperative Oncology Group Performance Status and treatment type, confirmed the prognostic impact of CONUT score in terms of PFS (HR 0.61, 95% CI 0.41 to 0.93, p=0.02) and OS (HR 0.60, 95% CI 0.38 to 0.96 p=0.03). Patients with CONUT score ≥3 displayed significantly higher blood levels of interleukin (IL)-1β, IL-12, IL-10, interferon-γ, IL-6, and soluble PD-L1 compared with those with CONUT score <3. A higher fraction of CD14+ cells (p=0.01) and CD8+Ki67+ (p<0.001) lymphocytes also characterized the blood of patients with CONUT score ≥3 compared with those with CONUT score <3. CONCLUSION:A baseline good nutritional status (CONUT score <3) is associated with a distinct circulating immune-inflammatory profile and correlates with improved clinical outcomes in patients with aNSCLC treated with first-line ICI±CHT.

Representativeness of Study Participants

Delta radiomic profiling of oligoAR and sysAR patients

BACKGROUND:Effective risk stratification is essential for guiding treatment decisions in patients with metastatic renal cell carcinoma (mRCC). The Meet-URO score is a novel prognostic model that integrates the International Metastatic RCC Database Consortium (IMDC) criteria with neutrophil-to-lymphocyte ratio (NLR) and the presence of bone metastases. Developed in the immunotherapy era, it has demonstrated superior prognostic accuracy compared to the IMDC score across various clinical settings and treatment strategies. Its validation in the context of first-line immune-based combinations has been awaited. METHODS:External validation of Meet-URO was performed using a large retrospective real-world cohort of mRCC patients treated with first-line immune-based combinations. Secondary analyses included a comparison with the IMDC score for predicting overall survival (OS) and progression-free survival (PFS). Additionally, restricted mean survival time (RMST) was assessed. RESULTS:A total of 1,418 patients were included in the analysis: 54% received ICI-ICI regimen (nivolumab plus ipilimumab), while 46% received the ICI-TKI combination. At baseline, 52.5% of patients had an NLR ≥ 3.2, and 32% had bone metastases. After a median follow-up of 26.8 months, the median OS and median PFS were 34.7 and 11.3 months, respectively. Meet-URO demonstrated effective prognostic stratification, identifying patient groups with markedly different outcomes (median OS 11.5-51.4 months; 3-year OS 26-66%; RMST 20.0-42.8 months). Compared to IMDC, Meet-URO showed a significantly better OS (c-index 0.675 vs 0.643; Δc = 0.032, P < .001) and PFS (c-index 0.60 vs 0.58; P < .001) prediction performance. CONCLUSIONS:Meet-URO demonstrated robust prognostic accuracy. Its integration into routine clinical practice and use as a stratification factor in clinical trials may support more personalized treatment strategies and enhance clinical trial design.

Immune checkpoint inhibitors (ICIs) have improved outcomes for patients with solid tumors, but reliable predictors of overall survival (OS) are limited. This retrospective study of 146 advanced solid tumor patients treated with ICIs aims to provide a nomogram to predict 1-year (1y) OS integrating body composition (BC) parameters with standard clinicopathological (CP) features. A two-stage approach was implemented: first random survival forest models were trained and tested to evaluate the prognostic value of (a) CP features alone, (b) BC metrics alone or as newly introduced BC scores, and (c) their combination. The best predictive performance (average cumulative AUC of 0.73 in test set) was achieved by combining 12 CP features with the BC score comprising intramuscolar adipose tissue content, visceral fat area index, and the visceral-to-subcutaneous fat area index ratio. Finally, a nomogram was developed with this feature set, offering a tool for personalized risk stratification and treatment planning (mean absolute error in calibration curve of 0.03 and overall AUC of 0.76). Integrating BC parameters with CP features substantially enhances 1y OS prediction in patients receiving ICIs.

Renal cell carcinoma (RCC) is a common malignancy with limited durable responses to first-line immune checkpoint inhibitor (ICI)-based therapies. Emerging evidence implicates the gut microbiome in modulating ICI efficacy. In the investigator-initiated, randomized, double-blind placebo-controlled phase 2a TACITO trial, we evaluated whether fecal microbiota transplantation (FMT) from complete ICI responders enhances clinical outcomes in treatment-naive patients with metastatic RCC (mRCC) receiving pembrolizumab + axitinib. The primary endpoint was the rate of patients free from disease progression at 12 months after randomization (12-month progression-free survival (PFS)). Secondary endpoints were median PFS and median overall survival, objective response rate (ORR), safety and microbiome changes, after randomization. Forty-five patients randomly received donor FMT (d-FMT) or placebo FMT (p-FMT). Although the primary endpoint was not met (70 NCT04758507 . In a double-blind, placebo-controlled phase 2 trial in patients with metastatic renal cell carcinoma treated with anti-PD-1 plus a VEGFR tyrosine kinase inhibitor, donor fecal microbial transplantation (FMT) from complete responders to immunotherapy did not significantly improve the primary endpoint of 12-month progression-free survival (PFS) but did significantly improve median PFS versus placebo FMT.

Technical parameters of CT volumes selected for segmentation

425 Background: Artificial Intelligence can integrate clinic-pathological features, radiomics, genomic and transcriptomic analysis to define an optimal allocation strategy in first line treatment of metastatic renal cell carcinoma (mRCC). Methods: This is a multicenter Italian prospective translational study including patients (pts) with clear cell mRCC receiving first-line treatment as per investigator’s choice. Tumor tissue was collected at baseline, plasma samples and CT scan were collected at baseline and every 3 months until progression. Due to the short follow up, here we report the preliminary analysis of the radiomic features to identify signatures associated with Objective Response Rate (ORR). A subset of non-analytically correlated radiomic features was extracted from the selected regions of interest. This subset included first-order statistics, three-dimensional shape descriptors, and texture-based features. All features were computed on the original images using PyRadiomics v.3.1.0. The radiomic analysis pipeline consisted of feature variance filtering, multicollinearity reduction, data harmonization and standardization, and feature importance estimation through a Random Forest-based algorithm. Results: 100 pts were enrolled. For the radiomic analysis, 68 patients were included to ensure a more reliable data harmonization process and to improve the robustness of subsequent analyses. 18 (26%) received IO-IO, 38 (56%) received IO-TKI, 12 (18) received TKI monotherapy as first line treatment. According to IMDC score, 16(24%) were good risk, 39(57%) intermediate and 13(19%) poor. The most common site of metastasis were lung (55%, 38), bone (23%,16), nodes (20%, 14/68) and liver (13%, 9). In the overall population, ORR was 48% (33), 44% (18) in the IO-TKI group, 44% (8) in the IO-IO group and 42% (5) in the TKI group. The two most influential features identified by the Random Forest model were original_firstorder_Mean and original_glcm_Contrast (0.59 accuracy, 0.58 precision, 0.58 recall, 0.58 F1 score, 0.49 AUROC). Higher values of these features—reflecting increased tissue density and heterogeneity—were associated with a higher ORR. Conclusions: This preliminary analysis suggests that 2 radiomic signatures are associated with higher ORR and are promising as early biomarkers of response in mRCC. However, they do not appear to provide optimal predictive value when used alone, and should therefore be integrated with clinical, genomic, and transcriptomic data to refine predictive modeling. Acknowledgments: We thank AIRC (Associazione Italiana Ricerca sul Cancro) for the support received to conduct this trial. Clinical trial information: NCT05782400 .

Immune checkpoint inhibitor (ICI)–based combinations represent the standard first-line treatment for metastatic clear cell renal cell carcinoma (mRCC), although robust biomarkers for treatment selection remain undefined. We conducted a systematic review to identify biomarkers assessed in randomized clinical trials (RCTs) on first-line ICI-based regimens. Following PRISMA guidelines, we searched PubMed, Web of Science and Scopus (January 2018–October 2025) for phase III RCTs investigating first-line ICI-based therapies in mRCC with molecular or circulating biomarker analyses. Given heterogeneity across studies, a qualitative synthesis was performed. Sixteen reports were included. Biomarkers were assessed using immunohistochemistry, transcriptomics, genomic sequencing and blood analyses. PD-L1 expression did not reliably discriminate benefit across ICI-based combinations, although it revealed a negative prognostic influence with sunitinib and a potential predictive role for nivolumab-ipilimumab. Tumours with angiogenic signatures were consistently associated with improved outcomes, suggesting prognostic relevance, while derived limited additional benefit from ICIs. Immune-related signatures were associated with ICI response, whereas proliferation and MYC-related signatures identified disease with poor prognosis across treatments. Individual mutations (e.g. PBRM1, VHL, BAP1, PTEN) showed heterogeneous and mainly prognostic associations, whereas composite gene panels (e.g. rDM) may offer better predictive value. Circulating biomarkers, including inflammatory cytokines and KIM-1 dynamics, demonstrated promising prognostic and early predictive signals. No validated biomarker currently supports treatment selection among first-line ICI-based combinations in mRCC. Future research should prioritize adaptive, biomarker-guided trial designs integrating longitudinal multi-omic profiling and circulating biomarkers to generate clinical evidence and support personalized treatments.

BACKGROUND:Concomitant medications may impair immune checkpoint inhibitor (ICI) activity through modulation of the gut microbiome and systemic immunity. While a medication-based risk model (drug score) has been validated in pan-cancer cohorts, evidence in advanced urothelial carcinoma (aUC) remains limited. This study assessed the association between concomitant medications and survival in patients receiving avelumab maintenance in the Meet-URO 25 cohort. METHODS:We retrospectively analyzed patients with aUC treated with avelumab maintenance in several Italian centers. The drug score assigned 1 point each for antibiotics and PPIs, and 2 points for corticosteroids ≥ 10 mg prednisone equivalent. Patients were classified as good (0), intermediate (1-2), or poor (3-4) risk. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan-Meier and Cox models. RESULTS:Among 251 patients (median age 72; 82% male), use of interfering medications was low. Drug score distribution was 76.5% good, 21.9% intermediate, and 1.6% poor risk. Median PFS was 8.0, 3.9, and 2.9 months, respectively; median OS was 27.6, 14.0, and 3.4 months. Drug score, ECOG performance status, and bone metastases were independent prognostic factors. CONCLUSIONS:The drug score showed significant prognostic value in aUC patients receiving avelumab maintenance, supporting its integration into risk stratification for ICI-treated UC.

List of antibodies employed for FACS analysis

681 Background: The therapeutic landscape of metastatic Urothelial Carcinoma (mUC) is rapidly evolving, alongside increasing opportunities to analyze molecular alteration and molecular classification. FGFR alteration (FGFRa) occur in about 15-20% of mUC patients. Data from randomized-controlled THOR trial demonstrated the clinical efficacy of erdafitinib, an FGFR 1-4inhibitor, in pretreated FGFR3/2a mUC. So, real-world data (RWD) on FGFRa patients remain an unmet need. Methods: SATURNO (NCT06235268) is an Italian, multicenter, prospective, non-interventional study enrolling all mUC patients managed at the participant institutions from Nov 2023 to Sept 2025. The Web National Registry includes patients with metastatic disease or with nodal involvement not suitable to surgery. Participating institutions were selected to adequately represent different geographical area. Results: A total of 237 patients were tested for FGFRa. Among them, 171 (72%) were FGFR3/2a and 66 (28%) were FGFR wild-type (WT). In the FGFR3/2a group, 134/171 (78%) were male and 37/171 (22%) were female; 165/171 (96%) had pure urothelial carcinoma histology. The most common metastatic sites were lung (61/171, 35%), liver (21/171, 12%), bone (41/171, 24%), and retroperitoneal lymph nodes (50/171, 29%). Compared with FGFR WT patients, older age was significantly associated with FGFR3/2a (OR 1.05, 95% CI 1.02–1.09, p = 0.003). Retroperitoneal lymph node involvement was less frequent among FGFR3/2a patients (29% vs 44%, OR 0.53, 95% CI 0.29–0.95, p = 0.033). FGFR3/2a tended to be more common in upper tract urothelial carcinomas (UTUC) compared with bladder tumors (23.4% vs 12.1%, OR 2.12, 95% CI 0.98–5.15, p = 0.073). FGFR3/2a patients were less likely to receive maintenance therapy (OR 0.36, 95% CI 0.19–0.65, p < 0.001). Among patients treated with platinum-based combinations (91/171, 53%), 41/91 (45%) FGFR3a patients received avelumab maintenance compared to 31/58 (53%) in the FGFR WT subgroup. Additionally, 26/91 (29%) FGFR3a patients had primary refractory disease to platinum-based therapy, compared with 14/58 (24%) among FGFR WT patients. Conclusions: RWD from this prospective registry show that FGFR3/2a is more common in older patients and, consistent with previous reports, tends to occur more frequently in UTUC. Retroperitoneal nodal involvement, usually associated with better prognosis, is less common in FGFR3/2a. FGFR3/2a are less likely to receive avelumab maintenance therapy due to primary progression to platinum-based combination. Acknowledgments: The IT infrastructure on which the urothelial tumor registry is based was developed thanks to the unconditional support of Gilead Sciences. Clinical trial information: NCT06235268 .

Lymph node involvement in prostate cancer has major prognostic and therapeutic implications, yet conventional imaging based on size and morphology remains limited in detecting small-volume metastatic disease. Although extended pelvic lymph node dissection is considered the reference standard for nodal staging, it is invasive, associated with morbidity, and primarily diagnostic in intent. Prostate-specific membrane antigen positron emission tomography (PSMA PET) has reshaped staging by enabling molecular detection of nodal metastases, consistently demonstrating superior accuracy compared with conventional imaging. This narrative review critically evaluates the role of PSMA PET in lymph node staging, with a primary focus on primary diagnosis and selected considerations on biochemical recurrence, focusing not only on diagnostic accuracy but on clinical utility and decision-making. PSMA PET shows high specificity but moderate sensitivity for pelvic nodal metastases, with reduced performance for micrometastatic disease; therefore, a negative scan cannot reliably exclude nodal involvement in high-risk patients. Evidence indicates frequent stage migration and management changes, including refinement of surgical planning, radiotherapy target delineation, and treatment intensification strategies. However, most pivotal therapeutic trials were based on conventional imaging, and long-term outcome data validating PSMA PET-guided treatment adaptations remain limited. We discuss biological rationale, radiotracer characteristics, interpretation frameworks, guideline perspectives, real-world variability in adoption, and current limitations, including false-positive findings, PSMA heterogeneity, and lack of universal standardization. Rather than replacing established staging paradigms, PSMA PET should be integrated within a comprehensive, risk-adapted framework. Ongoing prospective trials will clarify whether molecularly defined nodal staging translates into improved oncologic outcomes and will determine its definitive role in contemporary prostate cancer management.

Metastatic renal cell carcinoma remains clinically challenging because of heterogeneous outcomes and limited predictive biomarkers for immunotherapy. We performed an explainable machine learning analysis using data from the multicenter retrospective Meet-URO 15 study, including 571 patients with metastatic renal cell carcinoma treated with second-line or later nivolumab. Clinical and inflammatory variables were used to develop classification models for disease control rate, progression-free survival at 3 and 9 months, and overall survival at 6, 18 and 24 months, as well as survival models for continuous progression-free and overall survival. Model performance was assessed using weighted F1-score for classification and concordance index for survival analysis, with interpretability provided through Shapley additive explanations. The best classification performance was observed for 6-month overall survival using a support vector machine model combined with minimum redundancy maximum relevance feature selection, achieving an F1-score of 0.81 on the test set and 0.77 in external validation. In survival analysis, random survival forest achieved a test-set concordance index of 0.68 for overall survival. Inflammatory indices, IMDC score, hemoglobin, lymphocytes and platelets consistently emerged as relevant prognostic features. These findings support explainable machine learning as a transparent approach to refine outcome prediction in immunotherapy-treated metastatic renal cell carcinoma.

Introduction Bone metastases (BMs) in patients with metastatic renal cell carcinoma (mRCC) negatively affect survival, quality of life, and increase the risk of skeletal-related events (SREs). Evidence remains limited in the era of first-line immune-based combinations. Patients and methods Meet-URO 33 is an Italian multicenter observational retrospective–prospective study enrolling mRCC patients receiving first-line therapy. The primary endpoint was overall survival (OS). Secondary endpoints included progression-free survival (PFS), clinical characterization, incidence of SREs, and impact of bone-targeting agents (BTAs). Survival was analyzed using the Kaplan–Meier method, log-rank test and Cox proportional hazards model. Results A total of 1696 patients enrolled between 2021 and 2025 were included; 526 (31%) had BMs at metastatic diagnosis. Patients with BMs more frequently had poorer performance status and unfavorable IMDC risk. The presence of BMs was associated with significantly worse OS (median 26.9 vs 102.1 months; HR 0.53, p<0.001) and worse PFS (median 14.2 vs 19.4 months; HR 0.71, p<0.001), with OS and PFS varying according to first-line regimen. Worse OS persisted across IMDC risk classes and treatment types; PFS differences were not significant in favorable/intermediate IMDC risk groups and with TKI monotherapy. Neither anatomical site nor number of BMs significantly affected OS. SRE incidence in patients with BMs was 26.8%, more frequent with spinal, rib, or other-site involvement, and more common in BTA-treated patients (22.2% vs 13.7%, p = 0.03), likely reflecting selection bias. Conclusions BMs are confirmed a negative prognostic factor in mRCC involving persistent unmet clinical needs.