Background Papillary renal cell carcinoma (pRCC) is the most common non-clear cell RCC, and associated with poor outcomes in the metastatic setting. In this study, we aimed to comprehensively evaluate the immune tumor microenvironment (TME), largely unknown, of patients with metastatic pRCC and identify potential therapeutic targets. Methods We performed quantitative gene expression analysis of TME using Microenvironment Cell Populations-counter (MCP-counter) methodology, on two independent cohorts of localized pRCC (n=271 and n=98). We then characterized the TME, using immunohistochemistry (n=38) and RNA-sequencing (RNA-seq) (n=30) on metastatic pRCC from the prospective AXIPAP trial cohort. Results Unsupervised clustering identified two “TME subtypes”, in each of the cohorts: the “immune-enriched” and the “immune-low”. Within AXIPAP trial cohort, the “immune-enriched” cluster was significantly associated with a worse prognosis according to the median overall survival to 8 months (95% CI, 6 to 29) versus 37 months (95% CI, 20 to NA, p=0.001). The two immune signatures, Teff and JAVELIN Renal 101 Immuno signature, predictive of response to immune checkpoint inhibitors (CPI) in clear cell RCC, were significantly higher in the “immune-enriched” group (adjusted p<0.05). Finally, five differentially overexpressed genes were identified, corresponding mainly to B lymphocyte populations. Conclusion For the first time, using RNA-seq and immunohistochemistry, we have highlighted a specific immune TME subtype of metastatic pRCC, significantly more infiltrated with T and B immune population. This “immune-enriched” group appears to have a worse prognosis and could have a potential predictive value for response to immunotherapy, justifying the confirmation of these results in a cohort of metastatic pRCC treated with CPI and in combination with targeted therapies. Trial registration number NCT02489695.

Iron deficiency (ID) is very common in patients with solid tumors and may cause symptoms such as fatigue. However, its impact on clinical outcomes is poorly described. The aim of this prospective monocentric cohort study was to evaluate the evolution of quality of life (QoL) of these patients after iron supplementation. We included patients treated for a solid tumor, which were diagnosed with a functional (ferritin <800 ng/mL) or absolute (ferritin <300 ng/mL) ID (transferrin saturation coefficient <20%). The primary endpoint was patients’ QoL evolution between baseline and intermediate visit, 15-30 days after initial intravenous iron supplementation, assessed by the Functional Assessment of Cancer Therapy-Anemia (FACT-An) scale. Secondary endpoints were the same assessment between baseline, intermediate, and final visit at 6 months and the evolution of functional capacities. From 02/2014 to 12/2016, 248 patients were enrolled, of whom 186 were included in the analyses, including 140/186 (75.3%) with absolute ID. Anemia was detected in 141/174 (81.0%) patients at baseline. The FACT-An scores improved significantly between inclusion and intermediate visit (P = .001) and also between the 3 times of evaluation (P < .001). The most improved dimensions were those assessing physical, emotional well-being, and fatigue. Patients who performed the functional tests in all 3 phases had a significant improvement in performance on the majority of tests. The supplementation of ID was associated with an improvement of the QoL and functional capacities in patients with cancer. A randomized control trial is necessary to confirm our results. Our findings underline the importance of supportive care, including screening for ID, in oncology. NCT03625661.

Background: Papillary renal cell carcinoma (pRCC) is the most common non-clear cell RCC (nccRCC), representing up to 15% of RCC cases. Phase 2 trials have evaluated first-line (1 L) immunotherapy (IO)-based treatment in nccRCC, but with heterogeneous cohorts and limited comparative data. The specific value of IO for metastatic pRCC (mpRCC) remains unquantified. Methods: We analyzed prospectively collected data from the Canadian Kidney Cancer Information System (CKCis) to assess the efficacy of 1 L systemic therapy in mpRCC with IO-based regimens versus tyrosine kinase inhibitors (TKI). The primary endpoint was time-to-treatment failure (TTF). Secondary endpoints included overall survival (OS), objective response rate (ORR), and treatment-related adverse events (TRAEs). Analyses were adjusted (adj) for IMDC risk groups. Results: From 2011 to 2024, 197 mpRCC patients received 1 L therapy: 70 with IO (alone or in combination) and 127 with TKI. Median follow-up was 21.6 months. Median TTF was 9.9 months with IO vs 5.9 months with TKI (adjHR: 0.62 [0.43-0.91] p = 0.01). Median OS was 36.9 months with IO vs 23.2 months with TKI (adjHR: 0.54 [0.3-0.9], p = 0.018). ORR was 37% with IO vs 23% with TKI (adjOR: 2.2 [0.95-5.2] p = 0.07). The TKI-IO subgroup showed the longest TTF (16.9 months, adjHR: 0.47 [0.26–0.85], p = 0.01) and OS (not reached, adjHR: 0.26 [0.08–0.83], p = 0.02), compared to TKI. Grade 3–5 TRAEs occurred in 31% (IO) vs. 27% (TKI). Conclusion: This real-world study highlights the benefit of IO-based treatment in mpRCC, particularly in the TKI-IO subgroup. Our findings may inform further trials evaluating 1 L IO in mpRCC.

Background/Objectives: Ovarian cancer is a complex disease with poor outcomes that affects women worldwide. The lack of successful therapeutic options for this malignancy has led to the need to identify novel biomarkers for patient stratification. Here, we aim to develop the outcome predictors based on the gene expression data as they may serve to identify categories of patients who are more likely to respond to certain therapies. Methods: We used The Cancer Genome Atlas (TCGA) ovarian cancer transcriptomic data from 372 patients and approximately 16,600 genes to train and evaluate the deep learning survival models. In addition, we collected an in-house validation dataset of 12 patients to assess the performance of the trained survival models for their direct use in clinical practice. Despite deceptive generalization capabilities, we demonstrated how our model can be interpreted to uncover biological processes associated with survival. We calculated the contributions of the input genes to the output of the best trained model and derived the corresponding molecular pathways. Results: These pathways allowed us to stratify the TCGA patients into high-risk and low-risk groups (p-value 0.025). We validated the stratification ability of the identified pathways on the in-house dataset consisting of 12 patients (p-value 0.229) and on the external clinical and molecular dataset consisting of 274 patients (p-value 0.006). Conclusions: The deep learning-based models for survival prediction with RNA-seq data could be used to detect and interpret the gene-sets associated with survival in ovarian cancer patients and open a new avenue for future research.

Primary urethral cancer is an extremely rare malignancy, accounting for less than 1% of all cancers. Due to its rarity, evidence-based treatment recommendations are lacking. We report the case of a 44-year-old woman with metastatic squamous cell urethral carcinoma and paraneoplastic Sweet syndrome. The tumor was p16-positive with strong PD-L1 expression (CPS > 50%). Following surgery and adjuvant chemoradiotherapy, the patient developed hepatic and lymph node metastases. Pembrolizumab was initiated as first-line systemic therapy because of prior hematologic toxicity with cisplatin. After four cycles, complete radiologic remission of metastases and full resolution of the Sweet syndrome were achieved. This case highlights the potential benefit of immune checkpoint inhibitors in metastatic urethral SCC, particularly in p16-positive and PD-L1-high tumors, suggesting an inflamed and immunogenic microenvironment. To our knowledge, this is the first reported case of paraneoplastic Sweet syndrome successfully treated with pembrolizumab. These findings underscore the need for further investigation of immunotherapy in this rare and challenging malignancy.

Background: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment but may induce pseudoprogression (PP), an atypical response pattern that may mimic progressive disease (PD). Although iRECIST criteria were developed to characterize such atypical responses, distinguishing PP from PD when progression is first observed remains challenging. We aimed to characterize patients with clinically suspected PP and explore clinical and biological factors associated with subsequent classification as PP versus PD. Methods: We conducted a retrospective single-center study including patients with metastatic cancer treated with ICIs at the Institut de Cancérologie de l’Ouest (ICO) in whom PP was clinically suspected. Clinical, biological, treatment, and outcome data were collected at ICI initiation, PP suspicion, and subsequent PP/PD classification. Associations with PP versus PD were explored using univariable and multivariable logistic regression. Results: Among 123 patients with clinically suspected PP, 56 were subsequently classified as PP and 67 as PD. The most frequent primary tumors were lung (38%), kidney (24%), and bladder (11%) cancers. Median time from ICI initiation to PP suspicion was 79 days. ECOG performance status of 0 at ICI initiation was more frequent in the PP than in the PD group (55% vs. 32%; p = 0.046). At PP suspicion, median LDH levels were lower in the PP than in the PD group (189 vs. 232.5 U/L; p = 0.003). After multivariable adjustment, higher LDH levels at PP suspicion remained associated with PD (adjusted OR 2.78 per 100 U/L increase; 95% CI, 1.19–6.52; p = 0.019). Conclusions: In patients with clinically suspected PP, LDH may provide complementary information but cannot reliably distinguish PP from PD when considered alone. Confirmatory imaging therefore remains essential for treatment decision-making.