Search Results (14,693)

Approximately 7% of males globally suffer from male infertility, which is becoming more widely acknowledged as a clinical indicator of potential health hazards as well as a cause of reproductive failure. Among these, cancer has become a significant worry due to mounting evidence that spermatogenesis impairment is associated with increased risk of prostate, testicular, and other cancers. Male infertility may be an early clinical manifestation of systemic genomic instability due to shared biological pathways, such as Y-chromosome microdeletions (AZF regions), germline DNA repair defects, mutations in tumor suppressor genes (e.g., BRCA1/2, TP53), mismatch repair gene mutations (e.g., MLH1, MSH2), and dysregulated epigenetic profiles. This narrative review covers the most recent research on prognostic markers of cancer in infertile men. These include molecular biomarkers such as genetic, epigenetic, and proteomic signatures; endocrine and hormonal profiles; and clinical predictors such as azoospermia, severe oligozoospermia, and a history of cryptorchidism. The possibility of incorporating these indicators into risk stratification models for precision medicine and early cancer surveillance is highlighted. For this high-risk group, bridging the domains of andrology and oncology may allow for better counseling, earlier detection, and focused therapies. Full article

Kidney disease is a social and global health concern where early detection is crucial to reducing mortality and improving treatment outcomes. Traditional diagnostic methods are time-consuming and prone to human error. To address the issue, this study proposes an efficient automated deep learning diagnostic system using medical imaging for kidney disease detection and classification. The framework integrates DenseNet121 and EfficientNetB0 for deep feature extraction, followed by SVM, Random Forest, and XGBoost classifiers combined via soft voting. The proposed system was evaluated on 12,446 CT images encompassing four kidney classes: cyst, stone, tumor, and normal. The proposed model achieved outstanding performance metrics with an accuracy of 99.24% and an F1-score of 99%. The proposed model enables early and accurate detection of kidney disease, aiding timely treatment, especially in resource-limited settings. Full article

Perineural invasion (PNI), defined by cancer spreading or invading into the nerve, links to severe pain, recurrence, and poor prognosis. PNI contributes to nerve damage, Schwann cell activation, and sensory neuron dysfunction. Soluble tumor necrosis factor α (solTNFα) binds to TNFR1 to drive inflammation and nerve injury, playing a key role in cancer progression and pain. This study, using a mouse sciatic nerve PNI model, explored whether blocking solTNFα-TNFR1 signaling via TNFR1 knockout or pharmacological inhibition by XPro1595 could reduce PNI-associated pain. Data showed that XPro1595, but not TNFR1 knockout, reduced tumor burden, alleviated mechanical allodynia, and improved muscle function and locomotion, primarily in females. Histological analysis in females showed that XPro1595 increased the number of myelin and dendritic cells while reducing axonal damage that resulted from PNI. In the tumor zone outside the nerve truck, XPro1595 reduced T cell and increased macrophage and dendritic cell numbers. Transcriptomic analysis revealed that XPro1595 in females with PNI upregulated mitochondrial, myelination, motor function, and immune regulation gene pathways while it downregulated inflammatory, extracellular matrix, and tumor progression pathways. Overall, we demonstrated that XPro1595 exhibited antitumor, neuroprotective, and analgesic properties in female mice, likely by promoting neuronal regeneration and mitochondrial function, while reducing inflammation and extracellular remodeling. Full article

Background/Objectives: T cell bispecific antibodies (TCBs) result in the activation of T cell receptor signaling upon binding to tumor antigens providing signal 1 to T cells. To enhance and sustain their activity, a co-stimulatory signal 2 is required. Here CEACAM5-targeted 4-1BBL antibody fusion proteins for combination with CEA-TCB (cibisatamab, RG7802) are described in an investigation of the relationship between the CEACAM5 epitope and T cell activity. Methods: CEACAM5-targeted bispecific 4-1BBL antibody fusion proteins (CEA-4-1BBLs) were generated based on different CEACAM5 antibodies and characterized in vitro in Jurkat-4-1BB reporter and PBMC cell assays. The impact of shed CEA on in vitro activity and cynomolgus cross-reactivity was studied. In vivo efficacy was assessed in human stem cell humanized NSG mice xenograft models bearing MKN-45 and HPAFII tumors. Results: MFE23-4-1BBL and Sm9b-4-1BBL showed superior functional activity in Jurkat-4-1BB reporter and primary T cell assays when combined with the CD3 antibody V9, whereas T84.66-LCHA-4-1BBL and A5B7-4-1BBL performed better when combined with CEA-TCB. In humanized NSG mice MKN-45 and HPAFII xenograft models, T84.66-LCHA-4-1BBL mediated the best anti-tumor efficacy. Conclusions: For the assessment of the combination of CEA-TCB with CEA-4-1BBL, co-stimulatory antibody fusion protein in vitro assays are not sufficient to fully capture the complex relationships affecting efficacy. Thus, screening with different cell assays and in vivo efficacy studies in combination with CEA-TCB are essential to select the best candidate. Based on the totality of data on the T84.66-LCHA-4-1BBL antibody fusion protein comprising the CEACAM5 antibody, T84.66-LCHA was selected as the optimal combination partner for CEA-TCB. Full article

Background: KRAS mutations are detected in ~40% of colorectal cancer (CRC), yet their prognostic value is heterogeneous across specific substitutions; the impact of uncommon variants, particularly in non-metastatic disease, remains uncertain. Methods: We evaluated the prognostic role of the relatively infrequent KRAS G12A substitution in two independent retrospective cohorts of stage II–III CRC treated with surgical resection without neoadjuvant therapy: an institutional series (FMU; n = 299) and a public dataset (AC-ICAM; n = 178). Tumors were genotyped for KRAS (and BRAF in AC-ICAM), and relapse-free survival (RFS) and overall survival (OS) were investigated. Results: KRAS G12A comprised 3.0% (FMU) and 3.4% (AC-ICAM). Across genotypes, G12A showed the highest univariable hazards compared to wild-type (WT) references for both RFS and OS in each cohort. Notably, RFS events among G12A clustered within 12 months of surgery. In multivariable Cox models, G12A remained independently associated with worse RFS and OS in each cohort, whereas non-G12A KRAS mutations did not differ significantly from the WT references. Conclusions: Across two cohorts, KRAS G12A identified a small but clinically meaningful high-risk subset of stage II–III CRC characterized by early recurrence and inferior survival. Recognition of this variant may inform postoperative risk stratification in the adjuvant setting. Full article

This paper will present in vivo release profiles of Doxorubicin.HCl from halo-spun drug-loaded rubbery porous mats. For the very first time, Fluorescent Organism Bioimaging (FOBI) was used to follow drug release in a live animal model with induced tumors. A new predictive model based on apparent diffusion coefficients to simulate release profiles will also be presented and could have general applications for release profile predictions. Surprisingly, histological evaluation found that the tissue layer forming next to the drug-eluting mats had unordered morphology and only necrotic cells. This is a stunning contrast to the highly regular collagen structure next to mats without the drug, typical of an adverse foreign body type reaction. The findings suggest that this drug-eluting fiber mat can be used as a local chemotherapy approach coupled with mitigation of capsular contracture, the major complication associated with breast reconstruction following mastectomy. Full article

Cancers are diseases described by the irregular spread of cells that have developed invasive features, enabling them to invade adjacent tissues. The specific diagnosis and effective management of oncological treatments depend on the timely detection of circulating tumor cells (CTCs) in a patient’s bloodstream. One of the most promising approaches to CTC separation from blood fractions involves the dielectrophoresis (DEP) technique. This research presents a new DEP-based bionic system designed for MDA-MB-231 breast cancer cell isolation from white blood cell (WBC) subtypes with a viable approach to cell viability. This work leverages the principle that every cell type possesses a unique dielectric fingerprint. This dielectrophoresis microfluidic device is designed to act as a scanner, reading these fingerprints to achieve a continuous, label-free separation of cancer cells from blood components with a high efficiency. In the proposed system that consists of three different stages, the first stage allows for separating B-lymphocytes and Monocytes from Granulocytes and MDA-MB-231 cells. The separation of B-lymphocytes from Monocytes occurs in the second step, while the last step concerns the separation of Granulocytes and MDA-MB-231 cells. In the analysis, x-y graphs of the electric potentials, velocity fields, pressure distributions, and cellular DEP forces applied to the cells, as well as the resulting particle paths, are provided. The model predicts that the system operates with a separation efficiency of nearly 92%. This work focuses on an investigation of the impact of electrode potentials, the velocity of cells, the number of electrodes, the width of the channel, and the output angles on enhancing the separation efficiency of particles. Full article

Background: Artificial intelligence (AI) has the potential to significantly enhance clinical decision-making in oncology. However, its application in renal cell carcinoma (RCC) remains limited. The ART (Artificial Intelligence in Renal Tumors) project is a Spanish, multi-institutional initiative aimed at developing a dynamic, transcriptomics-based AI model to guide systemic treatment decisions for patients with metastatic RCC (mRCC). Objective: The aim of this paper is to present the rationale, methodology, and early implementation challenges of the ART project, as discussed during a dedicated Think Tank session at the 2025 International Kidney Cancer Symposium Europe (IKCSEU25), and to gather expert insights on its clinical and regulatory viability. Design, Setting, and Participants: The ART project includes three phases: (1) retrospective algorithm training using clinical and transcriptomic data from completed trials; (2) a prospective, non-interventional study collecting multi-omic and clinical data from 500 patients across 30 centers; and (3) a future comparative analysis of ART-guided versus standard clinical decisions. The AI model is designed to evolve continuously through ongoing data integration. Results and Limitations: Experts underscored the importance of integrating multimodal data—including circulating biomarkers and immune profiling—while expressing concerns about the reliance on short-term endpoints. Key barriers identified included data harmonization, external validation, and regulatory uncertainty regarding adaptive algorithms. The absence of a clear approval pathway for non-static clinical decision support systems also poses a challenge. Despite limited initial funding, the ART platform has generated strong institutional engagement and may serve as a scalable model for clinician-oriented AI tools. Conclusions: The ART project represents an innovative approach to AI-driven personalization of kidney cancer treatment. Expert feedback from IKCSEU25 highlighted the scientific robustness of the initiative, while also emphasizing the need for broader validation, regulatory clarity, and the use of clinically meaningful endpoints to support real-world implementation. Patient Summary: Experts reviewed a new AI-based tool being developed in Spain to help doctors choose the best treatments for kidney cancer. The tool shows promise but needs further testing and must meet regulatory standards before it can be used in routine clinical care. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, largely due to late diagnosis and the lack of reliable non-invasive biomarkers. Altered trace element homeostasis has been implicated in tumor biology and systemic inflammation, but comprehensive metallomic profiling in PDAC is still limited. Methods: Using inductively coupled plasma mass spectrometry (ICP-MS), we quantified 20 serum and 15 urinary metals in 71 PDAC patients and 69 matched controls. Statistical analyses included univariate Wilcoxon testing, correlation with systemic inflammatory indices (NLR, MLR, SIRI, AISI, HGB/RDW, PCT), and multivariate chemometric modeling (PCA-LDA). K-means clustering was applied to identify patient subgroups with distinct biochemical signatures. Results: PDAC patients showed significantly elevated urinary antimony, chromium, cadmium, and vanadium, whereas controls exhibited higher serum selenium, zinc, barium, vanadium, and cobalt (all p < 10⁻⁵). The PCA-LDA model achieved 99% classification accuracy (Monte Carlo cross-validation, 1000 iterations), highlighting complementary diagnostic contributions of serum and urinary profiles. Serum selenium was inversely associated with SIRI and NLR, while urinary cobalt correlated positively with NLR. Clustering revealed three PDAC subgroups with different inflammatory and metallomic patterns, suggesting underlying biological heterogeneity. Conclusions: PDAC is characterized by opposite serum-urine metal signatures, indicating altered absorption-excretion dynamics. Selenium depletion may represent a protective biomarker, whereas urinary cobalt excretion reflects systemic inflammation. This integrative ICP-MS–chemometric approach provides a promising diagnostic tool for improving early detection and patient stratification in clinical practice. Full article

Background: Colorectal cancer (CRC) remains a major global health concern, with increasing incidence and mortality projected over the coming decades. Despite the central role of staging systems, substantial heterogeneity in clinical outcomes persists among patients within the same stage, highlighting the need for additional prognostic biomarkers. This study aimed to evaluate whether segmentation-derived morphological and metabolic features of the primary tumor could serve as prognostic biomarkers associated with subsequent tumor evolution in CRC. Methods: In this retrospective, single-center study, 91 patients with histologically confirmed CRC who underwent baseline FDG PET/CT prior to treatment were analyzed. Morphological (tumor shape, cranio-caudal extension, volume) and metabolic (SUVmean, SUVmax, MTV, TLG) parameters of the primary tumor were extracted using 3D segmentation. Clinical benefit (CB) was defined according to RECIST criteria at six months. Logistic regression and Cox proportional hazards models were applied to identify predictors of short- and long-term outcomes, with performance assessed using ROC curves and Kaplan–Meier survival analyses. Results: Cranio-caudal extension was the strongest prognostic biomarker of short-term clinical benefit (AUC = 0.89), with a threshold of 6.2 cm discriminating favorable from unfavorable outcomes. In multivariate analysis, early UICC stage and lower cranio-caudal extension were independently associated with CB. For long-term outcomes, MTV emerged as a consistent prognostic factor: higher MTV predicted shorter progression-free survival (HR = 1.03, p < 0.01) and overall survival (HR = 1.03, p < 0.01). In addition, UICC stage IV significantly increased the risk of progression (HR = 9.65, p < 0.01). Conclusions: Segmentation of the primary tumor on baseline FDG PET/CT provides valuable prognostic information in CRC. While cranio-caudal extension was the strongest prognostic biomarker of short-term treatment response, MTV was independently associated with long-term outcomes, particularly progression-free survival. These findings highlight the complementary prognostic roles of morphological and metabolic tumor features and support the integration of PET/CT-based biomarkers into personalized treatment strategies for colorectal cancer. Full article

Background: Endometrial cancer (EC) is the most common gynecological malignancy in developed countries. While early-stage disease has favorable outcomes, advanced or recurrent EC remains associated with poor prognosis. Novel prognostic markers are needed to refine risk stratification. Systemic inflammation-based indices such as Pan-Immune Inflammation Value (PIV), Systemic Inflammation Response Index (SIRI), and Systemic Immune Inflammation Index (SII) have shown prognostic potential in solid tumors. Methods: We retrospectively evaluated 78 patients with endometrioid EC who had undergone hysterectomy with adnexectomy and lymphadenectomy. Demographic, clinicopathological, and laboratory data were extracted from electronic medical records. PIV, SII, and SIRI were calculated from the preoperative complete blood counts. Survival was assessed using Kaplan–Meier analysis, while prognostic factors were determined using univariate and multivariate Cox regression analyses. Results: The median age was 59 years, and 64.1% of the patients presented with early-stage disease. A high PIV (≥802) was significantly associated with a shorter overall survival (64 vs. 111 months, p < 0.001). PIV demonstrated the highest discriminatory accuracy (AUC = 0.776), followed by the SII (0.747) and SIRI (0.718). Univariate analysis identified that age, grade, LVSI, PNI, stage, distant metastasis, and high PIV, SII, SIRI, and NLR were predictors of poor survival. Multivariate analysis confirmed grade, distant metastasis and SIRI ≥ 1.5 as independent prognostic factors. Conclusions: Inflammation-based indices, particularly PIV and SIRI, correlated with survival outcomes in patients with EC. The SIRI retained an independent prognostic value, whereas PIV showed a strong discriminatory capacity. Incorporating these indices into established risk models may improve prognostic precision and support individualized management. Full article

Drug repurposing, that is, the identification of new therapeutic indications for existing medications, has been shown to be a cost-effective and time-efficient alternative to de novo drug development. This review provides a comprehensive overview of repurposed drugs in veterinary oncology, describing their mechanisms of action, current evidence of clinical benefit, and translational relevance. The therapeutic agents discussed include non-steroidal anti-inflammatory drugs (e.g., piroxicam), metabolic modulators (e.g., metformin), anti-parasitic drugs (e.g., fenbendazole), immunomodulators (e.g., thalidomide, oclacitinib), cardiovascular agents (e.g., propranolol, statins, losartan), and other compounds such as auranofin and disulfiram. A critical evaluation of the extant evidence-based data from preclinical research, naturally occurring tumor models, and clinical studies is provided, with particular emphasis on both the therapeutic potential and the current limitations. The present review also focused on combination strategies and multimodal protocols, where repurposed drugs may enhance the efficacy of chemotherapy, targeted therapies, or immunotherapy. Challenges to clinical implementation, including limited funding, regulatory and ethical considerations, and the need for well-designed, multi-institutional clinical trials, are discussed. Ultimately, drug repurposing represents a practical and translationally valuable approach to broaden therapeutic options, improve quality of life in companion animals, and advance comparative oncology by promoting progress that benefits both veterinary and human patients. Full article

Olive leaf tea (OLT), rich in phenolics, exhibits antioxidant, anti-inflammatory, and potential anticancer effects; however, the in vivo efficacy remains unclear. This study evaluated the chemopreventive and systemic effects of OLT in a murine Ehrlich Ascites Tumor (EAT) model, with a focus on the treatment timing. OLT was prepared by aqueous infusion and characterized for total phenolic content (TPC: 25.74 mg GAE/g), DPPH scavenging (197.88 µmol TE/g), FRAP activity (81.23 µmol Fe²⁺/g), and LC-MS/MS profile (oleuropein 77.6%). Mice received OLT orally before or after tumor inoculation. Prophylactic OLT reduced EAT cell counts (from 31.48 × 10⁷ to 21.15 × 10⁷), ascites volume (from 4.58 to 2.98 mL), elevated miR-155-5p (14.34-fold), normalized ALT/AST, and restored hepatic antioxidants without histopathological damage. Co-treatment with 5-FU preserved efficacy while reducing hepatotoxicity. In conclusion, OLT provides timing-dependent anticancer and systemic protective effects in the EAT model, supporting its potential as a cost-effective nutraceutical for cancer prevention and adjunctive therapy. Full article

Background: Centaurium erythraea Rafn. (C. erythraea) is a medicinal plant traditionally used in European folk medicine for the treatment of wounds, skin inflammations, and other dermatological conditions, in addition to its well-documented systemic antioxidant and anti-inflammatory effects. However, its topical applications remain insufficiently investigated, particularly using plant material collected from Romania. The purpose of this study was to prepare different ointment formulations containing C. erythraea Rafn. extract obtained from the aerial parts of the plant, using various excipients, and to evaluate their in vitro and in vivo efficacy. Methods: The phytochemical profile of C. erythraea extract was characterized using liquid chromatography–tandem mass spectrometry (LC–MS/MS). The lyophilized extract was pre-dissolved in different solubilizing agents—Transcutol^® P (diethylene glycol monoethyl ether), Capryol^® 90 (propylene glycol monocaprylate), or a combination of both—and then incorporated into five ointment formulations. Texture analysis and an in vitro membrane diffusion study were performed. The antioxidant capacity of the formulations was assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, ferric reducing antioxidant power (FRAP), and total phenolic content (TPC) assays. Anti-inflammatory activity was evaluated in vitro using tumor necrosis factor-alpha (TNF-α)-induced interleukin-1 beta (IL-1β) production in human keratinocyte (HaCaT) cells, and in vivo using a carrageenan-induced rat paw edema model. Results: LC–MS/MS identified 18 polyphenolic compounds, with hyperoside (3.78 ± 0.05 µg/mL), protocatechuic acid (1.13 ± 0.06 µg/mL), chlorogenic acid (1.07 ± 0.06 µg/mL), and quercetin (0.53 ± 0.03 µg/mL) as the principal constituents. The formulation containing both Transcutol^® P and Capryol^® 90 exhibited the most pronounced antioxidant activity (65% DPPH inhibition; 69.71 ± 0.83 mg gallic acid equivalent/mL) and significantly reduced IL-1β levels by 45.7% compared to the inflamed control. In vivo, this formulation showed comparable anti-edematous effects to a methylprednisolone ointment. Furthermore, it demonstrated the highest skin permeation efficiency, with a quercetin diffusion coefficient of 35.12 × 10⁻⁵ cm²/min. Conclusions: These findings highlight the therapeutic potential of C. erythraea extract from aerial parts in topical formulations and underscore the enhancing role of Transcutol^® P and Capryol^® 90 in improving both the pharmacodynamic and pharmacokinetic properties of bioactive compounds. Full article

Background: Non-small cell lung cancer (NSCLC) progression is driven by dysregulated competing endogenous RNA (ceRNA) networks, where non-coding RNAs sequester miRNAs to modulate oncogene expression. The tumor-suppressor miR-145 is frequently downregulated in NSCLC, but its lncRNA-mediated regulation remains incompletely characterized. Methods: Integrated transcriptomic analysis of NSCLC datasets (GSE135304: blood RNA from 712 patients; GSE203510: plasma miRNAs) was used to identify dysregulated genes (|log2FC| > 0.1, p < 0.05) and miRNAs (|log2FC| > 1, p < 0.05). Experimentally validated targets from miRTarBase/TarBase were intersected with dysregulated genes, followed by WikiPathways/GO enrichment. ceRNA networks were constructed via co-expression analysis. RT-qPCR validated miR-145-3p expression in A549/MRC-5 cells and NSCLC tissues. GEPIA assessed FN1/CCND1 clinical relevance. Results: We identified 8271 dysregulated genes and 52 miRNAs. miR-145-3p, critical in immune regulation, was significantly downregulated (log2FC = −1.24, p = 0.036). Intersection analysis revealed 27 miR-145-3p targets (e.g., FN1, CCND1, SMAD3) enriched in immune pathways (FDR < 0.05) and TGF-β-mediated EMT within the dysregulated geneset. Six immune-linked hub genes emerged. LncRNAs LOC729919 and LOC100134412 showed strong co-expression with hub genes and competitively bind miR-145-3p, derepressing the expression of the metastasis drivers FN1 (ECM regulator) and CCND1 (cell cycle controller). This ceRNA axis operates within a broader dysregulation of ATM-dependent DNA damage, Hippo signaling, and cell cycle pathways. RT-qPCR confirmed significant miR-145-3p suppression in NSCLC models (p < 0.05). GEPIA revealed a significant FN1-CCND1 co-expression (p = 0.0017). Conclusions: We characterize a novel LOC729919/LOC100134412–miR-145–FN1/CCND1 ceRNA axis in NSCLC pathogenesis. FN1’s prognostic value and functional linkage to CCND1 underscores its potential clinical relevance for therapeutic disruption. Full article