Search Results (663)

Background/Objectives: Tissue fold artifacts observed in hematoxylin-eosin (H&E)- stained preparations used in histology education can complicate the assessment of normal tissue architecture and affect students’ accurate interpretation of microscopic structures. This study aimed to automatically detect and localize tissue fold artifacts in histology teaching preparations using deep learning methods. Methods: A total of 2127 hematoxylin and eosin (H&E)-stained histological images of brain, kidney, liver, small intestine, and testis tissues obtained at 10× magnification were used in the study. The dataset consisted of 899 clean/artifact-free images and 1228 images containing tissue fold artifacts. Seven deep learning architectures, including convolutional neural networks (CNN)-based models and a vision transformer-based model, were evaluated for image-level classification: ResNet18, ResNet50, DenseNet121, EfficientNet-B0, EfficientNet-B3, ConvNeXt-Tiny, and Swin-Tiny. Classification performance was evaluated using an organ-based testing approach, a slide-level train–test split in which images from the same histological slide group were retained within a single subset, a general image-level 80/20 train–test split, and five-fold cross-validation. A DeepLabV3-ResNet50-based segmentation model was trained using QuPath-prepared masks to determine fold regions at the pixel level. Grad-CAM was used for qualitative visualization and quantitative comparison with manually annotated fold regions. Results: All classification models showed excellent performance overall. The Swin-Tiny model was the most accurate in terms of general image-level classification, scoring 99.06% for accuracy, 99.19% for F1-score, and 99.98% for AUC. In slide-level classification, EfficientNet-B3 showed the best performance in terms of accuracy (99.54%) and AUC (99.99%). No pairwise statistical difference was found among the models using Holm adjustment. In the five-fold cross-validation setting, ResNet50 achieved the best performance with the accuracy of 98.73 ± 0.54%. In the detailed small-intestine error analysis, classification accuracy was 67.67%, with high sensitivity (98.59%) but low specificity (24.34%), mainly because of false-positive predictions. In the segmentation evaluation, the final DeepLabV3-ResNet50 model trained with combined BCE + Dice loss resulted in Dice of 0.7630 ± 0.2425 and IoU of 0.6661 ± 0.2577 on the independent test set. False positive segmentations were rare in 899 artifact-free images (only 0.33% of images had a tissue fold region of at least 1%). The quantitative Grad-CAM analysis showed poor spatial agreement with the manually annotated tissue fold masks (Dice = 0.2423; IoU = 0.1441). In the independent MPP10 dataset, ResNet50 achieved 89.63% accuracy and 88.49% F1-score. Conclusions: The suggested method was able to detect tissue fold artifacts as well as localize them in the teaching images of histology. The strong performance recorded at the slide level validates the internal findings, but the limited performance in the case of small intestine images and on the external dataset reveals that tissue structure remains a crucial factor. Full article

Background and Objectives: Sinonasal inverted papilloma (IP) is a benign yet locally aggressive tumour associated with a clinically relevant risk of recurrence and malignant transformation. While surgical outcomes are well documented, data on long-term patient-reported quality of life (QoL) remain limited and are often based on short-term or single time-point assessments using disease-specific instruments alone. Materials and Methods: We conducted a single-centre observational cohort study of adults with histologically confirmed IP treated endoscopically. Patients were followed in a university-affiliated otorhinolaryngology outpatient clinic and completed the Sino-Nasal Outcome Test-22 (SNOT-22) at each visit; from 2022 onwards, the generic WHOQOL-BREF questionnaire was additionally administered. Longitudinal SNOT-22 trajectories were analysed using generalised additive models and linear mixed-effects models. In a subgroup of patients, retrospectively recalled preoperative SNOT-22 and WHOQOL-BREF scores were used only for exploratory paired pre–post comparisons. Results: Sixty-nine patients were included. Mean follow-up was 63.1 ± 27.8 months, and recurrence occurred in 21 of 69 patients (30%). A total of 461 postoperative SNOT-22 assessments with complete follow-up time data were included in the longitudinal analysis, with a median of six assessments per patient. Mean postoperative SNOT-22 score was 25.4 ± 19.8, and longitudinal postoperative trajectories showed a largely stable course over time. In the paired exploratory subgroup (n = 34), retrospectively recalled preoperative SNOT-22 scores were higher than postoperative scores, although these exploratory findings should be interpreted cautiously because baseline PROMs were not collected prospectively. Exploratory paired comparisons of WHOQOL-BREF showed higher postoperative scores in the physical, psychological and environmental domains. Conclusions: Patients with sinonasal IP treated endoscopically can achieve favourable and largely stable long-term disease-specific and generic QoL. No single baseline clinical factor showed a clear association with postoperative SNOT-22 scores in the longitudinal models. Combining disease-specific and generic patient-reported outcome measures with longitudinal modelling may support more informed postoperative counselling in this rare, recurrent condition, while structured surveillance remains essential. Full article

Background: Extensive prior work has established severe aortic stenosis as a whole-heart remodeling process involving chronic pressure overload, concentric hypertrophy, myocardial stiffness, and progressive ventricular fibrosis. However, direct paired histological characterization of both atria remains limited. Methods: This single-center observational comparative study included 28 patients with severe aortic stenosis referred for surgical aortic valve replacement and 14 coronary artery bypass grafting (CABG) controls without significant valvular disease, consecutively enrolled between 9 May 2024 and 28 April 2025. Left- and right-atrial tissue samples were collected intraoperatively. The relative expression of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha), and transforming growth factor-beta (TGF-beta) was quantified by RT-qPCR using pooled tissue samples and interpreted descriptively as a group-level molecular output. Atrial fibrosis was measured histologically at the patient level using Masson’s trichrome staining and digital image analysis. Results: Compared with CABG controls, patients with severe aortic stenosis demonstrated greater left-atrial fibrosis (median: 19.12% [IQR: 16.12–23.12] vs. 11.54% [9.53–14.29]; p < 0.0001) and right-atrial fibrosis (16.33% [15.07–19.13] vs. 8.40% [5.75–11.27]; p = 0.0001). Pooled RT-qPCR outputs descriptively suggested higher IL-6, TNF-alpha, and TGF-beta expression in both atria, although biological replication was insufficient for inferential testing. Echocardiographically, the aortic stenosis group showed higher aortic jet velocity and transvalvular gradients, thicker ventricular walls, a larger right-ventricular diameter, higher pulmonary artery systolic pressure, and a larger estimated left-atrial volume. A sensitivity analysis of 13 within-group correlations found that no correlation retained statistical significance at q < 0.05. Exploratory regressions restricted to patient-level histological outcomes suggested that severe aortic stenosis status remained associated with left- and right-atrial fibrosis after limited adjustment for age and sex. Conclusions: These findings complement the extensive ventricular fibrosis literature by providing paired human biatrial tissue evidence of greater atrial fibrosis in severe aortic stenosis compared with CABG controls. The pooled molecular findings remain descriptive and require validation using patient-level biological measurements. Full article

Precision nutrigenomics requires a diet–microbiome–host perspective because microorganisms can transform feed substrates, generate bioactive metabolites, compete with pathogens, and modify intestinal and systemic gene regulation. This structured narrative review synthesizes representative controlled feeding trials, transcriptomic and targeted gene-expression studies, microbiome analyses, and complementary multi-omic evidence concerning dietary regulations in cultured finfish. The available evidence is concentrated particularly on soybean-derived proteins, lipid-source replacements, selected amino acids and micronutrients, functional additives, probiotics, and fermented ingredients in a limited range of cultured finfish species; therefore, the synthesis is not intended to provide exhaustive coverage of every dietary intervention or finfish taxon. Recurrent host responses involve intestinal inflammation and barrier integrity, nutrient transport, lipid and bile-acid metabolism, long-chain polyunsaturated fatty-acid biosynthesis, targets of rapamycin/insulin-like growth factor (TOR/IGF) signaling, and nuclear factor erythroid 2-related factor 2/Kelch-like ECH-associated protein 1 (Nrf2/Keap1) antioxidant defense. The expanded microorganism-centered synthesis shows that dietary effects depend on microbial niche, substrate availability, community succession, metabolite production, and strain-specific probiotic or pathobiont activity. Lactic-acid bacteria, Bacillus-associated interventions, butyrate-generating strategies, fermented ingredients, and microbial biomass may support digestion, immune balance, and disease resistance, but taxonomic shifts alone do not demonstrate functional benefit. Current evidence is limited by extensive reliance on 16S ribosomal RNA (16S rRNA) relative-abundance data, inconsistent digesta-versus-mucosa sampling, inadequate feed and water controls, and weak causal validation. Future precision aquafeed studies should combine host transcriptomics with absolute microbial quantification, shotgun metagenomics, metatranscriptomics, metabolomics, culturomics, histology, and pathogen challenge. Integrating microbial function with host phenotype can improve sustainable feed design, intestinal health, and resilience. Full article

Soft tissue sarcomas (STSs) are a heterogeneous group of rare mesenchymal malignancies with overlapping morphological and immunohistochemical features, often making definitive diagnosis challenging. Recent advances in next-generation sequencing (NGS) have enabled the identification of recurrent molecular alterations that contribute to tumor classification, prognostic stratification, and precision oncology approaches. This retrospective study aimed to evaluate the diagnostic and clinical impact of molecular profiling in pediatric soft tissue sarcomas using the Oncomine Childhood Cancer Research Assay (OCCRA) panel. Fifty-five frozen tumor samples representing 24 distinct soft tissue sarcoma subtypes were obtained from the Pediatric Oncology Institute -IOP/GRAACC/UNIFESP Biobank (B-053). Molecular analysis was performed using NGS to identify gene fusions, single nucleotide variants (SNVs), copy number variations (CNVs), and insertions/deletions (InDels). Clinically relevant molecular alterations were identified in 70% (37/55) of cases, including 18 fusion transcripts, 13 SNVs, 8 CNVs, and 6 InDels. Recurrent and diagnostically relevant alterations included BCOR::CCNB3, ASPSCR1::TFE3, NFR1::BRAF, FUS::DDIT3, EML4::NTRK3, ETV6::NTRK3, CIC::DUX4, NAB2::STAT6 and SS18::SSX1/2 fusions, as well as amplifications involving PDGFRA, FGFR1, GLI1, CDK4, ERBB3, and KIT. Pathogenic variants affecting genes involved in tumor suppression and chromatin remodeling, including TP53, NF1, DICER1, SMARCA4, PTEN, and PIK3CA, were also detected. Importantly, molecular profiling had significant diagnostic impact in several histologically ambiguous tumors, enabling molecular reclassification and refinement of previously inconclusive or inaccurate pathological diagnoses. In multiple cases, NGS transformed descriptive histopathological interpretations into genetically defined sarcoma entities, including NTRK-rearranged spindle cell neoplasms, CIC-rearranged sarcomas, synovial sarcoma, low-grade fibromyxoid sarcoma, and clear cell sarcoma. Furthermore, the identification of actionable alterations highlighted potential opportunities for targeted therapies and precision medicine approaches. Our findings demonstrate that comprehensive molecular profiling significantly enhances diagnostic accuracy in pediatric soft tissue sarcomas, particularly in morphologically challenging cases. The integration of NGS into routine sarcoma diagnostics enables biologically informed tumor classification and supports personalized therapeutic strategies. Full article

The management of epidermal growth factor receptor-mutated (EGFRm) non-small cell lung cancer (NSCLC) after progression on osimertinib is becoming increasingly complex, particularly in Canada, where access to diagnostic testing and newer therapies remains uneven. Although treatment is evolving with regimens such as amivantamab−lazertinib (MARIPOSA/MARIPOSA-2) and osimertinib plus chemotherapy (FLAURA2), access to such treatments in first and second lines varies across provinces. This article provides a pragmatic Canadian perspective on post-osimertinib management informed by expert roundtable discussions, a focused clinician survey, and the contemporary literature. Key challenges identified include delays and barriers related to tissue biopsy, next-generation sequencing, timely immunohistochemistry in time to influence treatment decisions and access to novel therapies. These gaps reduce the ability to individualize care and often force clinicians to rely on platinum-pemetrexed therapy as the default systemic backbone, even when biologically relevant resistance mechanisms exist, highlighting that post-osimertinib care in Canada remains shaped as much by access and system constraints as by emerging evidence. Full article

Background: Circulating bile acid (BA) profiles are increasingly explored in pancreatic cancer, although their interpretation is often complicated by biliary obstruction and its clinical management. In this study, we characterized plasma BA profiles in pancreatic ductal adenocarcinoma (PDAC) and assessed the relative contributions of tumor localization, histological subtype, cholestasis, and cholestasis-related interventions. Methods: Plasma BAs were quantified by LC-MS/MS in patients with PDAC of the pancreatic head (hPDAC, n = 132), PDAC of the body-tail (tPDAC, n = 42), and non-PDAC tumors of the pancreatic head (hnonPDAC, n = 34). BA concentrations and derived ratios were log-transformed and standardized, and their associations with bilirubin were examined using multivariable linear models, LOESS, and multivariate longitudinal analyses. Results: UDCA therapy was associated with markedly increased circulating UDCA, higher total BA concentrations, and enrichment of secondary BA species. Direct bilirubin explained more variability in BA composition than binary jaundice classification and showed a non-linear association with BA remodeling, with a distinct metabolic profile emerging only at high bilirubin levels. Longitudinally, BA profiles changed substantially over time in hPDAC, largely in parallel with bilirubin, whereas they remained comparatively stable in tPDAC. After adjustment for bilirubin, tumor-related differences were modest and context-dependent. Conclusions: Overall, circulating BA profiles in pancreatic cancer appear to be driven predominantly by cholestasis and its management rather than by tumor-related features alone. Full article

Osteoarthritis (OA) of the knee is characterized by cartilage matrix degeneration, which eventually leads to joint dysfunction and surgical replacement. Preoperative radiography, the standard for treatment decision making, provides limited information on the extent of degeneration, emphasizing the need for quantitative intraoperative techniques. This study evaluates the potential of vibroacoustic signals generated from instrument–tissue interactions to assess cartilage degeneration severity. A total of 136 ex vivo cartilage specimens of varying degeneration severity, histologically graded using the OARSI score, were collected from 41 patients undergoing arthroplasty. The specimens were classified into three groups: healthy cartilage (OARSI $\le 2.0$), degenerated cartilage (OARSI ≥ 2.5), and subchondral bone. Vibroacoustic signals were captured during specimen palpation using a vibration measurement system affixed to a surgical probe. 26 characteristic signal features were extracted using Continuous-Wavelet Transformation, and their discriminative power was assessed using Support Vector Machine and k-Nearest-Neighbor classifiers under patient- and specimen-level grouped cross-validation with nested hyperparameter tuning. Bone was distinguished from cartilage with 84–$91\%$ recall. Healthy cartilage (OARSI $\le 2.0$) was identifiable with 74–$80\%$ sensitivity, whereas the specificity for degenerated cartilage (OARSI ≥ 2.5) remained limited (40–$57\%$), constituting the principal limitation of the approach. Interpreting the binary cartilage classification as a diagnostic test, a receiver-operating characteristic (ROC) analysis yielded an area under the curve (AUC) of up to $0.66$ ($95\%$ CI [$0.56$, $0.76$]). The study demonstrates that vibroacoustic signals from instrument–tissue interactions may provide complementary information for intraoperative cartilage evaluation and may contribute to decision making in arthroplasty, while the reliable grading of cartilage degeneration remains an open challenge. Full article

Background: Women treated for cervical intraepithelial neoplasia grade 2 (CIN2) face an increased risk of disease recurrence due to persistent or newly acquired human papillomavirus (HPV) infections, suggesting a potential role for adjuvant HPV vaccination. While a growing body of literature evaluates the outcomes of HPV vaccination following a large loop excision of the transformation zone (LLETZ) for high-grade squamous intraepithelial lesions (CIN2–3), data specifically focused on isolated CIN2 remain limited. This study aims to evaluate the clinical efficacy of the nonavalent HPV vaccine (9vHPV) as an adjuvant strategy to reduce CIN2+ recurrence in women undergoing LLETZ for histologically confirmed, isolated CIN2. Methods: Between November 2017 and November 2024, women undergoing LLETZ for histologically confirmed CIN2 received their first dose of adjuvant 9vHPV within one month of surgery. Patients who achieved double-negative co-testing (Pap test and high-risk HPV DNA test) at the 6-month post-LLETZ follow-up were included in the study group. Conversely, patients with at least one positive test result at 6 months were excluded to rule out residual disease. The study group underwent a subsequent Pap smear at 12 months and a full co-test at 18 months post-surgery; upon achieving negative results through the 18th month, patients returned to the organized screening program. The primary outcome was the recurrence rate, defined as histologically confirmed CIN2+ occurring more than 6 months post-treatment. It was compared against an unvaccinated historical control group treated with LLETZ prior to the study period. The secondary outcome evaluated the prevalence of HPV genotypes at baseline and at the time of recurrence. Results: In the vaccinated group, 3 women (2.03%) experienced CIN2+ recurrence compared to 6 women (5.71%) in the unvaccinated control group. This represents an absolute risk difference of 3.69% and a relative risk reduction of 64.6%, though the difference did not reach statistical significance via Fisher’s exact test (p = 0.165). In the study group, two recurrences were detected at 18 months (associated cytologies: ASC-H and LSIL; genotypes: HPV 51/53 and 16, respectively) and one at four years (cytology: HSIL; genotype: HPV 33/58). In the control group, recurrences occurred at 12 months (n = 3), 18 months (n = 2), and four years (n = 1). Associated cytology revealed HSIL in three cases, ASC-H in one case, LSIL in one case, and ASCUS in the final case. The corresponding HPV genotypes were 16 (two cases), 18, 51, 31 and 56 (co-infection), and one case of high-risk HPV, not further genotyped. Conclusions: Adjuvant 9vHPV administration after LLETZ for isolated CIN2 was associated with a clinically substantial lower absolute recurrence rate (2.03% vs. 5.71%, corresponding to a 64.6% relative risk reduction). Although this reduction did not achieve statistical significance ($p=0.165$) due to our small sample size and a low baseline recurrence rate in this isolated cohort, the effect size is highly comparable to broader CIN2+ studies. The study was likely underpowered to prove statistical significance, and larger multi-center studies are required to confirm the statistical value of adjuvant vaccination specifically in isolated CIN2 lesions. Full article

Nuclei instance segmentation in hematoxylin and eosin (H&E)-stained images plays an important role in automated histological image analysis, with various applications in downstream tasks. While several machine learning and deep learning approaches have been proposed for nuclei instance segmentation, most research in this field focuses on developing new segmentation algorithms and benchmarking them on a limited number of arbitrarily selected public datasets. In this work, rather than focusing on model development, we focused on the datasets used for this task. Based on an extensive literature review, we identified manually annotated, publicly available datasets of H&E-stained images for nuclei instance segmentation and standardized them into a unified input and annotation format. Using two state-of-the-art segmentation models, one based on convolutional neural networks (CNNs) and one based on a hybrid CNN and vision transformer architecture, we systematically evaluated and ranked these datasets based on their nuclei instance segmentation performance. Furthermore, we proposed a unified test set (NucFuse-test) for fair cross-dataset evaluation and a unified training set (NucFuse-train) for improved segmentation performance by merging images from multiple datasets. To the best of our knowledge, this is the first study to systematically benchmark and rank publicly available datasets for nuclei instance segmentation. By evaluating and ranking the datasets, performing comprehensive analyses, generating fused datasets, conducting external validation, and making our implementation publicly available, we provided a new protocol for training, testing, and evaluating nuclei instance segmentation models on H&E-stained histological images. Full article

Ewing sarcoma is a highly malignant tumor whose histological appearance often overlaps with that of other undifferentiated round-cell and ovoid-cell tumors, making accurate diagnosis challenging. Selecting the most appropriate immunohistochemical and molecular tests is critical, particularly when only limited core biopsy material is available and tissue preservation for additional molecular or biomarker testing is required. Artificial intelligence (AI)-based histopathological image analysis is emerging as a promising diagnostic tool in oncology. This study evaluated the potential of AI-based histopathological analysis to assist pathologists in the morphologic classification of Ewing sarcoma and selected histological mimics using tissue microarrays (TMAs), rather than to identify or predict molecular alterations. We analyzed 1926 digitized histological cores, from 729 patients, assembled into 45 tissue microarrays. The dataset comprised 517 Ewing sarcomas (ESs), 367 rhabdomyosarcomas (RMSs), 187 chondrosarcomas (CHSs), 138 gastrointestinal stromal tumors (GISTs), and 124 synovial sarcomas (SSs). A weakly supervised multiple-instance learning (MIL) framework with transformer-based aggregation was developed using only core-level diagnostic labels. The model achieved classification accuracies of 97.1% for Ewing sarcoma, 80.0% for rhabdomyosarcoma, 85.7% for gastrointestinal stromal tumors, 80.0% for chondrosarcoma, and 76.0% for synovial sarcoma. The overall classification accuracy was 91.6%, with no misclassifications between Ewing sarcoma and rhabdomyosarcoma. These findings highlight the model’s robustness in distinguishing tumor entities that present a well-recognized diagnostic challenge in routine pathology. The AI algorithm demonstrated strong potential as a diagnostic adjunct for assisting pathologists in the morphologic classification of Ewing sarcoma and selected tumor entities based on histopathological features. Although these tumor entities are characterized by specific molecular alterations, the model was not designed to identify or predict molecular alterations directly. Instead, it supports clinical decision-making by recognizing morphologic patterns associated with diagnostically defined tumor entities. The integration of AI-based histopathological analysis with immunohistochemistry and contemporary molecular diagnostic techniques has the potential to improve diagnostic accuracy, optimize the use of ancillary testing, enhance our understanding of genotype–phenotype relationships, and ultimately support more effective patient management. Full article

Relapsed and/or refractory follicular lymphoma (R/R FL) remains a therapeutic challenge due to its chronic relapsing course and increasingly complex treatment landscape. Novel therapies, including immunomodulatory combinations, bispecific antibodies (BsAbs), Bruton tyrosine kinase inhibitors, and chimeric antigen receptor (CAR) T-cell therapies, have expanded treatment options and increased the complexity of treatment selection and sequencing. The Canadian Hematology Consensus Group (CHCG) convened a national panel of lymphoma experts to develop evidence-informed consensus recommendations for the management of adults with R/R FL in the Canadian context. Clinical questions informed a structured literature review of studies published through February 2026, including randomized trials, phase II studies, observational data, conference proceedings, and relevant guidelines. Recommendations were developed using a modified Delphi consensus process and graded using a framework adapted from the British Committee for Standards in Haematology. Key recommendations include repeat biopsy to exclude histologic transformation at relapse, individualized treatment selection based on timing of relapse and patient-specific factors, preferential use of lenalidomide-rituximab (LenR)-based triplet combinations in most second-line settings, and incorporation of BsAb and CAR T-cell therapy in third-line and later disease. These recommendations aim to provide practical guidance for Canadian clinicians managing patients with R/R FL. Full article

Background/Objectives: Sinonasal inverted papilloma is a rare Schneiderian epithelial tumor, histologically benign in most cases, but characterized by locally aggressive behavior, a high recurrence rate and a recognized potential for malignant transformation, most frequently into sinonasal squamous cell carcinoma. The present article is a scoping review that maps and critically synthesizes the available evidence on epithelial, immunohistochemical and selected molecular markers in malignant-transformed sinonasal inverted papilloma, rather than a quantitative systematic review or meta-analysis. Methods: The literature search was performed according to PRISMA-ScR principles in PubMed/MEDLINE, Embase, Scopus/Web of Science and Google Scholar, using the search keywords sinonasal inverted papilloma, malignant transformation, markers, HPV, p63, p40, p16 and Ki-67, as well as complementary markers of the cell cycle and of the EGFR/CDKN2A/TP53 pathways. Results: Based on the available data, p40 and p63 have diagnostic value for defining and mapping the squamous phenotype, including invasive carcinomatous nests, but they are not standalone predictive markers of malignant transformation. p16 cannot be automatically used as a surrogate for active HPV infection in inverted papilloma, while the results regarding HPV remain inconclusive in relation to malignant transformation of sinonasal inverted papilloma. Ki-67, especially when interpreted topographically and in relation to dysplasia and invasion, may suggest proliferative acceleration, but prognostic thresholds have not yet been validated. Conclusions: The conclusion of our study is that the risk of malignant transformation cannot be reduced to a single marker; it must be interpreted through an integrative clinical, imaging, histopathological, immunohistochemical and molecular model, which requires prospective multicenter validation. Full article

Small-cell lung cancer (SCLC) is a recalcitrant form of cancer, accounting for 15% of lung cancer cases worldwide. In recent years, the histological transformation from non-small-cell lung cancer (NSCLC) to SCLC has become a significant mechanism of acquired resistance, especially in patients undergoing treatment with tyrosine kinase inhibitors (TKIs) or immunotherapy. Although there is growing clinical understanding, the crucial biological mechanisms that drive this phenotypic switch are still not fully understood. Transformed SCLC (T-SCLC) seems to exhibit differences from de novo SCLC regarding molecular characteristics and tumor microenvironment, indicating unique evolutionary paths. While traditional chemotherapy has been the main treatment method after transformation, patient outcomes continue to be unsatisfactory, highlighting the necessity for a more profound mechanistic insight and the development of more effective treatments. Full article

Urothelial carcinoma (UC) is a biologically and clinically heterogeneous disease arising from the bladder and upper urinary tract. Immune checkpoint inhibitors (ICIs) have transformed treatment of advanced UC, yet durable responses remain limited to a minority of patients, underscoring the need to better understand the tumor immune microenvironment (TME). This narrative review examines the UC immune phenotype across disease stages and anatomical sites, integrating evidence from bulk and single-cell transcriptomics, spatial profiling, and translational studies. We describe the principal immune cell populations of the UC TME—including cytotoxic and regulatory T cells, macrophages, myeloid-derived suppressor cells, natural killer cells, B cells, and dendritic cells—and their relationship to established molecular subtypes. We review how this immune landscape evolves from non-muscle-invasive to metastatic disease, including the distinct contexture of upper tract UC and variant histology. We critically evaluate established ICI biomarkers (PD-L1, FGFR3, tumor mutational burden, mismatch repair deficiency) alongside emerging candidates—tumor-infiltrating lymphocyte density, HLA class I expression, tertiary lymphoid structures, and multiparameter transcriptomic scores—noting that most remain investigational and require prospective validation before clinical use. Finally, we address key biological, technical, and clinical barriers to this research and outline future directions in AI-assisted digital pathology and multimodal biomarker integration. A comprehensive characterization of UC immune phenotype is essential to guide rational, biomarker-driven patient selection and optimize next-generation immunotherapy strategies. Full article