The Journal of Pathology

Bladder carcinoma in situ (CIS) is a multifocal, non-muscle-invasive disease with a high risk of progression to muscle-invasive cancer. Current management strategies are often guided by genomic profiling of single tumor samples, which incompletely capture tumor heterogeneity and may contribute to treatment failure. In particular, the multifocal nature of CIS raises uncertainty regarding the uniformity of genomic, immunologic, and microenvironmental features across anatomically distinct sites within the same patient. To address this, we performed spatial transcriptomic profiling of CIS-containing tissue from four anatomically distinct sites within a single individual. Unsupervised clustering with marker-based annotation, integrated with metabolic inference, identified epithelial tumor populations alongside stromal, immune, and smooth muscle compartments. While key cellular states were conserved, their spatial organization and relative abundance varied by site. Metabolic analysis further revealed region-specific microenvironments shaped by local cellular architecture. These findings indicate that both cellular composition and metabolic activity are spatially structured. Collectively, these results demonstrate that CIS exhibits significant intra-patient heterogeneity not captured by single-site profiling. These findings require validation in larger cohorts but support multi-region sampling could help improve risk stratification, biomarker development, and prediction of response to intravesical therapies, with potential implications for more personalized treatment strategies.

A subset of untreated primary prostate cancer (PCa) contain substantial focal T-cell infiltrates, but whether these reflect antitumor responses that could potentially be enhanced by immune checkpoint blockade (ICB) remains unclear. We used immunohistochemistry, immunofluorescence, whole-slide spatial analysis, bulk RNA sequencing, and immune-cell deconvolution to characterize immune infiltrates in untreated primary PCa. Absolute CD8 T-cell density generally increased with total CD3 T-cell density, but the CD8/CD3 ratio decreased as overall T-cell density increased, indicating a preferential increase in CD4 T cells. Highly infiltrated tumors also had lower GZMB abundance relative to CD8 T-cell abundance. Multiplex analysis showed trends toward greater TIM3 and LAG3 expression among PD1CD8 T cells and increased regulatory T-cell features in highly infiltrated tumors. TIGIT cell density and the TIGIT/CD3 ratio increased with T-cell infiltration, whereas PD1/CD3 was not associated with overall CD3 T-cell density. Both TIGIT/CD3 and PD1/CD3 ratios were enriched within lymphoid aggregates compared with matched tumor and benign regions, consistent with these structures being checkpoint-rich immune niches. Transcriptomic analyses supported a shift in relative immune composition toward CD4 T cells and selective increases in immune checkpoints. Together these findings suggest that effective immune responses in a subset of primary PCa with increased T-cell infiltration are being repressed by several mechanisms and may respond to therapies targeting specific immunosuppressive mechanisms.

Liver metastases (LM) remain a major cause of death from different cancer types, in particular malignancies of the gastrointestinal tract. Liver metastases predict a poor response to immunotherapy due, among others, to the immunotolerant microenvironment (ME) of the liver and loss of local and systemic cytotoxic T cells. Thus, strategies that can reprogram the immune ME of the liver and restore cytotoxic T cell reactivity are being sought. We previously reported that estrogen signaling blockade impedes the growth of LM by reducing MDSC accumulation and monocyte/macrophage polarization. The aim of this study was to elucidate the underlying mechanism(s) and assess whether estrogen signaling in the myeloid lineage was driving the immunotolerant ME of LM. To this end, we generated mice with conditional myeloid cell-specific deletions of estrogen receptors (ER) or ER{beta} and analyzed in these mice the effect of ER loss on the liver immune ME and the outgrowth of LM. In mice with ER, but not with ER{beta} deletion, we observed a marked reduction in the growth of murine colon carcinoma MC-38 liver metastases as compared to their respective controls. Flow cytometry and immunohistochemistry revealed a decrease in macrophages that were polarized to the pro-tumorigenic M2-like phenotype and a concomitant increase in activated CD8+ T and NK cells relative to controls. Bulk RNAseq analysis performed on hepatic immune cells infiltrating the liver revealed changes in the expression of key cytokines/chemokines mediating immune cell recruitment, activation and polarization, including Ccl5 (upregulated) and Csf1 (downregulated). Taken together, the data suggest that ER signaling in myeloid-derived cells programs the immune landscape and contributes to an immunosuppressive and metastases-growth permissive ME in the liver.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by high metastatic dissemination, therapy resistance, and poor clinical outcome. Inhibitor of differentiation 1 or ID1, is frequently overexpressed in PDAC and is associated with tumour progression and adverse clinical outcome. However, the mechanisms governing its post-transcriptional regulation remain insufficiently characterized. Here, we identify tumour-suppressive miR-615-5p as a regulator of ID1 expression in PDAC. Integrative in-silico target prediction prioritized miR-615-5p based on seed complementarity and thermodynamic stability with the ID1 3' -UTR. Expression analysis of available PDAC clinical datasets revealed reduced miR-615-5p expression associated with increased ID1 expression. Direct association was validated using luciferase reporter assays, where miR-615-5p suppressed 3' -UTR reporter activity of ID1 in a sequence dependent manner, while mutation of the predicted binding site attenuated this effect. Further biotinylated-RIP and AGO2-RIP assays demonstrated the co-enrichment of ID1 transcripts and miR-615-5p with AGO2 associated RISC complexes, while AntimiR mediated inhibition of miR-615-5p perturbs association between miR/ID1 to AGO2, supporting interaction specificity. Functionally, modulation of miR-615-5p altered ID1 expression and impacted PDAC cell migration in vitro. Mechanistic analyses further indicated that the miR-615-5p/ID1 axis influences autophagic flux where miR-615-5p mediated inhibition of autophagy suppresses ID1 dependent cellular migration. Collectively, these findings define a previously uncharacterized miRNA-dependent regulation of ID1 expression and link this axis to autophagy-associated migratory responses in PDAC cells. The study expands the post-transcriptional regulatory landscape of ID1 and provides a possible mechanism where suppression of miR-615-5p leads to ID1 overexpression and subsequent poor clinical outcome in PDAC cells.

Viral infections have long been proposed as environmental contributors to neurodegenerative diseases, including Parkinson's disease (PD), yet the molecular mechanisms linking infection and neurodegeneration are not well defined. Neuroinflammation and disruption of central nervous system (CNS) homeostasis have emerged as potential mediators. In this study, we used severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, as a model pathogen to investigate convergent molecular pathways between viral infection and PD. Single-nucleus RNA sequencing (snRNA-seq) was performed on post-mortem striatal tissue from 14 individuals stratified into four groups: COVID-19 only (COVID-19), PD only (PD), comorbid PD with COVID-19 (PD/COVID-19), and controls (Control). The PD/COVID-19 group exhibited an expanded astrocytic population and a pronounced interferon-associated molecular signature characterized by increased expression of canonical interferon-stimulated genes, including IFI44L (average log2FC= 3.9; adjusted p=2.3 x 10-373), IFI44 (average log2FC=2.9; adjusted p=8.0 x 10-266), ISG15 (average log2FC=3.1; adjusted p=1.2 x 10-197), and RSAD2 (average log2FC= 3.5; adjusted p=8.6 x 10-111). Pathway analyses demonstrated activation of innate immune and antiviral signaling pathways, particularly within microglia and astrocytes, including interferon signaling, pattern-recognition receptor pathways, and complement-associated responses. In parallel, genes involved in lipid metabolism, cholesterol homeostasis, synaptic maintenance, and neuronal signaling were reduced across disease groups. Proteomic analyses independently confirmed enrichment of antiviral and interferon-associated pathways and identified convergent suppression of sterol, cholesterol, and lipid metabolic processes. Our findings identify a convergent molecular signature linking PD and COVID-19, pronounced in comorbid individuals and characterized by interferon-driven innate immune activation, glial inflammatory responses, and dysregulation of lipid metabolic homeostasis. Collectively, the data support a model in which severe viral infection amplifies biological pathways already implicated in PD pathogenesis.

Background: Biochemical recurrence (BCR) occurs in 20-40% of men after radical prostatectomy. Existing postoperative recurrence risk tools based on PSA and pathology are clinically useful but show only moderate and variable discrimination, highlighting the need for biomarkers that improve risk stratification and consequent treatment decisions. We hypothesized that the prostate microenvironment, including both the tumor and non-cancerous adjacent tissue, may contain prognostic features associated with adverse postoperative PSA outcomes. Methods: We assembled a cohort of matched tumor-adjacent benign and tumor prostate tissue from 243 men across three institutions to establish a discovery cohort (n=123; 43 postoperative PSA events, 35%) and validation cohort (n=120; 46 events, 38%). For primary binary analyses, a postoperative PSA event included BCR, defined as two consecutive postoperative PSA values >=0.2 ng/mL, or PSA persistence. We performed RNA sequencing of matched tumor-adjacent benign and tumor tissues, quantified immune signatures, and developed an integrated model combining the adjacent-tissue B-cell signature, preoperative PSA, and radical prostatectomy Gleason score (BRIGADE). CAPRA-S-adjusted Cox analyses excluding recurrence-time-0 cases evaluated time to BCR, and CD19 multiplex immunofluorescence provided tissue-level confirmation (n=10). Results: In prostatectomy specimens, tumors from patients without a postoperative PSA event were enriched for B-cell transcriptional programs, whereas tumors from event-positive patients showed elevated proliferation signatures. B-cell-related transcriptional programs were correlated between tumor and adjacent tissue. Tumor-adjacent benign B-cell scores were higher in no-event cases and discriminated postoperative PSA-event status in PCBN discovery (AUC 0.63) and BM validation (AUC 0.81) cohorts, outperforming numerous other immune-related signatures. In CAPRA-S-adjusted Cox sensitivity analyses excluding recurrence-time-0 cases, higher adjacent-tissue B-cell activity was associated with reduced recurrence risk in PCBN (HR 0.42, 95% CI 0.19-0.94; BH-adjusted p=0.035) and BM (HR 0.54, 95% CI 0.30-0.95; BH-adjusted p=0.034). Tissue-based validation showed that CD19+ B-cell density in adjacent benign tissue was higher in no-event than event-positive patients (median 0.1145 vs 0.0471; p=0.008). BRIGADE achieved an AUC of 0.68 in cross-validation and 0.83 in independent validation, compared to AUCs of 0.54-0.63 and 0.44-0.78 for the tested clinical predictors, respectively. At the fixed classification threshold, the validation-cohort odds ratio for BRIGADE was 2.75. The adjacent B-cell score remained associated with lower odds of a postoperative PSA event after adjustment for PSA and Gleason score. Conclusions: B-cell infiltration in tumor-adjacent benign prostate tissue may complement existing clinicopathologic models for stratifying adverse postoperative PSA outcomes and subsequent BCR after radical prostatectomy. The transcriptomic signal was recapitulated by CD19-based tissue staining, supporting further development of a pathology-based assay.

Tumor-promoting myofibroblastic carcinoma-associated fibroblasts (myCAFs) are induced by activation of transforming growth factor-{beta} signaling. However, the molecular basis of myCAF-specific transcriptional programs regulated by TGF-{beta} signaling remains poorly understood. Using a meta-analysis of single-cell RNA-seq data from 132 human breast tumor and non-tumor tissues, we show that myCAFs activate gene regulatory programs relevant to skeletal and cardiovascular development that are associated with poorer outcomes in breast cancer patients. Of note, distal-less homeobox 5 (DLX5), a master transcription factor for skeletal development, is activated in human breast myCAFs at both epigenetic and transcriptional levels. DLX5 expression is also initiated by TGF-{beta}1 treatment in human mammary fibroblasts. Immunoprecipitation and CUT&RUN assays using DLX5-expressing fibroblasts demonstrate that DLX5 interacts with Smad2/3/4 proteins, enabling their cooperative occupancy at shared genomic binding sites of target genes, thereby promoting canonical TGF-{beta} signaling and the myCAF state. DLX5-primed myCAFs also enhance paracrine TGF-{beta} signaling and neuropilin-2 expression to promote collective tumor invasion. Our findings indicate that DLX5 induces myCAF formation and promotes breast tumor progression in collaboration with canonical TGF-{beta} signaling.

Background: Spatial organization is increasingly recognized as a key determinant of tumor-immune interactions in head and neck squamous cell carcinoma (HNSCC). The GSE300147 Xenium spatial transcriptomic resource generated by McCord and colleagues established a framework for mapping spatially coordinated T-cell states in HNSCC. However, how tumor-enriched epithelial immune states relate to metabolic, redox, and stress-adaptive transcript programs remains incompletely defined. Methods: A secondary, data-driven reanalysis of GSE300147 was performed, focusing on 17 confirmed HNSCC Xenium sections after exclusion of a non-HNSCC ameloblastoma specimen. A total of 1,148,244 cells were analyzed, including 558,867 EpCAM+ tumor-enriched epithelial cells. Tumor-enriched epithelial cells were classified into Hot, Intermediate, and Cold states using a Composite Hotness framework integrating T-cell inflammatory signature score, checkpoint-associated signaling, CD274 expression, IFN/antigen-presentation signature score (IFN/AP), and tumor-immune proximity. Six metabolic ecosystem states, neighborhood profiling, spatial permutation testing, and an integrated Immune-Metabolic-Redox Ecosystem Score (IMRES) were then applied. Results: Immune activation was spatially heterogeneous across HNSCC sections. Immune-hot tumor-enriched epithelial regions showed not only inflammatory, checkpoint-associated, and antigen-presentation signature scores, but also coordinated metabolic, oxidative-redox, and stress-response transcript programs. IMRES, derived from available immune, metabolic, redox, and stress-response transcript components represented in the Xenium panel, increased progressively from Cold to Intermediate to Hot tumor-enriched epithelial states and was associated with NFE2L2, GDF15, HLA-DRA, CD274, KEAP1, and MDM2. Integrating IMRES with Composite Hotness identified a distinct Hot+IMREShigh ecosystem comprising 106,874 tumor-enriched epithelial cells. This state showed the strongest immune-active and stress-adaptive features and was positioned closer to immune populations than expected by random assignment. An alternative rank-based robustness analysis reproduced the IMRES-associated ecosystem axis and correlated with the original module-based score (Spearman r = 0.597). Conclusions: This secondary reanalysis extends the original spatial T-cell framework by defining a complementary tumor-centered immune-metabolic-redox ecosystem in HNSCC. IMRES provides a transcript-derived framework for identifying Hot+IMREShigh neighborhoods where immune activation, checkpoint signaling, metabolic remodeling, and stress adaptation converge, providing a hypothesis-generating framework for studying immune resistance and therapeutic vulnerability.

Current approaches for imaging fibrotic remodeling have sensitivity, specificity and cost drawbacks that limit both preclinical research and clinical diagnosis. Here, we show that fast green FCF, a small molecule that binds to fibrillar collagen, enables highly sensitive and specific imaging of fibrosis in lung samples from mice and humans using fluorescence microscopy. We report strategies for using fast green FCF staining to assess fibrotic remodeling using precision-cut lung slice and whole-biopsy preparations. Our findings demonstrate that fluorescence imaging of fast green FCF-stained collagen will be useful for fibrosis research and may help to improve detection of fibrosis in clinical pathology.

The role of UBE2N in myeloid cell-mediated immune suppression in cancer remains undefined. Here, we examined the function of UBE2N in myeloid cell-mediated tumor progression using a temporally inducible myeloid-specific knockout model (LysMCreERUbe2nfl/fl). Temporally induced deletion of Ube2n in myeloid cells (Ube2nMyeKO) significantly hindered growth of YUMM1.7 melanoma. This was accompanied by reduced myeloid cell burden within the tumor microenvironment. We observed altered abundance of PD-1, PD-L1, and SPP1 in the Ube2nMyeKO tumor microenvironment at the tissue level. In vitro analysis showed that knock-in expression of a catalytically deficient UBE2NC87S mutant in bone marrow-derived macrophages (BMDMs) markedly decreased expression of Spp1. We observed decreased SPP1 secretion in Ube2nMyeKO BMDM-conditioned media (CM). Treatment with Ube2nMyeKO BMDM-CM decreased co-expression of PD-1, TIM-3, and LAG-3 on chronically stimulated T cells. Antibody-mediated neutralization of SPP1 in Ube2nWT BMDM-CM decreased PD-1 expression on CD8+ T cells. Together, these findings suggest a role for myeloid UBE2N in YUMM1.7 progression.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis have shown great promise in treating bladder cancer and are now part of the standard treatment for advanced disease. However, many patients still fail to respond to treatment and at present many biomarkers are assessed but have yet shown only limited results. Therefore, with the advent of combination treatments and the increase of immune related adverse event, the search for reliable predictive biomarkers is paramount. Using a multiplexed enhanced FRET-FLIM based technique (QF-Pro) we quantified the interaction of PD-1/PD-L1, CTLA-4/CD80 and TIGIT/CD155 immune checkpoints in a pre-treatment TMA of 46 patients treated with atezolizumab. The association between higher PD-1/PD-L1 ICP interaction state and treatment efficacy was demonstrated in the male sample cohort, where it identified patients with better PFS. Conversely, patients exhibiting higher CTLA-4/CD80 engagement had a worse response to atezolizumab. Remarkably, the dual assessment of patients with high PD-1/PD-L1 and low CTLA-4/CD80 allowed to identify the best responders. These results indicate that the monitoring of patients immune profile in urothelial carcinoma might be critical in identifying patients who may benefit from combination therapy.

Keloids are benign fibroproliferative disorders majorly characterized by excessive extracellular matrix deposition, with recurrence rates exceeding 80% following conventional therapy. Although epigenetic dysregulation has been implicated in keloid pathogenesis, whether genome-wide DNA methylation actively drives pathological cellular reprogramming, and whether this state is therapeutically reversible, remains unclear. We performed genome-wide DNA methylation profiling on keloid tissues, matched primary keloid fibroblasts, and normal controls. Our analysis revealed a shared DNA hypermethylation pattern between keloid tissues and fibroblasts, which was validated by three independent public cohorts. By integrating DNA methylome and transcriptome, we demonstrated that DNA methylation-regulated genes were enriched in osteochondrogenesis-related pathways, such as cartilage and bone development pathways. Furthermore, pharmacologic inhibition of DNA hypermethylation by DNA demethylating agent decitabine reduced the expression of osteochondrogenic markers and inhibited collagen deposition and keloid growth in primary keloid fibroblasts and patient-derived xenograft (PDX) model, offering a potential therapeutic strategy of keloid.

In large data sets discovery is often limited to pre-conceived hypotheses and data fishing. Here we tested whether systematic exploration of AI generated hypotheses could uncover clinically meaningful signals in extensively studied data. We deployed AutoDiscovery, a newly launched large language model (LLM) framework designed to search for hypotheses based on surprisal and systematically interrogate complex datasets, on The Cancer Genome Atlas breast cancer cohort. The system did not identify clinically meaningful novel findings without human input. However, a seeded warm-start run with minimal text input from an oncologist revealed multiple interesting and surprising hypotheses. Among these was that a robust immune signature was present across all subtypes of invasive lobular carcinoma (ILC) that exceeded invasive ductal carcinoma (IDC). This observation was independently validated in independent cohorts and confirmed by high-sensitivity multi-immunofluorescence tumor tissue analyses. These results suggest immunotherapy approaches should be tested in ILC including early stage ER+HER2- ILC; these patients are currently excluded from large neoadjuvant immunotherapy trials. They further demonstrate that surprisal-based hypothesis generation frameworks can extract previously unappreciated patterns from deeply interrogated cancer datasets and imply that disease domain experts working with LLMs can derive more meaningful insights from complex data than either could achieve alone.

Objective: To determine whether the most cited and the most publicly discussed benign prostatic hyperplasia (BPH) literature describe the same body of work, and whether clinicians and patients read different evidence. Methods: Four Boolean Web of Science searches and four matched Altmetric Explorer searches were run in February 2024, restricted to literature indexed with urologic terminology, and screened in duplicate. Two arms were assembled: the 50 most-cited articles (citation census May 2024) and the 50 with the highest Altmetric Attention Scores. Funding source and intervention focus were hand-coded from the full text of all 100 articles; open-access status came from Unpaywall. Arms were compared with Mann-Whitney U and Fisher exact tests Results: Eight of 50 articles (16%) appeared in both arms. Citation selected articles were older (median 2008 versus 2018, p<0.001), more often randomized trials (58% versus 22%, p<0.001), and more often published in urology-specific journals (96% versus 66%, p<0.001). Industry funded 50% versus 18% of articles (p=0.001) and non-industry sources 8% versus 36% (p=0.001). Only 10% of citation-selected articles were open access versus 56% (p<0.001). Attention data were recoverable for only 13 citation-selected articles (median score 9 versus 17). The two arms were cited in the 2026 AUA BPH Guideline at indistinguishable rates (22% versus 20%, p=1.00). Conclusions: These are largely distinct bodies of work, separated most decisively by whether they can be read without a subscription, yet both inform guideline development equally. Patients arrive with evidence systematically different from, and no less guideline-relevant than, that underpinning their urologist's training.

Purpose: To evaluate whether initiation of GLP-1 receptor agonists (GLP-1RAs) is associated with anti-VEGF treatment burden in type 2 diabetes patients with diabetic macular edema (DME) in the IRIS(R) Registry (Intelligent Research in Sight). Methods: Incident GLP-1RA initiators were matched 1:1 with controls via Mahalanobis distance matching (9,896 pairs; N=19,792) on sociodemographics, DME risk factors, and factors influencing GLP-1RA prescription including hypertension, obesity, chronic kidney disease. A longitudinal mixed-effects event-study model evaluated monthly anti-VEGF injection frequency over a 36-month window (12 months before through 24 months after initiation), adjusting for DME duration. Visual acuity (VA) and central subfield thickness (CST) were secondary outcomes. Results: Following GLP-1RA initiation, anti-VEGF injection trajectories did not significantly differ between the matched GLP-1RA and control cohorts (interaction coefficients -0.18 to 1.59, P>0.05). Likewise, no differences in VA were observed between cohorts (-0.05 to 0.04 logMAR, P>0.05) or CST (-14.12 to 33.58 {micro}m, P>0.05). Conclusion: In these matched cohorts, GLP-1RA initiation was not associated with the trajectory of anti-VEGF use or changes in VA or CST. Precis We used the American Academy of Ophthalmology IRIS(R) Registry (Intelligent Research in Sight) to identify patients with DME. In 19,792 matched patients, there was no significant reduction in injection frequency post GLP1-RA initiation and no significant change in VA or CST.

Background: Endometriosis affects approximately 10% of reproductive-age women and is associated with substantial diagnostic delay and heterogeneous symptom presentation. Prior machine-learning prediction models have relied on comorbidity data alone or on small candidate-variant genetic scores, with inconsistent or incompletely reported performance. No study has combined a well-powered, multi-ancestry polygenic risk score (PRS) with environmental, reproductive, and symptom data in a single hybrid model. We developed and evaluated hybrid risk-prediction models integrating a genome-wide, multi-ancestry PRS with clinical and symptom data for endometriosis in the US-based All of Us Research Program. Methods: Among 69,376 participants (15,382 endometriosis cases, 53,994 controls) across six genetically inferred ancestry groups, we computed individual-level PRS values using PRS-CS weights derived from an independent, multi-ancestry GWAS. Five nested logistic regression, random forest, and XGBoost models progressively added age, ancestry, and within-ancestry genetic principal components (Model 1), environmental and reproductive factors (Model 2), symptom and comorbidity indicators (Model 3), all covariates combined (Model 4), and PRS x environment interactions (Model 5). Performance was assessed by AUROC in a held-out test set and 5-fold cross-validation, with class-weighted, Youden-optimized thresholds used for sensitivity, specificity, and predictive values; permutation importance identified top contributors. Pairwise AUROC differences were tested with a Holm-corrected DeLong-type test. Results: Discrimination improved from AUROC 0.63 (PRS, age, ancestry, principal components) to 0.72 for the full model, driven mainly by symptom and comorbidity data. XGBoost consistently outperformed logistic regression and random forest. The PRS ranked among the top individual predictors by permutation importance in nearly every model, alongside age, while genetic and demographic information alone gave only modest discrimination, and PRS x environment interactions did not improve on environmental factors alone. Threshold optimization yielded balanced sensitivity and specificity (~0.67/0.65) versus near-zero sensitivity at a default threshold. Conclusions: Combining the PRS with symptom and comorbidity data gave the best discrimination compared to solely a well-powered, multi-ancestry PRS as a predictor of endometriosis. This study clarifies both the promise and current limits of hybrid genetic-clinical prediction for endometriosis and points to symptom-based phenotyping, molecular subtyping, and external validation as priorities.

Abstract Objective: Glaucoma is a chronic disorder that impairs ocular health and may exacerbate ocular surface disease leading to tear film instability, dry eye symptoms and decreased quality of life. This study compared changes in tear quantity among glaucoma subjects living with and without diabetes mellitus, attending an eye clinic in Nigeria. Methods: A comparative cross sectional research design was used. 157 subjects which comprised 74 glaucoma subjects living with diabetes mellitus and 83 glaucoma subjects living without diabetes mellitus participated in the study. Tear quantity assessment included the Schirmer I test and tear meniscus height (TMH) measurement. Descriptive statistics, independent samples t-test and Chi-square test were used to examine the data at 0.05 level of significance. Results: Glaucoma subjects living with diabetes mellitus showed substantially decreased tear production (11.4 +/- 6.8 mm) compared with glaucoma subjects living without diabetes mellitus (19.6 +/- 9.6 mm; p < 0.001). Tear meniscus height in glaucoma subjects living with diabetes mellitus (0.8 +/- 0.3 mm) was significantly greater than in subjects living without diabetes mellitus (0.7 +/- 0.3 mm; p = 0.034). Conclusion: Diabetes mellitus dramatically deteriorates the ocular surface function in glaucoma subjects by decreasing tear production, altering the tear meniscus height and increasing the severity of ocular surface symptoms. Routine glaucoma care, especially in patients with diabetes mellitus, should include a full ocular surface evaluation including Schirmer I test, TBUT, TMH, and OSDI assessment to allow early detection and management of ocular surface disease, better treatment adherence, and improved visual outcomes. Keywords: Glaucoma, Diabetes Mellitus, Tear production, Tear Meniscus Height, Ocular Surface Disease.

ZNF217 is an established oncogenic transcription factor that promotes cancer progression and therapeutic resistance; however, the mechanisms regulating ZNF217 protein abundance remain poorly understood. Here, we identify ubiquitin-specific peptidase 15 (USP15) as a critical regulator of ZNF217 stability and define a reciprocal USP15-ZNF217 signaling loop that sustains malignant phenotypes in ovarian cancer. Stable overexpression of ZNF217 in OVCA420 ovarian cancer cells enhanced proliferation, epithelial-mesenchymal transition, migration, invasion, and extracellular matrix adhesion. Notably, ZNF217 overexpression increased USP15 protein abundance without altering USP15 mRNA levels, whereas ZNF217 depletion reduced USP15 protein levels, suggesting post-transcriptional regulation. Conversely, USP15 depletion markedly reduced ZNF217 protein abundance while increasing ZNF217 mRNA levels, indicating that USP15 regulates ZNF217 predominantly at the post-transcriptional level. Proteasome inhibition restored ZNF217 protein levels following USP15 depletion, further demonstrating that USP15 promotes ZNF217 protein stability. Functionally, USP15 depletion in ZNF217-overexpressing ovarian cancer cells suppressed proliferation and multiple metastatic phenotypes, including migration, invasion, extracellular matrix adhesion, anoikis resistance, and multicellular aggregate formation. In vivo, USP15 depletion significantly reduced tumor progression and metastatic burden and prolonged survival in mice bearing ZNF217-driven ovarian tumors. Furthermore, USP15 depletion enhanced the sensitivity of ZNF217-overexpressing cells to carboplatin, paclitaxel, and doxorubicin. Collectively, these findings identify USP15 as an upstream regulator of ZNF217 protein stability and reveal a positive-feedback loop between USP15 and ZNF217 that reinforces oncogenic signaling. Targeting USP15 may therefore represent an indirect therapeutic strategy for suppressing ZNF217-driven ovarian cancer, particularly given the challenges associated with directly targeting oncogenic transcription factors.

High-grade serous ovarian carcinoma (HGSC) responds poorly to immune checkpoint blockade, partly due to a macrophage-dominated immunosuppressive microenvironment. We integrated single-cell spatial proteomics and spatial transcriptomics across 50 HGSC tumors and applied SPACEstat to resolve higher-order immune communities and their transcriptional programs. We identified six immune community types, with macrophage-dominated Myelonets representing the predominant spatial pattern of immune organisation. In chemotherapy-exposed tumors, Myelonets showed coordinated lipid metabolism-immunosuppression and inflammation-MHC-II macrophage transcriptional programs, with SPP1, C1Q, VEGF, MMPs, and CCL18 linked to immunosuppressive states and fibroblasts emerging as key mediators of macrophage communication. Chemotherapy contracted large Myelonets while increasing CD8+ T-cell organization into Lymphonets. Persistent macrophage dominance within Myelonets was associated with adverse outcomes among patients who achieved a complete response to treatment. Together, we identify Myelonets as clinically relevant, multicellular immunoregulatory niches sustained by spatiotemporally coordinated macrophage programs and stromal crosstalk.

Objective: The ocular surface is an integral unit of the visual system. Its smooth and wet surface which is maintained by the tear film, is the most important refractive interface of the visual system. This study compared ocular surface alterations among glaucoma subjects living with and without diabetes mellitus in a Owerri, Imo State, Nigeria Methods: Subjects diagnosed of glaucoma living with and without diabetes mellitus were included in the study. Ocular surface assessment included the Ocular Surface Disease Index (OSDI) questionnaire, and tear break-up time (TBUT). Descriptive statistics, independent samples t-test and Chi-square test were used to examine the data at 0.05 level of significance. Results: Considerable shorter tear break-up time (11.3 +/- 9.0s) was seen among glaucoma subjects living with diabetes mellitus than those living without diabetes mellitus (16.0 +/- 10.6s; p = 0.003), demonstrating the higher tear film instability. This was similarly reflected by the mean OSDI score, which was considerably higher in glaucoma patients living with diabetes mellitus (40.0 +/- 23.4) compared with those without diabetes mellitus (28.1 +/- 21.8; p = 0.001) showing a larger ocular surface symptom load. However, although the frequency of severe OSDI symptoms was greater in glaucoma subjects living with diabetes mellitus, the relationship between diabetes status and OSDI severity categories was not statistically significant ({chi} 2 = 7.584, p = 0.055). Conclusion: Diabetes mellitus significantly impacts the health of the ocular surface in glaucoma subjects. The combination of glaucoma and diabetes may result in more rapid tear film instability, increased ocular pain, and decreased quality of life and adherence to long-term glaucoma medication. Keywords: Glaucoma, Diabetes Mellitus, Tear Break Up Time, Ocular Surface Disease Index, Ocular surface symptoms