The evolution of metastatic upper tract urothelial carcinoma through genomic-transcriptomic and single-cell protein markers analysis.

The molecular characteristics of metastatic upper tract urothelial carcinoma (UTUC) are not well understood, and there is a lack of knowledge regarding the genomic and transcriptomic differences between primary and metastatic UTUC. To address these gaps, we integrate whole-exome sequencing, RNA sequencing, and Imaging Mass Cytometry using lanthanide metal-conjugated antibodies of 44 tumor samples from 28 patients with high-grade primary and metastatic UTUC. We perform a spatially-resolved single-cell analysis of cancer, immune, and stromal cells to understand the evolution of primary to metastatic UTUC. We discover that actionable genomic alterations are frequently discordant between primary and metastatic UTUC tumors in the same patient. In contrast, molecular subtype membership and immune depletion signature are stable across primary and matched metastatic UTUC. Molecular and immune subtypes are consistent between bulk RNA-sequencing and mass cytometry of protein markers from 340,798 single cells. Molecular subtypes at the single-cell level are highly conserved between primary and metastatic UTUC tumors within the same patient.

Canonical AREs are tumor suppressive regulatory elements in the prostate.

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

Nature's contribution to poverty alleviation, human wellbeing and the SDGs.

Millions of households globally rely on uncultivated ecosystems for their livelihoods. However, much of the understanding about the broader contribution of uncultivated ecosystems to human wellbeing is still based on a series of small-scale studies due to limited availability of large-scale datasets. We pooled together 11 comparable datasets comprising 232 settlements and 10,971 households in ten low-and middle-income countries, representing forest, savanna and coastal ecosystems to analyse how uncultivated nature contributes to multi-dimensional wellbeing and how benefits from nature are distributed between households. The resulting dataset integrates secondary data on rural livelihoods, multidimensional human wellbeing, household demographics, resource tenure and social-ecological context, primarily drawing on nine existing household surveys and their associated contextual information together with selected variables, such as travel time to cities, population density, local area GDP and land use and land cover from existing global datasets. This integrated dataset has been archived with ReShare (UK Data Service) and will be useful for further analyses on nature-wellbeing relationships on its own or in combination with similar datasets.

Semi-Supervised, Attention-Based Deep Learning for Predicting TMPRSS2:ERG Fusion Status in Prostate Cancer Using Whole Slide Images.

IMPLICATIONS: Our study illuminates the potential of deep learning in effectively inferring key prostate cancer genetic alterations from the tissue morphology depicted in routinely available histology slides, offering a cost-effective method that could revolutionize diagnostic strategies in oncology.

Distinct mesenchymal cell states mediate prostate cancer progression.

In the complex tumor microenvironment (TME), mesenchymal cells are key players, yet their specific roles in prostate cancer (PCa) progression remain to be fully deciphered. This study employs single-cell RNA sequencing to delineate molecular changes in tumor stroma that influence PCa progression and metastasis. Analyzing mesenchymal cells from four genetically engineered mouse models (GEMMs) and correlating these findings with human tumors, we identify eight stromal cell populations with distinct transcriptional identities consistent across both species. Notably, stromal signatures in advanced mouse disease reflect those in human bone metastases, highlighting periostin's role in invasion and differentiation. From these insights, we derive a gene signature that predicts metastatic progression in localized disease beyond traditional Gleason scores. Our results illuminate the critical influence of stromal dynamics on PCa progression, suggesting new prognostic tools and therapeutic targets.

HER2/ ERBB2 Immunohistochemical Expression and Copy Number Status in Ovarian Mucinous Tumors.

Primary mucinous ovarian carcinoma (MOC) is a rare ovarian epithelial cancer, which is often refractory to chemotherapy. HER2-targeting therapy is being increasingly considered in gynecologic malignancies. Although there have been limited studies examining the HER2 status of such tumors, the criteria for HER2 expression scoring have not been standardized for MOC as it has for other sites. This study aimed to survey immunohistochemical HER2 expression patterns in MOC and its precursor, mucinous borderline tumor in correlation with fluorescence in situ hybridization (FISH). Immunohistochemistry (IHC) for HER2 was performed on 12 cases of MOC and 15 mucinous borderline tumors, including 7 with intraepithelial carcinoma. HER2 expression was quantified using the gastric/gastroesophageal carcinoma protocol. Cases were considered 3+ if the tumor cells displayed strong complete or basolateral/lateral membranous staining in ≥10% of tumor cells. Cases (2+) had weak to moderate staining in ≥10% of tumor cells. Cases (1+) had faint staining in ≥10% of tumor cells. Cases considered 0 had no staining or faint staining in <10% of tumor cells. HER2 expression was also quantified with the endometrial serous carcinoma protocol, which uses a 30% tumor cell positivity cutoff. FISH for HER2 was performed on all 3+ and 2+ and a subset of 1+ cases. Of the MOC cases, 25% were 3+ and 1 mucinous borderline tumor with intraepithelial carcinoma had 3+ staining. All 3+ IHC MOC cases had >30% basolateral membranous staining. HER2 amplification was confirmed by FISH on all 3+ IHC cases and in one 2+ IHC case of MOC. Up to 25% of mucinous ovarian tumors showed HER2 IHC overexpression with an excellent correlation between IHC and FISH using the HER2 scoring protocol for either gastric/gastroesophageal carcinoma or uterine serous carcinoma.

Identifying deprived "slum" neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data.

Background: Identifying urban deprived areas, including slums, can facilitate more targeted planning and development policies in cities to reduce socio-economic and health inequities, but methods to identify them are often ad-hoc, resource intensive, and cannot keep pace with rapidly urbanizing communities. Objectives: We apply a spatial modelling approach to identify census enumeration areas (EAs) in the Greater Accra Metropolitan Area (GAMA) of Ghana with a high probability of being a deprived area using publicly available census and remote sensing data. Methods: We obtained United Nations (UN) supported field mapping data that identified deprived "slum" areas in Accra's urban core, data on housing and population conditions from the most recent census, and remotely sensed data on environmental conditions in the GAMA. We first fitted a Bayesian logistic regression model on the data in Accra's urban core (n=2,414 EAs) that estimated the relationship between housing, population, and environmental predictors and being a deprived area according to the UN's deprived area assessment. Using these relationships, we predicted the probability of being a deprived area for each of the 4,615 urban EAs in GAMA. Results: 899 (19%) of the 4,615 urban EAs in GAMA, with an estimated 745,714 residents (22% of its urban population), had a high predicted probability (≥80%) of being a deprived area. These deprived EAs were dispersed across GAMA and relatively heterogeneous in their housing and environmental conditions, but shared some common features including a higher population density, lower elevation and vegetation abundance, and less access to indoor piped water and sanitation. Conclusion: Our approach using ubiquitously available administrative and satellite data can be used to identify deprived neighbourhoods where interventions are warranted to improve living conditions, and track progress in achieving the Sustainable Development Goals aiming to reduce the population living in unsafe or vulnerable human settlements.

Evolution of structural rearrangements in prostate cancer intracranial metastases.

Intracranial metastases in prostate cancer are uncommon but clinically aggressive. A detailed molecular characterization of prostate cancer intracranial metastases would improve our understanding of their pathogenesis and the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) of 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n = 6) and nonbrain prostate cancer metastases (n = 36). This first whole genome sequencing study of prostate intracranial metastases led to several new insights. First, there was a higher diversity of complex structural alterations in prostate cancer intracranial metastases compared to primary tumor tissues. Chromothripsis and chromoplexy events seemed to dominate, yet there were few enrichments of specific categories of structural variants compared with non-brain metastases. Second, aberrations involving the AR gene, including AR enhancer gain were observed in 7/10 (70%) of intracranial metastases, as well as recurrent loss of function aberrations involving TP53 in 8/10 (80%), RB1 in 2/10 (20%), BRCA2 in 2/10 (20%), and activation of the PI3K/AKT/PTEN pathway in 8/10 (80%). These alterations were frequently present in tumor tissues from other sites of disease obtained concurrently or sequentially from the same individuals. Third, clonality analysis points to genomic factors and evolutionary bottlenecks that contribute to metastatic spread in patients with prostate cancer. These results describe the aggressive molecular features underlying intracranial metastasis that may inform future diagnostic and treatment approaches.

Factors that affect water column hydrocarbon concentrations have minor impacts on microbial responses following simulated diesel fuel spills.

Effects of season and mixing on hydrocarbon concentrations and the microbial community response was explored in a series of mesocosm experiments simulating surface spills of diesel into coastal waters. Mixing of any amount contributed to hydrocarbons entering the water column, but diesel fuel composition had a significant effect on hydrocarbon concentrations. Higher initial concentrations of aromatic hydrocarbons resulted in higher water column concentrations, with minimal differences among seasons due to high variability. Regardless of the concentrations of hydrocarbons, prokaryotes increased and there were higher relative abundances of hydrocarbon affiliated bacteria with indications of biodegradation within 4 d of exposure. As concentrations decreased over time, the eukaryote community shifted from the initial community to one which appeared to be composed of organisms with some resilience to hydrocarbons. This series of experiments demonstrates the wide range of conditions under which natural attenuation of diesel fuel is an effective response.

The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer.

Although recent efforts have led to the development of highly effective androgen receptor (AR)-directed therapies for the treatment of advanced prostate cancer, a significant subset of patients will progress with resistant disease including AR-negative tumors that display neuroendocrine features [neuroendocrine prostate cancer (NEPC)]. On the basis of RNA sequencing (RNA-seq) data from a clinical cohort of tissue from benign prostate, locally advanced prostate cancer, metastatic castration-resistant prostate cancer and NEPC, we developed a multi-step bioinformatics pipeline to identify NEPC-specific, overexpressed gene transcripts that encode cell surface proteins. This included the identification of known NEPC surface protein CEACAM5 as well as other potentially targetable proteins (e.g., HMMR and CESLR3). We further showed that cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) knockdown results in reduced NEPC tumor cell proliferation and migration in vitro. We provide in vivo data including laser capture microdissection followed by RNA-seq data supporting a causal role of CELSR3 in the development and/or maintenance of the phenotype associated with NEPC. Finally, we provide initial data that suggests CELSR3 is a target for T-cell redirection therapeutics. Further work is now needed to fully evaluate the utility of targeting CELSR3 with T-cell redirection or other similar therapeutics as a potential new strategy for patients with NEPC. Significance: The development of effective treatment for patients with NEPC remains an unmet clinical need. We have identified specific surface proteins, including CELSR3, that may serve as novel biomarkers or therapeutic targets for NEPC.

SPOP Mutations Target STING1 Signaling in Prostate Cancer and Create Therapeutic Vulnerabilities to PARP Inhibitor-Induced Growth Suppression.

PURPOSE: Speckle-type POZ protein (SPOP) is important in DNA damage response (DDR) and maintenance of genomic stability. Somatic heterozygous missense mutations in the SPOP substrate-binding cleft are found in up to 15% of prostate cancers. While mutations in SPOP predict for benefit from androgen receptor signaling inhibition (ARSi) therapy, outcomes for patients with SPOP-mutant (SPOPmut) prostate cancer are heterogeneous and targeted treatments for SPOPmut castrate-resistant prostate cancer (CRPC) are lacking. EXPERIMENTAL DESIGN: Using in silico genomic and transcriptomic tumor data, proteomics analysis, and genetically modified cell line models, we demonstrate mechanistic links between SPOP mutations, STING signaling alterations, and PARP inhibitor vulnerabilities. RESULTS: We demonstrate that SPOP mutations are associated with upregulation of a 29-gene noncanonical (NC) STING (NC-STING) signature in a subset of SPOPmut, treatment-refractory CRPC patients. We show in preclinical CRPC models that SPOP targets and destabilizes STING1 protein, and prostate cancer-associated SPOP mutations result in upregulated NC-STING-NF-κB signaling and macrophage- and tumor microenvironment (TME)-facilitated reprogramming, leading to tumor cell growth. Importantly, we provide in vitro and in vivo mechanism-based evidence that PARP inhibitor (PARPi) treatment results in a shift from immunosuppressive NC-STING-NF-κB signaling to antitumor, canonical cGAS-STING-IFNß signaling in SPOPmut CRPC and results in enhanced tumor growth inhibition. CONCLUSIONS: We provide evidence that SPOP is critical in regulating immunosuppressive versus antitumor activity downstream of DNA damage-induced STING1 activation in prostate cancer. PARPi treatment of SPOPmut CRPC alters this NC-STING signaling toward canonical, antitumor cGAS-STING-IFNß signaling, highlighting a novel biomarker-informed treatment strategy for prostate cancer.

Evaluating the Learning Curve for In-office Freehand Cognitive Fusion Transperineal Prostate Biopsy.

OBJECTIVE: To define the learning curve of the in-office, freehand MRI-ultrasound cognitive fusion transperineal prostate biopsy (CTPB) by assessing cancer detection, biopsy core quantity and quality, procedure times, and complications over the initial experience. METHODS: We reviewed 110 consecutive CTPB performed March 2021-September 2022 by a urologist inexperienced with the PrecisionPoint platform. The study period was divided into quarters to assess for temporal variation in outcomes. Univariable and multivariable analysis modeled the learning curve. RESULTS: Across quarters, there were no differences in the detection of clinically significant prostate cancer (Q1:50%, Q2:52%, Q3:50%, Q4:48%, P > .9) or Gleason grade group upgrading by targeted vs systematic biopsy (P = .6). Median procedure times improved with experience (Q1:17 minutes, Q2:14 minutes, Q3:12 minutes, Q4:13 minutes, P = .018). On multivariable analysis, procedure times decreased by 1minute per 20 cases (P < .001). On linear regression, CTPB procedure times approximated transrectal biopsy times after 90 cases (P < .001). The histopathologic core quality did not differ, as evidenced by consistent core length (P = .13) and presence of minimal fibromuscular tissue (P > .9). The most common complications, hematuria and hematospermia, were similar across quarters (P = .7, P = .3, respectively). There was a single episode of urinary retention and no reported infections. CONCLUSION: There is no evidence of a learning curve for CTPB as shown by consistent clinically significant prostate cancer detection, high-quality biopsy cores, and low complications. However, CTPB procedural times begin to approximate cognitive targeted transrectal biopsy times after 90 cases.

NSD2 maintains lineage plasticity and castration-resistance in neuroendocrine prostate cancer.

The clinical use of potent androgen receptor (AR) inhibitors has promoted the emergence of novel subtypes of metastatic castration-resistant prostate cancer (mCRPC), including neuroendocrine prostate cancer (CRPC-NE), which is highly aggressive and lethal 1 . These mCRPC subtypes display increased lineage plasticity and often lack AR expression 2-5 . Here we show that neuroendocrine differentiation and castration-resistance in CRPC-NE are maintained by the activity of Nuclear Receptor Binding SET Domain Protein 2 (NSD2) 6 , which catalyzes histone H3 lysine 36 dimethylation (H3K36me2). We find that organoid lines established from genetically-engineered mice 7 recapitulate key features of human CRPC-NE, and can display transdifferentiation to neuroendocrine states in culture. CRPC-NE organoids express elevated levels of NSD2 and H3K36me2 marks, but relatively low levels of H3K27me3, consistent with antagonism of EZH2 activity by H3K36me2. Human CRPC-NE but not primary NEPC tumors expresses high levels of NSD2, consistent with a key role for NSD2 in lineage plasticity, and high NSD2 expression in mCRPC correlates with poor survival outcomes. Notably, CRISPR/Cas9 targeting of NSD2 or expression of a dominant-negative oncohistone H3.3K36M mutant results in loss of neuroendocrine phenotypes and restores responsiveness to the AR inhibitor enzalutamide in mouse and human CRPC-NE organoids and grafts. Our findings indicate that NSD2 inhibition can reverse lineage plasticity and castration-resistance, and provide a potential new therapeutic target for CRPC-NE.

Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning.

Cities in the developing world are expanding rapidly, and undergoing changes to their roads, buildings, vegetation, and other land use characteristics. Timely data are needed to ensure that urban change enhances health, wellbeing and sustainability. We present and evaluate a novel unsupervised deep clustering method to classify and characterise the complex and multidimensional built and natural environments of cities into interpretable clusters using high-resolution satellite images. We applied our approach to a high-resolution (0.3 m/pixel) satellite image of Accra, Ghana, one of the fastest growing cities in sub-Saharan Africa, and contextualised the results with demographic and environmental data that were not used for clustering. We show that clusters obtained solely from images capture distinct interpretable phenotypes of the urban natural (vegetation and water) and built (building count, size, density, and orientation; length and arrangement of roads) environment, and population, either as a unique defining characteristic (e.g., bodies of water or dense vegetation) or in combination (e.g., buildings surrounded by vegetation or sparsely populated areas intermixed with roads). Clusters that were based on a single defining characteristic were robust to the spatial scale of analysis and the choice of cluster number, whereas those based on a combination of characteristics changed based on scale and number of clusters. The results demonstrate that satellite data and unsupervised deep learning provide a cost-effective, interpretable and scalable approach for real-time tracking of sustainable urban development, especially where traditional environmental and demographic data are limited and infrequent.

The KDM5B and KDM1A lysine demethylases cooperate in regulating androgen receptor expression and signalling in prostate cancer.

Histone H3 lysine 4 (H3K4) methylation is key epigenetic mark associated with active transcription and is a substrate for the KDM1A/LSD1 and KDM5B/JARID1B lysine demethylases. Increased expression of KDM1A and KDM5B is implicated in many cancer types, including prostate cancer (PCa). Both KDM1A and KDM5B interact with AR and promote androgen regulated gene expression. For this reason, there is great interested in the development of new therapies targeting KDM1A and KDM5B, particularly in the context of castrate resistant PCa (CRPC), where conventional androgen deprivation therapies and androgen receptor signalling inhibitors are no longer effective. As there is no curative therapy for CRPC, new approaches are urgently required to suppress androgen signalling that prevent, delay or reverse progression to the castrate resistant state. While the contribution of KDM1A to PCa is well established, the exact contribution of KDM5B to PCa is less well understood. However, there is evidence that KDM5B is implicated in numerous pro-oncogenic mechanisms in many different types of cancer, including the hypoxic response, immune evasion and PI3/AKT signalling. Here we elucidate the individual and cooperative functions of KDM1A and KDM5B in PCa. We show that KDM5B mRNA and protein expression is elevated in localised and advanced PCa. We show that the KDM5 inhibitor, CPI-455, impairs androgen regulated transcription and alternative splicing. Consistent with the established role of KDM1A and KDM5B as AR coregulators, we found that individual pharmacologic inhibition of KDM1A and KDM5 by namoline and CPI-455 respectively, impairs androgen regulated transcription. Notably, combined inhibition of KDM1A and KDM5 downregulates AR expression in CRPC cells. Furthermore, combined KDM1A and KDM5 inhibition impairs PCa cell proliferation and invasion more than individual inhibition of KDM1A and KDM5B. Collectively our study has identified individual and cooperative mechanisms involving KDM1A and KDM5 in androgen signalling in PCa. Our findings support the further development of KDM1A and KDM5B inhibitors to treat advanced PCa. Further work is now required to confirm the therapeutic feasibility of combined inhibition of KDM1A and KDM5B as a novel therapeutic strategy for targeting AR positive CRPC.

Self-management for sickle cell disease among patients and parents: A qualitative study.

OBJECTIVE: This study aimed to explore self-management practices among patients and parents of children with sickle cell disease (SCD). METHODS: The qualitative descriptive design was employed. The study involved 19 participants comprising adult SCD patients ≥16 years, and nine parents of SCD children ≤ 15 years. Purposive sampling was conducted to select participants from a teaching hospital and SCD association. Data was collected using one-on-one interviews, transcribed verbatim, and analysed using qualitative content analysis. RESULTS: Self-management was reported through four categories including preventive health, self-monitoring, self-diagnosis, and self-treatment. Hydration, nutrition, activity limitation, avoidance of cold temperatures, and supportive medications were the most common preventive health actions. Regarding self-monitoring and self-diagnosis, the parents emphasized objective indicators such as changes in urine and eye colour compared to the adults who utilize subjective indicators such as feeling unwell and easy fatigue. Pharmacological and non-pharmacological measures were reported by both groups for treating painful episodes, fever, leg ulcers, priapism, and unspecified symptoms. DISCUSSION: The participants in this study practice several self-management actions with some differences in application between adults and children. Tailored self-management services may be helpful for adults and children when developing services for SCD patients.

Targeting altered glycosylation in secreted tumor glycoproteins for broad cancer detection.

There is an urgent need to develop new tumor biomarkers for early cancer detection, but the variability of tumor-derived antigens has been a limitation. Here we demonstrate a novel anti-Tn antibody microarray platform to detect Tn+ glycoproteins, a near universal antigen in carcinoma-derived glycoproteins, for broad detection of cancer. The platform uses a specific recombinant IgG1 to the Tn antigen (CD175) as a capture reagent and a recombinant IgM to the Tn antigen as a detecting reagent. These reagents were validated by immunohistochemistry in recognizing the Tn antigen using hundreds of human tumor specimens. Using this approach, we could detect Tn+ glycoproteins at subnanogram levels using cell lines and culture media, serum, and stool samples from mice engineered to express the Tn antigen in intestinal epithelial cells. The development of a general cancer detection platform using recombinant antibodies for detection of altered tumor glycoproteins expressing a unique antigen could have a significant impact on cancer detection and monitoring.

Distinct mesenchymal cell states mediate prostate cancer progression.

Alterations in tumor stroma influence prostate cancer progression and metastatic potential. However, the molecular underpinnings of this stromal-epithelial crosstalk are largely unknown. Here, we compare mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for common and GEMM-specific transcriptional programs. We show that stromal responses are conserved in mouse models and human prostate cancers with the same genomic alterations. We noted striking similarities between the transcriptional profiles of the stroma of murine models of advanced disease and those of of human prostate cancer bone metastases. These profiles were then used to build a robust gene signature that can predict metastatic progression in prostate cancer patients with localized disease and is also associated with progression-free survival independent of Gleason score. Taken together, this offers new evidence that stromal microenvironment mediates prostate cancer progression, further identifying tissue-based biomarkers and potential therapeutic targets of aggressive and metastatic disease.