STEAP2 promotes hepatocellular carcinoma progression via increased copper levels and stress-activated MAP kinase activity.

Six Transmembrane Epithelial Antigen of Prostate 2 (STEAP2) belongs to a family of metalloreductases, which indirectly aid in uptake of iron and copper ions. Its role in hepatocellular carcinoma (HCC) remains to be characterized. Here, we report that STEAP2 expression was upregulated in HCC tumors compared with paired adjacent non-tumor tissues by RNA sequencing, RT-qPCR, Western blotting, and immunostaining. Public HCC datasets demonstrated upregulated STEAP2 expression in HCC and positive association with tumor grade. Transient and stable knockdown (KD) of STEAP2 in HCC cell lines abrogated their malignant phenotypes in vitro and in vivo, while STEAP2 overexpression showed opposite effects. STEAP2 KD in HCC cells led to significant alteration of genes associated with extracellular matrix organization, cell adhesion/chemotaxis, negative enrichment of an invasiveness signature gene set, and inhibition of cell migration/invasion. STEAP2 KD reduced intracellular copper levels and activation of stress-activated MAP kinases including p38 and JNK. Treatment with copper rescued the reduced HCC cell migration due to STEAP2 KD and activated p38 and JNK. Furthermore, treatment with p38 or JNK inhibitors significantly inhibited copper-mediated cell migration. Thus, STEAP2 plays a malignant-promoting role in HCC cells by driving migration/invasion via increased copper levels and MAP kinase activities. Our study uncovered a novel molecular mechanism contributing to HCC malignancy and a potential therapeutic target for HCC treatment.

GametesOmics: A Comprehensive Multi-omics Database for Exploring the Gametogenesis in Humans and Mice.

Gametogenesis plays an important role in the reproduction and evolution of species. The transcriptomic and epigenetic alterations in this process can influence the reproductive capacity, fertilization, and embryonic development. The rapidly increasing single-cell studies have provided valuable multi-omics resources. However, data from different layers and sequencing platforms have not been uniformed and integrated, which greatly limits their use for exploring the molecular mechanisms that underlie oogenesis and spermatogenesis. Here, we develop GametesOmics, a comprehensive database that integrates the data of gene expression, DNA methylation, and chromatin accessibility during oogenesis and spermatogenesis in humans and mice. GametesOmics provides a user-friendly website and various tools, including Search and Advanced Search for querying the expression and epigenetic modification(s) of each gene; Tools with Differentially expressed gene (DEG) analysis for identifying DEGs, Correlation analysis for demonstrating the genetic and epigenetic changes, Visualization for displaying single-cell clusters and screening marker genes as well as master transcription factors (TFs), and MethylView for studying the genomic distribution of epigenetic modifications. GametesOmics also provides Genome Browser and Ortholog for tracking and comparing gene expression, DNA methylation, and chromatin accessibility between humans and mice. GametesOmics offers a comprehensive resource for biologists and clinicians to decipher the cell fate transition in germ cell development, and can be accessed at http://gametesomics.cn/.

Pharmacological inhibition of the LIF/LIFR autocrine loop reveals vulnerability of ovarian cancer cells to ferroptosis.

Of all gynecologic cancers, epithelial-ovarian cancer (OCa) stands out with the highest mortality rates. Despite all efforts, 90% of individuals who receive standard surgical and cytotoxic therapy experience disease recurrence. The precise mechanism by which leukemia inhibitory factor (LIF) and its receptor (LIFR) contribute to the progression of OCa remains unknown. Analysis of cancer databases revealed that elevated expression of LIF or LIFR was associated with poor progression-free survival of OCa patients and a predictor of poor response to chemotherapy. Using multiple primary and established OCa cell lines or tissues that represent five subtypes of epithelial-OCa, we demonstrated that LIF/LIFR autocrine signaling is active in OCa. Moreover, treatment with LIFR inhibitor, EC359 significantly reduced OCa cell viability and cell survival with an IC50 ranging from 5-50 nM. Furthermore, EC359 diminished the stemness of OCa cells. Mechanistic studies using RNA-seq and rescue experiments unveiled that EC359 primarily induced ferroptosis by suppressing the glutathione antioxidant defense system. Using multiple in vitro, ex vivo and in vivo models including cell-based xenografts, patient-derived explants, organoids, and xenograft tumors, we demonstrated that EC359 dramatically reduced the growth and progression of OCa. Additionally, EC359 therapy considerably improved tumor immunogenicity by robust CD45+ leukocyte tumor infiltration and polarizing tumor-associated macrophages (TAMs) toward M1 phenotype while showing no impact on normal T-, B-, and other immune cells. Collectively, our findings indicate that the LIF/LIFR autocrine loop plays an essential role in OCa progression and that EC359 could be a promising therapeutic agent for OCa.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients.

Background: The incidence and mortality rates of hepatocellular carcinoma (HCC) among Hispanics in the United States are much higher than those of non-Hispanic whites. We conducted comprehensive multi-omics analyses to understand molecular alterations in HCC among Hispanic patients. Methods: Paired tumor and adjacent non-tumor samples were collected from 31 Hispanic HCC in South Texas (STX-Hispanic) for genomic, transcriptomic, proteomic, and metabolomic profiling. Additionally, serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed HCC. Results: Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in STX Hispanic HCCs, suggesting a predominant activation of the Wnt/ß-catenin pathway. The TERT promoter mutation frequency was also remarkably high in the Hispanic cohort. Cell cycles and liver functions were identified as positively- and negatively-enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in the serum samples of HCC patients. Two HCC subtypes from our Hispanic cohort were identified and validated with the TCGA liver cancer cohort. The subtype with better overall survival showed higher activity of immune and angiogenesis signatures, and lower activity of liver function-related gene signatures. It also had higher levels of immune checkpoint and immune exhaustion markers. Conclusions: Our study revealed some specific molecular features of Hispanic HCC and potential biomarkers for therapeutic management of HCC and provides a unique resource for studying Hispanic HCC.

Mesenteric adipose-derived exosomal TINAGL1 enhances intestinal fibrosis in Crohn's Disease via SMAD4.

INTRODUCTION: Crohn's Disease (CD) is a chronic inflammatory condition characterized by intestinal fibrosis, severely impacting patient quality of life. The molecular mechanisms driving this fibrosis remain inadequately understood. Recent evidence implicates mesenteric adipose tissue (MAT) in CD pathogenesis, particularly through its exosome secretion, which may influence fibrogenic pathways. Understanding the role of MAT-derived exosomes is crucial for unraveling these molecular processes. OBJECTIVES: This study aims to elucidate the role of MAT-derived exosomes in CD-related intestinal fibrosis. We focus on investigating their molecular composition and the potential impact on fibrosis progression, with an emphasis on identifying novel therapeutic targets. METHODS: We induced chronic intestinal inflammation in mice using dinitrobenzene sulfonic acid (DNBS), simulating CD-like fibrosis. Exosomes were isolated from DNBS-treated mice (MG) and normal controls (NG) for characterization using electron microscopy and proteomic analysis. Additionally, human colonic fibroblasts were exposed to exosomes from CD patients and healthy individuals, with subsequent assessment of fibrogenesis through proteomic and RNA sequencing analyses. RESULTS: Proteomic analyses revealed a significant activation of the TGF-ß signaling pathway in MG-treated mice compared to controls, correlating with enhanced intestinal fibrosis. In vitro experiments demonstrated that colonic fibroblasts exposed to CD patient-derived exosomes exhibited increased fibrogenic activity. Protein docking and co-immunoprecipitation studies suggested a critical interaction between TINAGL1 and SMAD4, enhancing fibrosis. Importantly, in vivo experiments corroborated that recombinant TINAGL1 protein exacerbated DNBS-induced intestinal fibrosis. CONCLUSION: Our findings highlight the pivotal role of MAT-derived exosomes, particularly those carrying TINAGL1, in the progression of intestinal fibrosis in CD. The involvement of the TGF-ß signaling pathway, especially the SMAD4 protein, offers new insights into the molecular mechanisms of CD-related fibrosis and presents potential targets for therapeutic intervention.

A Metastatic Cancer Expression Generator (MetGen): A Generative Contrastive Learning Framework for Metastatic Cancer Generation.

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

Avanzando Caminos (Leading Pathways): Design and Procedures of The Hispanic/Latino Cancer Survivorship Study.

PURPOSE: Avanzando Caminos (Leading Pathways): The Hispanic/Latino Cancer Survivorship Cohort Study aims to examine the influence of sociocultural, medical, stress, psychosocial, lifestyle, behavioral, and biological factors on symptom burden, health-related quality of life, and clinical outcomes among Hispanics/Latinos who have been previously treated for cancer. METHODS: Avanzando Caminos is a prospective, cohort-based study of 3,000 Hispanics/Latinos who completed primary cancer treatment within the past five years that is representative of the general Hispanic/Latino population in the U.S. Participants will complete self-report measures at baseline (T1), 6 months (T2), 1 year (T3), 2 years (T4), 3 years (T5), 4 years (T6), and 5 years (T7). Blood draws to assess leukocyte gene expression, cardiometabolic markers, and genetic admixture will be collected at baseline (T1), 1 year (T3), 3 years (T5), and 5 years (T7). Medical and cancer characteristics and clinical outcomes will be extracted from the electronic medical record and/or state cancer registry at each time point. Data analysis will include general latent variable modeling and latent growth modeling. CONCLUSIONS: Avanzando Caminos will fill critical gaps in knowledge to guide future secondary and tertiary prevention efforts to mitigate cancer disparities and optimize health-related quality of life among Hispanic/Latino cancer survivors.

Predicting drug response through tumor deconvolution by cancer cell lines.

Large-scale cancer drug sensitivity data have become available for a collection of cancer cell lines, but only limited drug response data from patients are available. Bridging the gap in pharmacogenomics knowledge between in vitro and in vivo datasets remains challenging. In this study, we trained a deep learning model, Scaden-CA, for deconvoluting tumor data into proportions of cancer-type-specific cell lines. Then, we developed a drug response prediction method using the deconvoluted proportions and the drug sensitivity data from cell lines. The Scaden-CA model showed excellent performance in terms of concordance correlation coefficients (>0.9 for model testing) and the correctly deconvoluted rate (>70% across most cancers) for model validation using Cancer Cell Line Encyclopedia (CCLE) bulk RNA data. We applied the model to tumors in The Cancer Genome Atlas (TCGA) dataset and examined associations between predicted cell viability and mutation status or gene expression levels to understand underlying mechanisms of potential value for drug repurposing.

shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning.

Advancing precision oncology requires accurate prediction of treatment response and accessible prediction models. To this end, we present shinyDeepDR, a user-friendly implementation of our innovative deep learning model, DeepDR, for predicting anti-cancer drug sensitivity. The web tool makes DeepDR more accessible to researchers without extensive programming experience. Using shinyDeepDR, users can upload mutation and/or gene expression data from a cancer sample (cell line or tumor) and perform two main functions: "Find Drug," which predicts the sample's response to 265 approved and investigational anti-cancer compounds, and "Find Sample," which searches for cell lines in the Cancer Cell Line Encyclopedia (CCLE) and tumors in The Cancer Genome Atlas (TCGA) with genomics profiles similar to those of the query sample to study potential effective treatments. shinyDeepDR provides an interactive interface to interpret prediction results and to investigate individual compounds. In conclusion, shinyDeepDR is an intuitive and free-to-use web tool for in silico anti-cancer drug screening.

Structural Engineering of Iridium(III) Phosphors with Imidazo[4,5-b]pyrazin-2-ylidene Cyclometalates for Efficient Blue Electroluminescence.

Iridium(III) complexes are particularly noted for their excellent potentials in fabrication of blue organic light-emitting diodes (OLEDs), but the severe efficiency roll-off largely hampered their practical applications. To reveal the underlying characteristics, three Ir(III) complexes, namely f-ct5c, f-ct5d, and f-ct11, bearing imidazo[4,5-b]pyrazin-2-ylidene cyclometalates are prepared and characterized in detail. Both f-ct5c and f-ct5d (also their mixture f-ct5mix) gave intensive blue emissions peaking at ≈465 nm with short radiative lifetimes of 1.76 and 2.45 µs respectively, in degassed toluene. Alternatively, f-ct11 with two 4-tert-butylphenyl substituents on each imidazo[4,5-b]pyrazin-2-ylidene entity, possessed a bluish-green emission (508 nm) together with an extended radiative lifetime of 34.3 µs in the dispersed PMMA matrix. Consequently, the resulting solution-processed OLED with f-ct11 delivered a maximum external quantum efficiency (EQEmax ) of 6.5% with serious efficiency roll-offs. In contrast, f-ct5mix based device achieved a high EQEmax of 27.2% and the EQE maintained at 23.0% of 1000 cd m-2 . Furthermore, the hyper-OLEDs with f-ct5mix as the sensitizer and v-DABNA as the terminal emitter afford narrowed emission with a considerably high EQEmax exceeding 32%, affirming the potential of f-ct5mix to serve as both the emitter and sensitizer in OLEDs.

Reconstitution of human PDAC using primary cells reveals oncogenic transcriptomic features at tumor onset.

Animal studies have demonstrated the ability of pancreatic acinar cells to transform into pancreatic ductal adenocarcinoma (PDAC). However, the tumorigenic potential of human pancreatic acinar cells remains under debate. To address this gap in knowledge, we expand sorted human acinar cells as 3D organoids and genetically modify them through introduction of common PDAC mutations. The acinar organoids undergo dramatic transcriptional alterations but maintain a recognizable DNA methylation signature. The transcriptomes of acinar organoids are similar to those of disease-specific cell populations. Oncogenic KRAS alone do not transform acinar organoids. However, acinar organoids can form PDAC in vivo after acquiring the four most common driver mutations of this disease. Similarly, sorted ductal cells carrying these genetic mutations can also form PDAC, thus experimentally proving that PDACs can originate from both human acinar and ductal cells. RNA-seq analysis reveal the transcriptional shift from normal acinar cells towards PDACs with enhanced proliferation, metabolic rewiring, down-regulation of MHC molecules, and alterations in the coagulation and complement cascade. By comparing PDAC-like cells with normal pancreas and PDAC samples, we identify a group of genes with elevated expression during early transformation which represent potential early diagnostic biomarkers.

TGFß and Hippo Signaling Pathways Coordinate to Promote Acinar to Ductal Metaplasia in Human Pancreas.

BACKGROUND & AIMS: Acinar-to-ductal metaplasia (ADM) serves as a precursor event in the development of pancreatic ductal adenocarcinoma (PDAC) upon constitutive environmental and genetical stress. While the role of ADM in PDAC progression has been established, the molecular mechanisms underlying human ADM remain elusive. We previously demonstrated the induction of ADM in human acinar cells through the transforming growth factor beta (TGFß) signaling pathway. We aim to investigate the interaction between TGFß and Hippo pathways in mediating ADM. METHODS: RNA-sequencing was conducted on sorted normal primary human acinar, ductal, and AD (acinar cells that have undergone ADM) cells. ATAC-seq analysis was utilized to reveal the chromatin accessibility in these three cell types. ChIP-Seq of YAP1, SMAD4, and H3K27ac was performed to identify the gene targets of YAP1 and SMAD4. The role of YAP1/TAZ in ADM-driven cell proliferation, as well as in oncogenic KRAS driven proliferation, was assessed using sphere formation assay. RESULTS: AD cells have a unique transcription profile, with upregulated genes in open chromatin states in acinar cells. YAP1 and SMAD4 co-occupy the loci of ADM-related genes, including PROM1, HES1, and MMP7, co-regulating biological functions such as cell adhesion, cell migration, and inflammation. Overexpression of YAP1/TAZ promoted acinar cell proliferation but still required the TGFß pathway. YAP1/TAZ were also crucial for TGFß-induced sphere formation and were necessary for KRAS-induced proliferation. CONCLUSIONS: Our study reveals the intricate transition between acinar and AD states in human pancreatic tissues. It unveils the complex interaction between the Hippo and TGF-ß pathways during ADM, highlighting the pivotal role of YAP1/TAZ and SMAD4 in PDAC initiation.

Improving few-shot relation extraction through semantics-guided learning.

Few-shot relation extraction (few-shot RE) aims to recognize relations between the entity pair in a given text by utilizing very few annotated instances. As a simple yet efficient approach, prototype network-based methods often directly incorporate relation information to enhance prototype representation or leverage contrastive learning to mitigate prediction confusion. Despite achieving good results, the above methods are still susceptible to false judgments of outlier samples and confusion of similar classes. To address these issues, we propose a novel Semantics-Guided Learning (SemGL) method that more effectively utilizes relation information to enhance both the representations of instances and prototypes for improving the performance of few-shot RE. First, SemGL employs the prompt encoder to encode various prompt templates of instances and relation information and obtains more accurate semantic representations of instances, instance prototypes, and concept prototypes via the prompt enhancement from large language models. Then, SemGL introduces a novel technique called relation graph learning, which leverages concept prototypes to cluster homogeneous instances together, emphasizing relation-specific features of concrete instances. Simultaneously, SemGL employs instance-level contrastive learning between instance prototypes and support instances to distinguish between intra-class instances and inter-class instances to promote shared features among intra-class instances. Additionally, prototype-level contrastive learning leverages concept prototypes to pull closer relation-specific features of the concept prototype and shared features of the instance prototype from the same relation. Finally, SemGL utilizes new relation prototypes that integrate interpretable features of concept prototypes and shared features of instance prototypes for prediction. Experimental results on two publicly available few-shot RE datasets demonstrate the effectiveness and efficiency of SemGL in introducing relation information, with particularly promising results for the domain adaptation challenge task.

How does new energy demonstration city pilot policy affect carbon dioxide emissions? Evidence from a quasi-natural experiment in China.

Energy transition policies are of great significance in adjusting the structure of energy supply and demand and coping with climate change. The new energy demonstration city pilot (NEDCP) policy, as an important pilot project in China's energy transition process, lacks a scientific assessment of the carbon reduction effect of the NEDCP policy and an in-depth explanation of the mechanism of the NEDCP. Based on panel data of 209 Chinese cities at the prefectural and higher levels from 2007 to 2019, this study takes the NEDCP policy as a quasi-natural experiment, using a difference-in-differences model combined with firm-level data to identify the impact of the NEDCP policy on urban carbon dioxide (CO2) emissions. This study analyzes the impact of heterogeneity of urban characteristics on the policy effect from multiple perspectives, and further investigates its mechanism. The conclusions are shown in the following aspects. (1) The implementation of the NEDCP policy decreases urban CO2 emissions significantly. Meanwhile, a series of robustness tests, including the instrumental variables method, propensity score matching difference-in-differences method, placebo test, exclusion of policy interference test, and machine learning method, support this conclusion. (2) The NEDCP policy achieves carbon reduction effects mainly through scale and structure effects. (3) The results of the heterogeneity test show that the NEDCP policy is more effective in cities with higher administrative levels, energy-demanding cities, cities in the southeast of Hu-line, and cities with a higher degree of nationalization. Therefore, the Chinese government should summarize the implementation experience of the NEDCP policy and expand its scope of application. The evaluation of the NEDCP policy in China has important reference value for the energy transition of other developing countries.

Comprehensive characterization of patient-derived xenograft models of pediatric leukemia.

Patient-derived xenografts (PDX) remain valuable models for understanding the biology and for developing novel therapeutics. To expand current PDX models of childhood leukemia, we have developed new PDX models from Hispanic patients, a subgroup with a poorer overall outcome. Of 117 primary leukemia samples obtained, successful engraftment and serial passage in mice were achieved in 82 samples (70%). Hispanic patient samples engrafted at a rate (51/73, 70%) that was similar to non-Hispanic patient samples (31/45, 70%). With a new algorithm to remove mouse contamination in multi-omics datasets including methylation data, we found PDX models faithfully reflected somatic mutations, copy-number alterations, RNA expression, gene fusions, whole-genome methylation patterns, and immunophenotypes found in primary tumor (PT) samples in the first 50 reported here. This cohort of characterized PDX childhood leukemias represents a valuable resource in that germline DNA sequencing has allowed the unambiguous determination of somatic mutations in both PT and PDX.

Experimental Study and Analytical Modeling on Properties of Freeze-Thaw Durability of Coal Gangue Pervious Concrete.

To assess the freeze-thaw (F-T) durability of coal gangue pervious concrete (CGPC) in different F-T cycle media (water, 3.5 wt% NaCl solution), experimental studies on 36 groups of cube specimens and 6 groups of prismatic specimens were carried out, with designed porosity, F-T cycling media, and F-T failure times as variables. The changes in apparent morphology, mass, compressive behavior, relative dynamic elastic modulus, and permeability coefficient have been analyzed in detail. To predict the compressive strength after F-T cycles, a GM (1,1) model based on the grey system theory was developed and further improved into a more accurate grey residual-Markov model. The results reported that the cement slurry and coal gangue aggregates (CGAs) on the specimen surface continued to fall off as F-T cycles increased, and, finally, the weak point was fractured. Meanwhile, the decrease in compressive behavior and relative dynamic elastic modulus was gentle in the early phase of F-T cycles, and they gradually became faster in the later stage, showing a parabolic downward trend. The permeability coefficient increased gradually. When F-T failure occurred, specimen mass dropped precipitously. The F-T failure of CGPC was more likely to occur in 3.5 wt% NaCl solution, and the F-T failure times of samples were 25 times earlier than that of water. This study lays the foundation for an engineering application and provides a basis for the large-scale utilization of CGPC.

Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer.

Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.

Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization.

Single cell spatial-omics data visualization plays a pivotal role in unraveling the intricate spatial organization and heterogeneity of cellular systems. Although various software tools and packages have been developed for this purpose, challenges persist in terms of user-friendly accessibility, data integration, and interactivity. In this study, we introduce Spatial-Live, a lightweight and versatile viewer tool designed for flexible single-cell spatial-omics data visualization. Spatial-Live overcomes the fundamental limitations of two-dimensional (2D) orthographic modes by employing a layer-stacking strategy, enabling efficient rendering of diverse data types with interactive features, and enhancing visualization with richer information in a unified three-dimensional (3D) space.

Effects of vortioxetine on hippocampal-related cognitive impairment induced in rats by androgen deprivation as a model of prostate cancer treatment.

Advances in prostate cancer treatment have significantly improved survival, but quality of life for survivors remains an under-studied area of research. Androgen deprivation therapy (ADT) is a foundational treatment for advanced prostate cancer and is used as an adjuvant for prolonged periods in many high-risk, localized tumors. More than half of patients treated with ADT experience debilitating cognitive impairments in domains such as spatial learning and working memory. In this study, we investigated the effects of androgen deprivation on hippocampal-mediated cognition in rats. Vortioxetine, a multimodal antidepressant, has been shown to improve cognition in depressed patients. Thus, we also tested the potential efficacy of vortioxetine in restoring impaired cognition after ADT. We further investigated mechanisms that might contribute to these effects, measuring changes in the circuitry and gene expression within the dorsal hippocampus. ADT via surgical castration induced impairments in visuospatial cognition on the novel object location test and attenuated afferent-evoked local field potentials recorded in the CA1 region of the dorsal hippocampus. Chronic dietary administration of vortioxetine effectively reversed these deficits. Castration significantly altered gene expression in the hippocampus, whereas vortioxetine had little effect. Pathway analysis revealed that androgen depletion altered pathways related to synaptic plasticity. These results suggest that the hippocampus may be vulnerable to ADT, contributing to cognitive impairment in prostate cancer patients. Further, vortioxetine may be a candidate to improve cognition in patients who experience cognitive decline after androgen deprivation therapy for prostate cancer and may do so by restoring molecular and circuit-level plasticity-related mechanisms compromised by ADT.

mTOR inhibition abrogates human mammary stem cells and early breast cancer progression markers.

BACKGROUND: Mammary physiology is distinguished in containing adult stem/progenitor cells that are actively amending the breast tissue throughout the reproductive lifespan of women. Despite their importance in both mammary gland development, physiological maintenance, and reproduction, the exact role of mammary stem/progenitor cells in mammary tumorigenesis has not been fully elucidated in humans or animal models. The implications of modulating adult stem/progenitor cells in women could lead to a better understanding of not only their function, but also toward possible breast cancer prevention led us to evaluate the efficacy of rapamycin in reducing mammary stem/progenitor cell activity and malignant progression markers. METHODS: We analyzed a large number of human breast tissues for their basal and luminal cell composition with flow cytometry and their stem and progenitor cell function with sphere formation assay with respect to age and menopausal status in connection with a clinical study (NCT02642094) involving a low-dose (2 mg/day) and short-term (5-7 days) treatment of the mTOR inhibitor sirolimus. The expression of biomarkers in biopsies and surgical breast samples were measured with quantitative analysis of immunohistochemistry. RESULTS: Sirolimus treatment significantly abrogated mammary stem cell activity, particularly in postmenopausal patients. It did not affect the frequency of luminal progenitors but decreased their self-renewal capacity. While sirolimus had no effect on basal cell population, it decreased luminal cell population, particularly in postmenopausal patients. It also significantly diminished prognostic biomarkers associated with breast cancer progression from ductal carcinoma in situ to invasive breast cancer including p16INK4A, COX-2, and Ki67, as well as markers of the senescence-associated secretary phenotype, thereby possibly functioning in preventing early breast cancer progression. CONCLUSION: Overall, these findings indicate a link from mTOR signaling to mammary stem and progenitor cell activity and cancer progression. Trial registration This study involves a clinical trial registered under the ClinicalTrials.gov identifier NCT02642094 registered December 30, 2015.