A prostate cancer gastrointestinal transcriptional phenotype may be associated with diminished response to AR-targeted therapy.

Background: Prostate cancer is a heterogenous disease, but once it becomes metastatic it eventually becomes treatment resistant. One mechanism of resistance to AR-targeting therapy is lineage plasticity, where the tumor undergoes a transformation to an AR-indifferent phenotype, most studied in the context of neuroendocrine prostate cancer (NEPC). However, activation of additional de- or trans-differentiation programs, including a gastrointestinal (GI) gene expression program, has been suggested as an alternative method of resistance. In this study, we explored the previously identified GI prostate cancer phenotype (PCa-GI) in a large cohort of metastatic castration-resistant prostate cancer (mCRPC) patient biopsy samples. Methods: We analyzed a dataset of 634 mCRPC samples with batch effect corrected gene expression data from the West Coast Dream Team (WCDT), the East Coast Dream Team (ECDT), the Fred Hutchinson Cancer Research Center (FHCRC) and the Weill Cornell Medical center (WCM). Survival data was available from the WCDT and ECDT cohorts. We calculated a gene expression GI score using the sum of z-scores of genes from a published set of PCa-GI-defining genes (N=38). Survival analysis was performed using the Kaplan-Meier method and Cox proportional hazards regression with endpoint overall survival from time of biopsy to death of any cause. Results: We found that the PCa-GI score had a bimodal distribution, identifying a distinct set of tumors with an activated GI expression pattern. Approximately 35% of samples were classified as PCa-GI high, which was concordant with prior reports. Liver metastases had the highest median score but after excluding liver samples, 29% of the remaining samples were still classified as PCa-GI high, suggesting a distinct phenotype not exclusive to liver metastases. No correlation was observed between GI score and proliferation, AR signaling, or NEPC scores. Furthermore, the PCa-GI score was not associated with genomic alterations in AR, FOXA1, RB1, TP53 or PTEN. However, tumors with MYC amplifications showed significantly higher GI scores (p=0.0001). Patients with PCa-GI tumors had a shorter survival (HR=1.5 [1.1-2.1], p=0.02), but this result was not significant after adjusting for the liver as metastatic site (HR=1.2 [0.82-1.7], p=0.35). Patients with PCa-GI low samples had a better outcome after androgen receptor signaling inhibitors (ASI, abiraterone or enzalutamide) than other therapies (HR=0.37 [0.22-0.61], p=0.0001) while the benefit of ASI was smaller and non-significant for PCa-GI high samples (HR=0.55 [0.29-1.1], p=0.07). A differential pathway analysis identified FOXA2 signaling to be upregulated PCa-GI high tumors (FDR = 3.7 × 10-13). Conclusions: The PCa-GI phenotype is prevalent in clinical mCRPC samples and may represent a distinct biological entity. PCa-GI tumors may respond less to ASI and could offer a strategy to study novel therapeutic targets.

Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer.

Targeting HPV16 E6 has emerged as an effective drug target for the treatment/management of cervical cancer. We utilized pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion (ADME) prediction, and molecular dynamics simulation approach for identifying potential inhibitors of HPV16 E6. Initially, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27) via the PHASE module implanted in the Schrödinger suite. We constructed four-point pharmacophore features viz., three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore feature further employed as a query for virtual screening against the ASINEX database via Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We then applied the high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits and a negative molecule were identified using docking in XP mode. The four lead compounds and a negative molecule were then further subjected to ADME profile prediction by engaging Qikprop module. The ADME properties of the four lead molecules indicate good pharmacokinetic (PK) properties rather than the negative molecule. The binding stability of the HPV16 E6-hit complexes were investigated at a different time scale (100 ns) by using the desmond package and the results were examined using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) and it revealed the stability of the protein-ligand complex throughout the simulation. Key residues, CYS 51 and GLN 107, also play a crucial role in enhancing the stability of the protein-ligand complex during the simulation. Furthermore, the binding free energy of the HPV16 E6-leads complexes was analyzed by prime which revealed that the ΔGbind coulomb and ΔGbind vdW interactions are crucially contributes to the binding affinity. In order to validate the computational findings, the efficacy of benzoimidazole and benzotriazole were ascertained for regulating ME180 cervical cancer cell survival, migration and ability to release MMP-2.

Inferring spatial transcriptomics markers from whole slide images to characterize metastasis-related spatial heterogeneity of colorectal tumors: A pilot study.

Over 150 000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually over 50 000 individuals will die from CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. Tumor metastasis is the primary factor related to the risk of recurrence and mortality. Yet, screening for nodal and distant metastasis is costly, and invasive and incomplete resection may hamper adequate assessment. Signatures of the tumor-immune microenvironment (TIME) at the primary site can provide valuable insights into the aggressiveness of the tumor and the effectiveness of various treatment options. Spatially resolved transcriptomics technologies offer an unprecedented characterization of TIME through high multiplexing, yet their scope is constrained by cost. Meanwhile, it has long been suspected that histological, cytological, and macroarchitectural tissue characteristics correlate well with molecular information (e.g., gene expression). Thus, a method for predicting transcriptomics data through inference of RNA patterns from whole slide images (WSI) is a key step in studying metastasis at scale. In this work, we collected tissue from 4 stage-III (pT3) matched colorectal cancer patients for spatial transcriptomics profiling. The Visium spatial transcriptomics (ST) assay was used to measure transcript abundance for 17 943 genes at up to 5000 55-micron (i.e., 1-10 cells) spots per patient sampled in a honeycomb pattern, co-registered with hematoxylin and eosin (H&E) stained WSI. The Visium ST assay can measure expression at these spots through tissue permeabilization of mRNAs, which are captured through spatially (i.e., x-y positional coordinates) barcoded, gene specific oligo probes. WSI subimages were extracted around each co-registered Visium spot and were used to predict the expression at these spots using machine learning models. We prototyped and compared several convolutional, transformer, and graph convolutional neural networks to predict spatial RNA patterns at the Visium spots under the hypothesis that the transformer- and graph-based approaches better capture relevant spatial tissue architecture. We further analyzed the model's ability to recapitulate spatial autocorrelation statistics using SPARK and SpatialDE. Overall, the results indicate that the transformer- and graph-based approaches were unable to outperform the convolutional neural network architecture, though they exhibited optimal performance for relevant disease-associated genes. Initial findings suggest that different neural networks that operate on different scales are relevant for capturing distinct disease pathways (e.g., epithelial to mesenchymal transition). We add further evidence that deep learning models can accurately predict gene expression in whole slide images and comment on understudied factors which may increase its external applicability (e.g., tissue context). Our preliminary work will motivate further investigation of inference for molecular patterns from whole slide images as metastasis predictors and in other applications.

Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity.

Background: Spatial transcriptomics involves studying the spatial organization of gene expression within tissues, offering insights into the molecular diversity of tumors. While spatial gene expression is commonly amalgamated from 1-10 cells across 50-micron spots, recent methods have demonstrated the capability to disaggregate this information at subspot resolution by leveraging both expression and histological patterns. However, elucidating such information from histology alone presents a significant challenge but if solved can better permit spatial molecular analysis at cellular resolution for instances where Visium data is not available, reducing study costs. This study explores integrating single-cell histological and transcriptomic data to infer spatial mRNA expression patterns in whole slide images collected from a cohort of stage pT3 colorectal cancer patients. A cell graph neural network algorithm was developed to align histological information extracted from detected cells with single cell RNA patterns through optimal transport methods, facilitating the analysis of cellular groupings and gene relationships. This approach leveraged spot-level expression as an intermediary to co-map histological and transcriptomic information at the single-cell level. Results: Our study demonstrated that single-cell transcriptional heterogeneity within a spot could be predicted from histological markers extracted from cells detected within a spot. Furthermore, our model exhibited proficiency in delineating overarching gene expression patterns across whole-slide images. This approach compared favorably to traditional patch-based computer vision methods as well as other methods which did not incorporate single cell expression during the model fitting procedures. Topological nuances of single-cell expression within a Visium spot were preserved using the developed methodology. Conclusion: This innovative approach augments the resolution of spatial molecular assays utilizing histology as a sole input through synergistic co-mapping of histological and transcriptomic datasets at the single-cell level, anchored by spatial transcriptomics. While initial results are promising, they warrant rigorous validation. This includes collaborating with pathologists for precise spatial identification of distinct cell types and utilizing sophisticated assays, such as Xenium, to attain deeper subcellular insights.

Predominant Founder Effect among Recurrent Pathogenic Variants for an X-Linked Disorder.

For disorders with X-linked inheritance, variants may be transmitted through multiple generations of carrier females before an affected male is ascertained. Pathogenic RS1 variants exclusively cause X-linked retinoschisis (XLRS). While RS1 is constrained to variation, recurrent variants are frequently observed in unrelated probands. Here, we investigate recurrent pathogenic variants to determine the relative burden of mutational hotspot and founder allele events to this phenomenon. A cohort RS1 variant analysis and standardized classification, including variant enrichment in the XLRS cohort and in RS1 functional domains, were performed on 332 unrelated XLRS probands. A total of 108 unique RS1 variants were identified. A subset of 19 recurrently observed RS1 variants were evaluated in 190 probands by a haplotype analysis, using microsatellite and single nucleotide polymorphisms. Fourteen variants had at least two probands with common variant-specific haplotypes over ~1.95 centimorgans (cM) flanking RS1. Overall, 99/190 of reportedly unrelated probands had 25 distinct shared haplotypes. Examination of this XLRS cohort for common RS1 haplotypes indicates that the founder effect plays a significant role in this disorder, including variants in mutational hotspots. This improves the accuracy of clinical variant classification and may be generalizable to other X-linked disorders.

Intrinsic Molecular Subtypes of Metastatic Castration-Resistant Prostate Cancer.

PURPOSE: Although numerous biology-driven subtypes have been described previously in metastatic castration-resistant prostate cancer (mCRPC), unsupervised molecular subtyping based on gene expression has been less studied, especially using large cohorts. Thus, we sought to identify the intrinsic molecular subtypes of mCRPC and assess molecular and clinical correlates in the largest combined cohort of mCRPC samples with gene expression data available to date. EXPERIMENTAL DESIGN: We combined and batch-effect corrected gene expression data from four mCRPC cohorts from the Fred Hutchinson Cancer Research Center (N = 157), a small-cell neuroendocrine (NE) prostate cancer (SCNC)-enriched cohort from Weill Cornell Medicine (N = 49), and cohorts from the Stand Up 2 Cancer/Prostate Cancer Foundation East Coast Dream Team (N = 266) and the West Coast Dream Team (N = 162). RESULTS: Hierarchical clustering of RNA-sequencing data from these 634 mCRPC samples identified two distinct adenocarcinoma subtypes, one of which (adeno-immune) was characterized by higher gene expression of immune pathways, higher CIBERSORTx immune scores, diminished ASI benefit, and non-lymph node metastasis tropism compared with an adeno-classic subtype. We also identified two distinct subtypes with enrichment for an NE phenotype, including an NE-liver subgroup characterized by liver metastasis tropism, PTEN loss, and APC and SPOP mutations compared with an NE-classic subgroup. CONCLUSIONS: Our results emphasize the heterogeneity of mCRPC beyond currently accepted molecular phenotypes, and suggest that future studies should consider incorporating transcriptome-wide profiling to better understand how these differences impact treatment responses and outcomes.

Zeranol down-regulates p53 expression in primary cultured human breast cancer epithelial cells through epigenetic modification.

Epidemiological studies have suggested that there are many risk factors associated with breast cancer. Silencing tumor suppressor genes through epigenetic alterations play critical roles in breast cancer initiation, promotion and progression. As a growth promoter, Zeranol (Z) has been approved by the FDA and is widely used to enhance the growth of beef cattle in the United States. However, the safety of Z use as a growth promoter is still under debate. In order to provide more evidence to clarify this critical health issue, the current study investigated the effect of Z on the proliferation of primary cultured human normal and cancerous breast epithelial cells (PCHNBECs and PCHBCECs, respectively) isolated from the same patient using MTS assay, RT-PCR and Western blot analysis. We also conducted an investigation regarding the mechanisms that might be involved. Our results show that Z is more potent to stimulate PCHBCEC growth than PCHNBEC growth. The stimulatory effects of Z on PCHBCECs and PCHBCECs may be mediated by its down-regulating expression of the tumor suppressor gene p53 at the mRNA and protein levels. Further investigation showed that the expression of DNA methylatransferase 1 mRNA and protein levels is up-regulated by treatment with Z in PCHBCECs as compared to PCHNBECs, which suggests a role of Z in epigenetic modification involved in the regulation of p53 gene expression in PCHBCECs. Our experimental results imply the potentially adverse health effect of Z in breast cancer development. Further study is continuing in our laboratory.

Germline polymorphisms associated with impaired survival outcomes and somatic tumor alterations in advanced prostate cancer.

INTRODUCTION: Germline variants in androgen metabolism genes may influence clinical response to androgen deprivation therapy (ADT) in advanced prostate cancer. We sought to investigate the prognostic significance of germline variants in androgen metabolism genes with respect to overall survival (OS) after ADT, and to associate germline variants with tumor genomic features. METHODS: Germline and somatic whole-genome sequencing (WGS) data were evaluated in a cohort of 101 men with metastatic castration-resistant prostate cancer (mCRPC). Survival analyses were performed to identify polymorphisms associated with impaired OS after primary ADT. Germline variants found to be prognostic of OS were associated with tumor somatic DNA-sequence alterations based on WGS performed on paired metastasis biopsies from the same 101 patients. Gene set enrichment analysis was performed based on tumor RNA-sequencing data to identify genomic pathways differentially expressed in patients with germline variants. RESULTS: A comprehensive literature review identified 17 candidate polymorphisms in nine androgen metabolism genes that have been previously shown to have an association with response to ADT in prostate cancer. Of these, the variant rs1856888 allele located 13 kb upstream of HSD3B1 was found to be significantly associated with impaired OS (P = 0.029). Variant rs1856888 was commonly co-inherited with the well-characterized HSD3B1(1245A>C) polymorphism, and there was a trend toward shorter median OS in patients with HSD3B1(1245A>C) compared with homozygous wild-type patients (P = 0.052). While HSD3B1 germline variants were not associated with common somatic tumor DNA alterations, they were associated with increased tumor expression of cell proliferation and cell cycle genes. CONCLUSIONS: This study presents a comprehensive assessment of germline variants in androgen metabolism genes and highlights HSD3B1 polymorphisms as prognostic of OS after ADT and associated with an aggressive gene expression tumor profile in mCRPC.

VRC34-Antibody Lineage Development Reveals How a Required Rare Mutation Shapes the Maturation of a Broad HIV-Neutralizing Lineage.

Rare mutations have been proposed to restrict the development of broadly neutralizing antibodies against HIV-1, but this has not been explicitly demonstrated. We hypothesized that such rare mutations might be identified by comparing broadly neutralizing and non-broadly neutralizing branches of an antibody-developmental tree. Because sequences of antibodies isolated from the fusion peptide (FP)-targeting VRC34-antibody lineage suggested it might be suitable for such rare mutation analysis, we carried out next-generation sequencing (NGS) on B cell transcripts from donor N123, the source of the VRC34 lineage, and functionally and structurally characterized inferred intermediates along broadly neutralizing and poorly neutralizing developmental branches. The broadly neutralizing VRC34.01 branch required the rare heavy-chain mutation Y33P to bind FP, whereas the early bifurcated VRC34.05 branch did not require this rare mutation and evolved less breadth. Our results demonstrate how a required rare mutation can restrict development and shape the maturation of a broad HIV-1-neutralizing antibody lineage.

Venous Thromboembolism Prophylaxis: Inadequate and Overprophylaxis When Comparing Perceived Versus Calculated Risk.

Guidelines for venous thromboembolism (VTE) prophylaxis recommend appropriate risk stratification using risk estimation models as high risk or low risk followed by initiation of chemical or mechanical prophylaxis, respectively. We explored adherence to guidelines on the basis of the documentation of VTE prophylaxis. A retrospective medical record review of 437 consecutive adult patients (≥18 years) admitted to general medical wards under medicine service between January 1, 2015, and March 1, 2015, was performed. The primary outcome was appropriateness of risk stratification using the Padua Prediction Score. Secondary outcomes were appropriateness of type of prophylaxis (chemical vs mechanical) and cost-benefit analysis. We observed appropriate stratification based on the documented risk (compared with the calculated risk) in 54.9% of the patients (40.8% with low risk vs 72.1% with high risk; P<.001). Overall, 182 of 240 low-risk patients received unnecessary chemical prophylaxis, whereas 23 of 197 high-risk patients without contraindications for chemical prophylaxis received mechanical or no prophylaxis. No clinical VTE events were noted in the patients inappropriately assigned to mechanical or no prophylaxis. Also, 67.3% of patients with both low documented and low calculated risk and 74.5% of patients with low documented and high calculated risk received chemical prophylaxis, consistent with a tendency toward overtreatment. A total of 4068 annualized patient-days ($77,652/y) of inappropriate chemical prophylaxis were administered. In conclusion, estimation of the risk of VTE based on clinical impression was not congruent with the risk calculated using risk prediction models and was associated with a tendency toward overtreatment. These data support the inclusion of VTE risk calculators in electronic health record systems.

Reliability and validity of conversion formulas between comprehensive osteopathic medical licensing examination of the United States level 1 and United States medical licensing examination step 1.

BACKGROUND: The Comprehensive Osteopathic Medical Licensing Examination of the United States (COMLEX-USA) Level 1 and United States Medical Licensing Examination (USMLE) Step 1 scores are important factors in the selection process of medical students into US residency programs. OBJECTIVES: The goals of this study were to investigate the correlation between the COMLEX-USA Level 1 and the USMLE Step 1 and to assess the accuracy of the existing formulas in predicting USMLE scores from COMLEX-USA scores. METHODS: A retrospective study of 1016 paired COMLEX-USA Level 1 and USMLE Step 1 scores was conducted. Formulas by Sarko et al and by Slocum and Louder were used to estimate USMLE Step 1 scores from COMLEX-USA Level 1 scores, and a paired t test between calculated USMLE Step 1 scores and actual USMLE Step 1 scores was performed. RESULTS: During 2006-2012, 1016 of 1440 students (71%) took both the USMLE Step 1 and the COMLEX-USA Level 1 tests in the College of Osteopathic Medicine of the Pacific. The USMLE Step 1 scores were higher than those predicted by Slocum and Louder and by Sarko et al by an average of 14.16 ± 11.69 (P < .001) and 7.80 ± 12.48 (P < .001), respectively. A Pearson coefficient of 0.83 was observed. Regression analysis yielded the following formula: USMLE Step 1  =  0.2392 × COMLEX-USA Level 1 + 82.563 (R (2)  =  0.69577). CONCLUSIONS: The USMLE Step 1 scores, on average, were higher than those predicted by the formulas derived by Slocum and Louder and by Sarko et al. Residency program directors should use caution when using formulas to derive USMLE Step 1 scores from COMLEX-USA Level 1 scores.

Serum derived from zeranol-implanted ACI rats promotes the growth of human breast cancer cells in vitro.

BACKGROUND: Zeranol (Z) is a non-steroidal anabolic growth promoter with potent estrogenic activity that is widely used as a growth promoter in the US beef industry. Consumption of beef derived from zeranol-implanted cattle may be a risk factor for breast cancer. MATERIALS AND METHODS: The effect of serum on the proliferation of human breast cancer MCF-7 cell line and primary cultured human breast epithelial cells (PCHBECs) was investigated. ACI rats were implanted with 12 mg zeranol pellet and the serum was harvested at day 110 after implantation. The effect of zeranol-serum on mRNA expression of cell cycle regulating gene (cyclin D1) and tumor suppressor genes (p53, and p21) was evaluated using real-time RT-PCR. RESULTS: The serum derived from ACI rats 110 days post-zeranol implantation significantly promoted the proliferation of MCF-7 cells and primary cultured human breast epithelial cells compared to control serum. Zeranol-serum up-regulated cyclin D1 and down-regulated p53 and p21 expression in PCHBECs compared with control serum. CONCLUSION: Bio-active zeranol metabolites contained in meat produced from cattle after zeranol implantation may be a risk factor for breast cancer.

Zeranol may increase the risk of leptin-induced neoplasia in human breast.

Breast cancer and obesity are serious health problems and their relationship has been studied for many years. Leptin is mainly secreted by adipocytes and plays a key role in breast cancer development. Leptin expression is up-regulated in obese individuals and promotes breast cancer cell growth. On the other hand, exposure to environmental estrogens has been found to be directly related to breast cancer. Zeranol (Z) is a non-steroidal anabolic growth promoter used in the beef industry in the US. This study focused on the evaluation of Z and Z-containing sera (ZS) and its adverse health risk to human consumption of Z-containing meat produced from Z-implanted beef cattle. We hypothesized that Z increases the risk of breast neoplasia in women, particularly in obese women. A cell proliferation assay, ELISA analysis, RT-PCR and Western blot analysis were conducted. Our study demonstrated that Z and ZS collected from Z-implanted heifers stimulated the proliferation of primary cultured human normal breast epithelial cells (HNBECs) by up-regulating cyclin D1 expression. Leptin increased the sensitivity of HNBECs to Z, and Z increased the ability of HNBECs to secrete leptin. These results suggest an interaction between leptin and Z in HNBECs. Furthermore, Z may play a role in leptin-induced breast neoplasia.

In vitro transformation of MCF-10A cells by sera harvested from heifers two months post-Zeranol implantation.

Among many risk factors of breast cancer, estrogens and non-estrogenic endocrine disruptors are considered to play critical roles in human breast carcinogenesis. Zeranol (Z) is a non-steroidal agent with potent estrogenic activity and has been widely used as an FDA approved beef growth promoter in the US. Recently, concerns have been raised about the potential adverse health risk by consumption of products containing biologically active Z and its metabolites. By utilizing cell proliferation assay, soft agar assay, quantitative real-time PCR and Western blotting analysis, we examined the potentially tumorigenic activity of bio-active Z containing sera harvested from heifers two months post Z-implantation and the underlying mechanisms. Our results showed that the growth of MCF-10A exposed to 0.2, 1 and 5% Z-containing serum (ZS) treatment for 3 weeks was 1.3, 1.75 and 1.8-fold faster compared to that of the control sera. After further investigation, we found that ZS increased cyclin D1 and decreased p53 expression at the mRNA and protein levels in MCF-10A compared to the controls. More importantly, treatment of 1% Z-containing sera for 21 days stimulated MCF-10A cells anchorage-independent colony formation in soft agar which illustrates its capability of inducing human normal breast epithelial cell neoplastic transformation. Our experimental results suggest that long-term exposure of low levels of Z and its metabolites contained in beef products might be a potential risk factor in human breast cancer initiation and development.

PIM kinase inhibitors downregulate STAT3(Tyr705) phosphorylation.

Using a cell-based high-throughput screen designed to detect small chemical compounds that inhibit cell growth and survival, we identified three structurally related compounds, 21A8, 21H7, and 65D4, with differential activity on cancer versus normal cells. Introduction of structural modifications yielded compound M-110, which inhibits the proliferation of prostate cancer cell lines with IC(50)s of 0.6 to 0.9 µmol/L, with no activity on normal human peripheral blood mononuclear cells up to 40 µmol/L. Screening of 261 recombinant kinases and subsequent analysis revealed that M-110 is a selective inhibitor of the PIM kinase family, with preference for PIM-3. The prostate cancer cell line DU-145 and the pancreatic cancer cell line MiaPaCa2 constitutively express activated STAT3 (pSTAT3(Tyr705)). Treatment of DU-145 cells with M-110 or with a structurally unrelated PIM inhibitor, SGI-1776, significantly reduces pSTAT3(Tyr705) expression without affecting the expression of STAT3. Furthermore, treatment of DU-145 cells with M-110 attenuates the interleukin-6-induced increase in pSTAT3(Tyr705). To determine which of the three PIM kinases is most likely to inhibit expression of pSTAT3(Tyr705), we used PIM-1-, PIM-2-, or PIM-3-specific siRNA and showed that knockdown of PIM-3, but not of PIM-1 or PIM-2, in DU-145 cells results in a significant downregulation of pSTAT3(Tyr705). The phosphorylation of STAT5 on Tyr694 in 22Rv1 cells is not affected by M-110 or SGI-1776, suggesting specificity for pSTAT3(Tyr705). These results identify a novel role for PIM-3 kinase as a positive regulator of STAT3 signaling and suggest that PIM-3 inhibitors cause growth inhibition of cancer cells by downregulating the expression of pSTAT3(Tyr705).

Zeranol enhances leptin-induced proliferation in primary cultured human breast cancer epithelial cells.

Breast cancer is the leading type of cancer in women in the United States. One of the known risk factors of breast cancer is obesity. Leptin is a product of the obese (ob) gene and plays an important role in breast cancer development. Its expression is up-regulated in obesity and it promotes breast cancer cell growth. Exposure to environmental estrogenic disruptors has been found to be directly related to the increase in the incidence of breast cancer. Zeranol (Z) is a non-steroidal anabolic growth promoter with potent estrogenic activity that is widely used in the US beef industry. The objective of this study was to determine the mechanisms of Z- and leptin-induced proliferation of primary cultured human breast cancer epithelial cells (HBCECs). A cell proliferation assay was used to determine the extent to which Z is capable of enhancing the mitogenic activity of leptin in HBCECs. RT-PCR was used to explore the possible mechanisms by quantifying the transcription of cyclin D1 and ObR genes. Our results demonstrated that when the HBCECs were pre-treated with 3 nM leptin for 24 h, the sensitivity to Z exposure greatly enhanced the mitogenic action of leptin. The experimental data observed show that there is interaction between leptin and Z in HBCEC growth.

Aromatase expression in leptin-pretreated human breast pre-adipocytes is enhanced by zeranol and suppressed by (-)-gossypol.

BACKGROUND: Obesity is associated with an increased risk of estrogen-dependent breast cancer. Recently, concerns have been raised regarding the role of zeranol (Z), a non-steroidal anabolic growth promoter with potent estrogenic activity widely used in the U.S.A. beef industry, as a possible contributor to an increased incidence of human breast cancer. This study hypothesized that obese individuals may be at greater risk of developing zeranol-induced breast cancer. MATERIALS AND METHODS: The aromatase mRNA expression level of three cell types isolated from adipose tissues were assayed by RT-PCR, and the cell proliferation of primary cultured human normal breast pre-adipocytes (HNBPADs) was investigated using the CellTiter96® non-radioactive method. The effects of Z and gossypol on aromatase expression of leptin-pretreated HNBPADs were evaluated by RT-PCR. RESULTS: HNBPADs expressed higher aromatase than primary cultured human breast epithelial cells and stromal cells. Z enhanced the mitogenic activity of leptin and increased aromatase expression in HNBPADs. Moreover, (-)-gossypol counteracted Z- and leptin-induced cell proliferation and aromatase expression. CONCLUSION: These results suggested that bioactive Z metabolites contained in meat produced from Z-implanted beef cattle may increase estrogen biosynthesis in obese individuals by increasing aromatase expression and estrogen production, which will promote cell sensitivity and increase breast cancer cell growth.

Leptin and zeranol up-regulate cyclin D1 expression in primary cultured normal human breast pre-adipocytes.

Adipocytes account for more than 90% of human breast volume and secrete adipocytokines, which play a role in breast cancer development. Among the adipocytokines is leptin, which is secreted mainly by adipocytes and plays a key role in breast cancer development. Leptin expression is up-regulated in both obese and breast cancer patients, and promotes breast cancer cell growth. Exposure to environmental estrogens has also been found to be directly related to the development of breast cancer. Zeranol (Z) is a non-steroidal anabolic growth promoter with estrogenic activity that is widely used in the US beef industry due to its commercial benefits. Gossypol is a natural compound extracted from cottonseed that inhibits breast cancer growth, and is potentially a chemopreventive food component. This study focused on Z and bio-active Z-containing sera (ZS) collected from Z-implanted beef, and evaluated their adverse health risk to humans. We hypothesized that Z increases the risk of breast cancer in obese women. A cell proliferation assay, ELISA analysis, RT-PCR and Western blotting were performed to investigate the interaction of leptin, Z and (-)-gossypol in primary cultured normal human breast pre-adipocytes. The results indicated that Z and ZS stimulated the growth of pre-adipocytes isolated from normal human breast tissues by up-regulating cyclin D1 expression, while (-)-gossypol reversed this effect.

Serum harvested from heifers one month post-zeranol implantation stimulates MCF-7 breast cancer cell growth.

Breast cancer is a serious disease in the US. Numerous risk factors have been linked to this disease. The safety of using growth promoters, such as zeranol, remains under debate due to the lack of sufficient in vitro and in vivo evidence. Using CellTiter 96(™) Aqueous Non-Radioactive Cell Proliferation assay, real-time PCR and Western blot analysis, we evaluated the effects of sera harvested from experimental and control heifers before and after one month of zeranol implantation on the growth of human breast cancer cell line MCF-7 as well as the involved mechanisms. We found that sera harvested from the heifers following one month of zeranol implantation were more mitogenically potent in stimulating the proliferation of MCF-7 cells when compared to sera harvested from the same heifers before zeranol implantation and the control heifers. Further investigation found that dextran-coated charcoal suppressed the stimulating effect of the sera on MCF-7 cell growth. The mechanisms involved in the MCF-7 cell proliferation stimulated by zeranol-containing sera may include up-regulation of cyclin D1 and down-regulation of p53 and p21 expression at the mRNA and protein levels in the cells. The results suggest that the consumption of beef products containing biologically active residues of zeranol or its metabolites is a risk linked to breast cancer development. Further investigation is required in order to clarify this critical issue.