Relationships of protein biomarkers of the urokinase plasminogen activator system with expression of their cognate genes in primary breast carcinomas.

BACKGROUND: uPA, its receptor uPAR, and inhibitors PAI-1 and PAI-2 play key roles in membrane remodeling/invasion and in predicting response to chemotherapy. We identified novel relationships of these biomarkers with ER/PR that indicate clinical utility for assessing breast carcinoma outcomes. METHODS: Retrospective studies were performed with de-identified results of (a) uPA, uPAR, and PAI-1; (b) estrogen (ER) and progestin receptor (PR); and (c) clinical outcomes. Relative expression of 22 000 genes from microarray of RNA from LCM-procured breast cancer cells was used with R Studio version 3.4.1. RESULTS: Primary ER/PR status was related to uPA, uPAR, or PAI-1 levels. ER- or PR- cancers expressed elevated uPA, uPAR, and PAI2 mRNA compared to ER+ or PR+ cells. Inverse relationships between ER/PR protein and expression of uPA, uPAR, and PAI-2 were observed, whereas HER2 status was unrelated. qPCR analyses showed RERG and NQO-1 expressions were elevated in uPA- lesions, while CD34 and EDG-1 were elevated in uPAR- cancers. ERBB4 was overexpressed in PAI-1+ carcinomas. Cox regression analyses revealed relationships of ER/PR status and uPA system members with regard to clinical outcomes of breast cancer. CONCLUSIONS: uPA, uPAR, PAI1, or PAI2 expression was increased in either ER- or PR- cancers similar to that of protein content in ER-/PR- carcinomas, suggesting sex hormones regulate the uPA system in breast cancer. Results revealed protein content of uPA system members was related to ER/PR status of primary lesions. Use of LCM-procured carcinoma cells uncovered relationships between expression of known cancer-associated genes and protein content of uPA system members. Collectively, results indicate evaluation of ER and PR protein of primary breast cancers combined with analyses of uPA, uPAR, and PAI-1 protein content improves assessment of clinical outcomes.

Clinical outcomes linked to expression of gene subsets for protein hormones and their cognate receptors from LCM-procured breast carcinoma cells.

PURPOSE: Certain peptide hormones and/or their cognate receptors influencing normal cellular pathways also have been detected in breast cancers. The hypothesis is that gene subsets of these regulatory molecules predict risk of breast carcinoma recurrence in patients with primary disease. METHODS: Gene expression levels of 61 hormones and 81 receptors were determined by microarray with LCM-procured carcinoma cells of 247 de-identified biopsies. Univariable and multivariable Cox regressions were determined using expression levels of each hormone/receptor gene, individually or as a pair. RESULTS: Molecular signatures for ER+/PR+, ER-/PR-, and ER- carcinoma cells deciphered by LASSO were externally validated at HRs (CI) of 2.8 (1.84-4.4), 1.53 (1.01-2.3), and 1.72 (1.15-2.56), respectively. Using LCM-procured breast carcinoma cells, a 16-gene molecular signature was derived for ER+/PR+ biopsies, whereas a 10-gene signature was deciphered for ER-/PR- cancers. Four genes, POMC, CALCR, AVPR1A, and GH1, of this 10-gene signature were identified in a 6-gene molecular signature for ER- specimens. CONCLUSIONS: Applying these signatures, Kaplan-Meier plots definitively identified a cohort of patients with either ER-/PR- or ER- carcinomas that exhibited low risk of recurrence. In contrast, the ER+/PR+ signature identified a cohort of patients with high risk of breast cancer recurrence. Each of the three molecular signatures predicted clinical outcomes of breast cancer patients with greater accuracy than observed with either single-gene analysis or by ER/PR protein content alone. Collectively, our results suggest that gene expression profiles of breast carcinomas with suspected poor prognosis (ER-/PR-) have identified a subset of patients with decreased risk of recurrence.

Interaction between smoking history and gene expression levels impacts survival of breast cancer patients.

In contrast to studies focused on cigarette smoking and risk of breast cancer occurrence, this study explored the influence of smoking on breast cancer recurrence and progression. The goal was to evaluate the interaction between smoking history and gene expression levels on recurrence and overall survival of breast cancer patients. Multivariable Cox proportional hazards models were fitted for 48 cigarette smokers, 50 non-smokers, and the total population separately to determine which gene expressions and gene expression/cigarette usage interaction terms were significant in predicting overall and disease-free survival in breast cancer patients. Using methods similar to Andres et al. (BMC Cancer 13:326, 2013a; Horm Cancer 4:208-221, 2013b), multivariable analyses revealed CENPN, CETN1, CYP1A1, IRF2, LECT2, and NCOA1 to be important predictors for both breast carcinoma recurrence and mortality among smokers. Additionally, COMT was important for recurrence, and NAT1 and RIPK1 were important for mortality. In contrast, only IRF2, CETN1, and CYP1A1 were significant for disease recurrence and mortality among non-smokers, with NAT2 additionally significant for survival. Analysis of interaction between smoking status and gene expression values using the combined samples revealed significant interactions between smoking status and CYP1A1, LECT2, and CETN1. Signatures consisting of 7-8 genes were highly predictive for breast cancer recurrence and overall survival among smokers, with median C-index values of 0.8 and 0.73 for overall survival and recurrence, respectively. In contrast, median C-index values for non-smokers was only 0.59. Hence, significant interactions between gene expression and smoking status can play a key role in predicting breast cancer patient outcomes.

Interrogating differences in expression of targeted gene sets to predict breast cancer outcome.

BACKGROUND: Genomics provides opportunities to develop precise tests for diagnostics, therapy selection and monitoring. From analyses of our studies and those of published results, 32 candidate genes were identified, whose expression appears related to clinical outcome of breast cancer. Expression of these genes was validated by qPCR and correlated with clinical follow-up to identify a gene subset for development of a prognostic test. METHODS: RNA was isolated from 225 frozen invasive ductal carcinomas,and qRT-PCR was performed. Univariate hazard ratios and 95% confidence intervals for breast cancer mortality and recurrence were calculated for each of the 32 candidate genes. A multivariable gene expression model for predicting each outcome was determined using the LASSO, with 1000 splits of the data into training and testing sets to determine predictive accuracy based on the C-index. Models with gene expression data were compared to models with standard clinical covariates and models with both gene expression and clinical covariates. RESULTS: Univariate analyses revealed over-expression of RABEP1, PGR, NAT1, PTP4A2, SLC39A6, ESR1, EVL, TBC1D9, FUT8, and SCUBE2 were all associated with reduced time to disease-related mortality (HR between 0.8 and 0.91, adjusted p < 0.05), while RABEP1, PGR, SLC39A6, and FUT8 were also associated with reduced recurrence times. Multivariable analyses using the LASSO revealed PGR, ESR1, NAT1, GABRP, TBC1D9, SLC39A6, and LRBA to be the most important predictors for both disease mortality and recurrence. Median C-indexes on test data sets for the gene expression, clinical, and combined models were 0.65, 0.63, and 0.65 for disease mortality and 0.64, 0.63, and 0.66 for disease recurrence, respectively. CONCLUSIONS: Molecular signatures consisting of five genes (PGR, GABRP, TBC1D9, SLC39A6 and LRBA) for disease mortality and of six genes (PGR, ESR1, GABRP, TBC1D9, SLC39A6 and LRBA) for disease recurrence were identified. These signatures were as effective as standard clinical parameters in predicting recurrence/mortality, and when combined, offered some improvement relative to clinical information alone for disease recurrence (median difference in C-values of 0.03, 95% CI of -0.08 to 0.13). Collectively, results suggest that these genes form the basis for a clinical laboratory test to predict clinical outcome of breast cancer.

Epigenetic analysis of laser capture microdissected fetal epithelia.

Laser capture microdissection (LCM) is a superior method for nondestructive collection of specific cell populations from tissue sections. Although DNA, RNA, and protein have been analyzed from LCM-procured samples, epigenetic analyses, particularly of fetal, highly hydrated tissue, have not been attempted. A standardized protocol with quality assurance measures was established to procure cells by LCM of the medial edge epithelia (MEE) of the fetal palatal processes for isolation of intact microRNA for expression analyses and genomic DNA (gDNA) for CpG methylation analyses. MicroRNA preparations, obtained using the RNAqueous Micro kit (Life Technologies), exhibited better yields and higher quality than those obtained using the Arcturus PicoPure RNA Isolation kit (Life Technologies). The approach was validated using real-time polymerase chain reaction (PCR) to determine expression of selected microRNAs (miR-99a and miR-200b) and pyrosequencing to determine CpG methylation status of selected genes (Aph1a and Dkk4) in the MEE. These studies describe an optimized approach for employing LCM of epithelial cells from fresh frozen fetal tissue that enables quantitative analyses of microRNA expression levels and CpG methylation.

Assessment of phytoestrogen and mycoestrogen recognition by recombinant human estrogen receptor-α using ligand titration arrays.

INTRODUCTION: Exposure to phytoestrogens and mycoestrogens has emerged as a public health issue due to their potentially endocrine disruption activities resulting from direct interaction with sex-steroid hormone receptors. There is a significant requirement for comprehensive, reproducible methods to determine the extent of estrogen mimicry by compounds encountered in the environment to estimate risk:benefit ratios, particularly in humans. OBJECTIVE: To develop a systematic approach for assessing recognition of chemically diverse compounds by human estrogen receptor proteins to aid in their assessment as endocrine disruptor compounds (EDCs). METHODS: Recombinant human estrogen receptor-α protein (rhERα) was expressed in Saccharomyces cervisiae as an ubiquitin fusion under control of a CUP1 promoter and partially purified with heparin affinity chromatography in the unliganded state. A novel radio-ligand binding array was developed to evaluate structurally diverse compounds, both naturally occurring and synthetic, for estrogen binding activity and affinity. RESULTS: Binding affinities of suspected estrogen mimics for rhERα were calculated over a range of [(3) H]estradiol-17ß concentrations using Lundon OneSite® and Compete® software. CONCLUSION: ß-zearalanol, a mycoestrogen similar to zearalenone used as an ICCVAM validation substance for the in vitro estrogen receptor binding assays (ICCAM report), was employed as a model estrogen mimic to illustrate the approach, methods and calculations using these techniques.

Expression of urokinase-type plasminogen activator (uPA), its receptor (uPAR), and inhibitor (PAI-1) in human breast carcinomas and their clinical relevance.

Serine proteases convert plasminogen to plasmin which is involved in tissue remodeling under physiologic and pathophysiologic conditions, including breast carcinoma invasion and progression. Both urokinase-type plasminogen activator (uPA) and pro-uPA associate with uPA receptor (uPAR) on target cells, where plasminogen activator inhibitors (e.g., PAI-1) may modulate their activities. Expression levels of these factors were compared in breast carcinomas relative to patient characteristics, carcinoma features, and clinical outcome. uPA, uPAR, and PAI-1 were quantified by enzyme-linked immunosorbent assay (ELISA) in extracts of 226 biopsies while estrogen receptor (ER) and progestin receptor (PR) were determined by enzyme immunoassay (EIA) or radio-ligand binding. Each set of assays contained a novel reference specimen with known quantities of each of these five analytes. Levels in ng/mg protein of these biomarkers exhibited ranges: uPA (0-12.3); uPAR (0-19.5); PAI-1 (0-91.2). When considered independently, expression of uPA, uPAR, or PAI-1 was unrelated to patient age or menopausal status. Although no correlation was observed between each analyte with stage, grade, or ER/PR status, levels appeared to differ with pathology and nodal status. A dendrogram from hierarchical clustering of uPA, uPAR, and PAI-1 levels in 106 specimens revealed three clusters of breast cancer patients. Kaplan-Meier analyses of uPA, uPAR, and PAI-1 indicated a correlation with overall survival (OS), suggesting collective examination of these biomarkers is useful in predicting clinical outcome of breast cancer.

Serine synthesis influences tamoxifen response in ER+ human breast carcinoma.

Estrogen receptor-positive breast cancer (ER+ BC) is the most common form of breast carcinoma accounting for approximately 70% of all diagnoses. Although ER-targeted therapies have improved survival outcomes for this BC subtype, a significant proportion of patients will ultimately develop resistance to these clinical interventions, resulting in disease recurrence. Phosphoserine aminotransferase 1 (PSAT1), an enzyme within the serine synthetic pathway (SSP), has been previously implicated in endocrine resistance. Therefore, we determined whether expression of SSP enzymes, PSAT1 or phosphoglycerate dehydrogenase (PHGDH), affects the response of ER+ BC to 4-hydroxytamoxifen (4-OHT) treatment. To investigate a clinical correlation between PSAT1, PHGDH, and endocrine resistance, we examined microarray data from ER+ patients who received tamoxifen as the sole endocrine therapy. We confirmed that higher PSAT1 and PHGDH expression correlates negatively with poorer outcomes in tamoxifen-treated ER+ BC patients. Next, we found that SSP enzyme expression and serine synthesis were elevated in tamoxifen-resistant compared to tamoxifen-sensitive ER+ BC cells in vitro. To determine relevance to endocrine sensitivity, we modified the expression of either PSAT1 or PHGDH in each cell type. Overexpression of PSAT1 in tamoxifen-sensitive MCF-7 cells diminished 4-OHT inhibition on cell proliferation. Conversely, silencing of either PSAT1 or PHGDH resulted in greater sensitivity to 4-OHT treatment in LCC9 tamoxifen-resistant cells. Likewise, the combination of a PHGDH inhibitor with 4-OHT decreased LCC9 cell proliferation. Collectively, these results suggest that overexpression of serine synthetic pathway enzymes contribute to tamoxifen resistance in ER+ BC, which can be targeted as a novel combinatorial treatment option.

Angiogenesis-associated sequence variants relative to breast cancer recurrence and survival.

INTRODUCTION: Breast cancer (BrCA) risk stratification using clinico-pathological biomarkers helps improve disease prognosis prediction. However, disease recurrence rates remain unfavorable and individualized clinical management strategies are needed. Consequently, we evaluated the influence of 14 sequence variants detected in IL-10, TGF-ß1, VEGF, and their associated receptors as effective predictors of BrCA clinical outcomes. METHODS: Tumor DNA samples collected from 441 BrCA patients were genotyped using TaqMan-PCR. Most selected targets alter cytokine serum/plasma levels or signaling pathways. Relationships between genetic profiles and recurrence as well as disease-related mortality were evaluated using cumulative incidence curves and competing risk regression models. RESULTS: The VEGF(-2578)C allele was associated with a 1.3- to 1.6-fold increase in BrCA recurrence (HR(trend) = 1.28; 95% CI = 0.96-1.72) and disease-related mortality (HR(trend) = 1.56; 95% CI = 0.93-2.56). Although this marker was marginally significant relative to BrCA outcomes, there were substantial gains in the 5- and 8-year predictive accuracy compared to standard prognostic indicators. Among ER(+)/PR(+) status patients, there was a significant impact of the VEGF(-2578)CC genotype on disease recurrence and predictive accuracy. CONCLUSIONS: Our findings suggest inheritance of the VEGF(-2578)C allele could serve as an independent prognostic indicator of BrCA prognosis. The VEGF(-2578) marker may have clinical implications among a subset of ER(+)/PR(+) patients with an aggressive phenotype. Because the VEGF(-2578)C allele is linked to high VEGF expression, this cytokine is a potential prognostic and targeted clinical management tool.

Steroid receptor and growth factor receptor expression in human nonsmall cell lung cancers using cells procured by laser-capture microdissection.

Few biomarkers exist for management of nonsmall cell lung cancers (NSCLC), although estrogen receptor (ERalpha and ERbeta) and EGF receptor (EGFR) expression has been related to clinical outcome. To circumvent problems of cellular heterogeneity in whole tissue, relative gene expression of ERalpha, ERbeta, EGFR, and HER-2 (c-erb-B2) was examined in pure lung carcinoma (LC) cells and normal epithelia by LCM. Cell-specific RNA was isolated and purified for RT-qPCR and microarray. Comparison of NSCLC cells to normal epithelia indicated increased levels of mRNA expression of ERbeta, ERalpha, EGFR, and HER-2 by 31%, 38%, 54%, and 62%, respectively, in LCs. The majority of NSCLC exhibiting low ERalpha and high HER-2 expression were from smokers. Although there was no correlation between ERbeta or EGFR expression and smoking history, there appeared to be an inverse relationship between levels of ERbeta and EGFR mRNAs in normal and neoplastic lung. Additionally, microarray analyses of LCM cells revealed >2,000 genes significantly altered in LC compared with normal epithelia. Herein, differences in NSCLC gene expression and normal lung cells were noted between specimens from gender and smoking groups. Microarray data revealed ERa expression was associated with alterations in <20 genes while ERbeta expression revealed >500 associated genes, suggesting a more prominent role for ERbeta in lung. HER-2 mRNA levels appeared associated with >1,000 genes, while EGFR mRNA levels were associated with far fewer genes. Collectively, results suggest quantitative genomic analyses of pure cell populations allow more accurate interpretation of LC status, which is being correlated with clinical outcome.

Molecular signatures of estrogen receptor-associated genes in breast cancer predict clinical outcome.

Our goal is to identify new molecular targets for drug design and improve understanding of the molecular basis of clinical behavior and therapeutic response of breast cancer (BC). Pure populations of BC cells were procured by laser capture microdissection (LCM) from deidentified tissue specimens. RNA from either LCM-procured cells or whole tissue sections was extracted, purified, and quantified by RT-qPCR using beta-actin for relative quantification. RNA was amplified, Cy5-labeled, and hybridized for microarray. Spectrophotometric and BioAnalyzer analyses evaluated aRNA yield, purity, and transcript length for gene microarray. Unsupervised and supervised methods selected 7,000 genes with significant variation. Expression profiles of BC cells were dominated by genes associated with estrogen receptor-alpha (ERalpha) status; over 3,000 genes were identified as differentially expressed between ERalpha+ and ERalpha(-) BC cells. Other prominent gene expression patterns divided ERalpha+ BCs into subgroups, which were associated with significantly different clinical outcomes (p < 0.01). While exploiting larger gene sets derived from LCM-cells and reports using whole tissues, a preliminary 14 gene subset was selected by UniGene Cluster analysis. Additionally, ERE-binding proteins (ERE-BP) were detected by EMSA, which were not recognized by ERa antibodies. Kaplan-Meier analysis indicated that patients with ERE-BP positive BCs had lower over-all survival than those with ERE-BP negative cancers. Collectively, these results will establish molecular signatures for assessing clinical features of BC and aid in the selection of molecular targets for drug development.

Biosensors for detecting estrogen-like molecules and protein biomarkers.

A novel evanescent-based biosensor (Endotect, ThreeFold Sensors, Inc.) was developed with laser-based fiber optics using fluorescent dye-labeled recombinant human estrogen receptor-alpha (rhERalpha) and hERbeta as probes. A three-tiered approach evaluating various steps in the formation of the estrogen-receptor complex and its subsequent activity was developed for instrument calibration to detect estrogen mimics in biological samples, water and soil. Using this approach, binding affinities and activities of certain known estrogen mimics were determined for their use as calibrator molecules. Results indicated rhERalpha and rhERbeta may be employed as probes to distinguish estrogen mimics with a broad range of affinities. In addition, application of the biosensor for detecting DNA-binding proteins in human tissue extracts was demonstrated. The later studies suggest the biosensor may be used as a clinical laboratory tool for assessing tumor marker proteins.

A three-tiered approach for calibration of a biosensor to detect estrogen mimics.

A three-tiered approach was developed to determine the influence of a chemically-diverse group of compounds exhibiting estrogen mimicry using recombinant human estrogen receptor (rhER) activity to calibrate a receptor protein-based biosensor. In the initial tier, a ligand competition array was developed to evaluate compounds inhibiting [3H]estradiol-17beta binding to rhER. Each of six different concentrations of [3H]estradiol-17beta was mixed with increasing concentrations of an unlabeled putative mimic. Each of these mixtures was incubated with a constant amount of rhERalpha and then receptor-bound [[3H]estradiol-17beta was measured. This array protocol analyzes ligand binding affinities of hERalpha with a potential inhibitor over the entire range of receptor protein saturation. When either hERalpha or hERbeta binds to an estrogenic ligand, the receptor monomer forms both homo- and hetero-dimers. Then the ligand-receptor dimer complex activates transcription by associating with an estrogen response element (ERE), which is a specific DNA sequence located upstream of estrogen-responsive genes. The second tier for ligand evaluation utilized an electrophoretic mobility shift assay (EMSA), which was performed with an ERE sequence labeled with [alpha[32]P]dATP and incubated with rhER in the presence or absence of unlabeled ligand. ERE-hER complexes were separated by electrophoresis and analyzed using phosphor imaging technology. To assess biological effects of an estrogen mimic on expression of an ER-target gene, a yeast cell-based bioassay was constructed with recombinant DNA technology using Saccharomyces cerevisiae. Each of these engineered yeast cells contained a rhERalpha expression plasmid (YEpE12) and a separate reporter plasmid (YRG2) containing an ERE sequence upstream of a beta-galactosidase reporter gene. Incubation of these yeast cells with an estrogenic compound allows formation of ligand-hERalpha complexes, which recognize the ERE sequence regulating beta-galactosidase expression. Estrogenic compounds, which were evaluated as calibrators for ligand-based and ERE-based biosensors, elicit varying responses in each of the three tiers of the protocol.

Expression of Genes for Methylxanthine Pathway-Associated Enzymes Accompanied by Sex Steroid Receptor Status Impacts Breast Carcinoma Progression.

Consumption of methylxanthine alkaloids appears to induce activities by antagonizing adenosine receptors, implicated in breast cancer behavior in vitro. Our goal was to evaluate expression of genes for methylxanthine receptors and metabolizing enzymes to assess risk of breast carcinoma recurrence. Clinical outcomes, estrogen/progestin receptor results, and gene expression assays guided selection. RNA was isolated from laser capture microdissection-procured carcinoma cells for microarray using established protocols. Gene expression levels of eight methylxanthine receptors, eight metabolizing enzymes, and various phosphodiesterases were retrieved from microarray results. Univariable Cox regressions and Kaplan-Meier plots were determined for each gene with R software. Individually, lower expressions of PDE4A, CYP2A6, or CYP2E were related to decreased progression-free survival (PFS) and overall survival (OS). PDE1A over-expression predicted decreased PFS and OS. ADORA2B and RYR1 over-expressions predicted diminished OS. ER+ cancers exhibited lower ADORA1, ADORA2B, and RYR1 and elevated PDE4A, CYP2A6, and CYP2E expressions. Of PR+ carcinomas, diminished ADORA2B and RYR1 and elevated expressions of ADORA3, PDE4A, CYP2C8, and CYP2E were noted. Least absolute shrinkage and selection operator (LASSO) revealed that CYP2E, PDE1A, and PDE4A expressions collectively predicted PFS whereas ADORA1, CYP2E, PDE1A, PDE1B, and PDE4A expressions jointly predicted OS. Models were clinically significant when validated externally. LASSO also derived a six-gene model and five-gene model that predicted PFS of ER- or PR- carcinomas, respectively. Similarly, five-gene and four-gene models predicted OS in ER- or PR- carcinomas, respectively. Collectively, expression of genes involved in methylxanthine action and metabolism in single-cell types predicted clinical outcomes of breast carcinoma indicating promise for developing diagnostics and design of new therapeutics.

Temporal Expression of miRNAs in Laser Capture Microdissected Palate Medial Edge Epithelium from Tgfß3(-/-) Mouse Fetuses.

Clefting of the secondary palate is the most common birth defect in humans. Midline fusion of the bilateral palatal processes is thought to involve apoptosis, epithelial to mesenchymal transition, and cell migration of the medial edge epithelium (MEE), the specialized cells of the palate that mediate fusion of the palatal processes during fetal development. Data presented in this manuscript are the result of analyses designed to identify microRNAs that are expressed and regulated by TGFß3 in developing palatal MEE. The expression of 7 microRNAs was downregulated and 1 upregulated in isolated MEE from wildtype murine fetuses on gestational day (GD) 13.5 to GD14.5 (prior to and during epithelial fusion of the palatal processes, respectively). Among this group were miRNAs linked to apoptosis (miR-378) and epithelial to mesenchymal transformation (miR-200b, miR-205, and miR-93). Tgfß3(-/-) fetuses, which present with a complete and isolated cleft of the secondary palate, exhibited marked dysregulation of distinct miRNAs both in the palatal MEE and mesenchyme when compared to comparable wild-type tissue. These included, among others, miRNAs known to affect apoptosis (miR-206 and miR-186). Dysregulation of miRNAs in the mesenchyme underlying the palatal MEE of Tgfß3(-/-) fetuses is also discussed in relation to epithelial-mesenchymal transformation of the MEE. These results are the first systematic analysis of the expression of microRNAs in isolated fetal palatal epithelium and mesenchyme. Moreover, analysis of the Tgfß3 knockout mouse model has enabled identification of miRNAs with altered expression that may contribute to the cleft palate phenotype.

A systems biology approach identifies a regulatory network in parotid acinar cell terminal differentiation.

OBJECTIVE: The transcription factor networks that drive parotid salivary gland progenitor cells to terminally differentiate, remain largely unknown and are vital to understanding the regeneration process. METHODOLOGY: A systems biology approach was taken to measure mRNA and microRNA expression in vivo across acinar cell terminal differentiation in the rat parotid salivary gland. Laser capture microdissection (LCM) was used to specifically isolate acinar cell RNA at times spanning the month-long period of parotid differentiation. RESULTS: Clustering of microarray measurements suggests that expression occurs in four stages. mRNA expression patterns suggest a novel role for Pparg which is transiently increased during mid postnatal differentiation in concert with several target gene mRNAs. 79 microRNAs are significantly differentially expressed across time. Profiles of statistically significant changes of mRNA expression, combined with reciprocal correlations of microRNAs and their target mRNAs, suggest a putative network involving Klf4, a differentiation inhibiting transcription factor, which decreases as several targeting microRNAs increase late in differentiation. The network suggests a molecular switch (involving Prdm1, Sox11, Pax5, miR-200a, and miR-30a) progressively decreases repression of Xbp1 gene transcription, in concert with decreased translational repression by miR-214. The transcription factor Xbp1 mRNA is initially low, increases progressively, and may be maintained by a positive feedback loop with Atf6. Transfection studies show that Xbp1 activates the Mist1 promoter [corrected]. In addition, Xbp1 and Mist1 each activate the parotid secretory protein (Psp) gene, which encodes an abundant salivary protein, and is a marker of terminal differentiation. CONCLUSION: This study identifies novel expression patterns of Pparg, Klf4, and Sox11 during parotid acinar cell differentiation, as well as numerous differentially expressed microRNAs. Network analysis identifies a novel stemness arm, a genetic switch involving transcription factors and microRNAs, and transition to an Xbp1 driven differentiation network. This proposed network suggests key regulatory interactions in parotid gland terminal differentiation.

Gender-associated expression of tumor markers and a small gene set in breast carcinoma.

Breast carcinomas in both genders share pathological features, although differences in incidence, prognosis and survival are reported. Expression of 33 genes was investigated in male and female breast carcinomas in association with ER, PR, HER-2/neu and EGF-receptor. Among 98 male breast cancers, 82 were ER+ and 78 were PR+. ER and PR protein levels were greater in males compared to females, although no differences were observed in ESR1 and PGR expression. A difference was observed in binding affinities of PR but not ER between genders. No differences were observed in HER-2/neu, EGFR protein, or patient age. Expression of NAT1, TBC1D9, IL6ST, RABEP1, PLK1 and LRBA was elevated in carcinomas of males compared to those of females, in which ER status appeared to be related to expression. Over-expression of protein products of these genes represents novel molecular targets for development of gender-specific therapeutics and companion diagnostics.

Protein tyrosine phosphatase 4A2 expression predicts overall and disease-free survival of human breast cancer and is associated with estrogen and progestin receptor status.

Expression of protein tyrosine phosphatase PTP4A2 (also known as PRL2) has been examined in a variety of human carcinomas, although its role in breast cancer remains inconclusive. Since the majority of previous breast cancer studies utilized tissue biopsies composed of heterogeneous cell populations, we hypothesized that an examination of PTP4A2 expression in carcinoma cells isolated by laser capture microdissection (LCM) would provide a more accurate means of assessing its predictive value. From investigations of 247 human breast cancer biopsies collected under standardized, stringent conditions, total RNA was extracted from LCM-procured carcinoma cells to perform microarray analyses to identify gene signatures associated with breast cancer behavior. Expression of PTP4A2 was corroborated by real-time quantitative polymerase chain reaction (qPCR) and referenced to estrogen and progesterone receptor levels. Patient outcomes for overall and disease-free survival were more favorable (p = 0.004 and p = 0.001, respectively) when the expression of PTP4A2 in breast carcinomas was increased compared to patients with biopsies with decreased PTP4A2 levels. PTP4A2 expression determined either by microarray or qPCR was elevated in either estrogen receptor (ER)-positive or progestin receptor (PR)-positive breast cancer biopsies compared to ER-negative or PR-negative biopsies. However, PTP4A2 expression was only correlated with overall survival in PR-positive breast carcinomas. These data suggest that PTP4A2 mRNA expression alone may serve as a biomarker for prediction of a breast cancer patient's risk of recurrence and overall survival.

Characterization of estrogen response element binding proteins as biomarkers of breast cancer behavior.

BACKGROUND: While investigating estrogen response element (ERE) binding properties of human estrogen receptor-α (hERα) in breast cancer cytosols, other ERE-binding proteins (ERE-BP) were observed. DESIGN AND METHODS: Recognition properties of ERE-BP were evaluated by electrophoretic mobility shift assays (EMSA) with ERE sequences of the 5'-flanking region of the estrogen responsive gene vitellogenin A2 (VitA2). Cytosols were incubated 16 h, 4 °C with [32P]ERE sequences and separated by EMSA. A method of estimating ERE-BP levels was developed by measuring band intensity from EMSA profiles, expressed in digital light units (DLU)/µg protein and normalized to total DLU. ERE-BP were purified by affinity chromatography and EMSA, and then identified by mass spectrometry. RESULTS: ERE-BP in cytosols did not supershift in the presence of anti-hERα or anti-hERß antibodies recognizing different ER epitopes suggesting that they are not fragments of either receptor isoform. ERE-BP competed with hERα for binding to VitA2-ERE. Increased levels of ERE-BP DNA-binding activities measured in 310 cytosols prepared from breast cancer biopsies correlated with decreased patient survival. Strikingly, breast cancer patients with ER negative status and high ERE-BP expression exhibited the poorest disease-free and overall survival. After purification, ERE-BP were identified as Ku70 (XRCC6) and Ku80 (XRCC5) using mass spectrometry. ERE-BP were confirmed to be Ku70/80 by supershift assay. CONCLUSION: Presence of these novel ERE-binding proteins in a breast carcinoma is a strong predictor of poor prognosis. Our results suggest that ERE-BP, identified as Ku70/Ku80, in cytosols prepared from breast carcinoma biopsies are useful biomarkers for assessing risk of breast cancer recurrence.

Co-expression of genes with estrogen receptor-α and progesterone receptor in human breast carcinoma tissue.

UNLABELLED: Abstract Background: To detect genes associated with the expression of ESR1 and PGR - as well as of their protein products, estrogen receptor (ER) and progesterone receptor (PR) - 221 de-identified invasive ductal carcinomas of the breast were investigated. Our long-term goal is to decipher relationships between the expression of ER- and PR-associated genes and breast cancer behavior to improve diagnostics and identify new molecular targets for drug design. MATERIALS AND METHODS: Frozen tissue sections were evaluated for structural integrity and pathology after hematoxylin and eosin staining. ER and PR protein levels were quantified by either enzyme immunoassay or radio-ligand binding assay. Total RNA preparations were reverse transcribed for qPCR measurements of ESR1, PGR and 31 gene candidates. RESULTS: Both ESR1 and PGR expression levels were correlated with their cognate receptor protein expression (Pearson correlations of 0.82 and 0.68, p<0.001, respectively), to assess molecular relationships between clinically relevant biomarkers in tissue specimens. Coordinate expression of EVL, NAT1, TBC1D9, SCUBE2, RABEP1, SLC39A6, TCEAL1, FUT8, XBP1, PTP4A2 or GATA3 with either ESR1 or PGR was detected. CONCLUSIONS: Examination of relationships between ESR1 and PGR gene expression and that of other genes of interest indicated: a high degree of correlation between ESR1 levels and expression of NAT1, SCUBE2, XBP1 and GATA3; and a high degree of correlation between PGR expression and that of NAT1, ESR1, SCUBE2 and RABEP1. These results suggest that direct relationships of these genes exist with estrogen and progestin receptor mediated pathways. Pathway analysis software provided additional evidence of gene interactions.