BackgroundGenomics 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.MethodsRNA 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.ResultsUnivariate 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.ConclusionsMolecular 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.

Results from investigations of human genomics which utilize intact tissue biopsy specimens maybe compromised due to a host of uncontrolled variables including cellular heterogeneity of a sample collected under diverse conditions, then processed and stored using different protocols. To determine the cellular origin and assess relationships of mRNA expression of two genes reported to be co-expressed in human breast carcinoma (estrogen receptor-α, ESR1 and X-box binding protein 1, XBP1), gene expression analyses were performed with intact tissue sections and compared with those of laser capture microdissection (LCM)-procured carcinoma and stromal cells from serial sections of the same tissue. Frozen sections of human breast carcinomas were first evaluated for structural integrity and pathology after hematoxylin and eosin (H&E) staining. Total RNA preparations from intact tissue sections and LCM-procured carcinoma and stromal cells were reverse transcribed for measurements of ESR1 and XBP1 expression by quantitative PCR (qPCR). These results were compared with those obtained from microarray analyses of LCM-procured carcinoma cells. Levels of ESR1 and XBP1 were detected in the intact breast cancer tissue sections suggesting coordinate gene expression. Although coordinate expression of these genes was observed in the LCM-procured carcinoma cells, it was not discerned in LCM-procured stromal cells. The origin of coordinate expression of ESR1 and XBP1 observed in whole tissue sections of human breast cancer biopsies is due principally to their co-expression in carcinoma cells and not in the surrounding stromal cells as substantiated using LCM-procured cells. Collectively, a microgenomic process was established from human tissue preparation to RNA characterization and analysis to identify molecular signatures of specific cell types predicting clinical behavior.

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.

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.

A series of hybrid ligands (H 2 L 1 −H 2 L 3 ) derived from 4-methyl-3-thiosemicarbazide and hydrazinecarbothioic acid O-alkyl esters were synthesized and characterized by NMR. The ligands were chelated with copper (4−6), nickel (7−9), and zinc (10−12) and characterized by spectroscopy, electrochemistry, and single crystal X-ray crystallography. The chelated metals displayed substantial anodic shifts in the Cu II/I reduction potential of ∼160 mV relative to their bis(thiosemicarbazone) analogues. The metal chelates 4−12 were evaluated for potential anticancer activity by MTT assays, and selected results were confirmed by clonogenic and trypan blue assays. The copper derivatives 4 and 6 were found to have potent and cancer-selective antiproliferative effects, with GI 50 values less than 100 nM in A549 lung adenocarcinoma cells compared with at least 20-fold less activity in IMR90 nonmalignant lung fibroblasts. In comparison, the nickel complexes were much less active and had little cancer-selectivity. Varying by ligand, the zinc complexes were less potent or had comparable activity compared to that of the corresponding copper complex. UV−visible spectroscopy indicated that zinc complex 10 was transmetalated in the presence of equimolar copper, whereas nickel complex 7 was not. Copper complexes 4 and 6 were also assessed in the NCI60 screen and were found to have cytotoxic activity against most solid tumor cell lines. In MTT assays, 4 and 6 were substantially more active against A549 cancer cells than Cu(ATSM) and were more cancer-selective (for A549 compared to IMR-90) than Cu(GTSM). Our results suggest that hybrid thiosemicarbazone− alkylthiocarbamate copper complexes have potential for development as new anticancer agents.