Estimation of Measurement Uncertainty in Quantitation of Benzoylecgonine (BZE) and 11-nor-Δ9-THC-9-carboxylic acid (THCA).

Calculating measurement uncertainty is a helpful exercise for identifying components or steps in a forensic analytical procedure that contribute to measurement variance. In this study, we used a bottom up approach to identify components in our procedures that contribute to measurement variance in our Department of Defense (DoD) Drug Demand Reduction Program (DDRP) Gas Chromatography Mass Spectroscopy (GCMS) analytical procedures for benzoylecgonine (BZE) and the THC metabolite, 11-nor-Δ9-THC-9-carboxylic acid (THCA) at 125% the DDRP concentration threshold (cutoff). Each assay was run 10 times over 30 days, each assay containing five calibrators and five samples (125%). Measurement uncertainty was estimated to be ±7.6 and ±0.6 ng/mL, for the BZE and THCA methods, respectively (α = 0.05). In both assays, method precision and the preparation of calibrator and samples were major contributors to measurement uncertainty. While this exercise will help with evaluating assay performance from a Quality Assurance perspective, these estimates should not be applied in interpreting DDRP test results. DDRP cut offs are already inherently conservative being above the Limit of Quantitation and were developed taking into consideration variability in assay performance across instruments and laboratories within the DDRP drug testing system.

Tumor intrinsic subtype is reflected in cancer-adjacent tissue.

INTRODUCTION: Overall survival of early-stage breast cancer patients is similar for those who undergo breast-conserving therapy (BCT) and mastectomy; however, 10% to 15% of women undergoing BCT suffer ipsilateral breast tumor recurrence. The risk of recurrence may vary with breast cancer subtype. Understanding the gene expression of the cancer-adjacent tissue and the stromal response to specific tumor subtypes is important for developing clinical strategies to reduce recurrence risk. METHODS: We utilized two independent datasets to study gene expression data in cancer-adjacent tissue from invasive breast cancer patients. Complementary in vitro cocultures were used to study cell-cell communication between fibroblasts and specific breast cancer subtypes. RESULTS: Our results suggest that intrinsic tumor subtypes are reflected in histologically normal cancer-adjacent tissue. Gene expression of cancer-adjacent tissues shows that triple-negative (Claudin-low or basal-like) tumors exhibit increased expression of genes involved in inflammation and immune response. Although such changes could reflect distinct immune populations present in the microenvironment, altered immune response gene expression was also observed in cocultures in the absence of immune cell infiltrates, emphasizing that these inflammatory mediators are secreted by breast-specific cells. In addition, although triple-negative breast cancers are associated with upregulated immune response genes, luminal breast cancers are more commonly associated with estrogen-response pathways in adjacent tissues. CONCLUSIONS: Specific characteristics of breast cancers are reflected in the surrounding histologically normal tissue. This commonality between tumor and cancer-adjacent tissue may underlie second primaries and local recurrences. IMPACT: Biomarkers derived from cancer-adjacent tissue may be helpful in defining personalized surgical strategies or in predicting recurrence risk.

Role of HGF in epithelial-stromal cell interactions during progression from benign breast disease to ductal carcinoma in situ.

INTRODUCTION: Basal-like and luminal breast cancers have distinct stromal-epithelial interactions, which play a role in progression to invasive cancer. However, little is known about how stromal-epithelial interactions evolve in benign and pre-invasive lesions. METHODS: To study epithelial-stromal interactions in basal-like breast cancer progression, we cocultured reduction mammoplasty fibroblasts with the isogenic MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and ductal carcinoma in situ). We used gene expression microarrays to identify pathways induced by coculture in premalignant cells (MCF10DCIS) compared with normal and benign cells (MCF10A and MCF10AT1). Relevant pathways were then evaluated in vivo for associations with basal-like subtype and were targeted in vitro to evaluate effects on morphogenesis. RESULTS: Our results show that premalignant MCF10DCIS cells express characteristic gene expression patterns of invasive basal-like microenvironments. Furthermore, while hepatocyte growth factor (HGF) secretion is upregulated (relative to normal, MCF10A levels) when fibroblasts are cocultured with either atypical (MCF10AT1) or premalignant (MCF10DCIS) cells, only MCF10DCIS cells upregulated the HGF receptor MET. In three-dimensional cultures, upregulation of HGF/MET in MCF10DCIS cells induced morphological changes suggestive of invasive potential, and these changes were reversed by antibody-based blocking of HGF signaling. These results are relevant to in vivo progression because high expression of a novel MCF10DCIS-derived HGF signature was correlated with the basallike subtype, with approximately 86% of basal-like cancers highly expressing the HGF signature, and because high expression of HGF signature was associated with poor survival. CONCLUSIONS: Coordinated and complementary changes in HGF/MET expression occur in epithelium and stroma during progression of pre-invasive basal-like lesions. These results suggest that targeting stroma-derived HGF signaling in early carcinogenesis may block progression of basal-like precursor lesions.

Impact of tumor microenvironment and epithelial phenotypes on metabolism in breast cancer.

PURPOSE: Cancer cells have altered metabolism, with increased glucose uptake, glycolysis, and biomass production. This study conducted genomic and metabolomic analyses to elucidate how tumor and stromal genomic characteristics influence tumor metabolism. EXPERIMENTAL DESIGN: Thirty-three breast tumors and six normal breast tissues were analyzed by gene expression microarray and by mass spectrometry for metabolites. Gene expression data and clinical characteristics were evaluated in association with metabolic phenotype. To evaluate the role of stromal interactions in altered metabolism, cocultures were conducted using breast cancer cells and primary cancer-associated fibroblasts (CAF). RESULTS: Across all metabolites, unsupervised clustering resulted in two main sample clusters. Normal breast tissue and a subset of tumors with less aggressive clinical characteristics had lower levels of nucleic and amino acids and glycolysis byproducts, whereas more aggressive tumors had higher levels of these Warburg-associated metabolites. While tumor-intrinsic subtype did not predict metabolic phenotype, metabolic cluster was significantly associated with expression of a wound response signature. In cocultures, CAFs from basal-like breast cancers increased glucose uptake and basal-like epithelial cells increased glucose oxidation and glycogen synthesis, suggesting interplay of stromal and epithelial phenotypes on metabolism. Cytokine arrays identified hepatocyte growth factor (HGF) as a potential mediator of stromal-epithelial interaction and antibody neutralization of HGF resulted in reduced expression of glucose transporter 1 (GLUT1) and decreased glucose uptake by epithelium. CONCLUSIONS: Both tumor/epithelial and stromal characteristics play important roles in metabolism. Warburg-like metabolism is influenced by changes in stromal-epithelial interactions, including altered expression of HGF/Met pathway and GLUT1 expression.

Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients.

INTRODUCTION: A gene expression signature indicative of activated wound responses is common to more than 90% of non-neoplastic tissues adjacent to breast cancer, but these tissues also exhibit substantial heterogeneity. We hypothesized that gene expression subtypes of breast cancer microenvironment can be defined and that these microenvironment subtypes have clinical relevance. METHODS: Gene expression was evaluated in 72 patient-derived breast tissue samples adjacent to invasive breast cancer or ductal carcinoma in situ. Unsupervised clustering identified two distinct gene expression subgroups that differed in expression of genes involved in activation of fibrosis, cellular movement, cell adhesion and cell-cell contact. We evaluated the prognostic relevance of extratumoral subtype (comparing the Active group, defined by high expression of fibrosis and cellular movement genes, to the Inactive group, defined by high expression of claudins and other cellular adhesion and cell-cell contact genes) using clinical data. To establish the biological characteristics of these subtypes, gene expression profiles were compared against published and novel tumor and tumor stroma-derived signatures (Twist-related protein 1 (TWIST1) overexpression, transforming growth factor beta (TGF-ß)-induced fibroblast activation, breast fibrosis, claudin-low tumor subtype and estrogen response). Histological and immunohistochemical analyses of tissues representing each microenvironment subtype were performed to evaluate protein expression and compositional differences between microenvironment subtypes. RESULTS: Extratumoral Active versus Inactive subtypes were not significantly associated with overall survival among all patients (hazard ratio (HR) = 1.4, 95% CI 0.6 to 2.8, P = 0.337), but there was a strong association with overall survival among estrogen receptor (ER) positive patients (HR = 2.5, 95% CI 0.9 to 6.7, P = 0.062) and hormone-treated patients (HR = 2.6, 95% CI 1.0 to 7.0, P = 0.045). The Active subtype of breast microenvironment is correlated with TWIST-overexpression signatures and shares features of claudin-low breast cancers. The Active subtype was also associated with expression of TGF-ß induced fibroblast activation signatures, but there was no significant association between Active/Inactive microenvironment and desmoid type fibrosis or estrogen response gene expression signatures. Consistent with the RNA expression profiles, Active cancer-adjacent tissues exhibited higher density of TWIST nuclear staining, predominantly in epithelium, and no evidence of increased fibrosis. CONCLUSIONS: These results document the presence of two distinct subtypes of microenvironment, with Active versus Inactive cancer-adjacent extratumoral microenvironment influencing the aggressiveness and outcome of ER-positive human breast cancers.

Interactions with fibroblasts are distinct in Basal-like and luminal breast cancers.

Basal-like breast cancers have several well-characterized distinguishing molecular features, but most of these are features of the cancer cells themselves. The unique stromal-epithelial interactions, and more generally, microenvironmental features of basal-like breast cancers have not been well characterized. To identify characteristic microenvironment features of basal-like breast cancer, we performed cocultures of several basal-like breast cancer cell lines with fibroblasts and compared these with cocultures of luminal breast cancer cell lines with fibroblasts. Interactions between basal-like cancer cells and fibroblasts induced expression of numerous interleukins and chemokines, including IL-6, IL-8, CXCL1, CXCL3, and TGFß. Under the influence of fibroblasts, basal-like breast cancer cell lines also showed increased migration in vitro. Migration was less pronounced for luminal lines; but, these lines were more likely to have altered proliferation. These differences were relevant to tumor biology in vivo, as the gene set that distinguished luminal and basal-like stromal interactions in coculture also distinguishes basal-like from luminal tumors with 98% accuracy in 10-fold cross-validation and 100% accuracy in an independent test set. However, comparisons between cocultures where cells were in direct contact and cocultures where interaction was solely through soluble factors suggest that there is an important impact of direct cell-to-cell contact. The phenotypes and gene expression changes invoked by cancer cell interactions with fibroblasts support the microenvironment and cell-cell interactions as intrinsic features of breast cancer subtypes.