Kaidi Mikhitarian

EpCAM Is Overexpressed in Breast Cancer and Is a Potential Target for Breast Cancer Gene Therapy

EpCAM (epithelial cell adhesion molecule) is a cell surface molecule that is known to be highly expressed in colon and other epithelial carcinomas. EpCAM is involved in cell-to-cell adhesion and has been the target of antibody therapy in several clinical trials. To assess the value of EpCAM as a novel target for breast cancer gene therapy, we performed real-time reverse transcription-PCR to quantify the level of EpCAM mRNA expression in normal breast tissue and primary and metastatic breast cancers. We found that EpCAM is overexpressed 100- to 1000-fold in primary and metastatic breast cancer. Silencing EpCAM gene expression with EpCAM short interfering RNA (siRNA) resulted in a 35–80% decrease in the rate of cell proliferation in four different breast cancer cell lines. EpCAM siRNA treatment decreased cell migration by 91.8% and cell invasion by 96.4% in the breast cancer cell line MDA-MB-231 in vitro. EpCAM siRNA treatment was also associated with an increase in the detergent-insoluble protein fraction of E-cadherin, α-catenin, and β-catenin, consistent with the known biology of EpCAM as a regulator of cell adhesion. Our hypothesis is that modulation of EpCAM expression can affect cell migration, invasion, and proliferation by enhancing E-cadherin-mediated cell-to-cell adhesion. These data provide compelling evidence that EpCAM is a potential novel target for breast cancer gene therapy and offer insights into the mechanisms associated with EpCAM gene silencing.

Quantitative real-time RT-PCR detection of breast cancer micrometastasis using a multigene marker panel

Real‐time RT‐PCR is a relatively new technology that uses an online fluorescence detection system to determine gene expression levels. It has the potential to significantly improve detection of breast cancer metastasis by virtue of its exquisite sensitivity, high throughput capacity and quantitative readout system. To assess the utility of this technology in breast cancer staging, we determined the relative expression levels of 12 cancer‐associated genes (mam, PIP, mamB, CEA, CK19, VEGF, erbB2, muc1, c‐myc, p97, vim and Ki67) in 51 negative‐control normal lymph nodes and in 17 histopathology‐positive ALNs. We then performed a receiver operating characteristic (ROC) curve analysis to determine the sensitivity and specificity levels of each gene. Areas under the ROC curve indicated that the most accurate diagnostic markers were mam (99.6%), PIP (93.3%), CK19 (91.0%), mamB (87.9%), muc1 (81.5%) and CEA (79.4.0%). mam was overexpressed in 16 of 17 lymph nodes known to contain metastatic breast cancer at levels ranging from 22‐ to 2.8 × 105‐fold above normal mean expression, whereas PIP was overexpressed from 30‐ to 2.2 × 106‐fold above normal in 13 lymph nodes. Real‐time RT‐PCR analysis of pathology‐negative LN from breast cancer patients revealed evidence of overexpression of PIP (6 nodes), mam (3 nodes) and CEA (1 node) in 8 of 21 nodes (38%). Our results provide evidence that mam, PIP, CK19, mamB, muc1 and CEA can be applied as a panel for detection of metastatic and occult micrometastatic disease.

Molecular detection of micrometastatic breast cancer in histopathology-negative axillary lymph nodes correlates with traditional predictors of prognosis: An interim analysis of a prospective multi-institutional cohort study

Objective:We sought to establish the clinical relevance of micrometastatic disease detected by reverse transcription polymerase chain reaction (RT-PCR) in axillary lymph nodes (ALN) of breast cancer patients. Background:The presence of ALN metastases remains one of the most valuable prognostic indicators in women with breast cancer. However, the clinical relevance of molecular detection of micrometastatic breast cancer in sentinel lymph nodes (SLN) and nonsentinel ALN has not been established. Methods:Four hundred eighty-nine patients with T1–T3 primary breast cancers were analyzed in a prospective, multi-institutional cohort study. ALN were analyzed by standard histopathology (H&E staining) and by multimarker, real-time RT-PCR analysis (mam, mamB, muc1, CEA, PSE, CK19, and PIP) designed to detect breast cancer micrometastases. Results:A positive marker signal was observed in 126 (87%) of 145 subjects with pathology-positive ALN, and in 112 (33%) of 344 subjects with pathology-negative ALN. In subjects with pathology-negative ALN, a positive marker signal was significantly associated with traditional indicators of prognosis, such as histologic grade (P = 0.0255) and St. Gallen risk category (P = 0.022). Mammaglobin was the most informative marker in the panel. Conclusion:This is the first report to show that overexpression of breast cancer–associated genes in breast cancer subjects with pathology-negative ALN correlates with traditional indicators of disease prognosis. These interim results provide strong evidence that molecular markers could serve as valid surrogates for the detection of occult micrometastases in ALN. Correlation of real-time RT-PCR analyses with disease-free survival in this patient cohort will help to define the clinical relevance of micrometastatic disease in this patient population.

Accurate discrimination of pancreatic ductal adenocarcinoma and chronic pancreatitis using multimarker expression data and samples obtained by minimally invasive fine needle aspiration

To augment cytological diagnosis of pancreatic ductal adenocarcinoma (PDAC) in tissue samples obtained by minimally invasive endoscopic ultrasound‐guided fine needle aspiration, we investigated whether a small set of molecular markers could accurately distinguish PDAC from chronic pancreatitis (CP). Expression levels of 29 genes were first determined by quantitative real‐time RT‐PCR in a training set of tissues in which the final diagnosis was PDAC (n = 20) or CP (n = 10). Using receiver operator characteristic curve analysis, we determined that the single gene with the highest diagnostic accuracy for discrimination of CP vs. PDAC in the training study was urokinase plasminogen activator receptor (UPAR; AUC value = 0.895, 95% CI = 0.728–0.976). In the set of test tissues (n = 14), the accuracy of UPAR decreased to 79%. However, we observed that the addition of 6 genes (EPCAM2, MAL2, CEA5, CEA6, MSLN and TRIM29; referred to as the 6‐gene classifier) to UPAR resulted in high accuracy in both training and testing sets. Excluding 3 samples (out of 44; 7%) for which results of the UPAR/6‐gene classifier were “undefined,” the accuracy of the UPAR/6‐gene classifier was 100% in training samples (n = 29), 92% in 12 test samples (p = 0.004 that results were randomly generated; p = 0.046 that the UPAR/6‐gene classifier was comparable to UPAR alone; χ2 test), 100% in 3 samples for which the initial cytological diagnosis was “suspicious” and 98% (40/41) overall. Our results provide evidence that molecular marker expression data can be used to augment cytological analysis.

Lunx Is a Superior Molecular Marker for Detection of Non-Small Lung Cell Cancer in Peripheral Blood

The clinical management of non-small cell lung cancer (NSCLC) would benefit greatly by a test that was able to detect small amounts of NSCLC in the peripheral blood. In this report, we used a novel strategy to enrich tumor cells from the peripheral blood of 24 stage I to IV NSCLC patients and determined expression levels for six cancer-associated genes (lunx, muc1, KS1/4, CEA, CK19, and PSE). Using thresholds established at three standard deviations above the mean observed in 15 normal controls, we observed that lunx (10 of 24, 42%), muc1 (5 of 24, 21%), and CK19 (5 of 24, 21%) were overexpressed in 14 of 24 (58%) peripheral blood samples obtained from NSCLC patients. Patients who overexpressed either KS1/4 (n = 2) or PSE (n = 1) also overexpressed either lunx or muc1. Of patients with presumed curable and resectable stage I to II disease (n = 7), at least one marker was overexpressed in three (43%) patients. In advanced stage III to IV patients (n = 17), at least one marker was overexpressed in 11 patients (65%). These results provide evidence that circulating tumor cells can be detected in NSCLC patients by a high throughput molecular technique. Further studies are needed to determine the clinical relevance of gene overexpression.

Real-Time Reverse Transcription-PCR Detects KS1/4 mRNA in Mediastinal Lymph Nodes from Patients with Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death for both men and women in the US. Standard therapies for patients with NSCLC include surgery, chemotherapy, and radiation therapy, and the stage of disease dictates choice of therapy. The current staging system for lung cancer uses the American Joint Committee on Cancer TNM system, and its goal is to classify patients into groups based on the extent of disease. This system relies heavily on the pathologic evaluation of the primary tumor (T), regional nodes (N), and distant metastases (M). Patients in whom mediastinal lymph nodes (MLNs) are involved (N2 or N3) are classified with stage III disease (1) and are generally considered inoperable. The recent identification of genes overexpressed in lung cancer (2)(3)(4) combined with advances in real-time reverse transcription-PCR (RT-PCR) provide the opportunity to establish sensitive and specific ways to analyze MLNs. In addition, molecular biology approaches using real-time RT-PCR are well suited to the analysis of lymph node tissue procured through minimally invasive procedures such as endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA). This technique enables reliable biopsy of MLNs without the need for general anesthesia or surgery (5). Given the advantages of EUS-FNA, we investigated the possibility that metastatic disease could be reliably detected in MLNs of NSCLC patients by real-time RT-PCR. To define the ability of real-time RT-PCR to detect metastatic NSCLC in MLNs, we procured by EUS-FNA nine MLNs containing metastatic NSCLC (five adenocarcinomas, one large cell carcinoma, one squamous cell carcinoma, and two uncharacterized carcinomas). For negative controls, we collected 30 cervical lymph nodes obtained by surgical resection. Protocols for tissue procurement and patient consent governing all aspects of this study were reviewed and approved by the Medical University of South Carolina Institutional Review Board. For EUS-FNA, a …

Detection of mammaglobin mRNA in peripheral blood is associated with high grade breast cancer: Interim results of a prospective cohort study

BackgroundWe sought to examine the detection rate of cancer cells in peripheral blood (PBL) and in bone marrow (BM) using an established 7-gene marker panel and evaluated whether there were any definable associations of any individual gene with traditional predictors of prognosis.MethodsPatients with T1-T3 primary breast cancer were enrolled into a prospective, multi-institutional cohort study. In this interim analysis 215 PBL and 177 BM samples were analyzed by multimarker, real-time RT-PCR analysis designed to detect circulating and disseminated breast cancer cells.ResultsAt a threshold of three standard deviations from the mean expression level of normal controls, 63% (136/215) of PBL and 11% (19/177) of BM samples were positive for at least one cancer-associated marker. Marker positivity in PBL demonstrated a statistically significant association with grade II-III (vs. grade I; p = 0.0083). Overexpression of the mammaglobin (mam) gene alone had a statistically significant association with high tumor grade (p = 0.0315), and showed a trend towards ER-negative tumors and a high risk category. There was no association between marker positivity in PBL and the pathologic (H&E) and/or molecular (RT-PCR) status of the axillary lymph nodes (ALN).ConclusionThis study suggests that molecular detection of circulating cancer cells in PBL detected by RT-PCR is associated with high tumor grade and specifically that overexpression of the mam gene in PBL may be a poor prognostic indicator. There was no statistically significant association between overexpression of cancer-associated genes in PBL and ALN status, supporting the concept of two potentially separate metastatic pathways.

An Innovative Microarray Strategy Identities Informative Molecular Markers for the Detection of Micrometastatic Breast Cancer

There is increasing evidence that molecular detection of micrometastatic breast cancer in the axillary lymph nodes (ALN) of breast cancer patients can improve staging. Molecular analyses of samples obtained from the Minimally Invasive Molecular Staging of Breast Cancer Trial (n = 489 patients) indicate that whereas the majority of molecular markers are informative for the detection of metastatic breast cancer (significant disease burden), only a few are sensitive for the detection of micrometastatic disease (limited disease burden). Frequency distribution and linear regression analyses reveal that relative levels of gene expression are highly correlated with apparent sensitivity for the detection of micrometastic breast cancer (P < 0.05). These data provides statistical validation of the concept that the most informative markers for detection of micrometastatic disease are those that are most highly expressed in metastatic disease. To test this hypothesis, we developed an innovative microarray strategy. RNA from a metastatic breast cancer ALN was diluted into RNA from a normal lymph node and analyzed using Affymetrix microarrays. Expression analysis indicated that only two genes [mammaglobin (mam) and trefoil factor 1 (TFF1)] were significantly overexpressed at a dilution of 1:50. Real-time reverse transcription-PCR analysis of pathology-negative ALN (n = 72) confirm that of all the markers tested, mam and TFF1 have the highest apparent sensitivity for detection of micrometastatic breast cancer. We conclude that a dilutional microarray approach is a simple and reliable method for the identification of informative molecular markers for the detection of micrometastatic cancer.

The molecular detection of micrometastatic breast cancer

BACKGROUND The rapid evolution of molecular technology and novel markers provides the opportunity to establish a more effective means to detect micrometastatic breast cancer. Given the controversies concerning application and clinical relevance, this review critically evaluates the current status of these molecular staging technologies. DATA SOURCES Breast cancer literature addressing (1). molecular detection methodologies (immunohistochemistry, reverse transcriptase polymerase chain reaction, and microarray analysis); (2). specific tissue applications such as lymph nodes, bone marrow aspirate, and peripheral blood; (3). expert commentary concerning the clinical applications and pitfalls of these technologies; and (4). recent data from our molecular diagnostics laboratory. CONCLUSIONS Molecular detection technologies such as reverse transcriptase polymerase chain reaction and microarray analyses are being developed that will likely have future application as cancer diagnostics. Further work is needed to establish assays that are validated by prospective clinical studies. Early identification of clinically relevant disease could lead to new treatment or staging approaches for breast cancer.

Accurate discrimination of Barrett's esophagus and esophageal adenocarcinoma using a quantitative three-tiered algorithm and multimarker real-time reverse transcription-PCR.

Esophageal adenocarcinoma (EA) is increasing faster than any other cancer in the U.S. In this report, we first show that EA can be distinguished from normal esophagus (NE) and esophageal squamous cell carcinoma by plotting expression values for EpCam, TFF1, and SBEM in three-dimensional Euclidean space. For monitoring progression of Barretts esophagus (BE) to EA, we developed a highly sensitive assay for limited quantities of tissue whereby 50 ng of RNA are first converted to cDNA using 16 gene-specific primers. Using a set of training tissues, we developed a novel quantitative three-tiered algorithm that allows for accurate (overall accuracy = 61/63, 97%) discrimination of BE versus EA tissues using only three genes. The gene used in the first tier of the algorithm is TSPAN: samples not diagnosed as BE or EA by TSPAN in the first tier are then subjected to a second-tier analysis using ECGF1, followed by a third-tier analysis using SPARC. Addition of TFF1 and SBEM to the first tier (i.e., a five-gene marker panel) increases the overall accuracy of the assay to 98% (62/63) and results in mean molecular diagnostic scores (± SD) that are significantly different between EA and BE samples (3.19 ± 1.07 versus −2.74 ± 1.73, respectively). Our results suggest that relatively few genes can be used to monitor progression of BE to EA.