Estrogen signaling pathways may play a significant role in the pathogenesis of non-small cell lung cancers (NSCLC) as evidenced by the expression of aromatase and estrogen receptors (ERα and ERβ) in many of these tumors. Here we examine whether ERα and ERβ levels in conjunction with aromatase define patient groups with respect to survival outcomes and possible treatment regimens. Immunohistochemistry was performed on a high-density tissue microarray with resulting data and clinical information available for 377 patients. Patients were subdivided by gender, age and tumor histology, and survival data was determined using the Cox proportional hazards model and Kaplan-Meier curves. Neither ERα nor ERβ alone were predictors of survival in NSCLC. However, when coupled with aromatase expression, higher ERβ levels predicted worse survival in patients whose tumors expressed higher levels of aromatase. Although this finding was present in patients of both genders, it was especially pronounced in women ≥ 65 years old, where higher expression of both ERβ and aromatase indicated a markedly worse survival rate than that determined by aromatase alone. Conclusion: Expression of ERβ together with aromatase has predictive value for survival in different gender and age subgroups of NSCLC patients. This predictive value is stronger than each individual marker alone. Our results suggest treatment with aromatase inhibitors alone or combined with estrogen receptor modulators may be of benefit in some subpopulations of these patients.

Lung cancer is the most common cause of cancer mortality in male and female patients in the US. Although it is clear that tobacco smoking is a major cause of lung cancer, about half of all women with lung cancer worldwide are never-smokers. Despite a declining smoking population, the incidence of non-small cell lung cancer (NSCLC), the predominant form of lung cancer, has reached epidemic proportions particularly in women. Emerging data suggest that factors other than tobacco, namely endogenous and exogenous female sex hormones, have a role in stimulating NSCLC progression. Aromatase, a key enzyme for estrogen biosynthesis, is expressed in NSCLC. Clinical data show that women with high levels of tumor aromatase (and high intratumoral estrogen) have worse survival than those with low aromatase. The present and previous studies also reveal significant expression and activity of estrogen receptors (ERα, ERβ) in both extranuclear and nuclear sites in most NSCLC. We now report further on the expression of progesterone receptor (PR) transcripts and protein in NSCLC. PR transcripts were significantly lower in cancerous as compared to non-malignant tissue. Using immunohistochemistry, expression of PR was observed in the nucleus and/or extranuclear compartments in the majority of human tumor specimens examined. Combinations of estrogen and progestins administered in vitro cooperate in promoting tumor secretion of vascular endothelial growth factor and, consequently, support tumor-associated angiogenesis. Further, dual treatment with estradiol and progestin increased the numbers of putative tumor stem/progenitor cells. Thus, ER- and/or PR-targeted therapies may offer new approaches to manage NSCLC.

The GATA family members are zinc finger transcription factors involved in cell differentiation and proliferation. GATA3 in particular is necessary for mammary gland maturation, and its loss has been implicated in breast cancer development. Our goal was to validate the ability of GATA3 expression to predict survival in breast cancer patients. Protein expression of GATA3 was analyzed on a high density tissue microarray consisting of 242 cases of breast cancer. We associated GATA3 expression with patient outcomes and clinicopathological variables. Expression of GATA3 was significantly increased in breast cancer, in situ lesions, and hyperplastic tissue compared to normal breast tissue. GATA3 expression decreased with increasing tumor grade. Low GATA3 expression was a significant predictor of disease-related death in all patients, as well as in subgroups of estrogen receptor positive or low grade patients. Additionally, low GATA3 expression correlated with increased tumor size and estrogen and progesterone receptor negativity. GATA3 is an important predictor of disease outcome in breast cancer patients. This finding has been validated in a diverse set of populations. Thus, GATA3 expression has utility as a prognostic indicator in breast cancer.

Smoking is the most important known risk factor for the development of lung cancer. Tobacco exposure results in chronic inflammation, tissue injury and repair. A recent hypothesis argues for a stem/progenitor cell involved in airway epithelial repair that may be a tumor-initiating cell in lung cancer, and which may be associated with recurrence and metastasis. We used immunostaining, quantitative real-time PCR, Western blots and lung cancer tissue microarrays to identify subpopulations of airway epithelial stem/progenitor cells under steady state conditions, normal repair, aberrant repair with premalignant lesions and lung cancer and their correlation with injury and prognosis. We identified a population of keratin 14 (K14)-expressing progenitor epithelial cells that was involved in repair after injury. Dysregulated repair resulted in persistence of K14+ cells in the airway epithelium in premalignant lesions. The presence of K14+ cells in non-small cell lung cancer (NSCLC) samples predicted poorer outcomes. This was especially true in smokers where the presence of K14+ cells in NSCLC was predictive of metastasis. The presence of K14+ progenitor airway epithelial cells in NSCLC predicted a poor prognosis and this predictive value was strongest in smokers, where it also correlated with metastasis. This suggests that reparative K14+ progenitor cells may be tumor-initiating cells in this subgroup of smokers with NSCLC.

Purpose

The tetraspan protein epithelial membrane protein-2 (EMP2) has been shown to regulate the surface display and signaling from select integrin pairs, and it was recently identified as a prognostic biomarker in human endometrial cancer. In this study, we assessed the role of EMP2 in human ovarian cancer.

Experimental Design

We examined the expression of EMP2 within a population of women with ovarian cancer using tissue microarray assay technology. We evaluated the efficacy of EMP2-directed antibody therapy using a fully human recombinant bivalent antibody fragment (diabody) in vitro and ovarian cancer xenograft models in vivo.

Results

EMP2 was found to be highly expressed in over 70% of serous and endometrioid ovarian tumors compared to non-malignant ovarian epithelium using a human ovarian cancer tissue microarray. Using anti-EMP2 diabody, we evaluated the in vitro response of 9 human ovarian cancer cell lines with detectable EMP2 expression. Treatment of human ovarian cancer cell lines with anti-EMP2 diabodies induced cell death and retarded cell growth, and these response rates correlated with cellular EMP2 expression. We next assessed the effects of anti-EMP2 diabodies in mice bearing xenografts from the ovarian endometrioid carcinoma cell line OVCAR5. Anti-EMP2 diabodies significantly suppressed tumor growth and induced cell death in OVCAR5 xenografts.

Conclusions

These findings indicate that EMP2 is expressed in the majority of ovarian tumors and it may be a feasible target in vivo.

Background

Raf-1 kinase inhibitor protein (RKIP) has been reported to negatively regulate signal kinases of major survival pathways. RKIP activity is modulated in part by phosphorylation on Serine 153 by protein kinase C, which leads to dissociation of RKIP from Raf-1. RKIP expression is low in many human cancers and represents an indicator of poor prognosis and/or induction of metastasis. The prognostic power has typically been based on total RKIP expression and has not considered the significance of phospho-RKIP.

Methods

The present study examined the expression levels of both RKIP and phospho-RKIP in human lung cancer tissue microarray proteomics technology.

Results

Total RKIP and phospho-RKIP expression levels were similar in normal and cancerous tissues. phospho-RKIP levels slightly decreased in metastatic lesions. However, the expression levels of phospho-RKIP, in contrast to total RKIP, displayed significant predictive power for outcome with normal expression of phospho-RKIP predicting a more favorable survival compared to lower levels (P = 0.0118); this was even more pronounced in more senior individuals and in those with early stage lung cancer.

Conclusions

This study examines for the first time, the expression profile of RKIP and phospho-RKIP in lung cancer. Significantly, we found that phospho-RKIP was a predictive indicator of survival.

Background

Tissue microarray (TMA) data are commonly used to validate the prognostic accuracy of tumor markers. For example, breast cancer TMA data have led to the identification of several promising prognostic markers of survival time. Several studies have shown that TMA data can also be used to cluster patients into clinically distinct groups. Here we use breast cancer TMA data to cluster patients into distinct prognostic groups.

Methods

We apply weighted correlation network analysis (WGCNA) to TMA data consisting of 26 putative tumor biomarkers measured on 82 breast cancer patients. Based on this analysis we identify three groups of patients with low (5.4%), moderate (22%) and high (50%) mortality rates, respectively. We then develop a simple threshold rule using a subset of three markers (p53, Na-KATPase-β1, and TGF β receptor II) that can approximately define these mortality groups. We compare the results of this correlation network analysis with results from a standard Cox regression analysis.

Results

We find that the rule-based grouping variable (referred to as WGCNA*) is an independent predictor of survival time. While WGCNA* is based on protein measurements (TMA data), it validated in two independent Affymetrix microarray gene expression data (which measure mRNA abundance). We find that the WGCNA patient groups differed by 35% from mortality groups defined by a more conventional stepwise Cox regression analysis approach.

Conclusions

We show that correlation network methods, which are primarily used to analyze the relationships between gene products, are also useful for analyzing the relationships between patients and for defining distinct patient groups based on TMA data. We identify a rule based on three tumor markers for predicting breast cancer survival outcomes.

Background

The protein AGR2 is a putative member of the protein disulfide isomerase family and was first identified as a homolog of the Xenopus laevis gene XAG-2. AGR2 has been implicated in a number of human cancers. In particular, AGR2 has previously been found to be one of several genes that encode secreted proteins showing increased expression in prostate cancer cells compared to normal prostatic epithelium.

Methods

Gene expression levels of AGR2 were examined in prostate cancer cells by microarray analysis. We further examined the relationship of AGR2 protein expression to histopathology and prostate cancer outcome on a population basis using tissue microarray technology.

Results

At the RNA and protein level, there was an increase in AGR2 expression in adenocarcinoma of the prostate compared to morphologically normal prostatic glandular epithelium. Using a tissue microarray, this enhanced AGR2 expression was seen as early as premalignant PIN lesions. Interestingly, within adenocarcinoma samples, there was a slight trend toward lower levels of AGR2 with increasing Gleason score. Consistent with this, relatively lower levels of AGR2 were highly predictive of disease recurrence in patients who had originally presented with high-stage primary prostate cancer (P = 0.009).

Conclusions

We have shown for the first time that despite an increase in AGR2 expression in prostate cancer compared to non-malignant cells, relatively lower levels of AGR2 are highly predictive of disease recurrence following radical prostatectomy.

Background

MED28 (also known as EG-1 and magicin) has been implicated in transcriptional control, signal regulation, and cell proliferation. MED28 has also been associated with tumor progression in in vitro and in vivo models. Here we examined the association of MED28 expression with human breast cancer progression.

Methods

Expression of MED28 protein was determined on a population basis using a high-density tissue microarray consisting of 210 breast cancer patients. The association and validation of MED28 expression with histopathological subtypes, clinicopathological variables, and disease outcome was assessed.

Results

MED28 protein expression levels were increased in ductal carcinoma in situ and invasive ductal carcinoma of the breast compared to non-malignant glandular and ductal epithelium. Moreover, MED28 was a predictor of disease outcome in both univariate and multivariate analyses with higher expression predicting a greater risk of disease-related death.

Conclusions

We have demonstrated that MED28 expression is increased in breast cancer. In addition, although the patient size was limited (88 individuals with survival information) MED28 is a novel and strong independent prognostic indicator of survival for breast cancer.