Epigenetic clock and methylation studies in elephants.

Age-associated DNA-methylation profiles have been used successfully to develop highly accurate biomarkers of age ("epigenetic clocks") in humans, mice, dogs, and other species. Here we present epigenetic clocks for African and Asian elephants. These clocks were developed using novel DNA methylation profiles of 140 elephant blood samples of known age, at loci that are highly conserved between mammalian species, using a custom Infinium array (HorvathMammalMethylChip40). We present epigenetic clocks for Asian elephants (Elephas maximus), African elephants (Loxodonta africana), and both elephant species combined. Two additional human-elephant clocks were constructed by combining human and elephant samples. Epigenome-wide association studies identified elephant age-related CpGs and their proximal genes. The products of these genes play important roles in cellular differentiation, organismal development, metabolism, and circadian rhythms. Intracellular events observed to change with age included the methylation of bivalent chromatin domains, and targets of polycomb repressive complexes. These readily available epigenetic clocks can be used for elephant conservation efforts where accurate estimates of age are needed to predict demographic trends.

Bladder cancer cells secrete while normal bladder cells express but do not secrete AGR2.

Anterior gradient 2 (AGR2) is a cancer-associated secreted protein found predominantly in adenocarcinomas. Given its ubiquity in solid tumors, cancer-secreted AGR2 could be a useful biomarker in urine or blood for early detection. However, normal organs express and might also secrete AGR2, which would impact its utility as a cancer biomarker. Uniform AGR2 expression is found in the normal bladder urothelium. Little AGR2 is secreted by the urothelial cells as no measurable amounts could be detected in urine. The urinary proteomes of healthy people contain no listing for AGR2. Likewise, the blood proteomes of healthy people also contain no significant peptide counts for AGR2 suggesting little urothelial secretion into capillaries of the lamina propria. Expression of AGR2 is lost in urothelial carcinoma, with only 25% of primary tumors observed to retain AGR2 expression in a cohort of lymph node-positive cases. AGR2 is secreted by the urothelial carcinoma cells as urinary AGR2 was measured in the voided urine of 25% of the cases analyzed in a cohort of cancer vs. non-cancer patients. The fraction of AGR2-positive urine samples was consistent with the fraction of urothelial carcinoma that stained positive for AGR2. Since cancer cells secrete AGR2 while normal cells do not, its measurement in body fluids could be used to indicate tumor presence. Furthermore, AGR2 has also been found on the cell surface of cancer cells. Taken together, secretion and cell surface localization of AGR2 are characteristic of cancer, while expression of AGR2 by itself is not.

MCT1 Modulates Cancer Cell Pyruvate Export and Growth of Tumors that Co-express MCT1 and MCT4.

Monocarboxylate transporter 1 (MCT1) inhibition is thought to block tumor growth through disruption of lactate transport and glycolysis. Here, we show MCT1 inhibition impairs proliferation of glycolytic breast cancer cells co-expressing MCT1 and MCT4 via disruption of pyruvate rather than lactate export. MCT1 expression is elevated in glycolytic breast tumors, and high MCT1 expression predicts poor prognosis in breast and lung cancer patients. Acute MCT1 inhibition reduces pyruvate export but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that co-express MCT1 and MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest MCT1 expression is elevated in glycolytic cancers to promote pyruvate export that when inhibited, enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors, further supporting their use as anti-cancer therapeutics.

High expression of AGR2 in lung cancer is predictive of poor survival.

BACKGROUND: Anterior gradient 2 (AGR2) is a protein disulfide isomerase-like protein widely expressed in many normal tissues as well as cancers. In our study, non-neoplastic bronchial epithelial cells as well as non-small cell lung cancer (NSCLC) cells express AGR2 protein. METHODS: AGR2 expression was analyzed on lung tissue microarrays. Tumor staining was correlated with clinical outcomes. RESULTS: On a lung cancer tissue microarray using immunohistochemistry, expression levels in cancer showed generally decreasing intensities in order from adenocarcinomas with mucinous components, other adenocarcinomas, squamous carcinomas, to large cell carcinomas. The study cohort was comprised of 400 cases. As a group, there was a slight trend of lower expression with increasing tumor grade. AGR2 expression level was a significant predictor of overall survival in younger patients only. Patients under 65 with lower levels showed a significantly better survival for both men and women. Patients over 65, in contrast, showed no such trend. CONCLUSIONS: Nearly all NSCLC tumors show AGR2 expression. Lung cancer expression of AGR2 has prognostic value for younger patients.

Ribonucleotide reductase subunit M2 predicts survival in subgroups of patients with non-small cell lung carcinoma: effects of gender and smoking status.

BACKGROUND: Ribonucleotide reductase catalyzes the conversion of ribonucleotide diphosphates to deoxyribonucleotide diphosphates. The functional enzyme consists of two subunits - one large (RRM1) and one small (RRM2 or RRM2b) subunit. Expression levels of each subunit have been implicated in prognostic outcomes in several different types of cancers. EXPERIMENTAL DESIGN: Immunohistochemistry for RRM1 and RRM2 was performed on a lung cancer tissue microarray (TMA) and analyzed. 326 patients from the microarray were included in this study. RESULTS: In non-small cell lung cancer (NSCLC), RRM2 expression was strongly predictive of disease-specific survival in women, non-smokers and former smokers who had quit at least 10 years prior to being diagnosed with lung cancer. Higher expression was associated with worse survival. This was not the case for men, current smokers and those who had stopped smoking for shorter periods of time. RRM1 was not predictive of survival outcomes in any subset of the patient group. CONCLUSION: RRM2, but not RRM1, is a useful predictor of survival outcome in certain subsets of NSCLC patients.

Prostate cancer cell phenotypes based on AGR2 and CD10 expression.

The combination of expression patterns of AGR2 (anterior gradient 2) and CD10 by prostate cancer provided four phenotypes that correlated with clinical outcome. Based on immunophenotyping, CD10(low)AGR2(high), CD10(high)AGR2(high), CD10(low)AGR2(low), and CD10(high)AGR2(low) were distinguished. AGR2(+) tumors were associated with longer recurrence-free survival and CD10(+) tumors with shorter recurrence-free survival. In high-stage cases, the CD10(low)AGR2(high) phenotype was associated with a ninefold higher recurrence-free survival than the CD10(high)AGR2(low) phenotype. The CD10(high)AGR2(high) and CD10(low)AGR2(low) phenotypes were intermediate. The CD10(high)AGR2(low) phenotype was most frequent in high-grade primary tumors. Conversely, bone and other soft tissue metastases, and derivative xenografts, expressed more AGR2 and less CD10. AGR2 protein was readily detected in tumor metastases. The CD10(high)AGR2(low) phenotype in primary tumors is predictive of poor outcome; however, the CD10(low)AGR2(high) phenotype is more common in metastases. It appears that AGR2 has a protective function in primary tumors but may have a role in the distal spread of tumor cells.

Protein expression based multimarker analysis of breast cancer samples.

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-ß1, and TGF ß 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.

Progesterone and estrogen receptor expression and activity in human non-small cell lung cancer.

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, ERß) 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.

Expression levels of estrogen receptor beta in conjunction with aromatase predict survival in non-small cell lung cancer.

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 ERß) in many of these tumors. Here we examine whether ERα and ERß 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 ERß alone was predictor of survival in NSCLC. However, when coupled with aromatase expression, higher ERß 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 ERß and aromatase indicated a markedly worse survival rate than that determined by aromatase alone. Expression of ERß 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.

Differential expression of anterior gradient gene AGR2 in prostate cancer.

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.