Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism.

Molecular subtyping of breast cancer is necessary for therapy selection and mandatory for all breast cancer patients. Metabolic alterations are considered a hallmark of cancer and several metabolic drugs are currently being investigated in clinical trials. However, the dependence of metabolic alterations on breast cancer subtypes has not been investigated on -omics scale. Thus, 204 estrogen receptor positive (ER+) and 67 estrogen receptor negative (ER-) breast cancer tissues were investigated using GC-TOFMS based metabolomics. 19 metabolites were detected as altered in a predefined training set (2/3 of tumors) and could be validated in a predefined validation set (1/3 of tumors). The metabolite changes included increases in beta-alanine, 2-hydroyglutarate, glutamate, xanthine and decreases in glutamine in the ER- subtype. Beta-alanine demonstrated the strongest change between ER- and ER+ breast cancer (fold change=2.4, p=1.5E-20). In a correlation analysis with genome-wide expression data in a subcohort of 154 tumors, we found a strong negative correlation (Spearman R=-0.62) between beta-alanine and 4-aminobutyrate aminotransferase (ABAT). Immunohistological analysis confirmed down-regulation of the ABAT protein in ER- breast cancer. In a Kaplan-Meier analysis of a large external expression data set, the ABAT transcript was demonstrated to be a positive prognostic marker for breast cancer (HR=0.6, p=3.2E-15). BIOLOGICAL SIGNIFICANCE: It is well-known for more than a decade that breast cancer exhibits distinct gene expression patterns depending on the molecular subtype defined by estrogen receptor (ER) and HER2 status. Here, we show that breast cancer exhibits distinct metabolomics patterns depending on ER status. Our observation supports the current view of ER+ breast cancer and ER- breast as different diseases requiring different treatment strategies. Metabolic drugs for cancer including glutaminase inhibitors are currently under development and tested in clinical trials. We found glutamate enriched and glutamine reduced in ER- breast cancer compared to ER+ breast cancer and compared to normal breast tissues. Thus, metabolomics analysis highlights the ER- subtype as a preferential target for glutaminase inhibitors. For the first time, we report on a regulation of beta-alanine catabolism in cancer. In breast cancer, ABAT transcript expression was variable and correlated with ER status. Low ABAT transcript expression was associated with low ABAT protein expression and high beta-alanine concentration. In a large external microarray cohort, low ABAT expression shortened recurrence-free survival in breast cancer, ER+ breast cancer and ER- breast cancer.

Ki67 measured after neoadjuvant chemotherapy for primary breast cancer.

PURPOSE: The value of Ki67 measured on residual disease after neoadjuvant chemotherapy is not sufficiently described. EXPERIMENTAL DESIGN: Participants of the GeparTrio study with primary breast cancer randomly received neoadjuvant response-guided [8 cycles TAC (docetaxel/doxorubicin/cyclophosphamide) in responding and TAC-NX (vinorelbine/capecitabine) in nonresponding patients] or conventional (6 cycles TAC) chemotherapy according to interim response assessment. Ki-67 levels were centrally measured immunohistochemically after neoadjuvant treatment if tumor tissue was available. Here, we analyze 1,151 patients having a pathologic complete response (pCR; n, 484), or residual disease with low (0-15%), intermediate (15.1-35%), or high (35.1-100%) posttreatment Ki67 levels in 488, 77, and 102 patients, respectively. RESULTS: Patients with high posttreatment Ki67 levels showed higher risk for disease relapse (P < 0.0001) and death (P < 0.0001) compared with patients with low or intermediate Ki67 levels. Patients with low Ki67 levels showed a comparable outcome to patients with a pCR (P = 0.211 for disease-free and P = 0.779 for overall survival). Posttreatment Ki67 levels provided more prognostic information than pretreatment Ki67 levels or changes of Ki67 from pre- to posttreatment. Information on pCR plus posttreatment Ki67 levels surmount the prognostic information of pCR alone in hormone-receptor-positive disease [hazard ratios (HR), 1.82-5.88] but not in hormone-receptor-negative disease (HR: 0.61-1.73). Patients with conventional and response-guided treatment did not show a different distribution of posttreatment Ki67 (P = 0.965). CONCLUSIONS: Posttreatment Ki67 levels provide prognostic information for patients with hormone-receptor-positive breast cancer and residual disease after neoadjuvant chemotherapy. Levels were not prognostic for outcome after response-guided chemotherapy. High posttreatment Ki67 indicates the need for innovative postneoadjuvant treatments.

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test.

BACKGROUND: EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory. METHODS: Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability. RESULTS: PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/µl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer's laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units. CONCLUSIONS: The EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.

Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study.

BACKGROUND: Changes in energy metabolism of the cells are common to many kinds of tumors and are considered a hallmark of cancer. Gas chromatography followed by time-of-flight mass spectrometry (GC-TOFMS) is a well-suited technique to investigate the small molecules in the central metabolic pathways. However, the metabolic changes between invasive carcinoma and normal breast tissues were not investigated in a large cohort of breast cancer samples so far. RESULTS: A cohort of 271 breast cancer and 98 normal tissue samples was investigated using GC-TOFMS-based metabolomics. A total number of 468 metabolite peaks could be detected; out of these 368 (79%) were significantly changed between cancer and normal tissues (p<0.05 in training and validation set). Furthermore, 13 tumor and 7 normal tissue markers were identified that separated cancer from normal tissues with a sensitivity and a specificity of >80%. Two-metabolite classifiers, constructed as ratios of the tumor and normal tissues markers, separated cancer from normal tissues with high sensitivity and specificity. Specifically, the cytidine-5-monophosphate / pentadecanoic acid metabolic ratio was the most significant discriminator between cancer and normal tissues and allowed detection of cancer with a sensitivity of 94.8% and a specificity of 93.9%. CONCLUSIONS: For the first time, a comprehensive metabolic map of breast cancer was constructed by GC-TOF analysis of a large cohort of breast cancer and normal tissues. Furthermore, our results demonstrate that spectrometry-based approaches have the potential to contribute to the analysis of biopsies or clinical tissue samples complementary to histopathology.

Integration of metabolomics and expression of glycerol-3-phosphate acyltransferase (GPAM) in breast cancer-link to patient survival, hormone receptor status, and metabolic profiling.

Changes in lipid metabolism are an important but not well-characterized hallmark of cancer. On the basis of our recent findings of lipidomic changes in breast cancer, we investigated glycerol-3-phosphate acyltransferase (GPAM), a key enzyme in the lipid biosynthesis of triacylglycerols and phospholipids. GPAM protein expression was evaluated and linked to metabolomic and lipidomic profiles in a cohort of human breast carcinomas. In addition, GPAM mRNA expression was analyzed using the GeneSapiens in silico transcriptiomics database. High cytoplasmic GPAM expression was associated with hormone receptor negative status (p = 0.013). On the protein (p = 0.048) and mRNA (p = 0.001) levels, increased GPAM expression was associated with a better overall survival. Metabolomic analysis by GC-MS showed that sn-glycerol-3-phosphate, the substrate of GPAM, was elevated in breast cancer compared to normal breast tissue. LC-MS based lipidomic analysis identified significantly higher levels of phospholipids, especially phosphatidylcholines in GPAM protein positive tumors. In conclusion, our results suggest that GPAM is expressed in human breast cancer with associated changes in the cellular metabolism, in particular an increased synthesis of phospholipids, the major structural component of cellular membranes.

Vascular CXCR4 expression - a novel antiangiogenic target in gastric cancer?

BACKGROUND: G-protein-coupled receptors (GPCRs) are prime candidates for novel cancer prevention and treatment strategies. We searched for differentially expressed GPCRs in node positive gastric carcinomas. METHODOLOGY/PRINCIPAL FINDINGS: Differential expression of GPCRs in three node positive vs. three node negative intestinal type gastric carcinomas was analyzed by gene array technology. The candidate genes CXCL12 and its receptor CXCR4 were validated by real-time reverse-transcription polymerase chain reaction in an independent set of 37 gastric carcinomas. Translation was studied by immunohistochemistry in 347 gastric carcinomas using tissue microarrays as well as in 61 matching lymph node metastases. Protein expression was correlated with clinicopathological patient characteristics and survival. 52 GPCRs and GPCR-related genes were up- or down-regulated in node positive gastric cancer, including CXCL12. Differential expression of CXCL12 was confirmed by RT-PCR and correlated with local tumour growth. CXCL12 immunopositivity was negatively associated with distant metastases and tumour grade. Only 17% of gastric carcinomas showed CXCR4 immunopositive tumour cells, which was associated with higher local tumour extent. 29% of gastric carcinomas showed CXCR4 positive tumour microvessels. Vascular CXCR4 expression was significantly associated with higher local tumour extent as well as higher UICC-stages. When expressing both, CXCL12 in tumour cells and CXCR4 in tumour microvessels, these tumours also were highly significantly associated with higher T- and UICC-stages. Three lymph node metastases revealed vascular CXCR4 expression while tumour cells completely lacked CXCR4 in all cases. The expression of CXCL12 and CXCR4 had no impact on patient survival. CONCLUSIONS/SIGNIFICANCE: Our results substantiate the significance of GPCRs on the biology of gastric carcinomas and provide evidence that the CXCL12-CXCR4 pathway might be a novel promising antiangiogenic target for the treatment of gastric carcinomas.

Prognostic significance of Dicer expression in ovarian cancer-link to global microRNA changes and oestrogen receptor expression.

MicroRNA (miRNA) deregulation is a hallmark of human cancer. However, the mechanisms underlying miRNA alteration and the specific role of proteins involved in miRNA processing remains to be elucidated. Dicer is a key enzyme in the miRNA processing pathway that is essential for the production of mature miRNAs from their precursors. We tested the hypothesis that Dicer has biological and clinical relevance in ovarian cancer, using a range of methods including in vitro manipulation of Dicer expression. We observed down-regulation of Dicer in a subgroup of ovarian carcinomas, and found that decreased Dicer expression correlates significantly with reduced patient survival in serous cancers and advanced disease stages. Moreover, microarray and functional analysis suggest that reduced Dicer expression is connected with a global down-regulation of the microRNAome and with gene expression changes, particularly reduced expression of oestrogen receptor (ER) mRNA and protein in tumour tissue and in cell culture. Our data suggest a common mechanism for miRNAs changes by alterations in the basic machinery controlling miRNA biogenesis, of which Dicer is a central enzyme. These alterations of miRNA processing are of prognostic value and may play a role in the molecular pathogenesis of ovarian carcinoma and, possibly, other tumours. Knowledge of these molecular pathways may help toward new targeted therapeutic approaches for ovarian cancer.

Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy.

INTRODUCTION: Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression might lead to a different clinical behavior of HR+/HER2+ co-expressing and HR+/HER2- tumors and whether subgroups of triple negative tumors might be identified by the help of Ki67 labeling index, cytokeratin 5/6 (CK5/6), as well as cyclooxygenase-2 (COX-2), and Y-box binding protein 1 (YB-1) expression. METHODS: Expression analysis was performed using immunohistochemistry and silver-enhanced in situ hybridization on tissue microarrays (TMAs) of pretherapeutic core biopsies. RESULTS: pCR rates were significantly different between the biology-based tumor types (P = 0.044) with HR+/HER2+ and HR-/HER2- tumors having higher pCR rates than HR+/HER2- tumors. Ki67 labeling index, confirmed as significant predictor of pCR in the whole cohort (P = 0.001), identified HR-/HER- (triple negative) carcinomas with a higher chance for a pCR (P = 0.006). Biology-based tumor type (P = 0.046 for HR+/HER2+ vs. HR+/HER2-), Ki67 labeling index (P = 0.028), and treatment arm (P = 0.036) were independent predictors of pCR in a multivariate model. DFS was different in the biology-based tumor types (P < 0.0001) with HR+/HER2- and HR+/HER2+ tumors having the best prognosis and HR-/HER2+ tumors showing the worst outcome. Biology-based tumor type was an independent prognostic factor for DFS in multivariate analysis (P < 0.001). CONCLUSIONS: Our data demonstrate that a biology-based breast cancer classification using estrogen receptor (ER), progesterone receptor (PgR), and HER2 bears independent predictive and prognostic potential. The HR+/HER2+ co-expressing carcinomas emerged as a group of tumors with a good response rate to neoadjuvant chemotherapy and a favorable prognosis. HR+/HER2- tumors had a good prognosis irrespective of a pCR, whereas patients with HR-/HER- and HR-/HER+ tumors, especially if they had not achieved a pCR, had an unfavorable prognosis and are in need of additional treatment options.

Expression of multidrug resistance-associated protein 1 in invasive ovarian carcinoma: implication for prognosis.

AIMS: Multidrug resistance is a major impediment in chemotherapeutic treatment of ovarian carcinoma patients. The aim of this study was to investigate the expression of multidrug resistance-associated protein 1 (MRP1) and to assess the possible associations with clinicopathological variables and patient outcome in primary ovarian carcinoma. METHODS AND RESULTS: Tumour specimens from 129 patients were obtained before chemotherapy and analysed by immunohistochemistry on tissue microarrays, and by real-time reverse transcriptase-polymerase chain reaction on RNA extracted from formalin-fixed paraffin-embedded tissue specimens using a new technique. Significantly increased MRP1 protein expression was observed in high-grade tumours (P = 0.005) and advanced International Federation of Gynaecology and Obstetrics stages (P = 0.036). On univariate Kaplan-Meier analysis, patients with higher expression of MRP1 protein had significantly decreased overall survival (P = 0.006). On multivariate Cox regression analysis, MRP1 protein expression retained its significance as an independent negative prognostic marker for overall survival (hazard ratio = 6.52, P = 0.003). Furthermore, MRP1 expression correlated with topoisomerase IIalpha expression both at mRNA and protein level (P < 0.001 and P = 0.023, respectively). CONCLUSION: In summary, in patients with primary ovarian cancer, overexpression of MRP1 is an adverse marker for patient outcome and cancer aggressiveness. Our data provide a translational basis for further clinical studies on the predictive value of MRP1 expression for response to chemotherapy.

A prognostic gene expression index in ovarian cancer - validation across different independent data sets.

Ovarian carcinoma has the highest mortality rate among gynaecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300-gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p = 0.0087). In a second validation step, the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p = 0.0063). In multivariate analysis, the OPI was independent of the post-operative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8-23.5, p = 0.0049) and 1.9 (Duke cohort, CI 1.2-3.0, p = 0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimized assessment of the prognosis of platinum-taxol-treated ovarian cancer. As traditional treatment options are limited, this analysis may be able to optimize clinical management and to identify those patients who would be candidates for new therapeutic strategies.

Topoisomerase IIalpha mRNA and protein expression in ovarian carcinoma: correlation with clinicopathological factors and prognosis.

Topoisomerase IIalpha (Top IIalpha) is a nuclear enzyme that plays a central role in DNA metabolism, and is a molecular target for a variety of chemotherapeutic agents. Top IIalpha has recently gained attention as a biomarker for therapy response and patient survival. In this study, we attempted to assess the feasibility of measuring Top IIalpha gene expression in RNA, isolated from archival formalin-fixed paraffin-embedded tissue specimens, which are used routinely in pathology laboratories. We have employed a new technique on the basis of magnetic particles' separation and purification of nucleic acids, and evaluated both protein and mRNA expressions from the same routinely processed tissue blocks. We investigated the expression of Top IIalpha mRNA and protein by real-time reverse transcription polymerase chain reaction and immunohistochemistry, in a cohort of 133 primary ovarian carcinomas, and evaluated the association between Top IIalpha expression and clincopathological variables as well as patient outcome. Elevated Top IIalpha mRNA expression was observed in high-grade tumors (P=0.003) and advanced stage disease (P=0.011). In univariate Kaplan-Meier analysis, patients with higher expression of Top IIalpha nuclear protein had a significantly decreased overall survival (P=0.045). Interestingly, we detected cytoplasmic protein expression of Top IIalpha in a subset of samples. Cytoplasmic expression of Top IIalpha was associated with the expression of chromosomal region maintenance/exportin 1 (CRM1)-a nuclear export protein (P=0.008). Our study suggests that Top IIalpha overexpression is involved in the progression of ovarian cancer in a subset of the patients. Our results encourage the further evaluation of the prognostic and predictive values of Top IIalpha expression in ovarian carcinoma, which might help to assess the patients' risk profile, and the planning of an individualized therapy.