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.

The EndoPredict Gene-Expression Assay in Clinical Practice - Performance and Impact on Clinical Decisions.

The validated EndoPredict assay is a novel tool to predict the risk of metastases of patients with estrogen receptor positive, HER2 negative breast cancer treated with endocrine therapy alone. It has been designed to integrate genomic and clinical information and includes clinico-pathological factors such as tumor size and nodal status. The test is feasible in a decentral setting in molecular pathology laboratories. In this project, we investigated the performance of this test in clinical practice, and performed a retrospective evaluation of its impact on treatment decisions in breast cancer. During one year, EndoPredict assays from 167 patients could be successfully performed. For retrospective evaluation of treatment decisions, a questionnaire was sent to the clinical partner. Regarding the molecular EP class, samples from 56 patients (33.5%) had a low-risk, whereas 111 patients (66.5%) showed a high-risk gene profile. After integration of the clinicopathological factors the combined clinical and molecular score (EPclin) resulted in a low-risk group of 77 patients (46.4%), while 89 (53.6%) had a high risk EPclin score. The EPclin-based estimated median 10-year-risk for metastases with endocrine therapy alone was 11% for the whole cohort. The median handling time averaged three days (range: 0 to 11 days), 59.3% of the tests could be performed in three or less than three days. Comparison of pre- and post-test therapy decisions showed a change of therapy in 37.7% of patients. 16 patients (12.3%) had a change to an additional chemotherapy while 25.4% of patients (n = 33) changed to an endocrine therapy alone. In 73 patients (56.2%) no change of therapy resulted. In 6.1% of patients (n = 8), the patients did not agree to the recommendation of the tumor board. Our results show that the EndoPredict assay could be routinely performed in decentral molecular pathology laboratories and the results markedly change treatment decisions.

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.

Differential expression of histone deacetylases HDAC1, 2 and 3 in human breast cancer--overexpression of HDAC2 and HDAC3 is associated with clinicopathological indicators of disease progression.

BACKGROUND: In breast cancer, the role of epigenetic alterations including modifications of the acetylation status of histones in carcinogenesis has been an important research focus during the last years. An increased deacetylation of histones leads to increased cell proliferation, cell migration, angiogenesis and invasion. Class 1 histone deacetylases (HDAC) seem to be most important during carcinogenesis. METHODS: The immunhistochemical expression of HDAC1, 2 and 3 was analyzed on tissue microarrays (TMAs) from 238 patients with primary breast cancer. We analyzed the nuclear staining intensity (negative, weak, moderate, strong) as well as the percentage of positive tumor cells and calculated the immunoreactivity score (0-12). Expression was correlated with clinicopathological parameters and patient survival. RESULTS: In this cohort, we found a differential positive expression of HDAC1, HDAC2 and HDAC3. HDAC2 and HDAC3 expression was significantly higher in less differentiated tumors: HDAC2 (n=207), p<0.001 and HDAC3 (n=220), p<0.001 and correlated with negative hormone receptor status: HDAC2 (n=206), p=0.02 and HDAC3 (n=219), p=0.04. Additionally, a high HDAC2 expression was significantly associated with an overexpression of HER2 (n=203, p=0.005) and the presence of nodal metastasis (n=200, p=0.04).HDAC1 was highly expressed in hormone receptor positive tumors (n=203; p<0.001). CONCLUSION: As a conclusion, our results show that the class-1 HDAC isoenzymes 1, 2 and 3 are differentially expressed in breast cancer. HDAC2 and HDAC3 are strongly expressed in subgroups of tumor with features of a more aggressive tumor type.

Quantitative imaging of the tissue contrast agent [Gd(DTPA)]²â» in articular cartilage by laser ablation inductively coupled plasma mass spectrometry.

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is an emerging analytical technique in the generation of quantitative images of MR contrast agent distribution in thin tissue sections of articular cartilage. An analytical protocol is described that includes sample preparation by cryo-cutting of tissue sections, mass spectrometric measurements by LA-ICP-MS and quantification of gadolinium images by one-point calibration, standard addition method (employing matrix-matched laboratory standards) and isotope dilution analysis using highly enriched stable Gd-155 isotope (abundance 92 vs 14.8% in the [Gd(DTPA)]²â» contrast agent). The tissue contrast agent concentrations of [Gd(DTPA)]²â» in cartilage measured in this work are in agreement with findings obtained by magnetic resonance imaging and other analytical methodologies. The LA-ICP-MS imaging data also confirm the observation that the spatial distribution of [Gd(DTPA)]²â» in the near-equilibrium state is highly inhomogeneous across cartilage thickness with the highest concentration measured in superficial cartilage and a strong decrease toward the subchondral bone. In the present work, it is shown for the first time that LA-ICP-MS can be applied to validate the results from quantitative gadolinium-enhanced MRI technique of articular cartilage.

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.

Higher cytoplasmic and nuclear poly(ADP-ribose) polymerase expression in familial than in sporadic breast cancer.

Poly(ADP-ribose) polymerase 1 (PARP) is a key element of the single-base excision pathway for repair of DNA single-strand breaks. To compare the cytoplasmic and nuclear poly(ADP-ribose) expression between familial (BRCA1, BRCA2, or non BRCA1/2) and sporadic breast cancer, we investigated 39 sporadic and 39 familial breast cancer cases. The two groups were matched for hormone receptor status and human epidermal growth factor receptor 2 status. Additionally, they were matched by grading with a maximum difference of ±1 degree (e.g., G2 instead of G3). Cytoplasmic PARP (cPARP) expression was significantly higher in familial compared to sporadic breast cancer (P = 0.008, chi-squared test for trends) and a high nuclear PARP expression (nPARP) was significantly more frequently observed in familial breast cancer (64 %) compared with sporadic breast cancer (36 %) (P = 0.005, chi-squared test). The overall PARP expression was significantly higher in familial breast cancer (P = 0.042, chi-squared test). In familial breast cancer, a combination of high cPARP and high nPARP expression is the most common (33 %), whereas in sporadic breast cancer, a combination of low cPARP and intermediate nPARP expression is the most common (39 %). Our results show that the overall PARP expression in familial breast cancer is higher than in sporadic breast cancer which might suggest they might respond better to treatment with PARP inhibitors.

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.

Comparison of the RNA-based EndoPredict multigene test between core biopsies and corresponding surgical breast cancer sections.

AIM: This study compared the perfomance of the RNA-based EndoPredict multigene test on core biopsies and surgical breast cancer specimens and analysed the influence of biopsy-induced tissue injuries on the test result. METHODS: 80 formalin-fixed paraffin-embedded samples comprising paired biopsies and surgical specimens from 40 ER-positive, HER2-negative patients were evaluated. Total RNA was extracted and the EndoPredict score was determined. RESULTS: RNA yield was considerably lower in core biopsies, but sufficient to measure the assay in all samples. The EndoPredict score was highly correlated between paired samples (Pearson r=0.92), with an excellent concordance of classification into a low or high risk of metastasis (overall agreement 95%). CONCLUSIONS: The measurements are comparable between core biopsies and surgical sections, which suggest that the EndoPredict assay can be performed on core biopsy tissue. Inflammatory changes induced by presurgical biopsies had no significant effect on the RNA-based risk assessment in surgical specimens.

Decentral gene expression analysis for ER+/Her2- breast cancer: results of a proficiency testing program for the EndoPredict assay.

Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone-receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test-performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer.

Neoadjuvant chemotherapy and bevacizumab for HER2-negative breast cancer.

BACKGROUND: Bevacizumab, a monoclonal antibody against vascular endothelial growth factor A, has shown clinical efficacy in patients with human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer. We evaluated the efficacy, measured according to the rate of pathological complete response (absence of invasive and intraductal disease in the breast and the axillary lymph nodes), and the safety of adding bevacizumab to neoadjuvant chemotherapy in patients with early-stage breast cancer. METHODS: We randomly assigned 1948 patients with a median tumor size of 40 mm on palpation to receive neoadjuvant epirubicin and cyclophosphamide followed by docetaxel, with or without concomitant bevacizumab. Patients with untreated HER2-negative breast cancer were eligible if they had large tumors, hormone-receptor-negative disease, or hormone-receptor-positive disease with palpable nodes or positive findings on sentinel-node biopsy, and no increased cardiovascular or bleeding risk. RESULTS: Overall, the rates of pathological complete response were 14.9% with epirubicin and cyclophosphamide followed by docetaxel and 18.4% with epirubicin and cyclophosphamide followed by docetaxel plus bevacizumab (odds ratio with addition of bevacizumab, 1.29; 95% confidence interval, 1.02 to 1.65; P=0.04); the corresponding rates of pathological complete response were 27.9% and 39.3% among 663 patients with triple-negative tumors (P=0.003) and 7.8% and 7.7% among 1262 patients with hormone-receptor-positive tumors (P=1.00). Breast-conserving surgery was possible in 66.6% of the patients in both groups. The addition of bevacizumab, as compared with neoadjuvant therapy alone, was associated with a higher incidence of grade 3 or 4 toxic effects (febrile neutropenia, mucositis, the hand-foot syndrome, infection, and hypertension) but with a similar incidence of surgical complications. CONCLUSIONS: The addition of bevacizumab to neoadjuvant chemotherapy significantly increased the rate of pathological complete response among patients with HER2-negative early-stage breast cancer. Efficacy was restricted primarily to patients with triple-negative tumors, in whom the pathological complete response is considered to be a reliable predictor of long-term outcome. (Funded by Sanofi-Aventis and Roche, Germany; ClinicalTrials.gov number, NCT00567554.).

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.

Prediction of Response to Neoadjuvant Chemotherapy: New Biomarker Approaches and Concepts.

SUMMARY: About 10-25% of breast cancer patients achieve a pathologically confirmed complete response after neoadjuvant chemotherapy. Tissue samples of pretreatment core biopsies are a valuable resource for translational research aiming towards predictive biomarkers for selecting patients who are likely to benefit from neoadjuvant therapy. The German Breast Group (GBG) and the AGO-B Group (AGO = Working Group Gynecological Oncology) have extensive experience in conducting neoadjuvant clinical trials. Technologies as immunohistochemistry on tissue microarrays and standardized reverse transcription-polymerase chain reaction (RT-PCR) approaches on formalin-fixed paraffin-embedded samples allow high-throughput investigation of protein and mRNA biomarkers. With these approaches, we could demonstrate that molecular tumor subtypes and immunological infiltrates are valuable and independent predictors of therapy response. New biomarkers such as poly(ADPribose) polymerase (PARP) might be useful for the prediction of response to conventional and new targeted therapies. This review summarizes current research projects focusing on biomarker discovery in the neoadjuvant setting.

Androgen receptor expression in primary breast cancer and its predictive and prognostic value in patients treated with neoadjuvant chemotherapy.

The androgen receptor (AR) has been shown to be of potential prognostic importance in retrospective cohorts. We evaluated immunohistochemical AR expression on a tissue microarray of 673 core biopsies from primary breast cancer patients treated with neoadjuvant docetaxel/doxorubicin/cyclophosphamide (TAC) chemotherapy in the prospective GeparTrio phase-III trial. AR was detected in 53.2% of tumours. Lowest AR expression was detected in triple-negative breast cancers (TNBC) with 21.2%. Highest AR expression was observed in Luminal A-like tumours with 67%. In AR-positive tumours, pathological complete response (pCR) rate was 12.8% compared to 25.4% in AR-negative tumours (P < 0.0001). In multivariate analysis, AR independently predicted pCR (OR 1.86; 95% CI [1.16-2.79] P = 0.0086). Overall patients with an AR-positive tumour had a significant better disease-free (DFS) (AR-positive 78.9% vs. AR-negative 72.5%; log-rank P = 0.0329) and overall survival (OS) (88.8% vs. 82.7%; log-rank P = 0.0234) than those with AR-negative tumours. Stratified analysis revealed that in the TNBC subgroup, but not in the other subgroups defined by ER, PgR and HER2, AR expression predicted a better DFS (AR-positive 85.7% vs. AR-negative 65.5% log-rank P = 0.0544) and OS (95.2% vs. 76.2%; log-rank P = 0.0355). Within the non-pCR subgroup, AR positivity selected a group with a significant better DFS (P = 0.045) and OS (0.021) but not within the pCR group. Patients with an AR-negative tumour have a higher chance of achieving a pCR than those with an AR-positive one. But, patients with AR-positive tumours have a better survival especially if they did not achieve a pCR.

Cytoplasmic poly(adenosine diphosphate-ribose) polymerase expression is predictive and prognostic in patients with breast cancer treated with neoadjuvant chemotherapy.

PURPOSE: Poly(adenosine diphosphate-ribose) polymerase (PARP) plays a key role in DNA repair and cellular stress response. Inhibitors of PARP show promising clinical activity in metastatic, triple-negative or BRCA-mutated breast cancer. PATIENTS AND METHODS: We investigated cytoplasmic PARP (cPARP) and nuclear PARP (nPARP) expression by immunohistochemistry in 638 pretreatment biopsies from patients on the GeparTrio study and evaluated its predictive and prognostic value after neoadjuvant anthracycline/taxane-based chemotherapy. RESULTS: cPARP expression was high in 23.7%, intermediate in 50.9%, and negative in 25.4% of tumors. High cPARP expression was significantly correlated with nonlobular histology (P < .001), undifferentiated grade (P < .001), positive nodal status (P = .049), and negative hormone receptor (HR) status (P < .001) but not with human epidermal growth factor receptor 2 (HER2) status. Expression was high in 35.5% of triple-negative tumors, 24.6% of HER2-positive tumors, and 18.0% of HR-positive/HER2-negative tumors (P < .001). Pathologic complete response (pCR) rates were 26.5%, 19.1%, and 8.0% in patients with high, intermediate, or negative expression, respectively (P < .001). This predictive effect was most prominent in HR-positive tumors (P = .035) or HER2-negative tumors (P < .001). High cPARP expression was a negative, but not independent, prognostic factor for disease-free survival (DFS; P = .0025) and overall survival (OS; P = .0022). cPARP expression was highly prognostic in patients without a pCR (DFS, P < .001; OS, P < .001) and in patients with HR-positive tumors (DFS, P < .001; OS, P < .001). No such correlations were found for nPARP expression. CONCLUSION: High cPARP expression correlates with aggressive tumor pattern and predicts high sensitivity to neoadjuvant taxane/anthracycline-based chemotherapy but also unfavorable long-term prognosis. As a potential target for PARP inhibitors, cPARP-positive breast cancer might become a new, clinically relevant entity.

Novel theranostic opportunities offered by characterization of altered membrane lipid metabolism in breast cancer progression.

Activation of lipid metabolism is an early event in carcinogenesis and a central hallmark of many cancers. However, the precise molecular composition of lipids in tumors remains generally poorly characterized. The aim of the present study was to analyze the global lipid profiles of breast cancer, integrate the results to protein expression, and validate the findings by functional experiments. Comprehensive lipidomics was conducted in 267 human breast tissues using ultraperformance liquid chromatography/ mass spectrometry. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, such as palmitate-containing phosphatidylcholines, were increased in tumors as compared with normal breast tissues. These lipids were associated with cancer progression and patient survival, as their concentration was highest in estrogen receptor-negative and grade 3 tumors. In silico transcriptomics database was utilized in investigating the expression of lipid metabolism related genes in breast cancer, and on the basis of these results, the expression of specific proteins was studied by immunohistochemistry. Immunohistochemical analyses showed that several genes regulating lipid metabolism were highly expressed in clinical breast cancer samples and supported also the lipidomics results. Gene silencing experiments with seven genes [ACACA (acetyl-CoA carboxylase α), ELOVL1 (elongation of very long chain fatty acid-like 1), FASN (fatty acid synthase), INSIG1 (insulin-induced gene 1), SCAP (sterol regulatory element-binding protein cleavage-activating protein), SCD (stearoyl-CoA desaturase), and THRSP (thyroid hormone-responsive protein)] indicated that silencing of multiple lipid metabolism-regulating genes reduced the lipidomic profiles and viability of the breast cancer cells. Taken together, our results imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment.

Quantitative determination of estrogen receptor, progesterone receptor, and HER2 mRNA in formalin-fixed paraffin-embedded tissue--a new option for predictive biomarker assessment in breast cancer.

The development of optimized therapy strategies against malignant tumors is critically dependent on the assessment of tissue-based biomarkers in routine diagnostic tissue samples. We investigated a novel, fully automated, and xylene-free method for RNA isolation and biomarker determination using formalin-fixed paraffin-embedded (FFPE) tissue. The aim was to show that this approach is feasible and gives results that are comparable to the current gold standards. Expression of the breast cancer biomarkers ESR1, PGR, and HER2 was measured in a total of 501 FFPE tissue samples from 167 breast carcinomas, which had been stored for up to 21 years. Total RNA was extracted from tissue sections and biomarker expression was measured by kinetic RT-PCR (RT-kPCR). The results of the new method were compared with immunohistochemistry as the current gold standard.RNA was successfully isolated from all samples, with a mean yield of 1.4 µg/sample and fragment lengths of at least 150 bp in 99% of samples. RT-kPCR analysis of ESR1, PGR, and HER2 was possible in all samples. Comparing RT-kPCR results with standard IHC, we found a good concordance for ESR1 (agreement: 98.4%), PGR (84.4%), and HER2 (89.8%). We observed a low section-to-section variability of kPCR results for all 3 biomarkers (root of mean squared errors: 0.2 to 0.5 Ct values). The new approach is a reliable high-throughput instrument for standardized testing of biomarkers in clinical routine and for research studies on archived FFPE material up to 21 years old. For the assessment of ESR1, PGR, and HER2 the results are comparable to the current gold-standard.

Genome-wide gene expression profiling of formalin-fixed paraffin-embedded breast cancer core biopsies using microarrays.

The routine workflow for invasive cancer diagnostics includes biopsy processing by formalin fixation and paraffin embedding. It has been shown only recently that this kind of sample can be used for gene expression analysis with microarrays. To support this view, the authors conducted a microarray study using formalin-fixed paraffin-embedded (FFPE) core needle biopsies from breast cancers. Typically, for the 3'-biased chip type that was used, the probe sets interrogate sequences near the poly-A-tail of the transcripts, and this kind of probe turned out to be suitable to measure RNA levels in FFPE biopsies. For ER and HER2, the authors observed strong correlations between RNA levels and protein expression (p = 0.000003 and p = 0.0022). ER and HER2 classification of the biopsies by the RNA levels was feasible with high sensitivity and specificity (AUROC = 0.93 and AUROC = 0.96). Furthermore, a signature of 346 genes was identified that correlated with ER and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 63%) could be confirmed by analysis of gene expression data from frozen tissues. The findings support the notion that clinically relevant information can be gained from microarray analyses of FFPE cancer biopsies. This opens new opportunities for biomarker detection studies and the integration of microarrays into the workflow of cancer diagnostics.

Down-regulation of the antigen processing machinery is linked to a loss of inflammatory response in colorectal cancer.

Antitumor inflammatory response is known to inhibit tumor growth in colorectal carcinoma. The density and functionality of tumor-infiltrating lymphocytes (TIL) is regulated by the antigen processing machinery through regulator proteins such as transporters associated with antigen processing (TAP) and major histocompatibility complex (MHC) class I antigen. We aimed to investigate the in vivo association of those factors and their impact on prognosis in colorectal cancer. TAP1, TAP2 and MHC class I antigen expression, inflammatory infiltrate and TIL (CD4(+), CD8(+), and CD20(+)) were assessed by immunohistochemistry in 336 sporadic colorectal carcinomas. The factors were correlated with each other and with clinic-pathological parameters and patient outcome. We found TAP1 and TAP2 expression to be significantly associated with MHC class I antigen expression (TAP1: r = 0.363, P < .001; TAP2: r = 0.393, P < .001). Increased density of CD8(+) TIL was predominantly found in TAP1, TAP2 and MHC class I antigen-positive cases. Increased density of CD4(+) TIL was linked with TAP1 and TAP2, but not with MHC class I antigen. High CD4(+) and CD8(+) cell count but not TAP1, TAP2 and MHC class I antigen expression had favorable prognostic impact in colorectal cancer (P = .003 and P = .003, respectively). In conclusion, our data show that the expression of key components of the antigen processing machinery is tightly linked to the density of TIL, which are positive prognostic factors in colorectal cancer in vivo. This implies that modulation of these factors may help to enhance antitumor inflammatory response which in turn may improve patient prognosis.