Metabolic biomarkers for response to PI3K inhibition in basal-like breast cancer

INTRODUCTION: The phosphatidylinositol 3-kinase (PI3K) pathway is frequently activated in cancer cells through numerous mutations and epigenetic changes. The recent development of inhibitors targeting different components of the PI3K pathway may represent a valuable treatment alternative. However, predicting efficacy of these drugs is challenging, and methods for therapy monitoring are needed. Basal-like breast cancer (BLBC) is an aggressive breast cancer subtype, frequently associated with PI3K pathway activation. The objectives of this study were to quantify the PI3K pathway activity in tissue sections from xenografts representing basal-like and luminal-like breast cancer before and immediately after treatment with PI3K inhibitors, and to identify metabolic biomarkers for treatment response. METHODS: Tumor-bearing animals (n = 8 per treatment group) received MK-2206 (120 mg/kg/day) or BEZ235 (50 mg/kg/day) for 3 days. Activity in the PI3K/Akt/mammalian target of rapamycin pathway in xenografts and human biopsies was evaluated using a novel method for semiquantitative assessment of Akt(ser473 )phosphorylation. Metabolic changes were assessed by ex vivo high-resolution magic angle spinning magnetic resonance spectroscopy. RESULTS: Using a novel dual near-infrared immunofluorescent imaging method, basal-like xenografts had a 4.5-fold higher baseline level of pAkt(ser473 )than luminal-like xenografts. Following treatment, basal-like xenografts demonstrated reduced levels of pAkt(ser473 )and decreased proliferation. This correlated with metabolic changes, as both MK-2206 and BEZ235 reduced lactate concentration and increased phosphocholine concentration in the basal-like tumors. BEZ235 also caused increased glucose and glycerophosphocholine concentrations. No response to treatment or change in metabolic profile was seen in luminal-like xenografts. Analyzing tumor sections from five patients with BLBC demonstrated that two of these patients had an elevated pAkt(ser473 )level. CONCLUSION: The activity of the PI3K pathway can be determined in tissue sections by quantitative imaging using an antibody towards pAkt(ser473). Long-term treatment with MK-2206 or BEZ235 resulted in significant growth inhibition in basal-like, but not luminal-like, xenografts. This indicates that PI3K inhibitors may have selective efficacy in basal-like breast cancer with increased PI3K signaling, and identifies lactate, phosphocholine and glycerophosphocholine as potential metabolic biomarkers for early therapy monitoring. In human biopsies, variable pAkt(ser473 )levels were observed, suggesting heterogeneous PI3K signaling activity in BLBC

Impact of Freezing Delay Time on Tissue Samples for Metabolomic Studies

Introduction: Metabolic profiling of intact tumor tissue by high resolution magic angle spinning (HR MAS) MR spectroscopy (MRS) provides important biological information possibly useful for clinical diagnosis and development of novel treatment strategies. However, generation of high-quality data requires that sample handling from surgical resection until analysis is performed using systematically validated procedures. In this study, we investigated the effect of postsurgical freezing delay time on global metabolic profiles and stability of individual metabolites in intact tumor tissue.Materials and methods: Tumor tissue samples collected from two patient-derived breast cancer xenograft models (n = 3 for each model) were divided into pieces that were snap-frozen in liquid nitrogen at 0, 15, 30, 60, 90, and 120 min after surgical removal. In addition, one sample was analyzed immediately, representing the metabolic profile of fresh tissue exposed neither to liquid nitrogen nor to room temperature. We also evaluated the metabolic effect of prolonged spinning during the HR MAS experiments in biopsies from breast cancer patients (n = 14). All samples were analyzed by proton HR MAS MRS on a Bruker Avance DRX600 spectrometer, and changes in metabolic profiles were evaluated using multivariate analysis and linear mixed modeling.Results: Multivariate analysis showed that the metabolic differences between the two breast cancer models were more prominent than variation caused by freezing delay time. No significant changes in levels of individual metabolites were observed in samples frozen within 30 min of resection. After this time point, levels of choline increased, whereas ascorbate, creatine, and glutathione (GS) levels decreased. Freezing had a significant effect on several metabolites but is an essential procedure for research and biobank purposes. Furthermore, four metabolites (glucose, glycine, glycerophosphocholine, and choline) were affected by prolonged HR MAS experiment time possibly caused by physical release of metabolites caused by spinning or due to structural degradation processes.Conclusion: The MR metabolic profiles of tumor samples are reproducible and robust to variation in postsurgical freezing delay up to 30 min

Impact of school-based malaria case management on school attendance, health and education outcomes: a cluster randomised trial in southern Malawi.

Introduction: Evidence indicates children who suffer from ill-health are less likely to attend or complete schooling. Malaria is an important cause of morbidity and mortality in school-age children. However, they are less likely to receive malaria treatment at health facilities and evidence for how to improve schoolchildren's access to care is limited. This study aimed to evaluate the impact of a programme of school-based malaria case management on schoolchildren's attendance, health and education. Methods: A cluster randomised controlled trial was conducted in 58 primary schools in Zomba District, Malawi, 2011-2015. The intervention, implemented in 29 randomly selected schools, provided malaria rapid diagnostic tests and artemisinin-based combination therapy to diagnose and treat uncomplicated malaria as part of basic first aid kits known as 'Learner Treatment Kits' (LTK). The primary outcome was school attendance, assessed through teacher-recorded daily attendance registers and independent periodic attendance spot checks. Secondary outcomes included prevalence of Plasmodium spp infection, anaemia, educational performance, self-reported child well-being and health-seeking behaviour. A total of 9571 children from standards 1-7 were randomly selected for assessment of school attendance, with subsamples assessed for the secondary outcomes. Results: Between November 2013 and March 2015, 97 trained teachers in 29 schools provided 32 685 unique consultations. Female schoolchildren were significantly more likely than male to seek a consultation (unadjusted OR=1.78 (95% CI 1.58 to 2.00). No significant intervention effect was observed on the proportion of child-days recorded as absent in teacher registers (n=9017 OR=0.90 (95% CI 0.77 to 1.05), p=0.173) or of children absent during random school visits-spot checks (n=5791 OR=1.09 (95% CI 0.87 to 1.36), p=0.474). There was no significant impact on child-reported well-being, prevalence of Plasmodium spp, anaemia or education scores. Conclusion: Despite high community demand, the LTK programme did not reduce schoolchildren's absenteeism or improve health or education outcomes in this study setting. Trial registration number: ClinicalTrials.gov NCT02213211

Merging transcriptomics and metabolomics - advances in breast cancer profiling

Background Combining gene expression microarrays and high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) of the same tissue samples enables comparison of the transcriptional and metabolic profiles of breast cancer. The aim of this study was to explore the potential of combining these two different types of information. Methods Breast cancer tissue from 46 patients was analyzed by HR MAS MRS followed by gene expression microarrays. Two strategies were used to combine the gene expression and metabolic data; first using multivariate analyses to identify different groups based on gene expression and metabolic data; second correlating levels of specific metabolites to transcripts to suggest new hypotheses of connections between metabolite levels and the underlying biological processes. A parallel study was designed to address experimental issues of combining microarrays and HR MAS MRS. Results In the first strategy, using the microarray data and previously reported molecular classification methods, the majority of samples were classified as luminal A. Three subgroups of luminal A tumors were identified based on hierarchical clustering of the HR MAS MR spectra. The samples in one of the subgroups, designated A2, showed significantly lower glucose and higher alanine levels than the other luminal A samples, suggesting a higher glycolytic activity in these tumors. This group was also enriched for genes annotated with Gene Ontology (GO) terms related to cell cycle and DNA repair. In the second strategy, the correlations between concentrations of myo-inositol, glycine, taurine, glycerophosphocholine, phosphocholine, choline and creatine and all transcripts in the filtered microarray data were investigated. GO-terms related to the extracellular matrix were enriched among the genes that correlated the most to myo-inositol and taurine, while cell cycle related GO-terms were enriched for the genes that correlated the most to choline. Additionally, a subset of transcripts was identified to have slightly altered expression after HR MAS MRS and was therefore removed from all other analyses. Conclusions Combining transcriptional and metabolic data from the same breast carcinoma sample is feasible and may contribute to a more refined subclassification of breast cancers as well as reveal relations between metabolic and transcriptional levels. See Commentary: http://www.biomedcentral.com/1741-7015/8/7

Reconstructing cancer genomes from paired-end sequencing data

<p>Abstract</p> <p>Background</p> <p>A cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or "blocks" of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data.</p> <p>Results</p> <p>By aligning paired reads from a cancer genome - and a matched germline genome, if available - to the human reference genome, we derive: (i) a partition of the reference genome into intervals; (ii) adjacencies between these intervals in the cancer genome; (iii) an estimated copy number for each interval. We formulate the Copy Number and Adjacency Genome Reconstruction Problem of determining the cancer genome as a sequence of the derived intervals that is consistent with the measured adjacencies and copy numbers. We design an efficient algorithm, called Paired-end Reconstruction of Genome Organization (PREGO), to solve this problem by reducing it to an optimization problem on an interval-adjacency graph constructed from the data. The solution to the optimization problem results in an Eulerian graph, containing an alternating Eulerian tour that corresponds to a cancer genome that is consistent with the sequencing data. We apply our algorithm to five ovarian cancer genomes that were sequenced as part of The Cancer Genome Atlas. We identify numerous rearrangements, or structural variants, in these genomes, analyze reciprocal vs. non-reciprocal rearrangements, and identify rearrangements consistent with known mechanisms of duplication such as tandem duplications and breakage/fusion/bridge (B/F/B) cycles.</p> <p>Conclusions</p> <p>We demonstrate that PREGO efficiently identifies complex and biologically relevant rearrangements in cancer genome sequencing data. An implementation of the PREGO algorithm is available at <url>http://compbio.cs.brown.edu/software/</url>.</p

Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy

<p>Abstract</p> <p>Background</p> <p>Today's clinical diagnostic tools are insufficient for giving accurate prognosis to breast cancer patients. The aim of our study was to examine the tumor metabolic changes in patients with locally advanced breast cancer caused by neoadjuvant chemotherapy (NAC), relating these changes to clinical treatment response and long-term survival.</p> <p>Methods</p> <p>Patients (n = 89) participating in a randomized open-label multicenter study were allocated to receive either NAC as epirubicin or paclitaxel monotherapy. Biopsies were excised pre- and post-treatment, and analyzed by high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The metabolite profiles were examined by paired and unpaired multivariate methods and findings of important metabolites were confirmed by spectral integration of the metabolite peaks.</p> <p>Results</p> <p>All patients had a significant metabolic response to NAC, and pre- and post-treatment spectra could be discriminated with 87.9%/68.9% classification accuracy by paired/unpaired partial least squares discriminant analysis (PLS-DA) (<it>p </it>< 0.001). Similar metabolic responses were observed for the two chemotherapeutic agents. The metabolic responses were related to patient outcome. Non-survivors (< 5 years) had increased tumor levels of lactate (<it>p </it>= 0.004) after treatment, while survivors (≥ 5 years) experienced a decrease in the levels of glycine (<it>p </it>= 0.047) and choline-containing compounds (<it>p </it>≤ 0.013) and an increase in glucose (<it>p </it>= 0.002) levels. The metabolic responses were not related to clinical treatment response.</p> <p>Conclusions</p> <p>The differences in tumor metabolic response to NAC were associated with breast cancer survival, but not to clinical response. Monitoring metabolic responses to NAC by HR MAS MRS may provide information about tumor biology related to individual prognosis.</p

Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models

<p>Abstract</p> <p>Background</p> <p>Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood.</p> <p>Methods</p> <p>The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS).</p> <p>The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses.</p> <p>The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer.</p> <p>Results</p> <p>In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (<it>CHKA</it>, <it>CHKB</it>) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (<it>PLA2G4A</it>) and phospholipase B1 (<it>PLB1</it>) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer.</p> <p>Conclusions</p> <p>The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.</p

Synthesis of 14C-labelled polystyrene nanoplastics for environmental studies

AbstractAvailable analytical methods cannot detect nanoplastics at environmentally realistic concentrations in complex matrices such as biological tissues. Here, we describe a one-step polymerization method, allowing direct radiolabeling of a sulfonate end-capped nano-sized polystyrene (nPS; proposed as a model nanoplastic particle representing negatively charged nanoplastics). The method, which produces nanoplastics trackable in simulated environmental settings which have already been used to investigate the behavior of a nanoplastic in vivo in a bivalve mollusc, was developed, optimized and successfully applied to synthesis of 14C-labeled nPS of different sizes. In addition to a description of the method of synthesis, we describe the details for quantification, mass balance and recovery of the labelled particles from complex matrices offered by the radiolabelling approach. The radiolabeling approach described here, coupled to use of a highly sensitive autoradiographic method for monitoring nanoplastic body burden and distributions, may provide a valuable procedure for investigating the environmental pathways followed by negatively charged nanoplastics at low predicted environmental concentrations. Whether the behaviour of the synthetic nPS manufactured here, synthesised using a very common inititator, represents that of manufactured nPS found in the environment, remains to be seen.</jats:p

Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype

<p>Abstract</p> <p>Background</p> <p>Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has been demonstrated to be useful for molecular profiling of common solid tumors. Using recently developed MALDI matrices for lipid profiling, we evaluated whether direct tissue MALDI MS analysis on proteins and lipids may classify human breast cancer samples according to the intrinsic subtype.</p> <p>Methods</p> <p>Thirty-four pairs of frozen, resected breast cancer and adjacent normal tissue samples were analyzed using histology-directed, MALDI MS analysis. Sinapinic acid and 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument.</p> <p>Results</p> <p>Protein and lipid profiles distinguish cancer from adjacent normal tissue samples with the median prediction accuracy of 94.1%. Luminal, HER2+, and triple-negative tumors demonstrated different protein and lipid profiles, as evidenced by permutation <it>P </it>values less than 0.01 for 0.632+ bootstrap cross-validated misclassification rates with all classifiers tested. Discriminatory proteins and lipids were useful for classifying tumors according to the intrinsic subtype with median prediction accuracies of 80.0-81.3% in random test sets.</p> <p>Conclusions</p> <p>Protein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.</p