Steinar Lundgren

Characterization of neoplastic and normal human breast tissues with in vivo1H MR spectroscopy

The purpose of this study was to evaluate whether the detection of choline‐containing compounds in in vivo 1H magnetic resonance spectroscopy (MRS) of breast lesions is specific for carcinomas, whether a choline peak in in vivo 1H MRS can be detected under physiological conditions of increased metabolism in breast parenchyma, and whether analysis of lipid signals can differentiate between various breast lesions and tissues. Forty patients and volunteers were examined with in vivo 1H MR spectroscopy. Three spectra with identical localization but increasing echo times were obtained. Choline‐containing compounds were detected in 9 of 11 carcinomas and in 2 of 11 benign lesions. A choline signal was also detected in five of seven volunteers who were breast‐feeding at the time of examination, demonstrating that choline compounds can be detected by in vivo 1H MRS in breast tissue under physiological conditions. Analysis of lipid signals did not contribute to differentiation between various breast lesions and tissues. J. Magn. Reson. Imaging 1999;10:159–164.

Multivariate modeling and prediction of breast cancer prognostic factors using MR metabolomics.

Axillary lymph node status together with estrogen and progesterone receptor status are important prognostic factors in breast cancer. In this study, the potential of using MR metabolomics for prediction of these prognostic factors was evaluated. Biopsies from breast cancer patients (n = 160) were excised during surgery and analyzed by high resolution magic angle spinning MR spectroscopy (HR MAS MRS). The spectral data were preprocessed and variable stability (VAST) scaled, and training and test sets were generated using the Kennard-Stone and SPXY sample selection algorithms. The data were analyzed by partial least-squares discriminant analysis (PLS-DA), probabilistic neural networks (PNNs) and Bayesian belief networks (BBNs), and blind samples (n = 50) were predicted for verification. Estrogen and progesterone receptor status was successfully predicted from the MR spectra, and were best predicted by PLS-DA with a correct classification of 44 of 50 and 39 of 50 samples, respectively. Lymph node status was best predicted by BBN with 34 of 50 samples correctly classified, indicating a relationship between metabolic profile and lymph node status. Thus, MR profiles contain prognostic information that may be of benefit in treatment planning, and MR metabolomics may become an important tool for diagnosis of breast cancer patients.

Psychosocial interventions as part of breast cancer rehabilitation programs? Results from a systematic review

Objective: This systematic review aimed to determine the effectiveness of psychoeducation, cognitive behavioural therapy (CBT) and social support interventions used in the rehabilitation of breast cancer (BC) patients.

Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI

To evaluate dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5‐year survival in patients with locally advanced breast cancer.

Merging transcriptomics and metabolomics - advances in breast cancer profiling

BackgroundCombining 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.MethodsBreast 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.ResultsIn 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.ConclusionsCombining 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/1741-7015/8/73

Predictive and prognostic impact of TP53 mutations and MDM2 promoter genotype in primary breast cancer patients treated with epirubicin or paclitaxel.

Background TP53 mutations have been associated with resistance to anthracyclines but not to taxanes in breast cancer patients. The MDM2 promoter single nucleotide polymorphism (SNP) T309G increases MDM2 activity and may reduce wild-type p53 protein activity. Here, we explored the predictive and prognostic value of TP53 and CHEK2 mutation status together with MDM2 SNP309 genotype in stage III breast cancer patients receiving paclitaxel or epirubicin monotherapy. Experimental Design Each patient was randomly assigned to treatment with epirubicin 90 mg/m2 (n = 109) or paclitaxel 200 mg/m2 (n = 114) every 3rd week as monotherapy for 4–6 cycles. Patients obtaining a suboptimal response on first-line treatment requiring further chemotherapy received the opposite regimen. Time from last patient inclusion to follow-up censoring was 69 months. Each patient had snap-frozen tumor tissue specimens collected prior to commencing chemotherapy. Principal Findings While TP53 and CHEK2 mutations predicted resistance to epirubicin, MDM2 status did not. Neither TP53/CHEK2 mutations nor MDM2 status was associated with paclitaxel response. Remarkably, TP53 mutations (p = 0.007) but also MDM2 309TG/GG genotype status (p = 0.012) were associated with a poor disease-specific survival among patients having paclitaxel but not patients having epirubicin first-line. The effect of MDM2 status was observed among individuals harbouring wild-type TP53 (p = 0.039) but not among individuals with TP53 mutated tumors (p>0.5). Conclusion TP53 and CHEK2 mutations were associated with lack of response to epirubicin monotherapy. In contrast, TP53 mutations and MDM2 309G allele status conferred poor disease-specific survival among patients treated with primary paclitaxel but not epirubicin monotherapy.

CHEK2 mutations affecting kinase activity together with mutations in TP53 indicate a functional pathway associated with resistance to epirubicin in primary breast cancer

Background Chemoresistance is the main obstacle to cure in most malignant diseases. Anthracyclines are among the main drugs used for breast cancer therapy and in many other malignant conditions. Single parameter analysis or global gene expression profiles have failed to identify mechanisms causing in vivo resistance to anthracyclines. While we previously found TP53 mutations in the L2/L3 domains to be associated with drug resistance, some tumors harboring wild-type TP53 were also therapy resistant. The aim of this study was; 1) To explore alterations in the TP53 gene with respect to resistance to a regular dose epirubicin regimen (90 mg/m2 every 3 week) in patients with primary, locally advanced breast cancer; 2) Identify critical mechanisms activating p53 in response to DNA damage in breast cancer; 3) Evaluate in vitro function of Chk2 and p14 proteins corresponding to identified mutations in the CHEK2 and p14(ARF) genes; and 4) Explore potential CHEK2 or p14(ARF) germline mutations with respect to family cancer incidence. Methods and Findings Snap-frozen biopsies from 109 patients collected prior to epirubicin (as preoperative therapy were investigated for TP53, CHEK2 and p14(ARF) mutations by sequencing the coding region and p14(ARF) promoter methylations. TP53 mutastions were associated with chemoresistance, defined as progressive disease on therapy (p = 0.0358; p = 0.0136 for mutations affecting p53 loop domains L2/L3). Germline CHEK2 mutations (n = 3) were associated with therapy resistance (p = 0.0226). Combined, mutations affecting either CHEK2 or TP53 strongly predicted therapy resistance (p = 0.0101; TP53 mutations restricted to the L2/L3 domains: p = 0.0032). Two patients progressing on therapy harbored the CHEK2 mutation, Arg95Ter, completely abrogating Chk2 protein dimerization and kinase activity. One patient (Epi132) revealed family cancer occurrence resembling families harboring CHEK2 mutations in general, the other patient (epi203) was non-conclusive. No mutation or promoter hypermethylation in p14(ARF) were detected. Conclusion This study is the first reporting an association between CHEK2 mutations and therapy resistance in human cancers and to document mutations in two genes acting direct up/down-stream to each other to cause therapy failure, emphasizing the need to investigate functional cascades in future studies.

Predicting long-term survival and treatment response in breast cancer patients receiving neoadjuvant chemotherapy by MR metabolic profiling

This study aimed to evaluate whether MR metabolic profiling can be used for prediction of long‐term survival and monitoring of treatment response in locally advanced breast cancer patients during neoadjuvant chemotherapy (NAC). Methods: High resolution magic angle spinning (HR MAS) MR spectra of pre‐ and post‐treatment biopsies from 33 patients were acquired. Tissue concentrations of choline‐containing metabolites (tCho), glycine and taurine were assessed using electronic reference to access in vivo concentration (ERETIC) of the signal and receiver operating characteristic (ROC) curves was used to define their potential to predict patient survival and treatment response. The metabolite profiles obtained by HR MAS spectroscopy were related to long‐term survival and treatment response by genetic algorithm partial least squares discriminant analysis (GA PLS‐DA).

Changes in radiation sensitivity and steroid receptor content induced by hormonal agents and ionizing radiation in breast cancer cells in vitro.

Possible influences of tamoxifen and estradiol on in vitro radiation sensitivity and cellular receptor content after irradiation and/or tamoxifen treatment were studied in breast cancer cell lines; estrogen receptor (ER) and progesterone receptor (PgR) positive cell lines MCF-7 and MCF-7/TAM(R)-1 and the ER and PgR negative cell line MDA-MB-231. The tamoxifen resistant MCF-7/TAM(R)-1 cells were more resistant to ionizing radiation than the MCF-7 and MDA-MB-231 cells. Exposure to tamoxifen made the MCF-7 cells more radiation resistant, while estradiol made the MDA-MB-231 cells more radiation sensitive. A radiation dose of 6 Gy reduced the ER content in cytosol in both MCF-7 and MCF-7/TAM(R)-1 cells, but brought no alterations to the PgR content. In MCF-7/TAM(R)-1 cells tamoxifen exposure significantly increased the ER and reduced the PgR content, an effect not observed in the MCF-7 cells. To conclude, the present study indicates that irradiation and tamoxifen may modify the ER and PgR content in cytosol in breast cancer cells. Hormonal treatment may alter the radiation sensitivity, even in ER negative cells, suggesting that hormonal agents may act both via receptor and non-receptor binding mechanisms.

Associations between tamoxifen, estrogens, and FSH serum levels during steady state tamoxifen treatment of postmenopausal women with breast cancer

BackgroundThe cytochrome P450 (CYP) enzymes 2C19, 2D6, and 3A5 are responsible for converting the selective estrogen receptor modulator (SERM), tamoxifen to its active metabolites 4-hydroxy-tamoxifen (4OHtam) and 4-hydroxy-N-demethyltamoxifen (4OHNDtam, endoxifen). Inter-individual variations of the activity of these enzymes due to polymorphisms may be predictors of outcome of breast cancer patients during tamoxifen treatment. Since tamoxifen and estrogens are both partly metabolized by these enzymes we hypothesize that a correlation between serum tamoxifen and estrogen levels exists, which in turn may interact with tamoxifen on treatment outcome. Here we examined relationships between the serum levels of tamoxifen, estrogens, follicle-stimulating hormone (FSH), and also determined the genotypes of CYP2C19, 2D6, 3A5, and SULT1A1 in 90 postmenopausal breast cancer patients.MethodsTamoxifen and its metabolites were measured by liquid chromatography-tandem mass spectrometry. Estrogen and FSH levels were determined using a sensitive radio- and chemiluminescent immunoassay, respectively.ResultsWe observed significant correlations between the serum concentrations of tamoxifen, N-dedimethyltamoxifen, and tamoxifen-N-oxide and estrogens (p < 0.05). The genotype predicted CYP2C19 activity influenced the levels of both tamoxifen metabolites and E1.ConclusionsWe have shown an association between tamoxifen and its metabolites and estrogen serum levels. An impact of CYP2C19 predicted activity on tamoxifen, as well as estrogen kinetics may partly explain the observed association between tamoxifen and its metabolites and estrogen serum levels. Since the role of estrogen levels during tamoxifen therapy is still a matter of debate further prospective studies to examine the effect of tamoxifen and estrogen kinetics on treatment outcome are warranted.