An update of the mechanisms of resistance to EGFR-tyrosine kinase inhibitors in breast cancer: gefitinib (Iressatrade mark)-induced changes in the expression and nucleo-cytoplasmic trafficking of HER-ligands (Review)

Intrinsic resistance to the epidermal growth factor receptor (EGFR; HER1) tyrosine kinase inhibitor (TKI) gefitinib, and more generally to EGFR TKIs, is a common phenomenon in breast cancer. The availability of molecular criteria for predicting sensitivity to EGFR-TKIs is, therefore, the most relevant issue for their correct use and for planning future research. Though it appears that in non-small-cell lung cancer (NSCLC) response to gefitinib is directly related to the occurrence of specific mutations in the EGFR TK domain, breast cancer patients cannot be selected for treatment with gefitinib on the same basis as such EGFR mutations have beenreported neither in primary breast carcinomas nor in several breast cancer cell lines. Alternatively, there is a generalagreement on the hypothesis that the occurrence of molecular alterations that activate transduction pathways downstreamof EGFR (i.e., MEK1/MEK2 - ERK1/2 MAPK and PI-3'K - AKT growth/survival signaling cascades) significantly affect the response to EGFR TKIs in breast carcinomas. However,there are no studies so far addressing a role of EGF-related ligands as intrinsic breast cancer cell modulators of EGFR TKIefficacy. We recently monitored gene expression profiles andsub-cellular localization of HER-1/-2/-3/-4 related ligands (i.e., EGF, amphiregulin, transforming growth factor-α, ß-cellulin,epiregulin and neuregulins) prior to and after gefitinib treatment in a panel of human breast cancer cell lines. First, gefitinibinduced changes in the endogenous levels of EGF-related ligands correlated with the natural degree of breast cancer cellsensitivity to gefitinib. While breast cancer cells intrinsically resistant to gefitinib (IC50 ≥15 μM) markedly up-regulated(up to 600 times) the expression of genes codifying for HERspecific ligands, a significant down-regulation (up to 106 times)of HER ligand gene transcription was found in breast cancer cells intrinsically sensitive to gefitinib (IC50 ≤1 μM). Second,loss of HER1 function differentially regulated the nuclear trafficking of HER-related ligands. While gefitinib treatment induced an active import and nuclear accumulation of the HER ligand NRG in intrinsically gefitinib-resistant breastcancer cells, an active export and nuclear loss of NRG was observed in intrinsically gefitinib-sensitive breast cancer cells.In summary, through in vitro and pharmacodynamic studies we have learned that, besides mutations in the HER1 gene,oncogenic changes downstream of HER1 are the key players regulating gefitinib efficacy in breast cancer cells. It now appears that pharmacological inhibition of HER1 functionalso leads to striking changes in both the gene expression and the nucleo-cytoplasmic trafficking of HER-specific ligands,and that this response correlates with the intrinsic degree of breast cancer sensitivity to the EGFR TKI gefitinib. Therelevance of this previously unrecognized intracrine feedback to gefitinib warrants further studies as cancer cells could bypassthe antiproliferative effects of HER1-targeted therapeutics without a need for the overexpression and/or activation of other HER family members and/or the activation of HER-driven downstream signaling cascades

Breast cancer incidence and overdiagnosis in Catalonia (Spain)

Introduction: Early detection of breast cancer (BC) with mammography may cause overdiagnosis and overtreatment, detecting tumors which would remain undiagnosed during a lifetime. The aims of this study were: first, to model invasive BC incidence trends in Catalonia (Spain) taking into account reproductive and screening data; and second, to quantify the extent of BC overdiagnosis. Methods: We modeled the incidence of invasive BC using a Poisson regression model. Explanatory variables were: age at diagnosis and cohort characteristics (completed fertility rate, percentage of women that use mammography at age 50, and year of birth). This model also was used to estimate the background incidence in the absence of screening. We used a probabilistic model to estimate the expected BC incidence if women in the population used mammography as reported in health surveys. The difference between the observed and expected cumulative incidences provided an estimate of overdiagnosis. Results: Incidence of invasive BC increased, especially in cohorts born from 1940 to 1955. The biggest increase was observed in these cohorts between the ages of 50 to 65 years, where the final BC incidence rates more than doubled the initial ones. Dissemination of mammography was significantly associated with BC incidence and overdiagnosis. Our estimates of overdiagnosis ranged from 0.4% to 46.6%, for women born around 1935 and 1950, respectively. Conclusions: Our results support the existence of overdiagnosis in Catalonia attributed to mammography usage, and the limited malignant potential of some tumors may play an important role. Women should be better informed about this risk. Research should be oriented towards personalized screening and risk assessment tools.

Competing risks to breast cancer mortality in Catalonia

Background: Breast cancer mortality has experienced important changes over the last century. Breast cancer occurs in the presence of other competing risks which can influence breast cancer incidence and mortality trends. The aim of the present work is: 1) to assess the impact of breast cancer deaths among mortality from all causes in Catalonia (Spain), by age and birth cohort and 2) to estimate the risk of death from other causes than breast cancer, one of the inputs needed to model breast cancer mortality reduction due to screening or therapeutic interventions. Methods: The multi-decrement life table methodology was used. First, all-cause mortality probabilities were obtained by age and cohort. Then mortality probability for breast cancer was subtracted from the all-cause mortality probabilities to obtain cohort life tables for causes other than breast cancer. These life tables, on one hand, provide an estimate of the risk of dying from competing risks, and on the other hand, permit to assess the impact of breast cancer deaths on all-cause mortality using the ratio of the probability of death for causes other than breast cancer by the all-cause probability of death. Results: There was an increasing impact of breast cancer on mortality in the first part of the 20th century, with a peak for cohorts born in 1945–54 in the 40–49 age groups (for which approximately 24% of mortality was due to breast cancer). Even though for cohorts born after 1955 there was only information for women under 50, it is also important to note that the impact of breast cancer on all-cause mortality decreased for those cohorts. Conclusion: We have quantified the effect of removing breast cancer mortality in different age groups and birth cohorts. Our results are consistent with US findings. We also have obtained an estimate of the risk of dying from competing-causes mortality, which will be used in the assessment of the effect of mammography screening on breast cancer mortality in Catalonia.

Estimation of age- and stage-specific Catalan breast cancer survival functions using US and Catalan survival data

Background: During the last part of the 1990s the chance of surviving breast cancer increased. Changes in survival functions reflect a mixture of effects. Both, the introduction of adjuvant treatments and early screening with mammography played a role in the decline in mortality. Evaluating the contribution of these interventions using mathematical models requires survival functions before and after their introduction. Furthermore, required survival functions may be different by age groups and are related to disease stage at diagnosis. Sometimes detailed information is not available, as was the case for the region of Catalonia (Spain). Then one may derive the functions using information from other geographical areas. This work presents the methodology used to estimate age- and stage-specific Catalan breast cancer survival functions from scarce Catalan survival data by adapting the age- and stage-specific US functions. Methods: Cubic splines were used to smooth data and obtain continuous hazard rate functions. After, we fitted a Poisson model to derive hazard ratios. The model included time as a covariate. Then the hazard ratios were applied to US survival functions detailed by age and stage to obtain Catalan estimations. Results: We started estimating the hazard ratios for Catalonia versus the USA before and after the introduction of screening. The hazard ratios were then multiplied by the age- and stage-specific breast cancer hazard rates from the USA to obtain the Catalan hazard rates. We also compared breast cancer survival in Catalonia and the USA in two time periods, before cancer control interventions (USA 1975–79, Catalonia 1980–89) and after (USA and Catalonia 1990–2001). Survival in Catalonia in the 1980–89 period was worse than in the USA during 1975–79, but the differences disappeared in 1990–2001. Conclusion: Our results suggest that access to better treatments and quality of care contributed to large improvements in survival in Catalonia. On the other hand, we obtained detailed breast cancer survival functions that will be used for modeling the effect of screening and adjuvant treatments in Catalonia.

Effectiveness of early detection on breast cancer mortality reduction in Catalonia (Spain)

Background: At present, it is complicated to use screening trials to determine the optimal age intervals and periodicities of breast cancer early detection. Mathematical models are an alternative that has been widely used. The aim of this study was to estimate the effect of different breast cancer early detection strategies in Catalonia (Spain), in terms of breast cancer mortality reduction (MR) and years of life gained (YLG), using the stochastic models developed by Lee and Zelen (LZ). Methods: We used the LZ model to estimate the cumulative probability of death for a cohort exposed to different screening strategies after T years of follow-up. We also obtained the cumulative probability of death for a cohort with no screening. These probabilities were used to estimate the possible breast cancer MR and YLG by age, period and cohort of birth. The inputs of the model were: incidence of, mortality from and survival after breast cancer, mortality from other causes, distribution of breast cancer stages at diagnosis and sensitivity of mammography. The outputs were relative breast cancer MR and YLG. Results: Relative breast cancer MR varied from 20% for biennial exams in the 50 to 69 age interval to 30% for annual exams in the 40 to 74 age interval. When strategies differ in periodicity but not in the age interval of exams, biennial screening achieved almost 80% of the annual screening MR. In contrast to MR, the effect on YLG of extending screening from 69 to 74 years of age was smaller than the effect of extending the screening from 50 to 45 or 40 years. Conclusion: In this study we have obtained a measure of the effect of breast cancer screening in terms of mortality and years of life gained. The Lee and Zelen mathematical models have been very useful for assessing the impact of different modalities of early detection on MR and YLG in Catalonia (Spain).

Cost-effectiveness of early detection of breast cancer in Catalonia (Spain)

Background: Breast cancer (BC) causes more deaths than any other cancer among women in Catalonia. Early detection has contributed to the observed decline in BC mortality. However, there is debate on the optimal screening strategy. We performed an economic evaluation of 20 screening strategies taking into account the cost over time of screening and subsequent medical costs, including diagnostic confirmation, initial treatment, follow-up and advanced care. Methods: We used a probabilistic model to estimate the effect and costs over time of each scenario. The effect was measured as years of life (YL), quality-adjusted life years (QALY), and lives extended (LE). Costs of screening and treatment were obtained from the Early Detection Program and hospital databases of the IMAS-Hospital del Mar in Barcelona. The incremental cost-effectiveness ratio (ICER) was used to compare the relative costs and outcomes of different scenarios. Results: Strategies that start at ages 40 or 45 and end at 69 predominate when the effect is measured as YL or QALYs. Biennial strategies 50-69, 45-69 or annual 45-69, 40-69 and 40-74 were selected as cost-effective for both effect measures (YL or QALYs). The ICER increases considerably when moving from biennial to annual scenarios. Moving from no screening to biennial 50-69 years represented an ICER of 4,469€ per QALY. Conclusions: A reduced number of screening strategies have been selected for consideration by researchers, decision makers and policy planners. Mathematical models are useful to assess the impact and costs of BC screening in a specific geographical area.

Contribution of early detection and adjuvant treatments to breast cancer mortality reduction in Catalonia, Spain

Background: Reductions in breast cancer (BC) mortality in Western countries have been attributed to the use of screening mammography and adjuvant treatments. The goal of this work was to analyze the contributions of both interventions to the decrease in BC mortality between 1975 and 2008 in Catalonia. Methodology/Principal Findings: A stochastic model was used to quantify the contribution of each intervention. Age standardized BC mortality rates for calendar years 1975-2008 were estimated in four hypothetical scenarios: 1) Only screening, 2) Only adjuvant treatment, 3) Both interventions, and 4) No intervention. For the 30-69 age group, observed Catalan BC mortality rates per 100,000 women-year rose from 29.4 in 1975 to 38.3 in 1993, and afterwards continuously decreased to 23.2 in 2008. If neither of the two interventions had been used, in 2008 the estimated BC mortality would have been 43.5, which, compared to the observed BC mortality rate, indicates a 46.7% reduction. In 2008 the reduction attributable to screening was 20.4%, to adjuvant treatments was 15.8% and to both interventions 34.1%. Conclusions/Significance: Screening and adjuvant treatments similarly contributed to reducing BC mortality in Catalonia. Mathematical models have been useful to assess the impact of interventions addressed to reduce BC mortality that occurred over nearly the same periods.

Forage preservation (grazing vs. hay) fed to ewes affects the fatty acid profile of milk and CPT1B gene expression in the sheep mammary gland

Background: Alterations in lipid metabolism occur when animals are exposed to different feeding systems. In the last few decades, the characterisation of genes involved in fat metabolism and technological advances have enabled the study of the effect of diet on the milk fatty acid (FA) profile in the mammary gland and aided in the elucidation of the mechanisms of the response to diet. The aim of this study was to evaluate the effect of different forage diets (grazing vs. hay) near the time of ewe parturition on the relationship between the fatty acid profile and gene expression in the mammary gland of the Churra Tensina sheep breed. Results: In this study, the forage type affected the C18:2 cis-9 trans-11 (CLA) and long-chain saturated fatty acid (LCFA) content, with higher percentages during grazing than during hay feeding. This may suggest that these FAs act as regulatory factors for the transcriptional control of the carnitine palmitoyltransferase 1B (CPT1B) gene, which was more highly expressed in the grazing group (GRE). The most highly expressed gene in the mammary gland at the fifth week of lactation is CAAT/ enhancer- binding protein beta (CEBPB), possibly due to its role in milk fat synthesis in the mammary gland. More stable housekeeping genes in the ovine mammary gland that would be appropriate for use in gene expression studies were ribosomal protein L19 (RPL19) and glyceraldehyde- 3- phosphate dehydrogenase (GAPDH). Conclusions: Small changes in diet, such as the forage preservation (grazing vs. hay), can affect the milk fatty acid profile and the expression of the CPT1B gene, which is associated with the oxidation of fatty acids. When compared to hay fed indoors, grazing fresh low mountain pastures stimulates the milk content of CLA and LCFA via mammary uptake. In this sense, LCFA in milk may be acting as a regulatory factor for transcriptional control of the CPT1B gene, which was more highly expressed in the grazing group.

The effects of milk as a food matrix for polyphenols on the excretion profile of cocoa (-)-Epicatechin metabolites in healthy humans subjects

The effect of different food matrices on the metabolism and excretion of polyphenols is uncertain. The objective of the study was to evaluate the possible effect of milk on the excretion of (2)-epicatechin metabolites from cocoa powder after its ingestion with and without milk. Twenty-one volunteers received the following three test meals each in a randomised cross-over design with a 1-week interval between meals: (1) 250 ml whole milk as a control; (2) 40 g cocoa powder dissolved in 250 ml whole milk (CC-M); (3) 40 g cocoa powder dissolved in 250 ml water (CC-W). Urine was collected before consumption and during the 0-6, 6-12 and 12-24 h periods after consumption. (2)-Epicatechin metabolite excretion was measured using liquid chromatography-MS. One (2)-epicatechin glucuronide and three (2)-epicatechin sulfates were detected in urine excreted after the intake of the two cocoa beverages (CC-M and CC-W). The results show that milk does not significantly affect the total amount of metabolites excreted in urine. However, differences in metabolite excretion profiles were observed; there were changes in the glucuronide and sulfate excretion rates, and the sulfation position between the period of excretion and the matrix. The matrix in which polyphenols are consumed can affect their metabolism and excretion, and this may affect their biological activity. Thus, more studies are needed to evaluate the effect of these different metabolite profiles on the body.

Residues of b-lactams and quinolones in tissues and milk samples. Confirmatory analysis by liquid chromatography-mass spectrometry

The aim of this work is to optimize and validate methods for the multiresidue determination of series of families of antibiotics as quinolones, penicillins and cephalosporins included in European regulation in food samples using LC-MS/MS. Different extraction techniques and clean-up applied to antibiotics in meat were compared. The quality parameters were established according with EU guideline. The developed method was applied to 49 positive raw milk samples from animal medicated with different antibiotics; the 63% of the analyzed samples were found to be compliant. ___________________________________________________________________________________________

Identification of metabolites and thermal transformation products of quinolones in raw cow milk by liquid chromatography coupled to high resolution mass spectrometry

The presence of residues of antibiotics, metabolites, and thermal transformation products (TPs), produced during thermal treatment to eliminate pathogenic microorganisms in milk, could represent a risk for people. Cow"s milk samples spiked with enrofloxacin (ENR), ciprofloxacin (CIP), difloxacin (DIF), and sarafloxacin (SAR) and milk samples from cows medicated with ENR were submitted to several thermal treatments. The milk samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) to find and identify TPs and metabolites. In this work, 27 TPs of 4 quinolones and 24 metabolites of ENR were found. Some of these compounds had been reported previously, but others were characterized for the first time, including lactose-conjugated CIP, the formamidation reaction for CIP and SAR, and hydroxylation or ketone formation to produce three different isomers for all quinolones studied.

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Identification of molecular subtypes and gene expression patterns of breast cancer analysing RNA-seq data

Breast cancer is the most common diagnosed cancer and the leading cause of cancer death among females worldwide. It is considered a highly heterogeneous disease and it must be classified into more homogeneous groups. Hence, the purpose of this study was to classify breast tumors based on variations in gene expression patterns derived from RNA sequencing by using different class discovery methods. 42 breast tumors paired-samples were sequenced by Illumine Genome Analyzer and the data was analyzed and prepared by TopHat2 and htseq-count. As reported previously, breast cancer could be grouped into five main groups known as basal epithelial-like group, HER2 group, normal breast-like group and two Luminal groups with a distinctive expression profile. Classifying breast tumor samples by using PAM50 method, the most common subtype was Luminal B and was significantly associated with ESR1 and ERBB2 high expression. Luminal A subtype had ESR1 and SLC39A6 significant high expression, whereas HER2 subtype had a high expression of ERBB2 and CNNE1 genes and low luminal epithelial gene expression. Basal-like and normal-like subtypes were associated with low expression of ESR1, PgR and HER2, and had significant high expression of cytokeratins 5 and 17. Our results were similar compared with TGCA breast cancer data results and with known studies related with breast cancer classification. Classifying breast tumors could add significant prognostic and predictive information to standard parameters, and moreover, identify marker genes for each subtype to find a better therapy for patients with breast cancer.

Identification of metabolites and thermal transformation products of quinolones in raw cow milk by liquid chromatography coupled to high resolution mass spectrometry.

The presence of residues of antibiotics, metabolites, and thermal transformation products (TPs), produced during thermal treatment to eliminate pathogenic microorganisms in milk, could represent a risk for people. Cow"s milk samples spiked with enrofloxacin (ENR), ciprofloxacin (CIP), difloxacin (DIF), and sarafloxacin (SAR) and milk samples from cows medicated with ENR were submitted to several thermal treatments. The milk samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) to find and identify TPs and metabolites. In this work, 27 TPs of 4 quinolones and 24 metabolites of ENR were found. Some of these compounds had been reported previously, but others were characterized for the first time, including lactose-conjugated CIP, the formamidation reaction for CIP and SAR, and hydroxylation or ketone formation to produce three different isomers for all quinolones studied.