The Cyclin D1 (CCND1) A870G polymorphism predicts clinical outcome to lapatinib and capecitabine in HER2-positive metastatic breast cancer

BACKGROUND: Lapatinib plus capecitabine emerged as an efficacious therapy in metastatic breast cancer (mBC). We aimed to identify germline single-nucleotide polymorphisms (SNPs) in genes involved in capecitabine catabolism and human epidermal receptor signaling that were associated with clinical outcome to assist in selecting patients likely to benefit from this combination.

PATIENTS AND METHODS: DNA was extracted from 240 of 399 patients enrolled in EGF100151 clinical trial (NCT00078572; clinicaltrials.gov) and SNPs were successfully evaluated in 234 patients. The associations between SNPs and clinical outcome were analyzed using Fisher's exact test, Kaplan-Meier curves, log-rank tests, likelihood ratio test within logistic or Cox regression model, as appropriate.

RESULTS: There were significant interactions between CCND1 A870G and clinical outcome. Patients carrying the A-allele were more likely to benefit from lapatinib plus capecitabine versus capecitabine when compared with patients harboring G/G (P = 0.022, 0.024 and 0.04, respectively). In patients with the A-allele, the response rate (RR) was significantly higher with lapatinib plus capecitabine (35%) compared with capecitabine (11%; P = 0.001) but not between treatments in patients with G/G (RR = 24% and 32%, respectively; P = 0.85). Time to tumor progression (TTP) was longer in patients with the A-allele treated with lapatinib plus capecitabine compared with capecitabine (median TTP = 7.9 and 3.4 months; P < 0.001), but not in patients with G/G (median TTP = 6.1 and 6.6 months; P = 0.92).

CONCLUSION: Our findings suggest that CCND1A870G may be useful in predicting clinical outcome in HER2-positive mBC patients treated with lapatinib plus capecitabine.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Impact of using different radiation therapy techniques in breat cancer: contralateral breast dose

RESUMO: O cancro de mama e o mais frequente diagnoticado a indiv duos do sexo feminino. O conhecimento cientifico e a tecnologia tem permitido a cria ção de muitas e diferentes estrat egias para tratar esta patologia. A Radioterapia (RT) est a entre as diretrizes atuais para a maioria dos tratamentos de cancro de mama. No entanto, a radia ção e como uma arma de dois canos: apesar de tratar, pode ser indutora de neoplasias secund arias. A mama contralateral (CLB) e um orgão susceptivel de absorver doses com o tratamento da outra mama, potenciando o risco de desenvolver um tumor secund ario. Nos departamentos de radioterapia tem sido implementadas novas tecnicas relacionadas com a radia ção, com complexas estrat egias de administra ção da dose e resultados promissores. No entanto, algumas questões precisam de ser devidamente colocadas, tais como: E seguro avançar para tecnicas complexas para obter melhores indices de conformidade nos volumes alvo, em radioterapia de mama? O que acontece aos volumes alvo e aos tecidos saudaveis adjacentes? Quão exata e a administração de dose? Quais são as limitações e vantagens das técnicas e algoritmos atualmente usados? A resposta a estas questões e conseguida recorrendo a m etodos de Monte Carlo para modelar com precisão os diferentes componentes do equipamento produtor de radia ção(alvos, ltros, colimadores, etc), a m de obter uma descri cão apropriada dos campos de radia cão usados, bem como uma representa ção geometrica detalhada e a composição dos materiais que constituem os orgãos e os tecidos envolvidos. Este trabalho visa investigar o impacto de tratar cancro de mama esquerda usando diferentes tecnicas de radioterapia f-IMRT (intensidade modulada por planeamento direto), IMRT por planeamento inverso (IMRT2, usando 2 feixes; IMRT5, com 5 feixes) e DCART (arco conformacional dinamico) e os seus impactos em irradia ção da mama e na irradia ção indesejada dos tecidos saud aveis adjacentes. Dois algoritmos do sistema de planeamento iPlan da BrainLAB foram usados: Pencil Beam Convolution (PBC) e Monte Carlo comercial iMC. Foi ainda usado um modelo de Monte Carlo criado para o acelerador usado (Trilogy da VARIAN Medical Systems), no c odigo EGSnrc MC, para determinar as doses depositadas na mama contralateral. Para atingir este objetivo foi necess ario modelar o novo colimador multi-laminas High- De nition que nunca antes havia sido simulado. O modelo desenvolvido est a agora disponí vel no pacote do c odigo EGSnrc MC do National Research Council Canada (NRC). O acelerador simulado foi validado com medidas realizadas em agua e posteriormente com c alculos realizados no sistema de planeamento (TPS).As distribui ções de dose no volume alvo (PTV) e a dose nos orgãos de risco (OAR) foram comparadas atrav es da an alise de histogramas de dose-volume; an alise estati stica complementar foi realizadas usando o software IBM SPSS v20. Para o algoritmo PBC, todas as tecnicas proporcionaram uma cobertura adequada do PTV. No entanto, foram encontradas diferen cas estatisticamente significativas entre as t ecnicas, no PTV, nos OAR e ainda no padrão da distribui ção de dose pelos tecidos sãos. IMRT5 e DCART contribuem para maior dispersão de doses baixas pelos tecidos normais, mama direita, pulmão direito, cora cão e at e pelo pulmão esquerdo, quando comparados com as tecnicas tangenciais (f-IMRT e IMRT2). No entanto, os planos de IMRT5 melhoram a distribuição de dose no PTV apresentando melhor conformidade e homogeneidade no volume alvo e percentagens de dose mais baixas nos orgãos do mesmo lado. A t ecnica de DCART não apresenta vantagens comparativamente com as restantes t ecnicas investigadas. Foram tamb em identi cadas diferen cas entre os algoritmos de c alculos: em geral, o PBC estimou doses mais elevadas para o PTV, pulmão esquerdo e cora ção, do que os algoritmos de MC. Os algoritmos de MC, entre si, apresentaram resultados semelhantes (com dferen cas at e 2%). Considera-se que o PBC não e preciso na determina ção de dose em meios homog eneos e na região de build-up. Nesse sentido, atualmente na cl nica, a equipa da F sica realiza medi ções para adquirir dados para outro algoritmo de c alculo. Apesar de melhor homogeneidade e conformidade no PTV considera-se que h a um aumento de risco de cancro na mama contralateral quando se utilizam t ecnicas não-tangenciais. Os resultados globais dos estudos apresentados confirmam o excelente poder de previsão com precisão na determinação e c alculo das distribui ções de dose nos orgãos e tecidos das tecnicas de simulação de Monte Carlo usados.---------ABSTRACT:Breast cancer is the most frequent in women. Scienti c knowledge and technology have created many and di erent strategies to treat this pathology. Radiotherapy (RT) is in the actual standard guidelines for most of breast cancer treatments. However, radiation is a two-sword weapon: although it may heal cancer, it may also induce secondary cancer. The contralateral breast (CLB) is a susceptible organ to absorb doses with the treatment of the other breast, being at signi cant risk to develop a secondary tumor. New radiation related techniques, with more complex delivery strategies and promising results are being implemented and used in radiotherapy departments. However some questions have to be properly addressed, such as: Is it safe to move to complex techniques to achieve better conformation in the target volumes, in breast radiotherapy? What happens to the target volumes and surrounding healthy tissues? How accurate is dose delivery? What are the shortcomings and limitations of currently used treatment planning systems (TPS)? The answers to these questions largely rely in the use of Monte Carlo (MC) simulations using state-of-the-art computer programs to accurately model the di erent components of the equipment (target, lters, collimators, etc.) and obtain an adequate description of the radiation elds used, as well as the detailed geometric representation and material composition of organs and tissues. This work aims at investigating the impact of treating left breast cancer using di erent radiation therapy (RT) techniques f-IMRT (forwardly-planned intensity-modulated), inversely-planned IMRT (IMRT2, using 2 beams; IMRT5, using 5 beams) and dynamic conformal arc (DCART) RT and their e ects on the whole-breast irradiation and in the undesirable irradiation of the surrounding healthy tissues. Two algorithms of iPlan BrainLAB TPS were used: Pencil Beam Convolution (PBC)and commercial Monte Carlo (iMC). Furthermore, an accurate Monte Carlo (MC) model of the linear accelerator used (a Trilogy R VARIANR) was done with the EGSnrc MC code, to accurately determine the doses that reach the CLB. For this purpose it was necessary to model the new High De nition multileaf collimator that had never before been simulated. The model developed was then included on the EGSnrc MC package of National Research Council Canada (NRC). The linac was benchmarked with water measurements and later on validated against the TPS calculations. The dose distributions in the planning target volume (PTV) and the dose to the organs at risk (OAR) were compared analyzing dose-volume histograms; further statistical analysis was performed using IBM SPSS v20 software. For PBC, all the techniques provided adequate coverage of the PTV. However, statistically significant dose di erences were observed between the techniques, in the PTV, OAR and also in the pattern of dose distribution spreading into normal tissues. IMRT5 and DCART spread low doses into greater volumes of normal tissue, right breast, right lung, heart and even the left lung than tangential techniques (f-IMRT and IMRT2). However,IMRT5 plans improved distributions for the PTV, exhibiting better conformity and homogeneity in target and reduced high dose percentages in ipsilateral OAR. DCART did not present advantages over any of the techniques investigated. Di erences were also found comparing the calculation algorithms: PBC estimated higher doses for the PTV, ipsilateral lung and heart than the MC algorithms predicted. The MC algorithms presented similar results (within 2% di erences). The PBC algorithm was considered not accurate in determining the dose in heterogeneous media and in build-up regions. Therefore, a major e ort is being done at the clinic to acquire data to move from PBC to another calculation algorithm. Despite better PTV homogeneity and conformity there is an increased risk of CLB cancer development, when using non-tangential techniques. The overall results of the studies performed con rm the outstanding predictive power and accuracy in the assessment and calculation of dose distributions in organs and tissues rendered possible by the utilization and implementation of MC simulation techniques in RT TPS.

The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death

The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.

Quantitative ultrasound imaging during shear wave propagation for application related to breast cancer diagnosis

Dans le contexte de la caractérisation des tissus mammaires, on peut se demander ce que l’examen d’un attribut en échographie quantitative (« quantitative ultrasound » - QUS) d’un milieu diffusant (tel un tissu biologique mou) pendant la propagation d’une onde de cisaillement ajoute à son pouvoir discriminant. Ce travail présente une étude du comportement variable temporel de trois paramètres statistiques (l’intensité moyenne, le paramètre de structure et le paramètre de regroupement des diffuseurs) d’un modèle général pour l’enveloppe écho de l’onde ultrasonore rétrodiffusée (c.-à-d., la K-distribution homodyne) sous la propagation des ondes de cisaillement. Des ondes de cisaillement transitoires ont été générés en utilisant la mèthode d’ imagerie de cisaillement supersonique ( «supersonic shear imaging » - SSI) dans trois fantômes in-vitro macroscopiquement homogènes imitant le sein avec des propriétés mécaniques différentes, et deux fantômes ex-vivo hétérogénes avec tumeurs de souris incluses dans un milieu environnant d’agargélatine. Une comparaison de l’étendue des trois paramètres de la K-distribution homodyne avec et sans propagation d’ondes de cisaillement a montré que les paramètres étaient significativement (p < 0,001) affectès par la propagation d’ondes de cisaillement dans les expériences in-vitro et ex-vivo. Les résultats ont également démontré que la plage dynamique des paramétres statistiques au cours de la propagation des ondes de cisaillement peut aider à discriminer (avec p < 0,001) les trois fantômes homogènes in-vitro les uns des autres, ainsi que les tumeurs de souris de leur milieu environnant dans les fantômes hétérogénes ex-vivo. De plus, un modéle de régression linéaire a été appliqué pour corréler la plage de l’intensité moyenne sous la propagation des ondes de cisaillement avec l’amplitude maximale de déplacement du « speckle » ultrasonore. La régression linéaire obtenue a été significative : fantômes in vitro : R2 = 0.98, p < 0,001 ; tumeurs ex-vivo : R2 = 0,56, p = 0,013 ; milieu environnant ex-vivo : R2 = 0,59, p = 0,009. En revanche, la régression linéaire n’a pas été aussi significative entre l’intensité moyenne sans propagation d’ondes de cisaillement et les propriétés mécaniques du milieu : fantômes in vitro : R2 = 0,07, p = 0,328, tumeurs ex-vivo : R2 = 0,55, p = 0,022 ; milieu environnant ex-vivo : R2 = 0,45, p = 0,047. Cette nouvelle approche peut fournir des informations supplémentaires à l’échographie quantitative statistique traditionnellement réalisée dans un cadre statique (c.-à-d., sans propagation d’ondes de cisaillement), par exemple, dans le contexte de l’imagerie ultrasonore en vue de la classification du cancer du sein.

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

Breast cancer incidence and overdiagnosis in Catalonia (Spain)

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. 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.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.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

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

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

Use of global gene expression patterns in mechanistic studies of oestrogen action in MCF7 human breast cancer cells

Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are down regulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0-4 weeks) but continuing through to later times (20-55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated >= 2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times. (C) 2009 Elsevier Ltd. All rights reserved.

Expression profiles in the progression of ductal carcinoma in the breast

An understanding of the multi-step nature of cancer as it is in the breast, as a series of pivotal genetic/epigenetic modifications is irrefutably a milestone in diagnostics, prognostics and eventually providing a cure. Here we have utilised a variant of analysis of variance (ANOVA) as a model for the identification and tracking of specific mRNA species whose transcription has been significantly altered at each grade in the progression of ductal carcinoma, making it possible to correlate histological progression with the genetic events underlying breast cancer. We show that in the progression of ductal carcinomas, from grade 1 to 3, there is a reduction in the actual number of mRNA species, which are significantly over or under expressed. We also show that this technique can be employed to generate differential gene expression patterns, whereby the combined expression profile of the tailored spectra of genes in the comparison of each ductal grade is sufficient to render them on clearly separate arms of an array-wise hierarchical cluster dendrogram.

Antitumor activity of Titanocene Y against freshly explanted human breast tumor cells and in xenografted MCF-7 tumors in mice

Bis-[(p-methoxybenzyl)cyclopentadienyl] titanium dichloride, better known as Titanocene Y, is a newly synthesized transition metal-based anticancer drug. We studied the antitumor activity of Titanocene Y with concentrations of 2.1, 21 and 210 mu mol/l against a freshly explanted human breast cancer, using an in-vitro soft agar cloning system. The sensitivity against Titanocene Y was highly remarkable in the breast cancer tumor in the full concentration range. Titanocene Y showed cell death induction at 2.1 mu mol/l, well comparable to cisplatin, given at a concentration of 1.0 mu mol/l. A further preclinical development of Titanocene Y was warranted and therefore an MCF-7 human breast cancer xenograft nonobese diabetic/severe combined immunodeficient mouse model was used. Titanocene Y was given for 21 days at 30 mg/kg/ day (75% of the maximum tolerable dose of Titanocene Y), which resulted in the reduction of the tumor volume to around one-third, whereas no mouse was lost because of the surprisingly low toxicity of Titanocene Y.

Differential effects of overexpression of ERalpha and ERbeta in MCF10A immortalised, non-transformed human breast epithelail cells

Background: Cellular effects of oestrogen are mediated by two intracellular receptors ERα and ERβ. However, to compare responses mediated through these two receptors, experimental models are needed where ERα and ERβ are individually stably overexpressed in the same cell type. Methods: We compared the effects of stable overexpression of ERα and ERβ in the MCF10A cell line, which is an immortalised but non-transformed breast epithelial cell line without high endogenous ER expression. Results: Clones of MCF10A cells were characterised which stably overexpressed ERα (10A-ERα2, 10A-ERα13) or which stably overexpressed ERβ (10A-ERβ12, 10A-ERβ15). Overexpression of either ERα or ERβ allowed induction of an oestrogen-regulated ERE-LUC reporter gene by oestradiol which was not found in the untransfected cells. Oestradiol also increased proliferation of 10A-ERα13 and 10A-ERβ12 cells, but not untransfected cells, by 1.3-fold over 7 days. The phytoestrogen, genistein, which is reported to bind more strongly to ERβ than to ERα, could induce luciferase gene expression from an ERE-LUC reporter gene at concentrations of 10−6 M and 10−5 M but only in the clones overexpressing ERβ and not in those overexpressing ERα. Clone 10A-ERβ12 also yielded growth stimulation with 10-6 M genistein. Finally, the overexpression of ERα, but not ERβ, gave rise to increased growth in semi-solid methocel suspension culture in the presence of 70 nM oestradiol, suggesting that overexpression of ERα, but not ERβ, produces characteristics of a transformed phenotype. Conclusions: This provides a model system to compare effects of oestradiol with other oestrogenic ligands in cells stably overexpressing individually ERα or ERβ.

Enhanced sensitivity to rapamycin following long-term oestrogen deprivation in MCF-7, T-47-D and ZR-75-1 human breast cancer cells

Human breast cancer cells (MCF-7, T-47-D and ZR-75-1) can adapt to circumvent any reduced growth rate during long-term oestrogen deprivation, and this provides three model systems to investigate mechanisms of endocrine resistance in breast cancer. In this paper we report consistent differences in the effects of three growth inhibitors following long-term oestrogen deprivation in all three cell models. Long-term oestrogen deprivation of MCF-7, T-47-D and ZR-75-1 cells resulted in reduced growth inhibition by PD98059 (2–10 µg/ml), implying a loss of dependence on mitogen-activated protein kinase pathways for growth. The growth inhibitor LY294002 (2–10 µM) inhibited growth of both oestrogen-maintained and oestrogen-deprived cells with similar dose–responses, implying continued similar dependence on phosphoinositide 3-kinase (PI3K) pathways with no alteration after adaptation to oestrogen independent growth. However, by contrast, long-term oestrogen deprivation resulted in an increased sensitivity to growth inhibition by rapamycin, which was not reduced by readdition of oestradiol. The enhanced inhibition of long-term oestrogen-deprived MCF-7-ED, T-47-D-ED and ZR-75-1-ED cell growth by combining rapamycin with LY294002 at concentrations where each alone had little effect, offers preclinical support to the development of therapeutic combinations of rapamycin analogues with other PI3K inhibitors in endocrine-resistant breast cancer.

Crosstalk with insulin and dependence on PI3K/Akt/mTOR rather than MAPK pathways in upregulation of basal growth following long-term oestrogen deprivation in three human breast cancer cell lines

Background: MCF-7, T-47-D, ZR-75-1 human breast cancer cell lines are dependent on oestrogen for growth but can adapt to grow during long-term oestrogen deprivation. This serves as a model for identification of therapeutic targets in endocrine-resistant breast cancer. Methods: An overlooked complication of this model is that it involves more than non-addition of oestrogen, and inadequate attention has been given to separating molecular events associated with each of the culture manipulations. Results: Insulin and oestradiol were shown to protect MCF-7 cells against upregulation of basal growth, demonstrating a crosstalk in the growth adaptation process. Increased phosphorylation of p44/42MAPK and c-Raf reflected removal of insulin from the medium and proliferation of all three cell lines was inhibited to a lesser extent by PD98059 and U0126 following long-term oestrogen/insulin withdrawal, demonstrating a reduced dependence on the MAPK pathway. By contrast, long-term oestrogen/insulin deprivation did not alter levels of phosphorylated Akt and did not alter the dose-response of growth inhibition with LY294002 in any of the three cell lines. The IGF1R inhibitor picropodophyllin inhibited growth of all MCF-7 cells but only in the long-term oestrogen/insulin-deprived cells was this paralleled by reduction in phosphorylated p70S6K, a downstream target of mTOR. Long-term oestrogen/insulin-deprived MCF-7 cells had higher levels of phosphorylated p70S6K and developed increased sensitivity to growth inhibition by rapamycin. Conclusions: The greater sensitivity to growth inhibition by rapamycin in all three cell lines following long-term oestrogen/insulin deprivation suggests rapamycin-based therapies might be more effective in breast cancers with acquired oestrogen resistance. Keywords Akt, breast cancer cells, endocrine resistance, insulin, MAPK, MCF-7 cells, mTOR, oestrogen, oestrogen-deprived, PI3K, picropodophyllin, rapamycin, T-47-D cells, ZR-75-1 cells

Hypersensitivity and growth adaptation of oestrogen-deprived MCF-7 human breast cancer cells

Background: Efficacy of endocrine therapy is compromised when human breast cancer cells circumvent imposed growth inhibition. The model of long-term oestrogen-deprived MCF-7 human breast cancer cells has suggested the mechanism results from hypersensitivity to low levels of residual oestrogen. Materials and methods: MCF-7 cells were maintained for up to 30 weeks in phenol-red-free medium and charcoal-stripped serum with 10-8 M 17-oestradiol and 10 g/ml insulin (stock 1), 10-8 M 17-oestradiol (stock 2), 10 g/ml insulin (stock 3) or no addition (stock 4). Results: Loss of growth response to oestrogen was observed only in stock 4 cells. Long-term maintenance with insulin in the absence of oestradiol (stock 3) resulted in raised oestrogen receptor alpha (ERlevels (measured by western immunoblotting) and development of hypersensitivity (assayed by oestrogen-responsive reporter gene induction and dose response to oestradiol for proliferation under serum-free conditions), but with no loss of growth response to oestrogen. Conclusion: Hypersensitivity can develop without any growth adaptation and therefore is not a prerequisite for loss of growth response in MCF-7 cells.