No description available.

No description available.

Introduction Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive (ER+) post-menopausal breast cancer. However, response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. There is a need to identify pre- or early on-treatment biomarkers to predict sensitivity which outperform those currently used, in a move towards stratified treatments and improved patient care. Given the heterogeneity known to exist in the breast cancer population, and the limited availability of matched pre- and on-treatment clinical material, this study also sought to develop novel data integration approaches allowing for the inclusion of similar previously published datasets, thus maximising the power of this study. Experimental Design Pre- and on-treatment (at 14 days and 3-months) biopsies were obtained from 34 postmenopausal women with ER+ breast cancer receiving 3 months of neoadjuvant letrozole. Illumina Beadarray gene expression data from these samples were combined with Affymetrix GeneChip data from a similar published study (n=55) and crossplatform integration approaches were evaluated. Dynamic clinical response was assessed for each patient from periodic 3D ultrasound measurements during treatment. Results Despite intrinsic differences between different microarray technologies, suitably similar studies can be directly integrated for robust and meaningful meta-analysis with improved statistical power. After mapping probe sequences to Ensembl genes it was demonstrated that, ComBat and cross platform normalisation (XPN), significantly outperform mean-centering and distance-weighted discrimination (DWD) in terms of minimising inter-platform variance. In particular it was observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. A pipeline for the successful integration of microarray datasets from different platforms was developed. Using this approach a classifier of clinical response to endocrine therapy in the neoadjuvant setting based on the expression of 4 genes was developed which predicted response with 96% and 91% accuracy in training (n=73) and independent validation (n=44) datasets respectively. An early on-treatment biopsy was found to improve predictive power in addition to pre-treatment alone. Conclusions Using a novel data integration approach developed as part of this study, a model comprising 4 novel biomarkers for accurate and robust prediction of clinical response to AIs by two weeks of treatment has been generated and validated. On-going work will investigate the applicability to other anti-estrogens, and the adjuvant setting and will assess the potential for a new therapy response test.

When women are faced with the diagnosis and treatment options for their care, they have high a need for information that persists throughout the course of their illness. When information needs are met, women are able to make informed decisions regarding their care, have increased quality of life, and cope better with their illness. The objective of this study was to identify the information needs of postmenopausal women with early stage breast cancer making treatment decisions regarding endocrine therapy. An integrative review of research was conducted to collate and describe the information needs assessment methodologies used to identify information needs for women with breast cancer. Based on this review and our long-term goal of identifying a list of questions or information needs of women at this stage of their cancer treatment, we conducted a qualitative descriptive study to identify information needs and interviewed 17 post-menopausal women with early stage breast cancer and 4 healthcare providers. Women were asked to describe the questions they had or the information that they needed when endocrine therapy became part of their care. The healthcare providers described the information that they felt was important for women to know in regard to endocrine therapy. A list of 91 questions regarding endocrine therapy was identified; including information needs related to side effects, drug characteristics, financial cost, and survival/recurrence. Most women were not aware that they had a choice about the different types of endocrine treatment and often followed the physician’s recommendations. This study supports the assertion that postmenopausal women with breast cancer wish to be informed that they have a choice and desire information to make the best personal choice in collaboration with the physician. Healthcare professionals need to be aware of both the common and individual patients’ information needs and present options to assist women making the best decisions about their care. / Thesis (Master, Nursing) -- Queen's University, 2010-06-25 15:21:29.869

Women undergoing endocrine therapy for breast cancer often experience hot flashes. As part of a performance improvement project, 14 patients were surveyed to determine who is at risk for hot flashes during endocrine therapy. This information encourages the education of patients, increases compliance with therapy, and improves quality of life.

Bakgrund: Bröstcancer är den vanligaste cancersjukdomen bland kvinnor idag och var tionde kvinna drabbas någon gång av sjukdomen. Genetiska faktorer kan öka risken för att drabbas av bröstcancer. Tidig menarche och sen menopaus hör även de till riskfaktorerna. De behandlingsmetoder för bröstcancer som finns tillgängliga är kirurgisk behandling, strålbehandling, cytostatika, hormonpreparat samt annan medicinsk behandling. Indikationen för hormonell behandling är om tumörcellerna har östrogenpositiva receptorer på sin cellyta. Hormonell behandling innefattar i huvudsak Tamoxifen och aromatashämmare. Kvinnor som genomgår en behandling med hormonpreparat kan uppleva typiska biverkningar som liknar de som uppkommer vid menopausen såsom vallningar och svettningar, torra och sköra slemhinnor i underlivet, fatigue, nedsatt sexuell lust samt dysparenui (smärta vid samlag). Sexualiteten berör våra djupaste känslor och bidrar till njutning och lycka. Det sexuella behovet är individuellt men är en essentiell del i människors hälsa. Vårdpersonal måste ha kunskap om sexualitet för att kunna ge denna patientgrupp råd om hur man kan främja den sexuella hälsan under behandlingsperioden. Livskvalitet är ett individuellt fenomen. Samma sjukdom, symtom och behandling kan därför upplevas olika av olika individer. Livskvalitet beror på många faktorer, varav sexualiteten är en av dem.Syfte Syftet var att undersöka hur kvinnor som får hormonell behandling mot bröstcancer upplevde sin sexualitet. Metod: En forskningsöversikt gjordes i enlighet med Forsberg och Wengström (2008). Totalt inkluderades 14 vetenskapliga artiklar i studiens resultat. Inklusionskriterier var att artiklarna skulle vara originalartiklar samt granskade enligt Ulrich. Resultat: Resultatet visade att den hormonella behandlingen påverkade kvinnans sexualitet. Hormonpreparaten gav biverkningar i form av exempelvis dysparenui, nedsatt sexuell lust samt torra slemhinnor i vagina och detta ledde ofta till att kvinnornas sexuella aktivitet minskade. Sjuksköterskan ansåg att diskussionen om sexualitet var en del av sjuksköterskans profession. Trots detta togs ämnet inte upp i den omfattning det borde vilket delvis kan bero på okunskap och osäkerhet inom området. En försämrad sexuell hälsa bidrog även till en sämre livskvalitet hos patienterna. Slutsats: Hormonell behandling för kvinnor med bröstcancer påverkar kvinnans sexualitet i olika grad. Biverkningar av behandlingen kan leda till att kvinnan får en försämrad livskvalitet. Vårdpersonal måste ha kunskap om hur behandling och diagnos kan påverka kvinnans sexulitet. Nyckelord: Breast neoplasms, Endocrine Therapy, Sexuality, Nursing, Quality of Life

Introduction Recent advances in microarray technology have allowed more understanding of the complex molecular biology of breast cancer. The traditional prognostic information afforded by hormone receptor status and pathology variables is being supplemented and superseded by gene signatures predictive of risk of recurrence and response to treatments. Approximately 75% of breast cancers are oestrogen receptor positive (ER+) and can be treated by drugs that block oestrogen production such as letrozole. However not all ER+ tumours respond and even those that initially respond can develop resistance. Treating patients with neoadjuvant letrozole affords a unique opportunity to sample the same tumour in vivo at different time points reducing any potential inter-patient and inter-tumour variability. The molecular effects of drugs can be assessed long before clinical outcome is apparent. Underlying genetic differences or characteristics of the patient, tumour or sample may affect the molecular response to treatment. This project set out to use sequential patient-matched samples to evaluate molecular changes in breast tumours in the presence or absence of endocrine treatment in different subtypes, defined by histology or mutation status and to assess molecular variation between primary tumour and nodal metastasis. Methods RNA was extracted and processed to generate whole transcriptome Illumina Beadarray gene expression data from four unique cohorts of patients. Clinical data on treatments, recurrence and survival was collected from medical records. The first cohort compared 25 breast cancer patients with matched samples at diagnosis and at surgery, 14-35 (median 23) days later, with no intervening treatment; with 36 patients treated with neoadjuvant letrozole. A PCR assay to detect 8 known PIK3CA mutations and assessment of PTEN status was performed at both the primary and secondary event in a second cohort of 120 patients with endocrine treated disease who relapsed with either recurrence, lymph node metastases, a new second primary or progression of disease on primary endocrine therapy. The third cohort compared the molecular response to neoadjuvant letrozole in 14 patients with invasive lobular cancer (ILC) and 14 patients with invasive ductal cancer (IDC). A fourth cohort of women with node positive disease at diagnosis were assessed for variations in gene expression profiles between primary tumour and synchronous metastatic axillary lymph nodes (68 samples from 31 patients). Results The genomic profile of the no intervening treatment cohort did not differ significantly. Some changes in inflammatory genes were evident. This reassures us that changes seen during treatment are truly due to drug effect. This validates the use of a second biopsy to explore prediction of response. PIK3CA mutation status is maintained in the majority of patients with endocrine resistant disease and changed in only 15.7%. Where there was a change in PIK3CA this was significantly more likely to be a second primary breast cancer rather than a recurrence or progression of the primary cancer. PTEN status was also maintained in most patients. This does not support the theory that acquisition of a PIK3CA mutation is responsible for developing endocrine resistance. Novel PI3K inhibitor drugs may still be suitable in endocrine-resistant disease if activation of the pathway develops by other mechanisms. Consistent with previous studies, significant molecular differences were observed between ILC and IDC pre-treatment. Over half of these molecular differences were maintained after 3 months of letrozole. However, changes over time in individual tumours in response to letrozole were highly consistent in both ILC and IDC. When comparing primary with synchronous metastatic nodes only 39% of tumours clustered together with their matched primary or node. The molecular subtype of the node was often a poorer prognosis than the primary. There were also differences in subtype between nodes in a small cohort of patients with 2 involved nodes. Conclusions We have demonstrated that neoadjuvant window studies are a valid model for assessment of drug effects and evaluated differences in histology and mutation status. Endocrine resistance in breast cancer is rarely related to acquisition of PIK3CA mutations. Synchronous lymph node metastases can differ greatly from their matched primary. These findings are highly relevant when considering prescribing (neo)/adjuvant therapy and have significantly improved our understanding of breast cancer as we strive towards personalised medicine.

Indiana University-Purdue University Indianapolis (IUPUI) / Oral endocrine therapy (OET) is standard therapy for millions of estrogen receptor-positive breast cancer survivors (ER+BCS). OET reduces recurrence, mortality, and metastasis. ER+BCS often do not take their OET as recommended due to adverse side effects. The purpose of this dissertation was to develop an explanatory framework of decision making by women with ER+ breast cancer who report experiencing side effects from OET. This project was comprised of two components. The first component was a systematic review with three main findings: (1) side effects negatively impact OET non-adherence, (2) there is an absence of decisional supports provided to or available for ER+BCS who are experiencing OET side effects,, and (3) ER+BCS likely have unmet decisional needs related to OET. The second component was a grounded theory study that included 31 ER+BCS reporting OET side effects. During a single semi-structured interview, participants described the experience of OET over time. This study produced two qualitatively derived projects. First, a theoretical framework was developed that depicted four stages through which the experience of OET decision making unfolded. The stages were (1) being told what I need to do to live, (2) doing what I need to do to live, (3) enduring what I need to do to live, and (4) deciding how I want to live. Second, a typology was developed that depicted six sources of external decisional supports (healthcare providers, husbands, other breast cancer survivors, friends and family, the internet and other media sources, and God) that met four types of decisional needs (information about OET and its side effects, in-depth discussions about side effects, help in managing side effects, and emotional support). Findings can be used to develop interventions, such as decision aids, to promote quality decision making in women experiencing OET side effects.

Estrogen receptor (ER)-positive breast cancer is responsive to a number of targeted therapies used clinically. Unfortunately, the continuous application of any targeted therapy often results in resistance to the therapy. Our ultimate goal is to use mathematical modelling to optimize alternating therapies that not only decrease proliferation but also stave off resistance. Toward this end, we measured levels of key proteins and proliferation over a 7-day time course in ER-positive MCF7 breast cancer cells. Treatments included endocrine therapy, either estrogen deprivation, which mimics the effects of an aromatase inhibitor, or fulvestrant, an ER degrader. These data were used to calibrate a mathematical model based on key interactions between ER signaling and the cell cycle. We show that the calibrated model is capable of predicting the combination treatment of fulvestrant and estrogen deprivation. Further, we show that we can add a new drug, palbociclib, to the model by measuring only two key proteins, c-Myc and hyperphosphorylated RB1, and adjusting only parameters associated with the drug. The model is then able to predict the combination treatment of estrogen deprivation and palbociclib. Then we added the dynamics of estrogen concentration in the medium into the model and extended the short-term model to a long-term model. The long-term model can simulate various mono- or combination treatments at different doses over 28 days. In addition to palbociclib, we add another Cdk4/6 inhibitor to the model, abemaciclib, which can induce apoptosis at high concentrations. Then the model can match the effects of abemaciclib treatment at two different doses and also capture the apoptosis effects induced by abemaciclib. After calibrating the model to these different treatment conditions, we used the model to explore the synergism among these different treatments. The mathematical model predicts a significant synergism between palbociclib or abemaciclib in combination with fulvestrant. And the predicted synergisms are verified by experiments. This critical synergism between these Cdk4/6 inhibitors and endocrine therapy could reflect the reason that Cdk4/6 inhibitors achieve pronounced success in clinic trails. Lastly, we used protein biomarkers (cyclinD1, cyclinE1, Cdk4, Cdk6 and Cdk2) and palbociclib dose-response proliferation assays to assess the difference between mono- and alternating therapy after 10 weeks of treatments. But neither the protein levels nor palbociclib dose-response show significant differences after 10 weeks of treatment. Therefore, we cannot conclude that alternating therapy delays palbociclib resistance compared with palbociclib mono-treatment after 10 weeks. Longer term experiments or other methods will be needed to uncover any difference. However, in this research we showed that a mechanism-based mathematical model is able to simulate and predict various effects of clinically-used treatments on ER-positive breast cancer cells at different time scales. And this mathematical model has the potential to explore ideas for potential drug treatments, optimize protocols that limit proliferation, and determine the drugs, doses, and alternating schedule for long term experiments. / Doctor of Philosophy / Estrogen receptors are proteins found inside breast cancer cells that are activated by the hormone estrogen. Estrogen-receptor positive breast cancer is the most common type of breast cancer and accounts for about 70% of breast cancer tumors. Endocrine therapy, which inhibits estrogen receptor signaling, and Cyclin-dependent kinase 4 and 6 (Cdk4/6) inhibitors are the preferred first-line therapy for patients with estrogen receptor-positive cancers. We built a mathematical model of MCF7 cells (an estrogen receptor-positive breast cancer cell line) in response to these standard first-line therapies. This mathematical model can capture the experimentally observed protein and cell proliferation changes in response to various treatment conditions, including different drug combinations, different doses, and different treatment durations up to 28 days. The model can then be used to look for more effective treatment possibilities. In particular, our mathematical model predicted a strong synergism between Cdk4/6 inhibitors and endocrine therapy, which could allow significant reductions in drug dosage while producing the same effect. This synergism was verified by experiments. In addition to treatment methods where one drug or combination of several drugs is used continuously, we consider alternating among various therapies in a fixed cycle. The mathematical model can help us determine which drugs and which doses might be most appropriate. Since an alternating therapy doesn't inhibit one particular target non-stop, the hope is that alternating therapies can delay the onset of drug resistance, where the drug becomes less effective or stops working completely. Unfortunately, an initial 10- week experiment to test for differences in resistance to a mono-therapy versus an alternating therapy did not show a significant difference, pointing to the need for longer experiments to see if alternating therapies can actually make a difference in resistance. Mathematical models will be important for determining the drugs, doses, and time intervals to be used in these experiments, as figuring out the best options by trial and error in such long-term experiments is not practical.

La résistance à l’hormonothérapie est un challenge majeur en clinique dans le choix du traitement chez les patientes atteintes de cancer du sein RE+ et l’activation des voies de signalisation PI3K/Akt/mTOR ou MAPK semble être impliquée dans la résistance à l’hormonothérapie. L’objectif de ce travail a été dédié à l’exploration de stratégies de réversion de la résistance à l’hormonothérapie et à l’identification de nouveaux biomarqueurs associés à cette résistance. Nous avons identifié dans des lignées résistantes à l’hormonothérapie ayant acquis l’activation endogène des voies PI3K/Akt/mTOR et MAPK, l’activation aberrante du système ErbB, pouvant être à la base de l’activation de ces deux voies de signalisation. L’inhibition d’au moins une des deux voies (par un inhibiteur de mTOR, un inhibiteur de PI3K et/ou un inhibiteur de MEK) a conduit dans la lignée sensible à une augmentation de la sensibilité au tamoxifène et au fulvestrant et dans les lignées résistantes à une restauration de la sensibilité à l’hormonothérapie. La réversion de la résistance au fulvestrant par la rapamycine a été démontrée non seulement au niveau de la prolifération cellulaire mais aussi au niveau de l’expression des gènes, explorés par une approche génomique. Par ailleurs, par une approche gènes candidats, nous avons identifié une signature de trois gènes (TACC1, NOV et PTTG1) présentant une valeur pronostique et associée à la résistance à l’hormonothérapie pouvant représenter un nouvel outil de diagnostic des patientes atteintes de cancer du sein hormono-dépendant. / Endocrine therapy resistance is one of the main challenges in the treatment of estrogen receptor positive breast cancer patients and the activation of PI3K/Akt/mTOR or MAPK signaling pathways seems to be implicated in the acquisition of the resistance. The objective of this work has been dedicated to the exploration of strategies to reverse the resistance to endocrine therapy and the identification of new biomarkers associated with this resistance. We have identified in cellular models resistant to hormone therapy, which have acquired the endogenous activation of PI3K/Akt/mTOR and MAPK pathways, the aberrant activation of the ErbB system which may be the cause of the activation of these pathways. The inhibition of at least one of these two pathways (by an mTOR inhibitor), a PI3K inhibitor) and/or a MEK inhibitor) was shown to increase sensitivity to tamoxifen and fulvestrant in the sensitive cells and to restore sensitivity to endocrine therapy in the resistant cells. The reversion of resistance to fulvestrant by rapamycin has been demonstrated not only at the cell proliferation level but also at the gene expression level explored by a genomic approach. In addition, using a candidate gene approach, we identified a signature of three genes (TACC1, NOV and PTTG1) with prognostic value and associated with resistance to endocrine therapy. These genes may represent a new diagnostic tool for patients treated with endocrine therapy.