Adjuvant endocrine therapy for early breast cancer

MCAM/CD146 promotes tamoxifen resistance in breast cancer cells through induction of epithelial-mesenchymal transition, decreased ERα expression and AKT activation

Tamoxifen resistance presents a prominent clinical challenge in endocrine therapy for hormone sensitive breast cancer. However, the underlying mechanisms that contribute to tamoxifen resistance are not fully understood. In this study, we established a tamoxifen resistant MCF-7 cell line (MCF-7-Tam-R) by continuously incubating MCF-7 cells with 4-OH-tamoxifen. We found that melanoma cell adhesion molecule (MCAM/CD146), a unique epithelial-to-mesenchymal transition (EMT) inducer, was significantly up-regulated at both mRNA and protein levels in MCF-7-Tam-R cells compared to parental MCF-7 cells. Mechanistic research demonstrated that MCAM promotes tamoxifen resistance by transcriptionally suppressing ERα expression and activating the AKT pathway, followed by induction of EMT. Elevated MCAM expression was inversely correlated with recurrence-free and distant metastasis-free survival in a cohort of 4142 patients with breast cancer derived from a public database, particularly in the subgroup only treated with tamoxifen. These results demonstrate a novel function of MCAM in conferring tamoxifen resistance in breast cancer. Targeting MCAM might be a promising therapeutic strategy to overcome tamoxifen resistance in breast cancer patients.

Influence of patient and treatment factors on adherence to adjuvant endocrine therapy in breast cancer

PURPOSE/OBJECTIVES

To comprehensively assess the patient and illness or treatment factors that may predict nonadherence to adjuvant endocrine therapy and to explore whether an interaction occurs between these factors in women with breast cancer.

DESIGN

Repeated-measures design.

SETTING

The Outpatient Services of the Women's Cancer Program at the University of Pittsburgh Cancer Institute and participants' homes.

SAMPLE

91 women with early-stage breast cancer who received endocrine therapy.

METHODS

Adherence was assessed continuously for the first 18 months of endocrine therapy. Patient and illness or treatment factors were assessed at four time points (Time 1 to Time 4). Time 1 (baseline) was within two weeks prior to the initiation of endocrine therapy. Times 2-4 occurred at six-month intervals, as many as 18 months after Time 1.

MAIN RESEARCH VARIABLES

Adherence, patient factors, and illness or treatment factors.

FINDINGS

Adherence to endocrine therapy declined significantly during the first 18 months of treatment in women with breast cancer. The presence of negative mood and symptoms before starting treatment predicted nonadherence to endocrine therapy over time. Perceptions of financial hardship, symptoms, disease stage, and more complex medication regimens intensified the effect of negative mood on adherence over time.

CONCLUSIONS

Women with breast cancer may be at risk for nonadherence to prescribed endocrine therapy if they experience depression or anxiety and symptoms prior to initiating therapy.

IMPLICATIONS FOR NURSING

Oncology nurses should be alert to women with breast cancer who are depressed or anxious or who are experiencing symptoms. Management of negative mood and symptoms may result in better adherence.

A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records data

Multistate models are used to characterize individuals' natural histories through diseases with discrete states. Observational data resources based on electronic medical records pose new opportunities for studying such diseases. However, these data consist of observations of the process at discrete sampling times, which may either be pre-scheduled and non-informative, or symptom-driven and informative about an individual's underlying disease status. We have developed a novel joint observation and disease transition model for this setting. The disease process is modeled according to a latent continuous-time Markov chain; and the observation process, according to a Markov-modulated Poisson process with observation rates that depend on the individual's underlying disease status. The disease process is observed at a combination of informative and non-informative sampling times, with possible misclassification error. We demonstrate that the model is computationally tractable and devise an expectation-maximization algorithm for parameter estimation. Using simulated data, we show how estimates from our joint observation and disease transition model lead to less biased and more precise estimates of the disease rate parameters. We apply the model to a study of secondary breast cancer events, utilizing mammography and biopsy records from a sample of women with a history of primary breast cancer.

Influence of patient and treatment factors on adherence to adjuvant endocrine therapy in breast cancer

PURPOSE/OBJECTIVES

To comprehensively assess the patient and illness or treatment factors that may predict nonadherence to adjuvant endocrine therapy and to explore whether an interaction occurs between these factors in women with breast cancer.

DESIGN

Repeated-measures design.

SETTING

The Outpatient Services of the Women's Cancer Program at the University of Pittsburgh Cancer Institute and participants' homes.

SAMPLE

91 women with early-stage breast cancer who received endocrine therapy.

METHODS

Adherence was assessed continuously for the first 18 months of endocrine therapy. Patient and illness or treatment factors were assessed at four time points (Time 1 to Time 4). Time 1 (baseline) was within two weeks prior to the initiation of endocrine therapy. Times 2-4 occurred at six-month intervals, as many as 18 months after Time 1.

MAIN RESEARCH VARIABLES

Adherence, patient factors, and illness or treatment factors.

FINDINGS

Adherence to endocrine therapy declined significantly during the first 18 months of treatment in women with breast cancer. The presence of negative mood and symptoms before starting treatment predicted nonadherence to endocrine therapy over time. Perceptions of financial hardship, symptoms, disease stage, and more complex medication regimens intensified the effect of negative mood on adherence over time.

CONCLUSIONS

Women with breast cancer may be at risk for nonadherence to prescribed endocrine therapy if they experience depression or anxiety and symptoms prior to initiating therapy.

IMPLICATIONS FOR NURSING

Oncology nurses should be alert to women with breast cancer who are depressed or anxious or who are experiencing symptoms. Management of negative mood and symptoms may result in better adherence.

Cancer therapy disparity: unequal access to breast cancer therapeutics and drug funding in Canada

Adjuvant therapy has made a significant contribution in reducing breast cancer-specific mortality. Standard chemotherapeutics and tamoxifen have been the mainstay treatment for years, but recent clinical evidence supports the use of novel small-molecule therapy and aromatase inhibitor therapy in selected settings, challenging not only the traditional paradigm of breast cancer treatment, but also provincial funding of oncologic care across Canada. The disparity in access to aromatase inhibitor therapy for postmenopausal women with early-stage hormone-sensitive breast cancer across Canada is highlighted as an example.

Combining computational and biochemical studies for a rationale on the anti-aromatase activity of natural polyphenols

Aromatase, an enzyme of the cytochrome P450 family, is a very important pharmacological target, particularly for the treatment of breast cancer. The anti-aromatase activity of a set of natural polyphenolic compounds was evaluated in vitro. Strong aromatase inhibitors including flavones, flavanones, resveratrol, and oleuropein, with activities comparable to that of the reference anti-aromatase drug aminoglutethimide, were identified. Through the application of molecular modeling techniques based on grid-independent descriptors and molecular interaction fields, the major physicochemical features associated with inhibitory activity were disclosed, and a putative virtual active site of aromatase was proposed. Docking of the inhibitors into a 3D homology model structure of the enzyme defined a common binding mode for the small molecules under investigation. The good correlation between computational and biological results provides the first rationalization of the anti-aromatase activity of polyphenolic compounds. Moreover, the information generated in this approach should be further exploited for the design of new aromatase inhibitors.