HER2 status in breast cancer--an example of pharmacogenetic testing

Signaling pathways in breast cancer: therapeutic targeting of the microenvironment

Breast cancer is the most common cancer in women worldwide. Understanding the biology of this malignant disease is a prerequisite for selecting an appropriate treatment. Cell cycle alterations are seen in many cancers, including breast cancer. Newly popular targeted agents in breast cancer include cyclin dependent kinase inhibitors (CDKIs) which are agents inhibiting the function of cyclin dependent kinases (CDKs) and agents targeting proto-oncogenic signaling pathways like Notch, Wnt, and SHH (Sonic hedgehog). CDKIs are categorized as selective and non-selective inhibitors of CDK. CDKIs have been tried as monotherapy and combination therapy. The CDKI Palbocyclib is now a promising therapeutic in breast cancer. This drug recently entered phase III trial for estrogen receptor (ER) positive breast cancer after showing encouraging results in progression free survival in a phase II trials. The tumor microenvironment is now recognized as a significant factor in cancer treatment response. The tumor microenvironment is increasingly considered as a target for combination therapy of breast cancer. Recent findings in the signaling pathways in breast cancer are herein summarized and discussed. Furthermore, the therapeutic targeting of the microenvironment in breast cancer is also considered.

Cost effectiveness of cytotoxic and targeted therapy for metastatic breast cancer: a critical and systematic review

Breast cancer is the leading cancer type diagnosed among women in Western countries. Despite great advances in cancer therapies, many of these patients develop non-curable metastases. The objective of cancer treatment in the metastatic setting is mainly to control symptoms and to prolong survival. The selection of the optimal chemotherapeutic regimen is affected by performance status, tumour biology, site and extent of the disease and the exposure to prior therapies. Recent developments in new kinds of cancer drugs have contributed not only to immense progress in clinical outcomes but also to dramatically increased treatment-related health costs. Cost-effectiveness analysis is a type of economic evaluation that compares costs and health outcomes of alternative intervention strategies in a systematic way. In this review, a systematic literature search was performed and the evidence on the cost effectiveness of conventional chemotherapy and targeted therapy for metastatic breast cancer was explored. Cost-effectiveness/-utility analysis of treatment regimens for metastatic breast cancer were identified using literature and reference searches (MEDLINE). Published reports on conventional and targeted cancer therapies were scrutinized and incremental cost-effectiveness ratios (ICERs) were abstracted. Furthermore, the quality of reporting, as well as methodological and modeling issues, were extensively discussed. From full-text article reviews, six cost-effectiveness analyses on conventional therapies and seven studies on targeted therapies were included. Eight analyses were conducted in European countries, three in the US and two in Canada. The economic models were primarily (69%) based on clinical trial data. Results from sensitivity analyses and study perspectives were reported by all studies. Discount rates were mentioned in five articles (39%). The methods of reporting costs and effects varied considerably, as did trial design across conventional chemotherapies, which made it difficult to compare those analyses. The pharmacoeconomic studies came to different conclusions. The actual clinical evidence does not suggest one conventional chemotherapy regimen as superior. Studies on cytotoxic agents showed mainly favourable cost-effectiveness ratios. Targeted therapies indicated both favourable and non-favourable ratios. Currently, trastuzumab is the only antibody-based targeted therapy that is established in the clinic for the metastatic setting.

Multipathway model enables prediction of kinase inhibitor cross-talk effects on migration of Her2-overexpressing mammary epithelial cells

Small-molecule kinase inhibitors often modulate signaling pathways other than the one targeted, whether by direct "off-target" effects or by indirect "pathway cross-talk" effects. The presence of either or both of these classes of complicating factors impedes the predictive understanding of kinase inhibitor consequences for cell phenotypic behaviors involved in drug efficacy responses. To address this problem, we offer an avenue toward comprehending how kinase inhibitor modulations of cell signaling networks lead to altered cell phenotypic responses by applying a quantitative, multipathway computational modeling approach. We show that integrating measurements of signals across three key kinase pathways involved in regulating migration of human mammary epithelial cells, downstream of ErbB system receptor activation by epidermal growth factor (EGF) or heregulin (HRG), significantly improves prediction of cell migration changes resulting from treatment with the small-molecule inhibitors 2-(4-morpholinyl)-8-phenyl-4H-1-benzopyran-4-one (LY294002) and 2'-amino-3'-methoxyflavone (PD98059) for both normal and HER2-overexpressing cells. These inhibitors are primarily directed toward inhibition of phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase kinase (MEK) but are known to exhibit off-target effects; moreover, complex cross-talk interactions between the PI3K/Akt and MEK/extracellular signal-regulated kinase (Erk) pathways are also appreciated. We observe here that treatment with LY294002 reduces migration of HRG-stimulated cells but not EGF-stimulated cells, despite comparable levels of reduction of Akt phosphorylation under both conditions, demonstrating that the target inhibition effect is not unilaterally predictive of efficacy against cell phenotypic response. Consequent measurement of levels of Erk and p38 phosphorylation, along with those for EGF receptor phosphorylation, after LY294002 treatment revealed unintended modulation of these nontargeted pathways. However, when these measurements were incorporated into a partial least-squares regression model, the cell migration responses to treatment were successfully predicted. Similar success was found for the same multipathway model in analogously predicting PD98059 treatment effects on cell migration. We conclude that a quantitative, multipathway modeling approach can provide a significant advance toward comprehending kinase inhibitor efficacy in the face of off-target and pathway cross-talk effects.