Current Landscape of Targeted Therapies for Hormone-Receptor Positive, HER2 Negative Metastatic Breast Cancer.

The majority of deaths from MBC are in patients with hormone receptor (HR) positive, HER2 negative disease. Endocrine therapy (ET) remains the backbone of treatment in these cases, improving survival and quality of life. However, treatment can lose effectiveness due to primary or acquired endocrine resistance. Analysis of mechanisms of ET resistance has led to the development of a new generation of targeted therapies for advanced breast cancer. In addition to anti-estrogen therapy with selective estrogen receptor modulators, aromatase inhibitors, and/or selective estrogen receptor degraders, combinations with cyclin dependent kinase (CDK) 4/6 inhibitors have led to substantial progression free survival (PFS) improvements in the first and second line settings. While the PI3K/AKT/mTOR pathway is known to be an important growth pathway in HR positive breast cancer, PI3K inhibitors have been disappointing due to modest effect sizes and significant toxicity. The mTOR inhibitor everolimus significantly improves progression free survival when added to ET, and recent studies have improved supportive care allowing less toxicity. While these combination targeted therapies improve outcomes and often delay initiation of chemotherapy, long term overall survival data are lacking and data for the ideal strategy for sequencing these agents remains unclear. Ongoing research evaluating potential biomarkers and mechanisms of resistance is anticipated to continue to improve outcomes for patients with HR positive metastatic breast cancer. In this review, we will discuss management and ongoing challenges in the treatment of advanced HR positive, HER2 negative breast cancer, highlighting single agent and combination endocrine therapies, targeted therapies including palbociclib, ribociclib, abemaciclib, and everolimus, and sequencing of therapies in the clinic.

Structure-based drug design: from nucleic acid to membrane protein targets.

The in silico methods for drug discovery are becoming increasingly powerful and useful. That, in combination with increasing computer processor power, in our case using a novel distributed computing grid, has enabled us to greatly enhance our virtual screening efforts. Herein we review some of these efforts using both receptor and ligand-based virtual screening, with the goal of finding new anti-cancer agents. In particular, nucleic acids are a neglected set of targets, especially the different morphologies of duplex, triplex, and quadruplex DNA, many of which have increasing biological relevance. We also review examples of molecular modeling to understand receptors and using virtual screening against G-protein coupled receptor membrane proteins.