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Despite advances in the treatment of patients with early and metastatic breast cancer, mortality remains high due to intrinsic or acquired resistance to therapy.

Increased understanding of the genomic landscape through massively parallel sequencing has revealed somatic mutations common to specific subtypes of breast cancer, provided new prognostic and predictive markers, and highlighted potential therapeutic targets.

The high degree of genomic preservation evident across primary tumors and their matching PDXs over serial passaging validate them as important preclinical tools.

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Nevertheless, a more refined breast cancer classification system has been developed over the past 15 years, integrating information based on gene expression arrays.Five intrinsic clusters were initially defined – luminal A, luminal B, basal-like, human epidermal growth factor 2 (HER2) over-expressing, and the normal breast-like subtypes.For this strategy to be successful, a complete set of clinically relevant and validated biomarkers is required, along with the development of companion diagnostic tests to evaluate treatment responses [].To date, these platforms do not exist for breast cancer.In this review, we discuss the importance of these models for assessing novel therapies and understanding molecular and cellular mechanisms that contribute to tumor evolution.].

These data are prognostic and provide clinicians with information to aid decision-making, particularly with respect to those patients who would derive little benefit from chemotherapy, thereby sparing them from its potential toxicity.The precise characteristics of the latter group remains unclear.These subtypes can predict clinical behavior including overall survival, patterns of metastasis, and response to treatment [].Click here for free sample gallery and video Hegre-Art The most breathtaking visuals in the history of contemporary erotic photography.Through intimate and authentic moments of sexual pleasure, some of the world’s most beautiful women come to explore their sexuality.Evaluating new targets using established cell lines is limited by the inexact correlation between responsiveness observed in cell lines versus that elicited in the patient.