Abstract
In recent years, the study of genomic alterations and protein expression involved in the pathways of breast cancer carcinogenesis has provided an increasing number of targets for drugs development in the setting of metastatic breast cancer (i.e., trastuzumab, everolimus, palbociclib, etc.) significantly improving the prognosis of this disease. These drugs target specific molecular abnormalities that confer a survival advantage to cancer cells. On these bases, emerging evidence from clinical trials provided increasing proof that the genetic landscape of any tumor may dictate its sensitivity or resistance profile to specific agents and some studies have already showed that tumors treated with therapies matched with their molecular alterations obtain higher objective response rates and longer survival. Predictive molecular biomarkers may optimize the selection of effective therapies, thus reducing treatment costs and side effects. This review offers an overview of the main molecular pathways involved in breast carcinogenesis, the targeted therapies developed to inhibit these pathways, the principal mechanisms of resistance and, finally, the molecular biomarkers that, to date, are demonstrated in clinical trials to predict response/resistance to targeted treatments in metastatic breast cancer.
Highlights
Breast cancer (BC) represents the most common cancer among women worldwide, with an estimated incidence of 246,660 new cases (29% of all sites cancers) and 40,450 estimated deaths (14% of all sites) in 2016 in the United States [1]
This review offers an overview of the main molecular pathways involved in breast carcinogenesis, the targeted therapies developed to inhibit these pathways, the principal mechanisms of resistance and, the molecular biomarkers that, to date, are demonstrated in clinical trials to predict response/resistance to targeted treatments in metastatic breast cancer
The revolutionary era of targeted therapy shifted the classic paradigm of BC treatment from a “stratified oncology” based on pathological and clinical parameters [9] to a “personalized medicine” based on the match between the targeted drug and the molecular alteration that confers to cancer cells a survival advantage [10]
Summary
Breast cancer (BC) represents the most common cancer among women worldwide, with an estimated incidence of 246,660 new cases (29% of all sites cancers) and 40,450 estimated deaths (14% of all sites) in 2016 in the United States [1]. BC is a heterogeneous disease that develops and progresses from alterations that take place in the genes that govern cell growth, proliferation and differentiation [7,8]. In the last two decades, the increasing knowledge on genomic abnormalities associated with gain of function or downstream signal activation involved in the BC evolution, allowed to find new therapeutic approaches “tailored” on the molecular alteration identified. The revolutionary era of targeted therapy shifted the classic paradigm of BC treatment from a “stratified oncology” based on pathological and clinical parameters [9] to a “personalized medicine” based on the match between the targeted drug and the molecular alteration that confers to cancer cells a survival advantage [10]. Swci.a2d01a7y, 1s8,, t8h5 e main challenge remains the identification of predictive biomarke2rosf f2o4 r the selection of the optimal treatment, in order to spare patients from the side effects associated with treatmorenint athnedctoontmexitnoimf cizlienitchael torviaelsraalnl dco, snto[w1a1d].ays, the main challenge remains the identification of Tphreids ircetivvieewbioamimarsketorsrfeoarstshuemseeletchteiomn oafinthme oopleticmualal rtrpeaattmhwenaty, isninorvdoelrvteodspinarBeCpactaierncitns ofrgoemnethsies, the targetseiddeteThfhefeirscatrpseiavesisesowdceiaavitmeeldsowtpoeitrdheattsorseuaintmmheiebtnhitteatmnhdoasitnoe mmpaointlehimcwuilazaeyrstph,aetthhoewveparryaislnliccniovpsotall[v1me1d]e.icnhBaCnicsamrcsinoofgreenseissitsa,nthcee and, finalltya,rtgheetemd othleercaupliaers bdieovmeloaprkedertsotihnahti,btitothdoastee,phatahvweadyes,mthoenpsrtrinactiepdaltompecrheadniicstmres sopf orenssiset/arnecseisatnadn,ce to targetfeindaltlrye,atthme emnotlse.cular biomarkers that, to date, have demonstrated to predict response/resistance to targeted treatments
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