While the genomic predictors are of current interest, the evolution of patients’ characteristics and treatments requires a permanent optimization. Several studies have attempted to report these genomic predictors. Frati et al. [14] established a genetic profile involved in the chemoresistance and extrapolated the drug sensitivity to breast cancer. ER+/HER−/low gene expression proliferation tumors are categorized as chemoresistant, whereas tumors with an ER−, HER2+, or ER+/HER2-/high proliferation gene expression profile can be categorized as chemosensitive tumors. Moreover, there is scientific evidence of chemoresistance in patients with ER+/HER2−/low proliferation tumors when treated with endocrine therapy, and evidence exists among oncologists to allow clinical use of gene expression tests to identify patients who do not require chemotherapy among node-negative ER+ patients [15]. A genomic predictor combining ER status, predicted chemoresistance, predicted chemosensitivity, and predicted endocrine sensitivity, identified patients with a high probability of survival following taxane and anthracycline chemotherapy.

Epigenetics and RNA-related markers are promising for the explanation of dysregulation cell pathways involved in cancer. Indeed, miRNA profiling has been convincingly demonstrated to classify tumor and non-tumor samples, sensitivity/resistance to drugs therapies, etc. Thus, evidence of miRNA-mediated reversal of multidrug resistance in human cancer [16] warrants further studies of miRNA-based approaches for treating drug-resistant tumors. Some specific results indicated that miRNA-125b played an important role in chemotherapeutic resistance in breast cancer cells, specifically in primary breast cancer cells. Experiments were carried out on breast cellular models showing that the expression of miR-125b decreased 5-FU-induced cytotoxicity and increased 5-FU resistance under various concentrations of 5-FU treatment in MCF-7 cells [17].

It is well known that treatment efficacy is optimal for one certain genotype group, while a similar drug is most efficacious for another genotype group, so that therapy can be personalized to achieve maximum success in patient care. If a polymorphism is identified to be associated with drug dosing, physicians can change clinical care using genotype in the dosing algorithm. Likewise, if a polymorphism is associated with a serious adverse event, an alternative treatment could be selected for such patients [18].

The aim of pharmacogenetics and the main targeted drug therapy of breast cancer are to determine whether there is a correlation between genetic polymorphism, such as in targeted molecular structures, and response to treatment or the development of drug-associated toxicity [19, 20].

Table 14.4 compiles the genes that have shown significant variability according to each drug that can be prescribed in breast cancer. These data have been obtained through www.​pharmagkb.​com database, which stratify the validated SNP according to clinical impact and outcome, FDA mandatory label, and other parameters. The majority of the genes are related to transporters, CYP450 alleles, and specific targeted therapies.

In the context of chemoresistance, among others, special attention should be paid to drug transporters, including ATP-binding cassette (ABC) transporters and solute carrier (SLC) transporters, which are also expressed at cancer cells.

The ABC transporters are a family of large proteins in membranes and are able to transport a variety of compounds including metabolites and drugs through membranes at the cost of ATP hydrolysis. Physiological functions of ABC transporters include the transport of lipids, bile salts, toxic compounds, and peptides for antigen presentation or other purposes, such as ion channel regulation. The human genome contains 48 ABC transporter genes; at least 14 of these are reportedly associated with heritable human diseases [21].

Commonly, polymorphisms in P-glycoprotein or ABCB1, ABCG2 have been widely described as affecting treatments of different diseases [22]. Moreover, the potential impact of ABCC11 genetic polymorphisms on the physiological function, breast cancer risk, and patients’ response to nucleoside-based chemotherapy has been described [13].

An important discovery has been the breast cancer resistance protein (BCRP), whose expression in the liver is needed for in vitro to in vivo extrapolation of the biliary clearance of a BCRP substrate drug. A polymorphic variant C421A (rs2231142) allele was significantly lower in breast cancer patients than that in the wild-type livers [22]. Currently, there are no arguments to determine the pharmacogenetic status of HER2 to individualize trastuzumab treatment [9]. The searching of biomarkers of trastuzumab resistance are focused on several mechanisms—i.e., deficiency of phosphatase and tensin homologue and activation of phosphoinositide 3-kinase result in greater activity of the Akt-mammalian target of rapamycin signal transduction pathway [23]. Also, the overexpression of other surface receptors, such as insulinlike growth factor, provides alternative growth factor signaling and is related to lower trastuzumab sensitivity [24].

Genome-wide associations (GWAS) based on large prospective randomized trials have the potential to greatly elucidate the genomic basis for optimizing drug efficacy and reducing toxicity. The studies on breast cancer have been mainly focused on how both disease susceptibility loci and risk prediction may lead to a better understanding of the biological mechanism for BC in order to improve prevention, early detection, and treatment. They are of clinical importance and may explain an appreciable proportion of the genetic variance in BC risk. There are few studies that specifically describe results affecting chemoresistance [25] and metastasis [26]. The power of GWAS may be increased by enlarging the number of samples in both the cases and the controls and by identifying clinical and molecular subtypes [27]. There is a long way to go toward improving the controversial results of different GWAs, and thus a novel multi-SNP GWAS analysis method called pathways of distinction analysis was developed. This method includes GWAS data and pathway-gene and gene-SNP associations to identify pathways that could permit the distinction of cases from controls [28]. Thus, new GWAS in breast cancer generation of large-scale association studies, in combination with replication analyses and multiple scans, could have the potential to identify many more loci.

In order to further exploit the transcriptome and genome data, it is usual to carry out an integrated analysis of transcriptome, proteomic, and metabolomic data, observing how this corresponds to the varying physiological and phenotype status.

One of the main aspects studied by transcriptomic studies is the epithelial to mesenchymal transition (EMT) that represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that is associated with a higher cell motility as well as enhanced chemoresistance and cancer stemness [29]. This issue will be developed further in the discussion below on metastasis of breast cancer. Moreover, some specific markers have been determined to impact the chemoresistance on breast cancer patients treated with endocrine therapy. The steroid coactivator protein SRC-1 drives tumor adaptability through ADAM22, a non-protease member of the ADAM family of disintegrins [30]. Taxol and etoposide resistance have been demonstrated to be mediated by TMEM45A [31].

Based on gene expression profiles, or proteomics of three or four validated biomarkers, it is apparent that there are multiple subtypes with different clinical characteristics, clinical courses, and sensitivities to existing therapies (ER, PR, HER2, and Ki-67 represent critical molecular markers that identify the largest molecular subsets and therapeutic decisions [32]). Current sensitivity levels may allow whole-cell proteomics approaches and subcellular fractions to now be sequenced at the protein level with success [33, 34].

Important molecules to be determined for classification are the metabolic enzymes and metabolism mediators that affect individually the impact of drug therapy [12, 18]. In particular, some authors have found important metabolism enzymes required for ketone body production that are highly upregulated within cancer-associated fibroblasts. L-Lactate and ketone body metabolisms are critical for tumor progression and metastasis [35].

There are nutrigenetic testing companies, which provide DNA-based nutritional advice analyzing the individual genome of patients or healthy people. The validity of biomarkers is not accurate in all cases and requires expert counseling [36]. Some authors have studied the impact of single nucleotide polymorphism, copy number, epigenetic events, and transcriptomic homeostasis as factors influencing the response to food components and breast cancer risk, among them the dietary n-3 fatty acids [37, 38]. There are also foods that can induce or inhibit the action of CYP450 enzymes involved in metabolism of drugs.

Lipid pathway analysis is acquiring importance in many clinical areas, as diet-controlled components, as metabolic mediators, and even as therapeutic molecules for breast cancer chemoresistance [39, 40]. Moreover, it is known that oxidation of membrane phospholipids is associated with cancer. Oxyradical damage to phospholipids results in the production of reactive aldehydes that adduct proteins and modulate their carcinogenic function [41].