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 Table of Contents  
REVIEW
Year : 2016  |  Volume : 2  |  Issue : 5  |  Page : 137-146

Identifying gaps and relative opportunities for discovering membrane proteomic biomarkers of triple-negative breast cancer as a translational priority


Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW 2109, Australia

Date of Submission10-Sep-2016
Date of Acceptance15-Oct-2016
Date of Web Publication24-Oct-2016

Correspondence Address:
Bhooma Venkatraman
Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, 2 Technology Place, Sydney, NSW 2109
Australia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2395-3977.192931

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  Abstract 

Triple-negative breast cancer (TNBC) remains a significant clinical and scientific challenge. The classification of TNBC is based on the lack of expression of the human epidermal growth factor 2, the estrogen receptor, and the progesterone receptor. TNBC accounts for more than 20% of all breast cancers (BCs), has a poorer prognosis compared to other BC subtypes, and has no targeted therapeutics. Primarily, this review focuses on the heterogeneity of BC and the importance of molecular subtyping for the accurate classification of TNBC. Further, it seeks to identify the molecular "omic" gaps in subtyping TNBC and the role of membrane protein biomarkers that could potentially advance clinical and translational research in BC.

Keywords: Biomarkers and membrane proteins, breast cancer, metastasis, triple negative


How to cite this article:
Venkatraman B. Identifying gaps and relative opportunities for discovering membrane proteomic biomarkers of triple-negative breast cancer as a translational priority. Cancer Transl Med 2016;2:137-46

How to cite this URL:
Venkatraman B. Identifying gaps and relative opportunities for discovering membrane proteomic biomarkers of triple-negative breast cancer as a translational priority. Cancer Transl Med [serial online] 2016 [cited 2019 Dec 9];2:137-46. Available from: http://www.cancertm.com/text.asp?2016/2/5/137/192931


  Introduction Top


Triple-negative breast cancer (TNBC) is so named because it lacks expression of the estrogen receptor (ER), the progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2). TNBC accounts for more than 20% of all new breast cancers (BCs),[1] and TNBC patients experience a more aggressive clinical course, with high rates of disease recurrence, visceral metastasis, and low survival rates. A clinical biomarker is defined as a substance that indicates a biological or pathological process or a response to a particular therapeutic intervention.[2] Known tumor biomarkers with established clinical utility include the prostate-specific antigen (prostate cancer), CA 19.9 (gastrointestinal), CA 125 (ovarian), CA 15.3 (breast) and α-fetoprotein (testicular). Their discovery has led to increased research into the discovery of proteomic biomarkers for patients with TNBC. Discovering new biomarkers for cancer prognosis, prediction, and monitoring through systems biology will provide valuable information about the patterns of disease development, will help inform therapeutic decisions, and allow for treatment monitoring. [Table 1] lists emerging, clinically relevant, and recommended BC biomarkers by the American Society of Clinical Oncology (ASCO) and National Academy of Clinical Biochemistry. In this review, we seek to outline the current understanding of TNBC's biology and discuss the potential of membrane proteins as biomarker for this disease.
Table 1. Biomarkers of breast cancer diagnosis and prognosis


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Assessment of HER2-positive BC follows standardized guidelines. However, hormone receptor measurements vary across countries. The lack of uniform assessment has been a major obstacle for understanding advanced BC such as TNBC.[24] The analysis of TNBC patients needs to be reproducible to select appropriate treatment options that could directly influence and revamp translational research. Through extensive genetic profiling, it is clear that TNBC is a heterogeneous disease, with complex mutational profiles, varying cellular morphologies, and behavior. This complexity in genetic profile means that treatment of TNBC with molecular targeted therapies will prove to be difficult.[25] Although much is known about TNBC, a number of critical limitations need to be addressed in the next few years to improve patient outcomes.


  Defining Triple-Negative Breast Cancer: Molecular Heterogeneity Top


Kinship between basal-like breast cancer and triple-negative breast cancer

With the aid of complementary DNA microarrays, Perou et al.[26] identified five distinct subgroups of BC that are biologically diverse and have different clinical outcomes: two luminal cell-related groups (luminal A and B), a myoepithelial cell-related group (basal like), a HER2-enriched group, and a normal breast-like group. Hierarchical classification of breast tumor has major, primary, and secondary divisions based on the ER and PR statuses, supported by the panelists of St Gallen Consensus 2009, also endorsed and approved by the expert panel of ASCO. From the primary division, the secondary division has been diversified considering the hormone receptor status which could be either positive or negative as well as optimal performance of HER2 status.[27],[28] Immunohistochemistry (IHC)-based proliferative index Ki67 has also been useful for classifying BC into luminal A (ER-positive, HER2-negative, and low Ki67) luminal B (ER-positive, HER2-negative, and high Ki67), and TNBC (any Ki67).[29] As a consequence, Ki67 has become a routine clinical assay for BC treatment. The luminal subgroup of BCs is further classified as luminal A and B tumors which are histologically graded as low and high, respectively. Tertiary division classifies the nonluminal subgroup of BCs into HER2 overexpressing or enriched group and the TNBC group. The latter shows two core basal subtypes, in which the tumor expresses genes such as KRT5, KRT14, and KRT17 characteristic to normal basal myoepithelial cells with cytokeratin (CK) and epidermal growth factor receptor (EGFR) expression.[30] These two TNBC basal subtypes are further subdivided into basal-like 1 and basal-like 2 subtypes based on keratin expression [Figure 1].
Figure 1. Breast tumor phylogeny - major molecular subtypes of breast cancer showing typical characteristics of immunohistochemistry biomarkers such as ER, PR, HER2, Ki67, CK5/6, epidermal growth factor receptor, basal keratins, and claudins. ER: Estrogen receptor; PR: Progesterone receptor; HER2: Human epidermal growth factor receptor 2; Ki67: Proliferation index %; CK: Cytokeratin; NP: Negative phenotype; AR: Androgen receptor; TN: Triple negative

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Triple-negative breast cancer's individuality within breast cancer heterogeneity

Gene expression profiling further classifies TNBCs into immunomodulatory cancers, which are enriched with lymphocytic infiltration. A subtype of TNBC also includes triple-negative cancers lacking expression of CK5/6 and EGFR, the so-called quintuple-negative phenotype. BC subtypes showing mesenchymal-like (M) and mesenchymal stem-like gene expression signatures which are enriched in epithelial-to-mesenchymal transition gene sets have also gained attention [Figure 1]. Finally, a subtype of triple-negative breast tumor classified as luminal AR contains all the ER tumors outside the basal group, which shows an androgen receptor signaling and a "molecular apocrine" gene expression signature.[31],[32] A significant overlap exists between TNBC and basal-like BCs (BLBC); approximately 85% of all TNBCs are basal-like tumors, which resemble the outer basal cells surrounding the mammary duct, and most BLBCs are TNBC. Understanding the biology and genetic heterogeneity of BC in general, and TNBC as a subtype, continues to evolve and not all TNBCs are treated equally. Although the application of gene expression profiling is limited in clinical practice due to its complexity and high cost, transcriptome profiling has enabled researchers to identify molecular signaling cascades and targets which may prove useful in the development of novel therapeutic agents.[33],[34] Interestingly, BC associated with mutations in the BRCA1 tumor suppressor gene frequently lacks expression of ER, PR, and HER2. These BRCA1-mutant breast tumors cluster closely with TNBC/BLBC on microarrays and share many common molecular features including expression of CK5/6, CK14, CK17, p-Cadherin, and EGFR.[35] Perou et al.[26] characterized BLBC by its low expression of ER/PR/HER2 and high levels of CK5/6, CK14, CK17, p-Cadherin, p63, caveolin-1, carbonic anhydrase IX gene (CA IX), and EGFR. Thus, the TNBC/BLBC subgroups are associated with altered BRCA function and genomic instability, along with defective DNA damage repair, which may reflect their sensitivity to certain therapies that induce DNA damage.[36]

Clinically, TNBC receives a significant attention as it occurs more often in young women (under 40 years of age), particularly in African-American and Hispanic populations. A majority of tumors defined as triple negative have their genesis from the breast ducts and are associated with certain morphological characteristics including large tumor size, regions of central necrosis, pushing borders with lymphocytic stromal invasion, high nuclear expression, and histological grading with higher mitotic index. TNBCs are considered a special type of BC as they show some similarity with medullary and adenoid cystic carcinomas. Furthermore, TNBC is characterized by an early peak in recurrence between the 1st and 3rd year postdiagnosis followed by a sharp decrease in subsequent years with relapse seldom reported after 8-10 years. Unlike other subtypes of BC, TNBC outcome is not clearly related to clinical stage.[37]

TNBC's rapid growth and disease frequency among younger women make mammographic detection difficult. In a nested case-control study carried out as part of National Mammographic Screening Program, TNBCs were predominantly seen among women having interval BCs and false alarm mammograms, especially within a period of 12 months.[38] However, for BC patients with ER/PR-positive and HER2-negative profiles, mammograms reveal specific features on magnetic resonance imaging (MRI), such as rim enhancement and very high intratumoral signal intensity on T2 -weighed images of MRI. In addition, BCs with a core basal phenotype, unlike nonbasal triple negative, may be more likely than ER-positive BC to recur locally. The Kaplan-Meier survival curve for patients with triple-negative or BLBC differs drastically in relation to other subtypes. Women with luminal A subtype had prolonged survival compared to patients with luminal B- and HER2-positive BC (P < 0.0001). Women with BLBC showed early decline over the first couple of years after diagnosis, followed by gradual decline on follow-up with central nervous system spread.[39] TNBCs tend to be more aggressive than all other BC subtypes and more likely to occur in the viscera, particularly lungs and brain, but less likely to spread to the bones.[40]


  Triple-Negative Breast Cancer Genomics-Mutations Affecting The BRCA and P53 Genes Top


Following the identification, mapping, and cloning of two major BC susceptibility genes such as BRCA1 (chromosome 17q21) and BRCA2 (chromosome 13q12.3), the biology and the molecular characteristics of BC have received greater attention. BRCA1 plays a significant role in repairing double-stranded DNA breaks and also acts as a regulator of the p53 pathway to maintain chromosome stability.[41] Loss of BRCA1 function, therefore, results in genomic instability, predisposing cells to transformation. Germ-line BRCA1 and BRCA2 mutations are inherited in an autosomal dominant fashion. More than 75% of BRCA1-mutant BCs exhibit a basal-like phenotype as assessed by gene expression microarray and IHC analysis. This is particularly true among younger patients who have a familial history of BC and who often present with p53 mutations.[42] Cytogenetic aberrations identified in BRCA1-mutant BCs, including the deletion of chromosome arm 5q, are also common in basal-like breast tumors, but not in other BC subtypes.[43] BRCA1-mutant BCs also resemble TNBC in having p53 loss of function mutations. The tumor suppressor p53 is involved in cell cycle checkpoint control and promotes cell cycle arrest or apoptosis in response to DNA damage. p53 is mutated in up to 82% of BLBCs by both gene and protein expression analysis.[44] Mutated p53 leads to increased genetic instability, cytogenetic changes, and loss of heterozygosity (LOH), which is in accordance with the genetic profile of BLBC/TNBC subtypes. For instance, gain of 6p21-p25 and loss of 5q11 are common alterations in BLBC, with the latter region carrying several DNA repair and suppressor genes, including MSH3, RAD17, and APC. Interestingly, the spectrum of p53 mutations in BRCA1-mutated TNBC is distinct from the p53 alterations found in sporadic TNBC. The ataxia-telangiectasia-mutated kinase is underexpressed with an expression of bi-allelic mutation in both BRCA1 mutant (33%) and BRCA2 mutant (30%) hereditary BC which is in contrast to sporadic TNBC (20%) that tends to be BRCA1/2 wild type.[45]

Linkage analysis suggests that BRCA1/2-mutant breast tumors have unique pathological and gene expression profiles compared to high-risk non-BRCA1/2 (BRCAx) BCs. The majority of BRCAx breast tumors are believed to have originated from a distinct set of genetic alterations. Shah et al.[46] reported that more than 20% of BLBCs carry genetic changes, such as BRAFV(600)E , EGFR copy number gains, and ERBB2/3 mutations, which can be inhibited by existing clinically trialed drugs. Integrative pathway analysis identified hyperactivated CTCF and FOXM1 transcriptional factors and increased MYC and HIF1-α/ARNT networks as key regulators of basal-like breast tumors.[47] Furthermore, loss of RB1, cyclin E copy number gains, and BRCA1/2 loss of function mutations were confirmed as the common features of basal-like breast tumors. The loss of BRCA expression due to gene silencing by promoter methylation has been shown in TNBCs, and BRCA1 normally suppresses the expression of basal-like-related genes, which could provide an explanation for "BRCAness" of basal-like sporadic cancers.[48] Studies report that sporadic TNBCs have similarities with BRCA1-linked BCs with their biological and histological features, both displaying genomic instability, lymphocytic infiltrate, central necrosis, and chromosomal loss. Moreover, BRCA1-linked BCs show typical molecular features of TNBC, such as EGFR overexpression, CK5/6 expression, ER/HER2 negativity, and p53 mutations. Finally, although the majority of BRCA1 mutant-BCs show the triple-negative/basal-like phenotype, it is important to recognize that majority of TNBCs are sporadic.[49]


  Metastasis-related Plasma Membrane Proteins of Breast Cancer Top


Systems biology approaches for discovering plasma membrane (PM) proteins in advanced BC are revealing exciting new potential biomarkers. TNBC metastases are established primarily when malignant cells disseminate to lymph nodes, and then start spreading preferentially into the organs such as the lungs, liver, and brain. The process of metastases is still not fully understood, but comprises a complex set of signaling networks. Metastasis involves the detachment of single cells from the original tumor, invasion into the tissue matrix, intravasation, survival in vasculature, and extravasation to distant locations and angiogenesis to enable survival and growth [Figure 2]. Why some disseminated cancer cells remain dormant for a lifespan and others get activated is a puzzle. However, it is likely that some dormant solitary cancer cells remain dormant and others get activated at distant organs by sensing environmental signals. For instance, inflammation, compromised immune system, changes to female hormonal levels, and hormone imbalances may all contribute to proliferation, differentiation, and metastatic growth. An experimental study on genetic signatures between metastatic tumors vs. primary tumors revealed that additional genomic changes gradually acquire during metastases. Reports claim frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q along with overexpression of multiple genes (BRAF, NEK2A, ATAD2, DERL1, and DNMTRB) in metastatic tumors, supporting high genetic instability.[50] Similarly, a panel of differentially expressed genes has been identified in the isogenic cell lines M-4A4 and NM-2C5 derived from aggressive ductal carcinoma MDA-MB-435 studies.[51] However, it is now important to turn to proteomic studies, which are much more complex than genomic studies. Focusing on membrane proteins is especially important as cell surface proteins in the PM which may add valuable biological insights for metastases. By validating both protein and RNA expression levels, we can gain a better understanding of the critical changes involved in tumor initiation and metastasis. It is important to select appropriate clinical cohorts with detailed and relevant clinical histories and to establish a comprehensive set of research standards and relevant in vitro assays to accurately explore the potential of membrane biomarkers.
Figure 2. Schematic representation showing the development, expansion, and metastasis of breast cancer. The extracellular matrix cooperates with many cell membrane proteins to activate signaling pathways, including mitogen-activated protein kinase and PI3K that modulate cell adhesion, migration, proliferation, and angiogenesis of tumor cells. Metastasis of triple-negative breast cancer occurs when tumor cells move into other organs through the circulation and the lymphatic system. Tumor cells can migrate as dormant solitary cells or as micrometastasis, both of which can proliferate in new target organs such as lungs, liver, and/or brain

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Fidler's classic study on the heterogeneous metastatic capacity of murine melanoma cell clones strongly suggests that some highly metastatic tumor cell variants preexist in the parental tumor population.[52] In BC, two metalloproteinases, ADAMTS1 and MMP1, modulate the bone microenvironment to promote bone metastases. Similarly, lung metastases showed COX2, EREG, and MMP1 and MMP2 expression, which promotes angiogenesis and extravasation of metastatic cells from the capillaries of lung.[53] There are several advantages in utilizing pathway-level analyses of membrane proteins in cancer. For instance, in vitro and in vivo studies support the conclusion that a number of ADAMs (a disintegrin and metalloproteinase), a family of transmembrane, and secreted proteins play a key role in cell adhesion, signaling, and cancer metastases. Considering their significant role in cancer progression and signaling, analysis of membrane proteins may provide a rich source of new prognostic and predictive biomarkers. Overexpression of the membrane-anchored protein urokinase plasminogen activator receptor (uPAR) has been reported in many cancers, including TNBCs. uPAR is an important regulator of extracellular matrix (ECM) proteolysis, cell adhesion, and also for signaling. uPAR interacts with the primary ligand uPA and several other proteins including the integrin family of membrane proteins, molecules of ECM, and transmembrane receptors to modulate intracellular signaling. The interaction of uPA/uPAR, integrins, and the uPAR inhibitor, PAI-1, has an important role in cancer, and its deregulation and expression are associated with a poor prognosis.[54] Kischel et al.[55] compared membrane protein profiles of the MDA-MB 231 BC cell line with bone metastatic subclones and showed upregulation of integrin αvβ3 in the bone metastatic cell variant. A comparison of uPAR expression in BC subtypes revealed that uPAR showed highest expression in TNBCs, and uPAR expression correlated with a poor prognosis and early disease recurrence.[56] Co-immunoprecipitation studies of integrin αvβ3 with uPAR have been carried out in invasive BC, but there has been little insight gained into the interaction of uPAR with any integrin subtype in advanced BC. Reports suggest that the integrin αvβ6 subtype is the activator of transforming growth factor β (TGFβ), which is implicated in promoting and controlling multiple cancer types including ductal carcinoma in situ.[57]


  Triple-Negative Breast Cancer Metastasis: Membrane Proteins and Molecular Signaling Top


Genomic and proteomic studies need to focus on molecular signaling in TNBC to identify the drivers of proliferation and metastasis. The RAS/mitogen-activated protein kinase (MAPK) pathway has been shown to be important for the initiation and progression of breast carcinoma. The RAS family of GTPases is activated by receptor tyrosine kinases and promotes the sequential activation of three tiers of kinases (i.e., the RAF, MEK1/2, and ERK1/2 proteins). ERK activation and nuclear localization promote the expression of many transcriptional factors, such as MYC, FOS, ELK-1, and ETS that support cell survival and proliferation. Alterations affecting the phosphatidylinositol-3-kinase (PI3K/AKT) pathway are frequent in luminal BCs whereas aberrant RAS activity has been identified in metastatic sites of BLBC/TNBC.[58] ERK phosphorylation has both negative and positive prognostic implications for TNBC and this apparent discrepancy may be due to rapid loss of phosphorylation during handling procedures of tissue extraction and processing. Jing et al.[59] reported that suppression of MAPK activity with the use of MEK inhibitors specifically blocks the proliferation of TNBC/BLBC cell lines. Role of microRNA (miRNA) as a noncoding RNA regulating mRNA stability and protein translation could possibly provide more insights about RAS/MAPK signaling within the TNBC/BLBC subtype.

Recent reports suggest that PI3K signaling, through the AKT and mTOR effectors, plays a central role in BC. Among the AKT isoforms, AKT1 mutations are found in ER positive breast tumors, and AKT3 alterations occur in ER negative breast tumors. Activated receptor tyrosine kinases bind the p85 subunit of PI3K, which then recruits the catalytic p110 subunit to form an active PI3K enzyme.[60] Phosphatase and tensin homolog and inositol polyphosphate 4-phosphatase type II directly oppose PI3K activity achieving cell arrest. AKT activation modifies several downstream proteins in TNBC and understanding their role provides an opportunity to inhibit PI3K signaling in advanced BC. MYC oncogene has been long known to be critical for breast tumor progression, but its exact role as a driver oncogene for promoting metastasis is unclear. Key molecular signatures for assessing MYC activity include Src, β-catenin, H-RAS, E2F3, Wnt and TGFβ signaling, which are analyzed with microarrays.[61] Wnt receptor frizzled-7 and Wnt co-receptor, lipoprotein receptor-related protein-6, have been reported to be upregulated in TNBC.[62] SMAD signaling is often initiated by TGFß receptor activation, which promotes the phosphorylation and activation of receptor-regulated SMADs (R-SMADs). SMADs also enhance TGFβ signaling through sumoylation and ubiquitination in metastatic BC even though the functional consequences of these modifications are unclear.[63] Rho family GTPase activity has also been demonstrated in invasive BC cells, and silencing RhoGDI-2 results in downregulation of the integrin β1, which is essential for cancer cell adherence to ECM. The role of RhoGDI-1 has been studied extensively in BC apoptosis, and findings by Muñiz Lino et al.[64] have established that TNBC tissue-derived samples exhibit Rho family proteins having upregulated RhoGDI-2 associated with inhibition of caspase 3 and 9 and deregulation of COX5, MTPN, and DB1 proteins.


  Triple-Negative Breast Cancer Metastasis and Circulating Tumor Cells Top


Circulating tumor cells (CTCs) are thought to be the metastatic seeds, which can break away from the primary site of cancer and spread to other parts of the body. Cells corresponding to the blood-borne tumor of BC patients could be tested, but their ability to disseminate is unclear. It has been suggested that the presence of putative BC stem cells with CD44(+) CD24(−/low) phenotype constitutes a population in primary BC having self-renewal and tumorigenic potential in bone marrow.[65] It remains unclear whether CTCs originate from the primary site of tumor, as micrometastases or from multiple tumor sites. Researchers at the University of Texas measured CTCs in 151 women with metastatic BC stage 3.[66] Blood-based prognostic biomarkers for hormone receptor status CA 27.29 were tested to measure metastatic activity, with results confirming that patients having five or more CTCs had a median overall survival of 13.5 months. The median overall survival increased to 29 months if CTCs were < 5 and their findings showed that five or more CTCs had the highest predictive value compared to all other tumor markers. Current methodologies rely only on the analysis of the parental tumor using specific markers, such as ER, PR, and HER2 to justify clinical decisions and treatment. However, analysis of a single primary or metastatic tumor may not provide sufficient details especially on the heterogeneity of cancer and the genetic variability of CTCs.[67] Cell-free tumor nucleic acid, both DNA and RNA, can also have prognostic value. For instance, circulating telomerase mRNA was increased in serum and plasma samples derived from patients with advanced BC.[68] Research is now focused on identifying differentially expressed blood-based markers, their role as prognostic markers, their malignancy potential, and their characteristics and relationship with primary tumors.

As explained previously, even though BRCA1 gene mutant BCs are phenotypically similar to TNBC, TNBCs have unique characteristics including the absence of ER, PR, and HER2 expression. The homologous recombination deficiency status of TNBCs has also made them a poor predictor of the outcome. As already discussed, it is important to define new prognostic and predictive biomarkers for TNBC, complemented by a detailed characterization of TNBC compared to other subtypes of BC.[69] Biomarker-led membrane protein characterization and cell signaling will help with patient stratification, therapy selection, and will provide a tool to improve the response to treatment. Biological markers of radiosensitivity for tumor and normal tissue require functional characterization so that personalized treatment would be highly efficacious, while minimizing radiotherapy-induced toxicity.[70] A combination of nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry (LC-MS) was used to measure serum metabolites which absolutely identified 80% of BC patients who failed to show a complete response to chemotherapy.[71] The role of lymphangiogenesis in metastasis, enlarged lymph nodes due to BC, needs more research. An understanding about the vascular endothelial growth factor-driven angiogenic signaling pathways and identification of specific biomarkers is required as there are no validated biomarkers currently available that address angiogenesis. Lymphedema-based research may be useful to validate responses in vasculature of anatomically dispersed TNBC metastases, especially the organ dissemination of lungs, liver, bone marrow, and brain.[72]


  Triple-Negative Breast Cancer Bio-Fluids: Plasma and Serum Proteomics Top


Human plasma and serum are the most commonly evaluated biofluids for diagnosis and prognosis. These biofluids are quickly accessible, have cellular versatility with the number of peptides with a mass ranging between 1 and 15 kD, and comprise ~ 40% of all detected molecular signaling.[73] Changes in the expression of plasma protein reflect the state of originating tissues at the molecular level as the tissues are constantly getting bathed in plasma. To study plasma as a source of clinically relevant biomarkers, high abundant proteins may require specific depletion to enrich and reveal specific low-abundant biomarkers. Currently, many proteomic techniques and methods have been applied in the analysis of human plasma.[74] Sample collection and processing is critical to ensure safe and secure handling that includes stabilization, processing, and storage to carefully avoid protein denaturation. It is also important to consider the plasma and serum yield which is generally very low, ranging from 0.2 to 1 μg RNA/mL. Importantly, one has to understand that plasma protein biomarker research and human plasma peptide research depend on the quality of processing and the sensitivity of the detection techniques.[75]

Comprehensive data on plasma research have revealed many potential biomarkers and some insights into the mechanisms of tissue-specific diseases in cancer, Alzheimer's disease, and myocardial infarction.[76] Circulating tumor cells and disseminated tumor cells have an impact on the levels of cell-free DNA in the blood of patients with BC. Circulating DNA can exist as naked (unbound) DNA, DNA-associated histones which could either be mononucleosomes or oligonucleosomes, DNA bound with plasma proteins, or DNA packed as apoptotic bodies. Enrichment and detection of CTCs in blood samples include the cell search system, positive or negative immunoselection or both, and molecular approaches. In BC patients independent of histological cancer type, elevated levels of circulating nucleosomes in blood have been detected.[77] In general for BC, the proliferation marker Ki67 is the blood-based serum/plasma biomarker which is under surveillance,[16] and uPA/PAI-1 is often assayed in combination as tissue-based biomarker for prognosis.[78] Circulating microRNAs have recently attracted a great deal of attention in the advanced stages of the breast disease, in which higher levels of miR-34a were observed having changes in miR-10b, miR-34a, and miR-155 levels which get correlated with metastases.[79] Circulating miR-155 induces EMT which, in turn, activates transforming growth factor signaling leading to cell invasion. The differential expression of the proteins in the serum showing hormone sensitivity compared to nonhormone-sensitive BC has a direct correlation to many factors such as clinical stage, p53 status, and also on the biomarkers. Experiments performed to analyze differences in protein expressions among various BC cell lines identified groups of protein which are being associated with invasive phenotype. A comprehensive review of genome-wide circulating miR data has been created for BC detection and the same could get attempted with circulating miRs that could be useful for detection and application.[80] An experimental technique using SELDI-based serum analysis in advanced BC metastasis accurately predicted the outcome of 83% of early BC patients. Another report with SELDI compared the serum profiles of patients with benign breast disease with serum healthy controls and led to the identification of potential biomarkers that separated healthy controls from cancer patients.[81],[82] To date, the development of a reliable, reproducible, and noninvasive clinical test using circulating biomarkers is still in its infancy, and extensive research is required to standardize and validate them prior to routine clinical use.


  Newly Identified Biomarkers of Breast Cancer and Future Directions Top


Although there has been substantial progress in subtyping BC, there is only limited information available on robust prognostic biomarkers exclusively for BC subtypes. HER2 amplification occurs in 30% of BCs, and HER2-amplified BCs commonly show amplification of the topoisomerase IIα, gene which has decreased sensitivity toward anthracycline.[83] TNBC usually expresses the EGFR protein, and high levels of Ki67 positivity are seen in luminal B BC subtype. FOXP3, a marker for immunosuppressive CD25 + TRegs, has been identified as a marker of larger tumor size. BC stem cell research has identified and recognized aldehyde dehydrogenase 1 as an independent prognostic marker of TNBC in African patient cohorts.[84] Ohi et al.[85] reported ALDH1 expression in 49% TNBC cases without any other correlating clinical parameters. Specific biomarkers of BC subtypes could help clinically in disease prognosis, optimizing therapies, and in predicting responses. Culmination of data gathered about specific biomarker subtype helps in differentiating specifically from other subtypes which could eventually support better patient outcomes.[85]


  Conclusion Top


In summary, TNBC is a molecular heterogeneous BC subtype that is, highly aggressive, with poor prognosis and with no effective therapy. Through this review on TNBC membrane protein biomarker discovery, important gaps and relative opportunities has been identified. It has been suggested, discovering newer biomarkers of TNBC through membrane research could map important functional biomarkers that are involved in adhesion, invasion, and metastasis corresponding with extracellular matrix. Newer protein discoveries could potentially evolve as a therapeutic target. However, current proteomic technologies require careful standardization across different sites to achieve sensitive, specific, and reproducible results. Research validation is also highly critical. Engagement with the HUPO Proteomic Standards Initiative will lead to significant advances in this area. Finally, it is important that the research community consider systems that can effectively integrate proteomics data with next-generation transcriptomic, genetic, epigenetic, and metabolomics data.

Acknowledgments

The author would like to thank Professor John Boyages and Professor Helen Rizos, Faculty of Medicine and Health Sciences, Macquarie University, for their valuable and critical comments about this review.

Financial support and sponsorship

The study was supported by International Macquarie Research Excellence Scholarship and Department of Advanced Medicine supplementary scholarship, Macquarie University, Sydney, Australia.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Lakshmaiah KC, Das U, Suresh TM, Lokanatha D, Babu GK, Jacob LA, Babu S. A study of triple negative breast cancer at a tertiary cancer care center in Southern India. Ann Med Health Sci Res 2014; 4 (6): 993-7.  Back to cited text no. 1
    
2.
Strimbu K, Tavel JA. What are biomarkers? Curr Opin HIV AIDS 2010; 5 (6): 463-6.  Back to cited text no. 2
    
3.
Duffy MJ. Serum tumor markers in breast cancer: are they of clinical value? Clin Chem 2006; 52 (3): 345-51.  Back to cited text no. 3
    
4.
Lee JS, Park S, Park JM, Cho JH, Kim SI, Park BW. Elevated levels of preoperative CA 15-3 and CEA serum levels have independently poor prognostic significance in breast cancer. Ann Oncol 2013; 24 (5): 1225-31.  Back to cited text no. 4
    
5.
Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, Dowsett M, Fitzgibbons PL, Hanna WM, Langer A, McShane LM, Paik S, Pegram MD, Perez EA, Press MF, Rhodes A, Sturgeon C, Taube SE, Tubbs R, Vance GH, van de Vijver M, Wheeler TM, Hayes DF; American Society of Clinical Oncology; College of American Pathologists. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 2007; 25 (1): 118-45.  Back to cited text no. 5
    
6.
Lam L, Czerniecki BJ, Fitzpatrick E, Xu S, Schuchver L, Xu X, Zhang H. Interference-free HER2 ECD as a serum biomarker in breast cancer. J Mol Biomark Diagn 2014; 4 (3): 151.  Back to cited text no. 6
    
7.
Nicolini A, Colombini C, Luciani L, Carpi A, Giuliani L. Evaluation of serum CA15-3 determination with CEA and TPA in the post-operative follow-up of breast cancer patients. Br J Cancer 1991; 64 (1): 154-8.  Back to cited text no. 7
    
8.
Mirabelli P, Incoronato M. Usefulness of traditional serum biomarkers for management of breast cancer patients. Biomed Res Int 2013; 2013: 685641.  Back to cited text no. 8
    
9.
Parise CA, Caggiano V. Breast cancer survival defined by the ER/PR/HER2 subtypes and a surrogate classification according to tumor grade and immunohistochemical biomarkers. J Cancer Epidemiol 2014; 2014: 469251.  Back to cited text no. 9
[PUBMED]    
10.
Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC Jr.; American Society of Clinical Oncology. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007; 25 (33): 5287-312.  Back to cited text no. 10
    
11.
Look MP, van Putten WL, Duffy MJ, Harbeck N, Christensen IJ, Thomssen C, Kates R, Spyratos F, Fernö M, Eppenberger-Castori S, Sweep CG, Ulm K, Peyrat JP, Martin PM, Magdelenat H, Brünner N, Duggan C, Lisboa BW, Bendahl PO, Quillien V, Daver A, Ricolleau G, Meijer-van Gelder ME, Manders P, Fiets WE, Blankenstein MA, Broët P, Romain S, Daxenbichler G, Windbichler G, Cufer T, Borstnar S, Kueng W, Beex LV, Klijn JG, O′Higgins N, Eppenberger U, Jänicke F, Schmitt M, Foekens JA. Pooled analysis of prognostic impact of urokinase-type plasminogen activator and its inhibitor PAI-1 in 8377 breast cancer patients. J Natl Cancer Inst 2002; 94 (2): 116-28.  Back to cited text no. 11
    
12.
Andres SA, Edwards AB, Wittliff JL. Expression of urokinase-type plasminogen activator (uPA), its receptor (uPAR), and inhibitor (PAI-1) in human breast carcinomas and their clinical relevance. J Clin Lab Anal 2012; 26 (2): 93-103.  Back to cited text no. 12
    
13.
Cass JD, Varma S, Day AG, Sangrar W, Rajput AB, Raptis LH, Squire J, Madarnas Y, Sengupta SK, Elliott BE. Automated quantitative analysis of p53, cyclin D1, Ki67 and pERK expression in breast carcinoma does not differ from expert pathologist scoring and correlates with clinico-pathological characteristics. Cancers (Basel) 2012; 4 (3): 725-42.  Back to cited text no. 13
    
14.
Brown JR, DiGiovanna MP, Killelea B, Lannin DR, Rimm DL. Quantitative assessment Ki-67 score for prediction of response to neoadjuvant chemotherapy in breast cancer. Lab Invest 2014; 94 (1): 98-106.  Back to cited text no. 14
    
15.
Weigel MT, Dowsett M. Current and emerging biomarkers in breast cancer: prognosis and prediction. Endocr Relat Cancer 2010; 17 (4): R245-62.  Back to cited text no. 15
    
16.
Banin Hirata BK, Oda JM, Losi Guembarovski R, Ariza CB, de Oliveira CE, Watanabe MA. Molecular markers for breast cancer: prediction on tumor behavior. Dis Markers 2014; 2014: 513158.  Back to cited text no. 16
[PUBMED]    
17.
Piura E, Piura B. Autoantibodies to tumor-associated antigens in breast carcinoma. J Oncol 2010; 2010: 264926.  Back to cited text no. 17
[PUBMED]    
18.
Lacombe J, Mangé A, Solassol J. Use of autoantibodies to detect the onset of breast cancer. J Immunol Res 2014; 2014: 574981.  Back to cited text no. 18
    
19.
Le Naour F, Misek DE, Krause MC, Deneux L, Giordano TJ, Scholl S, Hanash SM. Proteomics-based identification of RS/DJ-1 as a novel circulating tumor antigen in breast cancer. Clin Cancer Res 2001; 7 (11): 3328-35.  Back to cited text no. 19
    
20.
Misek D, Kim EH. Protein biomarkers for the early detection of breast cancer. Int J Proteomics 2011; 2011: 343582.  Back to cited text no. 20
    
21.
Pawlik TM, Hawke DH, Liu Y, Krishnamurthy S, Fritsche H, Hunt KK, Kuerer HM. Proteomic analysis of nipple aspirate fluid from women with early-stage breast cancer using isotope-coded affinity tags and tandem mass spectrometry reveals differential expression of Vitamin D binding protein. BMC Cancer 2006; 6: 68.  Back to cited text no. 21
[PUBMED]    
22.
Engel P, Fagherazzi G, Boutten A, Dupré T, Mesrine S, Boutron-Ruault MC, Clavel-Chapelon F. Serum 25(OH) Vitamin D and risk of breast cancer: a nested case-control study from the French E3N cohort. Cancer Epidemiol Biomarkers Prev 2010; 19 (9): 2341-50.  Back to cited text no. 22
    
23.
Tredwell GD, Miller JA, Chow HH, Thompson PA, Keun HC. Metabolomic characterization of nipple aspirate fluid by (1) H NMR spectroscopy and GC-MS. J Proteome Res 2014; 13 (2): 883-9.  Back to cited text no. 23
    
24.
Timmerman LA, Holton T, Yuneva M, Louie RJ, Padró M, Daemen A, Hu M, Chan DA, Ethier SP, van′t Veer LJ, Polyak K, McCormick F, Gray JW. Glutamine sensitivity analysis identifies the xCT antiporter as a common triple-negative breast tumor therapeutic target. Cancer Cell 2013; 24 (4): 450-65.  Back to cited text no. 24
    
25.
Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011; 121 (7): 2750-67.  Back to cited text no. 25
    
26.
Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lønning PE, Børresen-Dale AL, Brown PO, Botstein D. Molecular portraits of human breast tumours. Nature 2000; 406 (6797): 747-52.  Back to cited text no. 26
    
27.
Viale G. The current state of breast cancer classification. Ann Oncol 2012; 23 Suppl 10: x207-10.  Back to cited text no. 27
[PUBMED]    
28.
Goldhirsch A, Ingle JN, Gelber RD, Coates AS, Thürlimann B, Senn HJ; Panel Members. Thresholds for therapies: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2009. Ann Oncol 2009; 20 (8): 1319-29.  Back to cited text no. 28
    
29.
Pathmanathan N, Balleine RL, Jayasinghe UW, Bilinski KL, Provan PJ, Byth K, Bilous AM, Salisbury EL, Boyages J. The prognostic value of Ki67 in systemically untreated patients with node-negative breast cancer. J Clin Pathol 2014; 67 (3): 222-8.  Back to cited text no. 29
    
30.
Bianchini G, Balko JM, Mayer IA, Sanders ME, Gianni L. Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease. Nat Rev Clin Oncol 2016. doi: 10.1038/nrclinonc. 2016.66.  Back to cited text no. 30
    
31.
Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011; 121 (7): 2750-67.  Back to cited text no. 31
    
32.
Lehmann-Che J, Hamy AS, Porcher R, Barritault M, Bouhidel F, Habuellelah H, Leman-Detours S, de Roquancourt A, Cahen-Doidy L, Bourstyn E, de Cremoux P, de Bazelaire C, Albiter M, Giacchetti S, Cuvier C, Janin A, Espié M, de Thé H, Bertheau P. Molecular apocrine breast cancers are aggressive estrogen receptor negative tumors overexpressing either HER2 or GCDFP15. Breast Cancer Res 2013; 15 (3): R37.  Back to cited text no. 32
    
33.
Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, Hernandez-Boussard T, Livasy C, Cowan D, Dressler L, Akslen LA, Ragaz J, Gown AM, Gilks CB, van de Rijn M, Perou CM. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 2004; 10 (16): 5367-74.  Back to cited text no. 33
    
34.
Prat A, Parker JS, Karginova O, Fan C, Livasy C, Herschkowitz JI, He X, Perou CM. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res 2010; 12 (5): R68.  Back to cited text no. 34
    
35.
Laakso M, Loman N, Borg A, Isola J. Cytokeratin 5/14-positive breast cancer: true basal phenotype confined to BRCA1 tumors. Mod Pathol 2005; 18 (10): 1321-8.  Back to cited text no. 35
    
36.
Boyd NF, Huszti E, Melnichouk O, Martin LJ, Hislop G, Chiarelli A, Yaffe MJ, Minkin S. Mammographic features associated with interval breast cancers in screening programs. Breast Cancer Res 2014; 16 (4): 417.  Back to cited text no. 36
    
37.
Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, Karaca G, Troester MA, Tse CK, Edmiston S, Deming SL, Geradts J, Cheang MC, Nielsen TO, Moorman PG, Earp HS, Millikan RC. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006; 295 (21): 2492-502.  Back to cited text no. 37
    
38.
Park YH, Lee SJ, Cho EY, Choi YL, Lee JE, Nam SJ, Yang JH, Shin JH, Ko EY, Han BK, Ahn JS, Im YH. Clinical relevance of TNM staging system according to breast cancer subtypes. Ann Oncol 2011; 22 (7): 1554-60.  Back to cited text no. 38
    
39.
Haque R, Ahmed SA, Inzhakova G, Shi J, Avila C, Polikoff J, Bernstein L, Enger SM, Press MF. Impact of breast cancer subtypes and treatment on survival: an analysis spanning two decades. Cancer Epidemiol Biomarkers Prev 2012; 21 (10): 1848-55.  Back to cited text no. 39
    
40.
Liedtke C, Mazouni C, Hess KR, André F, Tordai A, Mejia JA, Symmans WF, Gonzalez-Angulo AM, Hennessy B, Green M, Cristofanilli M, Hortobagyi GN, Pusztai L. Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer. J Clin Oncol 2008; 26 (8): 1275-81.  Back to cited text no. 40
    
41.
Deng CX, Wang RH. Roles of BRCA1 in DNA damage repair: a link between development and cancer. Hum Mol Genet 2003; 12: R113-23.  Back to cited text no. 41
[PUBMED]    
42.
Wang ZC, Lin M, Wei LJ, Li C, Miron A, Lodeiro G, Harris L, Ramaswamy S, Tanenbaum DM, Meyerson M, Iglehart JD, Richardson A. Loss of heterozygosity and its correlation with expression profiles in subclasses of invasive breast cancers. Cancer Res 2004; 64 (1): 64-71.  Back to cited text no. 42
    
43.
Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Lønning PE, Børresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001; 98 (19): 10869-74.  Back to cited text no. 43
    
44.
Ozaki T, Nakagawara A. Role of p53 in cell death and human cancers. Cancers (Basel) 2011; 3 (1): 994-1013.  Back to cited text no. 44
    
45.
Reid S, Renwick A, Seal S, Baskcomb L, Barfoot R, Jayatilake H, Pritchard-Jones K, Stratton MR, Ridolfi-Lüthy A, Rahman N; Breast Cancer Susceptibility Collaboration (UK); Familial Wilms Tumour Collaboration. Biallelic BRCA2 mutations are associated with multiple malignancies in childhood including Familial Wilms tumour. J Med Genet 2005; 42 (2): 147-51.  Back to cited text no. 45
    
46.
Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice LM, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan SK, Griffith M, Moradian A, Cheng SW, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda OM, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486 (7403): 395-9.  Back to cited text no. 46
    
47.
Sanders DA, Ross-Innes CS, Beraldi D, Carroll JS, Balasubramanian S. Genome-wide mapping of FOXM1 binding reveals co-binding with estrogen receptor alpha in breast cancer cells. Genome Biol 2013; 14 (1): R6.  Back to cited text no. 47
    
48.
Gorski JJ, James CR, Quinn JE, Stewart GE, Staunton KC, Buckley NE, McDyer FA, Kennedy RD, Wilson RH, Mullan PB, Harkin DP. BRCA1 transcriptionally regulates genes associated with the basal-like phenotype in breast cancer. Breast Cancer Res Treat 2010; 122 (3): 721-31.  Back to cited text no. 48
    
49.
Collins LC, Martyniak A, Kandel MJ, Stadler ZK, Masciari S, Miron A, Richardson AL, Schnitt SJ, Garber JE. Basal cytokeratin and epidermal growth factor receptor expression are not predictive of BRCA1 mutation status in women with triple-negative breast cancers. Am J Surg Pathol 2009; 33 (7): 1093-7.  Back to cited text no. 49
    
50.
Salhia B, Kiefer J, Ross JT, Metapally R, Martinez RA, Johnson KN, DiPerna DM, Paquette KM, Jung S, Nasser S, Wallstrom G, Tembe W, Baker A, Carpten J, Resau J, Ryken T, Sibenaller Z, Petricoin EF, Liotta LA, Ramanathan RK, Berens ME, Tran NL. Integrated genomic and epigenomic analysis of breast cancer brain metastasis. PLoS One 2014; 9 (1): e85448.  Back to cited text no. 50
    
51.
Montel V, Mose ES, Tarin D. Tumor-stromal interactions reciprocally modulate gene expression patterns during carcinogenesis and metastasis. Int J Cancer 2006; 119 (2): 251-63.  Back to cited text no. 51
    
52.
Fidler IJ, Kripke ML. Metastasis results from preexisting variant cells within a malignant tumor. Science 1977; 197 (4306): 893-5.  Back to cited text no. 52
    
53.
Gupta GP, Nguyen DX, Chiang AC, Bos PD, Kim JY, Nadal C, Gomis RR, Manova-Todorova K, Massagué J. Mediators of vascular remodelling co-opted for sequential steps in lung metastasis. Nature 2007; 446 (7137): 765-70.  Back to cited text no. 53
    
54.
Smith HW, Marshall CJ. Regulation of cell signalling by uPAR. Nat Rev Mol Cell Biol 2010; 11 (1): 23-36.  Back to cited text no. 54
    
55.
Kischel P, Guillonneau F, Dumont B, Bellahcène A, Stresing V, Clézardin P, De Pauw EA, Castronovo V. Cell membrane proteomic analysis identifies proteins differentially expressed in osteotropic human breast cancer cells. Neoplasia 2008; 10 (9): 1014-20.  Back to cited text no. 55
    
56.
LeBeau AM, Duriseti S, Murphy ST, Pepin F, Hann B, Gray JW, VanBrocklin HF, Craik CS. Targeting uPAR with antagonistic recombinant human antibodies in aggressive breast cancer. Cancer Res 2013; 73 (7): 2070-81.  Back to cited text no. 56
    
57.
Marshall JF, Hart IR. The role of alpha v-integrins in tumour progression and metastasis. Semin Cancer Biol 1996; 7 (3): 129-38.  Back to cited text no. 57
    
58.
Adeyinka A, Nui Y, Cherlet T, Snell L, Watson PH, Murphy LC. Activated mitogen-activated protein kinase expression during human breast tumorigenesis and breast cancer progression. Clin Cancer Res 2002; 8 (6): 1747-53.  Back to cited text no. 58
    
59.
Jing J, Greshock J, Holbrook JD, Gilmartin A, Zhang X, McNeil E, Conway T, Moy C, Laquerre S, Bachman K, Wooster R, Degenhardt Y. Comprehensive predictive biomarker analysis for MEK inhibitor GSK1120212. Mol Cancer Ther 2012; 11 (3): 720-9.  Back to cited text no. 59
    
60.
Jamdade VS, Sethi N, Mundhe NA, Kumar P, Lahkar M, Sinha N. Therapeutic targets of triple-negative breast cancer: a review. Br J Pharmacol 2015; 172 (17): 4228-37.  Back to cited text no. 60
    
61.
Luo J, Cantley LC. The negative regulation of phosphoinositide 3-kinase signaling by p85 and it′s implication in cancer. Cell Cycle 2005; 4 (10): 1309-12.  Back to cited text no. 61
    
62.
Nguyen DX, Chiang AC, Zhang XH, Kim JY, Kris MG, Ladanyi M, Gerald WL, Massagué J. WNT/TCF signaling through LEF1 and HOXB9 mediates lung adenocarcinoma metastasis. Cell 2009; 138 (1): 51-62.  Back to cited text no. 62
    
63.
Sooud SM, Chantry A. Selective targeting of activating and inhibitory Smads by distinct WWP2 ubiquitin ligase isoforms differentially modulates TGFβ signalling and EMT. Oncogene 2011; 30 (21): 2451-62.  Back to cited text no. 63
    
64.
Muñiz Lino MA, Palacios-Rodríguez Y, Rodríguez-Cuevas S, Bautista-Piña V, Marchat LA, Ruíz-García E, Astudillo-de la Vega H, González-Santiago AE, Flores-Pérez A, Díaz-Chávez J, Carlos-Reyes Á, Álvarez-Sánchez E, López-Camarillo C. Comparative proteomic profiling of triple-negative breast cancer reveals that up-regulation of RhoGDI-2 is associated to the inhibition of caspase 3 and caspase 9. J Proteomics 2014; 111: 198-211.  Back to cited text no. 64
    
65.
Balic M, Lin H, Young L, Hawes D, Giuliano A, McNamara G, Datar RH, Cote RJ. Most early disseminated cancer cells detected in bone marrow of breast cancer patients have a putative breast cancer stem cell phenotype. Clin Cancer Res 2006; 12 (19): 5615-21.  Back to cited text no. 65
    
66.
Giuliano M, Giordano A, Jackson S, De Giorgi U, Mego M, Cohen EN, Gao H, Anfossi S, Handy BC, Ueno NT, Alvarez RH, De Placido S, Valero V, Hortobagyi GN, Reuben JM, Cristofanilli M. Circulating tumor cells as early predictors of metastatic spread in breast cancer patients with limited metastatic dissemination. Breast Cancer Res 2014; 16 (5): 440.  Back to cited text no. 66
    
67.
Eccles SA, Aboagye EO, Ali S, Anderson AS, Armes J, Berditchevski F, Blaydes JP, Brennan K, Brown NJ, Bryant HE, Bundred NJ, Burchell JM, Campbell AM, Carroll JS, Clarke RB, Coles CE, Cook GJ, Cox A, Curtin NJ, Dekker LV, Silva Idos S, Duffy SW, Easton DF, Eccles DM, Edwards DR, Edwards J, Evans D, Fenlon DF, Flanagan JM, Foster C, Gallagher WM, Garcia-Closas M, Gee JM, Gescher AJ, Goh V, Groves AM, Harvey AJ, Harvie M, Hennessy BT, Hiscox S, Holen I, Howell SJ, Howell A, Hubbard G, Hulbert-Williams N, Hunter MS, Jasani B, Jones LJ, Key TJ, Kirwan CC, Kong A, Kunkler IH, Langdon SP, Leach MO, Mann DJ, Marshall JF, Martin L, Martin SG, Macdougall JE, Miles DW, Miller WR, Morris JR, Moss SM, Mullan P, Natrajan R, O′Connor JP, O′Connor R, Palmieri C, Pharoah PD, Rakha EA, Reed E, Robinson SP, Sahai E, Saxton JM, Schmid P, Smalley MJ, Speirs V, Stein R, Stingl J, Streuli CH, Tutt AN, Velikova G, Walker RA, Watson CJ, Williams KJ, Young LS, Thompson AM. Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer. Breast Cancer Res 2013; 15 (5): R92.  Back to cited text no. 67
    
68.
Anker P, Mulcahy H, Stroun M. Circulating nucleic acids in plasma and serum as a noninvasive investigation for cancer: time for large-scale clinical studies? Int J Cancer 2003; 103 (2): 149-52.  Back to cited text no. 68
    
69.
Molyneux G, Smalley MJ. The cell of origin of BRCA1 mutation-associated breast cancer: a cautionary tale of gene expression profiling. J Mammary Gland Biol Neoplasia 2011; 16 (1): 51-5.  Back to cited text no. 69
    
70.
Coates PJ, Appleyard MV, Murray K, Ackland C, Gardner J, Brown DC, Adamson DJ, Jordan LB, Purdie CA, Munro AJ, Wright EG, Dewar JA, Thompson AM. Differential contextual responses of normal human breast epithelium to ionizing radiation in a mouse xenograft model. Cancer Res 2010; 70 (23): 9808-15.  Back to cited text no. 70
    
71.
Wei S, Liu L, Zhang J, Bowers J, Gowda GA, Seeger H, Fehm T, Neubauer HJ, Vogel U, Clare SE, Raftery D. Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer. Mol Oncol 2013; 7 (3): 297-307.  Back to cited text no. 71
    
72.
Schito L, Rey S, Tafani M, Zhang H, Wong CC, Russo A, Russo MA, Semenza GL. Hypoxia-inducible factor 1-dependent expression of platelet-derived growth factor B promotes lymphatic metastasis of hypoxic breast cancer cells. Proc Natl Acad Sci U S A 2012; 109 (40): E2707-16.  Back to cited text no. 72
    
73.
Anderson NL, Anderson NG. The human plasma proteome: history, character, and diagnostic prospects. Mol Cell Proteomics 2002; 1 (11): 845-67.  Back to cited text no. 73
    
74.
Ahmed FE. Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry. J Sep Sci 2009; 32 (5-6): 771-98.  Back to cited text no. 74
    
75.
Randall SA, McKay MJ, Baker MS, Molloy MP. Evaluation of blood collection tubes using selected reaction monitoring MS: implications for proteomic biomarker studies. Proteomics 2010; 10 (10): 2050-6.  Back to cited text no. 75
    
76.
Hanash SM, Pitteri SJ, Faca VM. Mining the plasma proteome for cancer biomarkers. Nature 2008; 452 (7187): 571-9.  Back to cited text no. 76
    
77.
Schwarzenbach H. Circulating nucleic acids as biomarkers in breast cancer. Breast Cancer Res 2013; 15 (5): 211.  Back to cited text no. 77
    
78.
Chung L, Baxter RC. Breast cancer biomarkers: proteomic discovery and translation to clinically relevant assays. Expert Rev Proteomics 2012; 9 (6): 599-614.  Back to cited text no. 78
    
79.
McGuire A, Brown JA, Kerin MJ. Metastatic breast cancer: the potential of miRNA for diagnosis and treatment monitoring. Cancer Metastasis Rev 2015; 34 (1): 145-55.  Back to cited text no. 79
    
80.
Kong W, Yang H, He L, Zhao JJ, Coppola D, Dalton WS, Cheng JQ. MicroRNA-155 is regulated by the transforming growth factor beta/Smad pathway and contributes to epithelial cell plasticity by targeting RhoA. Mol Cell Biol 2008; 28 (22): 6773-84.  Back to cited text no. 80
    
81.
Gonçalves A, Esterni B, Bertucci F, Sauvan R, Chabannon C, Cubizolles M, Bardou VJ, Houvenaegel G, Jacquemier J, Granjeaud S, Meng XY, Fung ET, Birnbaum D, Maraninchi D, Viens P, Borg JP. Postoperative serum proteomic profiles may predict metastatic relapse in high-risk primary breast cancer patients receiving adjuvant chemotherapy. Oncogene 2006; 25 (7): 981-9.  Back to cited text no. 81
    
82.
Hu Y, Zhang S, Yu J, Liu J, Zheng S. SELDI-TOF-MS: the proteomics and bioinformatics approaches in the diagnosis of breast cancer. Breast 2005; 14 (4): 250-5.  Back to cited text no. 82
    
83.
Yadav BS, Chanana P, Jhamb S. Biomarkers in triple negative breast cancer: a review. World J Clin Oncol 2015; 6 (6): 252-63.  Back to cited text no. 83
    
84.
Huang Y, Wang FM, Wang T, Wang YJ, Zhu ZY, Gao YT, Du Z. Tumor-infiltrating FoxP3+ Tregs and CD8+ T cells affect the prognosis of hepatocellular carcinoma patients. Digestion 2012; 86 (4): 329-37.  Back to cited text no. 84
    
85.
Ohi Y, Umekita Y, Yoshioka T, Souda M, Rai Y, Sagara Y, Sagara Y, Sagara Y, Tanimoto A. Aldehyde dehydrogenase 1 expression predicts poor prognosis in triple-negative breast cancer. Histopathology 2011; 59 (4): 776-80.  Back to cited text no. 85
    


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