Definition
Biomarkers are distinctive and relatively specific biological indicators (in the form of altered gene, protein, carbohydrate, or lipid expression) of physiological or disease processes. Clinical cancer biomarkers have been broadly categorized into prognostic biomarkers which aid in determining the disease outcome (prognosis) or predictive markers which predict response to therapy. Identification of prognostic and predictive biomarkers would enhance the management of breast cancer patients by helping clinicians make better decisions with regard to the mode of treatment for each patient, such as which group of patients would benefit from chemotherapy after surgical excision of the tumor. Prognostic biomarkers also form the basis for the development of effective targeted therapy against breast cancer.
Characteristics
Clinical Prognostic Indicators
Standard prognostic factors for breast malignancy take into account clinical and pathological criteria such as a patient’s age and the morphological features of the cancer, such as its stage and histological grade. Tumor stage involves measuring the size of the tumor and determining if the tumor has invaded into surrounding structures and draining lymph nodes as well as spread distally to other organs (metastasis). There are two main commonly used systems for staging of tumors: the TNM system (T, tumor; N, lymph node status; M, metastasis) and the American Joint Committee on Cancer (AJCC) staging. Histological grade is assessed by morphological examination of the tissues under a light microscope. Tumors are classified as histological Grade 1 (low grade where the tissue has more resemblance to normal tissue in terms of parameters such as variability of the size of the nucleus and mitosis), Grade 2 (moderately differentiated), and Grade 3 (poorly differentiated) tumors.
These parameters provide the basis for prognostic algorithms, such as the Nottingham Prognostic Indicator which is a reliable predictor of long-term survival of breast cancer patients. However, there are limitations in the use of conventional prognostic tools for predicting patient outcome. Herein lies the importance of the continuous search for clinically useful biomarkers that can provide additional prognostic information.
Traditional Prognostic Markers
Well-established traditional prognostic markers include estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2/neu (synonym neu or cerbB2) positivity, and Ki-67 cell proliferation marker.
Hormone Receptors
Estrogen receptor (ER) is a 65 kDa nuclear molecule and binds to 17β-estradiol as its principal ligand. Two ER subtypes, ERα and ERβ, have been described, with the former being present in approximately 70 % of breast cancers. Binding of estrogen to ER leads to either homo- or hetero-dimerization of the receptor, which then interacts with hormone response elements to induce transcription of genes which regulate cellular activity (Fig. 1).
This process can be deactivated by blocking the activity of the receptor or depriving the receptor of the estrogen hormone. Patients with ER-negative breast tumors are more likely to have a higher histological grade and decreased overall survival, whereas the prognosis in ER-positive tumors is relatively better. The presence of ER has been used to guide the use of endocrine therapy. Drugs such as tamoxifen target and block the ER receptor and therefore possess anticarcinogenic properties. They are able to reduce tumor cell proliferation and significantly reduce the risk of recurrence within 5 years by 40 % and overall breast specific mortality by 31 %. Aromatase inhibitors like anastrozole and letrozole inhibit the conversion of precursor molecules to estradiol. Patients need to be assessed of their tumor status for the ER marker (endocrine responsiveness) to qualify for either of the treatments. Furthermore, the presence of ER receptor is associated with fewer benefits from chemotherapy.
Like estrogen, progesterone is a steroid hormone and expression of the progesterone receptor (PR) is known to be strongly dependent on ER activity. Therefore, PR-positive breast cancers have a more favorable prognosis than PR-negative tumors.
The ER and PR status of breast cancer tissues is determined by immunohistochemistry (IHC), a technique which uses an antibody to detect the receptors (Fig. 2).
Human Epidermal Growth Factor Receptor-2 (HER-2)
Human epidermal growth factor receptor-2 (HER-2 or ERBB2) is a member of the family of epidermal growth factor receptors. The HER-2 gene is located on chromosome 17q21 and encodes a 185 kDa tyrosine kinase glycoprotein (Fig. 1). HER-2 regulates cell differentiation, adhesion, and motility. The status of HER-2 can be determined by immunohistochemistry or more sophisticated fluorescence in situ hybridization techniques. HER2 expression is estimated to be amplified in approximately 20 % of breast tumors. Most clinical studies have shown that amplification of the HER-2 gene or overexpression of the HER-2 protein is associated with higher-grade tumors, increased rate of recurrence, lower survival, and poorer prognosis. The identification of HER-2 as a prognostic biomarker has led to the clinical development of trastuzumab, a humanized monoclonal antibody against HER-2 protein (monoclonal antibody therapy). Targeted therapy using trastuzumab in combination with chemotherapy in either a first-line or adjuvant (adjuvant therapy) setting has demonstrated survival benefits in breast cancer patients with elevated HER-2 expression.
Ki-67 Proliferation Marker
The Ki-67 gene, located on chromosome 10q25, codes for a nuclear nonhistone protein. Two protein isoforms (359 and 320 kDa) can be formed by alternative splicing. Ki-67 is found in proliferating cells, where its expression increases during disruption of the nuclear membrane during early mitosis. Elevated expression of Ki-67 is a marker of poor prognosis and increased risk of recurrent disease.
Emerging Prognostic Markers
Breast cancer is a heterogeneous disease resulting from the accumulation of multiple gene mutations. Numerous studies have been carried out over the years to understand the different molecular mechanisms involved in breast cancer as well as to obtain prognostic markers to improve diagnosis, therapeutic approaches, and patient management. The development of expression profiling technologies has also accelerated the rate of discovery of novel potential markers for breast cancer.
Genomic Markers
The BRCA1 gene (breast cancer genes BRCA1 and BRCA2) is located on chromosome 17q21 and encodes a 1,863-amino acid nuclear protein that regulates transcriptional activation, cell cycle checkpoint control, DNA repair, chromosomal remodeling, and apoptosis. BRCA1 is a tumor suppressor gene, mutations of which relate to the progression of familial breast cancer (BRCA1/BRCA2 germline mutations and breast cancer risk). Loss of BRCA1 in sporadic tumors results in reduced BRCA1 expression or incorrect subcellular localization of the encoded protein. This well-studied gene is associated with high-grade and larger-sized tumors, advanced lymph node stages, vascular invasion, negative estrogen receptor, progesterone receptor and androgen receptor (AR) and E-cadherin expression, and basal-like type of breast carcinoma. Alterations in BRCA1 gene expression result in poor patient survival.
Proliferation Markers
Increased proliferative activity is one of the hallmarks of cancer. Besides Ki-67, which is an established proliferation marker, proteins associated with cell proliferation include the cyclins which are involved in regulation of the cell cycle and growth factor receptors such as insulin-like growth factor receptor 1. Other examples of breast cancer proliferation markers are FOXM1 (forkhead box M1; a member of the forkhead box superfamily of transcription factors), metallothionein (a metal-binding protein; metallothionein enzymes), securin (a regulatory protein), and YB-1 (a member of the cold shock domain DNA- and RNA-binding protein superfamily).
Anti-apoptosis Markers
BCL2 is a mitochondrial protein that inhibits chemotherapy-induced apoptosis (mitochondria apoptosis pathway). Its expression level is inversely correlated with that of oncogenic Ki-67. Patients with BCL2-negative breast cancer are more likely to respond to chemotherapy. However, overexpression of BCL2 is also correlated with increased survival rates, and this may be due to the presence of concurrent estrogen receptor expression. Mutation of the p53 tumor suppressor gene (TP53; p53 family) has long been implicated in the evasion of apoptosis in human tumors and associated with more aggressive breast cancers.
Structural Proteins
Cytokeratins (CKs) are a family of major structural proteins present in the cytoplasm of epithelial cells. Their molecular weights range from 40 to 68 kDa. In the human breast, CKs are mainly expressed in basally located myoepithelial cells. Basic CK5 (58 kDa) and acidic CK14 (50 kDa) and CK17 (46 kDa) are associated with high-grade basal-like breast carcinoma, early tumor recurrence, and poor prognosis. Furthermore, expression of these three CKs has been significantly correlated with BRCA1-expressing tumors.
Angiogenesis-Associated Markers
Another hallmark of cancer is the formation of new blood vessels (angiogenesis) to help nourish the tumor for its growth. Angiogenic factors include growth factors such as members of the vascular endothelial growth factor family, fibroblast growth factor 2, and hepatocyte growth factor(synonym scatter factor) as well as members of the angiopoietin family. Serum levels of vascular endothelial growth factor (VEGF) may be a useful prognostic factor in breast cancer, as they have been observed to be elevated in malignant breast tumors and predict overall survival and local recurrence. Expression of VEGF has been correlated with estradiol in tumors and may promote cancerous spread by regulating chemokine receptor CXCR4. However, a recent report has shown that contrary to expectation, angiogenic factors and receptors were downregulated in primary breast tumors. An intact uterus in postmenopausal women appears to protective females against distal spread of breast cancer by lowering serum VEGF levels.
Plasminogen Activators and Inhibitors
Cancer cells make use of proteolytic enzymes to assist in invading surrounding tissues and distant metastasis. Urokinase-type plasminogen activator (u-PA) is a serine protease that degrades extracellular matrix thus easing cancer progression. Elevated expression of u-PA and plasminogen activator inhibitor (PAI1; plasminogen-activating system) is associated with higher recurrence risk and poorer survival in patients with node-negative breast cancer. These patients have also been reported to derive greater benefits from chemotherapy.
Glycosaminoglycans and Proteoglycans
Glycosaminoglycans (GAGs) and proteoglycans (PGs) play vital roles in cancer progression. GAGs are long, unbranched polysaccharides that are formed by repeating disaccharides of an uronic acid residue alternating with an amino sugar. Four major classes of GAGs have been described, namely, heparan sulfate (HS), chondroitin sulfate/dermatan sulfate, keratan sulfate, and hyaluronan. Syndecans are transmembrane HSPGs and consist of four family members. Overexpression of syndecan-1 in breast cancer is linked to poor survival outcome and is predictive of response to neoadjuvant chemotherapy. Through its interactions with heparin-binding growth factors and integrin, syndecan-1 regulates cancer progression and tumor-associated angiogenesis. Syndecan-4 has also been found to be associated with aggressive ER-negative breast cancer. Glypican-1, an HSPG, has been found overexpressed in high-grade breast cancer tissues.
Multigene Arrays
Genomics technologies have led to the development of multigene arrays known to provide prognostic information such as the Oncotype DX assay, an array of 21 genes (comprising 16 outcome-related genes and five reference genes) and the MammaPrint 70-gene signature. The MammaPrint has been given approval by the US Federal Drug Administration (FDA) for application as a prognostic tool when used in combination with other clinicopathological parameters.
MicroRNA
MicroRNAs (miRNAs) are small noncoding RNAs that originate from genes transcribed by RNA polymerase II. Recent studies have demonstrated associations between miRNAs and cancer progression and stimulated interest in identifying the involved miRNAs. By suppressing the translation of mRNA or cleaving mRNA, miRNAs can regulate cellular proliferation, apoptosis, and differentiation. Alterations of miRNA expression have been reported to be associated with breast cancer development, invasion, and metastasis.
Future Directions
Well-established biomarkers of breast cancer are routinely used in medical practice to guide clinical management decisions and to aid in predicting disease outcome. Simultaneous analysis of several molecules has led to the identification of basal-like (also known as triple-negative) breast cancer. This subset of breast cancer is negative for ER, PR, and HER-2 and displays a more aggressive behavior and possesses a poorer prognosis compared with luminal (ER positive) and HER-2-like (ER negative, HER-2 positive) breast tumors. Technological advances in genomics, proteomics, and glycomics have led to the discovery of novel predictive and prognostic factors. Efforts are now required to validate the clinical usefulness of these molecules and to determine if they will contribute to personalized breast cancer treatment.
Cross-References
References
Dowsett M, Dunbier AK (2008) Emerging biomarkers and new understanding of traditional markers in personalized therapy for breast cancer. Clin Cancer Res 14:8019–8026
Duffy MJ, Crown J (2008) A personalized approach to cancer treatment: how biomarkers can help. Clin Chem 54:1770–1779
Pakkiri P, Lakhani SR, Smart CE (2009) Current and future approach to the pathologist’s assessment for targeted therapy in breast cancer. Pathology 41:89–99
Payne SJ, Bowen RL, Jones JL, Wells CA (2008) Predictive markers in breast cancer–the present. Histopathology 52:82–90
Yip GW, Smollich M, Gotte M (2006) Therapeutic value of glycosaminoglycans in cancer. Mol Cancer Ther 5:2139–2148
See Also
(2012) Adjuvant. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 75. doi:10.1007/978-3-642-16483-5_107
(2012) Antibody. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 208. doi:10.1007/978-3-642-16483-5_312
(2012) Checkpoint. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, pp 754–755. doi:10.1007/978-3-642-16483-5_1049
(2012) Cytokeratins. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1051. doi:10.1007/978-3-642-16483-5_1472
(2012) Differentiation. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1113. doi:10.1007/978-3-642-16483-5_1616
(2012) Epithelial cell. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, pp 1291–1292. doi:10.1007/978-3-642-16483-5_1958
(2012) Extracellular matrix. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1362. doi:10.1007/978-3-642-16483-5_2067
(2012) Familial breast cancer. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1373. doi:10.1007/978-3-642-16483-5_2107
(2012) Fibroblast growth factor 2. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1397. doi:10.1007/978-3-642-16483-5_2174
(2012) Flusorescence in situ hybridisation. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1436. doi:10.1007/978-3-642-16483-5_6740
(2012) Glypican 1. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1576. doi:10.1007/978-3-642-16483-5_2464
(2012) Glycoprotein. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1570. doi:10.1007/978-3-642-16483-5_2451
(2012) Glycosaminoglycans. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1570. doi:10.1007/978-3-642-16483-5_2453
(2012) Heparan sulfate. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1647. doi:10.1007/978-3-642-16483-5_2637
(2012) Hyaluronan. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1767. doi:10.1007/978-3-642-16483-5_2876
(2012) Integrin. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1884. doi:10.1007/978-3-642-16483-5_3084
(2012) Ki-67. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 1943. doi:10.1007/978-3-642-16483-5_3213
(2012) Metallothionein enzymes. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p. doi:225910.1007/978-3-642-16483-5_3667
(2012) Mitochondria apoptosis pathway. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 2331. doi:10.1007/978-3-642-16483-5_3764
(2012) Monoclonal antibody therapy. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, pp 2367–2368. doi:10.1007/978-3-642-16483-5_3823
(2012) Neoadjuvant. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 2472. doi:10.1007/978-3-642-16483-5_4003
(2012) Progesterone receptor. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 2990. doi:10.1007/978-3-642-16483-5_4754
(2012) Proteoglycans. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 3100. doi:10.1007/978-3-642-16483-5_4816
(2012) Syndecans. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 3593. doi:10.1007/978-3-642-16483-5_5623
(2012) Targeted therapy. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 3610. doi:10.1007/978-3-642-16483-5_5677
(2012) Transcription. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 3752. doi:10.1007/978-3-642-16483-5_5899
(2012) Tyrosine kinase. In: Schwab M (ed) Encyclopedia of cancer, 3rd edn. Springer, Berlin/Heidelberg, p 3822. doi:10.1007/978-3-642-16483-5_6079
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Bay, BH., Yip, G.WC. (2014). Breast Cancer Prognostic Biomarkers. In: Schwab, M. (eds) Encyclopedia of Cancer. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27841-9_6600-3
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