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Breast cancers arise to be one of the highest mortality facto worldwide. Many developed and advanced diagnostic and therapeutic techniques are using for detection of breast cancers. Tissue microarrays technology (TMAs) is one of the most reliable, specific, sensitive technique using worldwide. Many researches and studied proved the advantages and usefulness of TMAs technology in the diagnosis and development of therapy for breast and other carcinoma cases.
Normal human breasts consist of fat, connective and gland tissues. Glands form lobes which are connected to the nipple by a network of ducts. The following figure shows the normal structure of the human breast (Breast Image, On line).
Diagram showing the lobes and ducts of a breast
Figure 1: The normal structure of the human breast. (Breast Image, On line).
Breast cancer is a malignant breast neoplasm mostly seen in milk ducts or glands (lobules) (Breast cancer, On line).
Figure 2: Breast cancer seen in the duct of the breast that called Ductal carcinoma. (Breast cancer Image, On line).
Tissue microarrays (TMAs) technology is a technique that is used worldwide due to its sensitivity, accuracy, fastness, and reliability in both diagnosis and therapy of cancer cases (Shi Yun Chia, et al, 2008). In TMAs technique 100-500 even more sections from a microarray paraffin block can be made at the same time. The main tests used in TMAs are immunohistochemistry and fluorescent in situ hybridization (TMAs, On line).
(A) (B) (C)
Figure 3: (A) & (B) are examples of paraffin blocks of tissue microarray, and (C) is an example of stained slide of TMAs and it is ready for examination (TMAs, On line).
Bhargava R, et al, (2009) classified 205 breast tumors into molecular classes using HER2, ER, and PR as biomarkers. They also calculated Ki-67 labeling index using an image analysis system. The results showed that 113 (55%) were luminal A, 10 (5%) luminal A-HER2 hybrid, 34 (17%) luminal B, 8 (4%) as luminal B-HER2 hybrid, 32 (15%) as triple negative, and 8 (4%) were FRBB2 (Bhargava R, et al, 2009). Bhargava R, et al, (2009) concluded that immunohistochemistry is a reliable method for breast tumors classification using the gene expression profiles.
KusiÅ„ska, et al, (2005) said that three subgroups of breast cancer without expression of ER were identified by using cDNA microaaray technology; these are: normal breast-like, HER2-positive subtype, and basal-like subtype. KusiÅ„ska, et al, (2005) used TMAs technology for further subtype of basal-like subtype in ductal carcinoma by analyzing 195 cases, which were immunostained for CK17, CK5/6, PGR, ER, and HER2. Kusiniska, et al, (2005) found that 72 cases (36.9%) expressed CK5/6 or CK17 while 41cases (21%) expressed CK5/6 or CK 17 but without expression of ER/PGR or HER2 and three cases expressed all markers. Kusiniska, et al, (2005) concluded that immunohistochemistry is a good tool for the separation of subgroups of breast cancer; however they recommended an addition analysis for good characterization of cases expressing 2 or 3 markers.
Mohammedizadeh F, et al, (2009) aimed to work out the expression of ER, HER2, and PR in 67 breast invasive ductal carcinoma, which were evaluated and grouped into 3 phenotype groups: basal phenotype (luminal, pure basal and mixed basal groups), pure luminal, and null. Mohammedizadeh F, et al, (2009) concluded that using of a mixture of various markers help to get a true picture of any association between prognostic biomarkers and basal phenotype. They also agreed that TMAs is an important tool in gene expression-based researches.
Investigation and development of new therapies for breast tumors are performed by using breast cancer cell lines (Kao J, et al, 2009). Microarray researches divided molecular subtypes into: basal-like, normal-like, ERBB2-associated, luminal A, and luminal B (Kao J, et al, (2009). Kao J, et al, (2009) studied 52 breast cancer cell lines to assess their relation to breast cancer subtypes and to catalog molecular profiles. They used whole-genome DNA microarray to profile gene expression and copy number alterations (CNAs). Kao J, et al, (2009) identified one luminal and two basal-like (A&B) subtypes in transcriptional profile of breast cancer cell lines. They reported that cell lines showed similar patterns of CAN. Kao J, et al, (2009) concluded that collection of similar molecular profiles can help to discover new breast cancer genes, and can be used for investigations of cancer stem, cell biology, biomarkers, subtype-specific pathobiology, and therapies.
Triple-negative phenotype and basal-like are widely used in breast cancers identification Cheang MC, et al, (2008). Cheang MC, et al, (2008) tested 4046 samples to compare the prognosis of three and five-marker panels and to classify breast cancer subtypes using tissue microarrays (TMAs). The results showed that 17% and 9% were basal using the triple negative and the five-marker methods, respectively. This means the five-marker panel showed significant prognosis than the three-marker panel. Patients who were triple- negative and treated with adjuvant anthracycline-based chemotherapy and were positive basal markers had significant worse outcome Cheang MC, et al, (2008). Cheang MC, et al, (2008) concluded that using of expanded biomarker panels will give more specific identification of basal-like breast tumor and can be a prediction of breast tumor survival.
Liu ZB, et al, (2009) evaluated the immounohistochemical characterization of CK5/6 and CK17 markers and examined if the expression of these markers has correlation with clinical outcome in triple negative breast tumor. 112 breast cancers, which already reported as triple negative, were immunostained for CK5/6 and CK17 markers. Liu ZB, et al, (2009) found that 83 (73.2%) were disease free with no metastasis or relapse. Both markers were detected in 38 (33.9%) cases and 52 (46.4%) were either positive for CK 5/6 or CK17. Liu ZB, et al, (2009) concluded that high grade in invasive ductal tumors and worse prognosis was associated with high expression of CK5/6 or CK17.
Walter O, et al, (2009) said that IMP3 (an oncofetal protein) is an important biomarker in many types of cancers e.g. lung, renal, etc, however, its role in breast tumors has not been established. Walter O, et al, (2009) examined 138 breast invasive ducatl tumors for IMP3 expression. The results showed that 45 (33%) cases were positive for IMP3 expression, in which 25/45 IMP3 +ve were triple negative. They also reported that expression of IMP3 showed a significant correlation with CK 5/6 expression. Walter O, et al, (2009) concluded that IMP3 has a great role as a biomarker for basal-like (triple negative) in breast tumors and also can be used with decreased overall survival and more aggressive phenotype.
Muñoz M, et al, (2009) tested 257 invasive ductal tumors cases to define the prognostic influence of breast tumors using immunohistochemistry. Muñoz M, et al, (2009) reported that 26 cases (10.74%) had triple negative carcinoma, 33 (13.63%) cases showed HER2 +ve, 67 (27.68%) were luminal B, and 116 (47.93%) had luminal A tumors. They also found that recurrent rate was detected in luminal A (19%), however, the highest mean relapse free survival seen in triple negative cancers (83 months). The highest mortality rate was in HER2 (33.3%) (Muñoz M, et al, 2009). Muñoz M, et al, (2009) concluded that immunohistochemistry plays a significant tool in molecular classification of significant prognostic for breast invasive ductal tumors. They also found that "the worse prognosis observed for HER2 expressing lesions may have changed after trastuzumab use".
Kim MJ, et al, (2006) said that one of the breast cancer groups (basal-like subtype) showed poor clinical results in the western countries. Basal-like tumors was not examined among Korean population. Kim MJ, et al, (2006) studied 776 cases, which were classified into 5 subgroups, and TMAs used to test the luminal CK (CK8/18), c-kit, HER2/neu, EGFR, (HRs), p53, and basal cytokeratins (CK5 & CK14). Kim MJ, et al, (2006) reported that most expression of basal-like were associated with invasive ductal and metaplastic tumors. Kim MJ, et al, (2006) compared their findings with the findings of Western countries and concluded that "the HER2/neu status is the most important prognostic factor of breast cancers".
Al Tamimi DM, et al, (2010) urged that different populations have different distribution of molecular class that result in various clinical outcomes. They used EGFR, PR, ER, HER2, and CK5/6 as markers for gene expression to analyze 231 breast tumors of Saudi population. Al Tamimi DM, et al, (2010) reported that 99 (42%) of cases gave negative results for all markers and named as unclassified (penta negative). They also found various markers were co-positive in varied patterns [23 (10%) cases]. "There was no association between the molecular class and the histologic type or grade of the tumor" (Al Tamimi DM, et al, 2010). Al Tamimi DM, et al, 2010) concluded that the distribution of molecular class in Saudi population is different in contrast with all Western researches. This result showed that the use of present molecular markers may not contain all molecular classes; therefore the present classification systems require addition refining and development.
E-cadherin has a major role in the progression and formation of breast cancers Mohammedizadeh F, et al, (2009). Mohammedizadeh F, et al, (2009) examined 108 breast invasive ductal tumor samples to evaluate the relationship between prognostic markers and expression of E-cadherin, which was detected by immunohistochemistry. Mohammedizadeh F, et al, (2009) reported that there was no relationship between the E-cadherin and the prognostic biomarkers. They concluded that E-cadherin is associated with other prognostic biomarkers in breast ductal tumors; however, use of E-cadherin expression can help to measure the breast carcinoma prognosis.
Elevated level of choline-containing compounds had been noted in breast tumors, and it can be used as biomarkers for therapy and diagnostic purposes Moestue SA, et al, (2010). Moestue SA, et al, (2010) determined the level of cholin-derived metabolites in xenografted primary human breast tumors (basal-like and luminal-like types). They used microarray technology to detect the expression of genes that are involved in phosphatidylcholine (PtdCho) metabolism. Moestue SA, et al, (2010) compared the metabolite profiles from xenografts with human breast tumors profiles. From this study Moestue SA, et al, (2010) found that glycerophosphocholine (GPC) levels were elevated more than phosphocholine (PCho) levels in basal-like xenografts and it was the opposite picture for luminal-like xenografts. They concluded that different levels of choline metabolite are associated with different expression of gene. They also said that the choline metabolism in the xenograft models can represent basal-like and luminal-like in human breast tumors.
Most of the prognostic evaluation of HR is a confusing factor (Liu H, et al, 2008). They aimed to describe the prognostic features of basal-like tumors without the effect of HR in a series of hormone receptor-negative breast tumors by using tissue microarray (TMA). They grouped 713 hormone receptor-negative invasive breast tumors into three subtypes: basal-like, null, and HER2. Liu H., et al, (2008) subdivided the HER2 into pure-HER2 and basal-HER2. Liu H, et al, (2008) concluded that except for basal-HER2, which may need another way of treatment, there was no significant difference seen in 5-year survival between basal-like and hormone receptor-negative phenotype including null phenotypes and HER2.
ER-alpha is a major marker of invasive breast tumor; however, (ER-beta) not yet evaluated (Marotti JD, et al, 2010). So, they studied 3093 breast cancer cases using TMAs to find out the relationship between the expression of ER-beta and invasive breast tumors. All TMAs sections were immunostained for routine five markers, whereas ER-beta were stained with monoclonal antibody. Marotti JD, et al, (2010) reported that 2103 (68%) cases found to be positive for ER-beta, which were strongly associated with ER-alpha (P <0.0001) and PR (P <0.0001) expressions. However, ER-beta showed opposite relation to CK5/6 (P=0.02), EGFR (P=0.006), and HER2 (P=0.004). Marotti JD, et al, (2010) proved that expression of ER-beta is significantly associated with molecular category (P<0.0001) which also found to be more common in luminal B and A than in basal-like or HER2 types. They reported that ER-beta expression was seen in 60% of basal-like and 55% of HER2 tumors in absence of ER-alpha expression. Marotti JD, et al, (2010) concluded that in absence of ER-alpha expression, ER-beta can play an important role in the progression and development of breast tumors.
Gene mutations and alterations of epigenetic result in change of gene expression, however, the epigenetic had not been characterized and their mechanisms not well understood in specific breast cancer subtypes Bediaga NG, et al, (2010). They studied the breast tumor methylome in details to deliver any association of epigenotype with specific breast tumor subtypes. Bediaga NG, et al, (2010) analyzed DNA methylation in 28 breast tumors using microarray technology and they detected the most subtype predictive methylation profiles. Bediaga NG, et al, (2010) concluded that DNA methylation profiles can be used as a biomarker for prediction, prognostication and treatment of breast tumors.
Kotzsh M, et al, (2010) said that "the urokinase-type plasminogen activator receptor (uPAR) is a key molecule for pericellular proteolysis in tumor cell invasion and metastasis". The prognostication of uPAR expression in 270 invasive breast tumors was evaluated in the Kotzsh M, et al, (2010) study by using tissue microarrays (TMAs). The results showed that stromal and tumor cells (uPAR-Tc) had high uPAR values and opposite to ER status (Kotzsh M, et al, 2010). However, high uPAR-Tc values gave prognostic information for disease-free survival (hazard ratio 1.93, P = 0.007), but the expression of uPAR in stromal cells was not associated with prognosis Kotzsh M, et al, (2010). Kotzsh M, et al, (2010) concluded that, exclusion of stormal cells; expression of uPAR has a great value on prognosis in invasive breast tumor cells and helps in tumor phenotype. Livasy C A, et al, (2007) also found that poor prognostic results of high-grade nucli (P <.0001), elevated Ki-67 index (P < .0001), and p53 over expression (P < .0001) were seen in basal-like subtype.
Basal-like and ERBB2 cancers showed an excellent response to neoadjuvant chemotherapy (NACT) (Bhargava R, et al, 2010). Bhargava R, et al, (2010) hypothesized that, by using semiquantitative immunohistochemistry, a same result could be seen for PR, HER2, and ER. The three markers were used to characterize 359 breast cancers, which treated with NACT, in to six groups. Bhargava R, et al, (2010) reported that complete pathologic response found in 48 cases (13%). They also found that ERBB2 and triple negative carcinoma classes showed the highest rate of total response to NACT (33%; 19/57, and 30%; 24/79 respectively). Patients with complete responds showed 96% of 5-year survival, while those failed to complete response showed only 75% and it was worse in ER-negative group (Bhargava R, et al, 2010). Bhargava R, et al, (2009) also studied and reported previously that 359 cases that treated with neoadjuvant chemotherapy showed a pathologic complete response in ERBB2 and triple negative tumors.
Cai L, et al, (2010) studied cross reactivity of lidamycin apoprotein (LDP) to see binding ability to human breast tumors and normal tissues, which was identified by using tissue microarray (TMAs) technology. The results showed that 72.3% (30/41) was positive in breast tumor tissue and 48.3% (15/31) was also positive of the adjacent normal breast samples Cai L, et al, (2010). They reported that the immunoreactivity of LDP is associated with the over expression of HER2 and VEGF (P< 0.01 and < 0.001, r = 0.287 and 0.389 respectively). They also found that LDP had binding ability to mammary tumors MCF-7 cells. Cai L, et al, (2010) concluded that using of LDP in the development of new drugs is potential. They also concluded that "this study may provide reference for drug combination of LDM and other therapeutic agents".
Darb-Esfahani S, et al, (2009) said that reliable prognostic and predictive markers are important in treatment of breast tumors with neoadjuvant. They examined 116 to evaluate protein biomarkers to define if the there is any association of anthracycline/taxane-based neoadjuvant chemotherapy with pathological complete response (pCR) and disease-free survival (DFS). The study was performed using tissue microarrays (TMAs) of pretherapetic core biopsies (Darb-Esfahani S, et al, (2009). The results showed that different types of tumors showed significant different rates of pCR and it was higher in HR +ve/HER2 +ve and HR -ve/HER2 -ve (triple negative) than in HR +ve/HER2 -ve (Darb-Esfahani S, et al, 2009). "Biology- based tumor type was an independent prognostic factor for disease free survival (DFS) in multivariate analysis (P < 0.001)" (Darb-Esfahani S, et al, 2009). Darb-Esfahani S, et al, (2009) concluded that different breast cancer types gave different predictive and prognostic results.
Summary and Conclusion:
Tissue microarrays (TMAs) technology is an excellent tool for diagnosis and development of therapy for tumors e.g. breast cancers.
As cancer diseases are one of most mortality factors in the world, TMAs technology must be distributed worldwide due to its specification, reliability, quickness, therapy etc.
Modification and improvement of the present biomarkers is highly recommended and different ethnics or mixed populations must be included as they express different molecular classes.
Anti-cancer therapy must be modified according the type of gene expression and must be harmless targeting only to the carcinoma cells and not to the normal cells.