Breast Cancer Microcalcifications Research Articles

Exploration of utility of combined optical photothermal infrared and Raman imaging for investigating the chemical composition of microcalcifications in breast cancer.

Microcalcifications play an important role in cancer detection. They are evaluated by their radiological and histological characteristics but it is challenging to find a link between their morphology, their composition and the nature of a specific type of breast lesion. Whilst there are some mammographic features that are either typically benign or typically malignant often the appearances are indeterminate. Here, we explore a large range of vibrational spectroscopic and multiphoton imaging techniques in order to gain more information about the composition of the microcalcifications. For the first time, we validated the presence of carbonate ions in the microcalcifications by O-PTIR and Raman spectroscopy at the same time, the same location and the same high resolution (0.5 μm). Furthermore, the use of multiphoton imaging allowed us to create stimulated Raman histology (SRH) images which mimic histological images with all chemical information. In conclusion, we established a protocol for efficiently analysing the microcalcifications by iteratively refining the area of interest.

Mammographic Classification of Breast Cancer Microcalcifications through Extreme Gradient Boosting

In this paper, we proposed an effective and efficient approach to the classification of breast cancer microcalcifications and evaluated the mathematical model for calcification on mammography with a large medical dataset. We employed several semi-automatic segmentation algorithms to extract 51 calcification features from mammograms, including morphologic and textural features. We adopted extreme gradient boosting (XGBoost) to classify microcalcifications. Then, we compared other machine learning techniques, including k-nearest neighbor (kNN), adaboostM1, decision tree, random decision forest (RDF), and gradient boosting decision tree (GBDT), with XGBoost. XGBoost showed the highest accuracy (90.24%) for classifying microcalcifications, and kNN demonstrated the lowest accuracy. This result demonstrates that it is essential for the classification of microcalcification to use the feature engineering method for the selection of the best composition of features. One of the contributions of this study is to present the best composition of features for efficient classification of breast cancers. This paper finds a way to select the best discriminative features as a collection to improve the accuracy. This study showed the highest accuracy (90.24%) for classifying microcalcifications with AUC = 0.89. Moreover, we highlighted the performance of various features from the dataset and found ideal parameters for classifying microcalcifications. Furthermore, we found that the XGBoost model is suitable both in theory and practice for the classification of calcifications on mammography.

Prognostic significance of microcalcifications in breast cancer (literature review)

Abstract. Breast cancer is one of the most commonly diagnosed cancers worldwide. According to the World Health Organization, the incidence of breast cancer was 2.26 million in 2020, overtaking the incidence of lung cancer. In Russian Federation, the increase in new cases of breast cancer over the ten years from 2005 to 2015 was 31.76 %. Microscopic calcium deposits within breast tissue, microcalcifications, can be early signs of breast cancer. Being a significant diagnostic finding, microcalcifications allow the assessment of the extent of the disease. A detailed understanding of the morphogenesis of microcalcifications can improve knowledge about early stages of breast cancer, but there is no studies that would combine the results of the latest basic scientific research and current knowledge about their clinical significance.The aim of the study was to analyze and summarize the available data on the prognostic value of microcalcifications in patients with breast cancer.Material and Methods. A search was carried out for available literary sources published in the Medline, Elibrary, etc. databases for the period since 2015. A total of 250 sources devoted to the analysis of the morphogenesis of microcalcifications and their diagnostic value were found. Of them, 37 were included in this review.

Secretion of BMP-2 by tumor-associated macrophages (TAM) promotes microcalcifications in breast cancer

IntroductionBreast microcalcifications is a characteristic feature in diagnostic imaging and a prognostic factor of breast cancer. However, the underlying mechanisms of breast microcalcifications formation are not fully understood. Previous studies have shown that upregulation of bone morphogenetic protein 2 (BMP-2) is associated with the occurrence of microcalcifications and tumor-associated macrophages (TAMs) in the tumor microenvironment can secrete BMP-2. The aim of this study is to elucidate the role of secretion of BMP-2 by TAMs in promoting microcalcifications of breast cancer through immunohistochemical staining and co-culturing of breast cancer cells with TAMs.MethodsA total of 272 patients diagnosed with primary invasive breast cancer from January 2010 to January 2012 in the First Hospital of China Medical University were included in this study. Immunohistochemical staining of CD68 (marker of entire macrophages), CD168 (marker of the M2-like macrophages) and BMP-2 were performed on 4-μm tissue microarray (TMA) sections. Following induction, THP-1 cells were differentiated to M2-like TAMs and were then co-cultured with breast cancer cells (MCF-7). Calcifications and BMP-2 expression were analyzed by Alizarin Red S staining and western blot, respectively.ResultsImmunohistochemical analysis showed that the expression of CD168 was significantly increased in tissues with microcalcifications and was correlated with the expression of BMP-2 and poor prognosis. The formation of cellular microcalcifications and BMP-2 expression were significantly increased in MCF-7 cells co-cultured with TAMs compared with MCF-7 cells alone.ConclusionsThese findings support the hypothesis that TAMs secrete BMP-2 to induce microcalcifications in breast cancer cells and influence prognosis via multiple pathways including BMP-2 and its downstream factors.

Correlation between Breast Ultrasound Microcalcification and the Prognosis of Breast Cancer.

Breast cancer is a common gynecological disease, and its incidence and mortality are higher than those of other common malignant tumors. Breast ultrasound technology is a new surgical method, which has the advantages of reducing postoperative complications, improving the quality of life of patients, and improving the prognosis of patients. Breast microcalcification is a new method for the treatment of tumors. Its mechanism is that the proliferation of breast cancer cell walls increases the inflammatory factors in the cancer tissues and enhances the formation of tumors and peripheral vascular thrombosis. Breast microcalcification in the treatment of breast cancer patients will have a more significant impact compared to ordinary antibiotics alone. For this reason, the microcalcification performance of breast ultrasound is worthy of study, and related research on prognosis is also indispensable. The purpose of this study is to improve the understanding of the ultrasound manifestations of breast cancer microcalcification and the prognosis of breast cancer. This article mainly applied statistical analysis as well as experimental and survey methods to conduct breast ultrasound examination on 100 patients and analyzed the ultrasound manifestations of breast cancer MCs from three aspects: location, shape, and distribution. The experimental results show that there is no correlation between the location and distribution of breast cancer MCs and the diameter of the cancer foci, but there is a certain correlation between the morphology (non-gravel-like calcification) and the diameter of the cancer foci (>5 cm). Among them, HER-2 overexpression accounted for 11.9% in the grit-like MCs group and 51% in the non-grit-like MCs group.

Raman analysis of microcalcifications in male breast cancer

Microcalcifications (MCs) are important disease markers for breast cancer. Many studies were conducted on their characterization in female breast cancer (FBC), but no information is available on their composition in male breast cancer (MBC). Raman spectroscopy (RS) is a molecular spectroscopy that can rapidly explore the biochemical composition of MCs without requiring any staining protocol.In this study, we optimized an algorithm to identify the mineral components present in MCs from Raman images. The algorithm was then used to study and compare MCs identified on breast cancer pieces from male and female patients. In total, we analyzed 41 MCs from 5 invasive MBC patients and 149 MCs from 13 invasive FBC patients.Results show that hydroxyapatite is the most abundant type of calcium both in MBC and FBC. However, some differences in the amount and distribution of calcium minerals are present between the two groups. Besides, we observed that MCs in MBC have a higher amount of organic material (collagen) than FBC.To the best of our knowledge, this study provides the first overview of the composition of MCs present in MBC patients; and suggests that these patients have specific features that differentiate them from the previously studied FBC. Our result support thus the need for studies designed explicitly to the understanding of MBC.

Unravelling the Encapsulation of DNA and Other Biomolecules in HAp Microcalcifications of Human Breast Cancer Tissues by Raman Imaging.

Simple SummaryAlthough microcalcifications can be considered one of the first indicators of suspicious cancer lesions, depending on their morphology and distribution, the formation of hydroxyapatite calcifications and their relationship with malignancy remains unknown. In this work, we investigate in depth the biochemical composition of breast cancer microcalcifications, combining Raman spectroscopy imaging and advanced multivariate analysis. We demonstrate that DNA is naturally adsorbed and encapsulated inside hydroxyapatite found in breast cancer tissue. Furthermore, we also show the encapsulation of other relevant biomolecules such as lipids, proteins, cytochrome C and polysaccharides. The demonstration of the natural DNA biomineralization in cancer tissues represents an unprecedented advance in the field, as it can pave the way to understanding the role of hydroxyapatite in malignant tissues.Microcalcifications are detected through mammography screening and, depending on their morphology and distribution (BI-RADS classification), they can be considered one of the first indicators of suspicious cancer lesions. However, the formation of hydroxyapatite (HAp) calcifications and their relationship with malignancy remains unknown. In this work, we report the most detailed three-dimensional biochemical analysis of breast cancer microcalcifications to date, combining 3D Raman spectroscopy imaging and advanced multivariate analysis in order to investigate in depth the molecular composition of HAp calcifications found in 26 breast cancer tissue biopsies. We demonstrate that DNA has been naturally adsorbed and encapsulated inside HAp microcalcifications. Furthermore, we also show the encapsulation of other relevant biomolecules in HAp calcifications, such as lipids, proteins, cytochrome C and polysaccharides. The demonstration of natural DNA biomineralization, particularly in the tumor microenvironment, represents an unprecedented advance in the field, as it can pave the way to understanding the role of HAp in malignant tissues.

Carbonate and cation substitutions in hydroxylapatite in breast cancer micro-calcifications

Abstract Calcification within breast cancer is a diagnostically significant radiological feature that generally consists of hydroxylapatite. Samples from 30 cases of breast carcinoma with calcification were investigated using optical microscopy, energy-dispersive X-ray analysis, transmission-electron microscopy, Fourier-transform infrared spectroscopy, Raman spectroscopy, synchrotron radiation X-ray diffraction and X-ray fluorescence. Under optical microscopy, the calcifications were found to consist of either irregular aggregates with widths > 200 μm or spherical aggregates similar to psammoma bodies with an average diameter of 30 μm. Transmission-electron microscopy showed that short columnar or dumbbell-shaped crystals with widths of 10–15 nm and lengths of 20–50 nm were the most common morphology; spherical aggregates (~1 μm in diameter) with amorphous coatings of fibrous nanocrystals were also observed. Results indicated that hydroxylapatite was the dominant mineral phase in the calcifications, and both CO32– and cation substitutions (Na, Mg, Zn, Fe, Sr, Cu and Mn) were present in the hydroxylapatite structure. Fourier-transform infrared spectra show peaks at 872 and 880 cm–1 indicating that CO32– substituted both the OH– (A type) and PO43– (B type) sites of hydroxylapatite, making it an A and B mixed type. The ratio of B- to A-type substitution was estimated in the range of 1.1–18.7 from the ratio of peak intensities (I872/I880), accompanied with CO32– contents from 1.1% to 14.5%. Trace arsenic, detected in situ by synchrotron radiation X-ray fluorescence was found to be distributed uniformly in the calcifications in the form of AsO43– substituting for PO43–. It is therefore proposed that identifying these trace elements in breast cancer calcifications may be promising for future clinical diagnostics.

Fuzzy Histogram Equalization and Computer Vision Automated Identification of Microcalcifications in Breast Cancer

Simple signs existent in mammograms for diagnosing breast cancer are considered to be microcalcifications or MCs. Therefore, true detection of MCs is needed to minimize schedule diagnosis, efficient care and death rate due to breast cancer. A challenging task is to evaluate and interpret mammograms and, moreover to the poor contrast consistency of MCs relative to the remainder of the tissue, the precise identification of MCs, such as the minor size and random shape and size of the MC clusters, has several obstacles. These restrictions in the manual analysis of MCs increase the demand for an automated recognition system to help radiologists in mammogram analysis and it is important to design strength algorithm for this purpose. The goal of this paper is to present an efficient procedure that can be used to enhance images for extracting features to give excellent classification. The classifier senses which the region was normal, benign or malignant. The performance of KNN classifier with fuzzy histogram equalization using Otsu’s multi-threshold segmentation gives excellent results in detection and recognition in mammograms for breast cancer distinguished in image mammograms obtained from the hospital.

Abstract 5276: Secretory pathway calcium ATPase 2 (SPCA2) promotes cell survival and chemoresistance in receptor positive breast cancer cells

Abstract Introduction: Dysregulation of the Ca2+ toolkit has profound consequences for tumor growth and metastasis, raising hopes for novel avenues of therapeutic intervention. The Secretory Pathway Ca2+-ATPase Isoform 2 (SPCA2) has a dual function in sequestering Ca2+ and Mn2+ into secretory stores as well as eliciting their entry into cells by activating plasma membrane ion channels. We have previously showed that SPCA2 is implicated in breast cancer progression, microcalcifications, epithelial-mesenchymal transition, and metastasis. Methods and Results: High SPCA2 expression was associated with poor overall survival in receptor positive breast cancer patients (n=548, P =8.7e-0.6; KM Plotter). Depletion of SPCA2 (SPCA2 KD) in MCF-7 cells significantly reduced cell proliferation (P < 0.05). Analysis of the cell cycle (PI staining, Flow cytometry) revealed a significant increase (P < 0.05) in the number of cells in the G0/G1 phase, and significant increase in apoptosis (via TUNEL assay) (P < 0.05) in SPCA2 KD cells compared to control. Microarray analysis showed the p53 pathway is the most significantly upregulated pathway (P < 0.05) in SPCA2 KD cells compared to control. P53 knockout abrogated SPCA2 mediated cell cycle arrest and apoptosis. Depletion of SPCA2 increased reactive oxygen species (ROS, measured by DCFDA dye and MitoSox Red using flow cytometry) leading to DNA damage (confocal microscopy), and activation of ATM/ATR pathway (Immunoblotting, P < 0.05). As a consequence, SPCA2 KD cells showed specific hypersensitivity to DNA damaging agents used in breast cancer therapy (carboplatin, radiation, and doxorubicin) (determined by MTT assay) (P < 0.05). Thus SPCA2 is a novel molecular target in breast cancer therapy. Curcumin is currently being evaluated in clinical trials of breast cancer. We show that curcumin causes dose-dependence inhibition of SPCA2 expression (P < 0.05) in multiple receptor-positive cell lines, and that forced overexpression of SPCA2 decreased curcumin cytotoxicity. Interestingly, we did not observe these results with SPCA1, the housekeeping SPCA isoform, revealing isoform-specific function of Golgi calcium pumps in breast cancer subtypes. Conclusion: These novel findings point to a causal link between SPCA2, breast cancer progression, and chemoresistance to DNA damaging agents. Decrease of SPCA2 expression by curcumin may have therapeutic potential in treating receptor positive breast cancer. Citation Format: Monish Ram Makena, Donna Dang, Allatah Mekile, Phillip Buckhaults, Rajini Rao. Secretory pathway calcium ATPase 2 (SPCA2) promotes cell survival and chemoresistance in receptor positive breast cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5276.

On the chemical composition of psammoma bodies microcalcifications in thyroid cancer tissues

Recently the knowledge of chemical composition of pathological mineralizations is an important topic extensively studied because it could give more in-depth information to understand pathologies themselves and to improve prevention methods. In this work, psammoma bodies (PBs) microcalcifications in thyroid cancer tissue are investigated by different and complementary analytical methods as: micro-Fourier transformed spectroscopy, X-ray fluorescence spectroscopy, Inductively Coupled plasma Optical Emission Spectroscopy (ICP-OES) and scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy imaging (EDX). For the first time the micro-FTIR analysis of the only inorganic phase isolated from PBs was reported. Signals of the recorded spectrum showed that the main component of the calcifications is the amorphous carbonated calcium phosphate, and the IR spectrum of thyroid PBs is strongly consistent with that of PBs in human ovarian tumors. The XRF and the ICP analysis detected also the presence of iron ad zinc in thyroid PBs. These results are validated by scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy imaging (EDX) carried out on tissue samples of the papillary thyroid carcinoma. By these analytical methods magnesium and sodium were detected within PBs while the presence of iron was confirmed by the Perls test. Summarizing the results of applied analytical methods, the main detected elements within the thyroid psammoma bodies are Ca, P, Mg, Na, Fe and Zn. Magnesium and sodium are found in malignant breast cancer microcalcifications, thus they seem correlated to neoplastic transformation. The Fe and Zn elements could give information about the origin of these pathological microcalcifications.

Breast microcalcifications detection based on fusing features with DTCWT.

Breast cancer is a common disease in women. Early detection and early treatment can reduce breast cancer mortality. Studies have shown that breast cancer microcalcifications is one of the important clinical manifestations of early breast cancer, and sometimes even the only manifestation. When the mammography image shows typical malignant microcalcification, it can be diagnosed as breast cancer without any other signs of malignancy. In the aided diagnosis of microcalcifications, it is a crucial step to automatically find and locate regions of interest containing microcalcifications. However, the existing feature extraction method for microcalcifications only extracts features in the time domain or wavelet domain, and does not completely represent all the information of the region of interest. An extraction method based on the combination of Dual-Tree Complex Wavelet Transform (DTCWT) and texture features is proposed in the paper. First, the processing operations including denoising, enhancement, and edge detection were performed on mammograms. Sub-image segmentation is then performed. DTCWT features and texture features are extracted for each sub-image.DTCWT features are combined with texture features, and then genetic algorithm is used for feature optimization. The features are classified by the Extreme Learning Machine (ELM) to achieve rapid detection and automatic extraction of ROI with microcalcifications. The experimental results verify that the feature model proposed in this paper has the highest detection rate for ROI regions. The ROI region extracted by the proposed feature model was used as subsequent experimental data. Three different methods were used to detect the microcalcifications, including Top-hat, wavelet transform, and methods combining Top-Hat and wavelet transform. The method was applied to 100 mammograms from the mammograms database of women in Northeast China. In the automatic extraction of ROI, the accuracy, sensitivity, specificity, positive accuracy and negative accuracy of the proposed model combined with DTCWT were 95.92%, 96.71%, 92.20%, 93.65%, 96.33%, respectively. When the Top-hat algorithm was used for microcalcifications detection, the sensitivity reached 89.6%, and the false positive detection rate was 2.6. When the wavelet transform algorithm was used for microcalcifications detection, the sensitivity was 91.1%, and the false positive detection rate was 3.28. When the combined algorithm was used for microcalcifications detection, the sensitivity was 86.7%, and the false positive detection rate decreased to 1.35. The proposed model combined with DTCWT features achieves better result in the automatic extraction of ROI. Moreover, in the subsequent detection of microcalcifications based on three methods, the three methods achieved better results in sensitivity and false positive detection rate, respectively.

Microcalcification and BMP-2 in breast cancer: correlation with clinicopathological features and outcomes.

BackgroundMicrocalcification is a very important diagnostic information in breast cancer. The purpose of this study was to determine the relationship of clinicopathological features and prognosis of breast cancer with microcalcification and to detect biomarkers related to the possible mechanisms of microcalcifications.Patients and methodsAll 529 subjects with microcalcifications were selected from patients who had been examined using breast mammography. The control group did not have detectable microcalcifications, and was matched in a ratio of 1:3. The clinicopathological factors, progression-free survival (PFS), and overall survival were evaluated by SPSS.ResultsThere was a significant difference in tumor size between the two groups, with larger tumors in the calcification group than the control group, and the proportion of patients in the calcification group with tumors of >5 cm was 20.4% vs 17.2% in the control group (P=0.041). The proportion of patients with lymph node metastasis in the calcification group was higher than that of the control group (35% vs 27.9%, P=0.027). The recurrence rate in ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) patients with microcalcification was higher than that in the control group (P=0.035 and 0.044). BMP-2 expression was higher in breast cancer tissues, especially in breast cancer tissues with microcalcifications. The recurrence rate in the BMP-2(+) group was higher than that in the BMP-2(−) group both in DCIS and IDC (P=0.044 and 0.049). Microcalcifications and the positive expression of BMP-2 were independent factors affecting the PFS of the breast cancer patients.ConclusionThrough the analysis of this study, it was found that the prognosis of the patients with microcalcification was relatively poor. BMP-2 was highly expressed in the breast cancer with microcalcification and was associated with poor prognosis.

Upconversion raster scanning microscope for long-wavelength infrared imaging of breast cancer microcalcifications.

Long-wavelength identification of microcalcifications in breast cancer tissue is demonstrated using a novel upconversion raster scanning microscope. The system consists of quantum cascade lasers (QCL) for illumination and an upconversion system for efficient, high-speed detection using a silicon detector. Absorbance spectra and images of regions of ductal carcinoma in situ (DCIS) from the breast have been acquired using both upconversion and Fourier-transform infrared (FTIR) systems. The spectral images are compared and good agreement is found between the upconversion and the FTIR systems.

Studying biomineralization pathways in a 3D culture model of breast cancer microcalcifications

Microcalcifications serve as diagnostic markers for breast cancer, yet their formation pathway(s) and role in cancer progression are debated due in part to a lack of relevant 3D culture models that allow studying the extent of cellular regulation over mineralization. Previous studies have suggested processes ranging from dystrophic mineralization associated with cell death to bone-like mineral deposition. Here, we evaluated microcalcification formation in 3D multicellular spheroids, generated from non-malignant, pre-cancer, and invasive cell lines from the MCF10A human breast tumor progression series. The spheroids with greater malignancy potential developed necrotic cores, thus recapitulating spatially distinct viable and non-viable areas known to regulate cellular behavior in tumors in vivo. The spatial distribution of the microcalcifications, as well as their compositions, were characterized using nanoCT, electron-microscopy, and X-ray spectroscopy. Apatite microcalcifications were primarily detected within the viable cell regions and their number and size increased with malignancy potential of the spheroids. Levels of alkaline phosphatase decreased with malignancy potential, whereas levels of osteopontin increased. These findings support a mineralization pathway in which cancer cells induce mineralization in a manner that is linked to their malignancy potential, but that is distinct from physiological osteogenic mineralization.

Intelligent System for Detection of Micro-Calcification in Breast Cancer

Recently; medical image mining has become one of the well-recognized research area(s) of machine learning and artificial intelligence techniques have been vastly used in various computer added diagnostic systems. Specifically; breast cancer classification problem is considered as one of the most significant problems. For instance, complex, diverse and heterogamous malignant features of micro-calcification in DICOM (Digital Communication in Medicine) images of mammography are very difficult to classify because the persistence of noise in mammogram images creates lots of confusions for doctors. In order to reduce the chances of misdiagnosis and to discernment the difference between malignant and benign lesions of micro-calcification this paper proposes a system so called “Intelligent System For Detection of Micro-Calcification in Breast Cancer” by considering all above stated problems. Overall our system comprises over three main stages. In first stage, adaptive threshold algorithm is used to reduce the noise, and canny edge detection algorithm is used to detect the edges of every macro or micro classification. In second stage, deginated as feature selection is done by using auto-crop algorithm, which crops all types of calcifications and lesions by proposed algorithm so called CFEDNN (Calcification Feature Extraction Deep Neural Networks) which is designed to avoid the manual ROIs (Region of Interest). Decision model is constructed by using DNN (Deep Neural Networks) and the best classification accuracy is measured as 95.6%.

ANN and Adaboost application for automatic detection of microcalcifications in breast cancer

ObjectiveMicrocalcifications or MCs are considered to be the basic symptoms present in mammograms for breast cancer diagnosis. Therefore, the accurate detection of MCs is mandatory for the on-time diagnosis, effective treatment and reduction of mortality rates due to breast cancer. Mammogram analysis and interpretation is a challenging task, and there are many obstructions to the accurate detection of MCs such as small and non-uniform shape and size of the MCs clusters in addition to low contrast quality of MCs as compared to the rest of the tissue. These shortcomings of manual interpretation of MCs raise the need for an automatic detection system to assist radiologists in mammogram analysis. In this study, an automated system has been developed to minimize the manual inference and diagnose breast cancer with good precision. In this paper, we propose a two-fold detection algorithm. In the first stage, all suspicious regions from the mammogram are segmented out. In the next stage, these suspected regions are fed to a classifier which then detects whether the region was normal, benign or malignant. We compared the performance of a Neural Network classifier with Adaboost. ANN classifier shows more sensitivity and specificity but less accuracy as compared to Adaboost for tested images. Overall results show that the developed algorithm is able to achieve high accuracy and efficiency for the detection and diagnosis of breast cancer lesions for images from two different databases used, and also for mammograms obtained from a local hospital. ConclusionThe suggested algorithm was tested for DDSM, MIAS and local database and showed high level of overall accuracy (98.68%) and sensitivity (80.15%).

A Molecular View of Pathological Microcalcification in Breast Cancer

Breast microcalcification is a potential diagnostic indicator for non-palpable breast cancers. Microcalcification type I (calcium oxalate) is restricted to benign tissue, whereas type II (calcium hydroxyapatite) occurs both in benign as well as in malignant lesions. Microcalcification is a pathological complication of the mammary gland. Over the past few decades, much attention has been paid to exploit this property, which forms the basis for advances in diagnostic procedures and imaging techniques. The mechanism of its formation is still poorly understood. Hence, in this paper, we have attempted to address the molecular mechanism of microcalcification in breast cancer. The central theme of this communication is "how a subpopulation of heterogeneous breast tumor cells attains an osteoblast-like phenotype, and what activities drive the process of pathophysiological microcalcification, especially at the invasive or infiltrating front of breast tumors". The role of bone morphogenetic proteins (BMPs) and tumor associated macrophages (TAMs) along with epithelial to mesenchymal transition (EMT) in manipulating this pathological process has been highlighted. Therefore, this review offers a novel insight into the mechanism underlying the development of microcalcification in breast carcinomas.

Disappearing and re-development of microcalcifications in breast cancer;A case report

Disappearing and re-development of microcalcifications in breast cancer;A case report

CA1 contributes to microcalcification and tumourigenesis in breast cancer.

BackgroundAlthough mammary microcalcification is frequently observed and has been associated with poor survival in patients with breast cancer, the genesis of calcification remains unclear. Carbonic anhydrase I (CA1) has been shown to promote calcification by catalysing the hydration of CO2. This study aimed to determine whether CA1 was correlated with microcalcification and with other processes that are involved in breast cancer tumourigenesis.MethodsCA1 expression in breast cancer tissues and blood samples was detected using western blotting, real-time PCR, immunohistochemistry and ELISA. Calcification was induced in the cultured 4T1 cell line originating from mouse breast tumours, using ascorbic acid and β-glycerophosphate. Acetazolamide, a chemical inhibitor of CA1, was also added to the culture to determine the role of CA1 in calcification. The MCF-7 human breast cancer cell line was treated with anti-CA1 siRNA and was assessed using a CCK-8 cell proliferation assay, an annexin V cell apoptosis assay, transwell migration assay and a human breast cancer PCR array. The tag SNP rs725605, which is located in the CA1 locus, was genotyped using TaqMan® genotyping.ResultsIncreased CA1 expression was detected in samples of breast carcinoma tissues and blood obtained from patients with breast cancer. A total of 15.3 % of these blood samples exhibited a 2.1-fold or higher level of CA1 expression, compared to the average level of CA1 expression in samples from healthy controls. Following the induction of calcification of 4T1 cells, both the number of calcium-rich deposits and the expression of CA1 increased, whereas the calcification and CA1 expression were significantly supressed in the presence of acetazolamide. Increased migration and apoptosis were observed in MCF-7 cells that were treated with anti-CA1 siRNA. The PCR array detected up-regulation of the androgen receptor (AR) and down-regulation of X-box binding protein 1 (XBP1) in the treated MCF-7 cells. Significant differences in the allele and genotype frequencies of rs725605 were detected in the cohort of patients with breast cancer but not in other tumours.ConclusionThe results of this study suggested that CA1 is a potential oncogene and that it contributes to abnormal cell calcification, apoptosis and migration in breast cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1707-x) contains supplementary material, which is available to authorized users.