Breast cancer is one of the most commonly diagnosed cancers and one of the most significant sources of cancer mortality. Triple negative breast cancer (TNBC) is a particularly aggressive subtype that has proven diffic...Breast cancer is one of the most commonly diagnosed cancers and one of the most significant sources of cancer mortality. Triple negative breast cancer (TNBC) is a particularly aggressive subtype that has proven difficult to treat with standard chemotherapies. Obesity has also been shown to exacerbate breast cancer, and diagnoses of these two diseases frequently overlap. Both conditions are regulated in part by the fat mass and obesity-associated (FTO) demethylase, an RNA demethylase which may drive breast cancers through epigenetic alterations to gene expression. Methods of inhibiting FTO have been researched in vitro and in vivo as an alternative or adjunct to chemotherapies in multiple cancers, including breast cancer. Translating knowledge of the role of FTO in breast cancer and the development of novel agents may allow for improvements in the treatment of this refractory cancer. This review therefore aims to provide an overview of existing and developing chemical inhibitors of FTO that could be innovatively studied for the treatment of TNBC and associated comorbidity.展开更多
Background: The purpose of this study was to evaluate the association between the body mass index (BMI) of breast cancer patients and non-cancer females of the Eastern Province of Saudi Arabia. Methods: The weight, he...Background: The purpose of this study was to evaluate the association between the body mass index (BMI) of breast cancer patients and non-cancer females of the Eastern Province of Saudi Arabia. Methods: The weight, height and age was obtained from the patient records of 706 newly diagnosed breast cancer patients and of 20,872 non-cancer female patients who consulted the two largest hospitals in the Eastern Province of Saudi Arabia between 2006 and 2012. Factorial analysis of variance (ANOVA) was used to assess the association between the BMI, age and breast cancer status. Results: The mean BMI of the non-cancer females was 29.4 and the percentage of obese patients of the different age groups ranged from 23.9% to 66.5%. The BMI increased significantly with age. The ANOVA revealed that breast cancer patients older than 50 years had a significantly lower BMI compared to their non-cancer counterparts (p = 0.01). Conclusion: Our data confirm the high BMI of the Saudi Arabian female population. The reason for our finding of a lower BMI of postmenopausal breast cancer patients compared to their non-cancer counterparts is unclear. Future studies are warranted to assess the impact of possible confounding factors on the association between obesity and breast cancer risk. An interesting factor to investigate in future studies would particularly be the use of the anti-diabetic and cancer-protective drug metformin considering that diabetes mellitus is endemic in Saudi Arabia with a prevalence of 30%.展开更多
Breast cancer is one of the most common and deadliest types of cancer among women and early detection is of major importance to decrease mortality rates. Microcalcification clusters and masses are two major indicators...Breast cancer is one of the most common and deadliest types of cancer among women and early detection is of major importance to decrease mortality rates. Microcalcification clusters and masses are two major indicators of malignancy in the early stages of this disease, when mammography is typically used as the screening technology. Computer-Aided Diagnosis (CAD) systems can support the radiologists’ work, by performing a double-reading process, which provides a second opinion that the physician can take into account in the detection process. This paper presents a CAD model based on computer vision procedures for locating suspicious regions that are later analyzed by artificial neural networks, support vector machines and linear discriminant analysis, to classify them into benign or malignant, based on a set of features that are extracted from lesions to characterize their visual content. A genetic algorithm is used to find the subset of features that provide the greatest discriminant power. Our results show that the SVM presented the highest overall accuracy and specificity for classifying microcalcification clusters, while the NN outperformed the rest for mass-classification in the same parameters. Overall accuracy, sensitivity and specificity were measured.展开更多
Identification and quantification of low abundance growth factors and regulators in complex biological samples still present a challenging task in analytical biochemistry. Immunoassays are often used for such purpose ...Identification and quantification of low abundance growth factors and regulators in complex biological samples still present a challenging task in analytical biochemistry. Immunoassays are often used for such purpose but immunoassays face limitation of both availability and qualities of antibody reagents that are necessary for development of immune assays. With genomics data base available, mass spectrometry (MS) can analyze protein tryptic peptides directly for quantitative determination of proteins. In this study, we report a method for detection of matrix metalloproteinase 1 (MMP1), an important extracellular matrix modulator, in human breast cancer cells by quadrupole time-of-flight (Q-TOF) MS. Absolute quantification of MMP1 was conducted using the selected reaction monitoring (SRM) on a triple quadrupole (Triple-Quad) MS via transitions selected from MMP1 tryptic peptides using non isotope labeled MMP1 protein as a titration standard. In comparison with immune based assay, this MS method showed picogram level sensitivity for quantitative determination of MMP1 intotal cell lysates. Our results demonstrated the feasibility of absolute quantification of low abundance proteins using label-free protein standard by mass spectrometry. Therefore, this method provides not only advantages of high sensitivity but also cost saving in comparison with the commonly used mass spectrometry that currently employs isotype labeled proteins for quantitative analysis.展开更多
Background: Obesity is a well-known risk factor for breast cancer recurrence and poor prognosis. The objective of this study was to evaluate the effect of body mass index (BMI) on survival in breast cancer patients. M...Background: Obesity is a well-known risk factor for breast cancer recurrence and poor prognosis. The objective of this study was to evaluate the effect of body mass index (BMI) on survival in breast cancer patients. Methods: We performed a retrospective analysis of 50 breast cancer patients treated in our hospital from January 2012 to December 2013. Patients were divided according to body mass index when diagnosed into: normal weight BMI 25 Kg/m2, over weight BMI ≥ 25 Kg/m2 to 2, obesity BMI ≥ 30 Kg/m2. In this study the effect of body mass index on progression free survival (PFS) and overall survival (OS) was evaluated. Results: The disease free survival (DFS) and overall survival (OS) decreased in overweight and obese patients. Both overweight and obesity were predictors for increased risks of breast cancer relapse and mortality with a median disease free survival for overweight 29 mons and obese patients 11 mons and a median overall survival for overweight patients 49 mons and obese patients 39 mons. Conclusion: Obesity and overweight are associated with poorer disease free survival and overall survival in patients with breast cancer.展开更多
17-β-estradiol (estrogen) is a steroid hormone important to human development;however, high levels of this molecule are associated with increased risk of breast cancer primarily due to estrogen’s ability to bind and...17-β-estradiol (estrogen) is a steroid hormone important to human development;however, high levels of this molecule are associated with increased risk of breast cancer primarily due to estrogen’s ability to bind and activate the estrogen receptor (ER) and initiate gene transcription. Currently, estrogen mechanisms of action are classified as genomic and non-genomic and occur in an ER-dependent and ER-independent manner. In this study, we examine estrogen signaling pathways, by measuring changes in protein expression as a function of time of exposure to estrogen in both ER-positive (MCF-7) and ER-negative (MDA-MB-231) cell lines. Using a robust experimental design utilizing isotopic labeling, two-dimensional LC-MS, and bioinformatics analysis, we report genomic and non-genomic ER regulated estrogen responsive proteins. We find a little over 200 proteins differentially expressed after estrogen treatment. Cell proliferation, transcription, actin filament capping and cell to cell signaling are significantly enriched in the MCF-7 cell line alone. Translational elongation and proteolysis are enriched in both cell lines. Subsets of the proteins presented in this study are for the first time directly associated with estrogen signaling in mammary carcinoma cells. We find that estrogen affected the expression of proteins involved in numerous processes that are related to tumorigenesis such as increased cellular division and invasion in an ER-dependent manner. Moreover, we identified negative regulation of apoptosis as a non-genomic process of estrogen. This study complements gene expression studies and highlights the need for both genomic and proteomic analyses in unraveling the complex mechanisms by which estrogen affects progression of breast cancer.展开更多
Objective: To find an effective, sensitive, specific and noninvasive diagnostic method of breast cancer. Methods: 109 masses of 102 patients with breast lesions smaller than 2 cm in diameter were divided into three gr...Objective: To find an effective, sensitive, specific and noninvasive diagnostic method of breast cancer. Methods: 109 masses of 102 patients with breast lesions smaller than 2 cm in diameter were divided into three groups to undergo 99mTc-MIBI imaging and compared with the results of pathology examination. 20 cases without breast lesions were selected as control. Abnormal condensation of 99mTc-MIBI in the breast reaching 10% higher than that in the counterpart of the healthy breast was regarded as positive. Results: Of 32 breast cancers, positive imaging appeared in 25. Negative imaging were found in 31 of 38 benign breast lesions. Of 39 occult breast lesions, positive imaging appeared in 6 and 3 of them were breast cancer, 2 of 3 patients with slightly increased 99mTc-MIBI imaging threshold were breast cancer also. No positive imaging was found in the control group. The diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value of 99mTc-MIBI was 88.4%, 89.2%, 88.0%, 75.0% and 95.3%, respectively. Conclusion: 99mTc-MIBI imaging had higher sensitivity and accuracy in the diagnosis of breast cancer and differentiation between benign and malignant breast lesions. It could provide useful information for the diagnosis of clinically suspected breast cancer.展开更多
文摘Breast cancer is one of the most commonly diagnosed cancers and one of the most significant sources of cancer mortality. Triple negative breast cancer (TNBC) is a particularly aggressive subtype that has proven difficult to treat with standard chemotherapies. Obesity has also been shown to exacerbate breast cancer, and diagnoses of these two diseases frequently overlap. Both conditions are regulated in part by the fat mass and obesity-associated (FTO) demethylase, an RNA demethylase which may drive breast cancers through epigenetic alterations to gene expression. Methods of inhibiting FTO have been researched in vitro and in vivo as an alternative or adjunct to chemotherapies in multiple cancers, including breast cancer. Translating knowledge of the role of FTO in breast cancer and the development of novel agents may allow for improvements in the treatment of this refractory cancer. This review therefore aims to provide an overview of existing and developing chemical inhibitors of FTO that could be innovatively studied for the treatment of TNBC and associated comorbidity.
文摘Background: The purpose of this study was to evaluate the association between the body mass index (BMI) of breast cancer patients and non-cancer females of the Eastern Province of Saudi Arabia. Methods: The weight, height and age was obtained from the patient records of 706 newly diagnosed breast cancer patients and of 20,872 non-cancer female patients who consulted the two largest hospitals in the Eastern Province of Saudi Arabia between 2006 and 2012. Factorial analysis of variance (ANOVA) was used to assess the association between the BMI, age and breast cancer status. Results: The mean BMI of the non-cancer females was 29.4 and the percentage of obese patients of the different age groups ranged from 23.9% to 66.5%. The BMI increased significantly with age. The ANOVA revealed that breast cancer patients older than 50 years had a significantly lower BMI compared to their non-cancer counterparts (p = 0.01). Conclusion: Our data confirm the high BMI of the Saudi Arabian female population. The reason for our finding of a lower BMI of postmenopausal breast cancer patients compared to their non-cancer counterparts is unclear. Future studies are warranted to assess the impact of possible confounding factors on the association between obesity and breast cancer risk. An interesting factor to investigate in future studies would particularly be the use of the anti-diabetic and cancer-protective drug metformin considering that diabetes mellitus is endemic in Saudi Arabia with a prevalence of 30%.
文摘Breast cancer is one of the most common and deadliest types of cancer among women and early detection is of major importance to decrease mortality rates. Microcalcification clusters and masses are two major indicators of malignancy in the early stages of this disease, when mammography is typically used as the screening technology. Computer-Aided Diagnosis (CAD) systems can support the radiologists’ work, by performing a double-reading process, which provides a second opinion that the physician can take into account in the detection process. This paper presents a CAD model based on computer vision procedures for locating suspicious regions that are later analyzed by artificial neural networks, support vector machines and linear discriminant analysis, to classify them into benign or malignant, based on a set of features that are extracted from lesions to characterize their visual content. A genetic algorithm is used to find the subset of features that provide the greatest discriminant power. Our results show that the SVM presented the highest overall accuracy and specificity for classifying microcalcification clusters, while the NN outperformed the rest for mass-classification in the same parameters. Overall accuracy, sensitivity and specificity were measured.
文摘Identification and quantification of low abundance growth factors and regulators in complex biological samples still present a challenging task in analytical biochemistry. Immunoassays are often used for such purpose but immunoassays face limitation of both availability and qualities of antibody reagents that are necessary for development of immune assays. With genomics data base available, mass spectrometry (MS) can analyze protein tryptic peptides directly for quantitative determination of proteins. In this study, we report a method for detection of matrix metalloproteinase 1 (MMP1), an important extracellular matrix modulator, in human breast cancer cells by quadrupole time-of-flight (Q-TOF) MS. Absolute quantification of MMP1 was conducted using the selected reaction monitoring (SRM) on a triple quadrupole (Triple-Quad) MS via transitions selected from MMP1 tryptic peptides using non isotope labeled MMP1 protein as a titration standard. In comparison with immune based assay, this MS method showed picogram level sensitivity for quantitative determination of MMP1 intotal cell lysates. Our results demonstrated the feasibility of absolute quantification of low abundance proteins using label-free protein standard by mass spectrometry. Therefore, this method provides not only advantages of high sensitivity but also cost saving in comparison with the commonly used mass spectrometry that currently employs isotype labeled proteins for quantitative analysis.
文摘Background: Obesity is a well-known risk factor for breast cancer recurrence and poor prognosis. The objective of this study was to evaluate the effect of body mass index (BMI) on survival in breast cancer patients. Methods: We performed a retrospective analysis of 50 breast cancer patients treated in our hospital from January 2012 to December 2013. Patients were divided according to body mass index when diagnosed into: normal weight BMI 25 Kg/m2, over weight BMI ≥ 25 Kg/m2 to 2, obesity BMI ≥ 30 Kg/m2. In this study the effect of body mass index on progression free survival (PFS) and overall survival (OS) was evaluated. Results: The disease free survival (DFS) and overall survival (OS) decreased in overweight and obese patients. Both overweight and obesity were predictors for increased risks of breast cancer relapse and mortality with a median disease free survival for overweight 29 mons and obese patients 11 mons and a median overall survival for overweight patients 49 mons and obese patients 39 mons. Conclusion: Obesity and overweight are associated with poorer disease free survival and overall survival in patients with breast cancer.
文摘17-β-estradiol (estrogen) is a steroid hormone important to human development;however, high levels of this molecule are associated with increased risk of breast cancer primarily due to estrogen’s ability to bind and activate the estrogen receptor (ER) and initiate gene transcription. Currently, estrogen mechanisms of action are classified as genomic and non-genomic and occur in an ER-dependent and ER-independent manner. In this study, we examine estrogen signaling pathways, by measuring changes in protein expression as a function of time of exposure to estrogen in both ER-positive (MCF-7) and ER-negative (MDA-MB-231) cell lines. Using a robust experimental design utilizing isotopic labeling, two-dimensional LC-MS, and bioinformatics analysis, we report genomic and non-genomic ER regulated estrogen responsive proteins. We find a little over 200 proteins differentially expressed after estrogen treatment. Cell proliferation, transcription, actin filament capping and cell to cell signaling are significantly enriched in the MCF-7 cell line alone. Translational elongation and proteolysis are enriched in both cell lines. Subsets of the proteins presented in this study are for the first time directly associated with estrogen signaling in mammary carcinoma cells. We find that estrogen affected the expression of proteins involved in numerous processes that are related to tumorigenesis such as increased cellular division and invasion in an ER-dependent manner. Moreover, we identified negative regulation of apoptosis as a non-genomic process of estrogen. This study complements gene expression studies and highlights the need for both genomic and proteomic analyses in unraveling the complex mechanisms by which estrogen affects progression of breast cancer.
文摘Objective: To find an effective, sensitive, specific and noninvasive diagnostic method of breast cancer. Methods: 109 masses of 102 patients with breast lesions smaller than 2 cm in diameter were divided into three groups to undergo 99mTc-MIBI imaging and compared with the results of pathology examination. 20 cases without breast lesions were selected as control. Abnormal condensation of 99mTc-MIBI in the breast reaching 10% higher than that in the counterpart of the healthy breast was regarded as positive. Results: Of 32 breast cancers, positive imaging appeared in 25. Negative imaging were found in 31 of 38 benign breast lesions. Of 39 occult breast lesions, positive imaging appeared in 6 and 3 of them were breast cancer, 2 of 3 patients with slightly increased 99mTc-MIBI imaging threshold were breast cancer also. No positive imaging was found in the control group. The diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value of 99mTc-MIBI was 88.4%, 89.2%, 88.0%, 75.0% and 95.3%, respectively. Conclusion: 99mTc-MIBI imaging had higher sensitivity and accuracy in the diagnosis of breast cancer and differentiation between benign and malignant breast lesions. It could provide useful information for the diagnosis of clinically suspected breast cancer.