Early Detection of Breast Cancer: New Biomarker Tests on the Horizon?

Determine knowledge and belief of Somalian young women about breast cancer and breast self-examination with champion health belief model: a cross-sectional study

BACKGROUND

Breast cancer (BC) is an important reason for mortality rates in Somalian women. In Somalia, many women are late in applying to the hospital for the diagnosis of BC. Breast self-examination (BSE) is considered an important early detection method for BC in encouraging women to learn to practice BSE, especially for women in developing countries. This study purposed to determine knowledge, and belief of BC and BSE and BSE practice among women in Mogadishu, Somalia using the champion health belief model (CHBM).

METHODS

This cross-sectional study was conducted on 413 women who were between 18 and 49 years of age. The data were collected by using sociodemographic variables (age, marital status, education level, income status), Champion's Health Belief Model Scale (CHBMS), and an introductory questionnaire with questions about BC and BSE and between October 2020 and January 2021 in Mogadishu, Somalia. Further descriptive statistics, the Mann-Whitney U test, and Kruskal-Wallis analysis test were used to assess data that were not normally distributed.

RESULTS

Average age of participants was 22 ± 11.21 years. Only 35.4% of participants had information about BC, 37.8% had heard about BSE before, 25.2% knew BSE, and only 17.2% had done it. Income status, marital status, and age of first birth family were significantly associated with perceived sensitivity, health motivation, convenience, perceived benefits, and self-efficacy for BSE. Overall, the total scores of CHBMS were significantly higher among those who had heard and knowledge about BSE and practiced clinical breast examination (CBE). For the sub-dimensions of perceived sensitivity, health motivation, perceived benefits, barrier, and self-efficacy BSE with hearing about BSE, practicing BSE, knowing to practice BSE, knowing early detection methods of BC and practice CBE significant differences were observed (P < 0.005).

CONCLUSION

This study showed that BSE practice among Somalian women was very low, and they don't have sufficient knowledge about BSE and BC. Furthermore, this study revealed that many CHBMS significantly related to BSE practice in Somalian women, suggesting that BSE health education programs with CHBMS.

False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification

BACKGROUND AND OBJECTIVE

The aim of computer-aided-detection (CAD) systems for mammograms is to assist radiologists by marking region of interest (ROIs) depicting abnormalities. However, the confusing appearance of some normal tissues that visually look like masses results in a large proportion of marked ROIs with normal tissues. This paper copes with this problem and proposes a framework to reduce false positive masses detected by CAD.

METHODS

To avoid the error induced by the segmentation step, we proposed a segmentation-free framework with particular attention to improve feature extraction and classification steps. We investigated for the first time in mammogram analysis, Hilbert's image representation, Kolmogorov-Smirnov distance and maximum subregion descriptors. Then, a feature selection step is performed to select the most discriminative features. Moreover, we considered several classifiers such as Random Forest, Support Vector Machine and Decision Tree to distinguish between normal tissues and masses. Our experiments were carried out on a large dataset of 10168 ROIs (8254 normal tissues and 1914 masses) constructed from the Digital Database for Screening Mammography (DDSM). To simulate practical scenario, our normal regions are false positives asserted by a CAD system from healthy cases.

RESULTS

The combination of all the descriptors yields better results than each feature set used alone, and the difference is statistically significant. Besides, the feature selection steps yields a statistically significant increase in the accuracy values for the three classifiers. Finally, the random forest achieves the highest accuracy (81.09%), outperforming the SVM classifier (80.01%)) and decision tree (79.12%), but the difference is not statistically significant.

CONCLUSIONS

The accuracy of discrimination between normal and abnormal ROIs in mammograms obtained with the proposed gray level texture features sets are encouraging and comparable to these obtained with multiresolution features. Combination of several features as well as feature selection steps improve the results. To improve false positives reduction in CAD systems for breast cancer diagnosis, these features could be combined with multiresolution features.

Breast cancer diagnosis in digitized mammograms using curvelet moments

BACKGROUND

Feature extraction is a key issue in designing a computer aided diagnosis system. Recent researches on breast cancer diagnosis have reported the effectiveness of multiscale transforms (wavelets and curvelets) for mammogram analysis and have shown the superiority of curvelet transform. However, the curse of dimensionality problem arises when using the curvelet coefficients and therefore a reduction method is required to extract a reduced set of discriminative features.

METHODS

This paper deals with this problem and proposes a feature extraction method based on curvelet transform and moment theory for mammogram description. First, we performed discrete curvelet transform and we computed the four first-order moments from curvelet coefficients distribution. Hence, two feature sets can be obtained: moments from each band and moments from each level. In this work, both sets are studied. Then, the t-test ranking technique was applied to select the best features from each set. Finally, a k-nearest neighbor classifier was used to distinguish between normal and abnormal breast tissues and to classify tumors as malignant or benign. Experiments were performed on 252 mammograms from the Mammographic Image Analysis Society (mini-MIAS) database using the leave-one-out cross validation as well as on 11553 mammograms from the Digital Database for Screening Mammography (DDSM) database using 2×5-fold cross validation.

RESULTS

Experimental results prove the effectiveness and the superiority of curvelet moments for mammogram analysis. Indeed, results on the mini-MIAS database show that curvelet moments yield an accuracy of 91.27% (resp. 81.35 %) with 10 (resp. 8) features for abnormality (resp. malignancy) detection. In addition, empirical comparisons of the proposed method against state-of-the-art curvelet-based methods on the DDSM database show that the suggested method does not only lead to a more reduced feature set, but it also statistically outperforms all the compared methods in terms of accuracy.

CONCLUSIONS

In summary, curvelet moments are an efficient and effective way to extract a reduced set of discriminative features for breast cancer diagnosis.

Recent developments in DNA adduct analysis by mass spectrometry: a tool for exposure biomonitoring and identification of hazard for environmental pollutants

DNA adducts represent an important category of biomarkers for detection and exposure surveillance of potential carcinogenic and genotoxic chemicals in the environment. Sensitive and specific analytical methods are required to detect and differentiate low levels of adducts from native DNA from in vivo exposure. In addition to biomonitoring of environmental pollutants, analytical methods have been developed for structural identification of adducts which provides fundamental information for determining the toxic pathway of hazardous chemicals. In order to achieve the required sensitivity, mass spectrometry has been increasingly utilized to quantify adducts at low levels as well as to obtain structural information. Furthermore, separation techniques such as chromatography and capillary electrophoresis can be coupled to mass spectrometry to increase the selectivity. This review will provide an overview of advances in detection of adducted and modified DNA by mass spectrometry with a focus on the analysis of nucleosides since 2007. Instrument advances, sample and instrument considerations, and recent applications will be summarized in the context of hazard assessment. Finally, advances in biomonitoring applying mass spectrometry will be highlighted. Most importantly, the usefulness of DNA adducts measurement and detection will be comprehensively discussed as a tool for assessment of in vitro and in vivo exposure to environmental pollutants.

Resolving breast cancer heterogeneity by searching reliable protein cancer biomarkers in the breast fluid secretome

BACKGROUND

One of the major goals in cancer research is to find and evaluate the early presence of biomarkers in human fluids and tissues. To resolve the complex cell heterogeneity of a tumor mass, it will be useful to characterize the intricate biomolecular composition of tumor microenvironment (the so called cancer secretome), validating secreted proteins as early biomarkers of cancer initiation and progression. This approach is not broadly applicable because of the paucity of well validated and FDA-approved biomarkers and because most of the candidate biomarkers are mainly organ-specific rather than tumor-specific. For these reasons, there is an urgent need to identify and validate a panel of biomarker combinations for early detection of human tumors. This is especially important for breast cancer, the cancer spread most worldwide among women. It is well known that patients with early diagnosed breast cancer live longer, require less extensive treatment and fare better than patients with more aggressive and/or advanced disease.

RESULTS

In the frame of searching breast cancer biomarkers (especially using nipple aspirate fluid mirroring breast microenvironment), studies have highlighted an optimal combination of well-known biomarkers: uPA + PAI-1 + TF. When individually investigated they did not show perfect accuracy in predicting the presence of breast cancer, whereas the triple combination has been demonstrated to be highly predictive of pre-cancer and/or cancerous conditions, approaching 97-100% accuracy.

CONCLUSION

Despite the heterogeneous composition of breast cancer and the difficulties to find specific breast cancer biomolecules, the noninvasive analysis of the nipple aspirate fluid secretome may significantly improve the discovery of promising biomarkers, helping also the differentiation among benign and invasive breast diseases, opening new frontiers in early oncoproteomics.

Accurate sensitivity of quantum dots for detection of HER2 expression in breast cancer cells and tissues

Here we introduce novel optical properties and accurate sensitivity of Quantum dot (QD)-based detection system for tracking the breast cancer marker, HER2. QD525 was used to detect HER2 using home-made HER2-specific monoclonal antibodies in fixed and living HER2(+) SKBR-3 cell line and breast cancer tissues. Additionally, we compared fluorescence intensity (FI), photostability and staining index (SI) of QD525 signals at different exposure times and two excitation wavelengths with those of the conventional organic dye, FITC. Labeling signals of QD525 in both fixed and living breast cancer cells and tissue preparations were found to be significantly higher than those of FITC at 460-495 nm excitation wavelengths. Interestingly, when excited at 330-385 nm, the superiority of QD525 was more highlighted with at least 4-5 fold higher FI and SI compared to FITC. Moreover, QDs exhibited exceptional photostability during continuous illumination of cancerous cells and tissues, while FITC signal faded very quickly. QDs can be used as sensitive reporters for in situ detection of tumor markers which in turn could be viewed as a novel approach for early detection of cancers. To take comprehensive advantage of QDs, it is necessary that their optimal excitation wavelength is employed.

Beyond prostate-specific antigen - future biomarkers for the early detection and management of prostate cancer

Prostate-specific antigen is currently commonly used as a screening biomarker for prostate cancer, but it has limitations in both sensitivity and specificity. The development of novel biomarkers for early cancer detection has the potential to improve survival, reduce unnecessary investigations and benefit the health economy. Here we review the use and limitations of prostate-specific antigen and its subtypes, urinary biomarkers including PCA3, alpha-methylacyl-CoA racemase, the TMPRSS2-ERG fusion gene and microseminoprotein-beta, and other novel markers in both serum and urine. Many of these biomarkers are at early stages of development and require evaluation in prospective trials to determine their potential usefulness in clinical practice. Genetic profiling may allow for the targeting of high-risk populations for screening and may offer the opportunity to combine biomarker results with genotype to aid risk assessment.

Expression of the molecular chaperone αB-crystallin in infiltrating ductal breast carcinomas and the significance thereof: an immunohistochemical and proteomics-based strategy

This study aims to evaluate αB-crystallin expression in infiltrating ductal breast carcinomas (IDCAs), as well as, its prognostic significance. Using a two-dimensional electrophoresis matrix-assisted laser desorption/ionisation-time of flight mass spectrometry investigation coupled to an immunohistochemical approach, we have assessed the expression of αB-crystallin in IDCAs, as well as, in other types of breast tumors (invasive lobular carcinomas, medullary carcinomas, and in situ ductal carcinomas). Correlation between αB-crystallin expression and clinicopathological parameters of breast cancer has also been investigated. Proteomic analyses revealed an increased expression of αB-crystallin in IDCA tumors compared to adjacent nontumor tissues. Overexpression of this molecular chaperone was further confirmed in 51 tumor specimens. Statistical analyses revealed, however, no significant correlations between αB-crystallin expression and clinicopathological parameters of the disease (tumor stage, patient age, hormone receptors, SBR grade, and lymph node metastases). This study demonstrates the upregulation of αB-crystallin in IDCA tissues which may highlight its possible involvement in breast cancer development. Our findings do not, however, support the involvement of this molecular chaperone in the progression of this disease.

BREAST IMAGING SYSTEMS: A REVIEW AND COMPARATIVE STUDY

Due to the successful union between computational technologies and basic laws of physics and biological sciences, many biomedical imaging systems now find significant presence in clinical settings, aiding physicians in diagnosing most forms of human illness with more confidence. In the case of breast imaging, apart from the basic diagnosis, these imaging systems also help in locating the abnormal tissues for biopsy, identifying the exact margins of the lesion for good lumpectomy results, staging and restaging the cancer, detecting locations of metastases, and planning and following up treatment protocols. It is well known that early detection of cancer is the only way to increase the survival rate of the patient. Without such imaging systems, it would be hard and almost impossible for the physicians to determine the nature and extent of the disease by merely simple physical examinations and biopsies. This article presents a description of most of these invaluable breast-imaging systems. Moreover, a comparison of these modalities and a review of a few of the developments these devices have come across over the years are also given.

Updated recommendations for breast cancer screening

PURPOSE OF REVIEW

To describe the rationale behind the new recommendations for breast cancer screening issued by the U.S. Preventive Services Task Force (USPSTF).

RECENT FINDINGS

The USPSTF reviewed new summary evidence provided by the Oregon Evidence-based Practice Center and the Cancer Intervention Surveillance and Modeling Network about benefits and harms including radiation exposure and the likelihood of false-positive testing, unnecessary biopsies and treatments that may not impact overall breast cancer mortality.

SUMMARY

The USPSTF concluded maximal benefit in breast cancer mortality with least harms can be achieved with biennial mammography screening commenced at age 50 and continuing until age 74 years. A small additional benefit could be realized if screening starts at age 40 years. The USPSTF concluded that the decision to start biennial screening before age 50 years should be a personal one and take into account individual patient context, including an individual's values regarding specific benefits and harms. Evidence from large-scale randomized trials led the USPSTF to recommend against the teaching of breast self-examination. The USPSTF found insufficient evidence to recommend for or against performing clinical breast examination.

Discovery and preclinical validation of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer

Background

A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.

Methodology/Principal Findings

Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.

Conclusions

Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.

Tissue proteomics of the human mammary gland: towards an abridged definition of the molecular phenotypes underlying epithelial normalcy

Our limited understanding of the biological impact of the whole spectrum of early breast lesions together with a lack of accurate molecular-based risk criteria for the diagnosis and assignment of prognostic significance to biopsy findings presents an important problem in the clinical management of patients harboring precancerous breast lesions. As a result, there is a need to identify biomarkers that can better determine the outcome of early breast lesions by identifying subpopulations of cells in breast premalignant disease that are at high-risk of progression to invasive disease. A first step towards achieving this goal will be to define the molecular phenotypes of the various cell types and precursors - generated by the stem cell hierarchy - that are present in normal and benign conditions of the breast. To date there have been very few systematic proteomic studies aimed at characterizing the phenotypes of the different cell subpopulations present in normal human mammary tissue, partly due to the formidable heterogeneity of mammary tissue, but also due to limitations of the current proteomic technologies. Work in our laboratories has attempted to address in a systematic fashion some of these limitations and here we present our efforts to search for biomarkers using normal fresh tissue from non-neoplastic breast samples. From the data generated by the 2D gel-based proteomic profiling we were able to compile a protein database of normal human breast epithelial tissue that was used to support the biomarker discovery program. We review and present new data on the putative cell-progenitor marker cytokeratin 15 (CK15), and describe a novel marker, dihydropyriminidase-related protein 3 (DRP3) that in combination with CK15 and other well known proteins were used to define molecular phenotypes of normal human breast epithelial cells and their progenitors in resting acini, lactating alveoli, and large collecting ducts of the nipple. Preliminary results are also presented concerning DRP3 positive usual ductal hyperplasias (UDHs) and on single cell layer columnar cells (CCCs). At least two bona fide biomarkers of undifferentiated ERα/PgR negative luminal cells emerged from these studies, CK15 and c-KIT, which in combination with transformation markers may lead to the establishment of a protein signature able to identify breast precancerous at risk of progressing to invasive disease.