An overview of mammographic density and its association with breast cancer

Artificial intelligence in breast imaging

This article reviews current limitations and future opportunities for the application of computer-aided detection (CAD) systems and artificial intelligence in breast imaging. Traditional CAD systems in mammography screening have followed a rules-based approach, incorporating domain knowledge into hand-crafted features before using classical machine learning techniques as a classifier. The first commercial CAD system, ImageChecker M1000, relies on computer vision techniques for pattern recognition. Unfortunately, CAD systems have been shown to adversely affect some radiologists' performance and increase recall rates. The Digital Mammography DREAM Challenge was a multidisciplinary collaboration that provided 640,000 mammography images for teams to help decrease false-positive rates in breast cancer screening. Winning solutions leveraged deep learning's (DL) automatic hierarchical feature learning capabilities and used convolutional neural networks. Start-ups Therapixel and Kheiron Medical Technologies are using DL for breast cancer screening. With increasing use of digital breast tomosynthesis, specific artificial intelligence (AI)-CAD systems are emerging to include iCAD's PowerLook Tomo Detection and ScreenPoint Medical's Transpara. Other AI-CAD systems are focusing on breast diagnostic techniques such as ultrasound and magnetic resonance imaging (MRI). There is a gap in the market for contrast-enhanced spectral mammography AI-CAD tools. Clinical implementation of AI-CAD tools requires testing in scenarios mimicking real life to prove its usefulness in the clinical environment. This requires a large and representative dataset for testing and assessment of the reader's interaction with the tools. A cost-effectiveness assessment should be undertaken, with a large feasibility study carried out to ensure there are no unintended consequences. AI-CAD systems should incorporate explainable AI in accordance with the European Union General Data Protection Regulation (GDPR).

Epidemiological characteristics of and risk factors for breast cancer in the world

AIM

Breast cancer is the most common cancer among women and one of the most important causes of death among them. This review aimed to investigate the incidence and mortality rates of breast cancer and to identify the risk factors for breast cancer in the world.

MATERIALS AND METHODS

A search was performed in PubMed, Web of Science, and Scopus databases without any time restrictions. The search keywords included the following terms: breast cancer, risk factors, incidence, and mortality and a combination of these terms. Studies published in English that referred to various aspects of breast cancer including epidemiology and risk factors were included in the study. Overall, 142 articles published in English were included in the study.

RESULTS

Based on the published studies, the incidence rate of breast cancer varies greatly with race and ethnicity and is higher in developed countries. Results of this study show that mortality rate of breast cancer is higher in less developed regions. The findings of this study demonstrated that various risk factors including demographic, reproductive, hormonal, hereditary, breast related, and lifestyle contribute to the incidence of breast cancer.

CONCLUSION

The results of this study indicated that incidence and mortality rates of breast cancer is rising, so design and implementation of screening programs and the control of risk factors seem essential.

Breast Density Notification Letters and Websites: Are They Too "Dense"?

PURPOSE

To evaluate grade-level readability of dense breast notification letters (DBNs) and popular websites.

METHODS

HIPAA-compliant, institutional review board-exempt study. As of April 2018, letter characteristics and grade-level readability were evaluated from states with mandated text using five readability metrics, one of which was the Flesch-Kincaid Grade Level. For states that had mandated DBNs in 2016, the 2016 data were compared with 2018. Readability was also assessed for common websites about dense breasts.

RESULTS

Thirty states had mandated text for DBNs. All were written above a Flesch-Kincaid sixth-grade level. Eight state DBNs were around or below a Flesch-Kincaid eighth-grade level. Connecticut was the highest (19.4) and Alabama and New York lowest (both at 7.2). For all states, the mean readability score using the five metrics exceeded an eighth-grade level. Of states that had updated DBNs since 2016, only one state significantly improved readability (Missouri 13.1 to 8.5). All DBNs discussed that breast density may mask cancer on a mammogram, 20 discussed the association with increased risk of breast cancer, and 23 discussed supplemental screening. For websites, the range of Flesch-Kincaid grade-level readability was 6 to 11.3. The lowest was the American Cancer Society dense breast website (6.0) followed by ACR dense breast patient pamphlet (7.2).

CONCLUSION

As of 2018, the mean readability score using five metrics for all state-mandated DBNs exceeded an eighth-grade reading level. Compared with 2016, only one state significantly decreased DBN grade-level readability. Publicly available websites performed relatively better.

pSTAT3 expression associated with survival and mammographic density of breast cancer patients

BACKGROUND

Constitutive activation of STAT3 have been shown in several tumor types including breast cancer. We investigate STAT3 expresion as possible molecular marker for breast cancer early detection, as well as prognostic factor for determination of tumor agressiveness.

METHODS

In this study we measure p(Y705)STAT3 expression in tumor and adjacent tissue of breast cancer patients by Western blot. For relapse-free survival (RFS) and overall survival (OS) we used Log-Rank test.

RESULTS

We show that average expression of p (Y705) STAT3 in tumor tissue is higher compared to adjacent tissue. Moreover, we found that patients with HER2 positive receptors had significantly higher pSTAT3 expression compared to HER2 negative patients. We showed that patients with high mammographic density had significantly higher tumor expression of pSTAT3 compared to patients with low mammographic density. Also, we show that pSTAT3 expression correlates with longer RFS in the entire group of patients, as well as in the group of ER positive, in lymph node positive and in older group of breast cancer patients (with age over 50). Furthermore, in the entire group of patients, in ER positive, in lymph node positive and in older group of patient, high expression of pSTAT3 showed a better survival than low expression of pSTAT3.

CONCLUSION

Considering that the expression of pSTAT3 is associated with longer RFS and survival, it can be used as prognostic tools for determination of group of breast cancer patients with low-risk.

The mammography screening detection of ductal carcinoma in situ and invasive breast cancer according to women's characteristics: is it the same?

PURPOSE

Detection of ductal carcinoma in situ (DCIS) has increased with the mammography dissemination. Given the potential role of DCIS as a precursor of invasive breast cancer (IBC), we aimed to assess whether women's characteristics have a different effect on the DCIS compared to IBC detection rate.

METHODS

This study included 3,609,569 screening mammograms performed from 2002 to 2015 in our organized breast cancer screening program, which actively invites women 50-69 years of age. The association between women's characteristics and the DCIS detection rate, the IBC detection rate and the odds ratio of DCIS among screen-detected cancers was assessed by logistic regression and generalized estimating equations with independent correlation matrix and sandwich estimator.

RESULTS

A total of 4173 DCIS and 15,136 IBC were screen-detected. Increasing women's age, current hormone replacement therapy use and higher body mass index were less associated with the DCIS than with IBC detection rates (p value for the odds of DCIS among screen-detected cancers of, respectively, < 0.0001, 0.0244 and < 0.0001). In contrast, having a previous breast aspiration or biopsy and increasing breast density were more strongly associated with DCIS than with IBC detection rates (p value of, respectively, 0.0050 and < 0.0001).

CONCLUSION

The results suggest that some women's characteristics could be playing a role in the initiation and other in the progression from in situ to invasive breast cancer. These characteristics can also affect the screening sensitivity, and this effect may differ depending on whether screen-detected cases were DCIS or IBC.

Mechanisms of Matrix-Induced Chemoresistance of Breast Cancer Cells-Deciphering Novel Potential Targets for a Cell Sensitization

Tumor cell binding to microenvironment components such as collagen type 1 (COL1) attenuates the sensitivity to cytotoxic drugs like cisplatin (CDDP) or mitoxantrone (MX), referred to as cell adhesion mediated drug resistance (CAM-DR). CAM-DR is considered as the onset for resistance mutations, but underlying mechanisms remain elusive. To evaluate CAM-DR as target for sensitization strategies, we analyzed signaling pathways in human estrogen-positive MCF-7 and triple-negative MDA-MB-231 breast cancer cells by western blot, proteome profiler array and TOP-flash assay in presence of COL1. β1-Integrins, known to bind COL1, appear as key for mediating COL1-related resistance in both cell lines that primarily follows FAK/PI3K/AKT pathway in MCF-7, and MAPK pathway in MDA-MB-231 cells. Notably, pCREB is highly elevated in both cell lines. Consequently, blocking these pathways sensitizes the cells evidently to CDDP and MX treatment. Wnt signaling is not relevant in this context. A β1-integrin knockdown of MCF-7 cells (MCF-7-β1-kd) reveals a signaling shift from FAK/PI3K/AKT to MAPK pathway, thus CREB emerges as a promising primary target for sensitization in MDA-MB-231, and secondary target in MCF-7 cells. Concluding, we provide evidence for importance of CAM-DR in breast cancer cells and identify intracellular signaling pathways as targets to sensitize cells for cytotoxicity treatment regimes.

In Situ Drug Delivery to Breast Cancer-Associated Extracellular Matrix

The extracellular matrix (ECM) contributes to tumor progression through changes induced by tumor and stromal cell signals that promote increased ECM density and stiffness. The increase in ECM stiffness is known to promote tumor cell invasion into surrounding tissues and metastasis. In addition, this scar-like ECM creates a protective barrier around the tumor that reduces the effectiveness of innate and synthetic antitumor agents. Herein, clinically approved breast cancer therapies as well as novel experimental approaches that target the ECM are discussed, including in situ hydrogel drug delivery systems, an emerging technology the delivers toxic chemotherapeutics, gene-silencing microRNAs, and tumor suppressing immune cells directly inside the tumor. Intratumor delivery of therapeutic agents has the potential to drastically reduce systemic side effects experienced by the patient and increase the efficacy of these agents. This review also describes the opposing effects of ECM degradation on tumor progression, where some studies report improved drug delivery and delayed cancer progression and others report enhanced metastasis and decreased patient survival. Given the recent increase in ECM-targeting drugs entering preclinical and clinical trials, understanding and addressing the factors that impact the effect of the ECM on tumor progression is imperative for the sake of patient safety and survival outcome.

Role of extracellular matrix in breast cancer development: a brief update

Evidence is increasing on the crucial role of the extracellular matrix (ECM) in breast cancer progression, invasion and metastasis with almost all mortality cases owing to metastasis. The epithelial-mesenchymal transition is the first signal of metastasis involving different transcription factors such as Snail, TWIST, and ZEB1. ECM remodeling is a major event promoting cancer invasion and metastasis; where matrix metalloproteinases (MMPs) such as MMP-2, -9, -11, and -14 play vital roles degrading the matrix proteins for cancer spread. The β-D mannuronic acid (MMP inhibitor) has anti-metastatic properties through inhibition of MMP-2, and -9 and could be a potential therapeutic agent. Besides the MMPs, the enzymes such as LOXL2, LOXL4, procollagen lysyl hydroxylase-2, and heparanase also regulate breast cancer progression. The important ECM proteins like integrins (b1-, b5-, and b6- integrins), ECM1 protein, and Hic-5 protein are also actively involved in breast cancer development. The stromal cells such as tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs), and adipocytes also contribute in tumor development through different processes. The TAMs become proangiogenic through secretion of VEGF-A and building vessel network for nourishment and invasion of the tumor mass. The latest developments of ECM involvement in breast cancer progression has been discussed in this review and this study will help researchers in designing future work on breast cancer pathogenesis and developing therapy targeted to the ECM components.