An overview of mammographic density and its association with breast cancer

Circulating sex hormones and volumetric breast density: A prospective study in women from the EPIC Florence cohort

Mammographic breast density (MBD) is a known risk factor for breast cancer. This study aimed to evaluate prospectively how circulating levels of sex hormones and sex hormones binding globulin (SHBG) are associated with volumetric percent density (VPD, %) and absolute breast dense volume (DV, cm3) measured after an average 13.5 years of follow up. We included 422 post- and 445 pre-menopausal women enrolled in the Florence section of the European Prospective Investigation into Cancer and Nutrition study. Blood levels of circulating sex hormones and SHBG were determined in serum samples collected at enrollment. The automated Volpara™ density software was used to obtain DV and VPD measures from the first available full-field digital mammography performed after enrollment. We carried out adjusted linear regression models for post-menopausal and pre-menopausal women, separately. Higher baseline blood levels of SHBG were associated with higher VPD both in post-menopausal (%Diff 17.2 III vs. I tertile, p-value 0.02, p-trend 0.02) and pre-menopausal women (%Diff 21.1 III vs. I tertile, p-value 0.004, p-trend 0.004). Among pre-menopausal women a modifying effect of parity emerged, with significant inverse associations of estradiol, free estradiol, estrone, and free testosterone with VPD in women with a lower number of births or higher age at every birth. DV was not associated with sex hormones or SHBG. A direct association between increasing serum level of SHBG and VPD was observed both in post- and pre-menopausal women. This association need to be further investigated in order to better understand the underlying mechanisms.

Study on ABUS Applicability for Rural Women With Low Health Resources in China-Large-Scale Population, Non-Opportunistic Screening

OBJECTIVES

Comparing the screening performance of different breast cancer screening methods and exploring the applicability of automated breast ultrasonography (ABUS) in rural areas with low health resources in China.

METHODS

Women aged 35-64 underwent hand-held ultrasonography (HHUS) and ABUS in Zezhou County, Jincheng City, Shanxi Province, China from 2018 to 2021. Additionally, women aged 45-69 were also screened with mammography (MG). We compared the 3 methods' cancer detection rates, diagnostic accuracy, and overall screening performance, stratified by age groups and breast density. The chi-square test was used to analyze indicators such as sensitivity, specificity, and referral rate.

RESULTS

The mean age of the 9100 women studied was 45 ± 6.42 years, and 25 cases of breast cancer were identified (2.72‰). The proportion of dense breasts is higher among women aged 45-64 years (67.52%). Compared to the non-dense breast group, the detection rate of breast cancer by MG is significantly reduced in the dense breast group (3.42‰ versus 1.97‰). The diagnostic accuracy rate of ABUS and HHUS for lesions is higher than that of MG (P < .05). The kappa coefficient indicates moderate agreement in diagnostic results between HHUS and ABUS. However, the agreement between HHUS/ABUS and MG is poor. There were no statistical differences in sensitivity and specificity among the 3 screening methods. The referral rate and NNR for ultrasound were lower than those for MG (P < .05), but there were no statistically significant differences between ABUS and HHUS.

CONCLUSIONS

Among women with denser breasts, ultrasound has a higher diagnostic accuracy rate compared to MG, and it avoids unnecessary biopsies. Compared to HHUS, ABUS can diagnose malignant tumors more objectively and standardized.

Impact of breast density on re-excision and recurrence of breast cancer following breast conserving surgery

BACKGROUND

Mammographic breast density (BD) has garnered clinical interest due to its impact on breast cancer (BC) risk, sensitivity of mammographic screening, and tumour size at presentation. There is conflicting evidence as to BD's effect on re-excisions and recurrence following breast conserving surgery (BCS). We hypothesize that increasing BD may obscure disease, resulting in an underestimation of the extent of disease, and a greater risk of re-excision and local recurrence following BCS for invasive BC.

METHODS

A retrospective, population-based review of patients undergoing BCS for invasive BC between January 1, 2010 and December 31, 2016 was performed. Patients undergoing mastectomy as primary management, previous or recurrent BC, or who were lost to follow-up were excluded. Patient age, BI-RADS score, treatments, and pathologic findings were analyzed by Pearson's Chi-Square or Fisher's exact test for categorical variables and the Kruskal-Wallis test for continuous variables.

RESULTS

1371 and 1169 patients were eligible for re-excision and recurrence analysis, respectively. Higher BD is significantly associated with younger age, larger tumour size, and pathologic lymph node involvement. Multivariate analysis revealed no overall impact of BD on re-excision rate, though high BD (BI-RADS D vs A) was associated with a significant decrease re-excision rate (OR: 0.33, p ​= ​0.019). No influence of BD on disease recurrence was observed.

CONCLUSION

Contrary to previous reports, high BD was associated with a decreased need for re-excision following BCS, which may be related to unmeasured factors. Increased BD was not associated with increased local disease recurrence.

Relationship between breast tissue involution and breast cancer

Breast tissue involution is a process in which the epithelial tissue of the mammary gland gradually disappears with age. The relationship between breast tissue involvement and breast cancer (BC) has received increasing amounts of attention in recent years. Many scholars believe that breast tissue involution is a significant risk factor for BC. Breast imaging parameters, particularly mammographic density (MD), may indirectly reflect the degree of breast tissue involution, which may provide a solid basis for classifying priority screening groups for BC. This review explored the relationship between breast tissue involution and BC by providing an overview of breast tissue involution and elaborating on the association between MD and BC. Consistent with the results of other studies, women with complete breast tissue involution had a lower risk of BC, whereas women with a high MD had a relatively greater risk of BC.

The value of predicting breast cancer with a DBT 2.5D deep learning model

OBJECTIVE

To evaluate the accuracy and efficacy of a 2.5-dimensional deep learning (DL) model based on digital breast tomosynthesis (DBT) in predicting breast cancer.

METHODS

Through a retrospective analysis of data from 361 patients with breast tumor lesions treated at Shandong Provincial Hospital Affiliated to Shandong First Medical University between 2018 and 2020, this study utilized deep convolutional neural networks (DCNN) to automatically extract key features from DBT images. By applying dimensionality reduction and feature fusion selection, a variety of machine learning predictive models based on a 2.5-dimensional feature set were constructed. Additionally, a comprehensive predictive model was developed by combining univariate and multivariate logistic regression analyses with clinical data. The model's performance was assessed using receiver operating characteristic (ROC) curves, area under the curve (AUC) values, and accuracy rates.

RESULTS

In the test set, DBT 2.5D deep learning-based logistic regression, LightGBM, multilayer perceptron, and comprehensive models achieved accuracies of 72.2%, 75.0%, 79.2%, and 80.6%; AUCs of 0.826, 0.756, 0.859, and 0.871; sensitivities of 63.8%, 70.2%, 80.9%, and 87.2%; specificities of 88.0%, 84.0%, 76.0%, and 68.0%; PPVs of 90.9%, 89.2%, 86.4%, and 83.7%; NPVs of 56.4%, 60.0%, 67.9%, and 73.9%; and F1 scores of 75.0%, 78.6%, 83.5%, and 85.4%, respectively. These results underscore the high efficiency and potential of DBT 2.5D deep learning models in breast cancer diagnosis, particularly the comprehensive model's superior performance across key metrics.

CONCLUSION

The 2.5D deep learning model based on DBT shows good performance in preoperative breast cancer prediction, with its integration with clinical data further enhancing its effectiveness. The combination of deep learning and radiomics offers a viable approach for early breast cancer diagnosis, supporting the development of more accurate personalized diagnostic and treatment strategies.

Reproductive determinants of mammographic density in black women

PURPOSE

While high mammographic density has been established as one of the strongest, independent breast cancer risk factors, few studies have reported determinants of mammographic density in Black women. We aimed to identify reproductive-related characteristics associated with mammographic density in Black women.

METHODS

In data from a large mammography repository established in the Black Women's Health Study, we used Cumulus software to assess mammographic density from digital screening mammograms in 5,905 women ages 40-74. We used linear regression models to quantify the associations of parity, age at first birth, age at last birth, history of breastfeeding, and duration of breastfeeding with percent mammographic density. Models were adjusted for age, body mass index, and other breast cancer risk factors.

RESULTS

Among parous women age < 55 years, mean percent mammographic density was 2.0 percentage points (95% CI 0.3, 3.7) higher in women with a history of ≥ 3 births than in women with a history of only 1 birth. The magnitude of associations of number of births with mammographic density varied somewhat by age at first birth and age at mammography. We found no significant associations between other reproductive factors and mammographic density.

CONCLUSION

In this large population of Black women, a higher number of births was modestly associated with higher percent mammographic density. This association may in part be influenced by age at first birth and age at mammography.

Understanding Susceptibility to Breast Cancer: From Risk Factors to Prevention Strategies

Breast cancer is the most common malignancy among women globally, with incidence rates continuing to rise. A comprehensive understanding of its risk factors and the underlying biological mechanisms that drive tumor initiation is essential for developing effective prevention strategies. This review examines key non-modifiable risk factors, such as genetic predisposition, demographic characteristics, family history, mammographic density, and reproductive milestones, as well as modifiable risk factors like exogenous hormone exposure, obesity, diet, and physical inactivity. Importantly, reproductive history plays a dual role, providing long-term protection while temporarily increasing breast cancer risk shortly after pregnancy. Current chemoprevention strategies primarily depend on selective estrogen receptor modulators (SERMs), including tamoxifen and raloxifene, which have demonstrated efficacy in reducing the incidence of estrogen receptor-positive breast cancer but remain underutilized due to adverse effects. Emerging approaches such as aromatase inhibitors, RANKL inhibitors, progesterone antagonists, PI3K inhibitors, and immunoprevention strategies show promise for expanding preventive options. Understanding the interactions between risk factors, hormonal influences, and tumorigenesis is critical for optimizing breast cancer prevention and advancing safer, more targeted chemopreventive interventions.

Breast cancer shares many epidemiological, lifestyle, and local hormonal and metabolic underpinnings with endometrial and ovarian cancer: a narrative review

Background and Objective

Breast, endometrial, and ovarian cancers (OCs) are significant public health concerns. Approximately three million patients are diagnosed with one of the three tumor types annually. The three tumor types exhibit related epidemiological trends, lifestyle risk factors, and tumor-specific characteristics which may influence their incidence and outcomes. While the majority of the literature examining hormone dependence of cancer appropriately is centered around breast cancer (BC), insufficient attention has been paid to how lessons from the biology of endometrial and OC may inform what we know about the biology of BC and vice versa. This narrative review seeks to address that unmet need.

Methods

The construction of this narrative review involved searching PubMed in April and July 2024 for manuscripts related to breast cancer metabolism, ovarian cancer metabolism, and endometrial cancer metabolism. Only manuscripts written in English were considered.

Key Content and Findings

This narrative review discusses epidemiologic, systemic, and local factors that may affect breast, endometrial, and OC. Simultaneously analyzing these three tumors offers an opportunity to gain unifying insights into reproductive hormone-dependent cancer biology; unfortunately, the field lacks studies directly comparing the impact of the aforementioned factors on these three tumor types. Therefore, we are limited to comparing the impact of similar systemic factors on tumor progression in each tumor type.

Conclusions

There is some convergence of systemic metabolic changes, particularly with regard to factors associated with obesity, on the biology of breast, ovarian, and endometrial cancer. However, future research is needed in order to clarify the convergent-or potentially divergent-mechanism(s) by which obesity affects breast, endometrial and OC.

XGBoost Enhances the Performance of SAFE: A Novel Microwave Imaging System for Early Detection of Malignant Breast Cancer

BACKGROUND/OBJECTIVES

Breast cancer is a significant global health concern, and early detection is crucial for improving patient outcomes. Mammography is widely used but has limitations, particularly for younger women with denser breasts. These include reduced sensitivity, false positives, and radiation risks. This highlights the need for alternative screening methods. In this study, we assess the performance of SAFE (Scan and Find Early), a novel microwave imaging device, in detecting breast cancer in a larger patient cohort. Unlike previous studies that predominantly relied on cross-validation, this study employs a more reliable, independent evaluation methodology to enhance generalizability.

METHODS

We developed an XGBoost model to classify breast cancer cases into positive (malignant) and negative (benign or healthy) groups. The model was analyzed with respect to key factors such as breast size, density, age, tumor size, and histopathological findings. This approach provides a better understanding of how these factors influence the model's performance, using an independent evaluation methodology for increased reliability.

RESULTS

Our results demonstrate that SAFE exhibits high sensitivity, particularly in dense breasts (91%) and younger patients (83%), suggesting its potential as a supplemental screening tool. Additionally, the system shows high detection accuracy for both small (<2 cm) and larger lesions, proving effective in early cancer detection.

CONCLUSIONS

This study reinforces the potential of SAFE to complement existing screening methods, particularly for patients with dense breasts, where mammography's sensitivity is reduced. The promising results warrant further research to solidify SAFE's clinical application as an alternative screening tool for breast cancer detection.

Breast density awareness and cancer risk in the UAE: Enhancing Women's engagement in early detection

INTRODUCTION

Increased breast density (BD) is significantly correlated to higher rates of breast cancer (BC), yet awareness among women remains low. This study assesses women's understanding of BD, its implications for cancer risk, and their engagement in screening practices.

METHODS

A cross-sectional survey of 212 women aged 40 to 74 was conducted using an online questionnaire developed within Google Forms, including open and closed-ended questions. Demographic information was collected, followed by BC awareness and BD knowledge questions. Data were analyzed using IBM SPSS software, with categorical data reported as numbers and percentages, and Chi-square tests employed to explore associations between variables.

RESULTS

Of the 212 participants, those with healthcare involvement were significantly more likely to recognize BD as a BC risk factor, with 25.0 % acknowledging its impact compared to 16.8 % of non-professionals (χ2 = 9.520, p = 0.009). Formal training was associated with increased engagement in breast self-examinations (BSE), with 58.6 % of trained individuals practicing BSE versus 30.1 % without training (χ2 = 9.108, p = 0.003).

CONCLUSION

Findings underscore the need for targeted educational initiatives to improve BD awareness among women in the general public, empowering them to identify as at-risk and to participate in screening programs.

IMPACT ON PRACTICE

This study emphasizes integrating BD awareness into clinical practice. Healthcare providers are encouraged to implement educational strategies that inform women of BD, its associated risks, and the value of regular screening. Enhancing self-awareness among patients may facilitate earlier detection, ultimately improving BC outcomes and public health efforts.

Impact of prolactin treatment on enhancing the cellular responses of MCF7 breast cancer cells to tamoxifen treatment

Breast cancer remains one of the most challenging diseases to treat due to its heterogeneity, propensity to recur, capacity to spread to distant vital organs, and, ultimately, patient death. Estrogen receptor-positive illness comprises the most common breast cancer subtype. Preclinical progress is hampered by the scarcity of medication-naïve estrogen receptor-positive tumour models that recapitulate metastatic development and treatment resistance. It is becoming increasingly clear that loss of differentiation and increased cellular stemness and plasticity are important causes of cancer evolution, heterogeneity, recurrence, metastasis, and treatment failure. Therefore, it has been suggested that reprogramming cancer cell differentiation could offer an effective method of reversing cancer through terminal differentiation and maturation. In this context, the hormone prolactin is well recognized for its pivotal involvement in the development of the mammary glands lobuloalveolar tissue and the terminal differentiation that drives the production of the milk protein gene and lactation. Additionally, numerous studies have examined the engagement of prolactin in breast cancer as a differentiation player that resulted in the ablation of tumour growth and progression. Here, we showed that a pre-treatment of the estrogen-positive breast cancer cell line with prolactin led to a considerable improvement in the sensitivity of this cancer cell to Tamoxifen endocrine therapy. We also showed a favourable prognostic value of prolactin receptors/estrogen receptors 1 (or alpha) co-expression on breast cancer patients outcomes, and this co-expression is highly correlated with the well-differentiated breast tumour type. Our results revealed a fruitful aspect of the effects of prolactin in improving the responses of breast cancer cells to conventional endocrine therapy. Moreover, these findings further validated the ability of prolactin as a persuader of a more differentiated and less aggressive breast cancer phenotype. Hence, it suggested a potential implication of prolactin as a therapeutic candidate.

A bidirectional Mendelian randomization analysis of the causal relationship between inflammatory bowel disease and breast cancer based on estrogen receptor status

The incidence of patients diagnosed with either breast cancer (BC) or inflammatory bowel disease (IBD) is increasing each year. IBD has been shown to be strongly associated with the development of a variety of solid tumors, but the relationship with breast cancer is not yet definitive. We explored the causative relationship between IBD and BC using a Mendelian randomization (MR) strategy. MR-Egger regression, weighted median (WM), simple median (SM), maximum likelihood (ML), and inverse variance weighting (IVW) methods were among the analytical techniques used in this work. The examination of heterogeneity was conducted by the use of Cochran's Q test and Rucker's Q test. The sensitivity analysis in this study used the IVW and MR-Egger methodologies. The results of our investigation suggested that IBD had a beneficial impact on estrogen receptor-negative (ER-) breast cancer (odds ratio (OR) = 0.92, P = 0.02). The study did not find a significant association between IBD and the risk of developing overall breast cancer (OR = 0.99, P = 0.60), as well as estrogen receptor-positive (ER+) breast cancer (OR = 1.02, P = 0.60) specifically. In addition, our study findings indicated that there was a detrimental association between ER+ breast cancer and IBD as determined using reverse MR analysis (OR = 1.07, P = 0.04). Furthermore, this analysis failed to observe any significant association between overall breast cancer (OR = 1.07, P = 0.07) or ER- breast cancer (OR = 0.99, P = 0.89) and IBD. Our bidirectional MR study yielded a correlation between IBD and some specific hormone receptor status of BC.

Effect of patient age and breast parenchymal density on Breast Imaging-Reporting and Data System (BIRADS-4) Subcategorization

Background & Objectives

BI-RADS (Breast Imaging-Reporting and Data System) is a standard radiological risk assessment for breast lesions, including six categories, of which category four is the widest range of likelihood cancer risk (2% to 95%). This study aimed to evaluate the effect of patient age and ACR breast density on the positive predictive value (PPV) of BI-RADS 4 subcategorization (4A, 4B, and 4C).

Methods

A retrospective study was conducted at King Fahed Hospital (KFH) between September 1, 2021, and June 30, 2022. PPV was calculated based on a histopathological report for all lesions. The correlation was made with patients' age groups ranging from < 45 years, 45-55 years, and > 55 years and four types of breast density on mammography. We used IBM-SPSS for data synthesis. The Chi-square test was used to assess any correlation between variables. A p-value < 0.05 was considered statistically significant.

Results

The mean age was 44.62 ±14.32. Of the 248 cases, 81% were benign, 17% were malignant, and 2% were high-risk lesions. The age-related PPV of each BI-RADS category showed no significant differences among all age groups. However, the breast composition-related PPV cases with BI-RADS categories differed significantly within subcategory 4C (p-value<0.001).

Conclusions

There were no positive relationships between increasing age and PPV in BI-RADS 4 subcategories 4A, B, and C. Breast composition-related PPV showed significant differences with BI-RADS 4C subcategories.

Macrophages in tumor cell migration and metastasis

Tumor-associated macrophages (TAMs) are a phenotypically diverse, highly plastic population of cells in the tumor microenvironment (TME) that have long been known to promote cancer progression. In this review, we summarize TAM ontogeny and polarization, and then explore how TAMs enhance tumor cell migration through the TME, thus facilitating metastasis. We also discuss how chemotherapy and host factors including diet, obesity, and race, impact TAM phenotype and cancer progression. In brief, TAMs induce epithelial-mesenchymal transition (EMT) in tumor cells, giving them a migratory phenotype. They promote extracellular matrix (ECM) remodeling, allowing tumor cells to migrate more easily. TAMs also provide chemotactic signals that promote tumor cell directional migration towards blood vessels, and then participate in the signaling cascade at the blood vessel that allows tumor cells to intravasate and disseminate throughout the body. Furthermore, while chemotherapy can repolarize TAMs to induce an anti-tumor response, these cytotoxic drugs can also lead to macrophage-mediated tumor relapse and metastasis. Patient response to chemotherapy may be dependent on patient-specific factors such as diet, obesity, and race, as these factors have been shown to alter macrophage phenotype and affect cancer-related outcomes. More research on how chemotherapy and patient-specific factors impact TAMs and cancer progression is needed to refine treatment strategies for cancer patients.

Reflection mode polarimetry guides laser mass spectrometry to diagnostically important regions of human breast cancer tissue

To enhance the clinical utility of mass spectrometry (MS), lengthy dwell times on less informative regions of patient specimens (e.g., adipose tissue in breast) must be minimized. Additionally, a promising variant of MS known as picosecond infrared laser MS (PIRL-MS) faces further challenges, namely, lipid contamination when probing adipose tissue. Here we demonstrate on several thick non-sectioned resected human breast specimens (healthy and malignant) that reflection-mode polarimetric imaging can robustly guide PIRL-MS toward regions devoid of significant fat content to (1) avoid signal contamination and (2) shorten overall MS analysis times. Through polarimetric targeting of non-fat regions, PIRL-MS sampling revealed feature-rich spectral signatures including several known breast cancer markers. Polarimetric guidance mapping was enabled by circular degree-of-polarization (DOP) imaging via both Stokes and Mueller matrix polarimetry. These results suggest a potential synergistic hybrid approach employing polarimetry as a wide-field-imaging guidance tool to optimize efficient probing of tissue molecular content using MS.

Field cycling imaging to characterise breast cancer at low and ultra-low magnetic fields below 0.2 T

BACKGROUND

This prospective feasibility study explores Field-Cycling Imaging (FCI), a new MRI technology that measures the longitudinal relaxation time across a range of low magnetic field strengths, providing additional information about the molecular properties of tissues. This study aims to assess the performance of FCI and investigate new quantitative biomarkers at low fields within the context of breast cancer.

METHODS

We conducted a study involving 9 people living with breast cancer (10 tumours in total, mean age, 54 ± 10 years). FCI images were obtained at four magnetic field strengths (2.3 mT to 200 mT). FCI images were processed to generate T1 maps and 1/T1 dispersion profiles from regions of tumour, normal adipose tissue, and glandular tissue. The dispersion profiles were subsequently fitted using a power law model. Statistical analysis focused on comparing potential FCI biomarkers using a Mann-Whitney U or Wilcoxon signed rank test.

RESULTS

We show that low magnetic fields clearly differentiate tumours from adipose and glandular tissues without contrast agents, particularly at 22 mT (1/T1, median [IQR]: 6.8 [3.9-7.8] s-1 vs 9.1 [8.9-10.2] s-1 vs 8.1 [6.2-9.2] s-1, P < 0.01), where the tumour-to-background contrast ratio was highest (62%). Additionally, 1/T1 dispersion indicated a potential to discriminate invasive from non-invasive cancers (median [IQR]: 0.05 [0.03-0.09] vs 0.19 [0.09-0.26], P = 0.038).

CONCLUSIONS

To the best of our knowledge, we described the first application of in vivo FCI in breast cancer, demonstrating relevant biomarkers that could complement diagnosis of current imaging modalities, non-invasively and without contrast agents.

Role of SLC31A1 in prognosis and immune infiltration in breast cancer: a novel insight

OBJECTIVE

Copper, an essential metal element for humans, plays vital functions in cancer prognosis and immunity. SLC31A1, a high-affinity copper transporter, helps regulate copper homeostasis and has been implicated in tumor prognosis through mechanisms such as drug resistance, autophagy, ferroptosis, and cuproptosis. However, the role of SLC31A1 in breast cancer (BRCA) and its association with tumor immune infiltration has not been fully elucidated. This study aimed to investigate the expression pattern of SLC31A1, its clinical significance, and its effect on tumor immune infiltration in BRCA.

METHODS

We comprehensively analyzed multiple datasets, including Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), UALCAN, and Kaplan-Meier (KM) plotter, to assess the expression of SLC31A1 and its prognostic value in BRCA. Additionally, TIMER and TISIDB were used to explore the correlation between SLC31A1 expression and the extent of tumor immune infiltration.

RESULTS

SLC31A1 was significantly upregulated in BRCA tissues compared to adjacent non-tumor tissues. Higher SLC31A1 expression levels were associated with poorer clinical outcome. Multivariate Cox regression analysis confirmed that SLC31A1 served as an independent prognostic indicator. Furthermore, SLC31A1 expression showed significant associations with various immunomodulators, chemokines, chemokine receptors, and tumor-infiltrating lymphocytes (TILs), including CD8+ T cells, CD4+ T cells, regulatory T cells (Tregs), follicular helper T cells (Tfh), neutrophils, M2 macrophages, tumor-associated macrophages (TAMs), and monocytes. These findings suggest that SLC31A1 may regulate macrophage polarization and T cell exhaustion in BRCA, contributing to immune evasion and poor prognosis.

CONCLUSION

Our study underscores the importance of further research to explore the therapeutic potential of targeting SLC31A1 and to uncover its additional roles in BRCA beyond the known mechanisms of drug resistance, autophagy, ferroptosis, and cuproptosis.

Proteomic and Phosphoproteomic Profiling of Matrix Stiffness-Induced Stemness-Dormancy State Transition in Breast Cancer Cells

The dormancy of cancer stem cells is a major factor leading to drug resistance and a high rate of late recurrence and mortality in estrogen receptor-positive (ER+) breast cancer. Previously, we demonstrated that a stiffer matrix induces tumor cell dormancy and drug resistance, whereas a softened matrix promotes tumor cells to exhibit a stem cell state with high proliferation and migration. In this study, we present a comprehensive analysis of the proteome and phosphoproteome in response to gradient changes in matrix stiffness, elucidating the mechanisms behind cell dormancy-induced drug resistance. Overall, we found that antiapoptotic and membrane transport processes may be involved in the mechanical force-induced dormancy resistance of ER+ breast cancer cells. Our research provides new insights from a holistic proteomic and phosphoproteomic perspective, underscoring the significant role of mechanical forces stemming from the stiffness of the surrounding extracellular matrix as a critical regulatory factor in the tumor microenvironment.

Association between breastfeeding, mammographic density, and breast cancer risk: a review

BACKGROUND

Mammographic density has been associated with breast cancer risk, and is modulated by established breast cancer risk factors, such as reproductive and hormonal history, as well as lifestyle. Recent epidemiological and biological findings underscore the recognized benefits of breastfeeding in reducing breast cancer risk, especially for aggressive subtypes. Current research exploring the association among mammographic density, breastfeeding, and breast cancer is sparse.

MAIN FINDINGS

Changes occur in the breasts during pregnancy in preparation for lactation, characterized by the proliferation of mammary gland tissues and the development of mammary alveoli. During lactation, the alveoli fill with milk, and subsequent weaning triggers the involution and remodeling of these tissues. Breastfeeding influences the breast microenvironment, potentially altering mammographic density. When breastfeeding is not initiated after birth, or is abruptly discontinued shortly after, the breast tissue undergoes forced and abrupt involution. Conversely, when breastfeeding is sustained over an extended period and concludes gradually, the breast tissue undergoes slow remodeling process known as gradual involution. Breast tissue undergoing abrupt involution displays denser stroma, altered collagen composition, heightened inflammation and proliferation, along with increased expression of estrogen receptor α (ERα) and progesterone receptor. Furthermore, elevated levels of pregnancy-associated plasma protein-A (PAPP-A) surpass those of its inhibitors during abrupt involution, enhancing insulin-like growth factor (IGF) signaling and collagen deposition. Prolactin and small molecules in breast milk may also modulate DNA methylation levels. Drawing insights from contemporary epidemiological and molecular biology studies, our review sheds light on how breastfeeding impacts mammographic density and explores its role in influencing breast cancer.

CONCLUSION

This review highlights a clear protective link between breastfeeding and reduced breast cancer risk via changes in mammographic density. Future research should investigate the effects of breastfeeding on mammographic density and breast cancer risk among various ethnic groups and elucidate the molecular mechanisms underlying these associations. Such comprehensive research will enhance our understanding and facilitate the development of targeted breast cancer prevention and treatment strategies.

Pharmacogenetics of Toxicities Related to Endocrine Treatment in Breast Cancer: A Systematic Review and Meta-analysis

BACKGROUND/AIM

Endocrine therapy is the standard treatment for hormone receptor-positive (HR+) breast cancer (BC). Yet, it is accompanied by treatment-related toxicities, leading to poor treatment adherence, high relapse, and low rates of survival. While pharmacogenomic variants have the potential to guide personalized treatment, their predictive value is inconsistent across published studies.

MATERIALS AND METHODS

To systematically assess the literature's current landscape of pharmacogenomics of endocrine therapy-related adverse drug effects, systematic searches in MEDLINE, Embase, Cochrane CENTRAL, Google Scholar and PharmGKB databases were conducted.

RESULTS

We identified 87 articles. Substantial heterogeneity and variability in pharmacogenomic effects were evident across studies, with many using data from the same cohorts and predominantly focusing on the Caucasian population and postmenopausal women. Meta-analyses revealed Factor V Leiden mutation as a predictor of thromboembolic events in tamoxifen-treated women (p<0.0001). Meta-analyses also found that rs7984870 and rs2234693 were associated with musculoskeletal toxicities in postmenopausal women receiving aromatase inhibitors (p<0.0001 and p<0.0001, respectively).

CONCLUSION

Overall, the current body of evidence regarding the potential role of pharmacogenomics in endocrine therapy-related toxicity in BC remains largely inconclusive. Key concerns include the heterogeneity in toxicity definitions, lack of consideration for genotype-treatment interactions, and the failure to account for multiple testing. The review underscores the necessity for larger and well-designed studies, particularly with the inclusion of premenopausal women and non-Caucasian populations.

Breast Collagen Organization: Variance by Patient Age and Breast Quadrant

Breast density is an important marker for increased breast cancer risk, but the ideal marker would be more specific. Breast compactness, which reflects the focal density of collagen fibers, parallels breast cancer occurrence being highest in the upper outer quadrants of the breast. In addition, it peaks during the same time frame as breast cancer in women. Improved biomarkers for breast cancer risk could pave the way for patient-specific preventive strategies.

Constructing the Optimal Classification Model for Benign and Malignant Breast Tumors Based on Multifeature Analysis from Multimodal Images

The purpose of this study was to fuse conventional radiomic and deep features from digital breast tomosynthesis craniocaudal projection (DBT-CC) and ultrasound (US) images to establish a multimodal benign-malignant classification model and evaluate its clinical value. Data were obtained from a total of 487 patients at three centers, each of whom underwent DBT-CC and US examinations. A total of 322 patients from dataset 1 were used to construct the model, while 165 patients from datasets 2 and 3 formed the prospective testing cohort. Two radiologists with 10-20 years of work experience and three sonographers with 12-20 years of work experience semiautomatically segmented the lesions using ITK-SNAP software while considering the surrounding tissue. For the experiments, we extracted conventional radiomic and deep features from tumors from DBT-CCs and US images using PyRadiomics and Inception-v3. Additionally, we extracted conventional radiomic features from four peritumoral layers around the tumors via DBT-CC and US images. Features were fused separately from the intratumoral and peritumoral regions. For the models, we tested the SVM, KNN, decision tree, RF, XGBoost, and LightGBM classifiers. Early fusion and late fusion (ensemble and stacking) strategies were employed for feature fusion. Using the SVM classifier, stacking fusion of deep features and three peritumoral radiomic features from tumors in DBT-CC and US images achieved the optimal performance, with an accuracy and AUC of 0.953 and 0.959 [CI: 0.886-0.996], a sensitivity and specificity of 0.952 [CI: 0.888-0.992] and 0.955 [0.868-0.985], and a precision of 0.976. The experimental results indicate that the fusion model of deep features and peritumoral radiomic features from tumors in DBT-CC and US images shows promise in differentiating benign and malignant breast tumors.

3D Cell Migration Chip (3DCM-Chip): A New Tool toward the Modeling of 3D Cellular Complex Systems

3D hydrogel-based cell cultures provide models for studying cell behavior and can efficiently replicate the physiologic environment. Hydrogels can be tailored to mimic mechanical and biochemical properties of specific tissues and allow to produce gel-in-gel models. In this system, microspheres encapsulating cells are embedded in an outer hydrogel matrix, where cells are able to migrate. To enhance the efficiency of such studies, a lab-on-a-chip named 3D cell migration-chip (3DCM-chip) is designed, which offers substantial advantages over traditional methods. 3DCM-chip facilitates the analysis of biochemical and physical stimuli effects on cell migration/invasion in different cell types, including stem, normal, and tumor cells. 3DCM-chip provides a smart platform for developing more complex cell co-cultures systems. Herein the impact of human fibroblasts on MDA-MB 231 breast cancer cells' invasiveness is investigated. Moreover, how the presence of different cellular lines, including mesenchymal stem cells, normal human dermal fibroblasts, and human umbilical vein endothelial cells, affects the invasive behavior of cancer cells is investigated using 3DCM-chip. Therefore, predictive tumoroid models with a more complex network of interactions between cells and microenvironment are here produced. 3DCM-chip moves closer to the creation of in vitro systems that can potentially replicate key aspects of the physiological tumor microenvironment.

A systematic review and meta-analysis of correlation of automated breast density measurement

INTRODUCTION

Breast cancer is the most common cancer in women and a leading cause of mortality. This systematic review and meta-analysis aims to evaluate the correlation between breast density measurements obtained from various software and visual assessments by radiologists using full-field digital mammography (FFDM).

METHODS

Following the PRISMA 2020 guidelines, five databases (Pubmed, Google Scholar, Science Direct, Cochrane Library, and MEDLINE) were searched for studies correlating volumetric breast density with breast cancer risk. The Newcastle-Ottawa Scale and the Joanna Briggs Institute Checklist were used to assess the quality of the included studies. Meta-analysis of correlation was applied to aggregate correlation coefficients using a random-effects model using MedCalc Statistical Software version 19.2.6.

RESULTS

The review included 22 studies with a total of 58,491 women. The pooled correlation coefficient for volumetric breast density amongst Volpara™ and Quantra™ was found to be 0.755 (95% CI 0.496-0.890, p < 0.001), indicating a high positive correlation, albeit with a significant heterogeneity (I2 = 99.89%, p < 0.0001). Subgroup analyses based on study origin, quality, and methodology were performed but did not reveal the heterogeneity cause. Egger's and Begg's tests showed no significant publication bias.

CONCLUSION

Volumetric breast density is strongly correlated with breast cancer risk, underscoring the importance of accurate breast density assessment in screening programs. Automated volumetric measurement tools like Volpara™ and Quantra™ provide reliable assessments, potentially improving breast cancer risk prediction and management.

IMPLICATIONS FOR PRACTICE

Implementing fully automated breast density assessment tools could enhance consistency in clinical practice, minimizing observer variability and improving screening accuracy. These tools should be further validated against standardized criteria to ensure reliability in diverse clinical settings.

Comparison of diagnostic efficacy of 2D and 3D ultrasound in women under the age of mammography screening

Breast cancer is the most common cancer among women worldwide. Younger women are more likely than older women to have aggressive molecular subtypes and late-stage disease. Mammography has less sensitivity in detecting breast cancer in women with a dense breast, and 2D ultrasound (2D US) has limitations, such as the specialists high level of skill and experience and the time it takes to perform the examination. Nowadays, there is a new technique – automated volumetric ultrasound scanning of the breast (3D US), which allows you to obtain high-resolution images.

Aim. To perform a comparative analysis of the diagnostic efficacy of 2D US and 3D US among women under 40 years of age with high breast tissue density.

Methods. A retro-prospective clinical single-center study. From February 2019 to May 2023, 1511 patients under the age of 40 were examined. The patients were divided into two groups. Patients in group A underwent 2D ultrasound, the results of the study were evaluated according to the BI-RADS classification. In addition to 2D ultrasound, the patients who were placed in group B underwent 3D US also with the BI-RADS category. Based on the results of the study, the positive and negative predictive value, sensitivity, specificity and accuracy, as well as the compilation of a predictive model of the method were determined.

Results. The 2D US in group A showed sensitivity of 0.8, specificity 1, balanced accuracy of 0.9, and area under the predictive model curve of 0.947, US in group B 0.89, 0.98, 0.94, and 0.903, respectively, and US of the entire sample of 0.87, 0.99, 0.93, and 0.916, respectively. The 3D US in group B showed a sensitivity of 0.95, specificity of 0.99 and a balanced accuracy of 0.97 and an area under the predictive model curve of 0.968.

Conclusion. The diagnostic efficiency of 3D US of the mammary glands in patients under 40 years of age is comparable in terms of specificity and is better in terms of accuracy, sensitivity and a better prognostic model of the method compared to US examination in 2D mode. The 3D US method has advantages in comparison with 2D US examination, namely reproducibility, operator independence of the method, reduced examination time, obtaining visualization of the entire organ, improved visualization in multicentric and multifocal processes, the possibility of operational planning, the possibility of “double reading” of the results.

Mammographic density in relationships with relevant contributing factors: a multicentric study from Riyadh, Saudi Arabia

Background

Mammographic breast density (MBD), a well-established factor linked to breast cancer, is the focus of this preliminary report among women across multiple centers in Riyadh. The study aims to identify risk factors associated with high breast density.

Methods

MBD was assessed at three hospitals in Riyadh, Saudi Arabia, using the American College of Radiology (ACR) categories: A (almost entirely fatty), B (scattered areas of fibroglandular density), C (heterogeneously dense), and D (extremely dense). Breast density distributions were analyzed in relation to age, body mass index (BMI), family history, parity, and hormonal therapy usage.

Results

The study included 1,530 women, revealing an inverse association between dense breast proportion and age/BMI. Notably, 43.3% [95% confidence interval (CI): 43.2% to 43.5%] of women aged 40-79 years exhibited heterogeneously or highly dense breasts, with this proportion inversely correlated with age and BMI.

Conclusions

Healthcare providers should consider breast density for appropriate screening and, if necessary, recommend supplemental methods. Policymakers and healthcare providers, when discussing breast density notification legislation, should be mindful of its high prevalence, ensuring women notified have opportunities to evaluate breast cancer risk and pursue supplemental screening options if deemed appropriate.

TGF-β signaling: critical nexus of fibrogenesis and cancer

The transforming growth factor-beta (TGF-β) signaling pathway is a vital regulator of cell proliferation, differentiation, apoptosis, and extracellular matrix production. It functions through canonical SMAD-mediated processes and noncanonical pathways involving MAPK cascades, PI3K/AKT, Rho-like GTPases, and NF-κB signaling. This intricate signaling system is finely tuned by interactions between canonical and noncanonical pathways and plays key roles in both physiologic and pathologic conditions including tissue homeostasis, fibrosis, and cancer progression. TGF-β signaling is known to have paradoxical actions. Under normal physiologic conditions, TGF-β signaling promotes cell quiescence and apoptosis, acting as a tumor suppressor. In contrast, in pathological states such as inflammation and cancer, it triggers processes that facilitate cancer progression and tissue remodeling, thus promoting tumor development and fibrosis. Here, we detail the role that TGF-β plays in cancer and fibrosis and highlight the potential for future theranostics targeting this pathway.

Spatial N-glycomics of the normal breast microenvironment reveals fucosylated and high-mannose N-glycan signatures related to BI-RADS density and ancestry

Higher breast cancer mortality rates continue to disproportionally affect black women (BW) compared to white women (WW). This disparity is largely due to differences in tumor aggressiveness that can be related to distinct ancestry-associated breast tumor microenvironments (TMEs). Yet, characterization of the normal microenvironment (NME) in breast tissue and how they associate with breast cancer risk factors remains unknown. N-glycans, a glucose metabolism-linked post-translational modification, has not been characterized in normal breast tissue. We hypothesized that normal female breast tissue with distinct Breast Imaging and Reporting Data Systems (BI-RADS) categories have unique microenvironments based on N-glycan signatures that varies with genetic ancestries. Profiles of N-glycans were characterized in normal breast tissue from BW (n = 20) and WW (n = 20) at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). A total of 176 N-glycans (32 core-fucosylated and 144 noncore-fucosylated) were identified in the NME. We found that certain core-fucosylated, outer-arm fucosylated and high-mannose N-glycan structures had specific intensity patterns and histological distributions in the breast NME dependent on BI-RADS densities and ancestry. Normal breast tissue from BW, and not WW, with heterogeneously dense breast densities followed high-mannose patterns as seen in invasive ductal and lobular carcinomas. Lastly, lifestyles factors (e.g. age, menopausal status, Gail score, BMI, BI-RADS) differentially associated with fucosylated and high-mannose N-glycans based on ancestry. This study aims to decipher the molecular signatures in the breast NME from distinct ancestries towards improving the overall disparities in breast cancer burden.

Tamoxifen Dose De-Escalation: An Effective Strategy for Reducing Adverse Effects?

Tamoxifen, a cornerstone in the adjuvant treatment of estrogen receptor-positive breast cancer, significantly reduces breast cancer recurrence and breast cancer mortality; however, its standard adjuvant dose of 20 mg daily presents challenges due to a broad spectrum of adverse effects, contributing to high discontinuation rates. Dose reductions of tamoxifen might be an option to reduce treatment-related toxicity, but large randomized controlled trials investigating the tolerability and, more importantly, efficacy of low-dose tamoxifen in the adjuvant setting are lacking. We conducted an extensive literature search to explore evidence on the tolerability and clinical efficacy of reduced doses of tamoxifen. In this review, we discuss two important topics regarding low-dose tamoxifen: (1) the incidence of adverse effects and quality of life among women using low-dose tamoxifen; and (2) the clinical efficacy of low-dose tamoxifen examined in the preventive setting and evaluated through the measurement of several efficacy derivatives. Moreover, practical tools for tamoxifen dose reductions in the adjuvant setting are provided and further research to establish optimal dosing strategies for individual patients are discussed.

Risk of Breast Cancer After Diabetes in Pregnancy: A Population-based Cohort Study

OBJECTIVES

Diabetes is associated with an increased risk of several cancers, including postmenopausal breast cancer. The evidence for higher breast cancer risk after diabetes in pregnancy is conflicting. We compared the incidence of breast and other cancers between pregnant women with and without diabetes.

METHODS

This work was a propensity-matched, retrospective cohort study using population-based health-care databases from Ontario, Canada. Those deliveries with gestational diabetes mellitus (GDM) and pregestational diabetes mellitus (pregestational DM) were identified and matched to deliveries without diabetes mellitus (non-DM). Deliveries from each diabetes cohort were matched 1:2 on age, parity, year of delivery, and propensity score to non-DM deliveries. Matched subjects were followed from delivery for incidence of breast cancer as a primary outcome, and other site-specific cancers as secondary outcomes. We performed Cox proportional hazards regression to compare rates of breast cancer between matched groups.

RESULTS

Over a median of 8 (interquartile range 4 to 13) years of follow-up, compared with non-DM deliveries, the incidence of breast cancer was significantly lower for GDM but similar for pregestational DM deliveries (hazard ratio [HR] 0.90, 95% confidence interval [CI] 0.82 to 0.98; and HR 0.92, 95% CI 0.80 to 1.07, respectively). GDM was associated with a significantly higher incidence of pancreatic and hepatocellular cancer, and pregestational DM was associated with a higher incidence of thyroid, hepatocellular, and endometrial cancers.

CONCLUSIONS

Diabetes in pregnancy does not have a higher short-term risk of subsequent breast cancer, but there may be a higher incidence of other cancers.

Diagnostic performance of contrast-enhanced mammography for suspicious findings in dense breasts: A systematic review and meta-analysis

PURPOSE

Contrast-enhanced spectral imaging (CEM) is a new mammography technique, but its diagnostic value in dense breasts is still inconclusive. We did a systematic review and meta-analysis of studies evaluating the diagnostic performance of CEM for suspicious findings in dense breasts.

MATERIALS AND METHODS

The PubMed, Embase, and Cochrane Library databases were searched systematically until August 6, 2023. Prospective and retrospective studies were included to evaluate the diagnostic performance of CEM for suspicious findings in dense breasts. The QUADAS-2 tool was used to evaluate the quality and risk of bias of the included studies. STATA V.16.0 and Review Manager V.5.3 were used to meta-analyze the included studies.

RESULTS

A total of 10 studies (827 patients, 958 lesions) were included. These 10 studies reported the diagnostic performance of CEM for the workup of suspicious lesions in patients with dense breasts. The summary sensitivity and summary specificity were 0.95 (95% CI, 0.92-0.97) and 0.81 (95% CI, 0.70-0.89), respectively. Enhanced lesions, circumscribed margins, and malignancy were statistically correlated. The relative malignancy OR value of the enhanced lesions was 28.11 (95% CI, 6.84-115.48). The relative malignancy OR value of circumscribed margins was 0.17 (95% CI, 0.07-0.45).

CONCLUSION

CEM has high diagnostic performance in the workup of suspicious findings in dense breasts, and when lesions are enhanced and have irregular margins, they are often malignant.

Surgical and Radiology Trainees' Proficiency in Reading Mammograms: the Importance of Education for Cancer Localisation

Medical imaging with mammography plays a very important role in screening and diagnosis of breast cancer, Australia's most common female cancer. The visualisation of cancers on mammograms often forms a diagnosis and guidance for radiologists and breast surgeons, and education platforms that provide real cases in a simulated testing environment have been shown to improve observer performance for radiologists. This study reports on the performance of surgical and radiology trainees in locating breast cancers. An enriched test set of 20 mammography cases (6 cancer and 14 cancer free) was created, and 18 surgical trainees and 32 radiology trainees reviewed the cases via the Breast Screen Reader Assessment Strategy (BREAST) platform and marked any lesions identifiable. Further analysis of performance with high- and low-density cases was undertaken, and standard metrics including sensitivity and specificity. Radiology trainees performed significantly better than surgical trainees in terms of specificity (0.72 vs. 0.35; P < 0.01). No significant differences were observed between the surgical and radiology trainees in sensitivity or lesion sensitivity. Mixed results were obtained with participants regarding breast density, with higher density cases generally having lower performance. The higher specificity of the radiology trainees compared to the surgical trainees likely represents less exposure to negative mammography cases. The use of high-fidelity simulated self-test environments like BREAST is able to benchmark, understand and build strategies for improving cancer education in a safe environment, including identifying challenging scenarios like breast density for enhanced training.

Experimental and Computational Analysis of High-Intensity Focused Ultrasound Thermal Ablation in Breast Cancer Cells: Monolayers vs. Spheroids

High-intensity focused ultrasound (HIFU) is a non-invasive therapeutic modality that uses precise acoustic energy to ablate cancerous tissues through coagulative necrosis. In this context, we investigate the efficacy of HIFU ablation in two distinct cellular configurations, namely 2D monolayers and 3D spheroids of epithelial breast cancer cell lines (MDA-MB 231 and MCF7). The primary objective is to compare the response of these two in vitro models to HIFU while measuring their ablation percentages and temperature elevation levels. HIFU was systematically applied to the cell cultures, varying ultrasound intensity and duty cycle during different sonication sessions. The results indicate that the degree of ablation is highly influenced by the duty cycle, with higher duty cycles resulting in greater ablation percentages, while sonication duration has a minimal impact. Numerical simulations validate experimental observations, highlighting a significant disparity in the response of 2D monolayers and 3D spheroids to HIFU treatment. Specifically, tumor spheroids require lower temperature elevations for effective ablation, and their ablation percentage significantly increases with elevated duty cycles. This study contributes to a comprehensive understanding of acoustic energy conversion within the biological system during HIFU treatment for 2D versus 3D ablation targets, holding potential implications for refining and personalizing breast cancer therapeutic strategies.

Mechanosensitive TRPV4 channel guides maturation and organization of the bilayered mammary epithelium

Biophysical cues from the cell microenvironment are detected by mechanosensitive components at the cell surface. Such machineries convert physical information into biochemical signaling cascades within cells, subsequently leading to various cellular responses in a stimulus-dependent manner. At the surface of extracellular environment and cell cytoplasm exist several ion channel families that are activated by mechanical signals to direct intracellular events. One of such channel is formed by transient receptor potential cation channel subfamily V member, TRPV4 that is known to act as a mechanosensor in wide variaty of tissues and control ion-influx in a spatio-temporal way. Here we report that TRPV4 is prominently expressed in the stem/progenitor cell populations of the mammary epithelium and seems important for the lineage-specific differentiation, consequently affecting mechanical features of the mature mammary epithelium. This was evident by the lack of several markers for mature myoepithelial and luminal epithelial cells in TRPV4-depleted cell lines. Interestingly, TRPV4 expression is controlled in a tension-dependent manner and it also impacts differentation process dependently on the stiffness of the microenvironment. Furthermore, such cells in a 3D compartment were disabled to maintain normal mammosphere structures and displayed abnormal lumen formation, size of the structures and disrupted cellular junctions. Mechanosensitive TRPV4 channel therefore act as critical player in the homeostasis of normal mammary epithelium through sensing the physical environment and guiding accordingly differentiation and structural organization of the bilayered mammary epithelium.

Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study

Mammographic screening has contributed to a significant reduction in breast cancer mortality. Several studies have highlighted the correlation between breast density, as detected through mammography, and a higher likelihood of developing breast cancer. A polygenic risk score (PRS) is a numerical score that is calculated based on an individual's genetic information. This study aims to explore the potential roles of PRS as candidate markers for breast cancer development and investigate the genetic profiles associated with clinical characteristics in Asian females with dense breasts. This is a retrospective cohort study integrated breast cancer screening, population genotyping, and cancer registry database. The PRSs of the study cohort were estimated using genotyping data of 77 single nucleotide polymorphisms based on the PGS000001 Catalog. A subgroup analysis was conducted for females without breast symptoms. Breast cancer patients constituted a higher proportion of individuals in PRS Q4 (37.8% vs. 24.8% in controls). Among dense breast patients with no symptoms, the high PRS group (Q4) consistently showed a significantly elevated breast cancer risk compared to the low PRS group (Q1-Q3) in both univariate (OR = 2.25, 95% CI 1.43-3.50, P < 0.001) and multivariate analyses (OR: 2.23; 95% CI 1.41-3.48, P < 0.001). The study was extended to predict breast cancer risk using common low-penetrance risk variants in a PRS model, which could be integrated into personalized screening strategies for Taiwanese females with dense breasts without prominent symptoms.

Breast Cancer Incidence Among Asian American Women in New York City: Disparities in Screening and Presentation

BACKGROUND

Asian American (AsAm) women have some of the lowest rates of up-to-date breast cancer screening, and lack of disaggregated racial/ethnic data can mask disparities. We evaluated presentation patterns among AsAms at two hospitals with distinct communities: New York Presbyterian-Queens (NYPQ), in Flushing, Queens and Weill Cornell Medical Center (WCM), on the Upper East Side (UES) neighborhood of Manhattan.

PATIENTS AND METHODS

Patients with newly diagnosed breast cancer between January 2019 and December 2022 were identified using a prospective database and clinical data collected. Patients were categorized as self-reported Asian versus Non-Asian. The Asian group was disaggregated as Chinese-Asian versus Other-Asian. Physician workforce data were obtained from public records.

RESULTS

A total of 3546 patients (1162 NYPQ, 2384 WCM) were included. More NYPQ patients identified as Asian compared with WCM (49 vs. 14%, p < 0.001). Asian patients were mostly East Asian Chinese (NYPQ 61%, WCM 53%). More Chinese patients at NYPQ reported Chinese as their preferred language (81 vs. 33%, p < 0.001). Greatest differences of screen-detected disease frequency were seen between NYPQ and WCM Chinese patients (75 vs. 59%, p < 0.001). Eighty percent of NYPQ Chinese patients presented with stage 0/I disease versus 69% at WCM (p = 0.007), a difference not observed between Other-Asian patients (75% NYPQ, 68% WCM, p = 0.095). 3% of UES physicians versus 16% in Flushing reported speaking Chinese.

CONCLUSIONS

Chinese patients residing in a neighborhood with more Chinese-speaking physicians more frequently presented with screen-detected, early-stage breast cancer. Stage distribution differences were not apparent among the aggregated pool of Other-Asian patients, suggesting cancer disparities may be masked when ethnic groups are studied in aggregate.

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

BACKGROUND

Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women.

METHODS

A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC.

RESULTS

Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02).

CONCLUSION

Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

BRCA1 and BRCA2 germline mutations in Chinese Hakka breast cancer patients

OBJECTIVE

To investigate the prevalence of BRCA1/2 gene variants and evaluate the clinical and pathological characteristics associated with these variants in Chinese Hakka breast cancer patients.

METHODS

A total of 409 breast cancer patients were analyzed based on next-generation sequencing results, with 337 categorized as non-carriers and 72 as carriers of BRCA1/2 variants. Data on the patients' BRCA1/2 gene mutation status, clinical and pathological characteristics, as well as menstrual and reproductive information, were collected, analyzed, compared, and tabulated. Logistic regression analysis was performed to explore the relationship between clinical characteristics and pathogenic variants.

RESULTS

Among the patients, 72 were identified as carriers of pathogenic or likely pathogenic variants in BRCA1/2, while 337 had likely benign or benign mutations. The BRCA1 c.2635G > T (p. Glu879*) variant was detected at a high frequency, accounting for 12.5% (4/32) of the BRCA1 mutations, while the c.5164_5165del (p.Ser1722Tyrfs*4) variant was common among the BRCA2 mutations, accounting for 17.5% (7/40). It was observed that a higher proportion of BRCA1 carriers had the triple-negative breast cancer subtype, whereas more BRCA2 carriers exhibited estrogen receptor (ER) + and progesterone receptor (PR) + subtypes. Multivariate logistic regression analysis revealed that a family history of cancer (OR = 2.36, 95% CI = 1.00-5.54), bilateral cancer (OR = 4.78, 95% CI 1.61-14.20), human epidermal growth factor receptor 2 (HER2)- (OR = 8.23, 95% CI 3.25-20.84), and Ki67 ≥ 15% (OR = 3.88, 95% CI 1.41-10.65) were associated with BRCA1/2 mutations, with the age at diagnosis, age at menarche, and premenopausal status serving as covariates.

CONCLUSIONS

The most common pathogenic variant of the BRCA1 and BRCA2 in breast cancer patients was c.2635G > T and c.5164_5165del, respectively. Additionally, a family history of cancer, bilateral cancer, HER2-, and Ki67 ≥ 15% were identified as independent predictors of BRCA1/2 pathogenic variants.

Epidemiology of Breast, Corpus Uteri, and Ovarian Cancers in Lebanon With Emphasis on Breast Cancer Incidence Trends and Risk Factors Compared to Regional and Global Rates

OBJECTIVES

This study explores the incidence and trends of breast (Bca), corpus uteri (CUca), and ovarian (Oca) cancer in Lebanon, a Middle Eastern country. It compares the Bca rates to regional and global ones and discusses Bca risk factors in Lebanon.

INTRODUCTION

Globally, Bca is the premier cause of cancer morbidity and mortality in women.

METHODS

Data on female Bca, CUca, and Oca published by the Lebanese national cancer registry were obtained (ie, for the years of 2005 to 2016). The age-standardized incidence rates (ASIRw) and age-specific rates per 100,000 female population were computed.

RESULTS

From 2005 to 2016, Bca, Oca, and CUca ranked first, sixth, and seventh, respectively, for cancer incidence among women in Lebanon. Bca alone accounted for 39.4% of all new female cancer cases. The ASIRw increased significantly for Bca and CUca (APC: 3.60 and 3.73, P < .05) but not for Oca (APC: 1.27, P > .05). The Bca ASIRw (per 100,000) increased significantly from 71.0 in 2005 to 115.6 in 2013 (P < .05), then decreased steadily but non-significantly to reach 96.8 in 2016 (P > .05). Lebanon's Bca ASIRw is comparable to developed countries. This may reflect altered sociological and reproductive patterns as the country transitions from regional to global trends. The five-year age-specific rates analysis revealed that Bca rates rose steeply from 35-39 to 50-54, dropped slightly between 55 and 64, then rose till 75+. The five-year age-specific rates between 35 and 54 among Lebanese women were amongst the highest worldwide from 2008 to 2012, even higher than the rates in Belgium, which had the highest ASIRw of Bca worldwide in 2020.

CONCLUSION

Lebanon's Bca ASIRw is among the highest globally. It's important to investigate the contributing factors and develop a national Bca control strategy. This study supports the national recommendation in initiating Bca screening at age 40 for women.

Practical Challenges of DBT-Guided VABB: Harms and Benefits, from Literature to Clinical Experience

Vacuum-assisted breast biopsy (VABB) guided by digital breast tomosynthesis (DBT) represents one of the best instruments to obtain a histological diagnosis of suspicious lesions with no ultrasound correlation or those which are visible only on DBT. After a review of the literature, we retrospectively analyzed the DBT-guided VABBs performed from 2019 to 2022 at our department. Descriptive statistics, Pearson's correlation and χ2 test were used to compare distributions of age, breast density (BD) and early performance measures including histopathology. We used kappa statistics to evaluate the agreement between histological assessment and diagnosis. Finally, we compared our experience to the literature to provide indications for clinical practice. We included 85 women aged 41-84 years old. We identified 37 breast cancers (BC), 26 stage 0 and 11 stage IA. 67.5% of BC was diagnosed in women with high BD. The agreement between VABB and surgery was 0.92 (k value, 95% CI: 0.76-1.08). We found a statistically significant inverse correlation between age and BD. The post-procedural clip was correctly positioned in 88.2%. The post-procedural hematoma rate was 14.1%. No infection or hemorrhage were recorded. When executed correctly, DBT-guided VABB represents a safe and minimally invasive technique with high histopathological concordance, for detecting nonpalpable lesions without ultrasound correlation.

Automated 3D Ultrasound as an Adjunct to Screening Mammography Programs in Dense Breast: Literature Review and Metanalysis

Purpose: The purpose of this meta-analysis is to investigate the effectiveness of supplementing screening mammography with three-dimensional automated breast ultrasonography (3D ABUS) in improving breast cancer detection rates in asymptomatic women with dense breasts. Materials and Methods: We conducted a thorough review of scientific publications comparing 3D ABUS and mammography. Articles for inclusion were sourced from peer-reviewed journal databases, namely MEDLINE (PubMed) and Scopus, based on an initial screening of their titles and abstracts. To ensure a sufficient sample size for meaningful analysis, only studies evaluating a minimum of 20 patients were retained. Eligibility for evaluation was further limited to articles written in English. Additionally, selected studies were required to have participants aged 18 or above at the time of the study. We analyzed 25 studies published between 2000 and 2021, which included a total of 31,549 women with dense breasts. Among these women, 229 underwent mammography alone, while 347 underwent mammography in combination with 3D ABUS. The average age of the women was 50.86 years (±10 years standard deviation), with a range of 40-56 years. In our efforts to address and reduce bias, we applied a range of statistical analyses. These included assessing study variation through heterogeneity assessment, accounting for potential study variability using a random-effects model, exploring sources of bias via meta-regression analysis, and checking for publication bias through funnel plots and the Egger test. These methods ensured the reliability of our study findings. Results: According to the 25 studies included in this metanalysis, out of the total number of women, 27,495 were diagnosed with breast cancer. Of these, 211 were diagnosed through mammography alone, while an additional 329 women were diagnosed through the combination of full-field digital mammography (FFDSM) and 3D ABUS. This represents an increase of 51.5%. The rate of cancers detected per 1000 women screened was 23.25‱ (95% confidence interval [CI]: 21.20, 25.60; p < 0.001) with mammography alone. In contrast, the addition of 3D ABUS to mammography increased the number of tumors detected to 20.95‱ (95% confidence interval [CI]: 18.50, 23; p < 0.001) per 1000 women screened. Discussion: Even though variability in study results, lack of long-term outcomes, and selection bias may be present, this systematic review and meta-analysis confirms that supplementing mammography with 3D ABUS increases the accuracy of breast cancer detection in women with ACR3 to ACR4 breasts. Our findings suggest that the combination of mammography and 3D ABUS should be considered for screening women with dense breasts. Conclusions: Our research confirms that adding 3D automated breast ultrasound to mammography-only screening in patients with dense breasts (ACR3 and ACR4) significantly (p < 0.05) increases the cancer detection rate.

The Level of Awareness Among Healthcare Practitioners Regarding the Relationship Between Breast Density and Breast Cancer

Background Breast cancer is the most prevalent cancer in women, accounting for around 23% of all cancer-related deaths across 140 nations. The awareness about breast density (BD) has a significant impact on early diagnosis of breast cancer. Aim and objective This study aims to assess the awareness of healthcare providers about BD in King Abdullah Medical City. Methods This is an analytical cross-sectional questionnaire-based study among the healthcare practitioners of KAMC in Makkah, Saudi Arabia. Questions measured knowledge about BD and a pass mark indicated participant awareness. The collected data were analyzed using SPSS, and a chi-square test used for bivariate analysis. Results Out of 124 participants, 41% were well aware. Physicians (37% of the sample) were significantly more aware than allied healthcare practitioners and nurses (awareness: 59.6%, 33.3%, 30.4% respectively, (p = 0.03)). Regarding specialty, radiologists and surgeons had the top level of awareness (62% and 64%, respectively) as compared to oncologists (47.1%) and other specialties (29.7%), (p= 0.016). Those above 40 years of age were more aware than those below 40 years (awareness: 62.1% and 34%, respectively, (p=0.007)). Non-significant factors included: gender, years of experience, screened versus non-screened, and receiving information before about BD (p > 0.05). Conclusion The results of this population-based study indicate the existence of moderate deficits in the general knowledge about BD and its relation to breast cancer. This might lead to a late diagnosis. The results showed no dramatic differences in the awareness among healthcare providers.

Integrating clinical research in an operative screening and diagnostic breast imaging department: First experience, results and perspectives using microwave imaging

Rationale and objectives

Clinical research is crucial for evaluating new medical procedures and devices. It is important for healthcare units and hospitals to minimize the disruptions caused by conducting clinical studies; however, complex clinical pathways require dedicated recruitment and study designs.This work presents the effective introduction of novel microwave breast imaging (MBI), via MammoWave apparatus, into the clinical routine of an operative screening and diagnostic breast imaging department for conducting a multicentric clinical study.

Materials and methods

Microwave breast imaging, using MammoWave apparatus, was performed on volunteers coming from different clinical pathways. Clinical data, comprising demographics and conventional radiologic reports (used as reference standard), was collected; a satisfaction questionnaire was filled by every volunteer. Microwave images were analyzed by an automatic clinical decision support system, which quantified their corresponding features to discriminate between breasts with no relevant radiological findings (NF) and breasts with described findings (WF).

Results

Conventional breast imaging (DBT, US, MRI) and MBI were performed and adapted to assure best clinical practices and optimum pathways. 180 volunteers, both symptomatic and asymptomatic, were enrolled in the study. After microwave images' quality assessment, 48 NF (15 dense) and 169 WF (88 dense) breasts were used for the prospective study; 48 (18 dense) breasts suffered from a histology-confirmed carcinoma. An overall sensitivity of 85.8 % in breasts lesions' detection was achieved by the microwave imaging apparatus.

Conclusion

An optimum recruitment strategy was implemented to assess MBI. Future trials may show the clinical usefulness of microwave imaging, which may play an important role in breast screening.

Recent progress on the effect of extracellular matrix on occurrence and progression of breast cancer

Breast cancer (BC) metastasis is an enormous challenge targeting BC therapy. The extracellular matrix (ECM), the principal component of the BC metastasis niche, is the pivotal driver of breast tumor development, whose biochemical and biophysical characteristics have attracted widespread attention. Here, we review the biological effects of ECM constituents and the influence of ECM stiffness on BC metastasis and drug resistance. We provide an overview of the relative signal transduction mechanisms, existing metastasis models, and targeted drug strategies centered around ECM stiffness. It will shed light on exploring more underlying targets and developing specific drugs aimed at ECM utilizing biomimetic platforms, which are promising for breast cancer treatment.

Breast Imaging Physics in Mammography (Part I)

Breast cancer is the most frequently diagnosed neoplasm in women in Italy. There are several risk factors, but thanks to screening and increased awareness, most breast cancers are diagnosed at an early stage when surgical treatment can most often be conservative and the adopted therapy is more effective. Regular screening is essential but advanced technology is needed to achieve quality diagnoses. Mammography is the gold standard for early detection of breast cancer. It is a specialized technique for detecting breast cancer and, thus, distinguishing normal tissue from cancerous breast tissue. Mammography techniques are based on physical principles: through the proper use of X-rays, the structures of different tissues can be observed. This first part of the paper attempts to explain the physical principles used in mammography. In particular, we will see how a mammogram is composed and what physical principles are used to obtain diagnostic images.

Propagation-based phase-contrast imaging of the breast: image quality and the effect of X-ray energy and radiation dose

OBJECTIVES

Propagation-based phase-contrast computed tomography (PB-CT) is a new imaging technique that exploits refractive and absorption properties of X-rays to enhance soft tissue contrast and improve image quality. This study compares image quality of PB-CT and absorption-based CT (AB-CT) for breast imaging while exploring X-ray energy and radiation dose.

METHODS

Thirty-nine mastectomy samples were scanned at energy levels of 28-34keV using a flat panel detector at radiation dose levels of 4mGy and 2mGy. Image quality was assessed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), spatial resolution (res) and visibility (vis). Statistical analysis was performed to compare PB-CT images against their corresponding AB-CT images scanned at 32keV and 4mGy.

RESULTS

The PB-CT images at 4mGy, across nearly all energy levels, demonstrated superior image quality than AB-CT images at the same dose. At some energy levels, the 2mGy PB-CT images also showed better image quality in terms of CNR/Res and vis compared to the 4mGy AB-CT images. At both investigated doses, SNR and SNR/res were found to have a statistically significant difference across all energy levels. The difference in vis was statistically significant at some energy levels.

CONCLUSION

This study demonstrates superior image quality of PB-CT over AB-CT, with X-ray energy playing a crucial role in determining image quality parameters.

ADVANCES IN KNOWLEDGE

Our findings reveal that standard dose PB-CT outperforms standard dose AB-CT across all image quality metrics. Additionally, we demonstrate that low dose PB-CT can produce superior images compared to standard dose AB-CT in terms of CNR/Res and vis.

A robust and efficient AI assistant for breast tumor segmentation from DCE-MRI via a spatial-temporal framework

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows screening, follow up, and diagnosis for breast tumor with high sensitivity. Accurate tumor segmentation from DCE-MRI can provide crucial information of tumor location and shape, which significantly influences the downstream clinical decisions. In this paper, we aim to develop an artificial intelligence (AI) assistant to automatically segment breast tumors by capturing dynamic changes in multi-phase DCE-MRI with a spatial-temporal framework. The main advantages of our AI assistant include (1) robustness, i.e., our model can handle MR data with different phase numbers and imaging intervals, as demonstrated on a large-scale dataset from seven medical centers, and (2) efficiency, i.e., our AI assistant significantly reduces the time required for manual annotation by a factor of 20, while maintaining accuracy comparable to that of physicians. More importantly, as the fundamental step to build an AI-assisted breast cancer diagnosis system, our AI assistant will promote the application of AI in more clinical diagnostic practices regarding breast cancer.

[Breast density assessment and organised breast cancer screening]

INTRODUCTION

The objective of this study was to evaluate the intra- and inter-rater agreement of radiologists regarding the evaluation of breast density.

METHODOLOGY

Breast density assessments of 120 cases were performed by four radiologists in the city of Ouagadougou according to the fifth edition of the American College of Radiology BI-RADS atlas. Cohen's weighted kappa coefficients and Fleiss kappa coefficients were used to estimate agreement between observers and with a panel of three experts radiologists. A new evaluation of the 120 cases was performed by all raters one month after the initial evaluation.

RESULTS

Inter-rater kappa coefficients ranged from 0.55 to 0.74. The Fleiss kappa coefficient was 0.58, 0.43, 0.41, and 0.43 for categories A, B, C, and D respectively. In terms of classification into "sparse breasts" and "dense breasts", the kappa coefficients ranged from 0.47 to 0.67. Taking the results of the expert panel as a reference, the proportion of false positives in the diagnosis "dense breasts" ranged from 18.6% to 26.8%. Intraobserver agreement was good.

CONCLUSION

Our study showed moderate to good intra- and inter-raters agreements. Upgrading and harmonisation of practices will be used to empower radiologists to participate in organised breast cancer screening in Burkina Faso.

Breast cancer risk coordinators: Artificial intelligence-based density measurement and Mullerian-inhibiting substance

BACKGROUND

Due to its increasing prevalence, breast cancer has become a serious public health problem. In addition to the models used to identify individuals at risk, the search for fast and accurate tools has continued for years.

AIMS

In our study, we aimed to examine the correlation of mammographic density measurement and serum Mullerian-inhibiting substance (MIS) levels with an effective model such as Gail.

METHODS

Of the women whose serum MIS levels were measured in the last 1 year, 214 participants who applied for routine breast examination were included in the study. The age range was between 40 and 60. Exclusion criteria were determined as pathological mammographic findings, active breast symptom, and thoracic radiotherapy history. Mammographic density measurement (PD) was performed with the artificial intelligence-based Deep-LIBRA software. The relationship of these two parameters with the lifetime risk of developing breast cancer was examined.

RESULTS

The correlation between PD and GRP was remarkable (p < 0.01 cc:0.35). A positive correlation was observed between serum MIS levels and increased breast cancer, but it was not possible to prove this statistically (p = 0.056). It was thought that this situation was caused by perimenopausal patients. Because when the menopause group was excluded, the correlation between MIS levels and GRP decreased (p = 0.12 cc:0.17).

CONCLUSIONS

PD measurement can be considered as a promising method for the determination of individuals at risk for breast cancer in a large group of patients, but we think that serum MIS levels are not suitable for risk assessment in perimenopausal patients.

The association between mammographic density and breast cancer molecular subtypes: a systematic review and meta-analysis

AIM

To conduct a systematic review and meta-analysis to evaluate the whether high mammographic density (MD) is differentially associated with all subtypes of breast cancer.

MATERIALS AND METHODS

The PubMed, Cochrane Library, and Embase databases were searched systematically in October 2022 to include all studies that investigated the association between MD and breast cancer subtype. Aggregate data of 17,193 breast cancer cases from 23 studies were selected, including five cohort/case-control and 18 case-only studies. The relative risk (RR) of MD were combined using random/fixed effects models for case-control studies, and for case-only studies, relative risk ratios (RRRs) were a combination of luminal A, luminal B, and HER2-positive versus triple-negative tumours.

RESULTS

Women in the highest density category in case-control/cohort studies had a 2.24-fold (95% confidence interval [CI] 1.53, 3.28), 1.81-fold (95% CI 1.15, 2.85), 1.44-fold (95% CI 1.14, 1.81), and 1.59-fold (95% CI 0.89, 2.85) higher risk of triple-negative, HER-2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B breast cancer compared to women in the lowest density category. RRRs for breast tumours being luminal A, luminal B, and HER-2 positive versus triple-negative in case-only studies were 1.62 (95% CI 1.14, 2.31), 1.81 (95% CI 1.22, 2.71) and 2.58 (95% CI 1.63, 4.08), respectively, for BIRADS 4 versus BIRADS 1.

CONCLUSION

The evidence indicates MD is a potent risk factor for the majority of breast cancer subtypes to different degrees. Increased MD is more strongly linked to HER-2-positive cancers compared to other breast cancer subtypes. The application of MD as a subtype-specific risk marker may facilitate the creation of personalised risk prediction models and screening procedures.