Breast Tissue Biopsies Research Articles

Untargeted metabolomic profiling of small extracellular vesicles reveals potential new biomarkers for triple negative breast cancer.

Breast Cancer (BC) is one of the most diagnosed malignancies among women and the second leading cause of cancer related death in North America. Triple Negative BC (TNBC), one of the most severe subtypes of BC, is extremely aggressive and has a higher chance of occurrence in women under 50 years of age. Due to a lack of regular mammographic testing in women under 50, many individuals with TNBC are diagnosed late which can decrease their survival rate. Currently, liquid biopsy is being investigated as a potentially less-invasive alternative to traditional breast tissue biopsy, but this approach is not completely reliable. Blood contains extracellular vesicles (EVs), which carry biomolecular cargo and play a role in BC progression and metastasis. Examination of small EVs could potentially yield metabolite biomarkers for early BC diagnosis. We aim to study metabolites in small EVs to find biomarkers for BC diagnosis. In this work, an untargeted nano-LC MS/MS metabolomics approach was used to analyze metabolites from small EVs derived from metastatic MDA-MB-231 and compare it with a non-cancerous MCF10A cell line. Two metabolites, LysoPC 22:6/0:0 and N-acetyl-L-Phenylalanine, unique to sEVs of MDA-MB-231, were identified, validated, and proposed as potential BC biomarkers. Metabolites from sEVs may be used for BC diagnosis.

Comparison of state-of-the-art biopsy systems for ultrasound-guided breast biopsy using a chicken breast phantom.

To compare different biopsy systems with different-sized needles by determining the weight of the tissue cores, which is one of the important factors for precise pathological diagnoses, and to provide a rationale for choosing the appropriate breast biopsy system with the appropriate needle for breast cancer biopsy. Six different vacuum-assisted biopsy (VAB) systems and one core needle biopsy (CNB) system with different-sized needles in different modes were compared, representing 15 total combinations. Tissue cores were obtained from a chicken breast phantom, which is a common substitute for human breast tissue. Five cores were taken for each combination and weighed. The CNB combination provided significantly lighter tissue cores compared with the VAB combinations with the same-size (14-G) needle (P < 0.01). The combinations using the thickest needle obtained the heaviest among all systems (P < 0.02). The untethered battery-free VAB system yielded the lightest specimen among the VAB systems with the same-sized (12-G) needle (P < 0.04). The percent coefficient of variation (%CV) of the core weights obtained using VAB without a basket was significantly smaller compared with the core weights obtained using VAB with a basket (P < 0.01). VAB systems can yield larger tissue cores compared with CNB systems. The size of the tissue cores varies even with the same-sized needle among different VAB systems. When performing a breast tissue biopsy, it is important to consider not only CNB versus VAB but also what specific device to use with which needle size.

Promoter profiles in plasma CfDNA exhibits a potential utility of predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients

BackgroundGene expression profiles in breast tissue biopsies contain information related to chemotherapy efficacy. The promoter profiles in cell-free DNA (cfDNA) carrying gene expression information of the original tissues may be used to predict the response to neoadjuvant chemotherapy in breast cancer as a non-invasive biomarker. In this study, the feasibility of the promoter profiles in plasma cfDNA was evaluated as a novel clinical model for noninvasively predicting the efficacy of neoadjuvant chemotherapy in breast cancer.MethodFirst of all, global chromatin (5 Mb windows), sub-compartments and promoter profiles in plasma cfDNA samples from 94 patients with breast cancer before neoadjuvant chemotherapy (pCR = 31 vs. non-pCR = 63) were analyzed, and then classifiers were developed for predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Further, the promoter profile changes in sequential cfDNA samples from 30 patients (pCR = 8 vs. non-pCR = 22) during neoadjuvant chemotherapy were analyzed to explore the potential benefits of cfDNA promoter profile changes as a novel potential biomarker for predicting the treatment efficacy.ResultsThe results showed significantly distinct promoter profile in plasma cfDNA of pCR patients compared with non-pCR patients before neoadjuvant chemotherapy. The classifier based on promoter profiles in a Random Forest model produced the largest area under the curve of 0.980 (95% CI: 0.978–0.983). After neoadjuvant chemotherapy, 332 genes with significantly differential promoter profile changes in sequential cfDNA samples of pCR patients was observed, compared with non-pCR patients, and their functions were closely related to treatment response.ConclusionThese results suggest that promoter profiles in plasma cfDNA may be a powerful, non-invasive tool for predicting the efficacy of neoadjuvant chemotherapy breast cancer patients before treatment, and the on-treatment cfDNA promoter profiles have potential benefits for predicting the treatment efficacy.

Is fibroblast growth factor 11 (FGF11) a predictive marker for breast cancer?

The prognostic role of fibroblast growth factor 11 (FGF11) has only been reported in cancers such as nasopharyngeal carcinoma and prostate cancer. The role of FGF11 in breast cancer is not fully known. It was aimed to compare FGF11 expression levels in de novo metastatic hormone receptor-positive, human epidermal reseptor-2-negative breast tumor tissue and healthy breast tissue and investigate the effect of the FGF11 expression on survival in breast cancer patients. To determine the FGF11 expression rate, breast tumor tissue of breast cancer patients diagnosed by breast biopsy and healthy breast tissue of healthy individuals who underwent breast biopsy due to benign lesions were used. The study population included 38 breast cancer patients and 24 healthy controls. The number of patients with a FGF11 expression level score of 1 (15.8% vs 12.5%), score of 2 (18.4% vs 12.5%), and score of 3 (31.6% vs 0%) was significantly higher in the patient group compared to the healthy control group. The median overall survival and progression-free survival were numerically better in the group with a FGF11 expression score of 0 to 1 than the group with a FGF11 expression score of 2 and 3, but this difference was not statistically significant. FGF11 may be a predictive marker for breast cancer formation. Additionally, with new FGF11-targeted treatment agents to be developed, endocrine resistance may be reduced, and better survival results may be achieved in hormone receptor-positive, human epidermal reseptor-2-negative breast cancer.

A color-based tumor segmentation method for clinical ex vivo breast tissue assessment utilizing a multi-contrast brightfield imaging strategy.

We demonstrate an automated two-step tumor segmentation method leveraging color information from brightfield images of fresh core needle biopsies of breast tissue. Three different color spaces (HSV, CIELAB, YCbCr) were explored for the segmentation task. By leveraging white-light and green-light images, we identified two different types of color transformations that could separate adipose from benign and tumor or cancerous tissue. We leveraged these two distinct color transformation methods in a two-step process where adipose tissue segmentation was followed by benign tissue segmentation thereby isolating the malignant region of the biopsy. Our tumor segmentation algorithm and imaging probe could highlight suspicious regions on unprocessed biopsy tissue to guide selection of areas most similar to malignant tissues for tissue pathology whether it be formalin fixed or frozen sections, expedite tissue selection for molecular testing, detect positive tumor margins, or serve an alternative to tissue pathology, in countries where these services are lacking.

New resolution independent approach to noise estimation in Minimum Noise Fraction denoising of tissues measured with Infrared Imaging

The Minimum Noise Fraction (MNF) was originally developed for remote sensing data denoising. However, due to the hyperspectral character of Infrared (IR) imaging data, MNF is becoming increasingly popular in this field. IR imaging obtains data rich in biochemical information, therefore, it is extensively applied in tissue analysis and classification. It is popular to use different IR objectives of different magnification, which combined with Focal Plane Array (FPA) detector of fixed pixels size, give varying projected pixel sizes and as a result – different spatial resolutions. The MNF method proposed by Green et al. uses a noise correlation matrix that is calculated based on neighboring pixel difference, which heavily depends on the registered image magnification and thus spatial resolution, leading to different denoising efficiencies and signal loss. Here, we presented a new resolution-independent approach to noise matrix estimation (MNF2) based on the 2 sequential scans of the sample. In this way, the data acquisition step is only minimally changed, while offering a uniform denoising step. We decided to test our method on representative breast tissue biopsy, due to its spatial and biochemical heterogeneity. We compared the performance of the new method for data measured using objectives giving different spatial pixel projections: low - 11.4 μm (3.5x), standard - 2.7 μm (15x), and high - 1.1 μm (36x). Results of this study show that conventional MNF for standard and low resolutions produces an altered denoised signal, while MNF2 gives a denoised signal of very good quality. In the case of high resolution data, standard MNF gives reasonable results, likewise proposed MNF2.

CLINICAL VALUE OF MAGNETIC RESONANCE IMAGING-GUIDED CORE NEEDLE AND VACUUM-ASSISTED BREAST BIOPSIES

Breast cancer is the most common oncological disease in women. When changes in the breasts are not visible on an ultrasound or mammogram, they can be detected by a magnetic resonance imaging (MRI) scan. A biopsy of the breast tissue is performed to examine the changes and predict the most suitable further treatment method. Most often, a core needle biopsy is performed under ultrasound or mammography guidance, but if lesions are only visible on MRI images, the biopsy should be performed under MRI control. MRI-guided biopsy is a relatively new diagnostic method. The aim of our study was to assess the clinical value of MRI-guided core nee­dle and vacuum-assisted core needle breast biopsies. We conducted a systematic literature analysis. Articles were retrieved from PubMed and ClinicalKey electronic data­bases. Eligible articles were selected based on inclusion and exclusion criteria. 12 articles were included from 512 publications. We conclude that MRI -guided core needle and vacuum-assissted core needle biopsies are a safe and effective method of taking a breast tissue biopsy, allowing you to assess abnormalities that are not visible on mammography or ultrasound. MRI-guided biopsy is appropriate for all patients with suspicious lesions seen only on MRI, irrespective of breast cancer risk, as ma­lignant lesions are likely to be found in ~21% of patients. MRI-guided core needle biopsies have a low compli­cation rate. The diagnostic performance of MRI-guided core needle biopsy (sensitivity ~ 93%) is comparable to the diagnostic performance of other image-guided breast biopsy techniques.

Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.

This study explores the feasibility of using machine learning to predict accurate versus inaccurate diagnoses made by pathologists based on their spatiotemporal viewing behavior when evaluating digital breast biopsy images. The study gathered data from 140 pathologists of varying experience levels who each reviewed a set of 14 digital whole slide images of breast biopsy tissue. Pathologists' viewing behavior, including zooming and panning actions, was recorded during image evaluation. A total of 30 features were extracted from the viewing behavior data, and 4 machine learning algorithms were used to build classifiers for predicting diagnostic accuracy. The Random Forest classifier demonstrated the best overall performance, achieving a test accuracy of 0.81 and area under the receiver-operator characteristic curve of 0.86. Features related to attention distribution and focus on critical regions of interest were found to be important predictors of diagnostic accuracy. Further including case-level and pathologist-level information incrementally improved classifier performance. Results suggest that pathologists' viewing behavior during digital image evaluation can be leveraged to predict diagnostic accuracy, affording automated feedback and decision support systems based on viewing behavior to aid in training and, ultimately, clinical practice. They also carry implications for basic research examining the interplay between perception, thought, and action in diagnostic decision-making. The classifiers developed herein have potential applications in training and clinical settings to provide timely feedback and support to pathologists during diagnostic decision-making. Further research could explore the generalizability of these findings to other medical domains and varied levels of expertise.

Label-free multimodal electro-thermo-mechanical (ETM) phenotyping as a novel biomarker to differentiate between normal, benign, and cancerous breast biopsy tissues.

Technologies for quick and label-free diagnosis of malignancies from breast tissues have the potential to be a significant adjunct to routine diagnostics. The biophysical phenotypes of breast tissues, such as its electrical, thermal, and mechanical properties (ETM), have the potential to serve as novel markers to differentiate between normal, benign, and malignant tissue. We report a system-of-biochips (SoB) integrated into a semi-automated mechatronic system that can characterize breast biopsy tissues using electro-thermo-mechanical sensing. The SoB, fabricated on silicon using microfabrication techniques, can measure the electrical impedance (Z), thermal conductivity (K), mechanical stiffness (k), and viscoelastic stress relaxation (%R) of the samples. The key sensing elements of the biochips include interdigitated electrodes, resistance temperature detectors, microheaters, and a micromachined diaphragm with piezoresistive bridges. Multi-modal ETM measurements performed on formalin-fixed tumour and adjacent normal breast biopsy samples from N = 14 subjects were able to differentiate between invasive ductal carcinoma (malignant), fibroadenoma (benign), and adjacent normal (healthy) tissues with a root mean square error of 0.2419 using a Gaussian process classifier. Carcinoma tissues were observed to have the highest mean impedance (110018.8 ± 20293.8 Ω) and stiffness (0.076 ± 0.009 kNm-1) and the lowest thermal conductivity (0.189 ± 0.019 Wm-1K-1) amongst the three groups, while the fibroadenoma samples had the highest percentage relaxation in normalized load (47.8 ± 5.12%). The work presents a novel strategy to characterize the multi-modal biophysical phenotype of breast biopsy tissues to aid in cancer diagnosis from small-sized tumour samples. The methodology envisions to supplement the existing technology gap in the analysis of breast tissue samples in the pathology laboratories to aid the diagnostic workflow.

Domain and Histopathology Adaptations–Based Classification for Malignancy Grading System

Accurate proliferation rate quantification can be used to devise an appropriate treatment for breast cancer. Pathologists use breast tissue biopsy glass slides stained with hematoxylin and eosin to obtain grading information. However, this manual evaluation may lead to high costs and be ineffective because diagnosis depends on the facility and the pathologists' insights and experiences. Convolutional neural network acts as a computer-based observer to improve clinicians' capacity in grading breast cancer. Therefore, this study proposes a novel scheme for automatic breast cancer malignancy grading from invasive ductal carcinoma. The proposed classifiers implement multistage transfer learning incorporating domain and histopathologic transformations. Domain adaptation using pretrained models, such as InceptionResNetV2, InceptionV3, NASNet-Large, ResNet50, ResNet101, VGG19, and Xception, was applied to classify the ×40 magnification BreaKHis data set into eight classes. Subsequently, InceptionV3 and Xception, which contain the domain and histopathology pretrained weights, were determined to be the best for this study and used to categorize the Databiox database into grades 1, 2, or 3. To provide a comprehensive report, this study offered a patchless automated grading system for magnification-dependent and magnification-independent classifications. With an overall accuracy (means ±SD) of 90.17%±3.08% to 97.67%±1.09% and an F1 score of 0.9013 to 0.9760 for magnification-dependent classification, the classifiers in this work achieved outstanding performance. The proposed approach could be used for breast cancer grading systems in clinical settings.

Do physicians remember cases? Implications for longitudinal designs in medical research and competency assessment

Background In pathology and other specialties of diagnostic medicine, longitudinal studies and competency assessments often involve physicians interpreting the same images multiple times. In these designs, a washout period is used to reduce the chances that later interpretations are influenced by prior exposure. Objective/s The present study examines whether a washout period between 9 and 39 months is sufficient to prevent three effects of prior exposure when pathologists review digital breast tissue biopsies and render diagnostic decisions: faster case review durations, higher confidence, and lower perceived difficulty. Methods In a longitudinal breast pathology study, 48 resident pathologists reviewed a mix of five novel and five repeated digital whole slide images during Phase 2, occurring 9–39 months after an initial Phase 1 review. Importantly, cases that were repeated for some participants in Phase 2 were novel for other participants in Phase 2. We statistically tested for differences in participants’ case review duration, self-reported confidence, and self-reported difficulty in Phase 2 based on whether the case was novel or repeated. Results No statistically significant difference in review time, confidence, or difficulty as a function of whether the case was repeated or novel in a Phase 2 review occurring 9-39 months after initial viewing; this same result was found in a subset of participants with a shorter (9-14-months) washout. Conclusion These results provide evidence to support the efficacy of at least a 9-months washout period in the design of longitudinal medical imaging and informatics studies to ensure no detectable effect of initial exposure on participant’s subsequent case review.

Myths and Misconceptions of Breast Cancer in the Pakistani Population.

Background Breast cancer is one of the most prevalent types of cancer in the female population. The cultural diversity, religious beliefs, myths, and misinformation regarding the disease contribute to diagnostic delays and enhanced burden on the healthcare system. This study aimed to ascertain the extent of knowledge and prevalence of erroneous beliefs and misconceptions regarding breast cancer among Pakistani women belonging to diverse socioeconomic and educational backgrounds. Methodology This cross-sectional study was performed in a tertiary care hospital in Karachi, Pakistan. A total of 350 women were enrolled in the study as a representative female population, and 300 participants were included who met the inclusion criteria. Participants were conveniently interviewed using a pre-piloted questionnaire designed to assess the prevalent myths and misconceptions about breast cancer. The data were analyzed by SPSS version 23 (IBM Corp., Armonk, NY, USA) using descriptive statistics. Results The study findings point to a significant prevalence of erroneous beliefs and a lack of accurate information on breast cancer. The mean age of the participants was 20.8 ± 10.4 years. The majority of the participants belonged to a middle socioeconomic status (70%) and were undergraduates (61.4%). The participants' friends and family members were the most frequent sources of information regarding breast cancer. The most common myth was "breast-feeding offers immunity to breast cancer completely" (76.6%), followed by "breast cancer spreads after biopsy" (63.8%). Participants also believed that breast tissue biopsy can lead to the spread of cancer (63.4%) and that faith healers and alternative medicine can cure breast cancer (47.5%). One-third (33.3%) of the participants considered all lumps to be breast cancer; however, approximately half (41.6%) of the participants thought that only painful lumps were associated with breast cancer. A significant number of participants believed breast cancer to be a result of God's curse (31.4%) or evil eye (38.7%). Conclusions The findings suggest a critical need for community-based breast health education initiatives that take into account Pakistani women's distinctive cultural and societal attitudes and work to dispel common misconceptions about the condition.

Correlation of background parenchymal enhancement on breast MRI with breast cancer

To evaluate the prognostic value of background parenchymal enhancement (BPE) in breast magnetic resonance imaging (MRI) in women referred to radiological department as a high risk for breast cancer. A retrospective, cross-sectional study included 327 consecutive patients (mean age: 60 years, age range: 30-90 years) who underwent breast MRI and tissue biopsy between 2007 and 2016. All MRI images (T1, T2, and subtraction images) were evaluated visually. The relationship of BPE with patient age, fibroglandular tissue (FGT), Breast Imaging Reporting and Data System (BIRADS) categories, presence of breast cancer, and expression of human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR), oestrogen receptor (ER), and Ki67 were analysed. Furthermore, all variables were correlated with pre- and postmenopausal status. BPE of bilateral breast showed a weak correlation with FGT (right BPE: r=-0.14, p=0.004; left BPE: r=0.16, p=0.003), a weak negative correlation with patient age (right BPE: r=-0.14, p=0.007; left BPE: r=-0.15, p=0.006), and significant correlation with HER2 (right BPE, p=0.02), left BPE with HER2 was not significant. Among the correlations between BPE and BIRADS, only between right BPE and right BIRADS was significant (p=0.031). No clear evidence of an association between breast MRI BPE and breast cancer in premenopausal and postmenopausal status was observed, and no difference was found between the right and left breasts. The results of the present study showed no significant correlations between BPE and breast cancer. In addition, there was no significant difference between the right and left breast. Hence, BPE of MRI may not be a reliable biomarker of breast cancer development.

Selection biases in the systematic collection of breast biobank specimens.

6533 Background: A breast biopsy tissue biobank is a valuable resource for studying breast cancer biology and treatment response. However, underrepresentation of patient populations in biobanks limits the generalizability of findings. The aim of this study was to assess potential age and racial/ethnic disparities in the recruitment process for an institutional breast biopsy tissue bank. Methods: Ultrasound-guided (USG) research biopsy cores were collected immediately after routine clinical biopsy from January 2019 to October 2022 at a large academic center. Study eligibility included patients (pts) aged &gt; 18 years undergoing USG clinical breast biopsy with a radiographically evident mass ≥ 0.6 cm in the longest dimension. Eligible pts, identified by a research associate on the day of the biopsy, were invited to participate at the discretion of the radiologist performing the biopsy. Those approached either consented or declined a research biopsy. Demographic and clinical data of eligible pts were extracted from the EMR. Results: 2449 pts underwent USG breast biopsy and 1309 were deemed eligible for a research biopsy. Of the eligible population, 564 (43%) consented to the study, 322 (25%) declined, and 423 (32%) were not approached. Consented pts were younger compared to those who declined or to those not approached (median age 49, 51, and 51 years, respectively; p = .01). Comparison of study groups by age and race categories are shown in the table. Pts &gt; 70 were less likely to be approached compared to pts &lt; 70 (p = .01). However, The likelihood of pts being approached to consent did not differ significantly with age (p=.09 ). Of the eligible pts, 951 (73%) were White, 327 (25%) were non-White (10% Asian, 8% Black, 1% Hispanic, and 7% other race), and race was unknown for 31 (2%) pts. White and non-White pts were equally likely to be approached (p = .3). However, approached non-White pts were significantly less likely to consent compared to White pts (p =.01). Within the non-White population, Black pts were more likely to decline a research biopsy, with only 50% of approached Black pts consenting compared to 66% of White pts, 61% of Asian pts and 55% of pts of other race. Conclusions: We found disparities based on age and race/ethnicity in participation in a breast biopsy tissue biobank. Older pts were less likely to be offered participation but equally likely to consent when invited, while Black pts were equally likely to be offered participation, but less likely to consent when invited, compared to other racial subgroups. Our findings support targeted interventions to increase participation across diverse subgroups of pts. [Table: see text]

Outdoor air pollution and histologic composition of normal breast tissue

BackgroundBiologic pathways underlying the association between outdoor air pollution and breast cancer risk are poorly understood. Breast tissue composition may reflect cumulative exposure to breast cancer risk factors and has been associated with breast cancer risk among patients with benign breast disease. Herein, we evaluated whether fine particulate matter (PM2.5) was associated with the histologic composition of normal breast tissue. MethodsMachine-learning algorithms were applied to digitized hematoxylin and eosin-stained biopsies of normal breast tissue to quantify the epithelium, stroma, adipose and total tissue area from 3,977 individuals aged 18–75 years from a primarily Midwestern United States population who donated breast tissue samples to the Susan G. Komen Tissue Bank (2009–2019). Annual levels of PM2.5 were assigned to each woman’s residential address based on year of tissue donation. We applied predictive k-means to assign participants to clusters with similar PM2.5 chemical composition and used linear regression to examine the cross-sectional associations between a 5-μg/m3 increase in PM2.5 and square root-transformed proportions of epithelium, stroma, adipose, and epithelium-to-stroma proportion [ESP], overall and by PM2.5 cluster. ResultsHigher residential PM2.5 was associated with lower proportion of breast stromal tissue [β = -0.93, 95% confidence interval: (-1.52, −0.33)], but was not related to the proportion of epithelium [β = -0.11 (-0.34, 0.11)]. Although PM2.5 was not associated with ESP overall [β = 0.24 (-0.16, 0.64)], the association significantly differed by PM2.5 chemical composition (p-interaction = 0.04), with a positive association evident only among an urban, Midwestern cluster with higher concentrations of nitrate (NO3–) and ammonium (NH4+) [β = 0.49 (0.03, 0.95)]. ConclusionsOur findings are consistent with a possible role of PM2.5 in breast cancer etiology and suggest that changes in breast tissue composition may be a potential pathway by which outdoor air pollution impacts breast cancer risk. This study further underscores the importance of considering heterogeneity in PM2.5 composition and its impact on breast carcinogenesis.

407 Moving from observational studies to a clinical trial: the impact of obesity and surgical weight loss on breast imaging, tissue, and cancer screening experience: the B-BRITE study

OBJECTIVES/GOALS: Obesity is associated with increased incidence of breast cancer (BC), yet is not included in many lifetime-risk calculators. Obesity may impact breast cancer screening sensitivity. Retrospective studies show that bariatric surgery is associated with a lower risk of BC, but the effects of surgical weight loss on breast tissue are poorly understood. METHODS/STUDY POPULATION: We proposed a mixed-methods before and after study design to investigate the effects of surgical weight loss on breast tissue via pre- and post-weight loss breast tissue biopsies and imaging. In addition, we aimed to better understand barriers to BC screening for patients with obesity by conducting qualitative interviews. With institutional review board approval, we have begun recruiting 14 cisgender women who plan to undergo Roux-en-Y gastric bypass or sleeve gastrectomy. Participants must be at least 40 years old, with no prior history of breast biopsies or breast cancer and will undergo comprehensive breast cancer screening including mammography with quantitative density assessment, breast MRI, as well as breast core biopsies. RESULTS/ANTICIPATED RESULTS: We hypothesize that obesity and its associated metabolic changes lead to altered breast stroma, including increased inflammation, and tissue stiffness, with subsequent risk of carcinogenesis. If true, we expect to find obese women will have measurably increased inflammatory markers in their breast tissue, which are reduced after bariatric surgery. We expect that change in mammographic density may correlate with fibroglandular volume change on MRI; there are little data on change in background parenchymal enhancement in the setting of obesity and weight change and quantifying this will provide preliminary data for future work. Last, we expect that undergoing BC screening will be easier for patients after weight loss due to constraints of imaging equipment and potential bias in the screening process. DISCUSSION/SIGNIFICANCE: Screening for BC is paramount to improving outcomes yet people with obesity are screened less with worse outcomes. Studying the effects of weight loss on the breast may improve interpretation of breast imaging in the setting of obesity and identify markers of risk. Understanding barriers to screening may help us develop strategies to improve screening.

Zoom behavior during visual search modulates pupil diameter and reflects adaptive control states.

Adaptive gain theory proposes that the dynamic shifts between exploration and exploitation control states are modulated by the locus coeruleus-norepinephrine system and reflected in tonic and phasic pupil diameter. This study tested predictions of this theory in the context of a societally important visual search task: the review and interpretation of digital whole slide images of breast biopsies by physicians (pathologists). As these medical images are searched, pathologists encounter difficult visual features and intermittently zoom in to examine features of interest. We propose that tonic and phasic pupil diameter changes during image review may correspond to perceived difficulty and dynamic shifts between exploration and exploitation control states. To examine this possibility, we monitored visual search behavior and tonic and phasic pupil diameter while pathologists (N = 89) interpreted 14 digital images of breast biopsy tissue (1,246 total images reviewed). After viewing the images, pathologists provided a diagnosis and rated the level of difficulty of the image. Analyses of tonic pupil diameter examined whether pupil dilation was associated with pathologists' difficulty ratings, diagnostic accuracy, and experience level. To examine phasic pupil diameter, we parsed continuous visual search data into discrete zoom-in and zoom-out events, including shifts from low to high magnification (e.g., 1× to 10×) and the reverse. Analyses examined whether zoom-in and zoom-out events were associated with phasic pupil diameter change. Results demonstrated that tonic pupil diameter was associated with image difficulty ratings and zoom level, and phasic pupil diameter showed constriction upon zoom-in events, and dilation immediately preceding a zoom-out event. Results are interpreted in the context of adaptive gain theory, information gain theory, and the monitoring and assessment of physicians' diagnostic interpretive processes.

Abstract P2-07-01: Hydroxytyrosol, a Component of Olive Oil for Breast Cancer Prevention in Women at High Risk

Abstract Background Breast cancer is the most frequently diagnosed cancer in women in developed countries with increased incidence in women at high risk such as those with strong family history, BRCA mutations, atypical hyperplasia etc. Chemoprevention with drugs like tamoxifen and aromatase inhibitors come with challenges of intolerance and limited efficacy in estrogen receptor negative breast cancers. The purpose of our study was to evaluate the effects of hydroxytyrosol (HT), a component of olive oil on mammographic breast density reduction, which is a validated surrogate biomarker for breast cancer prevention as well as to explore on-target effects on Wingless-related integration site (Wnt) pathway, and alterations in key pathways of proliferation, DNA damage repair and stem cell function. Methods This study was conducted using 25mg/day oral dose of HT for 12 months in both pre- and post-menopausal women who are at increased risk of breast cancer with Gail 5-year risk score ≥ 1.67 and/or &amp;gt; 10% probability of BRCA mutation and had declined standard chemoprevention. These women underwent annual mammograms as well as had the option to have a biopsy of normal breast tissue before and after HT. Maximum volumetric breast density (Max VBD%) was assessed quantitatively using Volpara software (VIS 3.2) and the annualized percent decrease in max VBD% between baseline (BL) and end of treatment (EOT) with HT was analyzed in the study. RNA was extracted from the breast biopsies and RNA sequencing (RNA-Seq) and multiplex analysis of 28 proteins using NanoString nCounter analysis was performed to compare the BL with EOT samples. Results A total of 61 women were screened for the trial, 51 were enrolled and 41 patients completed the study. Median age for the study population was 54 years (range 35-76 years). There were 26 patients with paired BL and EOT mammograms. There were 14 patients with paired BL and EOT breast biopsies and seven patients with only BL and seven with only EOT biopsies. Mammographic density as measured by max VBD% showed a non-significant change of -0.038%, p = 0.49. However, on subgroup analysis in women 60-years or older, the mean decrease in max VBD% was - 3.7% (p = 0.0391), especially in those with high baseline mammographic density (&amp;gt; 10% baseline max VBD%). RNAseq data was generated from 15 BL and 17 EOT samples and pathways were confirmed by NanoString. Our bioinformatics pipeline identified 190 transcripts that were upregulated and 90 that were downregulated in EOT vs. BL by at least 1.5 fold. Reactome pathway R-HSA-195721 (Signaling by WNT) is identified as the top pathway enriched with EOT downregulated genes. On further review of the expression profiles, 82 of 261 member genes had p-value &amp;lt; 0.05 for EOT vs. BL, among which only 4 were upregulated and 78 were downregulated in EOT samples. These 82 genes were highly interactive with each other, with 379 high confidence protein-protein interactions (PPIs) (confidence score &amp;gt; 0.7 from STRING database) involving 81 out of 82 genes. In addition, mitotic telophase/cytokinesis (p = 0.004), ATM signaling (p = 0.007) were some pathways that were upregulated whereas, NOTCH signaling (p = 0.007), oxidative stress induced senescence (p = 0.0001) pathways were downregulated in EOT vs. BL. Conclusions Hydroxytyrosol, a component of olive oil did not show a decrease in breast density in the intention to treat population but showed some reduction in breast density in women 60-years of age and above, especially in those with high baseline breast density. HT showed on target effects by affecting Wnt signaling pathway, as well as decrease in proliferation. This study lays the foundation for future larger studies in exploring a natural compound such as HT for chemoprevention of breast cancer. Citation Format: Akshjot Puri, Zheng Yin, Sergio Granados-Principal, Joe Ensor, Liliana Guzman, Roberto Rosato, Hong Zhao, Stephen Wong, Tejal Patel, Jenny Chang. Hydroxytyrosol, a Component of Olive Oil for Breast Cancer Prevention in Women at High Risk [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-07-01.

Enhancing the Breast Histopathology Image Analysis for Cancer Detection Using Variational Autoencoder.

A breast tissue biopsy is performed to identify the nature of a tumour, as it can be either cancerous or benign. The first implementations involved the use of machine learning algorithms. Random Forest and Support Vector Machine (SVM) were used to classify the input histopathological images into whether they were cancerous or non-cancerous. The implementations continued to provide promising results, and then Artificial Neural Networks (ANNs) were applied for this purpose. We propose an approach for reconstructing the images using a Variational Autoencoder (VAE) and the Denoising Variational Autoencoder (DVAE) and then use a Convolutional Neural Network (CNN) model. Afterwards, we predicted whether the input image was cancerous or non-cancerous. Our implementation provides predictions with 73% accuracy, which is greater than the results produced by our custom-built CNN on our dataset. The proposed architecture will prove to be a new field of research and a new area to be explored in the field of computer vision using CNN and Generative Modelling since it incorporates reconstructions of the original input images and provides predictions on them thereafter.

Associations of breast cancer related exposures and gene expression profiles in normal breast tissue-The Norwegian Women and Cancer normal breast tissue study.

Normal breast tissue is utilized in tissue-based studies of breast carcinogenesis. While gene expression in breast tumor tissue is well explored, our knowledge of transcriptomic signatures in normal breast tissue is still incomplete. The aim of this study was to investigate variability of gene expression in a large sample of normal breast tissue biopsies, according to breast cancer related exposures (obesity, smoking, alcohol, hormone therapy, and parity). We analyzed gene expression profiles from 311 normal breast tissue biopsies from cancer-free, post-menopausal women, using Illumina bead chip arrays. Principal component analysis and K-means clustering was used for initial analysis of the dataset. The association of exposures and covariates with gene expression was determined using linear models for microarrays. Heterogeneity of the breast tissue and cell composition had the strongest influence on gene expression profiles. After adjusting for cell composition, obesity, smoking, and alcohol showed the highest numbers of associated genes and pathways, whereas hormone therapy and parity were associated with negligible gene expression differences. Our results provide insight into associations between major exposures and gene expression profiles and provide an informative baseline for improved understanding of exposure-related molecular events in normal breast tissue of cancer-free, post-menopausal women.