Breast Tissue Samples Research Articles

Fine-needle aspiration biopsy possibilities in studying the molecular genetic landscape of breast tissue

Background. Core biopsy of the breast is currently considered to be the standard method of obtaining material for morphological and molecular genetic methods. Unfortunately, this method is associated with a number of problems, primarily the risk of complications (bleeding, pneumothorax) and discomfort during manipulation.Aim. To analyze transcriptional signatures of breast tissue samples obtained by fine-needle aspiration biopsy. Materials and methods. Using reverse transcriptase polymerase chain reaction, we studied the mRNA expression level of 60 target genes in 60 samples obtained by fine-needle aspiration biopsy and in 60 corresponding formalin-fixed paraffin-embedded (FFPE) surgical specimens of breast. Samples were obtained from the tumor, adjacent tissue, the so-called tumor bed and formally normal tissue at a distance from the primary lesion.Results. A comparative analysis of transcriptional signatures in samples obtained by fine-needle aspiration biopsy and FFPE specimens (120 samples in total) reveled the strongest correlations between transcriptional signatures in biopsy samples and FFPE specimens of tumors. Very strong correlation in tumor samples was established for one gene (CTSL2); strong for 18 genes (MKI67, MYBL2, NAT1, PTEN, TPX2, PTTG1, UBE2T, CCNB1, ESR1, CCND1, MYC, SCGB2A2, MIA, TRAC, FGFR4, ANLN, GSTM1, PRLR); averages for 28 genes (PGR, AURCA, KRT5, FOXA1, SFRP1, EMSY, EXO1, PAK1, KIF14, ERBB2, MMP11, BCL2, BAG1, TMEM45B, BIRC5, CD274/PDL1, ZNF703, TYMS, CCNE1, TPT1, TMEM45A, BRCA1, BRCA2, ESR2, STS, TNFSF11/RANKL, TNFRSF11B/OPG, TNF); weak for 4 genes (GRB7, EGFR, PGRMC1, CYP19A). The presence of correlations between transcriptional signatures in biopsy samples and FFPE specimens can be established in case of sufficient material corresponding to sample intake control (SIC) ≥5 lg for B2M gene.Conclusion. The ability to conduct molecular genetic research on small samples of breast tissue makes it possible to obtain the material using the most minimally invasive method. And this, in turn, expands the possibilities of “genetic monitoring” of cancer, as well as the possibility of more accurate assessment the risks of malignant tumor development in the settings of benign conditions in women with fibrocystic disease and increased mammographic density.

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.

Enhanced Pelican Optimization Algorithm with Deep Learning-Driven Mitotic Nuclei Classification on Breast Histopathology Images.

Breast cancer (BC) is a prevalent disease worldwide, and accurate diagnoses are vital for successful treatment. Histopathological (HI) inspection, particularly the detection of mitotic nuclei, has played a pivotal function in the prognosis and diagnosis of BC. It includes the detection and classification of mitotic nuclei within breast tissue samples. Conventionally, the detection of mitotic nuclei has been a subjective task and is time-consuming for pathologists to perform manually. Automatic classification using computer algorithms, especially deep learning (DL) algorithms, has been developed as a beneficial alternative. DL and CNNs particularly have shown outstanding performance in different image classification tasks, including mitotic nuclei classification. CNNs can learn intricate hierarchical features from HI images, making them suitable for detecting subtle patterns related to the mitotic nuclei. In this article, we present an Enhanced Pelican Optimization Algorithm with a Deep Learning-Driven Mitotic Nuclei Classification (EPOADL-MNC) technique on Breast HI. This developed EPOADL-MNC system examines the histopathology images for the classification of mitotic and non-mitotic cells. In this presented EPOADL-MNC technique, the ShuffleNet model can be employed for the feature extraction method. In the hyperparameter tuning procedure, the EPOADL-MNC algorithm makes use of the EPOA system to alter the hyperparameters of the ShuffleNet model. Finally, we used an adaptive neuro-fuzzy inference system (ANFIS) for the classification and detection of mitotic cell nuclei on histopathology images. A series of simulations took place to validate the improved detection performance of the EPOADL-MNC technique. The comprehensive outcomes highlighted the better outcomes of the EPOADL-MNC algorithm compared to existing DL techniques with a maximum accuracy of 97.83%.

Metabolic coupling in phyllodes tumor of the breast and its association with tumor progression.

There are markers of metabolic coupling in breast cancer. Loss of caveolin-1 (Cav-1) and upregulation of monocarboxylate transporters (MCTs), especially MCT1 and MCT4, serve an important role in metabolic coupling necessary for release and uptake of metabolites. However, the occurrence of these phenomena in phyllodes tumors (PTs) of the breast is unclear. A total of 101 PTs (60 benign, 26 borderline and 15 malignant) and nine breast tissue samples with no pathological lesions were analyzed. Immunohistochemical staining for Cav-1, MCT1 and MCT4 was performed using tissue microarray and their expression in both stromal and epithelial components was assessed. Cav-1 expression in PTs demonstrated a significant decrease in the stromal component compared with that in the normal breast tissues (P<0.001). MCT1 expression in both epithelial and stromal components was significantly increased in PTs, compared with that in normal breast tissues (both P<0.001). Stromal MCT1 and MCT4 expression were different depending on tumor grade of PTs, and stromal MCT1 expression significantly increased with increasing tumor grade (P<0.001). Although not statistically significant, stromal Cav-1 expression notably decreased with increases in PT grade. High stromal MCT1 expression was significantly associated with lower disease-free survival rate in comparison with low stromal MCT1 expression (P<0.05). These results suggested that changes in protein expression of Cav-1, MCT1 and MCT4 may be associated with tumorigenesis and progression of PTs of the breast.

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning

Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast tissue, such as glandular tissue, fat, and lesions, differ in sound speed. Given a constant sound speed assumption, these differences can degrade the quality of reconstructed images via phase aberration. Sound speed images can be a powerful tool for improving image quality and identifying diseases if properly estimated. To this end, we propose a supervised deep-learning approach for sound speed estimation from analytic ultrasound signals. We develop a large-scale simulated ultrasound dataset that generates representative breast tissue samples by modeling breast gland, skin, and lesions with varying echogenicity and sound speed. We adopt a fully convolutional neural network architecture trained on a simulated dataset to produce an estimated sound speed map. The simulated tissue is interrogated with a plane wave transmit sequence, and the complex-value reconstructed images are used as input for the convolutional network. The network is trained on the sound speed distribution map of the simulated data, and the trained model can estimate sound speed given reconstructed pulse-echo signals. We further incorporate thermal noise augmentation during training to enhance model robustness to artifacts found in real ultrasound data. To highlight the ability of our model to provide accurate sound speed estimations, we evaluate it on simulated, phantom, and in-vivo breast ultrasound data.

Fine-needle aspiration biopsy of axillary lymph nodes: Areliable diagnostic tool for breast cancer staging.

Pathologic evaluation of sentinel lymph node biopsy (SLNB) samples is crucial for axillary staging in patients newly diagnosed with breast cancer. Patients with pathologic evidence of nodal metastasis scheduled for upfront surgery typically also undergo axillary lymph node dissection (ALND). Although SLNB is the gold standard method for detecting nodal metastasis, axillary lymph node fine-needle aspiration biopsy (FNAB) utility has not been thoroughly explored. Ultrasound-guided axillary lymph node FNAB samples along with concurrent ipsilateral breast tissue samples were searched and reviewed. The control group included histologic findings of axillary dissection or intraoperative SLNB results. A total of 354 axillary lymph node FNAB samples with matched histology were included. Of these, 187 (52.8%) were positive for metastatic carcinoma of breast origin; 143 (40.4%) were negative for metastasis; 12 (3.4%) showed atypical cells; six (1.7%) were suspicious for metastasis; and six (1.7%) were nondiagnostic because of a lack of lymphoid tissue and malignant cells. Of the 143 negative FNAB samples, 22 (15.4%) were positive on either intraoperative SLNB or ALND. When only the positive and negative FNAB samples were accounted for (n=330; 93.2%), overall diagnostic sensitivity and specificity were 89.4% and 99.2%, respectively. Although axillary SLNB is the standard procedure for detecting nodal metastasis of breast origin, axillary lymph node FNAB appears to be a suitable alternative in a significant proportion of patients. A standard SLNB should be performed in cases of negative axillary lymph node FNAB findings, particularly nodes with abnormal imaging findings.

SAT636 Obesity And Aging Interactions Modify The Breast Tissue Microbiome Influencing Cancer Risk

Abstract Disclosure: N.M. Iyengar: None. A. Chiba: None. M. Howard-McNatt: None. A. Thomas: None. D.R. Soto-Pantoja: None. K.L. Cook: None. Obesity is one of the few modifiable risk factors for postmenopausal breast cancer. While obesity influences on the gut microbiome are established, the effect of diet and adiposity on tissue resident microbiome populations are underexplored. Studies have shown that breast tissue has a distinct microbiome, which is shifted in the presence of tumors or diet. However, whether obesity and menopause modify the breast microbiome is unknown. Using a cohort of non-cancerous breast tissue samples (n=80) taken at surgery from women that underwent mastectomy for breast cancer, we now demonstrate that obesity and aging interact to shift the breast microbiome. DNA isolated from breast tissue collected at surgery was used to perform V3-V4 amplicon 16S bacterial sequencing. Breast tissue from postmenopausal women with obesity (mean BMI 34.7 ±3.7) displayed a significantly higher α-diversity than breast tissue from postmenopausal lean women (mean BMI 21.9 ±1.7). Postmenopausal women with obesity also displayed a significantly different β-diversity than all other groups (Bray-Curtis; PERMANOVA p&amp;lt;0.02). At the species level, breast tissue from postmenopausal women with obesity had a significantly elevated Akkermansia mucinphila proportional abundance (5.6%) when compared with all other groups (0.05-0.3% proportional abundance), demonstrating obesity and menopause interact to modify the breast tissue microbiome. Akkermansia muciniphila is a mucin-degrading bacteria. Breast tumors display aberrant mucin glycosylation and abundance, which previously were shown to promote carcinogenesis. Staining ER+ breast tumors for mucin-1 from patients with or without obesity indicates patient BMI positively correlates with tumor mucin-1 abundance, suggesting obesity regulation of mucin and/or mucin-degrading bacteria may promote breast tumorigenesis. To determine physiological relevance of breast Akkermansia muciniphila abundance, Western diet-fed MMTV-PyMT mice were intra-nipple injected with saline or Akkermanisa muciniphila bacteria into the mammary gland (MG) at 5, 7, and 9 weeks of age and palpated weekly for tumor formation. Elevated MG Akkermansia presence was associated with increased mammary tumorigenesis and multiplicity. Tumor mucin-1 was decreased with A. muciniphila administration. Flow cytometry analysis of single cell suspensions of breast tumors indicate A. muciniphila modified infiltrating immune populations. Overall, these results suggest obesity and aging may interact to enrich breast mucin-degrading bacteria abundance as a risk factor for postmenopausal breast cancer. Presentation: Saturday, June 17, 2023

The expression of matrix metalloproteinase 2, 9 and 11 in Ethiopian breast cancer patients

IntroductionMatrix metalloproteinases (MMPs) play a pathophysiological role in cancer initiation and progression. Numerous studies have examined an association between MMP-2, MMP-9, and MMP-11 expression and clinicopathological characteristics of breast cancer (BC); however, no research has been done on the MMP expression levels in BC cases from Ethiopia.Materials and methodsA total of 58 formalin-fixed paraffin-embedded breast tissue samples encompassing 16 benign breast tumors and 42 BC were collected. The RNA was extracted and quantitative reverse-transcription PCR was performed. GraphPad Prism version 8.0.0 was used for statistical analysis.ResultsThe MMP-11 expression levels were significantly higher in breast cancer cases than in benign breast tumors (P = 0.012). Additionally, BC cases with positive lymph nodes and ER-positive receptors had higher MMP-11, MMP-9, and MMP-2 expression than cases with negative lymph nodes and ER-negative, respectively. The MMP-11 and MMP-9 expressions were higher in grade III and luminal A-like tumors than in grade I-II and other subtypes, respectively.ConclusionThe MMP-11 expression was higher in BC than in benign breast tumors. Additionally, MMP-11, MMP-9, and MMP-2 were higher in BC with positive lymph nodes and estrogen receptors. Our findings suggest an important impact of MMPs in BC pathophysiology, particularly MMP-11.

Measurement of Total Iron in Breast Tissue Samples by Inductively Coupled Plasma-Mass Spectrometry

Measurement of Total Iron in Breast Tissue Samples by Inductively Coupled Plasma-Mass Spectrometry

Brief research report pesticide occupational exposure leads to significant inflammatory changes in normal mammary breast tissue.

Studies have documented the high occurrence of several tumors, including female breast cancer, in populations occupationally exposed to pesticides worldwide. It is believed that in addition to direct DNA damage, other molecular alterations that indicate genomic instability are associated, such as epigenetic modifications and the production of inflammation mediators. The present study characterized the profile of inflammatory changes in the breast tissue of women without cancer occupationally exposed to pesticides. In samples of normal breast tissue collected during biopsy and evaluated as negative for cancer by a pathologist, oxidative stress levels were assessed as inflammatory markers through measurements of lipoperoxides and total antioxidant capacity of the sample (TRAP) by high-sensitivity chemiluminescence, as well as levels of nitric oxide (NOx) metabolites. The levels of inflammation-modulating transcription factors PPAR-γ (peroxisome proliferator-activated receptor gamma) and NF-κB (nuclear factor kappa B) were also quantified, in addition to the pro-inflammatory cytokines tumor necrosis factor-alpha (TNF-α) and interleukin 12 (IL-12). The levels of lipoperoxides, TRAP, and NOx were significantly lower in the exposed group. On the other hand, PPAR-γ levels were increased in the breast tissue of exposed women, with no variation in NF-κB. There was also a rise of TNF-α in exposed women samples without significant variations in IL-12 levels. These findings suggest an inflammatory signature of the breast tissue associated with pesticide exposure, which may trigger mechanisms related to mutations and breast carcinogenesis.

Diagnostic Accuracy of Fine Needle Aspiration Cytology, Triple Test and Tru-cut Biopsy in the Detection of Breast Lesion

Background: The majority of breast illnesses manifest as a palpable mass. The vast majority of breast lesions are not malignant, and the vast majority of benign lesions do not progress to cancer; however, the accuracy of diagnosis can be improved by a combination of preoperative tests such as physical examination, mammography, fine-needle aspiration cytology (FNAC), and Trucut needle biopsy (TCNB) or core needle biopsy (CNB). FNAC has gained in popularity and is now the primary treatment performed after a history and clinical examination to diagnose solid and cystic breast masses. This study was designed to assess the accuracy of FNAC in comparison to Triple Test and TCNB for the diagnosis of breast masses. Methodology: From January 2023 through May 2023, this study was conducted in the Tezpur Medical College and Hospital. The research included all female patients over the age of 20 with clinically palpable lumps. Palpable breast lumps need a complete clinical breast examination, imaging, and tissue sample for a clear diagnosis to rule out cancer.The Ultrasonography/Mammography, FNAC and tru-cut biopsy procedures were performed concurrently in the same region, and the results were compared to final histopathology as the gold standard. Result: The majority of the patients in the study were in age group of &gt; 60 years. In our study Left breast was involved in 41 (58.5%) patients and right breast in 29 (41.4%) patients. The most frequent site involved was upper outer quadrant in 38 (54.2%). The overall sensitivity of FNAC in our study was 93.75%, tru-cut biopsy is 100% and that of triple test is 100% and specificity for malignancy was 91.6%, 93.6 and 95.6% for FNAC, tru-cut biopsy and triple test respectively. Conclusion: All three techniques have advantages and disadvantages. Core Needle Biopsy cannot be used in place of FNAC, and it is not required to identify all breast lesions. It can be utilised as an adjuvant in circumstances when cytology is definitive and biomarker tests are required. triple test and trucut were more accurate than FNAC in our testing.Trucut biopsy was able to provide histological diagnosis, and the findings were 100% consistent with the final histopathology report.&#x0D;

Low presence of papillomavirus and its lack of correlation with clinicopathological factors in breast cancer: a case control study.

Breast cancer is currently the most commonly diagnosed neoplasm in women worldwide. There is evidence that human papillomavirus (HPV) infection may play a key role in breast cancer aggressiveness, but results are conflicting across studies. The aim of this study was to investigate the presence of the HPV viral genome in benign and malignant breast tissue samples and its clinicopathological characteristics of cancer. In this case-control study, 100 formalin-fixed paraffin-embedded (FFPE) of breast cancer and 100 blocks of non-cancerous breast tissue were selected as a control group from the pathology department of Imam Khomeini Hospital in Ahvaz from 2020-2022. The presence of HPV was detected using nested PCR including MY09/11 primers and sequencing were performed for virus genotyping. The present study enrolled 100 subjects each in two cancer and control groups with a mean age of 52.81±13.23 and 35.77±11.65, respectively. The risk of cancer in HPV-infected patients is almost 5 times higher than in HPV-negative individuals, it is not statistically significant (OR =4.99, 95% CI 0.35 to 72.15, p=0.238). The prevalence of HPV in the cancer and control groups was 7% and 1%, respectively and HPVs detected in two groups were of the HPV 16 genotype. Although the chance of ER and PR expression, lymphvascular involvement, perineural invasion, and higher tumor grade was higher in HPV-positive subjects than in HPV-negative subjects, this was not statistically significant (OR>1, p>0.05). Based on studies reporting the existence of sequences of different high-risk HPV types (oncogenes) in breast cancer tissues, this study confirmed the hypothesis of a possible infectious cause in the development of breast cancer. So far, however, the results have been controversial and inconclusive. Further studies with large sample sizes are needed to demonstrate the link between HPV and breast cancer.

Histochemical Demonstration of Fungi in Breast Diseases at University of Maiduguri Teaching Hospital-North Eastern Nigeria

Breast disease is a global public health concern, and recent research suggests that fungal infections may be linked to its development and progression. This study aims to investigate the presence of fungi in formalin-fixed paraffinembedded (FFPE) breast tissue samples diagnosed with various breast diseases, including breast cancer, using histological staining techniques. The study design was a retrospective cross-sectional study that used convenience sampling to retrieve 49 breast tissue blocks diagnosed with various breast diseases from the Histopathology archive of the University of Maiduguri Teaching Hospital, Nigeria. The samples were re-embedded with paraffin wax, sectioned, and stained using Haematoxylin and Eosin and Grocott Methanamine Silver Stain. The data collected was analyzed descriptively and using chi-square tests. Fibroadenoma was the most common diagnosis in the study (69.3%), followed by Chronic Granulomatous Mastitis (18.4%) and breast cancer (12.2%). The highest frequency of Fibroadenoma diagnosis was in the age range of 30-39, whereas the highest frequency of breast cancer diagnosis was in the age range of 20-29. The study found that fungal infections were present in breast tissue samples, and the highest percentage of positive Gomori Methenamine Silver (GMS) stain test results were found in breast disease cases with breast cancer with a significant p value of 0.0175. This study provides evidence of a potential association between fungal infections and breast diseases in North Eastern Nigeria. Further research is needed to fully understand the mechanisms underlying this association and its implications for breast cancer prevention and treatment.

A cohort study investigating the role of Bisphenol A in the molecular pathogenesis of breast cancer.

Breast cancer is an abnormal division of breast cells. Bisphenol A (BPA), an environmental toxicant, is identified as an emerging risk factor for breast cancer development. However, to the best of our knowledge, no previous study has investigated the BPA levels in breast cancer patients in Pakistan. The present study sought to explore the role of BPA in tumor growth among the Pakistani population. The levels of BPA were analyzed in the serum samples of breast cancer patients and controls by using HPLC. To elucidate the role of BPA to initiate tumorigenic events in breast tissue different biochemical assays along with expression analysis of tumor markers were performed. The level of BPA in the serum samples of breast cancer patients was significantly higher than control. Histological analysis of breast cancer tissue samples revealed distinct subtypes of tumor, such as ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). There was a significant increase in ROS level while a significant decrease in the levels of superoxide dismutase (SOD) and catalase (CAT) enzymes in malignant breast tissue samples as compared to control tissue samples. We found upregulated expression of p53, ZEB1 and WNT1 genes at mRNA level in malignant breast tissue samples by 17 folds, 328 folds and 35 folds, respectively. p53 protein expression in malignant breast tissue samples was also enhanced at the translational level. Current findings suggest a relationship between BPA and the progression of breast cancer among the Pakistani population.

LC/MS-based untargeted lipidomics reveals lipid signatures of nonpuerperal mastitis

BackgroundNonpuerperal mastitis (NPM) is a disease that presents with redness, swelling, heat, and pain during nonlactation and can often be confused with breast cancer. The etiology of NPM remains elusive; however, emerging clinical evidence suggests a potential involvement of lipid metabolism.MethodLiquid chromatography‒mass spectrometry (LC/MS)-based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the NPM lipid change in breast tissue. Twenty patients with NPM and 10 controls were enrolled in this study.ResultsThe results revealed significant differences in lipidomics profiles, and a total of 16 subclasses with 14,012 different lipids were identified in positive and negative ion modes. Among these lipids, triglycerides (TGs), phosphatidylethanolamines (PEs) and cardiolipins (CLs) were the top three lipid components between the NPM and control groups. Subsequently, a total of 35 lipids were subjected to screening as potential biomarkers, and the chosen lipid biomarkers exhibited enhanced discriminatory capability between the two groups. Furthermore, pathway analysis elucidated that the aforementioned alterations in lipids were primarily associated with the arachidonic acid metabolic pathway. The correlation between distinct lipid populations and clinical phenotypes was assessed through weighted gene coexpression network analysis (WGCNA).ConclusionsThis study demonstrates that untargeted lipidomics assays conducted on breast tissue samples from patients with NPM exhibit noteworthy alterations in lipidomes. The findings of this study highlight the substantial involvement of arachidonic acid metabolism in lipid metabolism within the context of NPM. Consequently, this study offers valuable insights that can contribute to a more comprehensive comprehension of NPM in subsequent investigations.Trial registrationShuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (Number: 2019-702-57; Date: July 2019).

Assessment of resection margins during breast-conserving surgery using multimodal optical coherence tomography

Background. Breast cancer (BC) has been ranked first in morbidity and mortality among the female population in Russian Federation for several years. Rapid and accurate intraoperative examination of the cleanliness of resection margins is the main condition for breast-conserving surgery (BCS) to reduce the risks of local recurrence.Aim. To examine the tumor margins and assess the cleanliness of the resection margins in BCS in patients diagnosed with BC using multimodal optical coherence tomography (MM OCT) with comparative planned histological and additional molecular genetic analysis.Materials and methods. The study was carried out on postoperative samples of tumor and non-tumor breast tissue obtained from 115 patients with BC T1–2N0M0G2–3 stage IA–IIA, after BCS in the volume of radical resection or lumpectomy with histological control of the resection margins. A spectral domain MM OCT device (OCT 1300-E, BioMedTech LLC, Russia) was used, which provides structural OCT images to study the backscattering properties of tissue and allows performing a quantitative assessment of the elastic properties of the tissue by compression optical coherence elastography (OCE).Results. The MM OCT method was able to determine the exact margins between the tumor and non-tumor breast tissue. The main signs of the tumor were a decrease in the level and depth of penetration of the OCT signal in the structural OCT images, as well as an increase in the stiffness values (&gt;200 kPa) in the OCE images with the highest stiffness values (&gt;600 kPa) in the area of tumor cell accumulations. The use of compression OCE made it possible to detect clusters of tumor cells in the margins of resection at a distance of 5 mm from the visible border of the tumor. Among the 132 studied resection margins in 6 cases, the positive resection margin was determined by the OCE method, which was subsequently confirmed histologically. The negative resection margins were characterized by the lowest stiffness values (&lt;200 kPa) in the OCE images and were confirmed by both histological analysis and molecular genetic analysis. ROC-analysis established a threshold stiffness value of 159.8 kPa, which indicates the presence of tumor tissue at the resection margins in the presence of a high stiffness area larger than 500 µm. The high diagnostic accuracy of the OCE method (98.5 %) was determined to distinguish between the negative and positive resection margins during BCS.Conclusion. The use of MM OCT with OCE modality makes it possible to clearly distinguish different types of breast tissue in BC (adipose tissue, connective tissue, accumulation of tumor cells). MM OCT can be used as an additional intraoperative tool for visualizing tumor cells boundaries and assessing the cleanliness of resection margins in real time during BCS.

Association of the Estrogen Receptors Beta Expression with the Ki-67 Proliferative Index in Breast Cancer

Background. Estrogen receptors beta (ERβ) are an important biological regulator and target of antiestrogens, however, unlike estrogen receptors alpha (ERɑ), their significance in the prognosis and treatment of breast cancer remains unclear. Purpose. Evaluation of the ERβ prognostic value in the comparative assessment of frequency and level of the marker expression in groups with good and poor prognosis by Ki-67 proliferative index score in breast cancer. Methods. ERβ expression level (% of cells expressing the marker) in 68 breast tissue samples was quantified by immunofluorescence and flow cytometry. Primary antibodies to ERβ (clone 14C8, ab288) and secondary antibodies conjugated with DyLight650 (ab98729) were used. In the same samples, the Ki-67 expression level was assessed by the immunohistochemical method. Results. The ERβ and Ki-67 were detected in 100% breast tissue samples with high heterogeneity of the markers’ expression in different patients. Statistical analysis of good and poor prognosis in accordance with the Ki-67 proliferative index score (Ki-67≤20% and Ki-67&gt;20%) showed the prognostic value of the ERβ expression level of 50%. There was no association between the Ki-67 and ERβ expression levels in the same tumor sample (Spearman's rank correlation coefficient R=–0,16; P&gt;0,05). At the same time, high expression of ERβ≥50% was 2,3 times more frequently detected in the good vs poor prognostic group by Ki-67 — 41% vs 18%, P=0,02. Conclusion. The ERβ expression level ≥50% in the tumor can be considered as a factor of good prognosis of breast cancer.

Multiscale X-ray phase-contrast tomography: From breast CT to micro-CT for virtual histology

Phase-contrast imaging techniques address the issue of poor soft-tissue contrast encountered in traditional X-ray imaging. This can be accomplished with the propagation-based phase-contrast technique by employing a coherent photon beam, which is available at synchrotron facilities, as well as long sample-to-detector distances. This study demonstrates the optimization of propagation-based phase-contrast computed tomography (CT) techniques for multiscale X-ray imaging of the breast at the Elettra synchrotron facility (Trieste, Italy).Two whole breast mastectomy samples were acquired with propagation-based breast-CT using a monochromatic synchrotron beam at a pixel size of 60 µm. Paraffin-embedded blocks sampled from the same tissues were scanned with propagation-based micro-CT imaging using a polychromatic synchrotron beam at a pixel size of 4 µm. Images of both methodologies and of the same sample were spatially registered.The resulting images showed the transition from whole breast imaging with propagation-based breast-CT methodology to virtual histology with propagation-based micro-CT imaging of the same sample. Additionally, conventional histological images were matched to virtual histology images.Phase-contrast images offer a high resolution with low noise, which allows for a highly precise match between virtual and conventional histology. Furthermore, those techniques allow a clear discernment of breast structures, lesions, and microcalcifications, being a promising clinically-compatible tool for breast imaging in a multiscale approach, to either assist in the detection of cancer in full volume breast samples or to complement structure identification in paraffin-embedded breast tissue samples.

Exploring breast tissue microbial composition and the association with breast cancer risk factors

BackgroundMicrobial dysbiosis has emerged as an important element in the development and progression of various cancers, including breast cancer. However, the microbial composition of the breast from healthy individuals, even relative to risk of developing breast cancer, remains unclear. Here, we performed a comprehensive analysis of the microbiota of the normal breast tissue, which was analyzed in relation to the microbial composition of the tumor and adjacent normal tissue.MethodsThe study cohorts included 403 cancer-free women (who donated normal breast tissue cores) and 76 breast cancer patients (who donated tumor and/or adjacent normal tissue samples). Microbiome profiling was obtained by sequencing the nine hypervariable regions of the 16S rRNA gene (V1V2, V2V3, V3V4, V4V5, V5V7, and V7V9). Transcriptome analysis was also performed on 190 normal breast tissue samples. Breast cancer risk score was assessed using the Tyrer-Cuzick risk model.ResultsThe V1V2 amplicon sequencing resulted more suitable for the analysis of the normal breast microbiome and identified Lactobacillaceae (Firmicutes phylum), Acetobacterraceae, and Xanthomonadaceae (both Proteobacteria phylum) as the most abundant families in the normal breast. However, Ralstonia (Proteobacteria phylum) was more abundant in both breast tumors and histologically normal tissues adjacent to malignant tumors. We also conducted a correlation analysis between the microbiome and known breast cancer risk factors. Abundances of the bacterial taxa Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were associated with age (p < 0.0001), racial background (p < 0.0001), and parity (p < 0.0001). Finally, transcriptome analysis of normal breast tissues showed an enrichment in metabolism- and immune-related genes in the tissues with abundant Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp., whereas the presence of Ralstonia in the normal tissue was linked to dysregulation of genes involved in the carbohydrate metabolic pathway.ConclusionsThis study defines the microbial features of normal breast tissue, thus providing a basis to understand cancer-related dysbiosis. Moreover, the findings reveal that lifestyle factors can significantly affect the normal breast microbial composition.

Validating Sam68 expression and protein level in breast cancer.

Breast carcinoma ranks as the second most common cancer among women worldwide. Despite significant therapeutic advancements, approximately 25% of breast carcinoma cases have resistance to current treatment modalities, posing a significant challenge for patient management. This study aimed to investigate the role of Sam68 mRNA and its protein in promoting oncogenesis and breast cancer progression. Sam68 protein levels were assessed in tissue samples using an Enzyme-Linked Immunosorbent Assay kit from Sun Long Biotech. Whole RNA was isolated from malignant breast tissue samples obtained from patients. The RNA concentration was determined using an Eppendorf photometer, yielding an average concentration of 62.1±10.07 ng/µl. The purity of the isolated RNA was evaluated by measuring the A260/A280 ratio (1.9±0.07) and the A260/A230 ratio (1.7±0.3). The results indicated a significant upregulation of Sam68 mRNA expression in breast cancer tissues, supporting the findings from previous studies and indicating the correlation between altered Sam68 expression and the development of breast carcinoma, highlighting the potential significance of Sam68 in the pathogenesis of the disease. Estimating Sam68 in the blood may serve as a potential biomarker for assessing the malignant grade and metastatic spread of breast carcinoma cells.