The Vitamin D Receptor as a Prognostic Marker in Breast Cancer-A Cohort Study.

Previous research has indicated an association between the presence of the vitamin D receptor (VDR) in breast cancer tissue and a favorable prognosis. This study aimed to further evaluate the prognostic potential of VDR located in the nuclear membrane or nucleus (liganded). The VDR protein levels were analyzed using immunohistochemistry in tumor samples from 878 breast cancer patients from Lund, Sweden, included in the Breast Cancer and Blood Study (BCBlood) from October 2002 to June 2012. The follow-up for breast cancer events and overall survival was recorded until 30 June 2019. Univariable and multivariable survival analyses were conducted, both with complete case data and with missing data imputed using multiple imputation by chained equations (MICE). Tumor-specific positive nuclear membrane VDR(num) staining was associated with favorable tumor characteristics and a longer breast cancer free interval (BCFI; HR: 0.64; 95% CI: 0.44-0.95) and overall survival (OS; HR: 0.52; 95% CI: 0.34-0.78). Further analyses indicated that VDRnum status also was predictive of overall survival when investigated in relation to ER status. There were significant interactions between VDR and invasive tumor size (Pinteraction = 0.047), as well as mode of detection (Pinteraction = 0.049). VDRnum was associated with a longer BCFI in patients with larger tumors (HR: 0.36; 95% CI: 0.14-0.93) or clinically detected tumors (HR: 0.28; 95% CI: 0.09-0.83), while no association was found for smaller tumors and screening-detected tumors. Further studies are suggested to confirm our results and to evaluate whether VDR should and could be used as a prognostic and targetable marker in breast cancer diagnostics.

Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI.

Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming process, preventing its further spread can be aided by creating machine-based forecasts. Machine learning and Explainable AI are crucial in classification as they not only provide accurate predictions but also offer insights into how the model arrives at its decisions, aiding in the understanding and trustworthiness of the classification results. In this study, we evaluate and compare the classification accuracy, precision, recall, and F1 scores of five different machine learning methods using a primary dataset (500 patients from Dhaka Medical College Hospital). Five different supervised machine learning techniques, including decision tree, random forest, logistic regression, naive bayes, and XGBoost, have been used to achieve optimal results on our dataset. Additionally, this study applied SHAP analysis to the XGBoost model to interpret the model's predictions and understand the impact of each feature on the model's output. We compared the accuracy with which several algorithms classified the data, as well as contrasted with other literature in this field. After final evaluation, this study found that XGBoost achieved the best model accuracy, which is 97%.

Treatment Strategy for Breast Benign Intraductal Papilloma: A Meta-Analysis.

Currently, the optimal treatment approach for breast benign intraductal papilloma (IDP) diagnosed via biopsy remains uncertain. There is ongoing debate regarding the feasibility of clinical follow-up and the criteria for selective surgical excision. This study aims to conduct a meta-analysis to determine the rate of upgrade from breast benign IDP and identify predictive factors associated with the conversion of benign IDP to high-risk lesions or carcinoma, which could guide healthcare practitioners in selecting the appropriate clinical treatment strategy. We conducted a comprehensive search across multiple databases (PubMed, Web Of Science, Cochrane Library, and Embase) for studies published between 2012 and 2023 that evaluated upgrade rates and predictive factors of breast benign IDP diagnosed via biopsy. In addition, we included studies that reported on the clinical follow-up of patients with breast benign IDP. In total, 32 studies comprising 7371 cases of biopsy-diagnosed breast benign IDP were included. Among these cases, 720 demonstrated an upgrade to high-risk lesions or carcinoma, resulting in an upgrade rate of 6.94% [95% confidence interval (CI): 3.0-8.0%]. A subgroup of 1713 patients was clinically followed up, demonstrating an average follow-up duration of 30.95 months. Among them, 26 cases experienced an upgrade to high-risk lesions or carcinoma, yielding an upgrade rate of 1.51% (95% CI 0.00-2.00). Furthermore, we identified nine predictive factors associated with the upgrading of breast benign IDP, which included age at diagnosis, personal history of breast cancer, family history of breast cancer, multiple IDPs, lesion size ≥ 10 mm, palpable mass, calcification, and the presence of mass and asymmetry in mammographic findings. Although the conversion rate of breast benign IDP to high-risk lesions or carcinoma is relatively low, timely identification of predictive factors associated with benign IDP upgrades may help selecting the optimal clinical treatment strategy, such as surgery for patients with benign IDP presenting one or more predictive factors, while clinical follow-up for those without specific risk factors.

Juvenile Papillomatosis of the Breast: a Report of Two Cases with Review of the literature.

Background: Juvenile papillomatosis (JP) of the breast is a rare and benign proliferative disorder affecting young women. The affected patients tend to have an increased risk of breast cancer development during follow-up. Objective: This article aims to highlight a rare entity of breast disease, that harbor risk of breast cancer. Case Presentation: Here, we present 2 cases of JP in young females; the first case is a 13 year-old presented with spontaneous nipple discharge, while the other patient is a 24 year-old presented with a right breast lump. Both patients had a total excision of the breast lesions, revealing JP at histology. Discussion: Juvenile Papillomatosis is considered a clinicopathological entity and is usually misdiagnosed as fibroadenoma clinically and radiologically, which requires histological correlation. The histologic findings are well-defined (hyperplasia, papillomatosis, and multiple cysts with foamy histiocytes).The controversy in management between surgery and observation is because of insufficient knowledge about the direct relationship between JP and subsequent cancer. Conclusion: Considering the risk of developing breast cancer in JP, enrolling patients and their families in a close follow-up and surveillance program is crucial.

Assessment of breast cancer awareness among female pharmacy students at a university in Turkey.

BACKGROUND: Female breast cancer is the most frequently diagnosed cancer, and knowledge of breast cancer risk factors, and symptoms is crucial for early diagnosis and prevention. This study aims to evaluate breast cancer awareness among female students at a pharmacy faculty in Turkey. METHODS: A cross-sectional online survey study was conducted among female students at the Suleyman Demirel University Faculty of Pharmacy between 2 November and 17 November 2023, in Isparta, Turkey. RESULTS: This survey was answered by 237 (74.5%) female students. The median breast cancer risk factors score was 8 (IQR, 5-11), and the median breast cancer symptoms score was 5 (IQR, 2-8). Additionally, the breast cancer risk factors score was 46.16% (mean/max = 8.31/18, SD = 4.33) and the breast cancer symptom score was 58.5% (mean/max = 4.68/8, SD = 2.8). Few of the respondents (26.2%, and 20.3%, respectively) knew breast cancer risk factors such as late menopause, and no childbirth experience. Most respondents correctly answered symptoms of breast cancer, such as a painless and palpable breast lump, indrawing of the nipple, and sudden changes in breast shape (76.8%,44.3%, and 67.1% respectively). The students' sources of information were medical websites (29.5%), social media (27%), physicians (22.8%), friends & family (14.8%), and pharmacists (5.9%). CONCLUSIONS: This study showed that students' knowledge of breast cancer risk factors was poor, but their knowledge of breast cancer symptoms was acceptable. Breast cancer awareness courses should be included in faculties. Additionally, more attention should be given to different educational interventions such as social media, television, and brochure distribution.

Identification of miR-125a and miR-106b signature as a potential diagnostic biomarker in breast cancer tissues.

MicroRNAs (miRNAs) have essential roles in the etiology of breast cancer and are regarded as possible markers in this malignancy. In order to find new markers for breast cancer, the current study has measured expression level of four miRNAs, namely miR-125a, miR-106b, miR-96 and miR-92a-3p in the paired breast samples. Expression levels of miR-125a and miR-106b were higher in tumoral tissues compared with control tissues (Expression ratios (95% CI) = 4.01 (1.96-8.19) and 3.9 (1.95-7.81); P values = 0.0005 and 0.0003, respectively). miR-106b and miR-125a differentiated between malignant and non-malignant tissues with AUC values of 0.7 and 0.67, respectively. We detected association between expression of miR-106b and clinical stage (P = 0.03), in a way that its expression was the lowest in the advanced stages. Finally, significant relationships were found between miR-96 and miR-125a in both tumoral and non-tumoral specimens (ρ = 0.76 and 0.69, respectively). This nonparametric measure of rank correlation also showed relationship between miR-106b and miR-96 in both sets of samples (ρ = 0.63 and 0.61, respectively). Cumulatively, the assessed miRNAs, particularly miR-125a and miR-106b are putative targets for further expression and functional assays in breast cancer.

UTRN as a potential biomarker in breast cancer: a comprehensive bioinformatics and in vitro study.

Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer's development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN's pivotal role in tamoxifen resistance. Furthermore, the Kruskal-Wallis rank test indicated UTRN's potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN's close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN's role in breast cancer's prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

Population-based BRCA germline mutation screening in the Han Chinese identifies individuals at risk of BRCA mutation-related cancer: experience from a clinical diagnostic center from greater Shanghai area.

BACKGROUND: Deleterious BRCA1/2 (BRCA) mutation raises the risk for BRCA mutation-related malignancies, including breast, ovarian, prostate, and pancreatic cancer. Germline variation of BRCA exhibits substantial ethnical diversity. However, there is limited research on the Chinese Han population, constraining the development of strategies for BRCA mutation screening in this large ethnic group. METHODS: We profile the BRCA mutational spectrum, including single nucleotide variation, insertion/deletion, and large genomic rearrangements in 2,080 apparently healthy Chinese Han individuals and 522 patients with BRCA mutation-related cancer, to determine the BRCA genetic background of the Chinese Han population, especially of the East Han. Incident cancer events were monitored in 1,005 participants from the healthy group, comprising 11 BRCA pathogenic/likely pathogenic (PLP) variant carriers and 994 PLP-free individuals, including 3 LGR carriers. RESULTS: Healthy Chinese Han individuals demonstrated a distinct BRCA mutational spectrum compared to cancer patients, with a 0.53% (1 in 189) prevalence of pathogenic/likely pathogenic (PLP) variant, alongside a 3 in 2,080 occurrence of LGR. BRCA1 c. 5470_5477del demonstrated high prevalence (0.44%) in the North Han Chinese and penetrance for breast cancer. None of the 3 LGR carriers developed cancer during the follow-up. We calculated a relative risk of 135.55 (95% CI 25.07 to 732.88) for the development of BRCA mutation-related cancers in the BRCA PLP variant carriers (mean age 42.91 years, median follow-up 10 months) compared to PLP-free individuals (mean age 48.47 years, median follow-up 16 months). CONCLUSION: The unique BRCA mutational profile in the Chinese Han highlights the potential for standardized population-based BRCA variant screening to enhance BRCA mutation-related cancer prevention and treatment.

Breast Cancer Screening Recommendations for Transgender Patients: A Review.

Shifting societal attitudes trending toward increased acceptance of transgender people has contributed to a growth in the population of individuals who openly identify as transgender as well as an increase in utilization of gender-affirming surgeries. Therefore, health care providers should work toward increasing their knowledge with respect to the health care needs of the transgender population, particularly given that these individuals often face discrimination in the health care system. Moreover, transgender breast cancer screening rates lag behind breast cancer screening rates for cisgender individuals. We attempt to clarify important terminology about the transgender population and introduce the concept of equity-centered language. We review current transgender breast cancer screening guidelines by using PubMed, Google Scholar, and Google with search terms that included transgender breast cancer guidelines, transgender breast cancer screening guidelines, and transgender cancer screening guidelines. Searches were not filtered based on year of publication, language of publication, or geographic location. We compare the various guidelines as they pertain to both transgender men and transgender women and offer special considerations for upholding inclusivity in the health care field. An easy-to-reference summary of the current transgender breast cancer screening guidelines and the major points of this article were compiled into an original infographic that health care providers can reference to ensure that appropriate care is being offered.

[Non-primary solid malignancies of breast in needle core biopsy: a clinicopathological analysis of 23 cases].

Objective: To investigate the accurate diagnosis and differential diagnosis of non-primary solid malignant tumors in breast needle core biopsy. Methods: Twenty-three cases of breast, axilla or neck lymph nodes pathologically diagnosed as non-primary solid malignant tumors were collected at the First Affiliated Hospital of Nanjing Medical University, Nanjing, China from January 2013 to March 2023. The differential diagnoses and diagnostic features were analyzed, based on combining clinical data, histology, and expression characteristics of biomarkers. Results: All patients were female, with age ranging from 29 to 75 years (average 56 years). The average time from the diagnosis of primary tumor to the current diagnosis was 21 months (0 to 204 months).The primary sites included the ovary (9 cases), the lung (5 cases), the gastrointestinal tract (4 cases), the pancreas, intrahepatic bile duct, thyroid gland, nasal cavity and forearm skin (1 case each). No carcinoma in situ was found in any of the cases. The morphological differences were significant among the tumors, but similar to the primary tumors. The tumors of neuroendocrine and female reproductive tract had great morphological and immunophenotypic overlaps with breast cancer. Metastatic lung cancer cells showed obvious atypia and tumor giant cells. The morphology and immunophenotype of metastatic serous carcinoma of female reproductive system might resemble invasive micropapillary carcinoma of the breast. Metastatic adenocarcinoma of the gastrointestinal tract often had features of mucous secretion. Metastatic neuroendocrine tumors were bland in appearance and morphologically similar to solid papillary carcinoma of breast, but negative for ER. TRPS1 was mostly negative (18/23) and variably positive in ovarian (4/9) and intrahepatic bile duct (1/1) tumors. Conclusions: The diagnosis of breast needle core biopsy specimen should be combined with clinical history, imaging study, and careful examination of histological features, such as presence of in situ component, morphological similarity between the primary and metastatic tumors, and using appropriate markers to differentiate the primary from metastatic tumors.

Development and validation of a nomogram for predicting lymph node metastasis in ductal carcinoma in situ with microinvasion: A SEER population-based study.

BACKGROUND: Ductal carcinoma in situ with microinvasion (DCIS-MI) is a special type of breast cancer. It is an invasive lesion less than 1.0 mm in size related to simple ductal carcinoma in situ (DCIS). Lymph node metastasis (LNM) in DCIS-MI often indicates a poor prognosis. Therefore, the management of lymph nodes plays a vital role in the treatment strategy of DCIS-MI. Since DCIS-MI is often diagnosed by postoperative paraffin section and immunohistochemical detection, to obtain the best clinical benefits for such patients, we aim to establish and verify a nomogram to predict the possibility of lymph node metastasis in DCIS-MI patients and help preoperative or intraoperative clinical decision-making. METHODS: A retrospective analysis of patients with DCIS-MI in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019 was performed. The study cohort was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The risk factors were determined by univariate and multivariate logistic regression analyses in the training cohort, and a nomogram was constructed. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram in the training set and validation set. An independent data cohort was obtained from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) for external validation. RESULTS: This study included 3951 female patients from SEER with DCIS-MI, including 244 patients with regional lymph node metastasis, accounting for 6.18% of the total. An independent test set of 323 patients from SJTU-BCDB was used for external validation. According to the multifactorial logistic regression analysis results, age at diagnosis, ethnicity, grade, and surgical modality were included in the prediction model. The areas under the ROC curves (AUCs) were 0.739 (95% CI: 0.702~0.775), 0.732 (95% CI: 0.675~0.788), and 0.707 (95%CI: 0.607-0.807) in the training, validation and external test groups, suggesting that the column line graphs had excellent differentiation. The calibration curves slope was close to 1, and the model's predicted values were in good agreement with the actual values. The DCA curves showed good clinical utility. CONCLUSION: In this study, we constructed accurate and practical columnar maps with some clinical benefit to predict the likelihood of lymph node metastasis in patients with postoperatively diagnosed DCIS-MI and provide a reference value for specifying treatment strategies.

The Impact of Health Inequities on Population-Based Breast Cancer Survival in a Colombian Population, 2008-2015.

OBJECTIVE: To obtain breast cancer survival estimates in Manizales, Colombia, considering socioeconomic level, health insurance regime and residential area, while adjusting for age, histology and stage at diagnosis. METHODS: Analytical cohort study based on breast cancer incident cases recorded by the Population-based Manizales Cancer Registry between 2008-2015. Patients were followed-up for 60 months. Cause-specific survival was calculated using the Kaplan-Meier method for variables of interest, with the Wilcoxon-Breslow-Gehan test for differences. Cox multivariate regression models were fitted. RESULTS: 856 breast cancer cases were included. The 5-year cause-specific survival for the entire cohort was 78.2%. It was higher in women with special/exception health insurance, high socioeconomic level, <50 years old, ductal carcinoma, and stages I and II. Residential area did not impact survival. In Cox models, the subsidized health insurance regime (HR: 4.87 vs contributory) and low socioeconomic level (HR: 2.45 vs high) were predictors of the hazard of death in women with breast cancer, adjusted for age, histology, stage and interactions age-stage and insurance-stage. A positive interaction (synergistic effect modification) between health insurance regime and stage regarding to survival was observed. CONCLUSION: Socioeconomic factors significantly contribute to the inequities in breast cancer survival, independent of the stage at diagnosis. This suggests the need for comprehensive interventions to remove barriers to accessing the health system. This research provides evidence of survival gaps mediated by certain social determinants of health and generates data on the overall performance of the Colombian health system.

[Comparative immunohistochemistry study of different antibodies clones for detection of breast cancer markers (estrogen receptor, progesterone receptor, HER2/neu, Ki-67)]. / Sravnitel'noe issledovanie antitel razlichnykh klonov dlya vyyavleniya markerov raka molochnoi zhelezy (retseptorov estrogenov, progesterona, HER2/neu, Ki-67) immunogistokhimicheskim metodom.

OBJECTIVE: A comparative study of detection of breast cancer markers (estrogen receptors, progesterone receptors, HER2/neu, Ki-67) by immunohistochemical method with antibodies produced by PrimeBioMed (Russia) and antibodies produced by Roche Ventana (USA). MATERIAL AND METHODS: Surgical specimens and biopsies from 37 patients with invasive breast cancer were used. Sections were stained with antibodies of clones ER SP1 and GM030, PR 1E2 and PBM-5B8, HER2/neu 4B5 and PBM-46A6, Ki-67 30-9 and GM010. RESULTS: There was a high positive and significant correlation between the immunohistochemistry results and antibodies of the clones ER-SP1 and GM030, PR1E2 and PBM-5B8, HER2/neu4B5 and PBM-46A6, Ki-67 30-9 and GM010. CONCLUSION: The study showed the possibility of using antibodies of clones GM030, HER2/neu 4B5, PBM-46A6, GM010 (PrimeBioMed) on the Ventana Bench Marck Ultra automatic immunostainer using the detection system UltraView Universal DAB Detection Kit.

Molecular subtyping improves breast cancer diagnosis in the Copenhagen Breast Cancer Genomics Study.

BACKGROUNDIntrinsic molecular subtypes define distinct biological breast cancers and can be used to further improve diagnosis and risk allocation.METHODSThe Copenhagen Breast Cancer Genomics Study (CBCGS) prospectively included women diagnosed with breast cancer at Rigshospitalet from 2014 to 2021. Eligible patients were females with a primary invasive breast cancer (T1c, if N0M0; otherwise, any T, any N, or any M stage) and no prior malignancy. All patients underwent molecular profiling with the CIT256 and PAM50 molecular profile.RESULTSIn the study period, 2,816 patients were included in the CBCGS. Molecular subtyping showed an increase in nonluminal (molecular-apocrine, luminal C, and Basal-like) as compared with luminal (luminal A, luminal B, and Normal-like) subtypes with increasing stage from I to IV. Across all stages, we found a significant difference in survival among subtypes; 91% of patients with LumA were alive at 5 years compared with 91% for LumB, 84% for LumC, 82% for mApo, and 80% for Basal-like. We identified 442 tumors (16%) that were discordant in subtype between CIT256 and IHC. Discordant subtype proved to be a risk factor of death among patients with IHC luminal breast cancer (hazard ratio [HR], 2.08; 95% CI, 1.51-2.86) in a multivariable Cox regression analysis. Discordance occurred more often among patients with N3, stage IV, or grade III disease.CONCLUSIONOur findings indicate that molecular subtypes are a predominant classification for survival. Assessment is particularly crucial for patients with IHC luminal breast cancer with known high-risk factors, since they are at an increased risk of harboring an aggressive molecular subtype.

Breast Cancer Prediction Based on Multiple Machine Learning Algorithms.

INTRODUCTION: The incidence of breast cancer has steadily risen over the years owing to changes in lifestyle and environment. Presently, breast cancer is one of the primary causes of cancer-related deaths among women, making it a crucial global public health concern. Thus, the creation of an automated diagnostic system for breast cancer bears great importance in the medical community. OBJECTIVES: This study analyses the Wisconsin breast cancer dataset and develops a machine learning algorithm for accurately classifying breast cancer as benign or malignant. METHODS: Our research is a retrospective study, and the main purpose is to develop a high-precision classification algorithm for benign and malignant breast cancer. To achieve this, we first preprocessed the dataset using standard techniques such as feature scaling and handling missing values. We assessed the normality of the data distribution initially, after which we opted for Spearman correlation analysis to examine the relationship between the feature subset data and the labeled data, considering the normality test results. We subsequently employed the Wilcoxon rank sum test to investigate the dissimilarities in distribution among various breast cancer feature data. We constructed the feature subset based on statistical results and trained 7 machine learning algorithms, specifically the decision tree, stochastic gradient descent algorithm, random forest algorithm, support vector machine algorithm, logistics algorithm, and AdaBoost algorithm. RESULTS: The results of the evaluation indicated that the AdaBoost-Logistic algorithm achieved an accuracy of 99.12%, outperforming the other 6 algorithms and previous techniques. CONCLUSION: The constructed AdaBoost-Logistic algorithm exhibits significant precision with the Wisconsin breast cancer dataset, achieving commendable classification performance for both benign and malignant breast cancer cases.

Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival.

BACKGROUND: Breast cancers exhibit considerable heterogeneity in their biology, immunology, and prognosis. Currently, no validated, serum protein-based tools are available to evaluate the prognosis of patients with early breast cancer. METHODS: The study population consisted of 521 early-stage breast cancer patients with a median follow-up of 8.9 years. Additionally, 61 patients with breast fibroadenoma or atypical ductal hyperplasia were included as controls. We used a proximity extension assay to measure the preoperative serum levels of 92 proteins associated with inflammatory and immune response processes. The invasive cancers were randomly split into discovery (n = 413) and validation (n = 108) cohorts for the statistical analyses. RESULTS: Using LASSO regression, we identified a nine-protein signature (CCL8, CCL23, CCL28, CSCL10, S100A12, IL10, IL10RB, STAMPB2, and TNFß) that predicted various survival endpoints more accurately than traditional prognostic factors. In the time-dependent analyses, the prognostic power of the model remained rather stable over time. We also developed and validated a 17-protein model with the potential to differentiate benign breast lesions from malignant lesions (Wilcoxon p < 2.2*10- 16; AUC 0.94). CONCLUSIONS: Inflammation and immunity-related serum proteins have the potential to rise above the classical prognostic factors of early-stage breast cancer. They may also help to distinguish benign from malignant breast lesions.

Immunohistochemical study of CD74 biomarker in normal and malignant breast tissues.

OBJECTIVE: Aim: To detect the role of CD74 expression in breast carcinoma as a predictive marker for identifying the biological behavior of malignancy in Iraqi women.. PATIENTS AND METHODS: Materials and Methods: The study used technique of immunohistochemistry for detection CD74 protein role in breast cancer, and its expression in breast cancer tissue samples. Samples were collected in Al-Najaf city in Iraq, from Al-Forat Al-Awsat Oncology Center. The study was achieved at the Laboratories of the Faculty of Science in the University of Kufa. Fifty samples of breast cancer tissue, and twenty controls benign tissue were included in the study. The study has investigated relationship between expression of biomarker with grade, age of patient and tumor size. RESULTS: Results: The study showed that the cytoplasmic expression of CD74 with more clear and intensive staining in the cytoplasm, and reported that CD74 positivity rate was 52%. A significant association between CD74 expression and grade and size of tumor, so CD74 can be considered as a biomarker for prediction of breast cancer in women. No association was found between CD74 expression and each of patients' age and node metastasis. CONCLUSION: Conclusions: The study represents an important step in our region because there are a few studies about this topic; more efforts are required to approve the function of this biomarker.

Breast mucosa-associated lymphoid tissue lymphoma: A case report and literature review.

BACKGROUND: Mucosa-associated lymphoid tissue (MALT) lymphoma, also known as extranodal marginal zone lymphoma, is more commonly detected in the stomach and rarely in the breast. Our study presented a clinical and pathological examination of a patient diagnosed with breast MALT lymphoma, supplemented with pertinent research, to offer guidance for the diagnosis and treatment of this condition. PEOPLE CONCERNS: The occurrence of breast MALT lymphoma has risen in the past decade, but its etiology, progression and treatment response are less well-studied. DIAGNOSIS: Breast MALT lymphoma was diagnosed by excisional biopsy and histopathology. INTERVENTIONS: Following breast MALT lymphoma diagnosis, the patient was transferred to the hematology department for further treatment, and she made the decision to continue observing. OUTCOMES: After 3 months of observation, the patient remained asymptomatic. CONCLUSION: Breast MALT lymphoma is an indolent disease with an asymptomatic presentation, There are no standardized treatment guidelines for breast MALT lymphoma, treatment must be tailored to the patient willingness to treat and the severity of the disease. Hence, in order to give patients a better chance of cure, more research is needed to explore its pathogenesis and more clinical trials are needed investigate the treatment of this disease.

Knowledge of risk factors and early detection methods toward breast cancer among healthcare workers in Kinshasa, Democratic Republic of the Congo.

BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women, and it typically presents late in developing countries like the Democratic Republic of the Congo (DRC), leading to higher mortality rates. Late detection at advanced stages of breast cancer can be attributed to the absence of appropriate screening programs and low levels of awareness. AIMS: To evaluate the level of BC knowledge among healthcare workers (HCWs) and identify determinants of good BC knowledge. METHODS AND RESULTS: An analytical cross-sectional survey was conducted from March 1 to 31, 2022 involving HCWs practicing in Kinshasa, DRC. Data were collected using a questionnaire administered through direct interviews. Bivariate and multivariate regression techniques were applied. The study interviewed 543 HCWs, with a median age of 35 years (interquartile range: 29-43). Of these, 61% had good BC knowledge, while 39% had poor BC knowledge. Multivariate analysis revealed that HCWs aged 50 years and over (adjusted odds ratio [aOR] = 2.3 [1.2-4.5]), female HCWs (aOR = 1.8 [1.1-2.4]), HCWs working in public healthcare facilities (aOR = 1.5 [1.1-2.5]), and HCWs who had received training on BC (aOR = 1.9; 95% CI: 1.5-3.3) were determinants of good BC knowledge. CONCLUSION: This study found that 61% of the surveyed HCWs had good BC knowledge. However, there is still room for improvement in terms of knowledge dissemination. Therefore, it is important to implement continuing medical education programs that focus on raising awareness and improving BC knowledge among HCWs.

Physical health-related quality of life trajectories over two years following breast cancer diagnosis in older women: a secondary analysis.

PURPOSE: To identify distinct trajectories of physical health-related quality of life (HRQoL) in older women over the first two years following breast cancer diagnosis, and to examine characteristics associated with trajectory group membership. METHODS: A secondary analysis of a longitudinal study of women diagnosed with stage I-III breast cancer who completed surveys within eight months of diagnosis and six, twelve, and eighteen months later that focuses on a subset of women aged ≥ 65 years (N = 145).Physical HRQoL was assessed using the Physical Component Score (PCS) of the SF-36 Health Survey. Finite mixture modeling identified distinct PCS trajectories. Multivariable logistic regression identified variables predictive of low PCS group membership. RESULTS: Two distinct patterns of PCS trajectories were identified. The majority (58%) of women had PCS above the age-based SF-36 population norms and improved slightly over time. However, 42% of women had low PCS that remained low over time. In multivariable analyses, older age, difficulty paying for basics, greater number of medical comorbidities, and higher body mass index were associated with low PCS group membership. Cancer treatment and psychosocial variables were not significantly associated. CONCLUSION: A large subgroup of older women reported very low PCS that did not improve over time. Older age, obesity, multiple comorbidities, and lower socioeconomic status may be risk factors for poorer PCS in women with breast cancer. Incorporating routine comprehensive geriatric assessments that screen for these factors may help providers identify older women at risk for poorer physical HRQoL post breast cancer treatment.