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BACKGROUND: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has emerged as a new subtype of tumor, for which novel antibody-drug conjugates have shown beneficial effects. Assessment of HER2 requires several immunohistochemistry tests with an additional in situ hybridization test if a case is classified as HER2 2+. Therefore, novel cost-effective methods to speed up the HER2 assessment are highly desirable. METHODS: We used a self-supervised attention-based weakly supervised method to predict HER2-low directly from 1437 histopathological images from 1351 breast cancer patients. We built six distinct models to explore the ability of classifiers to distinguish between the HER2-negative, HER2-low, and HER2-high classes in different scenarios. The attention-based model was used to comprehend the decision-making process aimed at relevant tissue regions. RESULTS: Our results indicate that the effectiveness of classification models hinges on the consistency and dependability of assay-based tests for HER2, as the outcomes from these tests are utilized as the baseline truth for training our models. Through the use of explainable AI, we reveal histologic patterns associated with the HER2 subtypes. CONCLUSION: Our findings offer a demonstration of how deep learning technologies can be applied to identify HER2 subgroup statuses, potentially enriching the toolkit available for clinical decision-making in oncology.

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OBJECTIVE: Triple-negative breast cancer (TNBC) presents a clinical challenge as an aggressive tumor, correlated with unfavorable prognosis. Tumor-infiltrating lymphocytes (TILs) have garnered interest as a potential prognostic biomarker. However, the disparity in outcomes between varying TILs rates remains inadequately explored. METHODS: PubMed, Scopus, Web of Science, and Cochrane databases were searched for studies about the prognostic value of TILs in patients with TNBC receiving neoadjuvant chemotherapy. The hazard ratios (HRs) or odds ratios (ORs) were computed for binary endpoints, with 95% confidence intervals (CIs). RESULTS: Twenty-nine studies were included, involving a population of six thousand one hundred sixty-one (80.41%) with TNBC. The cut-off TILs value ranged from 10 to 60%, with 50% being the most related value. Compared with the low-TIL expression group, the disease-free survival (DFS) (HR 0.71; 95% CI 0.61-0.82; p < 0.00001) and overall survival (OS) (HR 0.76; 95% CI 0.63-0.90; p = 0.002) rates showed significant improvement with higher TIL infiltrations. In the subgroup analyses of the lymphocyte subtypes CD4 + and CD8 + , there was statistical significance favoring higher TILs rates in both subtypes, each associated with improved DFS (HR 0.48; 95% CI 0.33-0.71; p = 0.0002) and OS (HR 0.53; 95% CI 0.36-0.78; p = 0.001), regardless of which cell subtype was predominantly infiltrated. The complete pathological response analysis showed better rates for the higher TIL group than the control for both the TIL (OR 1.29; 95% CI 1.13-1.48; p = 0.0003) and Ki-67 (OR 2.74; 95% CI 2.01-3.73; p < 0.00001) analyses. CONCLUSION: Higher expressions of TILs in patients with TNBC were associated with improved significantly DFS, OS, and pCR outcomes.

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Breast cancer is the most common cancer in women and the leading cause of female deaths by cancer in the world worldwide. Hence, understanding the molecular mechanisms associated with breast cancer development and progression, including drug resistance and breast cancer metastasis, is essential for achieving the best management of breast cancer patients. Cancer-related long noncoding RNAs have been shown to be involved in the regulation of each stage of breast cancer progression. Additionally, exosomes are extracellular microvesicles that are central to intercellular communication and play an important role in tumorigenesis. Exosomes can be released from primary tumor cells into the bloodstream and transmit cellular signals to distant body sites. In this work, we review the findings regarding the cellular mechanisms regulated by exosomal lncRNAs that are essentials to chemoresistance development and metastasis of breast cancer. Likewise, we evaluate the outcomes of the potential clinical use of exosomal lncRNAs as breast cancer biomarkers to achieve personalized management of the patients. This finding highlights the importance of transcriptomic analysis of exosomal lncRNAs to understand the breast cancer tumorigenesis as well as to improve the clinical tests available for this disease.

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Gastric cancer (GC) is the fourth most deadly cancer globally. The adducin 1 (ADD1) protein is involved in oncogenic signal transduction pathways in several types of cancer, and the rs4961 variant (c.1378 G>T, p.Gly460Trp) of the ADD1 gene is associated with salt-sensitive hypertension, renal cell cancer and breast cancer susceptibility; however, it has not been investigated in GC. The aim of the present study was to evaluate the association between the rs4961 variant and the development of GC and preneoplastic gastric lesions (PGLs) in a population from western Mexico. A total of 225 individuals who underwent an endoscopy were evaluated, of which 71 patients had histopathologically diagnosed GC and 53 patients had PGLs, with 101 patients used as controls. The rs4961 variant was genotyped by using PCR and DNA sequencing. The frequency of the mutated homozygous genotype (TT) of the rs4961 variant was <10% in the three evaluated groups, and the frequency of the minor allele (T) was <21% in the GC, PGL and control groups. Genotypic and allelic frequencies were similarly distributed in all of the studied groups (P>0.05). In summary, in the study population, the rs4961 variant was not associated with GC risk; however, its role in other populations and in other types of cancer is worthy of future research.

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Background: Extracellular vesicles (EVs), ubiquitously released by blood cells, facilitate intercellular communication. In cancer, tumor-derived EVs profoundly affect the microenvironment, promoting tumor progression and raising the risk of recurrence. These EVs contain miRNAs (EV-miRNAs), promising cancer biomarkers. Characterizing plasma EVs and identifying EV-miRNAs associated with breast cancer recurrence are crucial aspects of cancer research since they allow us to discover new biomarkers that are effective for understanding tumor biology and for being used for early detection, disease monitoring, or approaches to personalized medicine. This study aimed to characterize plasma EVs in breast cancer (BC) patients and identify EV-miRNAs associated with BC recurrence. Methods: This retrospective observational study included 24 BC patients divided into recurrence (n= 11) and non-recurrence (n= 13) groups. Plasma EVs were isolated and characterized. Total RNA from EVs was analyzed for miRNA expression using NanoString's nCounter® miRNA Expression Assays panel. MicroRNA target prediction used mirDIP, and pathway interactions were assessed via Reactome. Results: A stronger presence of circulating EVs was found to be linked with a less favorable prognosis (p = 0.0062). We discovered a distinct signature of EV-miRNAs, notably including miR-19a-3p and miR-130b-3p, which are significantly associated with breast cancer recurrence. Furthermore, miR-19a-3p and miR-130b-3p were implicated in the regulation of PTEN and MDM4, potentially contributing to breast cancer progression.A notable association emerged, indicating a high concentration of circulating EVs predicts poor prognosis (p = 0.0062). Our study found a distinct EV-miRNA signature involving miR-19a-3p and miR-130b-3p, strongly associated with disease recurrence. We also presented compelling evidence for their regulatory roles in PTEN and MDM4 genes, contributing to BC development. Conclusion: This study revealed that increased plasma EV concentration is associated with BC recurrence. The prognostic significance of EVs is closely tied to the unique expression profiles of miR-19a-3p and miR-130b-3p. These findings underscore the potential of EV-associated miRNAs as valuable indicators for BC recurrence, opening new avenues for diagnosis and treatment exploration.

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BACKGROUND: Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. METHODS: BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. RESULTS: Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. CONCLUSION: The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.

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Aim: Breast cancer and its metastases involve high mortality even with advances in chemotherapy. Solid lipid nanoparticles provide a platform for drug delivery, reducing side effects and treatment-induced bone loss. A solid nanoparticle containing doxorubicin was evaluated for its ability to prevent bone loss in a pre-clinical breast cancer model. Methods: We investigated the effects of SLNDox in an aggressive metastatic stage IV breast cancer model, which has some important features that are interesting for bone loss investigation. This study evaluates bone loss prevention potential from solid lipid nanoparticles containing doxorubicin breast cancer treatment, an evaluation of the attenuation of morphological changes in bone tissue caused by the treatment and the disease and an assessment of bone loss imaging using computed tomography and electron microscopy. Results: Chemotherapy-induced bone loss was also observed in tumor-free animals; a solid lipid nanoparticle containing doxorubicin prevented damage to the growth plate and to compact and cancellous bones in the femur of tumor-bearing and healthy animals. Conclusion: The association of solid lipid nanoparticles with chemotherapeutic drugs with proven efficacy promotes the prevention of serious consequences of chemotherapy, reducing tumor progression, increasing quality of life and improving prognosis and survival.

[Box: see text].

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Introduction: Conservative surgery is the gold standard for the treatment of single and small tumors and, combined with the concept of oncoplastic tumors, brings good aesthetic results while maintaining cancer safety. The objective was to comparatively analyze the degree of satisfaction of patients undergoing breast conserving surgery (BCS), with and without oncoplastic surgery (OPS) using level II OPS techniques. Methods: Review with a search in the databases MEDLINE (by PubMed), EMBASE, Clinical Trials, Scopus, Web of Science, BVS and Oppen gray. The meta-analysis of random effects was performed using the Der Simonian-Laird method considering the odds ratio (OR) with a 95% confidence interval (95% CI). Results: There was no statistically significant difference in the aesthetic outcome between women who underwent OPS and BCS (OR 0.90; 95% CI 0.62-1.30). The staging (OR 1.93; 95% CI 0.97-3.84; I 2 = 15.83%); tumor location [central (OR 1.28; 95% CI 0.06-27.49; I 2 = 17.63%); lower (OR 0.75; 95% CI 0.21-2.65; I 2 = 2.21%); superior (OR 0.67; 95% CI 0.26-1.74; I 2 = 0.00%] and tumor size (OR 8.73; 95% CI -11.82-29.28; I 2 = 93.18%) showed no association with the type of BCS performed, with or without OPS. The degree of satisfaction remains even in cases of extreme oncoplasty. Conclusion: The level of patient satisfaction in relation to BCS was similar to that of the group undergoing OPS, highlighting that OPS allows the patient's satisfaction rate to be maintained even in the case of large or multicentric tumors.

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BACKGROUND: Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2- breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative prognostic and predictive performance of different ROR classifiers in a real-world LA cohort. METHODS: The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2- patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers. RESULTS: Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk: 4.06-9.97) than the traditional classifiers Ki67 and Nottingham Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively). CONCLUSION: In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2- MPBCS cohort.

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Introduction: Breast cancer (BC) is the leading cause of death among women, primarily due to its potential for metastasis. As BC progresses, the extracellular matrix (ECM) produces more type-I collagen, resulting in increased stiffness. This alteration influences cellular behaviors such as migration, invasion, and metastasis. Specifically, cancer cells undergo changes in gene expression that initially promote an epithelial-to-mesenchymal transition (EMT) and subsequently, a transition from a mesenchymal to an amoeboid (MAT) migration mode. In this way, cancer cells can migrate more easily through the stiffer microenvironment. Despite their importance, understanding MATs remains challenging due to the difficulty of replicating in vitro the conditions for cell migration that are observed in vivo. Methods: To address this challenge, we developed a three-dimensional (3D) growth system that replicates the different matrix properties observed during the progression of a breast tumor. We used this model to study the migration and invasion of the Triple-Negative BC (TNBC) cell line MDA-MB-231, which is particularly subject to metastasis. Results: Our results indicate that denser collagen matrices present a reduction in porosity, collagen fiber size, and collagen fiber orientation, which are associated with the transition of cells to a rounder morphology with bleb-like protrusions. We quantified how this transition is associated with a more persistent migration, an enhanced invasion capacity, and a reduced secretion of matrix metalloproteinases. Discussion: Our findings suggest that the proposed 3D growth conditions (especially those with high collagen concentrations) mimic key features of MATs, providing a new platform to study the physiology of migratory transitions and their role in BC progression.