Search Results (6)

Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies. Full article

Background: This research sought to screen potential biomarkers in diagnosing breast diseases and elucidating their immune-related mechanisms. Methods: Three datasets were attained from the Gene Expression Omnibus (GEO) database. LIMMA package and weighted gene co-expression network analysis (WGCNA) were used to ascertain differentially expressed genes (DEGs) and key modules in benign breast disease (BBD) and breast cancer (BC). The intersecting genes underwent functional enrichment analysis. Three machine learning (ML) methods (encompassing LASSO regression, random forest, and support vector machine recursive feature elimination (SVM-RFE)) were implemented to select core genes. The diagnostic performance of the core genes was evaluated by comparing their expression levels, plotting receiver operating characteristic (ROC) curves, and constructing a Nomogram. The TCGA-BRCA dataset was used to estimate the prognostic capability of the core genes among individuals with BC. Finally, the IC infiltration was ascertained utilizing the CIBERSORT algorithm. Results: In total, 2579 DEGs were identified in BBD. WGCNA exhibited that the 1652 genes in green and pink modules were strongly correlated with BBD. In BC, 2742 DEGs were identified. The turquoise and red modules contained 7286 genes exhibiting strong correlations with BC. After intersecting, 41 common genes were obtained, which were predominantly enriched in immune and inflammation regulation pathways. Through integrated screening with three ML algorithms, Arrestin Domain Containing 1 (ARRDC1) and ATPase Sarcoplasmic/Endoplasmic Reticulum Ca²⁺ Transporting 2 (ATP2A2) were identified as core genes. The ROC curve exhibited that the AUC for the two genes was greater than 0.8. The calibration curve of the nomogram signified a strong alignment between the anticipated risk and detected results. Survival analysis in TCGA-BRCA showed that the high expression of the two genes exhibited a significantly positive association with unfavorable prognosis. Immune infiltration analysis further demonstrated the dysregulation of multiple immune cells in patient samples. Conclusions:ARRDC1 and ATP2A2 are strongly linked to BBD and BC. These findings might enhance our comprehension of the pathogenesis and progression of both BBD and BC, offering prospective biological biomarkers and therapeutic targets for clinical treatment. Full article

The human microbiome is a critical factor in health and disease. While its association with breast cancer (BC) has been increasingly studied, this review provides a dedicated synthesis of the microbiota’s role in benign breast diseases (BBDs)—a common yet microbiologically overlooked spectrum of conditions. The primary aim of this work is to consolidate the current understanding of the composition, origins, and functional mechanisms of the mammary gland (MG) microbiota specifically in the context of BBD and to evaluate its potential for novel diagnostic and therapeutic targets. We detail the distinct MG microbiota, formed via exogenous (e.g., cutaneous, translocation) and endogenous (e.g., enteromammary, lymphohematogenous) pathways, and its interaction with the host through estrogen metabolism, immunomodulation, and epigenetic modifications. This narrative review reveals unique dysbiotic patterns in BBD, characterized by distinct microbial signatures, such as the enrichment of Corynebacterium kroppenstedtii in granulomatous mastitis and the presence of Staphylococcus aureus in fibroadenomas and lactational mastitis. Furthermore, specific gut microbial profiles are identified in BBD patients, including an increased abundance of genera such as Clostridium and Faecalibacterium, alongside a decrease in Collinsella and Alistipes compared to healthy controls. These specific taxa represent compelling candidates for diagnostic biomarkers. We conclude that microbial dysbiosis is a significant component of BBD pathogenesis. A paradigm shift toward multi-omics approaches and mechanistic studies is now essential to translate these associations into clinical applications. Understanding the BBD-specific microbiome holds the promise of revolutionizing patient care through microbiota-based diagnostics for differentiating benign subtypes and novel, personalized therapeutic strategies aimed at restoring microbial homeostasis. Full article

The overexpression of HER2 in breast cancer (BC) can contribute to redox imbalance, which is related to damage and structural modification in many biomolecules. To the best of our knowledge, this is the first study that has investigated the infrared spectrum wavenumbers obtained by ATR-FTIR and their relationship with the levels of redox status markers such as reduced glutathione, superoxide dismutase (SOD), catalase, Ferric Reducing Antioxidant Power (FRAP), and protein carbonyl among women with HER2+ BC, HER2− BC, and benign breast disease (BBD). The study was conducted with 25 women, 17 of whom were diagnosed with BC (6 HER2+ and 11 HER2−) and 8 with BBD. Our results indicate HER2+ BC cases could be distinguished from HER2− BC and BBD cases by their serum’s antioxidant capacity [HER2+ BC vs. HER2− BC (AUC = 0.818; specificity = 81.82%; sensitivity = 66.67%); HER2+ BC vs. BBD (AUC = 0.875; specificity = 75%; sensitivity = 83.33%)]. The changes in biochemical terms that occur in serum as a result of the scarcity of antioxidants are related to a peculiar fingerprint in the infrared spectrum obtained by ATR-FTIR. In the serum of women with BBD, the SOD enzyme level is the highest, and this characteristic allowed us to distinguish them from HER2− BC. Finally, data regarding the serological antioxidant capacity of FRAP and the infrared spectrum by ATR-FTIR will allow us to assess biochemical changes that occur before clinical signs, indicating whether changes in therapy or interventions are necessary. Full article

Insulin levels, adipocytokines, and inflammatory mediators trigger benign breast disease (BBD) and breast cancer (BC). The relationship between serum adipocytokines levels, overweight-obesity, metabolic disturbs, and BC is unclear. Methods: To analyze the serum levels of the adipocytokines, insulin, and the HOMA IR in women without breast disease, with BBD or BC, and the role of these as risk factors for benign breast disease or breast cancer. Results: Adipsin values > 0.91 and visfatin levels > 1.18 ng/mL represent a risk factor to develop BBD in NBD lean women (OR = 18; and OR = 12). Data in overweight-obese women groups confirm the observation due to insulin levels > 2.6 mU/mL and HOMA IR > 0.78, with OR = 60.2 and 18, respectively; adipsin OR = 26.4, visfatin OR = 12. Breast cancer risk showed a similar behavior: Adipsin risk, adjusted by insulin and visfatin OR = 56 or HOMA IR and visfatin OR = 22.7. Conclusion: Adipose tissue is crucial for premalignant and malignant tissue transformation in women with overweight-obesity. The adipocyte–breast epithelium interaction could trigger a malignant transformation in a continuum, starting with BBD as premalignant disease, especially in overweight-obese women. Full article

Breast cancer (BCa) is the most common type of cancer affecting women worldwide. Some histological subtypes of benign breast disease (BBD) are considered risk factors for developing BCa. Single nucleotide polymorphisms (SNPs) in the genes encoding apolipoproteins A-I (APOA1) and B (APOB) have been associated with BCa in Tunisian, Chinese, and Taiwanese populations. The objective of this pilot study is to evaluate the possible contribution of APOA1 and APOB polymorphisms to BCa and BBD in the Mexican population. We analyzed the association of 4 SNPs in genes encoding apolipoproteins: rs670 and rs5069 in the APOA1 gene, and rs693 and rs1042031 in the APOB gene, by performing PCR-RFLP with DNA extracted from the biopsy tissue of Mexican women with BCa or BBD and whole blood samples obtained from the general population (GP). Our results showed an association between the CT + TT genotypes of the SNP rs5069 and BBD (p = 0.03201). In the A-T haplotype, the frequency of the SNPs rs670 and rs5069 differed significantly between the BBD group and the GP and BCa groups (p = 0.004111; p = 0.01303). In conclusion, the SNP rs5069 is associated with BBD but not with BCa in the Mexican population. Full article