Fei Ge

Background: Breast metastasis from high-grade serous ovarian carcinoma is rare, and its coexistence with a synchronous primary breast carcinoma is exceptionally uncommon. Distinguishing metastatic ovarian carcinoma from primary breast carcinoma is clinically important because treatment strategies and prognosis differ substantially. Case presentation: We report a 48-year-old premenopausal woman who presented with pleural effusion, abdominal distension, bilateral adnexal masses, multiple breast nodules, and systemic lymphadenopathy. Pathological examination of the pelvic lesion supported high-grade serous carcinoma, whereas breast biopsy demonstrated two morphologically distinct adenocarcinoma components. Immunohistochemical profiling, including breast-lineage markers and Müllerian/ovarian markers, supported the coexistence of primary breast invasive carcinoma and metastatic ovarian carcinoma involving the breast. Intervention and outcome: The patient was diagnosed with FIGO stage IVB high-grade serous ovarian carcinoma with breast, pleural, peritoneal, and lymph node involvement, synchronous with primary breast carcinoma. She received neoadjuvant paclitaxel plus carboplatin and achieved a partial response, followed by interval cytoreductive surgery, additional chemotherapy combined with bevacizumab, breast tumor excision, and maintenance therapy with fluzoparib plus bevacizumab. At the last follow-up on December 20, 2025, no evidence of disease progression was observed. Conclusion: This case highlights the diagnostic difficulty of breast lesions in patients with ovarian carcinoma. Morphology combined with an appropriate immunohistochemical panel is essential for distinguishing primary breast carcinoma from metastatic ovarian carcinoma. Multidisciplinary evaluation and genetic assessment should be considered in similar cases.

Fat mass index (FMI) reflects adiposity normalized for height and may provide information beyond body mass index. Evidence on its relationship with depressive symptoms in U.S. adults remains limited. This cross-sectional study used data from adults participating in National Health and Nutrition Examination Survey 2011 to 2016. Fat mass index was calculated from dual-energy X-ray absorptiometry-derived fat mass divided by height squared. Depressive symptoms were defined using the Patient Health Questionnaire-9. Survey-weighted logistic regression, restricted cubic spline analysis, subgroup analyses, and machine-learning models were applied to evaluate the association and predictive performance. The final analysis included 7273 participants. After full adjustment, FMI was positively associated with depressive symptoms, with an odds ratio (OR) of 1.05 for each 1-unit increment (95% confidence interval [CI]: 1.03–1.08). In the quartile-based analysis, participants in Q4 showed greater odds of depressive symptoms compared with those in Q1 (OR = 1.50, 95% CI: 1.12–2.01). Restricted cubic spline analysis suggested an approximately linear positive association. In exploratory prediction models, FMI showed a higher AUC than body mass index, although the overall discrimination remained moderate. Higher FMI was associated with a higher prevalence of depressive symptoms among U.S. adults. FMI may serve as a useful adiposity-related indicator in epidemiological research, but prospective studies are needed before clinical predictive use can be recommended.

Breast carcinoma (BC) is a significant oncological issue, categorized based on estrogen receptor (ER) status into ER-positive and ER-negative types. The ER-positive variant relies on hormonal signaling, whereas the ER-negative form is characterized by increased aggressiveness. There exists a potential interplay between plasma metabolites and immune effectors that may influence BC susceptibility, although the underlying mechanisms remain largely undefined. This study employs Mendelian randomization (MR) to elucidate the causal pathways through which plasma metabolites affect both ER-positive and ER-negative BC susceptibility via immune mediators. In the context of ER-positive BC, sphingolipid metabolites (e.g., Sphingomyelin [d18:1/17:0] concentrations, odds ratio [OR] = 1.299, 95% confidence interval [CI]: 1.140–1.480) exhibited positive associations, whereas bile acid metabolites (e.g., Glycochenodeoxycholate 3-sulfate concentrations, OR = 0.876, 95% CI: 0.818–0.938) displayed negative correlations; immune phenotypes such as CD8br % leukocyte (OR = 1.165, 95% CI: 1.005–1.351) were positively linked. For ER-negative BC, the phosphate-to-tryptophan ratio (OR = 1.371, 95% CI: 1.047–1.796) showed a positive correlation, while indolepropionate (OR = 0.762, 95% CI: 0.647–0.896) had an inverse relationship; CD28 on CD39 + CD8br (OR = 1.052, 95% CI: 1.016–1.090) demonstrated a positive association. Mediation analyses revealed pathways: In ER-positive BC, 2R,3R-dihydroxybutyrate was mediated through EM DN (CD4−CD8−) %T cell (intermediation fraction 23.4%), and Sphingomyelin via CD38 on transitional cells (7.41%); in ER-negative BC, Dihomo-linoleoylcarnitine was mediated through human leukocyte antigen-DR on CD14+ CD16+ monocytes (9.98%), and homocitrulline through human leukocyte antigen-DR on plasmacytoid dendritic cells (12.7%). Plasma metabolites significantly influence susceptibility to different BC variants by modifying immune effector functions. This study provides genetic evidence supporting interventions targeting the metabolic-immune interface to improve prevention and management strategies. Utilizing publicly available genome-wide association study datasets, we examined 1440 plasma metabolites (identifiers GCST90199621 to GCST90201020), 731 immune phenotypes (ebi-a-GCST90001391 to ebi-a-GCST90002121), and the FinnGen R12 BC cohorts. Instrumental variables were selected based on criteria of P < 5 × 10 ⁻⁸ /10 ⁻⁷ , r ² < 0.001, and F-statistic > 10. We employed bidirectional two-sample MR, primarily using inverse-variance weighted methods, supplemented by MR-Egger and other techniques, to assess causal relationships and intermediary roles.

We propose using Mendelian randomization analysis on GWAS data and MetaboAnalyst to model gut microbiota, metabolic pathways, blood metabolites, and cancer risk. We examined 473 gut microbiota, 205 pathways, 1400 metabolites, and 8 cancers. Results were validated through bidirectional two-sample Mendelian Randomization (MR), heterogeneity tests, and pathway enrichment, leading to a mediation pathway model. We identified 129 gut microbiota, 57 pathways, and 463 metabolites linked to cancer, and 34 significant plasma pathways. 15 microbiota, 8 pathways, and 58 metabolites implicated in multiple cancers. Eight plasma metabolic pathways are involved in the development of multiple types of cancer. Through Multivariate Mendelian Randomization (MVMR) and mediation analysis, we found 9 mediation pathways, offering novel targets and research directions for cancer pathogenesis and treatment.

Background: Epidemiological studies have observed an association between atrial fibrillation (AF) and breast cancer (BC). However, the underlying mechanisms linking these two conditions remain unclear. This study aims to systematically explore the genetic association between AF and BC.Methods: We utilized the largest available genome-wide association study (GWAS) datasets for European individuals, including summary data for AF (N = 1,030,836) and BC (N = 247,173). Multiple approaches were employed to systematically investigate the genetic relationship between AF and BC from the perspectives of pleiotropy and causality.Results: Global genetic analysis using LDSC and HDL revealed a genetic correlation between AF and BC (rg = 0.0435, P = 0.039). Mixer predicted genetic overlap between non-MHC regions of the two conditions (n = 125, rg = 0.05). Local genetic analyses using LAVA and GWAS-PW identified 22 regions with potential genetic sharing. Cross-trait meta-analysis by CPASSOC identified one novel pleiotropic SNP and 14 pleiotropic SNPs, which were subsequently annotated. Eight of these SNPs passed Bayesian colocalization tests, including one novel pleiotropic SNP. Further fine-mapping analysis identified a set of causal SNPs for each significant SNP. TWAS analyses using JTI and FOCUS models jointly identified 10 pleiotropic genes. Phenome-wide association study (PheWAS) of novel pleiotropic SNPs identified two eQTLs (PELO, ITGA1). Gene-based PheWAS results showed strong associations with BMI, height, and educational attainment. PCGA methods combining GTEx V8 tissue data and single-cell RNA data identified 16 co-enriched tissue types (including cardiovascular, reproductive, and digestive systems) and 5 cell types (including macrophages and smooth muscle cells). Finally, univariable and multivariable bidirectional Mendelian randomization analyses excluded a causal relationship between AF and BC.Conclusion: This study systematically investigated the shared genetic overlap between AF and BC. Several pleiotropic SNPs and genes were identified, and co-enriched tissue and cell types were revealed. The findings highlight common mechanisms from a genetic perspective rather than a causal relationship. This study provides new insights into the AF-BC association and suggests potential experimental targets and directions for future research. Additionally, the results underscore the importance of monitoring the potential risk of one disease in patients diagnosed with the other.

Breast cancer (BC) is a malignant tumor, that damages the physical health of female patients. It is crucial to develop new treatment strategies for BC, as this disease significantly affects the quality of life of women in both developing and developed countries, despite the existence of effective treatment options to reduce mortality. Recently, several researchers have been studying circular RNAs (circRNAs) in BC due to their stability and sponge function. In the present study, a new circRNA, hsa_circ_0001508, was discovered using Gene Chip's prediction. This gene is important because it is novel in BC. However, due to financial constraints, the study was designed as a pilot study for future research. The present study included several common biomedical experimental techniques, such as reverse transcription‑quantitative PCR, flow cytometry, cell counting, cell invasion, wound healing assay and western blotting. It also involves the use of DNA microarray (gene chip) and prediction of microRNA and mRNA interactions using bioinformatics tools such as TargetScan. The findings revealed that hsa_circ_0001508 exhibits carcinogenic properties that facilitate the progression of BC. Furthermore, potential binding sites were identified as crucial areas for future investigation.

Background: There may be potential associations between various pathogens, antibody immune responses, and breast cancer (BC), but the specific mechanisms and causal relationships remain unclear. Methods: First, multiple Mendelian randomization (MR) methods were used for univariable MR analysis to explore potential causal relationships between 34 antibody immune responses (related to 12 pathogens), 46 antibody immune responses (related to 13 pathogens), antibody responses post-COVID-19 vaccination, 731 immune cell types, and various BC subtypes (including overall BC, ER-positive, ER-negative, Luminal A, Luminal B, Luminal B HER2-negative, HER2-positive, and triple-negative BC). The primary results were then subjected to reverse MR analysis, heterogeneity testing using Cochran’s Q, and horizontal pleiotropy testing. Robust findings were further used to design mediation pathways involving antibody immune responses, immune cells, and BC. After adjusting the effect estimates using multivariable MR (MVMR), a two-step mediation analysis was conducted to explore mediation pathways and mediation proportions. Finally, linkage disequilibrium score regression (LDSC) was applied to analyze the genetic correlation between phenotypes along mediation pathways, and cross-phenotype association analysis (CPASSOC) was performed to identify pleiotropic SNPs among three phenotypes along these pathways. Bayesian colocalization tests were conducted on pleiotropic SNPs using the multiple-trait-coloc (moloc). Results: We identified potential causal relationships between 15 antibody immune responses to 8 pathogens (Hepatitis B virus, Herpes Simplex Virus 2, Human Herpesvirus 6, Polyomavirus 2, BK polyomavirus, Cytomegalovirus, Helicobacter pylori, Chlamydia trachomatis), 250 immune cell phenotypes, and various BC subtypes. MVMR-adjusted mediation analysis revealed four potential mediation pathways. LDSC results showed no significant genetic correlation between phenotypes pairwise. CPASSOC analysis identified two potential mediation pathways with common pleiotropic SNPs (rs12121677, rs281378, rs2894250). However, none of these SNPs passed the Bayesian colocalization test by moloc. These results excluded horizontal pleiotropy, stabilizing MR analysis results. Conclusion: This study utilized MR methods to analyze potential causal relationships between various antibody immune responses, immune cell types, and BC subtypes, identifying four potential regulatory mediation pathways. The findings of this study offer potential targets and research directions for virus-related and immunotherapy-related studies, providing a certain level of theoretical support. However, limitations such as GWAS sample size constraints and unclear specific pathophysiological mechanisms need further improvement and validation in future studies.

Background: Breast cancer-related lymphedema (BCRL) frequently occurs after axillary lymph node dissection and remains incurable even with lymphaticovenular anastomosis. Exercise interventions have emerged as a potential non-pharmacological management approach. However, standardized exercise recommendations tailored to BCRL patients are lacking.Purpose: This study evaluated the impact of high and low compliance exercise interventions, aligned with ACSM recommendations, on quality of life (QOL), shoulder range of motion (ROM), and arm volume in BCRL patients. It further aimed to determine the optimal exercise dosage, assessed via the FITT (frequency, intensity, time, type) principle, that maximizes health benefits for BCRL patients.Methods: Adhering to the PRISMA guidelines for systematic reviews and meta-analyses, we conducted a comprehensive literature search in various databases, including PubMed, Embase, Cochrane Library, and Web of Science, encompassing the period from the inception of these databases to December 2023. We extracted data on exercise form, frequency, intensity, duration, repetitions, and sets from the identified studies. Subsequently, a meta-analysis and review were conducted. The exercise interventions were evaluated based on ACSM recommendations and categorized as either high or low compliance with ACSM standards. Fixed or random effects models were employed to compare outcomes across study subgroups with comparable results. Additionally, funnel plot analyses, sensitivity analyses, and Egger’s and Begg’s tests were conducted to evaluate the potential for bias.Results: 15 studies encompassing 863 patients with BCRL were analyzed. Eleven studies exhibited high ACSM compliance, while four demonstrated low ACSM compliance. Regarding QOL, the overall standard mean difference (SMD) was 0.13 (95% CI: −1.07, 1.33). Specifically, the SMD for the high-adherence subgroup was 0.91 (95% CI: 0.33, 1.49; p = 0.002). For ROM, the overall SMD was 1.21 (95% CI: −0.19, 2.61). For arm volume, the overall SMD was −0.06 (95% CI: −0.22, 0.10). QOL results differed significantly in the high-adherence subgroup, whereas no significant effect on ROM or arm volume was observed.Conclusion: The study revealed significant QOL improvements in patients with high ACSM compliance, contrasted with those with low compliance. Conversely, no notable changes in ROM or arm volume were observed. Notably, the high adherence group tended to show better ROM during exercise and stable arm volume. Future research is needed to validate these findings.

Immune checkpoint inhibitors (ICIs) have become extensively utilized in the early-stage treatment of various cancers, offering additional therapeutic possibilities for patients with advanced cancer. However, certain patient populations are susceptible to experiencing toxic adverse effects from ICIs, such as thyrotoxicosis, rashes, among others. Specifically, ICIDM, induced by immune checkpoint inhibitors, exhibits characteristics similar to insulin-dependent diabetes mellitus (Type 1 Diabetes Mellitus, T1DM). ICIDM is characterized by a rapid onset and may coincide with severe ketoacidosis. Despite a favorable response to insulin therapy, patients typically require lifelong insulin dependence. After discussing the autoimmune adverse effects and the specifics of ICIs-induced diabetes mellitus (ICIDM), it is important to note that certain patient populations are particularly susceptible to experiencing toxic adverse effects from ICIs. Specifically, ICIDM, which is triggered by immune checkpoint inhibitors, mirrors the characteristics of insulin-dependent diabetes mellitus (Type 1 Diabetes Mellitus, T1DM). This article conducts an in-depth analysis of the literature to explore the pathogenesis, disease progression, and treatment strategies applicable to diabetes induced by immune checkpoint inhibitors (ICIDM).