Breast Cancer Research最新文献

Background: HER2-positive breast cancer is a prevalent pathological subtype of breast cancer. Resistance to anti-HER2 targeted therapies remains a significant challenge in treatment. Understanding the role of HER2 in breast cancer progression is essential.

Methods: The proteomics analysis was used to explore the regulated proteins in patients with HER2-positive breast cancer. MTS, EdU staininig, flow cytometry and colony formation assays were used to cell proliferation and apoptosis. Protein expressions and interaction of CAND1 and HER2 were clarified by western blot, immunofluorescence and co-immunoprecipitation experiments. In vivo studies using nude mice demonstrated the role of CAND1 in HER2-positive breast cancer cell growth.

Results: An increase in CAND1 expression, which is associated with poor prognosis in patients with HER2-positive breast cancer. Functionally, CAND1-KD suppresses the growth of HER2-positive breast cancer cells by inducing cell cycle arrest and apoptosis. In vivo, CAND1-KD inhibits tumor growth in xenograft models. Mechanistically, CAND1 expression is positively correlated with HER2 protein levels in breast cancer tissues. CAND1 directly interacts with HER2, stabilizing its protein expression. The E3 ligase CUL7 promotes HER2 ubiquitination and is essential for the interaction between CAND1 and HER2. CAND1-KD enhances CUL7 neddylation, which activates its ligase activity and leads to HER2 ubiquitination. Importantly, HER2 overexpression reverses the proliferation inhibition caused by CAND1 loss both in vitro and in vivo.

Conclusion: In summary, this study highlights the critical role of CAND1 in regulating HER2 ubiquitination and suggests a potential therapeutic strategy for patients with HER2-positive breast cancer.

Background: In the U.S., poorer breast cancer survival in Black women relative to white women has persisted for over 30 years, with recent data showing a 38% higher mortality in Black women with breast cancer. Stage at diagnosis is the most powerful predictor of survival. However, despite rates of mammographic screening having become approximately equal in the two groups, Black women are more likely to be diagnosed at later stages. We examined whether perceived experiences of discrimination due to race in receipt of health care is associated with a late stage at diagnosis of breast cancer.

Methods: Nested within the prospective Black Women's Health Study (BWHS), this case-only study included 1,617 self-identified U.S. Black women diagnosed with a first invasive breast cancer in 2003 through 2022. Eligible cases had completed a BWHS questionnaire in 2003 in which participants were asked whether they received differential health care due to their race or insurance status. The primary outcome in the present research was stage at breast cancer diagnosis, obtained from medical records and cancer registry data. Odds ratios (OR) for the association of perceived racial discrimination in health care with later stage at diagnosis were estimated in logistic regression analyses, with each of stages II, III, and IV compared with stage I diagnosis.

Results: In multivariable analyses controlled for age, body mass index, socioeconomic factors, and mammographic screening, perceived racial discrimination in healthcare was associated with an increased odds of breast cancer diagnosis at stage IV versus stage I (OR = 2.10, 95% CI 1.15-3.83). The association was present even among women who reported having a mammogram in the two years before diagnosis. No associations were observed for stage II or III versus stage I.

Conclusions: The findings support reducing healthcare discrimination to alleviate the disproportionate burden of worse prognosis and survival experienced by Black women.

Background: While radiotherapy (RT) improves breast cancer survival outcomes, concerns persist regarding radiation-induced cardiovascular complications. We aimed to evaluate the incidence and risk of radiation-associated cardiovascular disease (CVD) among breast cancer survivors.

Methods: This population-based retrospective cohort study included 38,045 female breast cancer survivors in South Korea who survived at least 1 year following diagnosis between 2012 and 2019. Cumulative incidence of CVD was estimated using the cumulative incidence function accounting for competing risks. Hazard ratios (HRs) for radiation-associated CVD were calculated using cause-specific Cox proportional hazards models with adjustments for potential confounders.

Results: Among the study population, 67.8% received RT. The RT group was younger at diagnosis, had fewer distant-stage cancers, and lower prevalence of pre-existing cardiovascular conditions compared to the non-RT group. The 9-year cumulative incidence of overall CVD was 32.8%, with higher rates in the non-RT group. RT was not significantly associated with increased risk of overall heart disease (HR: 0.94; 95% CI 0.88-1.01) or specific subtypes. No significant differences were observed between RT techniques. While no significant interaction was observed between RT and chemotherapy for overall heart disease risk (p = 0.2641), a significant interaction was identified for heart failure (p = 0.0013); patients receiving both RT and chemotherapy exhibited an increased risk (HR: 1.31; 95% CI 1.03-1.65) compared to those receiving neither treatment.

Conclusions: RT was not significantly associated with increased overall CVD risk, nor were there significant differences based on RT technique or its combination with chemotherapy for most cardiac outcomes. However, combined RT and chemotherapy significantly elevated heart failure risk, suggesting a potential interaction effect. Given the relatively short follow-up period, cautious interpretation of these results is warranted.

Background: Mammographic density (MD) is a strong, heritable risk factor for breast cancer. To date, 55 independent MD-associated genetic loci have been identified through genome-wide association studies (GWASs) in women of European ancestry; however, no studies have been reported in Asian women.

Methods: To identify novel loci, we conducted genome-wide association studies (GWASs) of absolute dense, absolute nondense, and percentage area and volumetric densities, adjusting for age, body mass index (BMI), and ancestry-informative principal components, in a multi-ethnic cohort of 2,951 Asian women attending opportunistic mammography screening. We selected 175 novel loci that were associated with at least one MD phenotype at P < 5 × 10^- 6 for (a) replication in an independent set of 401 Asian breast cancer cases, using density measurements from the unaffected breasts, (b) evaluation in a GWAS meta-analysis of MD in 27,900 women of European ancestry and (c) evaluation with breast cancer risk in Asian women.

Results: Four of the 175 loci were replicated in women of Asian ancestry at P < 0.05, with directions of association that were consistent with those observed in the GWAS. The rs7018644 SNP at the 9p13.1 locus was the only loci replicated in both Asian and European cohorts. In addition, eight SNPs were also associated with breast cancer risk (P < 0.05) in a GWAS meta-analysis of Asian women.

Conclusion: This study identifies potential novel MD-associated loci in Asian women. Replication in a larger Asian study is needed to confirm these findings.

Background: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation, often face challenges due to densely packed nuclei, morphological variability, and inter-laboratory differences. Since Hematoxylin and Eosin (H&E) staining is routinely performed, accurately estimating Ki-67 from these slides could save resources by eliminating the need for additional immunohistochemical (IHC) staining. We developed and validated a transformer-based regression model to estimate Ki-67 expression directly from H&E-stained Whole Slide Images (WSIs).

Methods: We used seven public datasets to select optimal transformer-based architectures and hyperparameters. WSIs underwent preprocessing to filter poor-quality patches, with a classification model identifying gradable patches. Only gradable patches proceeded to Ki-67 quantification. Initially, a regression model was trained on IHC-stained patches using independently annotated datasets, bypassing segmentation methods. This model generated pseudo-labels for unlabeled IHC patches, which were then paired with corresponding H&E images, with a separate model trained using only these H&E patches. Both models were evaluated separately across 1153 H&E and 843 IHC-stained WSIs, employing metrics such as R².

Results: Our regression model had good predictive accuracy, with R² values exceeding 0.90 for quantifying positive cells, negative cells, and Ki-67 ratios. The classification model effectively distinguished gradable patches, achieving a near-perfect AUROC (~ 100%) across independent and unseen datasets. Cross-modality performance was robust, achieving R² values over 0.95 for positive and negative cell counts. Additionally, the model accurately captured the proliferation patterns from H&E-stained WSIs.

Conclusion: Our approach precisely quantifies Ki-67 expression and automates hotspot detection from WSIs, providing a scalable tool for digital pathology workflows. The cross-modality model potentially quantifies molecular expression from morphological features using H&E-stained WSIs.

Introduction: The prognostic implications of tumor-infiltrating lymphocytes (TILs) and their temporal changes (ΔTILs) during neoadjuvant chemotherapy (NAC) in hormone receptor-positive/ HER2-negative early breast cancer (HR+/HER2- eBC) remains clinically ambiguous. Our study investigates the association between TILs levels, longitudinal TILs evolution, and survival outcomes in a NAC-treated HR+/HER2- eBC cohort.

Methods: In this retrospective cohort analysis of 576 HR+/HER2- eBC patients (April 2011-December 2021), TILs were categorized as low (< 10%) or high (≥ 10%) using predefined thresholds. Multivariable Cox proportional hazards models evaluated invasive disease-free survival (iDFS) and overall survival (OS). ΔTILs patterns were analyzed in residual tumors.

Results: The cohort (median follow-up 68.1 months) comprised 393 TILs-low (68.2%) and 183 TILs-high (31.8%) tumors. Compared to TILs-low tumors, TILs-high tumors were associated with a higher Ki-67 index (≥ 20%) (P = 0.022), even though they were more frequently of smaller baseline size (< 3 cm) (P = 0.022). Elevated pre-NAC TILs independently predicted inferior iDFS (HR = 1.47, 95% CI 1.06-2.04, P = 0.021) and OS (HR = 1.64, 95% CI 1.11-2.43, P = 0.013). Post-NAC TILs escalation (low to high) conferred the worse prognosis versus sustained low TILs (iDFS: HR = 2.97, 95% CI 1.93-4.55, P < 0.001; OS: HR = 3.43, 95% CI 2.02-5.85, P < 0.001). Conversely, TILs reduction (high to low) correlated with improved survival over persistent high TILs (iDFS: HR = 0.51, 95% CI 0.30-0.86, P = 0.012; OS: HR = 0.54, 95%CI 0.31-0.96, P = 0.034).

Conclusion: In HR+/HER2- eBC, elevated pre-treatment TILs are independently associated with inferior survival outcomes, while chemotherapy-induced TILs reduction in residual disease correlates with significant prognostic improvement.

Objectives: To identify molecular clusters and establish a scoring model based on mechanical stimulus-related genes (MSRGs) for predicting the prognosis of breast cancer patients and understanding the role of mechanical stimuli in the breast tumor microenvironment (TME).

Methods: We utilized bulk and single-cell RNA sequencing analysis to characterize MSRGs associated with breast cancer prognosis. Unsupervised consensus molecular clustering was applied to identify distinct clusters based on overall survival-associated MSRGs from The Cancer Genome Atlas (TCGA) database. The scoring model was constructed by LASSO-Cox method and validated. Additionally, single-cell RNA sequencing analysis, along with in vitro and in vivo experiments, were conducted to further investigate the role of the model in breast cancer.

Results: We identified 23 overall survival-associated MSRGs and established two molecular subgroups with distinct survival outcomes. A prognostic signature incorporating 15 MSRGs was developed and validated, demonstrating its predictive capability for overall survival of breast cancer patients. The nomogram integrating clinical characteristics and the mechanical stimulus-related risk score exhibited promising predictive accuracy. The low-risk group displayed an immune "hot" phenotype with increased immune cell infiltration, while the high-risk group exhibited resistance to conventional chemotherapy but potential sensitivity to Sepantronium bromide. By using the SCISSOR algorithm, we provide evidence at single-cell resolution for the impact of mechanical stimulation on tumor immune microenvironment. The in vivo and in vitro assays demonstrated that knockdown of TEX19 significantly suppressed breast tumor proliferation.

Conclusion: We developed a pioneering prognostic signature incorporating MSRGs in breast cancer, with a particular focus on mechanical stimuli may influence breast cancer prognosis by remodeling the immune microenvironment. The findings highlighted the importance of personalized treatment strategies and provide new insights into the role of mechanical forces in breast tumor biology.