Breast Cancer Research最新文献

Background: Breast cancer, which is the most prevalent form of cancer among women globally, encompasses various subtypes that demand distinct treatment approaches. The tumor microenvironment and immune response are of crucial significance in the development and progression of breast cancer. Nevertheless, there has been scant evidence concerning the genes within breast cancer - specific immune cells.

Methods: We utilized summary data-based Mendelian randomization (SMR) to identify genes associated with breast cancer by utilizing expression quantitative trait loci (eQTL) datasets for 14 different immune cell types and genome-wide association studies (GWAS) for overall breast cancer and its subtypes. Furthermore, colocalization analysis was carried out to evaluate whether the observed association in SMR analyses is influenced by the same causal variant. Replication analysis and bulk RNA sequencing (bulkRNA-seq) analysis were employed to validate promising immune genes as potential drug targets.

Results: After correcting for the rate of false discovery, we discovered a total of 17 genes in 9 immune cell types that were significantly associated with overall breast cancer and its subtypes. The genes KCNN4, L3MBTL3, ZBTB38, MDM4, and TNFSF10 were identified in overall breast cancer and its subtypes. Colocalization analyses provided robust evidence in support of these associations. Notably, the KCNN4 gene in non-classical MONOcytes (MONOnc) was further validated through replication analysis and bulkRNA-seq analysis.

Conclusion: In summary, our research has revealed a repertoire of genes within diverse immune cells associated with breast cancer. KCNN4 gene in non-classical MONOcytes (MONOnc) exhibited a negative association with overall breast cancer and its subtypes, which was identified as a potential drug target for breast cancer, opening up new avenues for therapeutic interventions.

Background: To assess proportions of metastatic recurrence in women initially diagnosed with non-metastatic breast cancer by stage at diagnosis, breast cancer subtype, calendar period and age.

Methods: A systematic search of MEDLINE and Web of Science databases (January 2010-12 May 2022) was conducted. Studies reporting the proportion of distant metastatic recurrence in women with non-metastatic breast cancer were identified and outcomes and characteristics were extracted. Risk of bias was assessed independently by two reviewers. Random-effects meta-analyses of proportions were used to calculate pooled estimates and 95% confidence intervals (CIs).

Results: 193 studies covering over 280,000 patients were included in the main analysis. Pooled proportions of metastatic recurrence increased with longer median follow-up time from 12.2% (95% CI 10.5-14.0%) at 1-4 years post diagnosis, 14.3% (95% CI 12.9-15.7%) at 5-9 years to 23.3% (95% CI 20.1-26.8) at 10 years or more. Regional variation was observed with pooled estimates ranging from 11.0% (95% CI 8.5-13.7%) in Europe to 26.4% (95% CI 16.7-37.4%) in Africa (1-4 years follow-up). Proportions of recurrence were higher in studies with diagnosis before 2000 (22.2%, 95% CI 15.1-30.3) compared to studies with diagnosis from 2000 onwards (12.8%, 95% CI 11.7-14.0). At 1-4 years median follow-up, pooled proportions of metastatic recurrence were higher in women with hormone receptor negative (15.2%, 95% CI 12.0-18.7%) compared with receptor positive disease (9.6%, 95% CI 6.2-13.6%) and in women with locally advanced (33.2%, 95% CI 24.7-42.3%) relative to early disease at initial diagnosis (4.8%, 95% CI 2.5-7.8%). Proportions were higher in those under 50 years compared with 70+ years, 18.6% (95% CI 15.9-21.4%) versus 13.3% (95% CI 9.2, 18.0%), respectively. Heterogeneity was high in all meta-analyses and results should be interpreted with caution.

Conclusions: Higher proportions of metastatic recurrence in patients initially diagnosed at an advanced stage and in earlier calendar period emphasises the importance of early detection and treatment advancements. As the global number of breast cancer survivors increases, research and health policy efforts should be directed towards timely diagnosis and access to effective treatments and care.

Study registration: PROSPERO CRD42022314500.

Breast cancer (BCa) is a major global health challenge. The BCa genome often carries extensive somatic copy number alterations (CNAs), including gains/amplifications and losses/deletions. These CNAs significantly affect tumor development, drug response and patient survival. However, how individual CNAs contribute is mostly elusive. We identified loss of chromosome 13q14.2 as a key CNA in BCa, occurring in up to 63% of patients, depending on the subtype, and correlating with poor survival. Through multi-omics and in vitro analyses, we uncover a paradoxical role of 13q14.2 loss, promoting both cell cycle and pro-apoptotic pathways in cancer cells, while also associating with increased NK cell and macrophage populations in the tumor microenvironment. Notably, 13q14.2 loss increases BCa susceptibility to BCL2 inhibitors, both in vitro and in patient-derived xenografts. Thus, 13q14.2 loss could serve as a biomarker for BCa prognosis and treatment, potentially improving outcomes for BCa patients.

Background: Prolactin, a hormone produced by the pituitary gland, regulates breast development and may contribute to breast cancer etiology. However, most epidemiologic studies of prolactin and breast cancer have been restricted to single, often small, study samples with limited exploration of effect modification.

Methods: The Biomarkers in Breast Cancer Risk Prediction consortium includes 8,279 postmenopausal women sampled from four prospective cohort studies, of whom 3,441 were diagnosed with invasive breast cancer after enrollment. Prolactin concentrations were measured for all study participants on plasma samples collected when all women were postmenopausal and before any breast cancer diagnosis using ELISA assays. Pooled, unconditional logistic regression models, adjusted for confounders, estimated odd ratios (OR) for associations of prolactin and postmenopausal breast cancer risk overall and stratified by breast cancer risk factors.

Results: Higher plasma prolactin concentrations were positively associated with postmenopausal breast cancer risk (> 13.2 ng/mL vs. < 7.9 ng/mL, OR: 1.20, 95% CI: 1.06, 1.36; P-trend < 0.001). Although associations did not appear to vary by time since blood draw or most breast cancer risk factors, associations were primarily observed in current users of postmenopausal hormones at blood draw (> 13.2 ng/mL vs. < 7.9 ng/mL, current users, OR: 1.58, 95% CI: 1.27, 1.96, P-trend < 0.001; non-current users, OR: 1.08, 95% CI: 0.93, 1.27, P-trend = 0.11; P-heterogeneity = 0.06).

Conclusion: Prolactin may be a risk factor for postmenopausal breast cancer, particularly in the context of postmenopausal hormone use. Investigations of prolactin interactions with other hormonal factors may further inform breast cancer etiology.

Background: Elevated mammographic density is associated with increased breast cancer risk. However, the contribution of longitudinal changes in mammographic density to breast cancer risk beyond initial mammographic density levels, considering familial breast cancer risk and menopausal status, remains uncertain but holds important clinical implications.

Methods: In a nested case-control study within the Sister Study (323 cases, 899 controls; 12,095 mammograms), a cohort enriched for family history of breast cancer, we examined case-control status in relation to the largest annual change in percent density and dense area using mammograms available spanning 5.4 years, on average, using multivariable logistic regression and to the rate of mammographic density change using linear mixed-effects models. We considered effect modification by: mammographic density level of the earlier mammogram, the extent of family history, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation (BOADICEA) risk strata, and menopausal status.

Results: Cases (diagnosed < 60 years) had greater initial percent density and dense area levels and a slower rate of decline in dense area than controls. Women with stable mammographic density (≤ 10% annual change) had an increased breast cancer risk as compared with women whose largest mammographic density change was > 10% annual decline (e.g., Odds Ratio (OR) 2.34, 95% Confidence Interval (CI) 1.63-3.37 for dense area). Increasing vs. decreasing dense area was also associated with elevated risk, especially in women with the highest dense area levels at the earlier mammogram (OR: 2.56, 95%CI 1.50-4.36). Although generally similar across menopausal and familial risk categories, the associations of MD change with risk appeared stronger in pre-menopausal and lower-risk women.

Conclusions: Women who maintain higher levels of mammographic density (i.e. do not decrease over time) or have increasing mammographic density over time have a higher risk of subsequent breast cancer than women with high mammographic density that decreases over time. These findings suggest potential for incorporating mammographic density trajectories in clinical risk assessment, and the importance of additional breast cancer monitoring in women not experiencing declines in mammographic density over time.

Background: Patients with Triple Negative Breast Cancer (TNBC) currently lack targeted therapies, and consequently face higher mortality rates when compared to patients with other breast cancer subtypes. The tumor microenvironment (TME) cytokine Oncostatin M (OSM) reprograms TNBC cells to a more stem-like/mesenchymal state, conferring aggressive cancer cell properties such as enhanced migration and invasion, increased tumor-initiating capacity, and intrinsic resistance to the current standards of care. In contrast to OSM, Interferon-β (IFN-β) promotes a more differentiated, epithelial cell phenotype in addition to its role as an activator of anti-tumor immunity. Importantly, OSM suppresses the production of IFN-β, although the mechanism of IFN-β suppression has not yet been elucidated.

Methods: IFN-β production and downstream autocrine signaling were assessed via quantitative real-time PCR (qRT-PCR) and Western blotting in TNBC cells following exposure to OSM. RNA-sequencing (RNA-seq) was used to assess an IFN-β metagene signature, and to assess the expression of innate immune sensors, which are upstream activators of IFN-β. Cell migration was assessed using an in vitro chemotaxis assay. Additionally, TNBC cells were exposed to TGF-β1, Snail, and Zeb1, and IFN-β production and downstream autocrine signaling were assessed via RNA-seq, qRT-PCR, and Western blotting.

Results: Here, we identify the repression of Toll-like Receptor 3 (TLR3), an innate immune sensor, as the key molecular event linking OSM signaling and the repression of IFN-β transcription, production, and autocrine IFN signaling. Moreover, we demonstrate that additional epithelial-mesenchymal transition-inducing factors, such as TGF-β1, Snail, and Zeb1, similarly suppress TLR3-mediated IFN-β production and signaling.

Conclusions: Our findings provide a novel insight into the regulation of TLR3 and IFN-β production in TNBC cells, which are known indicators of treatment responses to DNA-damaging therapies. Furthermore, strategies to stimulate TLR3 in order to increase IFN-β within the TME may be ineffective in stem-like/mesenchymal cells, as TLR3 is strongly repressed. Rather, we propose that therapies targeting OSM or OSM receptor would reverse the stem-like/mesenchymal program and restore TLR3-mediated IFN-β production within the TME, facilitating improved responses to current therapies.

Background: Presently incurable, metastatic breast cancer is estimated to occur in as many as 30% of those diagnosed with early-stage breast cancer. Timely and accurate identification of those at risk for developing metastasis using validated biomarkers has the potential to have profound impact on overall survival rates. Our primary goal was to conduct a systematic review and synthesize the existing body of scientific knowledge on the candidate genes and their respective single nucleotide polymorphisms associated with metastasis-related outcomes among patients diagnosed with breast cancer. This knowledge is critical to inform future hypothesis-driven and validation research aimed at enhancing clinical decision-making for breast cancer patients.

Methods: Using PRISMA guidelines, literature searches were conducted on September 13th, 2023, using PubMed and Embase databases. The systematic review protocol was registered with INPLASY (DOI: https://doi.org/10.37766/inplasy2024.8.0014 ). Covidence software was used to facilitate the screening and article extraction processes. Peer-reviewed articles were selected if authors reported on single nucleotide polymorphisms directly associated with metastasis among adults diagnosed with breast cancer.

Findings: We identified 451 articles after 44 duplicates were removed resulting in 407 articles to be screened for study inclusion. Three reviewers completed the article screening process which resulted in 86 articles meeting the study inclusion criteria. Sampling varied across studies with the majority utilizing a case-control design (n = 75, 87.2%), with sample sizes ranging from 23 to 1,017 participants having mean age 50.65 ± 4.50 (min-max: 20-75). The synthesis of this internationally generated evidence revealed that the scientific area on the underlying biological contributions to breast cancer metastasis remains predominantly exploratory in nature (n = 74, 86%). Of the 12 studies with reported power analyses, only 9 explicitly stated the power values which ranged from 47.88 to 99%.

Discussion: Understanding the underlying biological mechanisms contributing to metastasis is a critical component for precision oncological therapeutics and treatment approaches. Current evidence investigating the contribution of SNPs to the development of metastasis is characterized by underpowered candidate gene studies. To inform individualized precision health practices and improve breast cancer survival outcomes, future hypothesis-driven research is needed to replicate these associations in larger, more diverse datasets.

Up to 40% of patients with estrogen receptor (ER)-positive breast cancer will develop resistance against the majority of current ER-directed therapies. Resistance can arise through various mechanisms such as increased expression levels of coregulators, and key mutations acquired in the receptor's ligand binding domain rendering it constitutively active. To overcome these resistance mechanisms, we explored targeting the ER Activation Function 2 (AF2) site, which is essential for coactivator binding and activation. Using artificial intelligence and the deep docking methodology, we virtually screened > 1 billion small molecules and identified 290 potential AF2 binders that were then characterized and validated through an iterative screening pipeline of cell-based and cell-free assays. We ranked the compounds based on their ability to reduce the transcriptional activity of the estrogen receptor and the viability of ER-positive breast cancer cells. We identified a lead compound, VPC-260724, which inhibits ER activity at low micromolar range. We confirmed its direct binding to the ER-AF2 site through a PGC1α peptide displacement experiment. Using proximity ligation assays, we showed that VPC-260724 disrupts the interaction between ER-AF2 and the coactivator SRC-3 and reduces the expression of ER target genes in various breast cancer models including the tamoxifen resistant cell line TamR3. In conclusion, we developed a novel ER-AF2 binder, VPC-260724, which shows antiproliferative activity in ER-positive breast cancer models. The use of an ER-AF2 inhibitor in combination with current treatments may provide a novel complementary therapeutic approach to target treatment resistance in ER-positive breast cancer.