A distinctive feature of BRCA1-linked breast cancers is that they typically do not express estrogen receptor-alpha (ER(alpha)). Previous investigation suggests that methylation of CpGs within the ER(alpha) promoter mediates repression of gene expression in some ER(alpha)-negative breast cancers. To determine if methylation of CpGs within the ER(alpha) promoter is associated with BRCA1-linked breast cancers, we evaluated methylation in exon 1 of the ER(alpha) gene in 40 ER(alpha)-negative breast cancers, 20 of which were non BRCA1-linked and 20 BRCA1-linked. CpG methylation was evaluated by either methylation-sensitive restriction digest (HpaII), methylation-sensitive PCR (MSP), or direct sequencing of bisulfite-treated genomic DNA. Results from HpaII digests and MSP documented a high degree of methylation, the MSP data showing slightly higher methylation in the BRCA1-linked group. CpGs analysed by direct sequencing showed an overall average methylation of 25% among non BRCA1-linked cancers and 40% among BRCA1-linked cancers (P=0.0031). The most notable difference was found at five particular CpGs, each of which exhibited a greater than twofold increase in methylation in the BRCA1-linked group compared to the non BRCA1-linked group (P<0.03 for each CpG). Methylation of certain critical CpGs may represent an important factor in transcriptional repression of the ER(alpha) gene in BRCA1-linked breast cancers.
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http://dx.doi.org/10.1038/sj.onc.1205844 | DOI Listing |
Sci Rep
December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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View Article and Find Full Text PDFthe evolution of axillary management in breast cancer has witnessed significant changes in recent decades, leading to an overall reduction in surgical interventions. There have been notable shifts in practice, aiming to minimize morbidity while maintaining oncologic outcomes and accurate staging for newly diagnosed breast cancer patients. These advancements have been facilitated by the improved efficacy of adjuvant therapies.
View Article and Find Full Text PDFthe axillary reverse mapping (ARM) procedure aims to preserve the lymphatic drainage structures of the upper extremity during axillary surgery for breast cancer, thereby reducing the risk of lymphedema in the upper limb. Material and this prospective study included 57 patients with breast cancer who underwent SLNB and ARM. The sentinel lymph node (SLN) was identified using a radioactive tracer.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Medicine, Institute of Biomedicine, University of Eastern Finland, Yliopistonranta 1, PO Box 1627, 70211 Kuopio, Finland.
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test various feature sets-potential biomarker solutions-to fine-tune a machine learning model's performance for supervised tasks, such as classifying cancer subtypes. This optimization process is undertaken using validation sets to evaluate and identify the most effective feature combinations.
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