Methylation of progesterone receptor isoform A promoter in normal breast tissue: An epigenetic link between early age at menarche and risk of breast cancer?

2019 ◽  
Vol 120 (8) ◽  
pp. 12393-12401 ◽  
Author(s):  
Abdolreza Daraei ◽  
Pantea Izadi ◽  
Ghasemali Khorasani ◽  
Nahid Nafissi ◽  
Mohammad Mehdi Naghizadeh ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Progesterone Receptor ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Age At Menarche ◽  
Early Age

scholarly journals Expression of estrogen receptor, progesterone receptor, and Ki67 in normal breast tissue in relation to subsequent risk of breast cancer

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Hannah Oh ◽  
A Heather Eliassen ◽  
Molin Wang ◽  
Stephanie A Smith-Warner ◽  
Andrew H Beck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Progesterone Receptor ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Subsequent Risk

scholarly journals Accelerated aging in normal breast tissue of women with breast cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Shoghag Panjarian ◽  
Jozef Madzo ◽  
Kelsey Keith ◽  
Carolyn M. Slater ◽  
Carmen Sapienza ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Anomaly Detection ◽  
Breast Tissue ◽  
Preventive Intervention ◽  
Normal Breast Tissue ◽  
Accelerated Aging ◽  
Normal Breast ◽  
Age Related ◽  
Unsupervised Anomaly Detection

Abstract Background DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. Methods We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation. Results We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. Conclusions A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.

scholarly journals Targeted next-generation sequencing assays using triplet samples of normal breast tissue, primary breast cancer, and recurrent/metastatic lesions

2020 ◽  
Author(s):  
Toshiaki Akahane ◽  
Naoki Kanomata ◽  
Oi Harada ◽  
Tetsumasa Yamashita ◽  
Junichi Kurebayashi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Tumor ◽  
Primary Breast Cancer ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Metastatic Breast ◽  
Normal Breast ◽  
Human Breast ◽  
Metastatic Lesions ◽  
Generation Sequencing

Abstract Background: Next-generation sequencing (NGS) has shown that recurrent/metastatic breast cancer lesions may have additional genetic changes compared with the primary tumor. These additional changes may be related to tumor progression and/or drug resistance. However, breast cancer-targeted NGS is not still widely used in clinical practice to compare the genomic profiles of primary breast cancer and recurrent/metastatic lesions.Methods: Triplet samples of genomic DNA were extracted from each patient’s normal breast tissue, primary breast cancer, and recurrent/metastatic lesion(s). A DNA library was constructed using the QIAseq Human Breast Cancer Panel (93 genes, Qiagen) and then sequenced using MiSeq (Illumina). The Qiagen web portal was utilized for data analysis.Results: Successful results for three or four samples (normal breast tissue, primary tumor, and at least one metastatic/recurrent lesion) were obtained for 11 of 35 breast cancer patients with recurrence/metastases (36 samples). We detected shared somatic mutations in all but one patient, who had a germline mutation in TP53. Additional mutations that were detected in recurrent/metastatic lesions compared with primary tumor were in genes including TP53 (three patients) and one case each of ATR, BLM, CBFB, EP300, ERBB2, MUC16, PBRM1, and PIK3CA. Actionable mutations and/or copy number variations (CNVs) were detected in 73% (8/11) of recurrent/metastatic breast cancer lesions.Conclusions: The QIAseq Human Breast Cancer Panel assay showed that recurrent/metastatic breast cancers sometimes acquired additional mutations and CNV. Such additional genomic changes could provide therapeutic target.

scholarly journals DNA Methylation and Breast Cancer Risk: An Epigenome-Wide Study of Normal Breast Tissue and Blood

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3088 ◽  
Author(s):  
Kaoutar Ennour-Idrissi ◽  
Dzevka Dragic ◽  
Elissar Issa ◽  
Annick Michaud ◽  
Sue-Ling Chang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Breast Epithelium ◽  
Normal Breast Epithelium ◽  
Differentially Methylated Genes

Differential DNA methylation is a potential marker of breast cancer risk. Few studies have investigated DNA methylation changes in normal breast tissue and were largely confounded by cancer field effects. To detect methylation changes in normal breast epithelium that are causally associated with breast cancer occurrence, we used a nested case–control study design based on a prospective cohort of patients diagnosed with a primary invasive hormone receptor-positive breast cancer. Twenty patients diagnosed with a contralateral breast cancer (CBC) were matched (1:1) with 20 patients who did not develop a CBC on relevant risk factors. Differentially methylated Cytosine-phosphate-Guanines (CpGs) and regions in normal breast epithelium were identified using an epigenome-wide DNA methylation assay and robust linear regressions. Analyses were replicated in two independent sets of normal breast tissue and blood. We identified 7315 CpGs (FDR < 0.05), 52 passing strict Bonferroni correction (p < 1.22 × 10−7) and 43 mapping to known genes involved in metabolic diseases with significant enrichment (p < 0.01) of pathways involving fatty acids metabolic processes. Four differentially methylated genes were detected in both site-specific and regions analyses (LHX2, TFAP2B, JAKMIP1, SEPT9), and three genes overlapped all three datasets (POM121L2, KCNQ1, CLEC4C). Once validated, the seven differentially methylated genes distinguishing women who developed and who did not develop a sporadic breast cancer could be used to enhance breast cancer risk-stratification, and allow implementation of targeted screening and preventive strategies that would ultimately improve breast cancer prognosis.

The role of low keV virtual monochromatic imaging in increasing the conspicuity of primary breast cancer in dual-energy spectral thoracic CT examination for staging purposes

2019 ◽  
Vol 61 (2) ◽  
pp. 168-174 ◽  
Author(s):  
Yavuz Metin ◽  
Nurgül Orhan Metin ◽  
Oğuzhan Özdemir ◽  
Filiz Taşçı ◽  
Sibel Kul
Keyword(s):  
Breast Cancer ◽  
Primary Breast Cancer ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Energy Levels ◽  
Iodine Content ◽  
Pectoral Muscle ◽  
Dual Energy ◽  
Normal Breast

Background The additive value of dual-energy spectral computerized tomography (DESCT) in breast cancer imaging is still unknown. Purpose To investigate the role of DESCT in improving the conspicuity of primary breast cancer. Material and Methods Twenty-nine patients who were histopathologically diagnosed with breast cancer and underwent DESCT for staging of lung metastasis were evaluated retrospectively. The visual conspicuity of breast cancer was scored by two readers separately in reconstructed virtual monochromatic images obtained at 40, 60, 80, and 100 keV. A circular region of interest slightly smaller than the maximum contrasted portion of the primary breast cancer was manually placed. Iodine enhancement (HU) and iodine content (mg/mL) values of tumor, normal breast tissue and pectoral muscle, and contrast-to-noise values of images at four different energy levels were calculated. Results The lesion conspicuity score peaked at 40-keV series for both readers and was significantly higher than those at other energy levels (all P < 0.001). Lesion iodine enhancement was highest at 40-keV virtual monochromatic image reconstructions ( P < 0.001). The iodine content was significantly higher in tumor than normal breast tissue, and pectoral muscle ( P < 0.001). The highest contrast-to-noise value was obtained at 60 keV (4.0 ± 2.5), followed by 40 keV (3.9 ± 2.2), without a significant difference ( P = 0.33). Conclusion The conspicuity of primary breast cancer was significantly higher in low keV virtual monochromatic images obtained by DESCT. This gives us hope that DESCT may play an effective role in detecting incidental breast lesions. It also raises the question of whether quantitative values obtained by DESCT can be used for characterization of primary breast lesion.

scholarly journals MicroRNA-203 Regulates Growth and Metastasis of Breast Cancer

2015 ◽  
Vol 37 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Shan Zhao ◽  
Jinzhu Han ◽  
Likang Zheng ◽  
Zixin Yang ◽  
Li Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Cycle ◽  
Cell Growth ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Cancer Cell Growth ◽  
Breast Cancer Cell Growth

Backgrounds/Aims: MicroRNAs (MiRNAs) control many biological events and play critical roles in the development of tumor. Among all miRNAs, miR203 has been recently shown to have an inhibitory effect on prostate cancer. However, its involvement in the carcinogenesis of breast cancer has not been reported. Methods: We examined the levels of miR203 in the breast cancer from the patients compared to the paired normal breast tissue. We also examined the levels of miR203 in several commonly used breast cancer cell lines. The effects of overexpression or depletion of miR203 on breast cancer cell growth were analyzed by a MTT assay, and on breast cancer cell invasion were examined by a scratch wound healing assay and a transwell cell migration assay. MiR203-targeted genes were analyzed by Western blot. Results: We detected significantly lower levels of miR203 in the breast cancer from the patients compared to the paired normal breast tissue. Moreover, the levels of miR203 were significantly lower in breast cancer tissue from the patients with cancer metastasis. Decreased miR203 levels were detected in all examined breast cancer lines. Overexpression of miR203 inhibited breast cancer cell growth and invasion, while antisense-mediated inhibition of miR203 enhanced cancer cell growth and invasion. Further analyses show that miR203 may inhibit cell growth through decreasing cell-cycle activator cyclinD2 and CDK6, increasing cell-cycle suppressor p21 and p27, and increasing apoptosis-associated protein Bcl-2. MiR203 may also inhibit cell metastasis through suppressing matrix metalloproteinase 2 (MMP2), MMP7 and MMP9. Conclusion: Our data thus highlight miR203 as a novel therapeutic target for breast cancer.

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