scholarly journals Lipid Markers of Breast Tissue for the Diagnosis of Regional Metastatic Lesion

2021 ◽  
Author(s):  
Vitaliy Chagovets ◽  
Alisa Tokareva ◽  
Natalia Starodubtseva ◽  
Vlada Kometova ◽  
Maria Rodionova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Tumor Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Diagnostic Model ◽  
Regional Lymph Nodes ◽  
Metastatic Lesions ◽  
P 16 ◽  
Lipid Markers

Abstract The development of minimally invasive, non-traumatic and stable approaches for the diagnosis of metastatic lesions of regional lymph nodes upon breast cancer is of great urgency. Here we recorded lipid profiles of normal breast tissue and malignant tissue to reveal potential lipid markers of metastatic lesions of regional lymph nodes. Lipid identification was done using the Lipid Match package. The search for lipid markers was carried out using the Mann-Whitney test. Lipids for the construction of a diagnostic logistic regression were selected according to the Akaike information criterion. For normal breast tissue, a diagnostic model was obtained with the area under the curve (AUC) of 0.83; for tumor tissue, a model with AUC = 0.86 was obtained. The species PC 14:0_20:4, PE 18:1_20:1, PC P-16:0/20:4, PC P-16:0/20:4, PE P-16:0/22:4, SM d18:1/18 0, SM d18:1/22:0 were determined as markers for normal breast tissue. The species PC 18:2_22:6, PC O-18:0/20:2, SM d16:1/18:1, SM d22:0/20:2, SM d16:0/18:2 were determined as markers for tumor tissue. The high AUC values ​​for the developed diagnostic model indicate the potential significance of the revealed marker species for the diagnosis of breast cancer metastasis and indicate the need for further research in this direction.

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

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
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.

The association of tissue and serum adiponectin levels with the parameters of insulin-resistance in breast cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22172-e22172
Author(s):  
M. Seker ◽  
F. Y. Erkal ◽  
A. Bilici ◽  
T. Salman ◽  
B. O. Ustaalioglu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Breast Tissue ◽  
Tumor Tissue ◽  
Normal Breast Tissue ◽  
Inverse Correlation ◽  
Normal Breast ◽  
The Other ◽  
Serum Adiponectin ◽  
Breast Cancer Patients

e22172 Background: Adiponectin is a novel adipocyte-secreted proteine and associated with insulin-resistant (IR) status, such as type 2 diabetes mellitus and obesity. The inverse correlation between serum adiponectin levels and breast cancer risk was previously documented. Moreover, the association of high tissue adiponectin levels with breast cancer has been recently reported. In the present study, the relationship among tumor, normal breast tissue and serum adiponectin levels, breast cancer, and the other IR parameters were evaluated. Methods: Fifty-three patients with diagnosed and histologically confirmed breast cancer were included in our study. We analyzed the correlation among the levels of normal and tumor breast tissue adiponectin and serum adiponectin levels. In addition, the association of tissue and serum adiponectin levels with the various classical risk and IR factors, such as body mass index, menopausal status and, tumor size, stage, lymph node status, hormonal status were also studied. Results: Tumor tissue adiponectin levels (56 ± 9.6 ng/ml) were similar with normal breast tissue (56 ± 10 ng/ml) (p>0.05). However, the serum adiponectin levels were significantly lower compared with both normal and tumor tissue (p<0.05). In addition, the inversely association of serum adiponectin levels with tumor tissue adiponectin levels was detected (p=0.001). The inverse correlation between T stage and tumor tissue adiponectin was found (p=0.03). The levels of serum adiponectin were significantly more higher in patients with c- erb-B2 overexpressed (p=0,008). Both nuclear and histologic grade were significantly associated with serum adiponectin levels (p=0.04,p=0.04, respectively). On the other hand, the reverse relationship between nuclear grade and, both tumor (p=0.01) and normal tissue (p=0.009) adiponectin levels was also detected. In subgroup analysis, the correlation among demographic, clinicopathologic, IR parameters, tissue and serum adiponectin levels was not found (p>0.05). Conclusions: Our results suggest that the low serum adiponectin and high normal and tumor tissue adiponectin levels detected in breast cancer patients and serum adiponectin levels inversely associated with tumor tissue adiponectin levels. No significant financial relationships to disclose.

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

2019 ◽  
Author(s):  
Toshiaki Akahane ◽  
Naoki Kanomata ◽  
Oi Harada ◽  
Tetsumasa Yamashita ◽  
Junichi Kurebayashi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Breast Cancer ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Primary Tumour ◽  
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 tumour. These additional changes may be related to tumour progression and/or drug resistance. The breast cancer-targeted NGS, however, is not still widely used for comparing genomic profile of primary breast cancer and recurrent/metastatic lesions in clinical practice.Methods Genomic DNA was extracted from normal breast tissue, primary breast cancer, and recurrent/metastatic lesion(s) from the same patient. A DNA library was constructed using the QIAseq Human Breast Cancer Panel (93 genes, Qiagen) and then sequenced by a MiSeq (Illumina). The Qiagen web portal was utilized for data analysis.Results Of 107 breast cancer cases with recurrence/metastases, successful results for three or four samples (normal breast tissue, primary tumour, and at least one metastatic/recurrent lesion) were obtained for 11 patients (36 samples). We detected shared somatic mutations in all but one patient, who had germline mutations in TP53 and KMT2C . Additional mutations were detected in recurrent/metastatic lesions compared with primary tumour in genes including TP53 (three patients) and one case each of ATR , BLM , CBFB , EP300 , ERBB2 , MUC16 , PBRM1, and PIK3CA . More copy number variations (CNVs) was detected in distant metastases than in local recurrence ( P =0.030).Conclusions The QIAseq Human Breast Cancer Panel assay could identify driver mutations in both primary breast tumour tissue and recurrent/metastatic lesions in almost all patients. This method can assist in identifying drug-targetable mutations and CNV in metastatic breast cancers.

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 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 Breast Cancer ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Primary Tumour ◽  
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 tumour. These additional changes may be related to tumour progression and/or drug resistance. The breast cancer-targeted NGS, however, is not still widely used for comparing genomic profile of primary breast cancer and recurrent/metastatic lesions in clinical practice.Methods: Genomic DNA was extracted from normal breast tissue, primary breast cancer, and recurrent/metastatic lesion(s) from the same patient. A DNA library was constructed using the QIAseq Human Breast Cancer Panel (93 genes, Qiagen) and then sequenced by a MiSeq (Illumina). The Qiagen web portal was utilized for data analysis.Results: Of 35 breast cancer cases with recurrence/metastases, successful results for three or four samples (normal breast tissue, primary tumour, and at least one metastatic/recurrent lesion) were obtained for 11 patients (36 samples). We detected shared somatic mutations in all but one patient, who had germline mutation in TP53. Additional mutations were detected in recurrent/metastatic lesions compared with primary tumour 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 82% (9/11) of recurrent/metastatic breast cancer cases.Conclusions: The QIAseq Human Breast Cancer Panel assay could identify driver mutations in both primary breast tumour tissue and recurrent/metastatic lesions in almost all patients. This method can assist in identifying drug-targetable mutation and CNV in metastatic breast cancers.

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.

Sign in / Sign up

Export Citation Format

Share Document