scholarly journals Differential impact of classical and non-canonical NF-κB pathway-related gene expression on the survival of breast cancer patients

2019 ◽  
Vol 10 (21) ◽  
pp. 5191-5211 ◽  
Author(s):  
Nancy Adriana Espinoza-Sánchez ◽  
Balázs Győrffy ◽  
Ezequiel M. Fuentes-Pananá ◽  
Martin Götte
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Differential Impact

scholarly journals Bioinformatic Analysis of Peripheral Blood miRNA of Breast Cancer Patients in Relation With Anthracycline Cardiotoxicity

2019 ◽  
Author(s):  
Wang Yadi ◽  
Chen Shurui ◽  
Zhang Tong ◽  
Chen Suxian ◽  
Tong Qing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Cancer Chemotherapy ◽  
Bioinformatic Analysis ◽  
Expression Data ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Anthracycline Cardiotoxicity ◽  
Breast Cancer Chemotherapy

Abstract The current diagnostic methods and treatments still fail to lower the incidence of anthracycline-induced cardiotoxicity effectively. In this study, we aimed to (1) analyze the cardiotoxicity-related genes after breast cancer chemotherapy in gene expression database and (2) carry out bioinformatic analysis to identify cardiotoxicity-related abnormal expressions, the biomarkers of such abnormal expressions, and the key regulatory pathways after breast cancer chemotherapy. Cardiotoxicity-related gene expression data (GSE40447) after breast cancer chemotherapy was acquired from the GEO database. The biomarker expression data of women with chemotherapy-induced cardiotoxicity (group A), chemotherapy history but no cardiotoxicity (group B), and confirmatory diagnosis of breast cancer but normal ejection fraction before chemotherapy (group C) were analyzed to obtain the mRNA with differential expressions and predict the miRNAs regulating the differential expressions. The miRanda formula and functional enrichment analysis were used to screen abnormal miRNAs. Then, the gene ontology (GO) analysis was adapted to further screen the miRNAs related to cardiotoxicity after breast cancer chemotherapy. The data of differential analysis of biomarker expression of groups A, B, and C using the GSE40447-related gene expression profile database showed that there were 30 intersection genes. The differentially expressed mRNAs were predicted using the miRanda and TargetScan software, and a total of 2978 miRNAs were obtained by taking the intersections. Further, the GO analysis and targeted regulatory relationship between miRNA and target genes were used to establish miRNA-gene interaction network to screen and obtain 7 cardiotoxicity-related miRNAs with relatively high centrality, including hsa-miR-4638-3p, hsa-miR-5096, hsa-miR-4763-5p, hsa-miR-1273g-3p, hsa-miR6192, hsa-miR-4726-5p and hsa-miR-1273a. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p had the highest centrality. The PCR verification results were consistent with those of the chip data. There are differentially expressed miRNAs in the peripheral blood of breast cancer patients with anthracycline cardiotoxicity. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p are closely associated with the onset of anthracycline cardiotoxicity in patients with breast cancer. Mining, integrating, and validating effective information resources of biological gene chips can provide a new direction for further studies on the molecular mechanism of anthracycline cardiotoxicity.

scholarly journals Bioinformatic Analysis of Peripheral Blood miRNA of Breast Cancer Patients in Relation With Anthracycline Cardiotoxicity

2019 ◽  
Author(s):  
Wang Yadi ◽  
Chen Shurui ◽  
Zhang Tong ◽  
Chen Suxian ◽  
Tong Qing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Cancer Chemotherapy ◽  
Bioinformatic Analysis ◽  
Expression Data ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Anthracycline Cardiotoxicity ◽  
Breast Cancer Chemotherapy

Abstract The current diagnostic methods and treatments still fail to lower the incidence of anthracycline-induced cardiotoxicity effectively. In this study, we aimed to (1) analyze the cardiotoxicity-related genes after breast cancer chemotherapy in gene expression database and (2) carry out bioinformatic analysis to identify cardiotoxicity-related abnormal expressions, the biomarkers of such abnormal expressions, and the key regulatory pathways after breast cancer chemotherapy. Cardiotoxicity-related gene expression data (GSE40447) after breast cancer chemotherapy was acquired from the GEO database. The biomarker expression data of women with chemotherapy-induced cardiotoxicity (group A), chemotherapy history but no cardiotoxicity (group B), and confirmatory diagnosis of breast cancer but normal ejection fraction before chemotherapy (group C) were analyzed to obtain the mRNA with differential expressions and predict the miRNAs regulating the differential expressions. The miRanda formula and functional enrichment analysis were used to screen abnormal miRNAs. Then, the gene ontology (GO) analysis was adapted to further screen the miRNAs related to cardiotoxicity after breast cancer chemotherapy. The data of differential analysis of biomarker expression of groups A, B, and C using the GSE40447-related gene expression profile database showed that there were 30 intersection genes. The differentially expressed mRNAs were predicted using the miRanda and TargetScan software, and a total of 2978 miRNAs were obtained by taking the intersections. Further, the GO analysis and targeted regulatory relationship between miRNA and target genes were used to establish miRNA-gene interaction network to screen and obtain 7 cardiotoxicity-related miRNAs with relatively high centrality, including hsa-miR-4638-3p, hsa-miR-5096, hsa-miR-4763-5p, hsa-miR-1273g-3p, hsa-miR6192, hsa-miR-4726-5p and hsa-miR-1273a. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p had the highest centrality. The PCR verification results were consistent with those of the chip data. There are differentially expressed miRNAs in the peripheral blood of breast cancer patients with anthracycline cardiotoxicity. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p are closely associated with the onset of anthracycline cardiotoxicity in patients with breast cancer. Mining, integrating, and validating effective information resources of biological gene chips can provide a new direction for further studies on the molecular mechanism of anthracycline cardiotoxicity.

scholarly journals A glycolysis-related gene expression signature in predicting recurrence of breast cancer

2020 ◽  
Author(s):  
Jianing Tang ◽  
Gaosong Wu
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
Gene Signature ◽  
Low Risk ◽  
Individual Treatment ◽  
Breast Cancer Patients ◽  
Related Gene

Abstract Background Metabolic change is the hallmark of cancer. Even in the presence of oxygen, cancer cells reprogram their glucose metabolism to enhance glycolysis and reduce oxidative phosphorylation. In the present study, we aimed to develop a glycolysis-related gene signature to predict the prognosis of breast cancer patients.Methods Gene expression profiles and clinical data of breast cancer patients were obtained from the GEO database. Univariate, Lasso-penalized, and multivariate Cox analysis were performed to construct the glycolysis-related gene signature.Results A four-gene based signature (ALDH2, PRKACB, STMN1 and ZNF292) was developed to separate patients into high-risk and low-risk groups. Kaplan-Meier survival analysis demonstrated that patients in low-risk group had significantly better prognosis than those in the high-risk group. Time-dependent ROC analysis demonstrated that the glycolysis-related gene signature had excellent prognostic accuracy. We further confirmed the expression of the four prognostic genes in breast cancer and paracancerous tissues samples using qRT-PCR analysis. Expression level of PRKACB was higher in paracancerous tissues, while STMN1 and ZNF292 were overexpressed in tumor samples. No difference was found in ALDH2 expression. The same results were observed in the IHC data from the human protein atlas. Global proteome data of 105 TCGA breast cancer samples obtained from the Clinical Proteomic Tumor Analysis Consortium were used to evaluate the prognostic value of their protein levels. Consistently, high expression of PRKACB protein level was associated with better prognosis, while high ZNF292 and STMN1 protein expression levels indicated poor prognosis.Conclusions The glycolysis-related gene signature might provide an effective prognostic predictor and a new view for individual treatment of breast cancer patients.

scholarly journals MicroRNAs and Metastasis-related Gene Expression in Egyptian Breast Cancer Patients

2012 ◽  
Vol 13 (2) ◽  
pp. 591-598 ◽  
Author(s):  
Mohamed M. Hafez ◽  
Zeinab K. Hassan ◽  
Abdel Rahman N. Zekri ◽  
Ayman A. Gaber ◽  
Salem S. Al Rejaie ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Related Gene

scholarly journals Prognostic significance of hedgehog signaling network‐related gene expression in breast cancer patients

2021 ◽  
Author(s):  
Julia Kuehn ◽  
Nancy Adriana Espinoza‐Sanchez ◽  
Felipe C. O. B. Teixeira ◽  
Mauro S. G. Pavão ◽  
Ludwig Kiesel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Hedgehog Signaling ◽  
Prognostic Significance ◽  
Signaling Network ◽  
Breast Cancer Patients ◽  
Related Gene

scholarly journals Bioinformatic Analysis of Peripheral Blood miRNA of Breast Cancer Patients in Relation With Anthracycline Cardiotoxicity

2019 ◽  
Author(s):  
Wang Yadi ◽  
Chen Shurui ◽  
Zhang Tong ◽  
Chen Suxian ◽  
Tong Qing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Cancer Chemotherapy ◽  
Bioinformatic Analysis ◽  
Expression Data ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Anthracycline Cardiotoxicity ◽  
Breast Cancer Chemotherapy

Abstract The current diagnostic methods and treatments still fail to lower the incidence of anthracycline-induced cardiotoxicity effectively. In this study, we aimed to (1) analyze the cardiotoxicity-related genes after breast cancer chemotherapy in gene expression database and (2) carry out bioinformatic analysis to identify cardiotoxicity-related abnormal expressions, the biomarkers of such abnormal expressions, and the key regulatory pathways after breast cancer chemotherapy. Cardiotoxicity-related gene expression data (GSE40447) after breast cancer chemotherapy was acquired from the GEO database. The biomarker expression data of women with chemotherapy-induced cardiotoxicity (group A), chemotherapy history but no cardiotoxicity (group B), and confirmatory diagnosis of breast cancer but normal ejection fraction before chemotherapy (group C) were analyzed to obtain the mRNA with differential expressions and predict the miRNAs regulating the differential expressions. The miRanda formula and functional enrichment analysis were used to screen abnormal miRNAs. Then, the gene ontology (GO) analysis was adapted to further screen the miRNAs related to cardiotoxicity after breast cancer chemotherapy. The data of differential analysis of biomarker expression of groups A, B, and C using the GSE40447-related gene expression profile database showed that there were 30 intersection genes. The differentially expressed mRNAs were predicted using the miRanda and TargetScan software, and a total of 2978 miRNAs were obtained by taking the intersections. Further, the GO analysis and targeted regulatory relationship between miRNA and target genes were used to establish miRNA-gene interaction network to screen and obtain 7 cardiotoxicity-related miRNAs with relatively high centrality, including hsa-miR-4638-3p, hsa-miR-5096, hsa-miR-4763-5p, hsa-miR-1273g-3p, hsa-miR6192, hsa-miR-4726-5p and hsa-miR-1273a. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p had the highest centrality. The PCR verification results were consistent with those of the chip data. There are differentially expressed miRNAs in the peripheral blood of breast cancer patients with anthracycline cardiotoxicity. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p are closely associated with the onset of anthracycline cardiotoxicity in patients with breast cancer. Mining, integrating, and validating effective information resources of biological gene chips can provide a new direction for further studies on the molecular mechanism of anthracycline cardiotoxicity.

scholarly journals Bioinformatic Analysis of Peripheral Blood miRNA of Breast Cancer Patients in Relation With Anthracycline Cardiotoxicity

2019 ◽  
Author(s):  
Wang Yadi ◽  
Chen Shurui ◽  
Zhang Tong ◽  
Chen Suxian ◽  
Tong Qing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Cancer Chemotherapy ◽  
Bioinformatic Analysis ◽  
Expression Data ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Anthracycline Cardiotoxicity ◽  
Breast Cancer Chemotherapy

Abstract The current diagnostic methods and treatments still fail to lower the incidence of anthracycline-induced cardiotoxicity effectively. In this study, we aimed to (1) analyze the cardiotoxicity-related genes after breast cancer chemotherapy in gene expression database and (2) carry out bioinformatic analysis to identify cardiotoxicity-related abnormal expressions, the biomarkers of such abnormal expressions, and the key regulatory pathways after breast cancer chemotherapy. Cardiotoxicity-related gene expression data (GSE40447) after breast cancer chemotherapy was acquired from the GEO database. The biomarker expression data of women with chemotherapy-induced cardiotoxicity (group A), chemotherapy history but no cardiotoxicity (group B), and confirmatory diagnosis of breast cancer but normal ejection fraction before chemotherapy (group C) were analyzed to obtain the mRNA with differential expressions and predict the miRNAs regulating the differential expressions. The miRanda formula and functional enrichment analysis were used to screen abnormal miRNAs. Then, the gene ontology (GO) analysis was adapted to further screen the miRNAs related to cardiotoxicity after breast cancer chemotherapy. The data of differential analysis of biomarker expression of groups A, B, and C using the GSE40447-related gene expression profile database showed that there were 30 intersection genes. The differentially expressed mRNAs were predicted using the miRanda and TargetScan software, and a total of 2978 miRNAs were obtained by taking the intersections. Further, the GO analysis and targeted regulatory relationship between miRNA and target genes were used to establish miRNA-gene interaction network to screen and obtain 7 cardiotoxicity-related miRNAs with relatively high centrality, including hsa-miR-4638-3p, hsa-miR-5096, hsa-miR-4763-5p, hsa-miR-1273g-3p, hsa-miR6192, hsa-miR-4726-5p and hsa-miR-1273a. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p had the highest centrality. The PCR verification results were consistent with those of the chip data. There are differentially expressed miRNAs in the peripheral blood of breast cancer patients with anthracycline cardiotoxicity. Among them, hsa-miR-4638-3p and hsa-miR-1273g-3p are closely associated with the onset of anthracycline cardiotoxicity in patients with breast cancer. Mining, integrating, and validating effective information resources of biological gene chips can provide a new direction for further studies on the molecular mechanism of anthracycline cardiotoxicity.

scholarly journals Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xu Yang ◽  
Geng-Xi Cai ◽  
Bo-Wei Han ◽  
Zhi-Wei Guo ◽  
Ying-Song Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cell Receptor ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Plasma Dna ◽  
Transcription Start Sites ◽  
Response To Chemotherapy

AbstractGene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

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