scholarly journals Dysregulation of miR-638 in Breast Cancer Patients and Bioinformatics Investigation of Its Target Genes in Apoptosis, Angiogenesis and Autophagy Pathways

2019 ◽  
Vol 12 (11) ◽  
Author(s):  
Samaneh Ahmadi ◽  
Mojtaba Saffari ◽  
Mohammad Hossein Modarressi ◽  
Reza Shirkoohi ◽  
Marjan Jamalian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Target Genes ◽  
Breast Cancer Patients

scholarly journals The target E2F family gene PTTG1 for prediction of distant relapse-free survival in breast cancer patients receiving taxane and anthracycline-based NACT

2021 ◽  
Author(s):  
Yuhao Xu ◽  
Yaoqiang Du ◽  
Qinghui Zheng ◽  
Hongchao Tang ◽  
Yangyang Qian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Target Genes ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
Breast Cancer Patients ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Distant Relapse ◽  
Potential Biomarker

Abstract Background Recent years, the breast cancer became the most commonly diagnosed cancer. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT. Methods We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F targets genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics. Results A novel nomogram was conducted. The receiver operating characteristic (AUC = 0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model. Conclusion Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.

Extracellular circular RNAs to promote the growth and metastasis of triple-negative breast cancer through remodeling the tumor immune microenvironment.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13047-e13047
Author(s):  
Sujin Yang ◽  
Jinhai Tang
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Cell Lines ◽  
Target Genes ◽  
Triple Negative ◽  
Circular Rnas ◽  
Breast Cancer Patients ◽  
Immune Microenvironment ◽  
Tnbc Cell ◽  
High Degree

e13047 Background: Triple-negative breast cancer (TNBC) has been confirmed to have a high degree of heterogeneity of breast cancer, which is more common in young women, with a high degree of malignancy, lack of effective clinical treatment and poor prognosis. Recently, many studies have also found that immune microenvironment (IME) can remarkablely affect the occurrence and metastasis of TNBC through exosome-mediated molecular transmission. Therefore, there is an urgent need to find new immune-related molecules as therapeutic targets and to predict the progress of TNBC and prognosis of treatment. Methods: Using RNA-sequencing and bioinformatics analysis, we found the differential-expressed circular RNAs (circRNAs) in exosomes from TNBC cell lines (BT549 and MDA-MB-231), non-TNBC cell lines (MCF-7 and MCF-10A) and tissues from breast cancer patients. Then, we used CIBERSORT and ESTIMATE algorithm to explore the tumor-infiltrating immune cells (TICs) or stromal components in IME, and identified the significant differential-expressed mRNAs in the immune cells between TNBC and non-TNBC samples. RT-qPCR was used to confirm the expression level of selected circRNAs and mRNAs in TNBC cell lines. Results: We profiled the circRNAs in the exosomes from TNBC cell lines and breast cancer patients by RNA sequencing and detected 27 significantly differentially-expressed circRNAs. After bioinformatic analysis and RT-qPCR, circRELB and circANXA1 were chose to further study. TICs and IME scores were found to associated with the survival and clinicopathological characteristics of TNBC patients and IME remodeling. Interestingly, 92 differentially-expressed genes were found to be enriched in the NF-kB signaling pathway and mTOR signaling pathway. Moreover, we identified 33 target genes of circRELB and circANXA1 by cross-analysis. Based on the predicted miRNAs and the corresponding mRNAs and circRNAs, we have established an IME-related circRNA-miRNA-mRNA network. Then, Kaplan-Meier plots showed the expression levels of certain targeted genes (PTEN, CCND1, IL6, CDKN1A, AKT1, TNF and WNT1) were connected to prognosis in TNBC metastasis patients. Conclusions: The expression levels of circRELB and circANXA1 was found significantly upregulated in exosomes from TNBC cell lines and tumor tissues from breast cancer patients. In addition, circRELB and circANXA1could affect the expression of downstream target genes by competing for endogenous RNA (ceRNAs), and ultimately promote the metastasis of TNBC and remodeling of IME. In summary, this study analyzes the mechanisms of exosome-contained circRNAs in TNBC and these targets from the IME-related circRNA-miRNA-mRNA network may be new potential prognostic biomarkers and immune treatment strategies to prevent the development and metastasis of TNBC.

scholarly journals Next-Generation Sequencing of MicroRNAs for Breast Cancer Detection

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Qian Wu ◽  
Zuhong Lu ◽  
Hailing Li ◽  
Jiafeng Lu ◽  
Li Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Ontology ◽  
Cancer Patients ◽  
Cancer Detection ◽  
Target Genes ◽  
Breast Cancer Detection ◽  
Gene Ontology Analysis ◽  
Breast Cancer Patients ◽  
Mirna Profiling ◽  
Serum Mirnas

It is reported that different microRNA (miRNA) profiles can be detected in the blood of cancer patients. We investigated that whether the key serum miRNAs could discriminate patients with and without breast cancer. This study was divided into three parts: (1) miRNA marker discovery using SOLiD sequencing-based miRNA profiling on cancerous and adjacent noncancerous breast tissue of one breast cancer patient; (2) marker selection and validation by real-time PCR on a small set of serum; (3) gene ontology analysis of the key miRNA target genes. Of genome-wide tissue miRNA expression analysis, five miRNAs were found to be altered more than fivefold by SOLiD sequencing (i.e., miR-29a, miR-23a, miR-23b, miR-192, and miR-21). All the five miRNAs were validated on the 20 breast cancer patients and 20 controls. miR-29a and miR-21 were significantly increased in the serum of breast cancer patients (). Gene ontology analysis of the target genes revealed enrichment for special biological process categories, that is, signal transduction, development, apoptosis, cell proliferation, and cell adhesion. SOLiD sequencing provides a promising method for cancer-related miRNA profiling. Serum miRNAs may be useful biomarkers for breast cancer detection.

scholarly journals The Target E2F Family Gene PTTG1 for Prediction of Distant Relapse-Free Survival in Breast Cancer Patients Receiving Taxane and Anthracycline-Based NACT

2021 ◽  
Author(s):  
Yu-hao Xu ◽  
Yao-qiang Du ◽  
Qing-hui Zheng ◽  
Qiu-ran Xu ◽  
Xuli Meng
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Target Genes ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
Breast Cancer Patients ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Distant Relapse ◽  
Potential Biomarker

Abstract Background: The breast cancer is the most commonly diagnosed cancer in recent years. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT.Methods: We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F target genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics.Results: There were 95 genes confirmed to be associated with DRFS both in GSE25055 and GSE25065. And PTTG1 was validated as a gene related to DRFS and associated with E2F target hallmark using GSEA analysis and chosen as our target gene. The AUC of PTTG1 model was 0.682 indicating a relatively poor prediction performance. Then a novel nomogram was conducted, the receiver operating characteristic (AUC=0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model.Conclusion: Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.

scholarly journals Identification of significantly mutated subnetworks in the breast cancer genome

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rasif Ajwad ◽  
Michael Domaratzki ◽  
Qian Liu ◽  
Nikta Feizi ◽  
Pingzhao Hu
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Target Genes ◽  
Cancer Survival ◽  
Clustering Algorithms ◽  
Molecular Taxonomy ◽  
Breast Cancer Treatment ◽  
Cancer Genome ◽  
Breast Cancer Patients

AbstractRecent studies showed that somatic cancer mutations target genes that are in specific signaling and cellular pathways. However, in each patient only a few of the pathway genes are mutated. Current approaches consider only existing pathways and ignore the topology of the pathways. For this reason, new efforts have been focused on identifying significantly mutated subnetworks and associating them with cancer characteristics. We applied two well-established network analysis approaches to identify significantly mutated subnetworks in the breast cancer genome. We took network topology into account for measuring the mutation similarity of a gene-pair to allow us to infer the significantly mutated subnetworks. Our goals are to evaluate whether the identified subnetworks can be used as biomarkers for predicting breast cancer patient survival and provide the potential mechanisms of the pathways enriched in the subnetworks, with the aim of improving breast cancer treatment. Using the copy number alteration (CNA) datasets from the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study, we identified a significantly mutated yet clinically and functionally relevant subnetwork using two graph-based clustering algorithms. The mutational pattern of the subnetwork is significantly associated with breast cancer survival. The genes in the subnetwork are significantly enriched in retinol metabolism KEGG pathway. Our results show that breast cancer treatment with retinoids may be a potential personalized therapy for breast cancer patients since the CNA patterns of the breast cancer patients can imply whether the retinoids pathway is altered. We also showed that applying multiple bioinformatics algorithms at the same time has the potential to identify new network-based biomarkers, which may be useful for stratifying cancer patients for choosing optimal treatments.

Comprehensive analysis of long noncoding RNA expression in circulation of breast cancer patients on neoadjuvant therapy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e12644-e12644
Author(s):  
Boris Krastev ◽  
Constanta Timcheva ◽  
Spartak Valev ◽  
Georgi Zhbantov ◽  
Ivaylo Stoykov ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Therapy ◽  
Cancer Patients ◽  
Expression Analysis ◽  
Cancer Biology ◽  
Target Genes ◽  
Locally Advanced ◽  
Breast Cancer Patients ◽  
Non Coding Rnas

e12644 Background: Though long considered “nonfunctional”, recent evidence is growing that non-coding RNAs, including long non-coding RNAs (lncRNAs), have an active role in tumor biology, mainly as gene expression regulators. Breast cancer is heterogeneous in nature and locally advanced cases are distinct entity in terms of curability. Being borderline between early and metastatic disease, long-term outcome here strongly depends on the efficacy of systemic therapy. To the best of our knowledge, no study has yet investigated global changes of circulating lncRNAs in this patient population during preoperative (neoadjuvant) treatment. Methods: We conducted a small transcriptomic trial on 10 locally advanced breast cancer patients, assessing lncRNA and messenger RNA (mRNA) expression in plasma samples before (S1) and after (S2) initiation of neoadjuvant therapy. Next-generation sequencing was performed with differential gene expression analysis between S1 and S2 groups. We assessed co-expression between lncRNAs and mRNAs, identifying mRNAs whose transcription was potentially regulated by lncRNAs, i.e. “lncRNA target genes”. In order to elucidate biological roles of these target mRNAs, we performed gene ontology (GO) and pathway analysis (Kyoto Encyclopedia of Genes and Genomes, KEGG). Results: 394 lncRNAs and 1085 mRNAs demonstrated statistically significant difference in expression between pretreatment and posttreatment samples. Co-expression analysis revealed positive correlation between 25 lncRNAs and 25 mRNAs located in cis, while potential trans interactions exceeded 105. GO evaluation of lncRNA target genes was significant for 44 terms: 28 for biological process (BP), 9 for cellular component (CC) and 7 for molecular function (MF). The most annotated terms for BP, MF and CC were respectively biosynthetic process, DNA-binding transcription factor activity and nucleus. KEGG analysis showed that 105 of 201 analyzed pathways were statistically significant with most prominent being pathways in cancer and transcriptional misregulation in cancer. Conclusions: Despite limited in size, present study provides broad view on transcriptional landscape in blood circulation, interrogating in vivo dynamics of systemic gene expression during neoadjuvant breast cancer treatment. It demonstrates that substantial number of circulating lncRNAs could be up- or downregulated in the course of therapy and this has the potential to control protein-coding genes that are tightly implicated in cancer biology.

scholarly journals Deregulated Serum Concentrations of Circulating Cell–Free MicroRNAs miR-17, miR-34a, miR-155, and miR-373 in Human Breast Cancer Development and Progression

2013 ◽  
Vol 59 (10) ◽  
pp. 1489-1496 ◽  
Author(s):  
Corinna Eichelser ◽  
Dieter Flesch-Janys ◽  
Jenny Chang-Claude ◽  
Klaus Pantel ◽  
Heidi Schwarzenbach
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Primary Tumor ◽  
Target Genes ◽  
Tumor Development ◽  
Her2 Status ◽  
Serum Concentrations ◽  
Breast Cancer Patients ◽  
Her2 Positive ◽  
Healthy Women

BACKGROUND MicroRNAs (miRs) are small, noncoding RNAs that target genes involved in tumor development and progression. In the current study, we investigated the use of circulating miR concentrations as biomarkers in the serum of breast cancer patients. METHODS We analyzed serum samples from 120 patients with primary breast cancer after surgery and before chemotherapy (M0, classified into 3 subgroups of 40 patients with progesterone/estrogen-positive, HER2-positive, and triple-negative cancer), 32 patients with overt metastasis (M1), and 40 healthy women. Using quantitative TaqMan MicroRNA PCR, we measured the relative concentrations of 6 circulating microRNAs (miR-10b, -17, -34a, -93, -155, and -373) known to be relevant for tumor development and progression. The data were correlated with clinicopathologic risk factors, with particular reference to HER2 and hormone receptor status of the primary tumor and the presence of metastases. RESULTS The relative serum concentrations of circulating miR-34a [P = 0.013, area under the curve (AUC) 0.636], miR-93 (P = 0.001, AUC 0.699), and miR-373 (P = 0.0001, AUC 0.879) were significantly different between M0 breast cancer patients and healthy women, whereas miR-17 (P = 0.002, AUC 0.679) and miR-155 (P = 0.0001, AUC 0.781) were differently expressed between M0 and M1 patients. Increased concentrations of miR-373 were associated with negative HER2 status of the primary tumor (P = 0.0001). Deregulated concentrations of miR-17 (P = 0.019) and miR-34a (P = 0.029) were detected in patients with progesterone/estrogen receptor–positive and –negative status, respectively. CONCLUSIONS Our findings indicate that serum concentrations of deregulated microRNAs may be linked to a particular biology of breast carcinomas favoring progression and metastatic spread.

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