scholarly journals MYEOV: A candidate gene for DNA amplification events occurring centromeric toCCND1in breast cancer

2002 ◽  
Vol 102 (6) ◽  
pp. 608-614 ◽  
Author(s):  
Johannes W.G. Janssen ◽  
Marguerite Cuny ◽  
Béatrice Orsetti ◽  
Carmen Rodriguez ◽  
Hélène Vallés ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Candidate Gene ◽  
Dna Amplification

Spherical Self-Organizing Map Detects MYBL 1 As Candidate Gene for Triple-Negative Breast Cancer

2015 ◽  
Vol 3 (2) ◽  
pp. 94-101 ◽  
Author(s):  
Masashi Ikeda ◽  
Kazuki Kumon ◽  
Kazuya Omoto ◽  
Yuh Sugii ◽  
Akifumi Mizutani ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Candidate Gene ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Self Organizing Map ◽  
Self Organizing

scholarly journals Refinement of the 22q12-q13 Breast Cancer–Associated Region: Evidence of TMPRSS6 as a Candidate Gene in an Eastern Finnish Population

2006 ◽  
Vol 12 (5) ◽  
pp. 1454-1462 ◽  
Author(s):  
Jaana M. Hartikainen ◽  
Hanna Tuhkanen ◽  
Vesa Kataja ◽  
Matti Eskelinen ◽  
Matti Uusitupa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Candidate Gene ◽  
Finnish Population

Genomic risk prediction of aromatase inhibitor-related arthralgias (AIA) in breast cancer (BC) patients using a novel analytical algorithm (NAA).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 10102-10102
Author(s):  
Raquel E. Reinbolt ◽  
Stephen T. Sonis ◽  
Cynthia Dawn Timmers ◽  
Juan Luis Fernández-Martínez ◽  
Enrique J. deAndrés-Galiana ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Candidate Gene ◽  
Learning Algorithm ◽  
Treatment Compliance ◽  
Controlled Study ◽  
Snp Data ◽  
Asymptomatic Patients ◽  
Candidate Gene Studies ◽  
Clinically Significant ◽  
Genomic Risk

10102 Background: Many BC patients treated with aromatase inhibitors (AIs) develop AIA; 20% have symptoms severe enough to effect treatment compliance. Results of candidate gene studies to identify AIA risk are limited in scope. In this case-controlled study, we evaluated the potential of a NAA to predict AIA using germline single nucleotide polymorphism (SNP) data obtained prior to treatment initiation. Methods: Systematic chart review of 700 AI-treated patients with stage I-III BC between 2003-2012 identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained from peripheral blood cells and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. The identity of the cluster of SNPs that most closely defined AIA risk was discovered using an NAA that sequentially combined statistical filtering and a machine learning algorithm. NCBI PhenGenI and Ensemble databases were used to define gene attribution of the 200 most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Results: Cases and controls were similar in demographic characteristics. A cluster of 70 SNPs, correlated to 57 genes (accounting for linkage disequilibrium), was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally and ontologically consistent. Conclusions: Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias. An ongoing prospective companion study will be used to validate and to expand upon results.

scholarly journals A Comprehensive RNA Study to Identify circRNA and miRNA Biomarkers for Docetaxel Resistance in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Peide Huang ◽  
Fengyu Li ◽  
Zongchao Mo ◽  
Chunyu Geng ◽  
Fang Wen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cell Lines ◽  
Predictive Biomarkers ◽  
Dna Amplification ◽  
Parental Cell ◽  
Circular Rnas ◽  
Docetaxel Resistance ◽  
Multi Level ◽  
Dna Copy Numbers

To investigate the relationship between non-coding RNAs [especially circular RNAs (circRNAs)] and docetaxel resistance in breast cancer, and to find potential predictive biomarkers for taxane-containing therapies, we have performed transcriptome and microRNA (miRNA) sequencing for two established docetaxel-resistant breast cancer (DRBC) cell lines and their docetaxel-sensitive parental cell lines. Our analyses revealed differences between circRNA signatures in the docetaxel-resistant and -sensitive breast cancer cells, and discovered circRNAs generated by multidrug-resistance genes in taxane-resistant cancer cells. In DRBC cells, circABCB1 was identified and validated as a circRNA that is strongly up-regulated, whereas circEPHA3.1 and circEPHA3.2 are strongly down-regulated. Furthermore, we investigated the potential functions of these circRNAs by bioinformatics analysis, and miRNA analysis was performed to uncover potential interactions between circRNAs and miRNAs. Our data showed that circABCB1, circEPHA3.1 and circEPHA3.2 may sponge up eight significantly differentially expressed miRNAs that are associated with chemotherapy and contribute to docetaxel resistance via the PI3K-Akt and AGE-RAGE signaling pathways. We also integrated differential expression data of mRNA, long non-coding RNA, circRNA, and miRNA to gain a global profile of multi-level RNA changes in DRBC cells, and compared them with changes in DNA copy numbers in the same cell lines. We found that Chromosome 7 q21.12-q21.2 was a common region dominated by multi-level RNA overexpression and DNA amplification, indicating that overexpression of the RNA molecules transcribed from this region may result from DNA amplification during stepwise exposure to docetaxel. These findings may help to further our understanding of the mechanisms underlying docetaxel resistance in breast cancer.

Lymphatic and proinflammatory candidate gene variations and lymphedema.

2013 ◽  
Vol 31 (26_suppl) ◽  
pp. 9-9
Author(s):  
Mei R. Fu ◽  
Deborah M. Axelrod ◽  
Amber Guth ◽  
Judith D. Goldberg ◽  
Xiaochun Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Growth Factors ◽  
Candidate Gene ◽  
Breast Cancer Survivors ◽  
Specific Growth ◽  
Repeated Measure ◽  
Continuous Variables ◽  
Arm Lymphedema ◽  
Breast Cancer Related Lymphedema ◽  
Prospective Longitudinal

9 Background: Traditionally, breast cancer-related lymphedema is considered to be mainly due to the mechanical injury from cancer surgery. Recent research identified that inflammation-infection may be one of the important predictors for lymphedema. This pilot study aimed to explore the associations between lymphatic and pro-inflammatory candidate gene variations and lymphedema. Methods: A prospective, longitudinal, repeated-measure, and comparative design was used to recruit 178 breast cancer survivors. To ensure the accuracy of lymphedema phenotype, lymphedema was classified into lymphedema of arm and breast. Arm lymphedema must have been validated by infra-red perometer and a bioimpedance device. Breast lymphedema was validated by an observational scale since no objective measure is available. Saliva samples were collected for DNA extraction. Candidate Gene Association Research Method was used to examine the eight genes known for inflammation and lymphatic specific growth factors: cytokines (IL1A, IL6, IL8, IL10, IL13) and PTGS2 (COX2), and lymphatic specific growth factors [VEGF-C and D]. Descriptive statistics, Chi-Squared tests for contingency tables and one-way analysis of variance for continuous variables were used to compare the genotypes for each of these genes in patients with and without lymphedema. Odds ratios of developing lymphedema are estimated. Results: Among 178 survivors, 39 women were confirmed to have arm lymphedema and 43 women had breast lymphedema. Five genes were significantly associated with breast cancer-related lymphedema. Specific single nucleic polymorphisms (SNPs) for lymphatic specific growth factors VEGF-C (rs4604006) and cytokine IL13 (rs1800925) were related to arm lymphedema. Specific SNPs of cytokine IL1A (rs1800587) and PTGS2 (COX2) (rs20417) were associated with breast lymphedema. Conclusions: Our findings provided preliminary data on genetic susceptibility as a risk factor for breast cancer-related lymphedema. Findings of our study may serve as a preliminary foundation for a priori recognition of genetic risk that may facilitate lymphedema risk prediction prior to surgery and raises the potential for early intervention for a high-risk group.

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