scholarly journals PheWAS-Based Systems Genetics Methods for Anti-Breast Cancer Drug Discovery

Genes ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 154
Author(s):  
Min Gao ◽  
Yuan Quan ◽  
Xiong-Hui Zhou ◽  
Hong-Yu Zhang
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Association Studies ◽  
Biological Significance ◽  
Cancer Drug ◽  
Systems Genetics ◽  
Cancer Genes ◽  
Genome Wide ◽  
A Genome ◽  
Breast Cancer Genes

Breast cancer is a high-risk disease worldwide. For such complex diseases that are induced by multiple pathogenic genes, determining how to establish an effective drug discovery strategy is a challenge. In recent years, a large amount of genetic data has accumulated, particularly in the genome-wide identification of disorder genes. However, understanding how to use these data efficiently for pathogenesis elucidation and drug discovery is still a problem because the gene–disease links that are identified by high-throughput techniques such as phenome-wide association studies (PheWASs) are usually too weak to have biological significance. Systems genetics is a thriving area of study that aims to understand genetic interactions on a genome-wide scale. In this study, we aimed to establish two effective strategies for identifying breast cancer genes based on the systems genetics algorithm. As a result, we found that the GeneRank-based strategy, which combines the prognostic phenotype-based gene-dependent network with the phenotypic-related PheWAS data, can promote the identification of breast cancer genes and the discovery of anti-breast cancer drugs.

scholarly journals Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome–wide interaction study

2013 ◽  
Vol 20 (6) ◽  
pp. 875-887 ◽  
Author(s):  
Anja Rudolph ◽  
Rebecca Hein ◽  
Sara Lindström ◽  
Lars Beckmann ◽  
Sabine Behrens ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fixed Effects ◽  
Association Studies ◽  
Meta Analysis ◽  
Case Control ◽  
Genome Wide Association Studies ◽  
Genetic Modifiers ◽  
Genome Wide ◽  
A Genome ◽  
Increased Risk

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case–control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0×10−3 were selected for replication using pooled case–control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9×10−6), two SNPs in SLC25A21 (combined Pint≤4.8×10−5), and three SNPs in PLCG2 (combined Pint≤4.5×10−5). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7×10−5), one SNP in CD80 (combined Pint≤8.2×10−6), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10−6), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6×10−5). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

scholarly journals Genomics-driven drug discovery based on disease-susceptibility genes

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Drug Repurposing ◽  
Susceptibility Genes ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

scholarly journals A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

2007 ◽  
Vol 39 (7) ◽  
pp. 870-874 ◽  
Author(s):  
David J Hunter ◽  
Peter Kraft ◽  
Kevin B Jacobs ◽  
David G Cox ◽  
Meredith Yeager ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Postmenopausal Breast Cancer ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

BIOM-32. ENDOPLASMIC RETICULUM PROTEIN SSR3 DETERMINES AND PREDICTS RESPONSE TO PACLITAXEL IN BREAST CANCER AND GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi17-vi18
Author(s):  
Crismita Dmello ◽  
Aarón Sonabend ◽  
Víctor Arrieta ◽  
Daniel Zhang ◽  
Deepak Kanojia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Endoplasmic Reticulum ◽  
Glioma Cells ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Precision Oncology ◽  
Patient Response ◽  
Knock Out ◽  
Genome Wide ◽  
A Genome

Abstract Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Given the potency of this drug for glioblastomas (GBM) several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for this disease. In spite of the efficacy of PTX, individual tumors exhibit variable susceptibility to this drug, with response rate in the range of 30%-60%. To identify predictive biomarkers for response to PTX, we performed a genome-wide CRISPR knock-out screen using human glioma cells. The most enriched genes in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort. This led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with response to PTX in breast cancer cells, glioma cells, in multiple intracranial glioma xenografts and in GBM patient derived explant cultures. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. In gliomas, SSR3-mediated susceptibility to PTX relates to modulation of phosphorylation of ER stress sensor IRE1α. Thus, by using genome-wide screen combined with patient response data, we discovered a biomarker that demonstrates causal and correlative relationship with response to PTX in breast cancer and GBM. Prospective validation of this biomarker is warranted for its broad implementation for precision oncology.

Breast Cancer Genes

2013 ◽  
pp. 267-267
Author(s):  
Timothy H. Wideman ◽  
Michael J. L. Sullivan ◽  
Shuji Inada ◽  
David McIntyre ◽  
Masayoshi Kumagai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Genes ◽  
Breast Cancer Genes
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