PET Imaging of Estrogen Metabolism in Breast Cancer

2002 ◽  
Author(s):  
Yu-Shin Ding
Keyword(s):  
Breast Cancer ◽  
Pet Imaging ◽  
Estrogen Metabolism

scholarly journals Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2370
Author(s):  
JooYong Park ◽  
Ji-Yeob Choi ◽  
Jaesung Choi ◽  
Seokang Chung ◽  
Nan Song ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Environmental Factors ◽  
Minor Allele ◽  
Estrogen Metabolism ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Estrogen Exposure ◽  
Gene Environment ◽  
Independent Population

In this study we aim to examine gene–environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10−3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10−4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

scholarly journals Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Feng Zhao ◽  
Zhixiang Hao ◽  
Yanan Zhong ◽  
Yinxue Xu ◽  
Meng Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Healthy Subjects ◽  
Metabolic Enzyme ◽  
Estrogen Metabolism ◽  
Polygenic Risk Score ◽  
Risk Genes ◽  
Polygenic Risk ◽  
Enzyme Gene

Abstract Background Multiple common variants identified by genome-wide association studies have shown limited evidence of the risk of breast cancer in Chinese individuals. In this study, we aimed to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes in breast cancer (BC) and establish a risk prediction model composed of estrogen-metabolizing enzyme genes and GWAS-identified breast cancer-related genes based on a polygenic risk score. Methods Unrelated BC patients and healthy subjects were recruited for analysis of estrogen levels and single nucleotide polymorphisms (SNPs) in genes encoding estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes, which was calculated using a Bayesian approach. An independent sample t-test was used to evaluate the differences between PRS scores of BC and healthy subjects. The discriminatory accuracy of the models was compared using the area under the receiver operating characteristic (ROC) curve. Results The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulating in the serum of BC patients. We then established a PRS model to evaluate the role of SNPs in multiple genes. PRS model 1 (M1) was established from SNPs in 6 GWAS-identified high risk genes. On the basis of M1, we added SNPs from 7 estrogen metabolism enzyme genes to establish PRS model 2 (M2). The independent sample t-test results showed that there was no difference between BC and healthy subjects in M1 (P = 0.17); however, there was a significant difference between BC and healthy subjects in M2 (P = 4.9*10− 5). The ROC curve results showed that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than that of M1 (AUC = 54.56%). Conclusion Estrogen and related metabolic enzyme gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme gene SNPs has a good predictive ability for breast cancer risk, and the accuracy is greatly improved compared with that of the PRS model that only includes GWAS-identified gene SNPs.

scholarly journals HER3-Mediated Resistance to Hsp90 Inhibition Detected in Breast Cancer Xenografts by Affibody-Based PET Imaging

2018 ◽  
Vol 24 (8) ◽  
pp. 1853-1865 ◽  
Author(s):  
Carlos D. Martins ◽  
Chiara Da Pieve ◽  
Thomas A. Burley ◽  
Rhodri Smith ◽  
Daniela M. Ciobota ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Pet Imaging ◽  
Hsp90 Inhibition ◽  
Breast Cancer Xenografts

Abstract PD6-09: Herpet study- PET imaging of HER2 expression in breast cancer using the novel Affibody tracer [18F]GE-226, a first in patient study

2021 ◽  
Author(s):  
Laura M. Kenny ◽  
Gosala S. Gopalakrishnan ◽  
Tara D. Barwick ◽  
Vijay Vaja ◽  
S. Hope McDevitt ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Pet Imaging ◽  
The Novel ◽  
Her2 Expression ◽  
Patient Study

maxPET, a dedicated mammary and axillary region PET imaging system for breast cancer

2001 ◽  
Vol 48 (3) ◽  
pp. 811-815 ◽  
Author(s):  
N.K. Doshi ◽  
R.W. Silverman ◽  
Y. Shao ◽  
S.R. Cherry
Keyword(s):  
Breast Cancer ◽  
Pet Imaging ◽  
Imaging System ◽  
Axillary Region
Sign in / Sign up

Export Citation Format

Share Document