Drug Discovery for Breast Cancer by Mirror-Image Display

2003 ◽  
Author(s):  
Stephen C. Blacklow
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Mirror Image ◽  
Image Display

Small-Molecule Drug Discovery in Triple Negative Breast Cancer: Current Situation and Future Directions

2021 ◽  
Vol 64 (5) ◽  
pp. 2382-2418 ◽  
Author(s):  
Minru Liao ◽  
Jin Zhang ◽  
Guan Wang ◽  
Leiming Wang ◽  
Jie Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Small Molecule ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Current Situation ◽  
Future Directions ◽  
Small Molecule Drug

Abstract 1344: HMGA2-targeted drug discovery for breast cancer brain metastasis

2011 ◽  
Author(s):  
Riesa Burnett ◽  
Hitesh Appaiah ◽  
Poornima Bhat-Nakshatri ◽  
Jim Wikel ◽  
Peter Crooks ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Brain Metastasis ◽  
Breast Cancer Brain Metastasis ◽  
Targeted Drug ◽  
Targeted Drug Discovery

scholarly journals Searching for essential genes and drug discovery in breast cancer and periodontitis via text mining and bioinformatics analysis

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Lan Luo ◽  
Weijie Zheng ◽  
Chuang Chen ◽  
Shengrong Sun
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Text Mining ◽  
Bioinformatics Analysis ◽  
Essential Genes

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.

NIR Spectroscopic Detection of Breast Cancer

2005 ◽  
Vol 4 (5) ◽  
pp. 497-512 ◽  
Author(s):  
S. Nioka ◽  
B. Chance
Keyword(s):  
Breast Cancer ◽  
Blood Volume ◽  
Near Infrared ◽  
Tumor Tissue ◽  
Signal To Noise Ratio ◽  
Mirror Image ◽  
Physiological Data ◽  
Cancer Therapies ◽  
Image Position

Near infrared spectroscopy (NIRS) utilizes intrinsic optical absorption signals of blood, water, and lipid concentration available in the NIR window (600–1000 nm) as well as a developing array of extrinsic organic compounds to detect and localize cancer. This paper reviews optical cancer detection made possible through high tumor-tissue signal-to-noise ratio (SNR) and providing biochemical and physiological data in addition to those obtained via other methods. NIRS detects cancers in vivo through a combination of blood volume and oxygenation from measurements of oxy- and deoxy-hemoglobin giving signals of tumor angiogenesis and hypermetabolism. The Chance lab tends towards CW breast cancer systems using manually scannable detectors with calibrated low pressure tissue contact. These systems calculate angiogenesis and hypermetabolism by using a pair of wavelengths and referencing the mirror image position of the contralateral breast to achieve high ROC/AUC. Time domain and frequency domain spectroscopy were also used to study similar intrinsic breast tumor characteristics such as high blood volume. Other NIRS metrics are water-fat ratio and the optical scattering coefficient. An extrinsic FDA approved dye, ICG, has been used to measure blood pooling with extravasation, similar to Gadolinium in MRI. A key future development in NIRS will be new Molecular Beacons targeting cancers and fluorescing in the NIR window to enhance in vivo tumor-tissue ratios and to afford biochemical specificity with the potential for effective photodynamic anti-cancer therapies.

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