International Conference on Biomedical and Cancer Research
  • Follow

Accepted Abstracts

Breast cancer target and therapeutic intervention

Awofisayo O Abosede* 
University of Uyo, Nigeria

Citation: Abosede AO (2019) Breast cancer target and therapeutic intervention. SciTech Bioemd-Cancer Science 2019. Tokyo: Japan

Received: May 17, 2019         Accepted: June 12, 2019         Published: June 12, 2019

Abstract

Breast cancer (BC) is the topmost out of five cancers in Europe with statistics breast (28.6%), colorectal (12.8%), lung (7.4%), uterus (6.2%) and ovary (4.1%) and in SSA, they were breast (25.5%), cervix uteri (25.2%), liver (3.8%), colorectal (3.7%) and Kaposi sarcoma (3.7%), (International Agency for Research on Cancer 2012). Breast cancer (BC) is thus the most common cancer worldwide prevalent among women with more than one million cases and is second only to lung cancer. Intercontinental variation has been observed however Cervical and breast cancers peaked in Sub Saharan Africa. Inherited  mutations in BRCA1, BRCA2, PALB2, or TP53 has been identified and the risk associated with these genes are very high. Optimization of standard treatment has improved the outlook for women but the fact that 40% still ultimately dies from the disease highlights the need for novel therapies BRCA1, BRCA2, ABCB1, PALB2, and TP53. The target genes are subjected to computational analysis to obtain their location and hence obtain the 16 base pair sequences which serves as the novel therapeutic targets. The DNA structure of the sequences were generated via the DNA sequence to structure software and novel drugs were designed and docked into the DNA structures via the DNA ligand docking software(SCFBio). The binding energy was determined at the possible binding sites. Potential lead candidates are thereby developed and optimized via established computational pathways to act as future drugs in the treatment of BC.The advent and completion of the human genome project has opened up greater opportunities for DNA targeted structure based drug discovery. The lead candidates generated in silico could be  used as  possible novel agents in breast cancer treatment