Breast cancer is fundamentally a disease of regulation of tissue growth. Targeting the pathways that promote or sustain growth and invasion of carcinoma cells is critical to effective treatment of breast cancer. Data curation adopting a bioinformatics/ biological data basing approach is presently employed to identify the candidate protein molecules mediating breast cancer signalling with a promise for therapeutic targeting. Signalling proteins are highly specific and precise and act in a modular manner, which allows us to modulate such interactions specifically by the use of drugs or other molecule for a better drug target. With this aim in mind, we thus, are creating a catalogue of biomarkers of signalling proteins mediating breast cancer. Presently, we have manually curated signalling data on proteins mediating breast cancer on the basis of PubMed reports. Of the 150 entries made so far based on about 250 Pubmed reports, the receptor tyrosine kinase (RTK) cascade has been found to be implicated in a high proportion of Breast cancers and the major downstream effector in the process emerged out to be Activator protein-1 (AP-1), CDc42 and FOXO3 in these responses. Other key markers found out were CDc42 (a GTPase) and FOXO3 (a transcription factor). Receptor mainly involved is estrogen receptors which in particular have been well documented to play a critical role in the etiology and progression of breast cancer. This collection highlights many recent studies that catalogue these alterations and shed light on the mechanisms by which cancer genes function.

Breast cancer, Oncology, Bioinformatics, AP-1, FOXO3, CDc42, PubMed

One of the most important issues in oncology is breast cancer, which is a challenging tissue to investigate. The dataset curated in the current study includes important signalling molecules linked to breast cancer. Receptor Tyrosine Kinase (RTK) cascade is currently thought to be the most frequent mediator of breast cancer. Activator protein-1 (AP-1), cell division control protein 42 (CDc42), a GTPase, and Forkhead box O3 (FOXO3a), a transcription factor, were found to be the process' main downstream effectors. Since it is clear that these prospective protein molecules have been shown to have a major role in the majority of cancer cases, a novel lead compound can be found through structure-based drug design employing a variety of bioinformatics tools. The identification of potential drug lead compounds for inhibiting the active site of protein molecules and preventing their involvement in the cancer pathway may be aided by In silico drug target discovery, drug design, docking or screening, drug metabolism prediction, interaction prediction, and general pharmaceutical education. The quick search for tiny compounds that might bind to biologically interesting targets is essential for the drug discovery process.

Piyusha Sharma and Vachaspati Mishra (2022). Data Curation of Signalling Protein Molecules in Breast Cancer. International Journal on Emerging Technologies, 13(2): 01–05.