Bioinformatic approach to predict structure, sequence motif and expression level of breast cancer biomarker molecule: protein and miRNA

Abstract

Breast cancer is an important public health issue. It is both a heterogeneous disease and most common cancer affecting women worldwide. It has become the reason of 69% cancer death in women throughout the whole world and 15% of cancer death in Bangladesh. Three reasons can be attributed to this disease, they are: Poor diagnosis, inefficient treatment and continuous recurrence. Within the borders of our own country in 50% cases the diagnosis miss early detection, 40% of the cases face relapse of the disease and most of the patients have to go through inefficient treatment. Geneticists, molecular biologists, cell biologists, oncologists all are trying to find a solution to this burning question of reducing breast cancer mortality rate, and according to recent findings biomarker studies can provide help in this vital research. Surprisingly, even though there has been many discovered biomarker molecules but due to lack of ample information about specific biomarker molecules most of these have not seen any clinical usage, which is ultimately no help to this critical development. The project was designed to find the basic properties -structure, sequence motif and expression level of potential biomarker molecules of breast cancer. Only protein and miRNA are selected as biomarkers even though there are others, because these two can be found in easily collectable body fluid. 11 protein and 7 miRNA were selected, as they are the one showing high specificity and sensitivity as biomarkers. The protein molecules are - ER, ER Beta, PR, TTR, Ki67, HSP60, Her2, CyclinD1, Cyclin E, P53 and CEA. The miRNAs were- miR10b, miR21, miR145, miR155, miR191, miR 382 and miR425. While doing this project bioinformatics approach was taken to find out properties. For structure SWISS MODEL Workspace (protein), mfold (miRNA), for sequence motif MEME, and for expression level GEO Profiles were used. This study about the biomarkers can help in the betterment of diagnosis, treatment and recurrence. Because knowing about the important properties of biomarker molecules can help in constructing a biomarker panel for diagnosis, treatment and recurrence. Currently mammography is used for diagnosis which give false results at times, can be replaced by biomarker panel that will detect breast cancer even before any symptoms show up, and for treatment, biomarkers can help in forming anti miRNA targets, site directed mutagenesis, specific inhibitors and virtual screening. For the recurrence part biomarker panel can check people for their risk of local or regional relapse. To sum it up the future of breast cancer treatment is in the hand of a good, specific and sensitive panel of biomarkers.