Computational Approach to Identify the Key Genes for Invasive Lobular Carcinoma (ILC) Diagnosis and Therapies

Abstract

Invasive Lobular Carcinoma (ILC) is a common form of breast cancer that begins in milk-producing glands lobules and spreads to other parts of the breast. According to the American Cancer Society, about 10–15% of breast cancer cases are ILC. ILC risk rises with age. The number of deaths caused by this cancer each year can be decreased through early diagnosis and if accurate therapy is given. However, diagnosis of ILC is difficult due to its development pattern as it grows as single file strands and not as lumps. Treatments of ILC involve chemotherapy, hormonal therapy and radiation therapy. Drugs that are being used for ILC, are commonly used to treat all types of breast cancer and there are no specific drugs that target receptors of ILC are available. Microarray technology’s emergence helps in finding the differentially expressed genes (DEGs) in malignant cells. From the DEGs, highly interacting genes were identified using the online tool, string. Seven key genes were identified based on the interaction and they are FN1, CDKN2A, COL1A1, COL3A1, COL11A1, LEF1 and IL1B. Thus, the drugs targeting these biomarkers were identified by doing molecular docking using the tool Autodock and molecular dynamic (MD) simulation using the tool iMODs. The response of the identified drugs to the ILC cell line was compared with the control drugs by in silico pharmacogenomic analysis and it was found that the identified drugs have a good response to the ILC cell line.