Genomics and Proteomics for Cancer Research

The uncontrolled division of cells creates an abnormal environment in the body, leading to a condition known as cancer. It is the biggest challenge across the globe to combat this deadly condition. Every year, new cases of cancer are brought up. We lack the resources to find the exact cause of the condition and have failed to develop medicines for it. The abnormal cell proliferation further deteriorates health and makes it susceptible to other diseases. 

The estimation of cancer statistics indicates twelve million new cases of cancer every year. The survival rates of cancer patients do not exceed 50 percent. Thus, we needed some strategies to tackle this situation. The cancer therapeutic industry focused on cytotoxic agents and identified a few processes based on cell lines. However, these processes still need a lot of improvement to get a good response from the patients. Most of the medications for cancer proved to be cytotoxic, with devastating side effects. Thus, they showed less efficacy after the completion of the few cycles of therapy. Cell biologists working on cancer cells have tried targeting the cell signaling pathways. These pathways included proliferation, growth, apoptosis, metastasis, or migration of the cancer cells. Using the information from the cellular signaling pathways, rapid technologies for detecting the condition at a very early stage got a boost. These technologies included rapid DNA analysis and personalized analysis. These technologies accurately detect the susceptibility of cancer in newborn babies. Hence, right after the baby takes birth, it is possible to detect the cells susceptible to cancerous conditions and take measures accordingly. These technologies identify the genetic components responsible for causing cancer right at the molecular level. Thus, it gives a wide scope for drug design based on molecular targets. 
Cancer proteomics works well at the protein level. It also utilizes DNA microarrays. It analyzes the transcriptome data. This type of analysis helps in classifying the different types of cancers in addition to detecting unknown cancer genes. Examples include unidentified protooncogenes, oncogenes, tumor-inducing genes, and tumor suppressor genes. The analysis of the proteome data also helps in cancer studies and research.