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Identifying predominant clinical and genomic features for glioblastoma multiforme using sequential backward selection

Cancer is a deadly disease which can start almost anywhere in human body. Among different types of cancer, Brain Cancer is the one which is difficult to cure and are the second-leading cause of death due to cancer. Brain Tumors can be benign or malignant. Glioblastoma Multiforme is one such malignant and most aggressive (grade IV) brain tumor. One of the main challenges in treatment of such a deadly disease is to find an optimal treatment plan for patients. Even though there is a standard line of treatment for cancers, there is a lot of variation in the subsequent treatment chosen. An effective treatment plan can improve the quality of care given to patients. Before developing a personalized treatment plan, we need to find out what are the predictive clinical and genomic features that need to be taken into account. Different individuals have a varying clinical and genomic profile and hence the therapeutic effect on these individuals will be different. Identifying the predictive clinical and genomic factors act as a prefatory step towards development of a personalized treatment plan.