Abstract:
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Head-Neck Squamous Cell Carcinoma is one of the most common types of cancer among older people. The Collective cancer known as Head-Neck usually begins in squamous cell and account for approximately 4% of all cancers in the United States. In this work, our main goal is to detect the significant miRNAs and how their expression level gets affected by lymphovascular invasion, considered as a strong and independent predictor of several other cancer types. To better understand the connection, we first cluster the genes and then develop a summary measure for each cluster. We use the cluster information to develop a predictive model and obtain connection among survival status, lymphovascular invasion, and miRNA expressions. We implement our algorithm on the Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) data.
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