Cancer arises from genetic mutations in cells, leading to uncontrolled proliferation and potential invasion of nearby tissues. Cancer cells can spread through the lymph and blood systems. DNA sequence alterations cause cancer. Gene expression differences have been linked to various cancer types. Recent advances in DNA sequencing have shifted the focus of cancer classification to gene expression-based methods. Genetic variants that drive cancer development are distinct from neutral mutations that have no impact on tumors. Our proposed method accurately classifies nine classes of mutation effects based on medical literature abstracts. The machine learning classifier support vector machine (SVM) has been shown to classify genetic mutations and gene expression, offering a promising approach to cancer class identification.