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Tumor protein P53 is believed to be involved in over half of human cancerscases, the prediction of malignancies plays essential roles not only in advancedetection for cancer, but also in discovering effective prevention andtreatment of cancer, till now there isn't approach be able in prediction themutated in tumor protein P53 which is caused high ratio of human cancers likebreast, Blood, skin, liver, lung, bladder etc. This research proposed a newapproach for prediction pre-cancer via detection malignant mutations in tumorprotein P53 using bioinformatics tools like FASTA, BLAST, CLUSTALW and TP53databases worldwide. Implement and apply this new approach of predictionpre-cancer through mutations at tumor protein P53 shows an effective resultwhen used more specific parameters/features to extract the prediction resultthat means when the user increase the number of filters of the results whichobtained from the database gives more specific diagnosis and classify, additionthat the detecting pre-cancer via prediction mutated tumor protein P53 willreduces a person's cancers in the future by avoiding exposure to toxins,radiation or monitoring themselves at older ages by change their food,environment, even the pace of living. Also that new approach of predictionpre-cancer will help if there is any treatment can give for that person totherapy the mutated tumor protein P53. Index Terms (Normal Homology TP53 gene,Tumor Protein P53, Oncogene Labs, GC and AT content, FASTA, BLAST, ClustalW)

New Approach for Prediction Pre-cancer via Detecting Mutated in Tumor Protein P53