A mathematical methodology for predicting the primary site of metastatic adenocarcinoma cancer based on rough set theory

Patients with metastatic adenocarcinoma of unknown origin are a common clinical problem. Knowledge of the primary site is important for their management but histologically, such tumors appear similar. Better diagnostic markers are needed to enable the assignment of metastases to likely sites of origin on pathologic samples. The field of bioinformatics has transformed from being a discipline mainly associated with sequence databases and sequence analysis to a computational science that uses different types of data to describe biology. Thus, the ultimate goal of this research is to allow a computational simulation of cancer microarray data by propose a mathematical methodology based on Rough set theory to extracting decision rules which acts as classification scheme for prediction on biopsy material of the primary site in patients with metastatic adenocarcinoma of unknown origin. Finally a set of maximally classification rules are generated to predict origin for many tumors.