Cancer is one of the most deadly diseases known till date, which is growing around the world, both in its type and number of people annually affected. Different types and stages of cancer create complexities in its treatment. Common molecular interactions behind different cancer types can reveal a way to prevent multiple cancer types with a same kind of treatment. As cDNA microarray technique had proved well in determining a cell's transcript level, at any stage of a cell. It can be utilized in determining, genome wide gene expression pattern of cells, which may determine molecular mechanisms involved in cancer condition. In this work with the aim of finding core-gene group for cancer, gene expression data of wide range of cancers were analyzed. For data analysis we followed standard microarray data analysis pipeline which mainly include pre-processing, normalization, transformation, clustering, annotation of genes and network analysis. Through Differential gene expression analysis 305 genes were observed as common genes that showing two fold changes in gene expression. Out of these 305, 200 genes were clearly classified as over expressed and 36 under-expressed genes in cancer and 105 genes were remains unclassified. Further to check the biological importance of proteins of these genes PPIN analysis, followed by clustering and protein enrichment analysis was performed. On the basis of the network features and enrichment results it has been conclude that there are 46 genes which play very crucial role in all cancer types and considered them as core-gene for cancer. Interaction among these genes-protein conceded as core-gene-interactome, which can be utilized as biomarker as well as can be utilized as efficient drug target.