Affiliation: Department of Biological Sciences, Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL 33431.
The post genome era has ushered us into therapeutic target discovery empowering us to mine the genome using rational approaches. Numerous cancer targets have emerged from the genome project for diagnostics, therapeutics and response to therapy prediction. Among thousands of genes predicted in the human genome, nearly half of them remain uncharacterized. Considerable attention in the last decade has focused on the well-characterized known genes. However, the future of cancer target discovery resides in the uncharacterized or novel genes called the dark matter of the human genome. Realizing the importance of this vast untapped potential, recently the US National Cancer Institute announced a new initiative called "Illuminating the Dark Matter of the Genome for Druggability". This area of cancer research albeit exciting, remains a challenge due to the lack of adequate information about the uncharacterized genes. Amongst the plethora of bioinformatics tools and databases, a streamlined approach remains elusive. In this review, we present a simplified approach to mine directly the cancer proteome for rapid target discovery. Using such an approach, we have created a database of uncharacterized cancer genes and have shown the biomarker and drug target potential for an uncharacterized protein, C1ORF87, as a putative solid tumor target. In view of this protein's association with carcinomas, the C1ORF87 is termed as Carcinoma-Related EF-Hand (CREF) gene. The approaches discussed in this review should aid in lighting the dark matter of the human cancer proteome.