Abstract 4189: Discovery of a novel carcinoma-associated EF hand containing protein by mining the dark matter of the human proteome

Abstract

The human genome contains thousands of novel and uncharacterized proteins. These unknown genes are difficult to mine due to lack of adequate information. Hence, they remain largely untapped. Reasoning that new druggable targets for cancer can be discovered from these uncharacterized proteins, we have developed a protocol to mine these proteins for cancer relevance. Using various cancer-related databases, we have developed a database of uncharacterized ORF proteins. Numerous ORFs from this database offer druggable targets. To develop a proof of concept for mining these targets, we have chosen one target, C1ORF87 for detailed characterization. The C1ORF87 was analyzed using bioinformatics approaches for mRNA and protein expression, SNPs, LOH, protein motifs and domains and for gene network interactions. We have identified the C1ORF87 gene as a calcium binding protein with an EF-Hand motif. The EF-hand motifs are present in numerous calcium binding proteins, which exert a complex function in tumor growth and suppression. We show that the C1ORF87 gene is down-regulated in the lung and breast carcinomas and up-regulated in the liver carcinomas. Hematopoietic and neuronal tumors were largely negative. Its expression in select normal tissues suggests that the C1ORF87 may be a putative druggable gene. Our results suggest that the C1ORF 87 gene may play a significant role in specific carcinomas. We further demonstrate that the dark matter of the human proteome can be readily mined to predict putative cancer targets. Detailed characterization of the C1ORF87 gene will be presented. Citation Format: Ana Paula Delgado, Pamela Brandao, Sheilin Hamid, Wim Van de Ven, Ramaswamy Narayanan. Discovery of a novel carcinoma-associated EF hand containing protein by mining the dark matter of the human proteome. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4189. doi:10.1158/1538-7445.AM2014-4189

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LENS: Landscape of Effective Neoantigens Software

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