Integrated genomics approach to identify biologically relevant alterations in fewer samples. (December 2015)

• Record Type: Journal Article
• Authors: Chandrani, Pratik; Upadhyay, Pawan; Iyer, Prajish; Tanna, Mayur; Shetty, Madhur; Raghuram, Gorantala; Oak, Ninad; Singh, Ankita; Chaubal, Rohan; Ramteke, Manoj; Gupta, Sudeep; Dutt, Amit
• Is Part Of: BMC genomics. Volume 16:Number 1(2015)
• Page Start: 1
• Page End: 13
• Publication Date: 2015-12
• Subjects: Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-015-2138-4
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Background Several statistical tools have been developed to identify genes mutated at rates significantly higher than background, indicative of positive selection, involving large sample cohort studies. However, studies involving smaller sample sizes are inherently restrictive due to their limited statistical power to identify low frequency genetic variations. Results We performed an integrated characterization of copy number, mutation and expression analyses of four head and neck cancer cell lines - NT8e, OT9, AW13516 and AW8507-- by applying a filtering strategy to prioritize for genes affected by two or more alterations within or across the cell lines. Besides identifyingTP53, PTEN, HRAS andMET as major altered HNSCC hallmark genes, this analysis uncovered 34 novel candidate genes altered. Of these, we find a heterozygous truncating mutation in Nuclear receptor binding protein, NRBP1 pseudokinase gene, identical to as reported in other cancers, is oncogenic when ectopically expressed in NIH-3 T3 cells. Knockdown ofNRBP1 in an oral carcinoma cell line bearingNRBP1 mutation inhibit transformation and survival of the cells. Conclusions In overall, we present the first comprehensive genomic characterization of four head and neck cancer cell lines established from Indian patients. We also demonstrate the ability of integrated analysis to uncover biologically important genetic variation in studies involving fewer or rare clinical specimens.