Integrated genomics approach to identify biologically relevant alterations in fewer samples

Abstract

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. 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 identifying TP53, PTEN, HRAS and MET 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 of NRBP1 in an oral carcinoma cell line bearing NRBP1 mutation inhibit transformation and survival of the cells. 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.

DOI: 10.1186/s12864-015-2138-4

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@inproceedings{Chandrani2015IntegratedGA, title={Integrated genomics approach to identify biologically relevant alterations in fewer samples}, author={Pratik Chandrani and Pawan Upadhyay and Prajish Iyer and Mayur Tanna and Madhur Shetty and Gorantala Venkata Raghuram and Ninad Oak and Ankita Singh and Rohan Chaubal and Manoj P. Ramteke and Sudeep Gupta and Amit Dutt}, booktitle={BMC Genomics}, year={2015} }