Integrated genomics approach to identify biologically relevant alterations in fewer samples

Pratik Chandrani, Pawan Upadhyay, Prajish Iyer, Mayur Tanna, Madhur Shetty, Gorantala Venkata Raghuram, Ninad Oak, Ankita Singh, Rohan Chaubal, Manoj Ramteke, Sudeep Gupta, Amit Dutt

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.