TY - JOUR T1 - Integrated analysis of oral tongue squamous cell carcinoma identifies key variants and pathways linked to risk habits, HPV, clinical parameters and tumor recurrence JF - bioRxiv DO - 10.1101/028845 SP - 028845 AU - Neeraja M Krishnan AU - Saurabh Gupta AU - Vinayak Palve AU - Linu Varghese AU - Swetansu Pattnaik AU - Prachi Jain AU - Costerwell Khyriem AU - Arun K Hariharan AU - Kunal Dhas AU - Jayalakshmi Nair AU - Manisha Pareek AU - Venkatesh K Prasad AU - Gangotri Siddappa AU - Amritha Suresh AU - Vikram D Kekatpure AU - Moni Abraham Kuriakose AU - Binay Panda Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/10/11/028845.abstract N2 - Oral tongue squamous cell carcinomas (OTSCC) are a homogenous group of tumors characterized by aggressive behavior, early spread to lymph nodes and a higher rate of regional failure. Additionally, the incidence of OTSCC among younger population (<50yrs) is on a rise; many of who lack the typical associated risk factors of alcohol and/or tobacco exposure. We present data on SNVs, indels, regions with LOH, and CNVs from fifty-paired oral tongue primary tumors and link the significant somatic variants with clinical parameters, epidemiological factors including HPV infection and tumor recurrence. Apart from the frequent somatic variants harbored in TP53, CASP8, RASA1, NOTCH and CDKN2A genes, significant amplifications and/or deletions were detected in chromosomes 6-9, and 11 in the tumors. Variants in CASP8 and CDKN2A were mutually exclusive. CDKN2A, P1K3CA, RASA1 and DMD variants were exclusively linked to smoking, chewing, HPV infection and tumor stage. We also performed whole-genome gene expression study that identified matrix metalloproteases to be highly expressed in tumors and linked pathways involving arachidonic acid and NF-κ-B to habits and distant metastasis, respectively. Functional knockdown studies in cell lines demonstrated the role of CASP8 in HPV-negative OTSCC cell line. Finally, we identified a 38-gene minimal signature that predicts tumor recurrence using an ensemble machine learning method. Taken together, this study links molecular signatures to various clinical and epidemiological factors in a homogeneous tumor population with a relatively high HPV prevalence. ER -