Abstract 4604: Landscape of human and viral genomic alterations in cervical carcinomas.
Authors: Ojesina Akinyemi I. , Lichtenstein Lee , Ambrogio Lauren , Cibulskis Kristian , Freeman Samuel , Pedamallu Chandra Sekhar , Bertelsen Bjørn , Imaz Ivan , Vazquez Karla , Salido Guadarrama Alberto , Treviño Victor , Romero-Cordoba Sandra , Duke Fujiko , Kaplan Bethany , Rodriguez Iram , Espinosa Castilla Magali , Woie Katherine , Bjorge Line , Wik Elisabeth , Halle Mari K. , Høivik Erling , Krakstad Camilla , Gómez Macías Gabriela , de Lourdes Garza Rodríguez María , Vazquez Jorge , Rodea Carlos , Cravioto Adrian , Cortes Maria L. , Greulich Heidi , Crum Christopher P. , Akslen Lars , Barrera Saldaña Hugo , Melendez-Zajgla Jorge , Getz Gad , Salvesen Helga B. , Meyerson Matthew L. 
Published: August 2014

Background: Cervical cancer is a major public health problem worldwide. The etiological role of human papilloma virus (HPV) infections in cervical cancer is well established. However, HPV infection is insufficient to account for the development of cervical cancers because only 2 % of women infected with HPV eventually develop invasive carcinomas. We have therefore initiated a large scale sequencing effort to provide comprehensive data on the global landscape of genomic aberrations and HPV variants that contribute to cervical cancer. Methods: We have carried out comprehensive whole exome sequencing analyses on 120 tumor-normal paired samples from Mexico and Norway. We also carried out transcriptome and whole genome sequencing analyses on a subset of the patients (81 and 14 individuals respectively). Results: The aggregate mutation rate across the dataset was 3.8 per megabase (Mb), with the most common mutations being C to T/G in the Tp*C dinucleotide context, at a rate of 15 mutations per Mb. In all, 18,037 mutations were found across the entire dataset, including 11,536 missense, 984 nonsense, 4691 silent, 231 splice site, 32 translation start site mutations, as well 443 deletions and 142 insertions. MutSig analyses to identify genes that were mutated at statistically significant frequencies across our dataset revealed 11 genes to be recurrently mutated with a false discovery rate of q&lt;0.1 after correction for multiple hypothesis testing (and RNASeq-based evidence of robust gene expression). The most significantly mutated genes encode for members of the PIK3CA/PTEN and RAS/RAF/MAPK signaling pathways, as well as the major histocompatibility complex (MHC). We have also uncovered novel patterns of HPV transcript abundance and sites of recurrent HPV integration in cell cycle related genes. In addition, our whole genome sequencing data suggests that HPV-negative p53-mutant tumors harbor high frequencies of genomic rearrangements. Conclusion: The comprehensive catalogue of genomic alterations provided by this project reveals potential novel therapeutic targets in cervical carcinomas. Our data also sets the stage for improving diagnostic and preventive strategies, especially in resource-limited settings with the highest incidence of cervical cancer.

Citation Format: Akinyemi I. Ojesina, Lee Lichtenstein, Lauren Ambrogio, Kristian Cibulskis, Samuel Freeman, Chandra Sekhar Pedamallu, Bjørn Bertelsen, Ivan Imaz, Karla Vazquez, Alberto Salido Guadarrama, Victor Treviño, Sandra Romero-Cordoba, Fujiko Duke, Bethany Kaplan, Iram Rodriguez, Magali Espinosa Castilla, Katherine Woie, Line Bjorge, Elisabeth Wik, Mari K. Halle, Erling Høivik, Camilla Krakstad, Gabriela Gómez Macías, María de Lourdes Garza Rodríguez, Jorge Vazquez, Carlos Rodea, Adrian Cravioto, Maria L. Cortes, Heidi Greulich, Christopher P. Crum, Lars Akslen, Hugo Barrera Saldaña, Jorge Melendez-Zajgla, Gad Getz, Helga B. Salvesen, Matthew L. Meyerson. Landscape of human and viral genomic alterations in cervical carcinomas. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4604. doi:10.1158/1538-7445.AM2013-4604