Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

• Published in: PLoS genetics Vol. 12; no. 1; p. e1005755
• Main Authors: Halabi, Najeeb M, Martinez, Alejandra, Al-Farsi, Halema, Mery, Eliane, Puydenus, Laurence, Pujol, Pascal, Khalak, Hanif G, McLurcan, Cameron, Ferron, Gwenael, Querleu, Denis, Al-Azwani, Iman, Al-Dous, Eman, Mohamoud, Yasmin A, Malek, Joel A, Rafii, Arash
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.01.2016; Public Library of Science (PLoS)
• Subjects: Alleles; Allelic Imbalance; Allelic Imbalance - genetics; Allelomorphism; Bias; Biochemistry, Molecular Biology; Biology; Cancer; Cell adhesion & migration; Female; Gene expression; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks; Genetic aspects; Genomes; Genomics; Germ Cells; Gynecology and obstetrics; Health aspects; High-Throughput Nucleotide Sequencing; Human health and pathology; Humans; Life Sciences; Metastasis; Mutation; Neoplasm Proteins; Neoplasm Proteins - biosynthesis; Neoplasm Proteins - genetics; Observations; Ovarian cancer; Ovarian Neoplasms; Ovarian Neoplasms - genetics; Ovarian Neoplasms - pathology; Patients; Studies; Transcriptome
• ISSN: 1553-7404; 1553-7390; 1553-7404
• DOI: 10.1371/journal.pgen.1005755

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies.