期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2015
卷号：112
期号：23
页码：E3050-E3057
DOI：10.1073/pnas.1508057112
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：SignificanceIdentifying molecules that are specific to tumors for use in early detection, diagnosis, prognosis, and therapy is both a primary goal and a key discovery challenge across diverse areas of oncology. To discover ovarian tumor-specific molecules, we developed custom bioinformatics algorithms to analyze transcriptome sequence data of 296 ovarian cancer and 1,839 normal tissues and validated putative tumor-specific mRNA isoforms by RT-quantitative PCR. The results revealed multiple candidate diagnostic and therapeutic targets with unique sequences that were expressed in most of the cancers examined but not in normal tissues. The process we developed can be readily applied to identify diagnostic and therapeutic targets for any of the 30 or more tumor types for which large amounts of transcriptome data now exist. Tumor-specific molecules are needed across diverse areas of oncology for use in early detection, diagnosis, prognosis and therapy. Large and growing public databases of transcriptome sequencing data (RNA-seq) derived from tumors and normal tissues hold the potential of yielding tumor-specific molecules, but because the data are new they have not been fully explored for this purpose. We have developed custom bioinformatic algorithms and used them with 296 high-grade serous ovarian (HGS-OvCa) tumor and 1,839 normal RNA-seq datasets to identify mRNA isoforms with tumor-specific expression. We rank prioritized isoforms by likelihood of being expressed in HGS-OvCa tumors and not in normal tissues and analyzed 671 top-ranked isoforms by high-throughput RT-qPCR. Six of these isoforms were expressed in a majority of the 12 tumors examined but not in 18 normal tissues. An additional 11 were expressed in most tumors and only one normal tissue, which in most cases was fallopian or colon. Of the 671 isoforms, the topmost 5% (n = 33) ranked based on having tumor-specific or highly restricted normal tissue expression by RT-qPCR analysis are enriched for oncogenic, stem cell/cancer stem cell, and early development loci--including ETV4, FOXM1, LSR, CD9, RAB11FIP4, and FGFRL1. Many of the 33 isoforms are predicted to encode proteins with unique amino acid sequences, which would allow them to be specifically targeted for one or more therapeutic strategies--including monoclonal antibodies and T-cell-based vaccines. The systematic process described herein is readily and rapidly applicable to the more than 30 additional tumor types for which sufficient amounts of RNA-seq already exist.
关键词：ovarian cancer ; RNA-seq ; bioinformatics ; diagnostics ; therapeutics
