Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival
Metrics: PDF 593 views | HTML 1282 views | ?
Hanna Engqvist1, Toshima Z. Parris1, Elisabeth Werner Rönnerman1,2, Elin M.V. Söderberg3, Jana Biermann1, Claudia Mateoiu2, Karin Sundfeldt4, Anikó Kovács2, Per Karlsson1,* and Khalil Helou1,*
1Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Cancer Center, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
2Sahlgrenska University Hospital, Department of Clinical Pathology and Genetics, Gothenburg, Sweden
3Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Cancer Center, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
4Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
*These authors have contributed equally to this work
Hanna Engqvist, email: firstname.lastname@example.org
Keywords: ovarian cancer; diagnostic biomarker; prognostic biomarker; genomics
Received: June 13, 2018 Accepted: September 01, 2018 Published: October 12, 2018
Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I and II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.