Literature DB >> 31789830

Prediction of Epithelial Ovarian Cancer Outcomes With Integration of Genomic Data.

Andreea M Newtson1, Eric J Devor2,3, Jesus Gonzalez Bosquet1,3.   

Abstract

Some of the patients with epithelial ovarian cancer will not respond to initial therapy. These patients have a poor prognosis. Our aim was to identify patients with a worse prognosis by integrating clinical, pathologic, and genomic data. Using publicly available genomic data and integrating it with clinical data, we significantly improved the prediction of patients with worse surgical outcomes and those who do not respond to initial chemotherapy. We further improved these models with more precise data collection and better understanding of the genetic background of the studied population. Better prediction will lead to better patient classification and opportunities for individualized treatment.

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Year:  2020        PMID: 31789830     DOI: 10.1097/GRF.0000000000000493

Source DB:  PubMed          Journal:  Clin Obstet Gynecol        ISSN: 0009-9201            Impact factor:   2.190


  4 in total

1.  Identification of Novel Fusion Transcripts in High Grade Serous Ovarian Cancer.

Authors:  Andreea Newtson; Henry Reyes; Eric J Devor; Michael J Goodheart; Jesus Gonzalez Bosquet
Journal:  Int J Mol Sci       Date:  2021-04-30       Impact factor: 5.923

2.  Identification of Novel lncRNAs in Ovarian Cancer and Their Impact on Overall Survival.

Authors:  Nicholas Cardillo; Douglas Russo; Andreea Newtson; Henry Reyes; Yasmin Lyons; Eric Devor; David Bender; Michael J Goodheart; Jesus Gonzalez-Bosquet
Journal:  Int J Mol Sci       Date:  2021-01-22       Impact factor: 5.923

3.  Creation and validation of models to predict response to primary treatment in serous ovarian cancer.

Authors:  Jesus Gonzalez Bosquet; Eric J Devor; Andreea M Newtson; Brian J Smith; David P Bender; Michael J Goodheart; Megan E McDonald; Terry A Braun; Kristina W Thiel; Kimberly K Leslie
Journal:  Sci Rep       Date:  2021-03-16       Impact factor: 4.379

4.  Bacterial, Archaea, and Viral Transcripts (BAVT) Expression in Gynecological Cancers and Correlation with Regulatory Regions of the Genome.

Authors:  Jesus Gonzalez-Bosquet; Silvana Pedra-Nobre; Eric J Devor; Kristina W Thiel; Michael J Goodheart; David P Bender; Kimberly K Leslie
Journal:  Cancers (Basel)       Date:  2021-03-05       Impact factor: 6.639

  4 in total

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