Literature DB >> 25810134

Efficient molecular subtype classification of high-grade serous ovarian cancer.

Huei San Leong1, Laura Galletta1, Dariush Etemadmoghadam1,2,3, Joshy George4, Martin Köbel5, Susan J Ramus6, David Bowtell1,2,3,7,8.   

Abstract

High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials.
Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Entities:  

Keywords:  Fluidigm; Illumina targeted RNA expression; Nanostring; TaqMan low-density arrays; classification; molecular subtypes; serous ovarian cancer

Mesh:

Year:  2015        PMID: 25810134     DOI: 10.1002/path.4536

Source DB:  PubMed          Journal:  J Pathol        ISSN: 0022-3417            Impact factor:   7.996


  36 in total

1.  Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes.

Authors:  Stefan Kommoss; Boris Winterhoff; Ann L Oberg; Gottfried E Konecny; Chen Wang; Shaun M Riska; Jian-Bing Fan; Matthew J Maurer; Craig April; Viji Shridhar; Friedrich Kommoss; Andreas du Bois; Felix Hilpert; Sven Mahner; Klaus Baumann; Willibald Schroeder; Alexander Burges; Ulrich Canzler; Jeremy Chien; Andrew C Embleton; Mahesh Parmar; Richard Kaplan; Timothy Perren; Lynn C Hartmann; Ellen L Goode; Sean C Dowdy; Jacobus Pfisterer
Journal:  Clin Cancer Res       Date:  2017-02-03       Impact factor: 12.531

Review 2.  Rationale for Developing a Specimen Bank to Study the Pathogenesis of High-Grade Serous Carcinoma: A Review of the Evidence.

Authors:  Mark E Sherman; Ronny I Drapkin; Neil S Horowitz; Christopher P Crum; Sue Friedman; Janice S Kwon; Douglas A Levine; Ie-Ming Shih; Donna Shoupe; Elizabeth M Swisher; Joan Walker; Britton Trabert; Mark H Greene; Goli Samimi; Sarah M Temkin; Lori M Minasian
Journal:  Cancer Prev Res (Phila)       Date:  2016-05-24

3.  Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes.

Authors:  Chen Wang; Sebastian M Armasu; Kimberly R Kalli; Matthew J Maurer; Ethan P Heinzen; Gary L Keeney; William A Cliby; Ann L Oberg; Scott H Kaufmann; Ellen L Goode
Journal:  Clin Cancer Res       Date:  2017-03-09       Impact factor: 12.531

4.  Molecular Classification of Epithelial Ovarian Cancer Based on Methylation Profiling: Evidence for Survival Heterogeneity.

Authors:  Clara Bodelon; J Keith Killian; Joshua N Sampson; William F Anderson; Rayna Matsuno; Louise A Brinton; Jolanta Lissowska; Michael S Anglesio; David D L Bowtell; Jennifer A Doherty; Susan J Ramus; Aline Talhouk; Mark E Sherman; Nicolas Wentzensen
Journal:  Clin Cancer Res       Date:  2019-05-29       Impact factor: 12.531

5.  Metabolic Markers and Statistical Prediction of Serous Ovarian Cancer Aggressiveness by Ambient Ionization Mass Spectrometry Imaging.

Authors:  Marta Sans; Kshipra Gharpure; Robert Tibshirani; Jialing Zhang; Li Liang; Jinsong Liu; Jonathan H Young; Robert L Dood; Anil K Sood; Livia S Eberlin
Journal:  Cancer Res       Date:  2017-04-17       Impact factor: 12.701

Review 6.  The rise of genomic profiling in ovarian cancer.

Authors:  Rebecca A Previs; Anil K Sood; Gordon B Mills; Shannon N Westin
Journal:  Expert Rev Mol Diagn       Date:  2016-12       Impact factor: 5.225

7.  Multisite Tumor Sampling Reveals Extensive Heterogeneity of Tumor and Host Immune Response in Ovarian Cancer.

Authors:  Sotirios Lakis; Vassiliki Kotoula; Georgia-Angeliki Koliou; Ioannis Efstratiou; Sofia Chrisafi; Alexios Papanikolaou; Pantelis Zebekakis; George Fountzilas
Journal:  Cancer Genomics Proteomics       Date:  2020 Sep-Oct       Impact factor: 4.069

Review 8.  Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells.

Authors:  Ugo Testa; Eleonora Petrucci; Luca Pasquini; Germana Castelli; Elvira Pelosi
Journal:  Medicines (Basel)       Date:  2018-02-01

9.  Inter-pathologist and pathology report agreement for ovarian tumor characteristics in the Nurses' Health Studies.

Authors:  Mollie E Barnard; Alexander Pyden; Megan S Rice; Miguel Linares; Shelley S Tworoger; Brooke E Howitt; Emily E Meserve; Jonathan L Hecht
Journal:  Gynecol Oncol       Date:  2018-07-09       Impact factor: 5.482

10.  Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs.

Authors:  Zhong Chen; Wensheng Zhang; Hongwen Deng; Kun Zhang
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2022-02-03       Impact factor: 3.710

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.