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Efficient molecular subtype classification of high‐grade serous ovarian cancer
Author(s) -
Leong Huei San,
Galletta Laura,
Etemadmoghadam Dariush,
George Joshy,
Köbel Martin,
Ramus Susan J,
Bowtell David
Publication year - 2015
Publication title -
the journal of pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.964
H-Index - 184
eISSN - 1096-9896
pISSN - 0022-3417
DOI - 10.1002/path.4536
Subject(s) - serous fluid , ovarian cancer , biology , serous ovarian cancer , microarray , computational biology , gene expression profiling , gene , pathology , cancer research , bioinformatics , cancer , gene expression , medicine , genetics , biochemistry
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.